{"input": "-19\nrelated demands (ICR, page 37). Therefore, the indicator is **unsatisfactory** .\n\n\n**RI 10.** This indicator measured the number of reports on consolidated post-disaster expenditure that were\nproduced annually and submitted to the Budget Department within National Treasury. This indicator could\nbe verified. On the other hand, the change in the covered contents of the reports reduced the relevance of\nthe RI. At appraisal, the target expected to have one consolidated expenditure report per year during the\nimplementation period (ICR, para 52). The RI would measure the financial management capacity of the\nGoK to consolidate data on post-disaster expenditure from various stakeholders and provide evidence on\nchanges in post-disaster expenditure over time during implementation. However, the GoK decided to\nprepare expenditure reports of 2019/2020 on the following 5 topics, and changed the RI accordingly: (i)\nlocust infestation, (ii) floods, (iii) droughts, (iv) other minor disasters, and (v) COVID-19 epidemic (ICR,\npage 11). The number of reports on post-disaster expenditure in 2019/2020 was not a direct measure of\nthe Government’s financial capacities to manage the impact of climate and disaster risks. Therefore, the\nindicator is **unsatisfactory** .\n\n\n**Table. Results Indicators (RIs), the Prior Actions (PAs), baseline, target values, actual change in**\n\n**<u>RI relative to target and RI achievement rating.</u>**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|RI|Associated<br>PAs|RI<br>relevance|Baseline<br>(including<br>units and<br>dates).|Target<br>(including<br>units and<br>dates).|Actual value<br>as of target<br>date|Actual<", "output": {"entities": {"named_data": [], "descriptive_data": ["data on post-disaster expenditure"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002082", "page": 7, "chunk": 1, "title": "Kenya - Kenya CAT DDO", "pdf_url": "https://documents.worldbank.org/curated/en/099042823161529352/pdf/P1615620f445c80290b78708fde57d0b18c.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on post-disaster expenditure", "label": "DESCRIPTIVE_DATA", "score": 0.704761803150177, "start": 632, "end": 665, "probe_score": 0.1753, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " growth quality, poverty has remained elevated and the job content of**\n**growth has been weak.** Based on available but incomplete data, significant progress was made\nin reducing poverty prior to the civil war. Since that date, however, progress has stopped, and\neven reversed as poverty incidence has hovered around 28 percent for the few data points\navailable. Extreme poverty has remained stable at around 8 percent since the end of the civil war.\nThe country’s employment challenge is also daunting as job growth has not kept pace with the\ngrowth of the labor force. Even during periods of relatively rapid economic growth, Lebanon\nexperienced weak private sector job creation with an employment growth elasticity of only 0.2,\nwhich is considerably lower than those observed in other countries in the region. Meanwhile, the\nlabor force has been growing, in part driven by an increase in the working age population. Under\ncurrent conditions, Lebanon is not making significant progress toward increasing shared\nprosperity or eliminating extreme poverty.\n\n\n**B.** **Situations of Urgent Need of Assistance**\n\n\n4. This project is being prepared and implemented in accordance with the provisions of\nparagraph twelve of World Bank OP10.00, “Projects in situations of urgent need of Assistance or\nCapacity Constraints.” This permits the provision of investment project financing with specific\nexceptions in cases where there is an urgent need of assistance because of a natural or man-made\ndisaster or conflict (among other factors). The situation in Lebanon reflects both the impact of a\nconflict in neighboring Syria and of a man-made disaster, in the form of the continuing influx of\n\n\n1 This and the following paragraphs in the Country Context section draw directly from the concept note of the\nLebanon Systematic Country Diagnostic (2015).\n\n\n1", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["available but incomplete data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000030", "page": 9, "chunk": 1, "title": "Lebanon - Emergency Education System Stabilization Project", "pdf_url": "http://documents.worldbank.org/curated/en/578481467991017996/pdf/PAD1190-PAD-P152848-PUBLIC-Box391435B-LB-EESSP-Final-PAD-for-printing.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "available but incomplete data", "label": "VAGUE_DATA", "score": 0.7144440412521362, "start": 107, "end": 136, "probe_score": 0.0384, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "It is however our strong recommendation to UETCL to redefine the **RoW** as the land needed permanently\n\nfor the maintenance track s while the **Way leaves** should be the land for the physical electric facility\n\nincluding the towers, cross arms and the conductors <sup>1</sup> [^1: This is a result of our extensive study of the different tower designs that are wider than the 5 meter defined by\nUETCL and the fact that the access road needs to divert from the towers every time a tower is encountered.] . This recommendation is derived from the\n\nstudies conducted on ongoing projects undertaken by UETCL where the tower footprint is wider than the **5**\n\n\nmeter strip. The ideal definition of the way leaves and the true meaning of easements should be\n\n\nemployed <sup>2</sup> [^2: See definition of easements adapted from the legal dictionary.] .\n\n\nIn general however, following the UETCL definitions, the project currently requires **754.9 acres** for the way\nleaves while **110.4 acres** are permanently needed for the RoW. Additionally from the data collected and\nanalysed, UETCL will require about 120 acres for purposes of resettlement while 12 acres per camp in the\n3 districts will temporarily needed as storage or lay down area during construction.\n\n\n**Basis of Valuation**\n\n\nThe appraisal exercise was based on the Open Market Value which is defined as the best price at which the sale of\n\n\nan interest in a property might reasonably be expected to have been completed unconditionally for cash\n\n\nconsideration on the valuation, which was done in 2008 basing on the cut-off date of **18** <sup>**th**</sup> **February 2008 and 30** <sup>**th**</sup>\n\n\n**October 2010 for the diversion route** . These values will be reviewed by the Chief Government Valuer before\n\n\npayment. The valued property", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data collected and\nanalysed"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015699", "page": 9, "chunk": 0, "title": "Review and update of environmental and social impact assessment for 137km Kawanda - Masaka 220kV transmission line", "pdf_url": "https://documents.worldbank.org/curated/en/620641468108860596/pdf/631520BR0P11970e0only0900BOX361502B.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data collected and\nanalysed", "label": "VAGUE_DATA", "score": 0.6571838855743408, "start": 1050, "end": 1077, "probe_score": 0.1098, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " of data, monitoring, planning and course correction in real time;\n(iii) transparency for good governance by promoting the publication of key RMNCAH-N data in the public domain;\nand (iv) climate change adaptation by bringing RMNCAH-N services closer to the underserved populations in the\nregions and among the refugee and host community populations and improving energy efficiency and climate\nresiliency by repairing existing facilities.\n\n42. **The proposed Project will directly contribute to the WBG’s twin goals of ending extreme poverty and**\n**boosting shared prosperity** by investing in RMNCAH-N services and strengthening health systems more broadly,\nboth of which would support Djibouti’s objectives of strengthening its human capital.\n\n\nPage 24 of 64", "output": {"entities": {"named_data": ["RMNCAH-N data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000131", "page": 28, "chunk": 2, "title": "Djibouti - Health System Strengthening Project", "pdf_url": "http://documents1.worldbank.org/curated/en/772381653594094662/pdf/Djibouti-Health-System-Strengthening-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "RMNCAH-N data", "label": "NAMED_DATA", "score": 0.663691520690918, "start": 142, "end": 155, "probe_score": 0.0153, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "locations and assess their income, consumption, human capital acquisition, and quality of life.\n\n\nBecause of a lack of data on many aspects of urban life, much of the literature focuses on wages\n\n\nand productivity and attempts to measure an urban wage or productivity premium.\n\n\n_The link between city scale and labor productivity_\n\n\nCities enjoy a productive advantage over rural areas, and this advantage is larger for larger cities.\n\n\nThis conjecture dates back at least to Adam Smith (1776) and was more fully articulated by\n\n\nAlfred Marshall (1890). The positive association between various measures of productivity and\n\n\nurban scale has been repeatedly documented since Shefer (1973) and Sveikauskas (1975). The\n\n\nfact that larger cities obtain higher scores on many productivity metrics, from wages to output\n\n\nper worker or the total factor productivity of firms, is now beyond doubt. Most of the studies\n\n\nreviewed by Rosenthal and Strange (2004), Melo, Graham, and Noland (2009), and Puga (2010)\n\n\nmeasure an elasticity of wages or firm productivity with respect to city employment or urban\n\n\ndensity of between 0.02 and 0.10. That is, a city that is 10% larger in population offers wages\n\n\nthat are 0.2 to 1% higher.\n\n\nThis type of work involves regressing an outcome variable by location on a measure of\n\n\nagglomeration. In the early literature, the typical regression of choice involved using output per\n\n\nworker as the dependent variable and city population as the explanatory variable. In the early\n\n\n1990s, authors often employed more indirect strategies and began to use variables such as\n\n\nemployment growth or firm creation as outcome measures (e.g., Glaeser, Kallal, Scheinkman,\n\n\nand Shleifer 1992; Henderson, Kuncoro, and Turner 1995). More recently, the literature has\n\n\nmoved to microdata and returned to more direct outcome measures, namely the total factor\n\n\nproductivity of firms and wages. Importantly, the focus is on differences in", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["microdata"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005937", "page": 6, "chunk": 0, "title": "wps6818", "pdf_url": "https://local/prwp/wps6818.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "microdata", "label": "VAGUE_DATA", "score": 0.619998037815094, "start": 1803, "end": 1812, "probe_score": 0.9344, "gold": "DATA_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "# **RÉPUBLIQUE DÉMOCRATIQUE DU CONGO**\n### **POINTS SAILLANTS DE PROTECTION – NOVEMBRE 2024**\n\n\n\ndéfenseurs des droits, sont monnaie courante, particulièrement dans la\ncommune rurale de Lac Munkamba. Les acteurs de la société civile\nsubissent des pressions croissantes des autorités administratives et\nmilitaro-policières locales.\n\nParallèlement, des conflits liés au pouvoir coutumier opposent\nviolemment des clans dans les groupements de Bakua Kashila 3 et\nBakua Lonji. Ces luttes ont causé le déplacement forcé de populations\net des pertes humaines, notamment trois décès à Bakua Lonji.\n\n\n- À **Mbujimayi,** une recrudescence du banditisme juvénile dans les\ncommunes de Diulu et Bipemba a conduit à des affrontements, causant\ndes blessures graves et un meurtre.\nDans la commune de la Muya, le meurtre d’un homme par un « homme\nfort » local, sous prétexte d’une moquerie, a déclenché des violences\ndans le quartier Kajiba, entraînant des destructions de maisons et des\naffrontements inter-familiaux.\nÀ Bipemba, une seconde vague de démolitions autour de l’aéroport a\ncausé la panique, tandis que les victimes de la première vague vivent\ntoujours dans des conditions précaires.\n\n**<mark>KASAI Central</mark>**\n\n- La province du Kasaï Central a été le théâtre de tensions généralisées,\navec des préoccupation", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000727", "page": 10, "chunk": 0, "title": "République démocratique du Congo | Points Saillants de Protection | novembre 2024", "pdf_url": "https://reliefweb.int/attachments/6a46544e-64a7-451d-bef1-1845ffe7e9f8/points_saillants_situation_de_protection_en_rd_congo_novembre_2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nLebanon Health Resilience Project (P163476)\n\n\n|Indicator Name|Core|Unit of<br>Measure|Baseline|End Target|Frequency|Data Source/Methodology|Responsibility for<br>Data Collection|\n|---|---|---|---|---|---|---|---|\n|Description:Percent of female beneficiaries of the total number of beneficiaries who will have access to the essential healthcare services package.|Description:Percent of female beneficiaries of the total number of beneficiaries who will have access to the essential healthcare services package.|Description:Percent of female beneficiaries of the total number of beneficiaries who will have access to the essential healthcare services package.|Description:Percent of female beneficiaries of the total number of beneficiaries who will have access to the essential healthcare services package.|Description:Percent of female beneficiaries of the total number of beneficiaries who will have access to the essential healthcare services package.|Description:Percent of female beneficiaries of the total number of beneficiaries who will have access to the essential healthcare services package.|Description:Percent of female beneficiaries of the total number of beneficiaries who will have access to the essential healthcare services package.|Description:Percent of female beneficiaries of the total number of beneficiaries who will have access to the essential healthcare services package.|\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Name: Pregnant women<br>receiving at least four<br>antenatal care visits|Col3|Percentage|50.00|70.00|Annual|HIS|PMU|Col10|\n|---|---|---|---|---|---|---|---|---|---|\n||Description:Percent of pregnant women (from among the cumulative number of", "output": {"entities": {"named_data": ["Lebanon Health Resilience Project"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000032", "page": 43, "chunk": 0, "title": "Lebanon - Health Resilience Project", "pdf_url": "http://documents.worldbank.org/curated/en/616901498701694043/pdf/Lebanon-Health-PAD-PAD2358-06152017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Lebanon Health Resilience Project", "label": "NAMED_DATA", "score": 0.7395796179771423, "start": 19, "end": 52, "probe_score": 0.947, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**IBRD Map 43032**\n\n\n83", "output": {"entities": {"named_data": ["IBRD Map"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000144", "page": 96, "chunk": 0, "title": "Cameroon - Inclusive and Resilient Cities Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/832091503626454254/pdf/CAMEROON-PAD-NEW-08032017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "IBRD Map", "label": "NAMED_DATA", "score": 0.5452316999435425, "start": 2, "end": 10, "probe_score": 0.0124, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nGreater Beirut Public Transport Project (P160224)\n\n\n93. **The CDR has significant experience in implementing World Bank-financed projects, including**\n**FM aspects.** CDR FM performance on past and current projects is considered satisfactory. The CDR has a\nfunctional unit undertaking FM responsibilities, including funds flow management, accounting, reporting,\nand facilitating an acceptable external audit. The CDR’s external auditor will conduct the audit of the\nWorld Bank-financed projects. This functional unit consists of several financial officers (FOs) who have\nalready gained adequate experience in carrying out the FM arrangements of World Bank-financed projects\nand one of them will be assigned to handle this project’s FM arrangements implementation.\n\n\n94. **The CDR’s main challenge related to FM is its lack of proper maintenance of asset lists.** The CDR\nwill operationalize the asset module of its accounting software to ensure proper management of assets\npurchased under the project to mitigate FM-related risks. The CDR has the responsibility to provide the\nasset registry to RPTA by Project closure.\n\n\n**D. Procurement**\n\n\n95. **The implementing agency’s procurement capacity is generally adequate given the CDR’s**\n**extensive experience in implementing donor-funded projects.** The project will be implemented by the\nCDR, which was recently managing the UTDP that closed on December 31, 2015. The CDR has a solid\nmanagement structure and is staffed with adequate and experienced procurement and technical\nspecialists. Additional specialists will be recruited in the PIU, as needed, to support the CDR as well as the\nRPTA in the management of the PPP contracts. Diligence is also observed in record keeping and quality of\nevaluation. The procurement processing and contract management was rated satisfactory, and the\nImplementation Completion and Results Report (ICR) of the UTDP rated the performance of the\nimplementing agency, the CDR, satisfactory. The", "output": {"entities": {"named_data": [], "descriptive_data": ["asset registry"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000074", "page": 41, "chunk": 0, "title": "Lebanon - Greater Beirut Public Transport Project", "pdf_url": "http://documents1.worldbank.org/curated/en/471241521338566907/pdf/PAD-final-02262018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "asset registry", "label": "DESCRIPTIVE_DATA", "score": 0.8838169574737549, "start": 1096, "end": 1110, "probe_score": 0.0219, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**B.** **Sectoral and Institutional Context**\n\n\n4. **The pre‐tertiary education system in Jordan is organized in three levels** : (1) early childhood\neducation (ECE) or preprimary—kindergarten (KG) 1 and 2; (2) compulsory basic education,\ncomprising primary and lower secondary levels (grades 1–10); and (3) upper secondary education\ncomprising both academic and vocational streams (grades 11 and 12). The pre‐tertiary education\nsystem is managed by the Ministry of Education (MOE), while the Ministry of Higher Education and\nScientific Research (MOHESR) manages tertiary institutions (universities and vocational colleges).\n\n\n5. **Over the last two decades, Jordan has made efforts to improve access to education for boys**\n**and girls**, and to increase the efficiency of its education system. The country has spent many years\npursuing reforms toward a knowledge economy. Through multi‐donor development programs such\nas the Education Reform for Knowledge Economy (ERfKE), Jordan made impressive strides in terms of\nschool access and attainment and enrollment rates. Under the first phase of ERfKE, the primary gross\nenrollment ratio increased from 71 percent in 1994 to 99 percent in 2010 (98 percent for girls and 99\npercent for boys), and the transition rate to secondary school increased from 63 percent to 98 percent\nover the same period (98 percent for both girls and boys). <sup>6</sup> [^6: World Bank EdStats data base—illiteracy rates, primary gross enrollment ratio, and transition rate to secondary\nschool.] The transition rate between grades is\nrelatively stable above 96 percent from grades 1–8; however, in grade 9, there is a marked drop down\nto 90 percent and a corresponding surge in dropout up to 7 percent. Repetition peaks at 3 percent in\ngrade 10, but it is comparatively lower than in many other Middle East and North Africa (MENA", "output": {"entities": {"named_data": ["World Bank EdStats data base"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000127", "page": 9, "chunk": 0, "title": "Jordan - Education Reform Support Program-for-Results Project", "pdf_url": "http://documents1.worldbank.org/curated/en/731311512702123714/pdf/Jordan-Educ-Reform-121282-JO-PAD-11142017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Bank EdStats data base", "label": "NAMED_DATA", "score": 0.9011772274971008, "start": 1401, "end": 1429, "probe_score": 0.9965, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**(b)** furnish an assessment to the Association for review. The table below outlines\ndisbursement linked indicators not achieved in 2020/2021.\n\n\n\nDisbursement\nLinked Indicator Progress in\n**No.** (DLI) Disbursement Linked Results (DLR) DLI's\n\n\n\n**1** Scope, coverage, **(1b)** (i)-re-registration exercise in the four Overdue\nand functionality of original counties completed and beneficiary\nsingle Registry list updated accordingly- WB **IDA-** **EUR** **3.5** MEnhanced **(US** **$** 4m) **DFID-US** **$ 0.5** M-June 2020\n2 New Inua Jamii **(2b)-** **100%** of beneficiaries receiving Partially\npayment payments through the new payment achieved\nmechanism for mechanism **-IDA** **EUR** 4.3m **(US** **$** 9m) -June\nthree **NSNP** cash 2021\ntransfer programs\n\nis rolled out\n**3** Integrated **G** **& CM** (3a)- **G** **&CM** Mechanism is functional at all Overdue\nmechanism is levels for four National Safety Net Programme\nstrengthened and **(NSNP)** programs in 47 counties **-IDA** **EUR**\nrolled out at **8.65** m **(US** **$** 10M)-June 2020\ndecentralized level\n4 Increased access (4b)(i) tools designed and formal agreement Overdue\nto social inclusion between the **SDSP,** MOH and **NHIF** in place", "output": {"entities": {"named_data": [], "descriptive_data": ["beneficiary\nsingle Registry list"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002755", "page": 18, "chunk": 0, "title": "Kenya - AFRICA EAST - P164654 - Kenya Social and Economic Inclusion Project - Audited Financial Statement", "pdf_url": "https://documents.worldbank.org/curated/en/099055104052219056/pdf/P1646540c3ed480670a1050e7ed31265c9a.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "beneficiary\nsingle Registry list", "label": "DESCRIPTIVE_DATA", "score": 0.6741775274276733, "start": 380, "end": 412, "probe_score": 0.0372, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " not\nanticipate a significant negative impact\non wages due to increased competition.\nEnhancing language fluency is one way\nto address occupational downgrading. To\navoid double counting, we estimated that\naround PLN 1 billion has been already\nincluded in the previously estimated gains\nfrom reduced downgrading.\n\n\n\n**A further increase in labour**\n**participation of refugees would**\n**yield significant macroeconomic**\n**benefits.** Although the employment rate\nof Ukrainian refugees in Poland is already\nhigh when compared to other countries,\nthere is still room for improvement.\nIncreasing the employment of refugees by\n15 thousand people, which would close\nhalf of the gap between the employment\nrate of refugees and Poles, would yield at\nleast PLN 1 billion of value added in the\neconomy. This calculation is made under\nan assumption that those newly hired\nwould be paid minimum wage and should\nbe considered a lower-bound estimate, as\nit understates potential benefits. In part,\nthe higher productivity of workers might\nboost the profits for employers, further\nenhanced by increased investment.\n\n\n#### **4.4 Persons not previously in employment**\n\n\n\n**Employment rates among Ukrainian**\n**refugees are exceptionally high, with**\n**only a minority requiring targeted**\n**assistance to enter the labour market,**\n**in particular those who were not**\n**employed before their displacement.**\nIn the SEIS survey, employment rates\namong refugees aged 18-64 previously\nemployed or self-employed in Ukraine, are\n81% and 91% respectively. That is already\nvery high and any further increase would\nbe marginal. On the other hand, those who\nback in Ukraine managed the household\nhave an employment rate in Poland of\n38%. Even before becoming refugees, they\nwould have required support to enter the\nworkforce and now, in the host country,\nthey would be likely to benefit from such\nhelp even more. Some of them may be\ndiscouraged by not having been able", "output": {"entities": {"named_data": ["SEIS survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 17, "chunk": 2, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS survey", "label": "NAMED_DATA", "score": 0.8570196628570557, "start": 1400, "end": 1411, "probe_score": 0.9295, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "DJIBOUTI\nSchool Access and Improvement Program\n\n\n**Project Appraisal Document**\n\n\nMiddle East and North Africa Region\n\nMNSHD\n\n\n\nDate: November 17, 2000 Team Leader: Qaiser M. Khan\n\n\n\nCountry Director: Inder K. Sud Sector Director: Baudouy\nProject **ID:** P044585 Sector(s): EP - Primary Education, ES - Secondary\n\n\n\n. Education\nLending Instrument: Adaptable Program Loan <sup>(APL)</sup> Theme(s): Education; Gender and development\n\n\n\nPoverty Targeted Intervention: N\n\n\n\nProgram Fin ncing Data\n\n\n\nEstimated\nAPL Indicative Financing Plan Implementation Period (Bank FY) Borrower\n\n\n\n**IBRD** Others **Total** **COMMITMENT** **Closing**\n**US$** m % US$ m US$ m Date Date\nAPL 1 10.00 75.8 3.20 13.20 03/31/2001 06/30/2005 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\n________________ Education\n\n\n\nAPL 2 10.0 65.8 5.20 15.20 07/01/2005 06/30/2008 Republic of\n\n\n\nLoan/ Credit Djibouti\n\n\n\nCredit Ministry of\n\n\n\ni_________ ________________ Education\n\n\n\nAPL 3 10.00 41.0 14.40 24.40 07/01/2008 06/30/2011 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\nEducation\n\n\n\nTotal 30.00 22.80 52.80\nProject Financing Data Credit\nFor Loans/Credits/Others: Amount (US$m): 10.0\n\n\n\nProposed Terms: Standard Credit\n\n\n\nGrace period (years): 10 Years to maturity: 40\nCommitment fee: 0.50% (0% for FY01) Service charge: 0.75", "output": {"entities": {"named_data": ["Project Financing Data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013616", "page": 4, "chunk": 0, "title": "Kenya - Third Forestry Project", "pdf_url": "https://documents.worldbank.org/curated/en/478061468283488704/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Project Financing Data", "label": "NAMED_DATA", "score": 0.5102046728134155, "start": 1106, "end": 1128, "probe_score": 0.1169, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " per<br>year<br>|Project<br>monitoring<br>system<br>|Internal validation of<br>accessibility of<br>monitoring tool<br>|Project Coordination<br>Team<br>|\n|External users of monitoring tool for<br>access to bread satisfied with information<br>provided|Level of satisfaction<br>reported by external users<br>of monitoring tool for access<br>to bread|<br>Twice per<br>year<br>|Monitoring<br>tool for<br>access to<br>bread<br>developed<br>under the<br>project<br>|Online survey of<br>external users of the<br>monitoring tool<br>|Project Coordination<br>Team<br>|\n|External users of monitoring tool for<br>access to animal feed satisfied with|Level of satisfaction<br>reported by external users|Twice per<br>year|Monitoring<br>tool for|Online survey of<br>external users of the|Project Coordination|\n\n\nPage 42 of 54", "output": {"entities": {"named_data": [], "descriptive_data": ["Online survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 46, "chunk": 1, "title": "Jordan - Emergency Food Security Project", "pdf_url": "http://documents.worldbank.org/curated/en/486071652556836130/pdf/Jordan-Emergency-Food-Security-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Online survey", "label": "DESCRIPTIVE_DATA", "score": 0.5113463997840881, "start": 459, "end": 472, "probe_score": 0.0306, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "sup>recently</sup> <sup>come</sup> <sup>under Government control.</sup>\n\n\n\n**2.** **Main sector** issues **and** <sup>**Government strategy:**</sup>\n\n\n\n_Sector Issues._\n_Poverty in Sierra Leone._ Sierra <sup>Leone has</sup> <sup>the lowest</sup> <sup>Human Development Index</sup> <sup>**in**</sup> <sup>the world</sup>\n\n\n\nand has a GNP per capita <sup>of only US$130</sup> <sup>compared</sup> <sup>to the average</sup> <sup>for Sub-Saharan</sup> <sup>Africa</sup> <sup>of $470.</sup>\n\n\n\nOver 82% of the population <sup>currently</sup> <sup>lives below</sup> <sup>the poverty line and life expectancy is only</sup> <sup>38 years.</sup>\n\n\n\nFertility, infant and child <sup>mortality are</sup> <sup>high</sup> <sup>and over</sup> <sup>a third</sup> <sup>of children and</sup> <sup>a fourth</sup> <sup>of adults</sup> <sup>are</sup>\n\n\n\nmalnourished. The pnmary <sup>school enrollment</s", "output": {"entities": {"named_data": ["Human Development Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000017", "page": 7, "chunk": 1, "title": "West Bank and Gaza - Integrated Community Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/158081468762622780/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Human Development Index", "label": "NAMED_DATA", "score": 0.6837996244430542, "start": 251, "end": 274, "probe_score": 0.0779, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Domestic preference** as specified under paragraph 5.51 of the Procurement Regulations **(Goods**\n**and Works)** .\n\n\nGoods: is applicable for those contracts identified in the Procurement Plan tables;\n\n\nWorks: is applicable for those contracts identified in the Procurement Plan tables\n\n\n**Other Relevant Procurement Information.**\n\n\n**Not Applicable**", "output": {"entities": {"named_data": [], "descriptive_data": ["Procurement Plan tables", "Procurement Plan tables"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015244", "page": 1, "chunk": 0, "title": "Ethiopia/AFRICA- P163438- Ethiopia Rural Productive Safety Net Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/590441521015932043/pdf/Ethiopia-AFRICA-P163438-Ethiopia-Rural-Productive-Safety-Net-Project-Procurement-Plan.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Procurement Plan tables", "label": "DESCRIPTIVE_DATA", "score": 0.7340602278709412, "start": 178, "end": 201, "probe_score": 0.0004, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Procurement Plan tables", "label": "DESCRIPTIVE_DATA", "score": 0.636336088180542, "start": 264, "end": 287, "probe_score": 0.0002, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n\n**<u>SHARE OF POPULATION PAYING FOR RENTED HOUSING: HOSTS VS REFUGEES</u>**\n\n\nShare of hosts living in rented housing (2023) Share of refugees fully paying for rent (2024) Share of refugees partially paying for rent (2024)\n\n\n100%\n\n\n80%\n\n\n60%\n\n\n40%\n\n\n20%\n\n\n0%\nBulgaria Czechia Estonia Hungary Latvia Lithuania Moldova Poland Romania Slovakia Region\n\n\nSource: Eurostat, survey data, SAG estimates\n\n\n**<u>HOUSING COST AS A SHARE OF HOUSEHOLD DISPOSABLE INCOME</u>**\n\n\nRefugees (2024) Hosts (2022)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nBulgaria Czechia Estonia Hungary Latvia Lithuania Moldova Poland Romania Slovakia Region\n\n\nSource: Eurostat, survey data, SAG estimates\n\n\n**<u>REFUGEE POVERTY RATES WITH AND WITHOUT CORRECTION FOR EXCESSIVE HOUSING COSTS</u>**\n\n\nRefugees (2024) Refugees with housing expense correction (2024) Hosts (2023)\n\n\n\n65%\n\n\n\n40%\n\n\n\n52%\n\n\n\n\n\n\n\n\n\n\n\n31%\n\n\n\n\n\n46%\n43%\n37%\n\n\n\n\n\n\n\n\n\nBulgaria Czechia Hungary Moldova Poland Romania Slovakia Estonia Latvia Lithuania Region\n\n\nSource: Eurostat, survey data, SAG estimates\n\n\n**6**", "output": {"entities": {"named_data": [], "descriptive_data": ["survey data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 5, "chunk": 0, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "DESCRIPTIVE_DATA", "score": 0.5848392844200134, "start": 476, "end": 487, "probe_score": 0.9968, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and social concern are:\n The NRMD, in which the Public Works Coordination Unit (PWCU) will be responsible for overseeing and\nsupporting the Public Works sub-component, including the implementation of E&S Standards;\n The LCU in the FSCD, which will be responsible for overseeing and supporting the implementation of E&S\nStandards for the Livelihoods sub-component;\n MoLSA will be responsible for monitoring and reporting on the implementation of Social Standards at the\ncommunity level (child labor, OHS, and GBV/SEA)\nThe PSNP has in place several supervision mechanisms including third party spot-checks. While given the size of the\nprogram it is not realists to plan for full coverage of all subprojects, under SEASN the sample size of the third party\nspot-checks will be increased and will also cover the physical outputs of the program using technology (GEMS).\n\n\nEntities responsible for the Public Works Sub-Component\nThe PWCU of the NRMD has been responsible for environmental and social safeguards management for the Public\nWorks sub-component since 2005 under the previous World Bank safeguards architecture, and will continue to take\nresponsibility for meeting the Bank’s E&S Standards under Phase V. The PWCU currently includes two staff qualified in\nenvironmental risk management, which is being increased to three for PSNP5. Under PSNP Phase IV safeguards\ncompliance is currently rated Moderately Satisfactory, shortcomings being principally in:\n(a) Varying quality of safeguards compliance monitoring, and\n(b) frequently inadequate implementation of safeguards in Afar and Somali regions.\nIt is expected that by the beginning of PSNP Phase V the monitoring of E&S Standards compliance by the Public Works\nsub-component will be greatly facilitated by the roll-out of the forthcoming Mapped Public Works Database System,\nand will thus improve. The mapped database system was developed during the course of PSNP4 and is about to be", "output": {"entities": {"named_data": ["Mapped Public Works Database System"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013866", "page": 5, "chunk": 1, "title": "Appraisal Environmental and Social Review Summary (ESRS) - Strengthen Ethiopia?s Adaptive Safety Net - P172479", "pdf_url": "https://documents.worldbank.org/curated/en/496811598191222064/pdf/Appraisal-Environmental-and-Social-Review-Summary-ESRS-Strengthen-Ethiopia-s-Adaptive-Safety-Net-P172479.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Mapped Public Works Database System", "label": "NAMED_DATA", "score": 0.873559296131134, "start": 1798, "end": 1833, "probe_score": 0.1456, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_<u>AAWSA – Resettlement Policy Framework</u>_\n\n\n**Land Tenure Regimes**\n\n_Ownership and Usage Rights_\nAs mentioned above, Ethiopian law does not recognize individual ownership of land. Land is\nowned by the state, in urban as well as in rural areas. In rural areas, land is primarily managed\nthrough traditional manners, and seldom do individuals hold documents ascertaining their\nusage rights over it. Although there may be local variations, farmland is typically used under\nindividual customary rights while grazing land is held under community customary rights. In\nurban areas, land usage is formalized through long term leasing agreements.\n\n_Tenancy and Sharecropping_\nSeveral types of tenancy and sharecropping systems can be practiced in Ethiopia:\n\n    - “Erta” is a typical sharecropping arrangement whereby a farmer who has land\nprovides all farm inputs and land tax while another farmer with no land ploughs,\nsows, and harvests. The two farmers then share the yield equally;\n\n    - Other common sharecropping arrangements include oxen belonging to one farmer\nbeing used to plough another farmer’s plot, the service being eventually paid by a\ncertain share of the harvest.\n\nLand can also be informally leased for one or more crop seasons to investors or tenants.\n\n\n**OTHER POTENTIALLY AFFECTED ASSETS**\n\n\nTogether with land, other immovable assets could potentially be impacted by construction of\na sub-project, for instance the following:\n\n    - Buildings, whether inhabited or not,\n\n    - Other structures (wells, channels, agricultural or commercial buildings, etc…),\n\n    - Trees and perennial crops,\n\n    - Annual crops.\n\n\n**ENTITLEMENTS**\n\n\nAll affected assets (and related affected people, ie. owners and users of the said affected\nassets) located within the footprint of a sub-project shall be inventoried. Only affected assets\nidentified during the census will be eligible for compensation. Appendix 3 presents\nframeworks of forms to be used for this census", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["census", "census"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013386", "page": 26, "chunk": 0, "title": "Ethiopia - Urban Water Supply and Sanitation Project : resettlement plan (Vol. 1 of 2) : Resettlement policy framework", "pdf_url": "https://documents.worldbank.org/curated/en/461921468037784937/pdf/RP5200AAWSA1RPF1R11251Jan107.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "census", "label": "VAGUE_DATA", "score": 0.5897162556648254, "start": 1866, "end": 1872, "probe_score": 0.5699, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "census", "label": "VAGUE_DATA", "score": 0.6166889071464539, "start": 1968, "end": 1974, "probe_score": 0.5041, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "-compliance with the financing agreement terms.\n\n**9.** **MANAGEMENT LETTER**\n\n\nIn addition to the audit report, the auditor will prepare a management letter, in which the\nauditor will:\n\n(a) Give comments and observations on the accounting records, systems and controls that\n\nwere examined during the course of the audit;", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001778", "page": 43, "chunk": 1, "title": "Official Documents- Disbursement and Financial Information Letter for Grant E308-ET.pdf", "pdf_url": "https://documents.worldbank.org/curated/en/099041124140526202/pdf/P1763031f9b6e10cf18ccd15e91c2ccaad1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". <sup>19</sup>\n\n\n18 WYD can be downloaded from http://econ.worldbank.org/projects/inequality.\n19 It has been argued that income measures from household survey data that\nis representative of the entire economy is a more reliable estimate of GDP\nthan the corresponding measures from the national accounts. In particular,\neven though survey-based estimates of income have their own problems,\nDeaton (2005) argues that: “If we need to measure poverty in a way that\n\n\n19", "output": {"entities": {"named_data": [], "descriptive_data": ["household survey data", "national accounts"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003194", "page": 18, "chunk": 1, "title": "wps3981", "pdf_url": "https://local/prwp/wps3981.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8796451687812805, "start": 143, "end": 164, "probe_score": 0.8364, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "national accounts", "label": "DESCRIPTIVE_DATA", "score": 0.593187689781189, "start": 286, "end": 303, "probe_score": 0.9449, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### **5. REPONSE**\n\n**a.** **Apercu des activités de protection générale (janvier-juin 2022)**\n\n\nFigure 3 : Dashboard des réalisations de protection\n\n\n\n8", "output": {"entities": {"named_data": ["Dashboard des réalisations de protection"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000679", "page": 7, "chunk": 0, "title": "Niger : Analyse de Protection Juillet 2022", "pdf_url": "https://reliefweb.int/attachments/64bb6e1c-43c5-44cb-9a6a-3d9a1b79cbde/Protection-Analysis-Update_Niger_July2022.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Dashboard des réalisations de protection", "label": "NAMED_DATA", "score": 0.543972373008728, "start": 108, "end": 148, "probe_score": 0.2986, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**OCCUPIED PALESTINIAN TERRITORY (OPT) |** July 2025\n\n\n**<u><mark>RISK 4</mark></u>**\n**Psychological / emotional abuse and inflicted distress**\n\n\nMonths of intense violence, destruction, displacement and witnessing of traumatic events have caused and gravely aggravated mental\nhealth needs and conditions, which were already very high in Gaza prior to the start of the escalation, contributing to widespread\nsymptoms of depression, anxiety, stress, trauma, and other mental health and psychosocial concerns. <sup>110</sup> Protection monitoring data\nshows **growing psychosocial risks reported by communities since September 2024 to unprecedented levels with a rapid rise during**\n**May and June 2025.** <sup>111</sup> Mental health service providers in Gaza expect trauma-related mental health deterioration will lead to longterm mental health conditions if left without rapid interventions and quality support. <sup>112</sup>\n\n\nUNICEF estimates that almost all of Gaza’s 1.2 million children require mental health and psychosocial support (MHPSS) <sup>113</sup>, and children\nwith disabilities are particularly at risk due to compounded vulnerabilities. 92 per cent of families with children with disabilities\nassessed by Atfaluna reported signs of extreme distress, including crying during sleep or panicking, and 90 percent reported violent\nbehavior or hyperactivity. <sup>114</sup>\n\n\nPsychological distress is particularly acute for persons with disabilities and newly injured individuals who face a dramatic shift in their\nphysical capabilities, loss of independence, and separation from caregivers. <sup>115</sup> The disruption of previous social roles, including loss of\nlivelihoods and changing social roles in the family and community, for example role as a breadwinner, has led to heightened emotional\nsuffering, anxiety and feelings of worthlessness,", "output": {"entities": {"named_data": [], "descriptive_data": ["Protection monitoring data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000931", "page": 8, "chunk": 0, "title": "Occupied Palestinian Territory (oPt): Gaza Protection Analysis Update, July 2025 - Risks and barriers faced by persons with disabilities and older persons [EN/AR]", "pdf_url": "https://reliefweb.int/attachments/8afad9c6-f6e0-5297-a6cd-bef1f06bfeb4/opt_gaza_protection_analysis_update_july2025.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Protection monitoring data", "label": "DESCRIPTIVE_DATA", "score": 0.8515501022338867, "start": 524, "end": 550, "probe_score": 0.9874, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", food security, assets, education, and health. The EHCVM data are\nrepresentative at the national and regional levels for each of the five countries.\n\n\nThe timing of the EHCVM makes it possible to assess the impact of seasonality in four of the five Sahelian\ncountries surveyed as the data were collected in two distinct waves during the same agricultural year; the\nfirst wave corresponding to the harvest period and the second one to the lean season. The waves collected\ninformation on different households, so the EHCVM data do not have a panel structure. However, the\n\n\n4", "output": {"entities": {"named_data": ["EHCVM data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000906", "page": 5, "chunk": 2, "title": "idu091e7bd240e2a00450e0a53507e80c0de6c4c", "pdf_url": "https://local/prwp/idu091e7bd240e2a00450e0a53507e80c0de6c4c.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "EHCVM data", "label": "NAMED_DATA", "score": 0.7837333679199219, "start": 52, "end": 62, "probe_score": 0.9578, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "HELPING HANDS\nTHE ROLE OF \nHOUSING \nSUPPORT AND \nEMPLOYMENT \nFACILITATION IN \nECONOMIC \nVULNERABILITY \nOF REFUGEES \nFROM UKRAINE\nAn inter-agency \nexploration of socio-\neconomic data\nApril 2024", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["socio-\neconomic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 0, "chunk": 0, "title": "3", "pdf_url": "https://local/jad_paddy_docs/3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "socio-\neconomic data", "label": "VAGUE_DATA", "score": 0.7336421608924866, "start": 161, "end": 181, "probe_score": 0.4913, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**2. Different Methods Used for Sampling Migrants, Families of Migrants, and Other**\n\n\n**Rare Elements**\n\n\nAny attempt to carry out a specialized survey of migrants or of migrant-sending\n\n\nhouseholds must face the problem that international migration is a relatively rare event in\n\n\nmost countries. Bilsborrow et al. (1997) note that in three-quarters of the countries in the\n\n\nworld, the proportion of international migrants was at most 6.5 percent in the early 1990s.\n\n\nEven in countries in which international migration is more common, finding a household\n\n\nwith a migrant currently abroad or a recently returned migrant can be a rare event.\n\n\nTherefore carrying out a survey of migrant-sending households is essentially a problem\n\n\nof surveying “rare elements” or “rare populations” (Kish, 1965, Kalton and Anderson,\n\n\n1986). Our application fits well this description: it is estimated that there are\n\n\napproximately 1.4 million Nikkei households in Brazil, relative to an overall population\n\n\nof over 170 million.\n\n\nConducting a probabilistic sample of a rare population presents no problem if a full\n\n\nsample frame is available. Representative samples of legal migrants have thus been\n\n\nrecently conducted using administrative records on new immigrants. Examples include\n\n\nthe New Immigrant Survey (NIS) in the United States, the Longitudinal Survey of\n\n\nImmigrants to Australia (LSIA) and the Longitudinal Immigration Survey (LISNZ) in\n\n\nNew Zealand. This is more difficult to carry out for migrant-sending households, as it\n\n\nrequires obtaining from migrants and migrant records the contact details for the\n\n\nremaining household unit. The only application we are aware of which does this is the\n\n\nPacific Island-New Zealand Migration Survey (McKenzie, Gibson and Stillman, 2006),\n\n\nwhich links new Tongan migrants in New Zealand to their remaining households in\n\n\nTonga, and surveys the sending households in Tonga.\n\n\nThe much more common situation is one in which no survey frame is available. Three\n\n\napproaches to sampling rare elements", "output": {"entities": {"named_data": ["New Immigrant Survey", "Longitudinal Survey of\n\n\nImmigrants to Australia", "Longitudinal Immigration Survey", "Pacific Island-New Zealand Migration Survey"], "descriptive_data": ["survey of migrant-sending households", "administrative records on new immigrants"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003626", "page": 5, "chunk": 0, "title": "wps4419", "pdf_url": "https://local/prwp/wps4419.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey of migrant-sending households", "label": "DESCRIPTIVE_DATA", "score": 0.5041717886924744, "start": 672, "end": 708, "probe_score": 0.7662, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "administrative records on new immigrants", "label": "DESCRIPTIVE_DATA", "score": 0.7407452464103699, "start": 1218, "end": 1258, "probe_score": 0.9565, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "New Immigrant Survey", "label": "NAMED_DATA", "score": 0.9033451676368713, "start": 1283, "end": 1303, "probe_score": 0.9732, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Longitudinal Survey of\n\n\nImmigrants to Australia", "label": "NAMED_DATA", "score": 0.9272944331169128, "start": 1336, "end": 1384, "probe_score": 0.9981, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Longitudinal Immigration Survey", "label": "NAMED_DATA", "score": 0.8947762846946716, "start": 1400, "end": 1431, "probe_score": 0.9927, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Pacific Island-New Zealand Migration Survey", "label": "NAMED_DATA", "score": 0.9225559830665588, "start": 1705, "end": 1748, "probe_score": 0.9826, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "#### **3 Methodology**\n\n###### **3.1 Synthetic control case study**\n\nWe first employ the synthetic control method for a state-level comparative case study of the impact\n\n\nof Rajasthan’s labor law amendments on the state’s aggregate industrial outcomes. This method is\n\n\nincreasingly used to study the aggregate-level impacts of interventions that affect a small number\n\n\nof aggregate entities (in our case, a single state). It entails comparing the evolution of aggregate\n\n\noutcomes of interest in the entity affected by the intervention (the treatment unit) with comparable\n\n\nentities not affected by the intervention (the control).\n\n\nThe synthetic control method uses a systematic, data-driven procedure to select the control\n\n\ngroup. The idea behind this approach is that often, a weighted combination of potential compari\n\nson units is a good control group (Abadie and Gardeazabal (2003); Abadie et al. (2010)).\n\n\nSuppose there are a total of _J_ + 1 units (such as states) indexed by s. Let _Yst_ be unit _s_ ’s period\n\n\n_t_ outcome in the absence of the intervention. The intervention affects unit _s_ = 1 at a time _T_ 0 _>_ 1.\n\n\nThe other units are the potential controls. Suppose that\n\n\n_Yst_ = ∆ _t_ + Θ _t.Zs_ + Λ _t.µs_ + _est,_ (1)\n\n\nHere, ∆ _t_ is a time-varying factor that affects all units similarly, _Zs_ a vector of observed covariates\n\n\nnot affected by the intervention, Λ _t_ a vector of unobserved time-varying common factors whose\n\n\neffect on the outcome depends on unknown unit-specific factors _µs_, and _est_ an unobserved tran\n\nsitory shocks with zero mean. In order to estimate the impact of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001086", "page": 10, "chunk": 0, "title": "idu0de829349018930480b0a4ba0e627b6576af2", "pdf_url": "https://local/prwp/idu0de829349018930480b0a4ba0e627b6576af2.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".(13 155,94 ]\n\n2003-04 157,955\n\n2004-05 210,838\n\n2005-06 224,819\n\n2006-07 251,156\n\n2007-08 259,020\n\n2008-09 299,620e\n\n2009-10 337,OOOe\n\n352,309f\n2010-11\n\n_Source:_ ICR estimate, based on data from MoARD and other sources.\n_Note:_ e = estimate; f= forecast.\n\n\n-40\n\n\nUrea\n43,269\n\n51,808 -87,976\n\n94,919\n\n100,562\n\n98,057\n\n76,329\n\n106,394\n\n112,101\n\n121,735\n\n124,561\n\n129,121\n\n105,485e\n\n90,00Oe\n\n201,576f", "output": {"entities": {"named_data": ["data from MoARD"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008519", "page": 46, "chunk": 1, "title": "Ethiopia - Fertilizer Support Project", "pdf_url": "https://documents.worldbank.org/curated/en/139301468023443586/pdf/ICR17240P113150Official0Use0Only090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from MoARD", "label": "NAMED_DATA", "score": 0.766258716583252, "start": 187, "end": 202, "probe_score": 0.9932, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["M&E data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000050", "page": 29, "chunk": 2, "title": "Albania - Social Services Delivery Project", "pdf_url": "http://documents1.worldbank.org/curated/en/357561468742548905/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "M&E data", "label": "VAGUE_DATA", "score": 0.5883201956748962, "start": 530, "end": 538, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nBalochistan Human Capital Investment Project (P166308)\n\n\n_Education Component CBA_\n\n\n13. **The project is estimated to generate a total of 22,550 additional years of schooling** by increasing\nthe number of children enrolled in project schools by 10 percent annual growth rate and the school\ncompletion rate, that is, the share of students enrolled in grade 1 of a school level who graduate from it,\nby 40 percent. In the absence of longitudinal data to estimate current completion rates, the CBA is limited\nto the benefits of additional years of schooling due to the project’s impact on school enrollment. The sex\nand grade distribution of students in each project district from Balochistan’s EMIS is used to determine\nthe share of girls and boys in each grade among the 18,000 students currently enrolled. Assuming no\nimpact in the first project year, the number of additional boys and girls enrolled in each grade for each\nyear in FY21–FY24 is then estimated using the targeted annual growth rate of enrollment (table 1.5).\n\n\n**Table 1.5. Additional School Years Accrued Due to Project Impact**\n\n|Col1|2021|Col3|2022|Col5|2023|Col7|2024|Col9|Total|\n|---|---|---|---|---|---|---|---|---|---|\n||**Girls**|**Boys**|**Girls**|**Boys**|**Girls**|**Boys**|**Girls**|**Boys**|**Boys**|\n|Primary|672|909|1,417|1,914|2,240|3,027|3,151|4,258|", "output": {"entities": {"named_data": ["EMIS"], "descriptive_data": [], "vague_data": ["longitudinal data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000085", "page": 45, "chunk": 0, "title": "Pakistan - Balochistan Human Capital Investment Project", "pdf_url": "http://documents1.worldbank.org/curated/en/519111593223468766/pdf/Pakistan-Balochistan-Human-Capital-Investment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "longitudinal data", "label": "VAGUE_DATA", "score": 0.6740000247955322, "start": 451, "end": 468, "probe_score": 0.9585, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "EMIS", "label": "NAMED_DATA", "score": 0.706631064414978, "start": 712, "end": 716, "probe_score": 0.407, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**S R I** LANKA: **PUTTALAM HOUSING PROJECT**\n**Annex** **1:** **Background and Project Design Framework**\n\n\n**Background**\n\n\nThe District o f Puttalam in North West Sri Lanka i s now home to many refugees displaced from the North\nin 1990. According to the UNHCR supervised census o f IDPs in Puttalam conducted in April 2006,\n63,145 persons or 15,480 families lived in 141 refugee camps. 41% o f the Puttalam IDPs were children\nunder the age o f 18. 72% o f the IDPs originate from Mannar; 14% come from Jafha and 10% from\nMullaitivu. The rest come from other districts in the North. The S A carried out as part o f project\npreparation indicated that 62% of the adult population worked as seasonal day labor in the informal\n\nsector. About 18% o f those surveyed in the UNHCR exercise reported that they had n o schooling while\n23% had a primary school education alone. Just 8% had completed their high school education. The IDPs\nare located in four divisions in the Puttalam district: Kalpitiya (55%), Puttalam (33%), Mundel (8%) and\nVanathavillu (3%). 96% o f Puttalam IDPs (14,928 families) indicated that they wished to remain and\nintegrate in Puttalam, citing security concerns as the major obstacle to return to their original homes.26\n74% o f the IDP households had in fact bought land in Puttalam demonstrating a resolve to remain there.\n\n\nMost refugee camps lack basic services including access to safe drinking water, toilet facilities, proper\ndrainage and garbage disposal. The UNHCR survey indicated that only 40% o f the IDP population had\nprivate permanent toilets. Since the provision", "output": {"entities": {"named_data": ["UNHCR supervised census o f IDPs in Puttalam", "UNHCR survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000023", "page": 21, "chunk": 0, "title": "Sri Lanka - Puttalam Housing Project", "pdf_url": "http://documents1.worldbank.org/curated/en/194731468104646411/pdf/38147core.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR supervised census o f IDPs in Puttalam", "label": "NAMED_DATA", "score": 0.7430752515792847, "start": 257, "end": 301, "probe_score": 0.988, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHCR survey", "label": "NAMED_DATA", "score": 0.7111182808876038, "start": 1489, "end": 1501, "probe_score": 0.9949, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014834", "page": 19, "chunk": 1, "title": "Uganda - Railways Project", "pdf_url": "https://documents.worldbank.org/curated/en/562991468349148742/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7292463183403015, "start": 272, "end": 283, "probe_score": 0.8771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "All data collection is done by GISSE a research institute in Bamako. The anonymized unit record\n\n\ndata of the baseline and the monthly surveys can be downloaded from www.gisse.org. The\n\n\nresponse rate for the phone interviews has been very high (Table 1): after 6 rounds of monthly\n\n\ninterviews the original sample is almost entirely intact. The low level of attrition demonstrates that\n\n\nmobile phone samples can be maintained over prolonged periods without being unduly affected\n\n\nby (non-random) respondent drop-out.\n\n\n**3.** **Characteristics of the Displaced and Returnee Population**\n\n\nAccording to the 2009 population census, the two most sizeable ethnic groups in northern Mali are\n\n\nthe Songhai (45%) and Kel Tamasheq (32%) --see Table 2. The crisis brought about an ethnic\n\n\ndivide, which is reflected in the composition of the three sub-samples. The majority of IDPs and\n\n\nreturnees are Songhai (75% and 71% respectively), while the majority of refugees are Kel\n\n\nTamasheq. Results suggest that the decision of where to flee was determined by ethnicity: Kel\n\n\nTamasheq and Arabs left the country; Songhai fled towards Bamako.\n\n\n**Table 2: Ethnic composition of IDPs, refugees, returnees in the North**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Ethnicity|IDPs in<br>Bamako<br>(%)|Refugees<br>Niger<br>(%)|Refugees<br>Mauritania<br>(%)|Returnees<br>(%)|Total I+R+R<br>(%)|Ethnic<br>composition of<br>the North (%)|\n|---|---|---|---|---|---|---|\n|Songhai <", "output": {"entities": {"named_data": ["2009 population census"], "descriptive_data": ["anonymized unit record\n\n\ndata"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006318", "page": 8, "chunk": 0, "title": "wps7253", "pdf_url": "https://local/prwp/wps7253.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "anonymized unit record\n\n\ndata", "label": "DESCRIPTIVE_DATA", "score": 0.6632113456726074, "start": 73, "end": 102, "probe_score": 0.3828, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "2009 population census", "label": "NAMED_DATA", "score": 0.7152212262153625, "start": 609, "end": 631, "probe_score": 0.928, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", assets and facilities (+230% compared to 66\nacts of violence in Q2). Out of 68 incidents of interference in the\nimplementation of humanitarian activities, 39 (57%) had a gender\ndynamic, with most of these relating to participation of female staff\nin humanitarian activities. Main actors responsible for all access\nconstraints in Q3 include Taliban (80%), ACG (9%), community\nmembers (5%), ANDSF (4%), and ISK (2%). Meanwhile, incidents\nstemming from military operations and kinetic activity and\nmovement restrictions decreased by 10% and 54% respectively <sup>12</sup> .\n\n\n12 HAG Q3 Report – July Sept. 2021", "output": {"entities": {"named_data": ["HAG Q3 Report"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001240", "page": 11, "chunk": 1, "title": "Afghanistan: Protection Analysis Update 2021 - Quarter 3 (October 2021)", "pdf_url": "https://reliefweb.int/attachments/be6857fb-5a09-389a-9c2f-8b1db873d126/afg_protection_analysis_update_q3_final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "HAG Q3 Report", "label": "NAMED_DATA", "score": 0.5960419774055481, "start": 578, "end": 591, "probe_score": 0.9997, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "where _yi_ <sup>_SE_</sup>\n\n\n\n_i_ <sup>_SE_</sup> <sup>,</sup> <sup>_y_</sup> _i_ <sup>_L_</sup>\n\n\n\n_i_ <sup>_L_</sup> <sup>,</sup> <sup>and</sup> <sup>_y_</sup> _i_ <sup>_K_</sup>\n\n\n\n_i_ <sup>_K_</sup> <sup>represent</sup> <sup>self-employed</sup> <sup>income,</sup> <sup>labor</sup> <sup>income,</sup> <sup>and</sup> <sup>capital</sup> <sup>income</sup>\n\n\n\nrespectively. Households reported receipts of incomes through various forms and over\n\n\nvarious time intervals. The variables used for income receipts and the time intervals over\n\n\nwhich they were received are reported as follows:\n\n\nTable B2: Income sources and time intervals in LSMS surveys\n\n\n**Income Source** **Time Interval**\n\n\nLast payment in cash Hour, Day, Week, Fortnight, Month, Quarter or Year\nLast payment in kind (value in LCU) Hour, Day, Week, Fortnight, Month, Quarter or Year\nNet income from business Week or Month\nRemittances in cash Year\nRemittances in kind Year\nRent of property Year\nPrivate or govt pensions Year\nDomestic remittances Year\nRent of farmland Year or cropping season\nSales of crops Year or cropping season\nSales of crop residue Year or cropping season\nSale of", "output": {"entities": {"named_data": ["LSMS surveys"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007590", "page": 66, "chunk": 0, "title": "wps8678", "pdf_url": "https://local/prwp/wps8678.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "LSMS surveys", "label": "NAMED_DATA", "score": 0.8333953022956848, "start": 638, "end": 650, "probe_score": 0.9526, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Public Disclosure Copy\n\n\n**The World Bank** Implementation Status & Results Report\nJudicial Performance Improvement (P105269)\n\n\nProgress on PDO 4 (distance to new courts) is not linear (as predicted in the results framework) throughout the life of the project as the bulk of\nthe new courts are larger in size and thus take longer to construct and therefore only open later on in the project period - when progress on this\nindicator will show.\nRe PDO 5 (user satisfaction), the next court user survey is planned for February 2017, which will allow an update of the user satisfaction data.\n\n\n**Intermediate Results Indicators**\n\n\nPHINDIRITBL\n\n\n\n\n\n\n\nPHINDIRITBL\n\n\n\n\n\n\n\nPHINDIRITBL\n\n\n\n\n\n\n\nPHINDIRITBL\n\n\n\n\n\n1/3/2017 Page 4 of 7\n\nPublic Disclosure Copy", "output": {"entities": {"named_data": [], "descriptive_data": ["court user survey"], "vague_data": ["user satisfaction data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009061", "page": 3, "chunk": 0, "title": "Kenya - Judicial Performance Improvement : P105269 - Implementation Status Results Report : Sequence 07", "pdf_url": "https://documents.worldbank.org/curated/en/175021483496314933/pdf/ISR-Disclosable-P105269-01-03-2017-1483496304330.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "court user survey", "label": "DESCRIPTIVE_DATA", "score": 0.8488234281539917, "start": 482, "end": 499, "probe_score": 0.3312, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "user satisfaction data", "label": "VAGUE_DATA", "score": 0.6609174013137817, "start": 564, "end": 586, "probe_score": 0.3341, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "G20 members collectively had 3.2 percent of their import product lines subject to TTBs in 2011; for\n\n\ncomparison, this is more than double their import coverage (1.5 percent) from a decade earlier, as\n\n\nreported by column (2). <sup>6</sup> [^6: This includes Argentina, Brazil, China, India, Indonesia, South Africa and Turkey. To be consistent with Bown\n(2011), Mexico is omitted from this particular aggregation given that it removed antidumping import restrictions\non China in 2008 that covered over 20 percent of its import product lines and had been in effect since 1993.] Six of the eight individual G20 emerging economies had higher levels of import\n\n\ncoverage in 2011 relative to 2001 – the two exceptions are Mexico and South Africa. In comparison, the\n\n\ncohort of six _high income_ economy G20 members in the sample combined to increase their coverage to\n\n\nonly 1.9 percent of import product lines in 2011, up from 1.8 percent in 2001.\n\n\nColumns (3) through (7) of Table 1 report information for each of the 24 policy-imposing\n\n\ncountries’ use of temporary trade barrier policies in 2011 based on an alternatively constructed measure\n\n\nthat _trade-weights_ policy use by bilateral, product-level (HS-06) import data. The four cohorts of policy\n\nimposing economies in Table 1 are each ranked by column (3). For example, among the cohort of\n\n\nemerging economy G20 members, this coverage ranged from a low of 0.3 percent of imports (Mexico)\n\n\nto a high of 6.3 percent of imports (India). Turkey, China, Argentina, Brazil and Indonesia also had a\n\n\nsignificant share of imports affected by TTBs in 2011. From the non-G20 cohort of emerging economies,\n\n\nPakistan, Peru and Thailand each had more than 1 percent of imports subject to TTBs in 2011.\n\n\nColumn (4) provides information to disentangle the extent to which the country relies\n\n\nexclusively on its antidumping policy to implement TTBs. For example, while 6.", "output": {"entities": {"named_data": [], "descriptive_data": ["bilateral, product-level (HS-06) import data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005328", "page": 6, "chunk": 0, "title": "wps6162", "pdf_url": "https://local/prwp/wps6162.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "bilateral, product-level (HS-06) import data", "label": "DESCRIPTIVE_DATA", "score": 0.5452430248260498, "start": 1181, "end": 1225, "probe_score": 0.9246, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " SRH\nservices and one in five did not trust local\nhealthcare providers, in addition to facing language\nbarriers.\n\n\nWomen with a disability reported more barriers with\n11% across the region (N=29) compared to those\nwithout disability (5%).\n\n\nAn in-depth assessment is needed to better\nunderstand sexual and reproductive health (SRH)\nneeds, the role of SRH access barriers in decisions\nto visit Ukraine, and how these barriers vary among\nwomen of different age groups, pregnant and\nbreastfeeding women, and women with disabilities.\n\n\n**Support services for survivors of gender-based**\n**violence**\nServices for survivors of gender-based violence\nencompass a range of functions, including safety\nand security, legal assistance, healthcare, mental\nhealth and psychosocial support. A critical\ncomponent is access to clinical management of\nrape to ensure timely medical treatment and care.\nAs this service is provided by the health care sector,\nas part of SRH, it is included in this analysis.\n\n\nThe SEIS identified gaps in awareness about on\navailable GBV services. In 2024, 38% of\nrespondents were unaware of health services\nproviding support to GBV survivors in their area,\nwhile 58% were unaware of available psychosocial\nsupport services. Respondents were less aware of\nhealth services in rural areas (45%) compared to\nurban areas (37%). Key barriers to accessing\nGBV-related services in general included lack of\nawareness (58%), language and cultural barriers\n(53%) and stigma/ shame (46%). This indicates that\nadditional coordinated efforts between the health,\nprotection and GBV working groups and partners\nare required to enable access to all lifesaving\nGBV-related services including clinical management\nof rape.\n\n\n**17**", "output": {"entities": {"named_data": ["SEIS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000004", "page": 16, "chunk": 1, "title": "NAVIGATING HEALTH AND WELL BEING CHALLENGES FOR REFUGEES FROM UKRAINE   2nd Edition", "pdf_url": "https://local/jad_paddy_docs/navigating health and well-being challenges for refugees from ukraine - 2nd edition.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS", "label": "NAMED_DATA", "score": 0.7348252534866333, "start": 994, "end": 998, "probe_score": 0.0002, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Figure 2. Percentage of Working People Contributing to Social Security per Educational Level.\n\n\n80%\n\n\n70%\n\n\n60%\n\n\n50%\n\n\n40%\n\n\n30%\n\n\n20%\n\n\n10%\n\n\n0%\n\n2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016\n\n\nDid not attend Incomplete Primary Studies\nComplete Primary Studies Incomplete Secondary Studies\nComplete Secondary Studies Incomplete University Studies\nComplete University Studies\n\n\nSource: author elaboration based on ENEMDU\n\n\nFigure 3 shows the percentage of working people contributing to social security per geographical area\n\n\n(whether urban or rural). Results show a wide difference in scope in the pension contributory system\n\nper area. While in year 2016, the percentage of contributing working people in urban areas achieved\n\n\n36%, in rural areas it only climbed up to 17%. These differences were stable throughout the whole\n\nstudy term.\n\n\nFigure 3. Percentage of Working People Contributing to Social Security per Urban/Rural Area.\n\n\n50%\n\n\n40%\n\n\n30%\n\n\n20%\n\n\n10%\n\n\n0%\n\n2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016\n\n\nRural Urban\n\n\nSource: author elaboration based on ENEMDU\n\n\n10", "output": {"entities": {"named_data": ["ENEMDU", "ENEMDU"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001957", "page": 11, "chunk": 0, "title": "performance and challenges of the income protection system for older people in ecuador", "pdf_url": "https://local/prwp/performance-and-challenges-of-the-income-protection-system-for-older-people-in-ecuador.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "ENEMDU", "label": "NAMED_DATA", "score": 0.7888545393943787, "start": 439, "end": 445, "probe_score": 0.9893, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "ENEMDU", "label": "NAMED_DATA", "score": 0.565976083278656, "start": 1120, "end": 1126, "probe_score": 0.9908, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nnew areas to examine staffing, equipment, jurisdictional issues, core function capacities, local service mapping capability,\nand GBV referral capacities and (b) the provision of technical assistance for county government officials on service delivery\nplanning; positive engagement with communities through participatory development planning, subproject\nimplementation monitoring, BDCs/PDCs’ performance monitoring, and periodic reporting on ECRP-II implementation. The\nlevels of technical assistance will be tailored to each county based on the findings of the ECRP functionality assessments\nfor previously engaged counties and new functionality assessments for new counties engaged under ECRP-II. This\nassistance will also facilitate the county government officials’ visiting subproject sites and participating in the BDCs/PDCs’\nplanning workshops as needed. Given the unknowns with regard to the level of functionality of county governments,\nespecially in conflict-affected areas, this subcomponent does not have an explicit result indicator. Where functionality\nassessments determine that some county governments are not functional, the project will focus on supporting community\ninstitutions.\n\n38. **Subcomponent 2.3 National Government Strengthening** . This sub-component will support the capacity building\nof the PMU based on an assessment of their technical competencies in the areas of financial management, procurement,\nproject planning, monitoring and evaluation, community engagement methods, and safeguards. The Project will also\ndevelop standards and training for fiduciary and technical supervision capacities. ECRP-II will facilitate linkages between\nthe PMU and the CCTs at the county level to establish protocols and regularized support for constructive county\nengagement in local resource management and service delivery improvement and maintenance activity.\n\n\n39. GIZ, who has long engaged in local governance strengthening support in South Sudan with LGB, has shown interest\nin collaborating with the Bank on the implementation of ECRP-II. While discussions are still underway, GIZ may provide\nparallel financing to all or part of the ECRP-II activities while utilizing the same government agencies as the implementing", "output": {"entities": {"named_data": [], "descriptive_data": ["ECRP functionality assessments"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000027", "page": 15, "chunk": 1, "title": "Concept Project Information Document (PID) - Enhancing Community Resilience and Local Governance Project Phase II - P177093", "pdf_url": "http://documents.worldbank.org/curated/en/538641629099997119/pdf/Concept-Project-Information-Document-PID-Enhancing-Community-Resilience-and-Local-Governance-Project-Phase-II-P177093.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "ECRP functionality assessments", "label": "DESCRIPTIVE_DATA", "score": 0.5915431380271912, "start": 562, "end": 592, "probe_score": 0.4898, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<br>signed documents at<br>MOE|Third Party|The verification agency will check<br>that the national assessment<br>strategy has been adopted, signed,<br>and published on MOE's website.|\n|**DLR#7.2**Grade 3 diagnostic<br>test on early grade reading and<br>math implemented in all target<br>schools|Schools are conducting rapid, no‐stakes formative assessments<br>given by Grade 3 teachers at the beginning of the year to<br>evaluate student learning needs, particularly in math and<br>reading.|School records of<br>assessments|Third Party|Check assessments records for a<br>sample of schools|\n|**DLR#7.3**First phase of _Tawjihi_<br>exam reform completed and<br>action plan for reform rollout is<br>produced|The first phase of the_Tawjihi_reform will consist of conducting<br>consultations on the reform with the various stakeholders, the<br>design of the new examination instruments and the piloting of<br>those instruments. After the first phase, MOE will analyze the<br>examination data, in addition to perception ", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["examination data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000127", "page": 47, "chunk": 1, "title": "Jordan - Education Reform Support Program-for-Results Project", "pdf_url": "http://documents1.worldbank.org/curated/en/731311512702123714/pdf/Jordan-Educ-Reform-121282-JO-PAD-11142017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "examination data", "label": "VAGUE_DATA", "score": 0.6958522796630859, "start": 970, "end": 986, "probe_score": 0.9862, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012555", "page": 62, "chunk": 2, "title": "Kenya - Kamburu Hydroelectric Project", "pdf_url": "https://documents.worldbank.org/curated/en/409091468047424896/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouthern Niger Connectivity and Integration Project (P179770)\n\n\nto the ongoing climate change in the project area. This activity will consist of: (i) consultant services to carry out a study\nto optimize drainage works quantities in areas with RHC populations most critically affected by flooding; (ii) consultant\nservices to train individuals from RHC in HIMO-type drainage works; and (iii) non-procurable HIMO-type drainage works\nto be supervised by the corresponding project team and performed exclusively by RHC. Local training and employmentgeneration opportunities will be managed by the PCU in coordination with the ministry in charge of interior affairs’\nDGECMR and the corresponding project team. While this activity will target the training of a large population within RHC\n(3,000), only 400 refugees and 100 hosts will be targeted from the most vulnerable for employment opportunities as only\n50 km of concrete blocks will be constructed.\n\n\n48. **Implementation risk reduction through a feasibility studies approach.** The streamlined focus on feasibility studies\nand institutional arrangements makes implementation more straightforward and less risky. The project avoids direct\nfinancial implementation risks, such as weak absorption capacity among financial intermediaries, MSMEs, or difficulties in\nfund disbursement. By shifting to value chain and trade facilitation studies, the project enables private sector engagement,\nensuring that logistics operators, exporters, and traders can contribute to shaping future investments. Consequently,\nunder the technical leadership of the DGTPI: (i) institutional partners will consult with financial institutions involved in the\nLAMP (e.g., commercial banks, the Sahelian Financial Company – SAHFI <sup>67</sup> [^67: The Sahelian Financial Company (SAHFI SA- Société Sahélienne de Financement) established in 2005 as a joint initiative between the European Union (EU) and the State of Niger for providing guarantees to small and\nmedium enterprises and small and medium industries (SMEs/SMIs).] ) for the logistics value chain support program to\ninform suitable recommendations applicable to the informal value chain logistics context;", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000184", "page": 30, "chunk": 0, "title": "Niger - Southern Niger Connectivity and Integration Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099043025161072911/pdf/BOSIB-850e0c11-07c1-4c9c-8d44-4286704221bd.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Table 1. Country and Industry Coverage**\nThis table presents the distribution of observations and unique firms among the countries. Panel A presents the country\ncoverage. Panel B presents the industry coverage. Industry definitions are from Institutional Shareholder Services\n(ISS) database.\n\n\n**<u>Panel A: Country Coverage</u>**\n**<u>Countries</u>** **<u># of Observations</u>** **<u>% of Observations</u>** **<u># of Unique Firms</u>** **<u>% of Unique Firms</u>**\nAustralia 479 1.42 125 1.48\nAustria 95 0.28 23 0.27\nBelgium 121 0.36 30 0.35\nCanada 858 2.54 221 2.61\nDenmark 116 0.34 26 0.31\nFinland 153 0.45 33 0.39\nFrance 413 1.23 97 1.15\nGermany 427 1.27 100 1.18\nGreece 193 0.57 43 0.51\nHong Kong SAR, China 252 0.75 65 0.77\nIreland 143 0.42 34 0.40\nItaly 297 0.88 77 0.91\nJapan 2,668 7.91 596 7.05\nNetherlands 251 0.74 58 0.69\nNew Zealand 74 0.22 20 0.24\nNorway 103 0.31 25 0.30\nPortugal 70 0.21 15 0.18\nSingapore 271 0.8 58 0.69\nSpain 245 0.73 60 0.71\nSweden 220 0.65 54 0.64\nSwitzerland 304 0.9 72 0.85\nUnited Kingdom 1,798 5.33 531 6.28\n<u>United States</u> <u>24,163</u> <u>71.67</u> <u>6090</u>", "output": {"entities": {"named_data": ["Institutional Shareholder Services\n(ISS) database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001759", "page": 9, "chunk": 0, "title": "is short term debt a substitute or a complement to good governance", "pdf_url": "https://local/prwp/is-short-term-debt-a-substitute-or-a-complement-to-good-governance.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Institutional Shareholder Services\n(ISS) database", "label": "NAMED_DATA", "score": 0.8719097375869751, "start": 243, "end": 292, "probe_score": 0.9997, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". South Sudan Flooding Situation Report: Inter-Cluster Coordination Group, as of 31 January 2021.\n20 HDI’s life-course gender gap compiles 12 indicators that analyze gender gaps in choices and opportunities across the lifespan including education, labor and work,\npolitical representation, time use, and social protection. HDI’s women’s empowerment dashboard compiles 13 woman-specific empowerment indicators in three\ncategories: reproductive health and family planning, violence against women and girls, and socioeconomic empowerment.\n21 UNDP. 2018. _Human Development Indices and Indicators: 2018 Statistical Update - South Sudan._\n22 Kenwill International Limited. 2015 _. Fortifying Equality and Economic Diversification (FEED): Improved Livelihoods in South Sudan._ Gender Assessment Report, World\nVision, July 2015.\n23 Kenwill International Limited. 2015 _._\n\n\nAug. 1, 2021 Page 5 of 20", "output": {"entities": {"named_data": ["women’s empowerment dashboard"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000027", "page": 4, "chunk": 3, "title": "Concept Project Information Document (PID) - Enhancing Community Resilience and Local Governance Project Phase II - P177093", "pdf_url": "http://documents.worldbank.org/curated/en/538641629099997119/pdf/Concept-Project-Information-Document-PID-Enhancing-Community-Resilience-and-Local-Governance-Project-Phase-II-P177093.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "women’s empowerment dashboard", "label": "NAMED_DATA", "score": 0.5302514433860779, "start": 329, "end": 358, "probe_score": 0.8809, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "COMPOUNDING MISFORTUNES\nChanges in Poverty since the onset of Covid-19 on Syrian Refugees and 11\nHost Communities in Jordan, the Kurdistan Region of Iraq and Lebanon\n\n\n\nrecent, and more representative, welfare data\nbeen available.\n\nIn many respects the countries in this study\nhave experienced comparable dynamics,\nincluding tight fiscal space, receiving and\nsupporting large numbers of Syrian refugees\nand have weathered the resulting pressures,\nincluding on public services. Syrian refugees\nregistered with UNHCR in Jordan, KRI and\nLebanon have at times exceeded a fifth of the\nhost population. As of November 2020,\nUNHCR has registered 5.6 million Syrian\nrefugees, of which 1.8 million are hosted by\nJordan, KRI and Lebanon. <sup>2</sup> The total number\nof Syrians is even higher when including\ngovernment estimates of those not registered\nwith UNHCR. Jordan, KRI and Lebanon also\ndiffer in a number of ways: the general state of\ntheir economies, labor policies for refugees,\nlockdown policies and the prevalence and\nimpact of COVID-19 on their societies.\n\nIn Lebanon, the total number of Syrians\nrefugees is estimated at 1.5 million. Lebanon\nhas been grappling with political instability,\nan economic crisis and, most recently, the\naftermath of the Port of Beirut explosion. The\neconomic crisis comes on multiple fronts:\ncurrency and banking crises, increasing\nunemployment and soaring levels of inflation.\nAll these have had devastating effects on both\nLebanese and refugee communities.\n\nJordan hosts 650,000 registered Syrian\nrefugees in addition to Iraqi refugees and\nrefugees of other nationalities. The\ngovernment estimates that the total number\nof Syrians refugees could reach as many as 1.4\nmillion. <sup>3</sup> The country’s fiscal position has\nbeen deteriorating since 2017 and coming\ninto the COVID-19 crisis unemployment had\nbeen near 19 percent.\n\nKRI hosts around 250,000 refugees – almost\nall the Syrian refugees in Iraq – and around\nhalf of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["welfare data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000383", "page": 10, "chunk": 0, "title": "Compounding Misfortunes - Changes in Poverty since the Onset of COVID-19 on Syrian Refugees and Host Communities in Jordan, the Kurdistan Region of Iraq and Lebanon [EN/AR]", "pdf_url": "https://reliefweb.int/attachments/3259e81a-0a06-3628-80b9-78422fb24586/Compounding-Misfortunes-Changes-in-Poverty-Since-the-Onset-of-COVID-19.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "welfare data", "label": "VAGUE_DATA", "score": 0.7009276747703552, "start": 202, "end": 214, "probe_score": 0.8642, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " of the GIS project, the paper identifies some of its key findings, some of\nwhich have important implications for refugee protection in Nairobi. For example:\n\n\n  - self-identified refugee leaders who were relied upon to transmit information\nto their communities have not done so in an effective manner;\n\n\n  - significant numbers of people who consider themselves to be refugees had\nnot registered with UNHCR and some were not aware of the services it\nprovides, despite the organization’s long-term presence in Nairobi; and,\n\n\n  - amongst refugees from the Horn of Africa, women are the main\nbreadwinners while men are more reliant on remittances.\n\n103.   While GIS has proven to be a useful tool in terms of understanding the urban\nrefugee population, it is heavily reliant on regular and accurate data input, especially\nif it is to provide a useful picture of the changing dynamics of that population.\nUnfortunately, since the initial mapping exercise was undertaken, a shortage of\nresources has prevented the existing data from being updated – a significant\ndrawback in a context where new refugees are arriving and existing populations are\nknown to be mobile. A partnership with UN-HABITAT, which has particular\nexpertise in relation to the mapping of urban and slum areas, should be explored in\nthis respect.\n\n\n24", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["existing data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001064", "page": 26, "chunk": 1, "title": "Navigating Nairobi: A review of the implementation of UNHCR's urban refugee policy in Kenya's capital city", "pdf_url": "https://reliefweb.int/attachments/a1368b0f-707c-3e58-8c27-da3056830b63/DD1F3B9EF6706831852578340073DA98-Full_Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "existing data", "label": "VAGUE_DATA", "score": 0.5577818751335144, "start": 1011, "end": 1024, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "# 2 Background\n\n**WHAT IS IT?**\nThis is the fourth edition of “Safe Pathways for\nRefugees,” <sup>3</sup> a publication series that forms part\nof an ongoing joint project between UNHCR and\nOECD to address information gaps and build\na foundation of evidence on complementary\npathways. The project began in 2018 and\ncompiles statistical information from 37 OECD\ncountries and Brazil between 2010 and 2022.\nIt focuses on the pathways of family reunification,\neducation, and labour mobility of seven\nnationalities (Afghans, Eritreans, Iranians, Iraqis,\nSyrians, Somalis, and Venezuelans); ongoing\nwork aims to expand analyses to humanitarian\nadmissions and further incorporate information\nabout named sponsorship permits. This latest\nedition provides an update including new data\nfor 2022 and some revisions to earlier figures as\npart of a continuous effort to improve the existing\nevidence base on complementary pathways.\n\n\n**WHY DO WE NEED IT?**\nThe Global Compact on Refugees (GCR), <sup>4</sup>\naffirmed in 2018, has laid out the objective\nto expand access to third country solutions\nincluding resettlement opportunities as well\nas complementary pathways for the safe\nadmission of refugees. Complementary pathways\nsupplement the refugee resettlement system\nby offering additional safe and legal admission\navenues to refugees and other persons in need\nof international protection who are outside their\ncountry of origin and are seeking opportunities\nin a third country. <sup>5</sup> Complementary pathways for\nadmission should contribute to a progressive\napproach to solutions, ensuring access to rights\nand opportunities that can help meet needs\n\n\n\nand lead to a comprehensive solution. Findings\nfrom the first round of this joint OECD-UNHCR\nproject were used to establish a global target\non complementary pathways in “The ThreeYear Strategy (2019–2021) on Resettlement\nand Complementary Pathways” (3YS), a multistakeholder, multi-sectoral blueprint on the\nprocess of the GCR objective of expanding third\ncountry solutions. <s", "output": {"entities": {"named_data": [], "descriptive_data": ["statistical information from 37 OECD\ncountries and Brazil"], "vague_data": ["new data\nfor 2022"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000620", "page": 5, "chunk": 0, "title": "Safe Pathways for Refugees IV: OECD-UNHCR study on pathways used by refugees linked to family reunification, study programmes and labour mobility between 2010 and 2022 [EN/AR]", "pdf_url": "https://reliefweb.int/attachments/5af28923-d4e7-4b35-8b2e-840c03f927c8/UNHCR-OECD%20Safe%20Pathways%20for%20Refugees%20Report%20IV.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistical information from 37 OECD\ncountries and Brazil", "label": "DESCRIPTIVE_DATA", "score": 0.6723483800888062, "start": 322, "end": 379, "probe_score": 0.9752, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "new data\nfor 2022", "label": "VAGUE_DATA", "score": 0.7296961545944214, "start": 766, "end": 783, "probe_score": 0.3448, "gold": "NON_MENTION", "gold_tier": "human-final"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|\n|CONSULTANCY SERVICES FOR SUPERVISION OF THE THREE CIVIL WORKS CONTRACTS:<br>SOROTI-DOKOLO; DOKOLO-LIRA & KAMPALA-GAYAZA-ZIROBWE|3.93|\n|DETAILED DESIGN OF UPGRADING OF 300KM FROM DISTRICT (GRAVEL) TO NATIONAL<br>(BITUMEN)|1.02|\n|FEASIBILITY AND DESIGN CONSULTANCY SERVICES FOR 600KM UPGRADING OF NATIONAL<br>ROADS TO BITUMEN|2.31|\n|CONSULTANCY SERVICES INSTITUTIONAL SUPPORT TO RAFU/ROAD AUTHORITY|2.76|\n\n\n**<u>Overall Ratings</u>**\n\n\n\nPage 1 of 8", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010411", "page": 0, "chunk": 2, "title": "Uganda - THIRD PHASE OF THE ROAD DEVELOPMENT PROGRAM : P074079 - Implementation Status Results Report : Sequence 15", "pdf_url": "https://documents.worldbank.org/curated/en/264351468781801083/pdf/P0740790ISR0Di012201101302648246479.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " <sup>'</sup> С� ' 14 �и, �� 7 .4' Е� <sup>�</sup> О\n\n\n\nW -, - Vj ��� -,} <sup>�</sup> �� v м� **�** �г� <sup>4</sup> <sup>�</sup> 41r <sup>'</sup> С� ' 14 �и, �� 7 .4' Е� <sup>�</sup> О\n\n                                                                               - -- в\n\n\n\n\n - N S r. Сб�� - 4 - <sup>�</sup> rr р�С <sup>1</sup> ' �У ы� - flS ч�� p ���к,. �� ' Л .\n\n\n```\n�\n\n```\n\n\nN Q r.'- ��С - 4 - rr р�С . �� ' �У -,v flS �ч��� p <sup>,+</sup> Э �кч�,. ���\n\nС� t - ��ггч, - ' �� ' t �� <sup>'</sup> �г + - �� r <sup>'</sup> <sup>,</sup> <sup>��</sup> <sup>st</sup>\n\n\n\n\n- ' �а� ; �� #' s`3, ��иу ` - �� <sup>п</sup> <sup>,-</sup> <sup>� �</", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019524", "page": 33, "chunk": 6, "title": "Audit Report", "pdf_url": "https://documents.worldbank.org/curated/en/881491516901691829/pdf/Audit-Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". The complete questionnaires, along with the\nconsolidated anonymized dataset, are available in\nthe <u>[UNHCR Microdata Library.](https://microdata.unhcr.org/index.php/catalog/?page=1&from=2023&to=2024&region%5B%5D=3&ps=100)</u>\n\n\n# Limitations\n\nThis analysis has several limitations that should be\nconsidered when interpreting the findings. First, due\nto sampling constraints (lack of complete sampling\nframe) and the non-probabilistic selection of\nrespondents, the results may not fully represent the\nentire Ukrainian refugee population. Additionally,\nthe choice of sampling locations may have\nintroduced a bias toward more vulnerable segments\nof the population. Variations in sampling\napproaches and data collection periods across\ncountries can also affect comparability.\n\n\nThe findings on disability, chronic illness, and\nvaccination are based on self-reports and were not\nverified against medical records, which may impact\ntheir accuracy.\n\n\nA high non-response rate was observed for\nsensitive questions related to mental health,\npsychosocial well-being, protection, income and\nexpenditure which could affect the completeness of\nthe data. Additionally, the survey results for certain\nindicators, such as infant and young child feeding\nand SRH barriers, should be interpreted with\ncaution due to the small sample size or low\nresponse rates. As a result, some indicators could\nnot be further analyzed to assess how factors such\nas gender, age, disability, or place of residence\nimpact access to health and MHPSS services.\n\n\nIt is also important to note that there were slight\ndifferences in the questionnaire across countries\nand years, such as adjustments to answer options.\nTherefore, the regional trend analysis was limited to\nquestions that were consistently used across all\nparticipating countries and years to ensure\ncomparability. Furthermore, certain indicators were\nexcluded from the regional analysis due to\ninsufficient sample size or the unavailability of data\nacross all countries.\n\n\n\n7. <u>[", "output": {"entities": {"named_data": [], "descriptive_data": ["consolidated anonymized dataset"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000004", "page": 6, "chunk": 1, "title": "NAVIGATING HEALTH AND WELL BEING CHALLENGES FOR REFUGEES FROM UKRAINE   2nd Edition", "pdf_url": "https://local/jad_paddy_docs/navigating health and well-being challenges for refugees from ukraine - 2nd edition.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "consolidated anonymized dataset", "label": "DESCRIPTIVE_DATA", "score": 0.709354817867279, "start": 46, "end": 77, "probe_score": 0.1552, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "contracts), setting the Bank’s prior review threshold at US$10 million for all contracts with a risk rating of\nsubstantial and below, declaration of mis-procurement for the misapplication of the rated criteria weightings, direct\npayment for all high value contracts, and the removal of reference to the publication in the United Nations\nDevelopment Business Online (UNDB Online). This will apply to the Upper check dam (UCD) works contract and\ntherefore its procurement is now urgent. **The Bank team will continue to monitor progress regularly and**\n**support MoWSI/PMU on these actions and any other emerging issues including organizing technical visits**\n**for specific discussions.**\n\n\n**20.** **This Aide Memoire has 8 annexes as follows:**\n\n\nAnnex 1: Overview of next steps and key agreed actions\nAnnex 2: Overview of the 10 issues from May 9, 2024, letter, status and agreed actions\nAnnex 3: Overview of main community complaints, status and agreed actions\nAnnex 4: Detailed progress by sub-component\nAnnex 5: People met during the mission\nAnnex 6: Results Framework", "output": {"entities": {"named_data": ["United Nations\nDevelopment Business Online"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002105", "page": 5, "chunk": 0, "title": "Kenya - Coastal Region Water Security and Climate Resilience Project : Implementation Support Mission - March 10 to 22, 2025", "pdf_url": "https://documents.worldbank.org/curated/en/099042925222089610/pdf/P145559-8754dc7a-23f3-4bb6-ab46-99e72c50704a.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "United Nations\nDevelopment Business Online", "label": "NAMED_DATA", "score": 0.6985815763473511, "start": 322, "end": 364, "probe_score": 0.2508, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", respectively. Regarding geography,\n\n\nfrom _Familias_ we obtain the altitude in meters, a dummy for three different degrees of\n\n\nrurality and a dummy for one of four regions. In our context, geography is important for\n\n\ntwo reasons. First, a municipality with difficult physical access will naturally enjoy less", "output": {"entities": {"named_data": ["_Familias_"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004113", "page": 10, "chunk": 1, "title": "wps4918", "pdf_url": "https://local/prwp/wps4918.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "_Familias_", "label": "NAMED_DATA", "score": 0.5151711702346802, "start": 44, "end": 54, "probe_score": 0.6585, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " foundation for democratic and sustainable local\n\n\n\ndevelopment. The Community Development Program will finance social and economic\ninfrastructure and support social capital building activities to facilitate the restoration of basic\nsocial services such as health and education and provide an incentive for teachers, health workers\nand displaced persons to return to their communities. The Rural Public Works and Shelter\nprograms will provide employment for demobilized soldiers and unemployed youth, housing for\ndisplaced persons and feeder roads to stimulate local economic activities. The innovative\nactivities including training and technical support will strengthen local government capacity to\nplan, contract, manage and sustain investments in local development and engage a wide array of\n\n\n\nstakeholders in participatory processes that contribute to sustainable local development.\n\n\n\nTargeting will be consistent with the Government's 2002-2003 National Recovery\nStrategy and the March 3, 2002 Transitional Support Strategy. Resources will be directed to (a)\nnewly accessible areas that have not received any support in more than a decade; and (b) remote\nareas that have received little, if any support from the ongoing IDA-financed CRRP or other\nsimilar projects. The results of the living standards measurement survey currently underway will\nbe available at the end of 2003 and will be used to review the validity of existing targeting\nmodalities.\n\n\nTarget Populations: Target groups include demobilized soldiers and unemployed youth,\nrefugees, IDPs, female-headed households, child laborers, orphans, primary school dropouts,\n\n\n_- 8 -_", "output": {"entities": {"named_data": [], "descriptive_data": ["living standards measurement survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000176", "page": 12, "chunk": 1, "title": "Sierra Leone - National Social Action Project", "pdf_url": "http://documents1.worldbank.org/curated/en/976421468759851028/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "living standards measurement survey", "label": "DESCRIPTIVE_DATA", "score": 0.8663687705993652, "start": 1291, "end": 1326, "probe_score": 0.7112, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "DJIBOUTI\nSchool Access and Improvement Program\n\n\n**Project Appraisal Document**\n\n\nMiddle East and North Africa Region\n\nMNSHD\n\n\n\nDate: November 17, 2000 Team Leader: Qaiser M. Khan\n\n\n\nCountry Director: Inder K. Sud Sector Director: Baudouy\nProject **ID:** P044585 Sector(s): EP - Primary Education, ES - Secondary\n\n\n\n. Education\nLending Instrument: Adaptable Program Loan <sup>(APL)</sup> Theme(s): Education; Gender and development\n\n\n\nPoverty Targeted Intervention: N\n\n\n\nProgram Fin ncing Data\n\n\n\nEstimated\nAPL Indicative Financing Plan Implementation Period (Bank FY) Borrower\n\n\n\n**IBRD** Others **Total** **COMMITMENT** **Closing**\n**US$** m % US$ m US$ m Date Date\nAPL 1 10.00 75.8 3.20 13.20 03/31/2001 06/30/2005 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\n________________ Education\n\n\n\nAPL 2 10.0 65.8 5.20 15.20 07/01/2005 06/30/2008 Republic of\n\n\n\nLoan/ Credit Djibouti\n\n\n\nCredit Ministry of\n\n\n\ni_________ ________________ Education\n\n\n\nAPL 3 10.00 41.0 14.40 24.40 07/01/2008 06/30/2011 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\nEducation\n\n\n\nTotal 30.00 22.80 52.80\nProject Financing Data Credit\nFor Loans/Credits/Others: Amount (US$m): 10.0\n\n\n\nProposed Terms: Standard Credit\n\n\n\nGrace period (years): 10 Years to maturity: 40\nCommitment fee: 0.50% (0% for FY01) Service charge: 0.75", "output": {"entities": {"named_data": ["Project Financing Data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000147", "page": 4, "chunk": 0, "title": "Rwanda - Human Resources Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/837731468759911848/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Project Financing Data", "label": "NAMED_DATA", "score": 0.5102046728134155, "start": 1106, "end": 1128, "probe_score": 0.1169, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "aged 1549) to be 6.1 %; in\nFreetown, 4% in rural areas and 4.9% nationwide. In response to the crisis, Government has developed\na multi-sector HIV/AIDS Program, which is being supported by various partners, including the Bank.\n\nEducation. Although gross primary school enrollment rose by about 7% when the government\nrecently introduced universal free primary education, low enrollment, education of children who were\nforcibly recruited during the war, and gender imbalance are still an issue (male/female pupil ration of\n165:100) and only 52% of teachers are qualified. A large number of schools were rehabilitated through\nthe IDA financed CRRP Project.\n\nRisk and Vulnerability. The biggest risk that Sierra Leone's poor face is a return to civil\nconflict, political instability and chaos in public administration that would prevent the government from\nresponding to the population's needs for food, shelter and economically productive activity. The project\nis expected to respond to this risk through investments in rehabilitation, employment, and the\nreinforcement of basic services. As conditions improve, endogenous resistance to a resurgence of\nconflict is expected to increase. However there is still a need to understand the profile of risks, identify\nhigh risk groups, define the interface between vulnerability mapping and poverty mapping, coordinate\npublic programs to reduce nsks and reinforce the coping capacity of the poor. Initially, a participatory\nassessment of risks and vulnerability will be commissioned using available and forthcoming data from\nthe living standards measurement survey (LSMS) of 2003. Risk and vulnerability concepts have already\nbeen introduced into the PRSP preparation process by including appropriate questions in the 2003\nLSMS. This should enhance the poverty diagnostic dimensions of the PRSP, and inform the\ndevelopment of strategies to ensure that poverty levels do not increase.\n\nRisk and vulnerability concepts would be introduced in the design of individual sub-projects\nselected by communities. Sub-projects would address the most common risks faced by communities,\nsuch as inadequate", "output": {"entities": {"named_data": ["2003\nLSMS"], "descriptive_data": ["living standards measurement survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000052", "page": 10, "chunk": 1, "title": "Croatia - Municipal Environmental Infrastructure Project", "pdf_url": "http://documents1.worldbank.org/curated/en/367181468770702078/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "living standards measurement survey", "label": "DESCRIPTIVE_DATA", "score": 0.672607421875, "start": 1571, "end": 1606, "probe_score": 0.9203, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2003\nLSMS", "label": "NAMED_DATA", "score": 0.6768845915794373, "start": 1760, "end": 1769, "probe_score": 0.8716, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " births|\n|Frequency|Annually|\n|Data source|Survey|\n|Methodology for Data<br>Collection|Survey|\n|Responsibility for Data<br>Collection|Third Party Monitor / PMU|\n|**Under ive years’ mortality rate (per 1000 live births) for HC**|**Under ive years’ mortality rate (per 1000 live births) for HC**|\n|Description|The probability of a child born in a specific year or period dying before reaching the age of 5 years, if subject to|\n\n\nPage 47 of 68", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000006", "page": 50, "chunk": 2, "title": "South Sudan - Health Sector Transformation Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099121123152529349/pdf/BOSIB12886229a02a1bcdc12ee681b5fe59.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "/10182/2322024/Cudzoziemcy+w+polskim+systemie+ubezpiecze%C5%84+spo%C5%82ecznych_2022.pdf/)</u> 32  According to NBP (2023), there were few respondents in this situation, and they most likely had secured other sources of income.\n\n\n28\n\n\n\n29", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 14, "chunk": 3, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".”_ <sup>_84_</sup>\n\nSource: Amnesty International, Oct 26, 2004.\n\nThe media, health care practitioners and advocacy groups are doing a good job in\ndenouncing human rights violations in DRC. But these groups have failed to indicate\nclearly and systematically that the Eastern part of the country currently lacks HIV\ndata. Thus, one can only speculate about how the atrocities are affecting the spread of\nHIV among the population. Although the fears of HIV spreading in DRC as a result of\nsystemic rape in the East are highly alarming, sweeping generalizations must be\navoided as the HIV/AIDS stigma risks marginalizing people, like IDPs, from the rest\nof society. The citations in the box above illustrate the problem. The report from the\nrecent HIV sentinel surveillance in the Eastern part of the country is needed to help us\nbetter understand and react to this horrific situation. Misleading and inaccurate\nreporting on the alarming spread of HIV in the Eastern part of DRC only risks\njeopardizing the security of IDPs.\n\n\n34", "output": {"entities": {"named_data": [], "descriptive_data": ["HIV sentinel surveillance"], "vague_data": ["HIV\ndata"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001616", "page": 33, "chunk": 1, "title": "HIV/AIDS and internally displaced persons in 8 priority countries", "pdf_url": "https://reliefweb.int/attachments/fa83ae60-19ea-39d4-8b52-7cffd15cf4c0/9C98099373994210C12571BF003628F6-unhcr-gen-30jan.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "HIV\ndata", "label": "VAGUE_DATA", "score": 0.7169383764266968, "start": 312, "end": 320, "probe_score": 0.1682, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "HIV sentinel surveillance", "label": "DESCRIPTIVE_DATA", "score": 0.7255556583404541, "start": 746, "end": 771, "probe_score": 0.7158, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "#### **1 INTRODUCTION**\n###### **1.1 Project Background**\n\n67. This document presents the VMGF for the KSEIP. It is based on the Social Assessment that was done\nfor this project in May 2018. As an ESSA and VMGF was already done for the NSNP and Cash Transfer for\nOrphans and Vulnerable Children in 2013, information has been drawn from these documents and other\nrelevant documents such as the 2018 NSNP operational monitoring reports to inform this VMGF. Thus, the\nfield work focused on VMG areas where new KSIEP activities are planned to be implemented.\n\n68. The VMGF was guided by the World Bank’s OP 4.10 and the provisions of the Constitution of Kenya\n(CoK) 2010 on Vulnerable and Marginalized Groups.\n\n69. The KSEIP triggered the OP4.10 of the World Bank, which contributes to poverty reduction and\nsustainable development. This policy is activated when it is likely that groups that meet criteria of OP 4.10\n“ _are present in, or have collective attachment to, the project area_ .” The OP4.10 <sup>2</sup> [^2: World Bank, Operational Policy (OP) 4.10 Indigenous Peoples, July 2005.] “ensures project interventions fully\nrespect the dignity, human rights, economies, and cultures of Indigenous Peoples by including measures to:\n(i) avoid potentially adverse effects on the Indigenous Peoples’ communities; or (ii) when avoidance is not\nfeasible, minimize, and mitigate, such effects; (iii) ensure that the vulnerable and marginalized people receive\nsocial and economic benefits that are culturally appropriate and gender as well as inter-generationally\ninclusive.”\n\n70. The proposed project aims to enhance access of poor and vulnerable households and strengthen\ndelivery systems for provision of social and economic inclusion services and shock responsive safety nets. The\nKSEIP proposes to (i) further strengthen social protection delivery systems, building on the existing systems", "output": {"entities": {"named_data": ["2018 NSNP operational monitoring reports"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008714", "page": 21, "chunk": 0, "title": "Kenya - Social and Economic Inclusion Project : indigenous peoples plan : Vulnerable and marginalised group framework", "pdf_url": "https://documents.worldbank.org/curated/en/151591531302091733/pdf/SFG4483-REVISED-IPP-P164654-PUBLIC-Disclosed-7-18-2018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2018 NSNP operational monitoring reports", "label": "NAMED_DATA", "score": 0.6455897688865662, "start": 393, "end": 433, "probe_score": 0.8378, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nInclusive Growth Development Policy Operation (P514383) PROGRAM DOCUMENT\n\n\nthe World Bank with timely macroeconomic data to support monitoring of macroeconomic adequacy. The World Bank\nremains committed to providing technical assistance to support timely and effective reform implementation and robust\ndata collection, monitoring, and evaluation of reform progress.\n\n\n91. **Grievance Redress.** Communities and individuals who believe that they are adversely affected by specific country\npolicies supported as Prior Actions or tranche release conditions under a World Bank Development Policy Financing may\nsubmit complaints to the responsible country authorities, appropriate local/national grievance mechanisms, or the Bank’s\nGrievance Redress Service (GRS). The GRS ensures that complaints received are promptly reviewed to address pertinent\nconcerns. Project affected communities and individuals may submit their complaint to the Bank’s independent\nAccountability Mechanism (AM). The AM houses the Inspection Panel, which determines whether harm occurred, or could\noccur, because of Bank non-compliance with its policies and procedures, and the Dispute Resolution Service, which provides\ncommunities and borrowers with the opportunity to address complaints through dispute resolution. Complaints may be\nsubmitted at any time after concerns have been brought directly to the World Bank’s attention, and Bank Management has\nbeen given an opportunity to respond. For information on how to submit complaints to the World Bank’s corporate\n[Grievance Redress Service (GRS), please visit http://www.worldbank.org/GRS. For information on how to submit complaints](https://www.worldbank.org/en/projects-operations/products-and-services/grievance-redress-service)\n[to the Bank’s Accountability Mechanism, please visit https://accountability.worldbank.org.](https://www.worldbank.org/en/programs/accountability)\n\n\n**V. SUMMARY OF", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["macroeconomic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002779", "page": 36, "chunk": 0, "title": "Ethiopia - Inclusive Growth Development Policy Operation Program", "pdf_url": "https://documents.worldbank.org/curated/en/099060226161033684/pdf/BOSIB-82b946b6-ccb3-4f15-8dbd-bd599ec938e6.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "macroeconomic data", "label": "VAGUE_DATA", "score": 0.6846814155578613, "start": 121, "end": 139, "probe_score": 0.1757, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "21\n\n\nthey have to purchase water from trucks which costs four times as high than a household connection;\nand qat consumption poses a major social, income and productivity issue.\n\n\nIn order to capture as much of the school-age population presently out of school due to the lack of\nexisting places, the project will construct additional/rehabilitate classrooms. In addition, sanitation\n\nservices will be rehabilitated, and a study will be undertaken on which sanitation services best serve\nthe area, especially in a drought-prone area, and the most cost-effective methods of implementation\nand maintenance. The project will finance a study to analyze the factors that hinder girls' attendance\nand achievement, and of the feasibility of measures to overcome them, including the issues\n\nsurrounding access to education by the poor. The problems are cross-sectoral which the project, in\nPhase I, will not address (unemployed youth, health issues, non-Djiboutian school-age population,\netc.). See Section C above for program details.\n\n\nThe IDA's regional team will discuss with Government on updating the initial 1997 poverty\n\nassessment in order to produce a better picture of the issues as they exist now. In addition, it is\nenvisaged that IDA will discuss the rising health issues with the Government and the best ways for\naddressing these problems.\n\n\n_6.2 Participatory Approach: How are key stakeholders participating in the project?_\n\n\nKey stakeholders participated in the National Educational Forum _(Etats-Generaux de l'Education)_\nwhich was held in December 1999. This included officials, teachers, parents, students, members of\nparliament and the general public. The project is based on the outcome of the conference. The new\neducation law (approved in August 2000) sets in place the conditions for broadening participation in\nDjibouti's education system. It provides for setting up school management committees with parent\n\nand community involvement. The law also provides for the creation of conditions to increase private", "output": {"entities": {"named_data": [], "descriptive_data": ["1997 poverty\n\nassessment"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000093", "page": 24, "chunk": 0, "title": "Tajikistan - Education Reform Project (LIL)", "pdf_url": "http://documents1.worldbank.org/curated/en/555901468777299385/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1997 poverty\n\nassessment", "label": "DESCRIPTIVE_DATA", "score": 0.8141470551490784, "start": 1107, "end": 1131, "probe_score": 0.6186, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\n**II.** **PROJECT DESCRIPTION**\n\n\n**A. Project Development Objective**\n\n\n**PDO Statement**\n\n\n28. **The Project Development Objectives (PDO) are to provide cash transfers and access to income generating**\n**opportunities and strengthen the National Safety Net Delivery System.** Provision of access to income generating\nopportunities will focus on investments in income generating activities (IGAs) to strengthen livelihoods opportunities\nfor improved economic welfare.\n\n\n**PDO Level Indicators**\n29. **The progress toward achievement of the PDO will be measured by the following outcome indicators:**\n\n\na) Access to income opportunities to poor and vulnerable HHs\n\n       - Beneficiaries of social safety net programs (core indicator, number)\n\n`o` Of which female\n\n`o` Of which refugees (households)\n\n`o` Of which host communities (households)\n\n       - Beneficiary and non-beneficiary households reporting satisfaction with community assets created\nthrough Labor-Intensive Public Works (LIPW) (percentage)\nb) Provide income generating opportunities to poor and vulnerable households to poor and vulnerable\n\nhouseholds\n\n       - Beneficiary households receiving economic opportunities (number)\n\n       - Eligible beneficiary households with functional income-generating investments four months after\nthe receipt of the full economic opportunities package (percentage)\nc) Strengthen the national safety net delivery system\n\n       - Project Coordination unit established and functional within MGCSW (Y/N)\n\n       - Percentage of beneficiaries paid using the integrated biometric and Management Information\nSystem (MIS)\n\n**B. Project Components**\n\n\n30. **The proposed project is a US$129million grant from the IDA, and will support four components, to be**\n**implemented over a four-year period.** Of the total financing envelop of US$129 million, US$74 million will be financed", "output": {"entities": {"named_data": ["integrated biometric and Management Information\nSystem"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 20, "chunk": 0, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "integrated biometric and Management Information\nSystem", "label": "NAMED_DATA", "score": 0.6096355319023132, "start": 1650, "end": 1704, "probe_score": 0.0155, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "</u> <u>75,107</u> <u>21</u>\n<u>Means and standard deviations are weighted by sampling weights that have been adjusted to give equal weight to each country; for literacy,</u>\nnumeracy, and problem-solving skills, mean and SD are estimated using plausible values.\n\n\n<u>Table 2. Descriptive statistics of the industry-level dataset</u>\n<u>Variable</u> <u>mean</u> <u>SD</u> <u>obs.</u> <u>countries</u>\nCog. skills per worker (literacy skills, 2nd percentile set as zero) 127.98 18.55 373 22\nOutput per worker (euros 2012) 67,820 140,618 356 21\nCapital per work (euros 2012) 471,920 1,661,381 319 19\n<u>Emissions per worker (tonnes)</u> <u>24.80</u> <u>81.74</u> <u>356</u> <u>21</u>\n\n\n13", "output": {"entities": {"named_data": [], "descriptive_data": ["industry-level dataset"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000337", "page": 14, "chunk": 1, "title": "education quality green technology and the economic impact of carbon pricing", "pdf_url": "https://local/prwp/education-quality-green-technology-and-the-economic-impact-of-carbon-pricing.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "industry-level dataset", "label": "DESCRIPTIVE_DATA", "score": 0.8951584100723267, "start": 307, "end": 329, "probe_score": 0.99, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n# Glossary List of charts and tables\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\n**GUS** - Główny Urząd Statystyczny, Polish statistical office, also known as Statistics Poland.\n**LFS** - Labour Force Survey, Eurostat labour market survey conducted by national statistical offices.\n**MSNA** - Multi-Sector Needs Assessment, a 2023 UNHCR survey of refugees from Ukraine.\n**PESEL/PESEL UKR** - Powszechny Elektroniczny System Ewidencji Ludności, Universal Electronic System for Registration of the Population.\nAn ID number of every Polish citizen. **PESEL UKR** is a version issued to Ukrainian citizens in connection with the armed conflict in the\nterritory of that country.\n**Poviat** - a middle tier of sub-central government in Poland between voivodship (province) and gmina (commune) level.\n**Pre-war Ukrainian migrants** - persons who migrated from Ukraine, primarily for economic reasons, before the full-scale Russian\ninvasion of Ukraine in February 2022.\n**SEIS** - Socio-Economic Inclusion Survey, a 2024 UNHCR survey of refugees from Ukraine as a follow-up to MSNA from the year before.\n**Ukrainian refugees** - persons fleeing Ukraine after the full-scale Russian invasion in February 2022, covered by EU's Temporary\nProtection Directive.\n**ZUS** - Zakład Ubezpieczeń Społecznych, Polish social security administration, also known as Social Insurance Institution.\n\n\n44\n\n\n\nChart 1. Poland-Ukraine border movement balance and registered/active PESEL data\b 07\nChart 2. Ukrainians registered for social insurance\b 07\nChart 3. Number of Ukrainians registered in Poland for social", "output": {"entities": {"named_data": ["Labour Force Survey", "Eurostat labour market survey", "Multi-Sector Needs Assessment", "Socio-Economic Inclusion Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 22, "chunk": 0, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Labour Force Survey", "label": "NAMED_DATA", "score": 0.5387635231018066, "start": 297, "end": 316, "probe_score": 0.9765, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Eurostat labour market survey", "label": "NAMED_DATA", "score": 0.6474771499633789, "start": 318, "end": 347, "probe_score": 0.9974, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Multi-Sector Needs Assessment", "label": "NAMED_DATA", "score": 0.6410594582557678, "start": 402, "end": 431, "probe_score": 0.8511, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Socio-Economic Inclusion Survey", "label": "NAMED_DATA", "score": 0.6588104963302612, "start": 1082, "end": 1113, "probe_score": 0.8576, "gold": "DATA_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " The revenue potential of the BRT will need to be thoroughly\nanalyzed before BRT operation bidding launch and is a major determinant in the feasibility of attracting private sector\ninvestment and participation through a PPP arrangement. The structuring of PPPs or concessions and the\nimplementation of Bank policies will require institutional capacity development. The Bank will be incorporating\nlessons learned from other BRT projects and transport-related PPPs financed by the World Bank Group to mitigate\nthese risks. As is the case for all transport projects, demand forecasting is subject to estimation error and data\nuncertainty. Since travel demand data for the Region is scarce, the Project is also supporting the update of origindestination surveys and the development of a transport demand model to help structure concession agreements. The\ninstitutional strengthening activities under Component 4 will help mitigate these risks. The Project will also provide\n\n\nPage 36 of 77", "output": {"entities": {"named_data": [], "descriptive_data": ["origindestination surveys"], "vague_data": ["travel demand data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000182", "page": 40, "chunk": 2, "title": "Brazil - Integrated Sustainable Mobility Project in the Foz do Rio Itajaí Region", "pdf_url": "https://documents1.worldbank.org/curated/en/099032624162515430/pdf/BOSIB-60d57288-4e09-4519-ae6c-ffdc0037e0b1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "travel demand data", "label": "VAGUE_DATA", "score": 0.741884171962738, "start": 642, "end": 660, "probe_score": 0.0215, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "origindestination surveys", "label": "DESCRIPTIVE_DATA", "score": 0.89009690284729, "start": 732, "end": 757, "probe_score": 0.0275, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " support the implementation of the project with regard to these technical\nitems, the following measures will be undertaken:\n\n\na. The project will finance specialized consulting firms to undertake the required technical designs, which\nwill be reviewed the by Bank. In addition, specialized road engineering consultants will be financed from\nthe loan to ensure that road works are implemented according to design standards.\n\n\nb. As data availability and data collection practices is weak in Lebanon, and given the shortcomings of\nprevious projects to establish a sustainable asset management system despite heavy investments in\nsoftware and laboratory equipment, the project will design a simple and rather basic asset management\nsystem which requires little data collection and low cost data collection techniques (visual survey of the\nroad condition, IRAP safety rating, and traffic data). The asset management system will be implemented\nin collaboration with international consultants and universities, who will also provide capacity building\nto Lebanese consultants on data collection and update methodology. The asset management system will\nbe installed within both CDR and MPWT, with IT linkages, therefore ensuring redundancy and\nsustainability. Finally, an engineer will be financed from the loan to be part of the PIU and in charge of\nthe maintenance and update of the asset management system to support CDR and MPWT staff. The\nWorld Bank will bring international experience in best practices regarding road asset management\nsystems and will mobilize resources and expertise to assess the network vulnerability and improve its\n\n\nPage 65 of 90", "output": {"entities": {"named_data": ["IRAP safety rating"], "descriptive_data": ["visual survey of the\nroad condition"], "vague_data": ["traffic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 68, "chunk": 1, "title": "Lebanon - Roads and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/210611486651815142/pdf/Lebanon-Roads-Employment-PAD-P160223-01262017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "visual survey of the\nroad condition", "label": "DESCRIPTIVE_DATA", "score": 0.9062021374702454, "start": 814, "end": 849, "probe_score": 0.2576, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "IRAP safety rating", "label": "NAMED_DATA", "score": 0.5772058963775635, "start": 851, "end": 869, "probe_score": 0.0066, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "traffic data", "label": "VAGUE_DATA", "score": 0.6931682229042053, "start": 875, "end": 887, "probe_score": 0.2222, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "u>(USh)</u>\n\n\n\n<u>Hours worked</u>\n\n\n\nper week\n\n\n\n<u>Hourly</u>\n\n\n\nwage per week wage wage per week wage\n<u>(USh)</u> <u>(Hrs.)</u> <u>(USh)</u> <u>(USh)</u> <u>(Hrs.)</u> <u>(USh)</u>\n\n<u>No schooling/below P1</u> <u>69,696</u> <u>37.8</u> <u>461</u> <u>93,970</u> <u>44.6</u> <u>527</u>\nSome primary 119,322 42.1 709 139,762 50.3 695\nPrimary completed 167,770 47.6 881 194,652 53.7 906\nSome lower secondary 182,227 55.3 824 201,804 57.1 884\nLower secondary completed 216,050 59.3 911 251,784 58.0 1,085\nSome or completed upper secondary 308,920 59.3 1,303 348,405 56.6 1,539\nPost-primary TVET 305,407 49.5 1,543 343,265 51.5 1,666\nPost-secondary TVET 353,743 48.9 1,807 456,475 49.8 2,292\nHigher/tertiary level of education 767,550 48.8 3,930 955,036 48.9 4,883\nData on educational level missing 173,136 37.8 1,145 371,596 45.1 2,060\n<u>Total</u> <u>194,926</u>", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Data on educational level missing"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 93, "chunk": 1, "title": "Uganda - Secondary Education Expansion Project", "pdf_url": "http://documents.worldbank.org/curated/en/406361595815248191/pdf/Uganda-Secondary-Education-Expansion-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data on educational level missing", "label": "VAGUE_DATA", "score": 0.6072640419006348, "start": 764, "end": 797, "probe_score": 0.2814, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "21\n\n\nOn the other hand, all industry level measures still retain significance, although the\n\n\nmagnitudes drop. The only sign reversal is that industry concentration now has no significant\n\n\nimpact on TFP. As the fixed-effect estimation holds constant the industry structure before 1994,\n\n\nthis suggests that firms in industries that have increased in concentration over the period have\n\n\ngrown as rapidly as firms in industries that have become less concentrated. <sup>15</sup> <sup>16</sup> Overall, changes\n\n\nin industry concentration are also very small, so industry concentration had a negligible impact\n\n\non TFP over the period.\n\n\nAll the other estimated industry effects support the role of competition in enhancing firm\n\n\nefficiency. Firms in industries that have higher market shares controlled by private firms,\n\n\nforeign owned firms, new entrants or import penetration had rising TFP. Industries with high\n\n\nproportions of exiters are less efficient, and so they gained efficiency on average as their least\n\n\nefficient members dropped out. The aggregated effect of the industry effects, γ **,** evaluated at the\n\n\nchange in sample means over the sample period, is 0.085 or 35% of the change in TFP over the\n\n\nperiod. These represent external benefits from market competition, independent of the impact of\n\n\nfirm-specific factors. For example, there is no evidence that a change to foreign ownership\n\n\ninfluences that firm’s productivity, but higher industry shares controlled by foreign owners make\n\n\nall firms in the industry more efficient.\n\n\nBecause current firm status has a negligible effect on TFP, the balance of the TFP effect\n\n\nis attributable to the firm fixed-effects. In essence, this represents a sorting effect. Over time,\n\n\nthe least efficient firms dropped out, while the most efficient firms remained. New entrants had\n\n\nto match the efficiency of the surviving firms in order to compete.\n\n\nWhen we redo the exercise of assessing the aggregated impact of the δ,µ, and γ using\n\n\nthe column 4 estimates", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002514", "page": 21, "chunk": 0, "title": "wps3189", "pdf_url": "https://local/prwp/wps3189.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "دة إدارة البرنامج<br>  نسخة<br> إلى<br>بالضافة<br>  نظام<br> من<br>مطبوعة<br>  المعلومات<br>تكنولوجيا<br>  للبيانات<br> اللي<br>(النظام<br> الجمركية) للتحقق من عدد<br> المدخ<br>البنود  بمعرفة<br>لة<br> الشركات وعدد عمليات<br> الفحص التي أجريت، إن<br> .وجدت<br>  ديوان<br> يؤكد<br>سوف<br> المحاسبة العدد ويجري<br> ،عمليات تحقق عشوائية<br>حسبلقتضاء، وي صدر<br> تقاريره خلل شهرين من<br> تاريخ إخطار وحدة إدارة<br>.البرنامج<br> <br> سوف تقدم وزارة التخطيط|ديوان المحاسبة|برنامج القائمة الذهبية<br> التابع لدارة خدمة<br> العملء وإدارة المخاطر<br>ال نظام التلقائي لقاعدة<br>بيانات الجمارك<br>|نعم|النتيجة المرتبطة بالصرف4<br>-<br>1<br", "output": {"entities": {"named_data": [], "descriptive_data": ["بيانات الجمارك"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000051", "page": 43, "chunk": 1, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents1.worldbank.org/curated/en/359731477935246872/pdf/108201-PAD-ARABIC-P159522.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "بيانات الجمارك", "label": "DESCRIPTIVE_DATA", "score": 0.5084899663925171, "start": 568, "end": 582, "probe_score": 0.4175, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Chapter 5\n\n\n**Unaccompanied and**\n**separated children**\n\n\nChildren separated from their parents and families\nbecause of conflict, forced displacement, or natural\ndisasters are among the most vulnerable. It is\nimperative that governments and agencies collect data\nto identify these children and assist them. However,\ndata availability on displaced unaccompanied and\nseparated children is limited, and not all countries\nreport these data, including countries with significant\nnumbers of asylum claims such as South Africa and the\nUnited States of America.\n\n\nFor the first time, UNHCR began reporting on the\nnumber of unaccompanied and separated children who\nare registered as refugees. To date, reporting has been\nonly on asylum applications, and unfortunately these\ndata are reported in only a minority of countries. While\nefforts are being made, including with partner agencies\nsuch as UNICEF, to improve data on displaced\nchildren, <sup>**62**</sup> current available data significantly\nunderestimate numbers of both asylum-seeking and\nrefugee unaccompanied and separated children.\n\n\n**Asylum applications**\n\n\nProvisional data indicated that 45,500 unaccompanied\nand separated children sought asylum on an individual\nbasis in 2017, with 67 countries reporting at least one\nsuch application. This number, while known to be an\nunderestimate due to under-reporting, was lower than in\n2016 when 75,000 were reported and in 2015 (98,400).\nNevertheless, it was more than double the 34,300\napplications from unaccompanied and separated\nchildren reported in 2014. Most applications were from\nchildren aged 15 to 17 (33,300), but a substantial minority\nof applications (12,200) were from unaccompanied and\nseparated children aged 14 or younger.\n\n\nThe number of claims from unaccompanied and\nseparated children in 2017 was the greatest in Italy with\n\n\n\n9,900 claims, a 68 per cent increase from 2016 when\n5,900 claims were registered. The number of\nunaccompanied and separated children arriving by sea\nin that country was estimated at 15,800 in 2017,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Provisional data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000669", "page": 47, "chunk": 0, "title": "Global Trends: Forced Displacement in 2017", "pdf_url": "https://reliefweb.int/attachments/629105a1-324c-3c0c-9dc4-f656aa0fe543/5b27be547.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Provisional data", "label": "VAGUE_DATA", "score": 0.5503535866737366, "start": 1112, "end": 1128, "probe_score": 0.435, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " security administration, also known as Social Insurance Institution.\n\n\n44\n\n\n\nChart 1. Poland-Ukraine border movement balance and registered/active PESEL data\b 07\nChart 2. Ukrainians registered for social insurance\b 07\nChart 3. Number of Ukrainians registered in Poland for social insurance by sex\b 08\nChart 4. Age and gender structure of Ukrainian refugees\b 09\nChart 5. Ukrainian refugee households’ demographic composition\b 10\nChart 6. Local population shares of Ukrainian refugees\b 11\nChart 7. Income of Ukrainian refugee households by source\b 12\nChart 8. Ukrainian refugee household incomes from Poland and Ukraine in 2023 and 2024\b 12\nChart 9. Ukrainian refugee labour status 15\nChart 10. Ukrainian refugee median net wage 15\nChart 11. Main occupational groups of Ukrainian refugees, pre-war Ukrainians, other foreigners,\n\nand Polish citizens registered for social insurance, Q2 2022 and Q2 2024 (civilian, non-agricultural)\b 16\nChart 12. Ukrainian refugee wages relative to Polish citizens in the same employee-cells\b 17\nChart 13. Polish citizens and Ukrainian refugees’ employment rates by age group\b 18\nChart 14. Ukrainian refugee median net wage estimates in Q2 2024\b 19\nChart 15. Ukrainian refugees wages median net wage by age group\b 20\nChart 16. Median net wages of Ukrainian refugees median net wage by sector \b 21\nChart 17. Gross domestic product growth paths with and without Ukrainian refugees\b 23\nChart 18. Over-qualification rates by citizenship\b 27\nChart 19. Tertiary education and corresponding occupational groups shares\b 28\nChart 20. Ukrainian refugees median net wages by educational attainment\b 28\nChart 21. Share of regulated professions by citizenship and legal status, Q2 2024\b 29\nChart 22. Econometric model of determinants of Ukrainian refugees’ net wages\b 32\nChart 23. Average number of months since arrival of a Ukrainian refugee by Polish language fluency\b 33\nChart 24. What Ukrainian refugee groups have weakest Polish language fluency?\b 33\nChart 25. Ukrainian refugees’ employment rate in", "output": {"entities": {"named_data": ["PESEL data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 22, "chunk": 1, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PESEL data", "label": "NAMED_DATA", "score": 0.859616756439209, "start": 148, "end": 158, "probe_score": 0.6316, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020715", "page": 19, "chunk": 1, "title": "Ethiopia - Agricultural and Industrial Development Bank (AIDB) Project", "pdf_url": "https://documents.worldbank.org/curated/en/958461468023107558/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7292463183403015, "start": 272, "end": 283, "probe_score": 0.8771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ") ............................. 17\n\n\nGraphique 7 : Stratégies habituellement utilisées pour répondre aux chocs alimentaires (JAM 2013) .......................... 19\n\n\nGraphique 8 : Répartition des ménages selon les groupes de sécurité alimentaire ..................................................... 20\n\n\nGraphique 9 : Répartition (%) des groupes des moyens d’existence selon les groupes de l’étude ................................ 24\n\n\nGraphique 10 : Pourcentage (%) des ménages réfugiés et autochtones pratiquant l’agriculture ou l’élevage. .............. 25\n\n\nGraphique 11 : Principales priorités actuelles des ménages hôtes et réfugiés enquêtés (JAM 2013) ............................ 29\n\n## LISTE DES TABLEAUX\n\n\nTableau 1 : Effectif de la population enquêtée lors les entretiens communautaires ..........................", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000948", "page": 3, "chunk": 2, "title": "Evaluation de l’assistance humanitaire et de la situation des réfugiés Centrafricains vivant au Cameroun (Juillet 2013)", "pdf_url": "https://reliefweb.int/attachments/8d1bd75b-190a-3e20-b37c-ddd3a797355d/wfp266745.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_|_Hausman test_|_Coefficient_|_Hausman test_|\n|_P90/P10_|0.53***|127.36***|0.43***|9.68|\n|_P90/P10_|[0.04]|[0.04]|[0.11]|[0.11]|\n|_P80/P20_|0.32***|133.74***|0.01|0.07|\n|_P80/P20_|[0.02]|[0.02]|[0.05]|[0.05]|\n\n\n\n_Notes:_ Robust standard errors in brackets; <sup>*</sup> _p_ < 0.10, <sup>**</sup> _p_ < 0.05, <sup>***</sup> _p_ < 0.01.\n\n_Source:_ Authors’ own elaboration using Luxembourg Income Study’s data.\na OLS regression\n\n\n\n35", "output": {"entities": {"named_data": ["Luxembourg Income Study’s data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000307", "page": 36, "chunk": 2, "title": "does gender equality in labor participation bring real equality evidence from developed and developing countries", "pdf_url": "https://local/prwp/does-gender-equality-in-labor-participation-bring-real-equality-evidence-from-developed-and-developing-countries.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Luxembourg Income Study’s data", "label": "NAMED_DATA", "score": 0.8190492391586304, "start": 378, "end": 408, "probe_score": 0.9994, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEmergency Food Security Project (P178936)\n\n\n<mark>of producing countries have recently implemented export bans or restrictions on their domestic supplies, further</mark>\n<mark>tightening global availability and adding additional upward pressure on prices.</mark> <sup>22</sup> [^22: As of April 5, 2022, 11 countries have implemented export bans, including Russia, Belarus, Hungary, Serbia, Turkey, North Macedonia,\nand Egypt, for products ranging from wheat, wheat flour, barley, rye, corn, and oilseeds, to lentils, fava beans, and pasta.] <mark>The supply and price shock caused</mark>\n<mark>by the war in Ukraine is thus rapidly changing the geopolitics and economics of trade in basic agricultural</mark>\n<mark>commodities where small buyers, like Jordan, are competing in a tight market with larger buyers and fewer</mark>\n<mark>suppliers that are geographically farther from the Middle East and North Africa (MENA) region. Sourcing options</mark>\n<mark>for Jordan are further constrained by the fact that not only price, but also quality parameters play an important</mark>\n<mark>role in the grain purchasing decisions of the GOJ. These impediments and global risk factors could severely limit</mark>\n<mark>the ability of the GOJ to manage its strategic grain reserves as the primary means to mitigate shortages or price</mark>\n<mark>fluctuations in the coming months and years.</mark>\n\n\n**16.** **The shock to global commodity markets and the uncertainty regarding future supplies and prices caused**\n**by the war in Ukraine call for the effective implementation of Jordan’s National Food Security Strategy (2021-**\n**2030).** The expected persistence of the high prices and supply risks requires a rethinking of the overall", "output": {"entities": {"named_data": ["Emergency Food Security Project"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 16, "chunk": 0, "title": "Jordan - Emergency Food Security Project", "pdf_url": "http://documents.worldbank.org/curated/en/486071652556836130/pdf/Jordan-Emergency-Food-Security-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Emergency Food Security Project", "label": "NAMED_DATA", "score": 0.5979304909706116, "start": 19, "end": 50, "probe_score": 0.2247, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " The indicator is on track, projected to meet the year-end<br>June 30, 2026 target of 9 and will be verified under APA4 by IVA.|Interim data as of March 31, 2026. The indicator is on track, projected to meet the year-end<br>June 30, 2026 target of 9 and will be verified under APA4 by IVA.|\n|GKMA sub-national entities<br>that have prepared an ISG<br>plan that includes urban<br>resilience and climate<br>change/disaster risk<br>management (Number)  DLI|0.00|Jan/2022|9|30-Sep-2025|9|31-Mar-2026|9.00|Dec/2027|\n|GKMA sub-national entities<br>that have prepared an ISG<br>plan that includes urban<br>resilience and climate<br>change/disaster risk<br>management (Number)  DLI|Comments on<br>achieving  targets|Comments on<br>achieving  targets|Interim data as of March 31, 2026. The indicator already meets the year-end June 30, 2026<br>target of 9 and will be verified under APA4 by IVA.|Interim data as of March 31, 2026. The indicator already meets the year-end June 30, 2026<br>target of 9 and will be verified under APA4 by IVA.|Interim data as of March 31, 2026. The indicator already meets the year-end June 30, 2026<br>target of 9 and will be verified under APA4 by IVA.|Interim data as of March 31, 2026. The indicator already meets the year-end June 30, 2026<br>target of 9 and will be verified under APA4 by IVA", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Interim data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002285", "page": 13, "chunk": 4, "title": "Disclosable Version of the ISR - Greater Kampala Metropolitan Area Urban Development Program - P175660 - Sequence No : 10", "pdf_url": "https://documents.worldbank.org/curated/en/099050626102530191/pdf/P175660-c056ef89-166e-4454-9538-6b51829539e2.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Interim data", "label": "VAGUE_DATA", "score": 0.5206433534622192, "start": 128, "end": 140, "probe_score": 0.9955, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Procurement Documents:** The World Bank’s Standard Procurement Documents (SPDs) shall be used for\nprocurement of goods, works, and non-consulting services under Open International Competitive Procedures. National\nBidding documents as set forth in the Public Procurement and Disposal Act, 2003 may be used under Open National\ncompetitive as well as for the Request for Quotation method subject to the inclusion of the universal eligibility and ES\nprovisions. Selection of consultant firms shall use the World Bank’s SPDs, in line with procedures described in the\nProcurement Regulations.\n\n\n37. In accordance with paragraph 5.3 of the Procurement Regulations, the request for bids/request for proposals\ndocument shall require that Bidders/Proposers submitting Bids/Proposals to present a signed acceptance at the time of\nbidding, to be incorporated in any resulting contracts, confirming application of, and compliance with, the World Bank’s\nAnti-Corruption Guidelines, including without limitation the World Bank’s right to sanction and the World Bank’s\ninspection and audit rights.\n\n\n38. **Record keeping and management.** All records pertaining to award of tenders, including bid notification, register\npertaining to sale and receipt of bids, bid opening minutes, bid evaluation reports and all correspondence pertaining to\nbid evaluation, communication sent to/with the World Bank in the process, bid securities, and approval of\ninvitation/evaluation of bids will be retained by the respective agencies in electronic or hard copy and uploaded in STEP.\n\n\n40 (a) open advertising of the procurement opportunity at the national level; (b) the procurement is open to eligible firms from any country; (c) the\nrequest for bids/request for proposals document shall require that Bidders/Proposers submitting Bids/Proposals present a signed acceptance at the\ntime of bidding, to be incorporated in any resulting contracts, confirming application of, and compliance with, the World Bank’s Anti-Corruption\nGuidelines,", "output": {"entities": {"named_data": [], "descriptive_data": ["register\npertaining to sale and receipt of bids"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000088", "page": 70, "chunk": 1, "title": "Uganda - Generating Growth Opportunities and Productivity for Women Enterprises Uganda Project", "pdf_url": "http://documents1.worldbank.org/curated/en/527091655323259747/pdf/Uganda-Generating-Growth-Opportunities-and-Productivity-for-Women-Enterprises-Uganda-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "register\npertaining to sale and receipt of bids", "label": "DESCRIPTIVE_DATA", "score": 0.544321596622467, "start": 1196, "end": 1243, "probe_score": 0.023, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*2**<br>**3**<br>**5**|**2**|Actual|Actual||Post|CQS|18-Aug-09|18-Aug-09|27-Aug-09|14-Sep-09|22-Sep-09||5-Oct-09|2-Nov-09||||||||||||\n|**MOWI**<br>**1**<br>**2**<br>**3**<br>**5**|**3**|Planned|Consultancy studies on<br>Baseline  Data survey  and<br>collection|150,000|Post|CQBS|13-Dec-08|20-Dec-08|1-Jan-09|15-Jan-09|18-May-09|25-May-09|23-May-09|20-Jun-09|4-Jul-09|11-Jul-09|11-Jul-09|18-Jul-09|25-Jul-09|8-Aug-09|N/A|8-Aug-09|15-Aug-09|22-Aug-09|3-Sep-09|\n|**MOWI**<br>**1**<br>**2**<br>**3**<br>**5**|**3**|Actual|Actual|180,610.30|Post|CQBS|17-Apr-08||19-Mar-09|3-Apr-09|15-May-09|17-May-09|2-Jun-09|29-Jun-09|9-", "output": {"entities": {"named_data": [], "descriptive_data": ["Baseline  Data survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011566", "page": 4, "chunk": 3, "title": "Kenya - Natural Resource Management Project : procurement plan", "pdf_url": "https://documents.worldbank.org/curated/en/344331468046143117/pdf/524870PROP0P091M00Procurement0Plan0.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Baseline  Data survey", "label": "DESCRIPTIVE_DATA", "score": 0.8134611248970032, "start": 220, "end": 241, "probe_score": 0.006, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "is higher is due to the exclusion of China, which has both a large population and low rate of extreme\n\n\npoverty. Nonetheless, the data in our analysis is representative of nearly 5.9 billion people or more\n\n\nthan 3/4 <sup>th</sup> of the world’s population. The coverage of people estimated to be living in extreme\n\n\npoverty, the population that is relevant for this analysis, is much larger – the data cover 98 percent\n\n\nof this population.\n\n\nFor each country, the surveys have been conducted in different years and the data are\n\n\nreported in local currency units in current prices. Following the methodology used to report on\n\n\nSDG 1.1, we convert all income and consumption data into 2011 constant local prices using\n\n\nConsumer Price Indices from each country, and then convert the resulting vector into an\n\n\ninternationally comparable US dollars using 2011 purchasing power parity exchange rates (PPPs). <sup>9</sup> [^9: For more details on the CPI series, see: <u>[https://worldbank.github.io/PIP-Methodology/convert.html#CPIs.](https://worldbank.github.io/PIP-Methodology/convert.html#CPIs)</u>\nFor more details on the PPPs, see: <u>[https://worldbank.github.io/PIP-Methodology/convert.html#PPPs .](https://worldbank.github.io/PIP-Methodology/convert.html#PPPs)</u>]\n\n\nThe CPIs are used to estimate real changes in income and consumption over time, while the PPPs\n\n\naccount for relative price differences across countries. In addition to using the same CPI and PPP\n\n\ndata as used by the World Bank for global poverty monitoring, we also use the same population\n\n\nand national accounts data. For more details on how the World Bank estimates poverty, see World\n\n\nBank (2020a).\n\n\nIn the second part of the analysis, we use", "output": {"entities": {"named_data": [], "descriptive_data": ["Consumer Price Indices", "CPI and PPP\n\n\ndata", "population\n\n\nand national accounts data"], "vague_data": ["income and consumption data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001052", "page": 10, "chunk": 0, "title": "idu0d253ce79097d604a370b4dd086b73941ff60", "pdf_url": "https://local/prwp/idu0d253ce79097d604a370b4dd086b73941ff60.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "income and consumption data", "label": "VAGUE_DATA", "score": 0.5881279110908508, "start": 654, "end": 681, "probe_score": 0.9421, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Consumer Price Indices", "label": "DESCRIPTIVE_DATA", "score": 0.5682351589202881, "start": 722, "end": 744, "probe_score": 0.7345, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "CPI and PPP\n\n\ndata", "label": "DESCRIPTIVE_DATA", "score": 0.6586686372756958, "start": 1460, "end": 1478, "probe_score": 0.7445, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "population\n\n\nand national accounts data", "label": "DESCRIPTIVE_DATA", "score": 0.8662704825401306, "start": 1557, "end": 1596, "probe_score": 0.7031, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Development Object remains relevant and the\nimplementing entities, EEU and MoWE, are well positioned to complete its implementation and achieve the expected results.\n\n\n**Data on Financial Performance**\n\n\n**Disbursements (by loan)**\n\n\nProject Loan/Credit/TF Status Currency Original Revised Cancelled Disbursed Undisbursed % Disbursed\n\n\nP160395 IDA-61570 Effective USD 125.00 125.00 0.00 35.87 89.13 29%\n\n\nP160395 IDA-61580 Effective USD 250.00 250.00 0.00 246.13 2.29 99%\n\n\n**Key Dates (by loan)**\n\n\nProject Loan/Credit/TF Status Approval Date Signing Date Effectiveness Date Orig. Closing Date Rev. Closing Date\n\n\nP160395 IDA-61570 Effective 01-Mar-2018 09-Mar-2018 07-Jun-2018 07-Jul-2023 07-Jul-2023\n\n\nP160395 IDA-61580 Effective 01-Mar-2018 09-Mar-2018 07-Jun-2018 07-Jul-2023 07-Jul-2023\n\n\n6/26/2022 Page 1 of 17", "output": {"entities": {"named_data": [], "descriptive_data": ["Data on Financial Performance"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007346", "page": 0, "chunk": 1, "title": "Disclosable Version of the ISR - Ethiopia Electrification Program (ELEAP) - P160395 - Sequence No : 09", "pdf_url": "https://documents.worldbank.org/curated/en/099715006262223343/pdf/P1603950d113c509a0851e090c2a6a2aae3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data on Financial Performance", "label": "DESCRIPTIVE_DATA", "score": 0.6551288366317749, "start": 171, "end": 200, "probe_score": 0.0047, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nTajikistan Water Supply and Sanitation Investment Project (P177325)\n\n\ndrinking water quality. The quality of drinking water sources may also be compromised by increased\nsediment and nutrient inputs due to extreme storm events. Sanitation-related public health risks tend to\nbe higher during/after the occurrence of extreme weather events such as floods and droughts, and the\nabsence of sustainable WASH solutions may further exacerbate the spread and transmission of\nwaterborne diseases. The impact of increasing temperatures on the incidence, transmission, season\nduration, and spread of diseases represents a major threat to rural communities, particularly those\naffected by heat waves. <sup>28</sup> Investments in piped water supply services to the rural areas, where wastewater\ncollection and treatment is almost nonexistent will result in an inevitable increase in volume of\nwastewater flows in the medium term, which if not considered and addressed duly may be associated\nwith the environmental and public health threats.\n\n\n16. The World Bank multi-sector rapid needs and impact assessment was conducted by the World\nBank in September 2021 to support the Government to prepare for potential influx of refugees under\ndifferent scenarios. Based on existing data and information, the impact assessment focused on Khatlon\nand GBAO provinces as locations for temporary refugee settlements. The assessment identified urgent\nand short- and medium-term needs to reduce the negative impacts of inflow on host communities and\nmaximize the positive benefits of refugee arrivals and settlement after registration. The assessment\nidentified provision of at least basic WSS services among priorities for the Khatlon and GBAO regions,\nparticularly along the border areas and high-density rural and peri-urban settlements characterized by\nlow coverage and poor quality of basic infrastructure and services (especially for children and women).\n\n\n**Sector Policy and Strategy**\n\n\n17. Recognizing the importance of water to its development agenda, Tajikistan has embarked on a\nprocess of water sector transformation in the last decade. Tajikistan’s goals and macro-strategies are laid", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["existing data and information"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000162", "page": 16, "chunk": 0, "title": "Tajikistan - Water Supply and Sanitation Investment Project", "pdf_url": "http://documents1.worldbank.org/curated/en/932351655916461178/pdf/Tajikistan-Water-Supply-and-Sanitation-Investment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "existing data and information", "label": "VAGUE_DATA", "score": 0.6771590709686279, "start": 1272, "end": 1301, "probe_score": 0.8919, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Procurement Pro<br>cess|Prequalification<br>(Y/N)|High SEA/SH R<br>isk|Procurement D<br>ocument Type|Estimated<br>Amount (U<br>S$)|Actual Am<br>ount (US$<br>)|Process St<br>atus|Planned|Actual|Planned|Actual|Planned|Actual|Planned|Actual|Planned|Actual|Planned|Actual|Planned|Actual|Planned|Actual|Planned|\n|KE-GARISSA COUNTY-20513<br>0-CW-RFB / Rehabilitation/Op<br>ening up of  Jarajara Canal In<br>take in Balambala|IDA / 59450|Component 1: Upscaling Cli<br>mate-Smart Agricultural Pra<br>ctices (US$163.8 million equ<br>ivalent, of which IDA US$150<br>.0 million eq uivalent)|Post|Request for Bids|Open - National|Single Stage - One E<br>nvelope||||223,188.80|188,858.93|Signed|||||2020-11-24|2020-12-18|2020-11-29|2021-08-27|||2021-01-10|2021-01-11|2021-02-09|2021-01-25|2021-03-16|2021-02-12|2021-07-1<br>4|\n|KE-GARISSA COUNTY-22097<br>5-CW-RFB / desilting and exp<br>ansion of afweine water pan<br>and pasture  conservation pr<br>", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007688", "page": 2, "chunk": 2, "title": "Kenya - Eastern and Southern Africa- P154784- Kenya Climate Smart Agriculture Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099855105242220253/pdf/P1547840bf133c0490b98b025ee7275d395.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " public hospitals decreased from 89 percent to 71\npercent. Results from an analysis of unmet needs over the last five years <sup>17</sup> indicate that approximately\n\n\n11 LCRP 2017-2020.\n12 UNHCR data, 2016.\n13 Hariri University Hospital data, 2017.\n14 LCRP 2017-2020.\n15 MoPH data, 2012-2015.\n16 Interview with Syndicate of Private Hospitals, Lebanon. March 2017.\n17 The analysis is based on a model that examined the change in patient proportions under the assumption that any change in\npatient proportions from one nationality comes at the expense of patients from another nationality.\n\n\nPage 15 of 54", "output": {"entities": {"named_data": ["UNHCR data", "Hariri University Hospital data", "MoPH data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000032", "page": 17, "chunk": 2, "title": "Lebanon - Health Resilience Project", "pdf_url": "http://documents.worldbank.org/curated/en/616901498701694043/pdf/Lebanon-Health-PAD-PAD2358-06152017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR data", "label": "NAMED_DATA", "score": 0.7280141115188599, "start": 190, "end": 200, "probe_score": 0.9903, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Hariri University Hospital data", "label": "NAMED_DATA", "score": 0.7673715353012085, "start": 211, "end": 242, "probe_score": 0.9924, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "MoPH data", "label": "NAMED_DATA", "score": 0.7869482636451721, "start": 272, "end": 281, "probe_score": 0.9913, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|\n\n\n\n54 The plan, according to the POM, will contain a complete overview of all activities for the coming year under the DLI 8. The plan will also specify the target areas, districts, urban centers\nand parishes, based on analysis of the needs and coverage. The plan will also specify the allocation formulas, based on quick assessment of the needs of the 7 target areas.\n55 This will clarify the land rights in the wake of pressure on land occasioned by influx of refugees. The data base will provide quick information on land ownership in case any entity needs\nto acquire land for any purpose.\n56 This will encompass, minimum mission p.a. to each target areas to ensure that the LGs mainstream the PDPs in the annual work-plans, support identification of eligible projects, and\nensure that procurement processes are conducted in accordance with the legal framework.\n\n31", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data base"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000014", "page": 38, "chunk": 2, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents1.worldbank.org/curated/en/143681526614252328/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data base", "label": "VAGUE_DATA", "score": 0.6851150393486023, "start": 478, "end": 487, "probe_score": 0.0016, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " insufficient enabling\nlegislation and resources allocated to carrying out:\n\n\n  - Pest Surveillance and monitoring\n\n  - Border control and inspections\n\n  - Expertise in risk assessment\n\n  - Diagnostic tools for early Pest, weed and disease detections\n\n  - Expertise in diagnosis (taxonomy)\n\n  - Data collection and access to information\n\n  - Tools for rapid response to entry, establishment and spread of pests and diseases\n\n**Pesticides Management** - There is limited or no budget for chemicals management in most\ngovernment ministries/agencies. Most Line Ministries have restricted themselves to policy issues\nwithout putting in place adequate structures to monitor and implement the policies they put in place.\nIn some ministries/sectors where the technical staff is available, there is inadequate funding; weak\npolicies; lack of a pesticides inventory and lack of equipment which has led to poor service delivery.\nThe capacity for regulation has not kept pace with the liberalization of the pesticides market. Just as\n\n\n13", "output": {"entities": {"named_data": [], "descriptive_data": ["pesticides inventory"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012470", "page": 29, "chunk": 1, "title": "Uganda - Multisectoral Nutrition Project : environmental assessment : Environmental and social management framework", "pdf_url": "https://documents.worldbank.org/curated/en/403941468174879369/pdf/E46850ESMF0P1400Box385383B00PUBLIC0.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "pesticides inventory", "label": "DESCRIPTIVE_DATA", "score": 0.8004924654960632, "start": 836, "end": 856, "probe_score": 0.0001, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Methodology**\nPaving pathways for inclusion: A global overview of refugee education data\n\n\nEach framework pillar will be discussed in turn below\n(see Figure 2), and it is important to keep in mind that\neach of them will have slightly different considerations\ndepending on which DCEs the report is referring to.\nFor instance, an administrative data system such as\nEMIS will have different methodological considerations\nthan a household survey, and the potential refugee\nidentification methods will also differ. Given that\ninclusion in data systems includes all data in a context,\nit is critical that a data inclusion framework allows for\nthis flexibility of approaches.\n\n\n**Methodology and inclusion by design**\n\n\nThe methodology and inclusion by design pillar of the\nframework aims to establish whether there is systematic\ninclusion of refugees in the DCE. The key point here\nis that forcibly displaced groups must deliberately be\nincluded in sample design, otherwise, any estimates\nmade from those surveys will not be statistically\nrepresentative of them. While this has implications for\nsurvey design and usually involves additional costs (as\nsample size must increase), it is the only way to ensure\nconsistent coverage of this specific population group.\nIn reviewing the extent of inclusion based on this\ndimension of the framework, there are two main areas\nof interest:\n\n\ny **Inclusion in sample frames and samples:**\n\nBy definition, census-like DCEs should include\nrefugees and provide valuable data about their\nliving conditions in the host country, including\neducation aspects, as well as provide a useful\nsample frame for other types of DCEs. Censuses,\nhowever, have limitations in terms of frequency and\nscope. Consequently, sample-based surveys could\ncontribute to refugee data inclusion if refugees are\nincluded in the sampling frame for the DCE. For\nexample, was UNHCR registration data used as a\nsampling frame for registered refugees in a given\ncountry, or do the enumeration areas included in\nthe survey cover those areas where refugees are\nlocated? This only applies to", "output": {"entities": {"named_data": ["UNHCR registration data"], "descriptive_data": ["refugee education data", "household survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000382", "page": 23, "chunk": 0, "title": "Paving pathways for inclusion: a global overview of refugee education data", "pdf_url": "https://reliefweb.int/attachments/31f00be7-0481-4224-80ce-378c049a02d4/Paving%20pathways%20for%20inclusion%20--%20a%20global%20overview%20of%20refugee%20education%20data.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "refugee education data", "label": "DESCRIPTIVE_DATA", "score": 0.5624305009841919, "start": 68, "end": 90, "probe_score": 0.7579, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "household survey", "label": "DESCRIPTIVE_DATA", "score": 0.5133077502250671, "start": 427, "end": 443, "probe_score": 0.6894, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "UNHCR registration data", "label": "NAMED_DATA", "score": 0.758009672164917, "start": 1877, "end": 1900, "probe_score": 0.7877, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Kenya National Bureau of Statistics . . KNBS KENYA **...** **o-STATI-NATIONAL**\n\n\n**III.** **The** **Senior Management** **Team**\n\n\nThe **KNBS** structure comprises six directorates as shown below. Each Directorate is\nheaded **by** a Director.\n\n\nMr Zachary Mwangi Chege has over 24 years' experience in\nthe public service. He holds a Bachelor of Arts (First Class\nHonors) from University of Nairobi and a Masters of Arts in\nEconomic Policy Management, Makerere University,\nUganda. He has expertise in official statistics, strategic\nmanagement, surveys and censuses implementation, public\npolicy analysis, budgeting, and project management,\nIamong others.\n**Mr Zachary** **Mwangi,**\n\n\n\nPrior to his current appointment as the Director General of\n**Director General** the Kenya National Bureau of Statistics **(KNBS),** he was the\n\nDirector of Macroeconomic Statistics, **KNBS,** from **2008** to\n2012. From **1991** to **2008** he worked in the mainstream civil\nservice rising to the position of Chief Economist in the then\n\nMinistry of Planning and National Development.\nHe has coordinated the preparation of various publications\nincluding, Annual Economic Survey reports, Annual\nStatistical Abstract reports, Quarterly **GDP** reports, Socio\n\nEconomic Atlas, various survey reports, Public Expenditure\nReview reports, Quarterly Budget Review reports and District\nDevelopment Plans.\n\n\nHe has attended various courses and workshops, both\nlocally and abroad, on Regional Integration, Statistical\nDevelopments, Public Expenditure Management, Financial\nProgramming and Policies, Risk Management, Quality\nManagement System, Project Management, Macroeconomic\nanalysis and modelling, among others.\n\n\n\nMr James Gatungu has a vast experience in Statistics,\nEconomics and Data Management Skills drawn from over 20\nyears of work experience with", "output": {"entities": {"named_data": ["Annual Economic Survey reports", "Socio\n\nEconomic Atlas"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008638", "page": 12, "chunk": 0, "title": "KNBS CERIFICATE 2016 2017", "pdf_url": "https://documents.worldbank.org/curated/en/147471522239494215/pdf/KNBS-CERIFICATE-2016-2017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Annual Economic Survey reports", "label": "NAMED_DATA", "score": 0.5568429827690125, "start": 1141, "end": 1171, "probe_score": 0.2044, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Socio\n\nEconomic Atlas", "label": "NAMED_DATA", "score": 0.5789583921432495, "start": 1237, "end": 1258, "probe_score": 0.0538, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " households); socioeconomic data which would be used to classify individual identities into poverty or vulnerability\ncategories through the application of PMT. Hence, the social registry supports targeting, scoring,\nselection, on-boarding, identification, and, verification processes all linked to identity. Moreover,\nthe registry eventually would allow: (a) different actors and programs to target households\naccording to their own program objectives; (b) better coordinate interventions, avoid duplication\nand save significant costs in data collection activities; and (c) improve capacity to quickly scale\nup safety net programs in face of shocks. By having a database with larger geographical\ncoverage, when crises/shocks happen, humanitarian organizations and government agencies will\nbe able to respond faster and in a more coordinated way. The social registry and business\nfunctions for the two safety net pilots will be supported by the MIS developed under this\nComponent 2 during the project. As the social registry’s use is expanded in the future, it can\npotentially de-linked from this MIS and have its own information system to facilitate flow of\ninformation between the social registry and other programs.\n\n\n30. **Payment system.** The project will support the development of a payment system for\nGovernment safety nets. The payment system would enable Government to distribute the correct\namount of benefits to the right people, at the right time, and with the right frequency, while\nminimizing transaction costs for both the program and the beneficiaries and allowing increased\ntransparency and accountability of financial transactions. The project will use a small number of\npayment agencies to provide payments to beneficiaries and the selection of payment agencies\nwill be supported by existing (or new) information outlining the various agencies and resources\navailable, their pros and cons in the project areas and humanitarian and UN agencies experience\nfor paying cash benefits in Chad. Payment agencies may be selected in each region based on the\n\n\n33", "output": {"entities": {"named_data": [], "descriptive_data": ["social registry"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000028", "page": 44, "chunk": 1, "title": "Chad - Safety Nets Project", "pdf_url": "http://documents1.worldbank.org/curated/en/221251471265217930/pdf/Project-Appraisal-Document-PAD-disclosable-version-P156479-08122016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "social registry", "label": "DESCRIPTIVE_DATA", "score": 0.521354615688324, "start": 171, "end": 186, "probe_score": 0.0118, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000147", "page": 19, "chunk": 1, "title": "Rwanda - Human Resources Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/837731468759911848/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7292463183403015, "start": 272, "end": 283, "probe_score": 0.8771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Disbursement forecast\n\n\n\nContract number\n*Contract subject\nAwardee\n*Launching date\n-Expected delivery date\n-Non objection date\n*Expected date of final delivery\n*Bidder nationality\n*Contract allocation (general account, budget, loan\ncategory, geographic area)\n*List of contracts\nManagement of financial -Standard financial statements (balance sheet;\naccounts statement of sources and uses of funds/income\nstatement, ...)\n*LACI reports for the project duration\nFixed Assets management -Inventory of Fixed Assets (type, quantity, valuation,\ndate of service, etc.)\n\n\n\nSupplier\nAccounting category ; budgetary and accounting\nallocation of fixed assets\n\n\n\nLocation\nDepreciation\n-Disposal of Fixed assets\n\n\n\n**Module** Functions\nSorting parameters Project ID and currency used\n\n                  - Fiscal years\nCurrency\nDecentralized data entry locations\n\n\n\nChart of accounts, managerial reports, geographic\nareas of intervention, etc.\n\n\n\n\n                - Books of accounts\nDonors\n\n                 - Contracts\nCategories of disbursement\nUser Management Data storage ; restitution ; correction; cleaning; etc.\n\n                - Import/export of data to other Tempro modules\n\n\n\nIt is expected that the application would be modified to differentiate the operations from the\nprojects, as well as funding sources to allow for reporting in financial and accounting terms of the\nproject objectives and activities. The concept should allow for proper monitoring of the project\nduring the life of the credit, namely: (i) chart of accounts; (ii) by category, component, and subcomponent; (iii) by geography (type of establishment, site and district); (iv) by category of\nexpenses; and (v) in local and foreign currency. Reporting of multi-level data is planned, which\n**wiU** bring about a more dynamic approach to the management of the project, and which should", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["multi-level data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000170", "page": 51, "chunk": 0, "title": "Albania - Water Supply Urgent Rehabilitation Project", "pdf_url": "http://documents1.worldbank.org/curated/en/949361468742522118/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "multi-level data", "label": "VAGUE_DATA", "score": 0.6651609539985657, "start": 1720, "end": 1736, "probe_score": 0.4661, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nLebanon Health Resilience Project (P163476)\n\n\nstate the capacity needs of the PHCCs while the contract will state the targets to be achieved,\nquality measures, and payment terms and modalities. Contracting with PHCCs will rely on the\nexisting draft contracts already used by the MoPH. To mitigate the risk of inability to attract and\nenroll beneficiaries, as well as possible fraud and errors in enrollment of beneficiaries, the\nproject will support: (i) expanding the outreach program; (ii) a timely information campaign at\nthe community level, engaging community volunteers for outreach and demand generation; and\n(iii) utilization of the existing NPTP system and individualized photo identification cards to\nensure that the project reaches the targeted poor, avoids potential enrollment errors, and\nminimizes fraud.\n\nc) **Institutional capacity for implementation and sustainability risks** are substantial and are\n\nassociated with: (i) inadequate capacity at the central and facility levels, especially for managing\nthe additional load of beneficiaries and enhanced requirements for monitoring and supervision;\n(ii) expected delays in implementation due to the time required to start the enrollment process,\nand contracting with PHCCs; and (iii) slow disbursement due to the flow of funds mechanism\nbetween the Ministry of Finance (MOF) and MoPH. _Mitigation:_ Component 3 of the project will\nstrengthen the capacity of the existing PMU. In addition, the MoPH is already undertaking\ntested measures that will be further supported by the project, including: (i) providing a lump\nsum up-front budget to PHCCs as part of their contracts to advance their implementation\nreadiness and provide flexibility to recruit additional health workers and provide training as\nneeded; (ii) completing a facility survey that will help identify needs and gaps among the PHCCs\nand hospitals to allow for targeted capacity strengthening; (iii) preparing and maintaining a\ndisbursement plan that will be based on the overall budget", "output": {"entities": {"named_data": [], "descriptive_data": ["facility survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000032", "page": 30, "chunk": 0, "title": "Lebanon - Health Resilience Project", "pdf_url": "http://documents.worldbank.org/curated/en/616901498701694043/pdf/Lebanon-Health-PAD-PAD2358-06152017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "facility survey", "label": "DESCRIPTIVE_DATA", "score": 0.9122602343559265, "start": 1810, "end": 1825, "probe_score": 0.0504, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "During my review, I observed some **inade** acies in the system; however, they are not senrous\n\n\n\nenough to withhold certification. hav detailed these inadequacies in the attachment, and\nincluded an action plan for remedy thsituation that was agreed upon with the Borrower.\n\n\n\nSigned by: _0 1_\nProcurement Specialist _\"_ i **°S** **TQI** 3 _1_ _,L_\nChristi fitAccraiT&~ Date\nProcureme taff, MNSt\n\n\n\n**Part III: Physical Monitorable Indicators and Overall Assessment**\n\nI have reviewed the project's system for monitoring physical implementation progress, including\nits monitorable indicators for major outputs. In my view, the system cannot provide the\nappropriate data on physical progress (PMR-Section 2) required by IDA.\n\nDuring my review, I observed some inadequacies in the system; however, they are not serious\nenough to withhold certification. I have detailed these inadequacies in the attachment, and\nincluded an action plan for remedying the situation that was agreed upon with the Borrower.\n\nSigned by: i A\n### Task Team Leader 1/ 4 -L- UJ 2, dO\n\nQaiser Khan, MNSHD Date\n\n\n**Part** IV: **Concurrence of** LOA for Eligibility of Project for PMR-Based Disbursements\n\n\nI have conducted a reasonable review of the process followed by the Task Team in assessing the\nproject, and I concur with its recommendation that this project is not eligible for PMR-Based\nDisbursements.\n\nSigned by: C____ __a _\nFMS-LOAADO Andrina Ambrose, LOAEL Date\n\n\nT.\n\n\nThu-Ha Nguyen, LOAEL Date", "output": {"entities": {"named_data": [], "descriptive_data": ["data on physical progress"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008350", "page": 55, "chunk": 0, "title": "Kenya - Emergency Power Supply Project", "pdf_url": "https://documents.worldbank.org/curated/en/129181468774950902/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on physical progress", "label": "DESCRIPTIVE_DATA", "score": 0.6098982691764832, "start": 665, "end": 690, "probe_score": 0.023, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Beneficiary Selection Process**\n\n\n**Stage One: District** Districts allocated funds based on their percentage of total damage across the **8** project dlstncts\n\n\n\n**Stage Two:** **Village**\n**Selection and Division**\n**Allocations** (Prior to\nProject effectiveness)\n\n\n**Stage Three**\n**Damage assessment**\n**and Social Verification**\n**Survey**\n(Months 1 **&2)**\n\n\n**Stage Four: Ranking**\n**Of beneficiaries**\n(Month 3 of phase)\n\n\n\n~~ ~ ~\n1. Villages in each division rated based on the following criteria:\n**1** Number of housing units damageddestroyed\n\n\n\n**1**\n\n**1** .\n\n\n\nNumber of housing units damageddestroyed in Divisiodvillage.\nNumber of returnees in Divisiodvillage.\nAvailable vulnerability/poverty maps or data.\n\n\n\n4\n\n\n\n**a** Mine clearance certification.\n\n\n\n2. Villages selected for participation, based on the above rating, taking into account ethnic sensitivities\n3. Number of grants per village allocated based on damage and retumees\n\n\n\n1 I\n\n\n\n1. Damage Assessment and Social Verification Survey done in selected villages by an assessment team\nconsisting of a Divisional technical officer, VRC member, NGO/CBO representative led by village\nheadmad-woman (Grama Niladari representative)\nBeneficiary has to meet ALL the following four conditions to be considered for the housing assistance:\n\n\n\n1.\n2.\n3.\n**4.**\n\n\n\nThe beneficiary including major breadwinner i s settled in the village.\nThe beneficiary possesses a formal right to the land on which the reconstruction is proposed..\nThe beneficiary possesses only one house and it is fully or partly damaged.\nFamily income of the beneficiary is less than Rs. 2,SOOimonth.\n\n\n\n2. Prioritization o f", "output": {"entities": {"named_data": ["Damage Assessment and Social Verification Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000115", "page": 42, "chunk": 0, "title": "Sri Lanka - North East Housing Reconstruction Program", "pdf_url": "http://documents1.worldbank.org/curated/en/672131468763807868/pdf/304360LK.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Damage Assessment and Social Verification Survey", "label": "NAMED_DATA", "score": 0.791977047920227, "start": 963, "end": 1011, "probe_score": 0.8598, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "## Inflation Dynamics and Global Value Chains\n\nFrançois de Soyres & Sebastian Franco\n\nWorld Bank <sup>_∗_</sup>\n\n\nKeywords: inflation synchronization, global value chains.\n\nJEL classification: E16, E31, F1, F14, F15, F42, F62.\n\n\n_∗_ This is a background paper for the World Bank’s World Development Report 2020 \"Global Value\n\nChains: Trading for Development\". We thank the WDR 2020 team for their comments. The views\n\nexpressed in this paper are solely those of the authors and do not necessarily reflect those of the World\n\nBank.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001704", "page": 2, "chunk": 0, "title": "inflation dynamics and global value chains", "pdf_url": "https://local/prwp/inflation-dynamics-and-global-value-chains.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "65. No Designated Account will be opened for this project. A Blanket Commitment will be\nset up for WFP and FAO for the full amount to be transferred to each UN agency as an Advance.\nThe Grant will finance 100 percent of eligible expenditures of the project, inclusive of taxes.\n\n\n66. On August 22, 2014, the Financial Management Operation Review Committee approved\nthe Request for Elimination of Audit Requirements for the proposed emergency project,\ncoordinated by the EAPSP, as part of project preparation. Alternative mechanisms (detailed in\nthe request) will be put in place to support the elimination of the Bank’s audit requirements,\nhowever. First, at least two field-based visits will be conducted during the first 12 months of the\nproject implementation period. The supervision intensity will be adjusted over time, taking into\naccount the project’s financial management performance and financial management risk level.\nSecond, the Government of Chad will have the entire responsibility to ensure during the project\nimplementation period that goods and services are delivered effectively to the beneficiaries.\nWhere deemed appropriate, however—for example, if the UN agencies’ systems or periodic\nreports have showed some weaknesses or deficiencies—the Bank team may request the\ngovernment to institute arrangements to physically inspect works, goods, and services delivered\nby WFP and FAO.\n\n\n**D.** **Procurement**\n\n67. **_Guidelines._** Procurement for the proposed project will be carried out in accordance with\nthe World Bank “Guidelines: Procurement of Goods, Works, and Non-Consulting Services under\nIBRD Loans and IDA Credits and Grants by World Bank Borrowers,” dated January, 2011, and\n“Guidelines: Selection and Employment of Consultants under IBRD Loans and IDA Credit and\nGrants by World Bank Borrowers,” dated January, 2011, and the provisions stipulated in the\nLegal Agreement. Contract awards will also be published in UNDB, in accordance with the\nBank’s Procurement Guidelines", "output": {"entities": {"named_data": ["UNDB"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000007", "page": 27, "chunk": 0, "title": "Chad - Emergency Food and Livestock Crisis Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/179061468215115488/pdf/PAD11010PAD0P1010Box385329B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNDB", "label": "NAMED_DATA", "score": 0.6660885810852051, "start": 1943, "end": 1947, "probe_score": 0.4866, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Col1|Col2|Table A.1 – continued from previous page|Col4|Col5|\n|---|---|---|---|---|\n|**No**|**Article**|**Publication**|**Sectors**|**# Est.**|\n|168<br>169<br>170<br>171<br>172<br>173<br>174<br>175<br>176<br>177<br>178<br>179<br>180<br>181<br>182<br>183<br>184<br>185<br>186<br>187<br>188<br>189<br>190<br>191<br>192<br>193<br>194<br>195<br>196<br>197<br>198<br>199<br>200<br>201<br>202<br>203<br>204<br>205<br>206<br>207<br>208<br>209<br>210|Matilde et al. (1993)<br>Matilde et al. (1994)<br>Mensah (2018)<br>Michaels (2008)<br>Mizutani & Tanaka (2010)<br>Molinder et al. (2021)<br>Moreno & Lopez-Bazo (2007)<br>Moreno et al. (1997)<br>Moreno-Monroy & Ramos (2021)<br>Morten & Oliveira (2018)<br>Munnell (1990)<br>Naaraayanan & Wolfenzon (2019)<br>Nakamura et al", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001426", "page": 43, "chunk": 0, "title": "idu18a9d8af41f7d51487e1837218744c048b215", "pdf_url": "https://local/prwp/idu18a9d8af41f7d51487e1837218744c048b215.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Refugees in Turkey. Livelihoods Survey Findings._ Ankara: Turk Kizilay\nand World Food Programme.\n7 World Bank and World Food Programme. 2019. _Vulnerability and Protection of Refugees in Turkey: Findings from the Rollout of_\n_the Largest Humanitarian Cash Assistance Program in the World_ . Washington, DC: World Bank and World Food Programme.\n8 Enterprise Surveys (database), International Finance Corporation and World Bank, Washington, DC,\nhttps://www.enterprisesurveys.org/.\n9 Enterprise Surveys (database), International Finance Corporation and World Bank, Washington, DC.,\nhttps://www.enterprisesurveys.org/.\n10 Ayyagari, M., A. Demirgüç-Kunt, and V. Maksimovic. 2011. “Small vs. Young Firms Across the World: Contribution to\nEmployment, Job Creation, and Growth.” Policy Research Working Paper 5631, World Bank, Washington, DC.\n11 World Bank. 2014. _Turkey’s Transitions: Integration, Inclusion, Institutions_ . Report 90509-TR. Washington, DC: World Bank.\n12 World Bank 2014 and 2018 data of the Survey on the Access to Finance of Enterprises (database), European Central Bank,\nFrankfurt, https://www.ecb.europa.eu/stats/ecb_surveys/safe/html/index.en.html.\n\n\nPage 11 of 86", "output": {"entities": {"named_data": ["Enterprise Surveys (database)"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000025", "page": 15, "chunk": 2, "title": "Turkey - Formal Employment Creation Project", "pdf_url": "http://documents1.worldbank.org/curated/en/211181585965751622/pdf/Turkey-Formal-Employment-Creation-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Enterprise Surveys (database)", "label": "NAMED_DATA", "score": 0.5901848673820496, "start": 346, "end": 375, "probe_score": 0.186, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|ET-AFAR BWIE-211248-GO-R<br>FB / Procurement of supply a<br>nd installation of solar pumps<br>, panels with accessories, wel<br>lhead fittings, and fencing for<br>Hugub,Ferahte,Medereli,Bad<br>a Erimli & Korolita RPSs. By A<br>far Bureau of Water, Irrigatio<br>n, and Energy.|IDA / 64450|Rural Water Supply, Sanitati<br>on, and Hygiene (Rural WAS<br>H)|Post|Request for Bids|Open - National|Single Stage - One E<br>nvelope|Col8|307,000.00|0.00|Under Imple<br>mentation|Col12|Col13|Col14|Col15|2021-06-15|2021-06-15|2021-06-22|2021-07-09|Col20|Col21|2021-07-22|2021-08-12|2021-08-12|2021-10-08|2021-09-16|Col27|2022-02-13|Col29|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n|ET-AFAR BWIE-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000061", "page": 4, "chunk": 0, "title": "Ethiopia - EASTERN AND SOUTHERN AFRICA- P167794- One WASH?Consolidated Water Supply, Sanitation, and Hygiene Account Project (One WASH?CWA) - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099010424081022809/pdf/P16779410bb22f0fe1bf15174da8cb9dcd5.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Service Delivery (LGMSD)**\n\n\n    - **DLI 5** : Strengthening LGMSD and improving the weakest performing LGs was measured by a combined average\nperformance assessment score. The Independent Verification Agent (IVA) reported achievement across all\nassessment areas, unlocking USD 7 million.\n**Result Area 4: Improvement in the Effectiveness and Efficiency of Service Delivery**\n\n\n    - **DLI 6** : Service delivery performance was strengthened, and the IVA reported this DLI as achieved, unlocking a\ntotal of USD 14 million.\n\n\n**4.** **DATA ON FINANCIAL PERFORMANCE**\n\n\n**4.1** **Disbursements (by loan)**\n\n\nLoan/Credit/TF Status Original Revised Cancelled Disbursed Undisbursed % Disbursed\n\n\n**4.2** **Key Dates (by loan)**\n\n\nApr 19, 2025 Page 2 of 35", "output": {"entities": {"named_data": ["DATA ON FINANCIAL PERFORMANCE"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001919", "page": 1, "chunk": 1, "title": "Disclosable Version of the ISR - Uganda Intergovernmental Fiscal Transfers Program - P160250 - Sequence No : 8", "pdf_url": "https://documents.worldbank.org/curated/en/099041925040522847/pdf/P160250-9c3f99ff-441e-4caf-9d6c-19c432a2da8c.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "DATA ON FINANCIAL PERFORMANCE", "label": "NAMED_DATA", "score": 0.5001603364944458, "start": 535, "end": 564, "probe_score": 0.0001, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on social development issues"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012636", "page": 24, "chunk": 0, "title": "Kenya - Second Smallholders Agricultural Credit Project", "pdf_url": "https://documents.worldbank.org/curated/en/413331468915119430/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on social development issues", "label": "VAGUE_DATA", "score": 0.581004798412323, "start": 1670, "end": 1703, "probe_score": 0.333, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "up>terms of numbers</sup> <sup>of</sup>\ntemporary and permanent jobs created, <sup>progress</sup> <sup>made toward</sup> <sup>the eventual devolution</sup> <sup>of this program</sup> <sup>to</sup>\nlocal government authorities, maintenance of <sup>works,</sup> <sup>and recurrent</sup> <sup>cost financing implications.</sup> <sup>Draft</sup>\nterms of reference for the recruitment of <sup>one</sup> <sup>or more</sup> <sup>implementing</sup> <sup>partners to carry</sup> <sup>out this program,</sup> <sup>as</sup>\n\nwell as a draft contract and letter of invitation <sup>have</sup> <sup>been agreed</sup> <sup>upon.</sup>\n\n\n**Project Component** **3 -** **US$** **10.00** **million**\n\n\n**Project Management and Innovative** **Activities.**\n\nThis component would support NaCSA's efforts <sup>to coordinate,</sup> <sup>plan, monitor,</sup> <sup>program,</sup> <sup>and</sup>\nsupervise a wide range of community <sup>driven</sup> <sup>and</sup> <sup>poverty</sup> <", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017249", "page": 35, "chunk": 3, "title": "Uganda - Private Sector Competitiveness Project", "pdf_url": "https://documents.worldbank.org/curated/en/723671468308969806/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "The current study aims to build on this literature by comparing the links between conflict, forced\ndisplacement and IPV in two different conflict-affected settings: Colombia and Liberia. Both\ncountries have faced long-running civil conflict and high levels of societal violence. This paper\ndraws on the availability of Demographic and Health Survey (DHS) data, which provides\npopulation-based data on health outcomes in countries around the globe. Unique to Colombia\nand Liberia, however, is the fact that the DHS collected data on internal displacement in addition\nto information about exposure to IPV. The 2007 data from Liberia was collected four years postconflict and can provide insight into the long-term impact of displacement on women. Similarly,\n2010 data from Colombia gives insight into displacement and IPV during the ongoing\nColombian conflict. The availability of this data for two conflict-affected countries allows for a\nunique comparative analysis. The analysis of experiences of IPV after conflict exposes the longterm impacts conflict has on the lives of women and calls us to include these experiences in our\ndevelopment programming to support peace and state building.\n\nIn both countries, conflict has led to high levels of forced displacement. During Liberia’s two\nconsecutive civil wars between 1998 and 2003, around 1.4 million people were forced to flee\ntheir homes (Global IDP Project, 2003). Colombia, a more populous country, has seen roughly\n15 percent of its population displaced between 1995 and 2018 (IDMC, 2019). At the same time,\nboth countries have also experienced some success in establishing peace agreements and\nundertaking subsequent social programs to aid the implementation of the agreements and\ndemobilization efforts. Both Liberia and Colombia also present a unique opportunity to examine\nthe links between IPV and displacement because each contains unique data from the DHS not\nreadily available from other countries- namely, information about displacement as a result of\nconflict. Below, we examine the literature on the drivers of IPV in conflict and displacement\nsettings, followed by a detailed", "output": {"entities": {"named_data": ["Demographic and Health Survey"], "descriptive_data": ["2007 data from Liberia", "2010 data from Colombia"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002278", "page": 4, "chunk": 0, "title": "the risk that travels with you links between forced displacement conflict and intimate partner violence in colombia and liberia", "pdf_url": "https://local/prwp/the-risk-that-travels-with-you-links-between-forced-displacement-conflict-and-intimate-partner-violence-in-colombia-and-liberia.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Demographic and Health Survey", "label": "NAMED_DATA", "score": 0.850991427898407, "start": 319, "end": 348, "probe_score": 0.9718, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2007 data from Liberia", "label": "DESCRIPTIVE_DATA", "score": 0.787733256816864, "start": 608, "end": 630, "probe_score": 0.87, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2010 data from Colombia", "label": "DESCRIPTIVE_DATA", "score": 0.7830317616462708, "start": 756, "end": 779, "probe_score": 0.5507, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "ities applicable for the project.**\nThe Annual Workplan and Budget (AWPB) of the project will be prepared by the SDD following the Government budget\nprocess and will require approval by the World Bank. The project will be identifiable through a separate budget code. The\nproject will use the Government IFMIS for budgeting, funds flows, payments, and reporting. The project will update the\nFM Manual from KDSP I and will use it to guide the FM aspects of the project under the overall purview of the PFM Act\nand regulations. In addition, the internal audit unit of the SDD will incorporate the project in its annual work plan and\nreview the project regularly. The project will also submit quarterly financial reports to the World Bank within 45 days of\nthe quarter end. The project will be audited by the OAG annually and the report will be submitted to the World Bank\nwithin 6 months of the year end. The SDD will take timely action on all audit report findings.\n\n\n25. **The Designated Account of the project will be managed by the SDD.** The SDD will be required to open a\nsegregated foreign currency Designated Account with the CBK, which will be managed by the NT through which funds\nfrom the World Bank shall be deposited. It will also open a segregated local currency PA in the CBK through which eligible\npayments will be made. SDD with advice from the NT will discuss with the implementing agencies on agreeable mechanism\nfor funds flow but the overall fiduciary responsibility remains with SDD. <sup>20</sup> [^20: The necessary fiduciary and procurement reviews will be conducted to inform this process and any institutional strengthening activities be\nincluded in the PAP.] Other national-level agencies will have all their\nplanned activities funded and payment made from the PA at the SDD without funds being transferred. Once agreement is\nreached by the NT, SDD, and CoG, the Program will adopt any changes to funds flow and disbursement arrangements for\nfunding to CoG. Details of disbursement modalities and requirements will", "output": {"entities": {"named_data": ["Government IFMIS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005140", "page": 26, "chunk": 1, "title": "Kenya - Second Devolution Support Program Project", "pdf_url": "https://documents.worldbank.org/curated/en/099111723103091275/pdf/BOSIB-f3efc82c-63ed-42bc-950a-9372bebec063.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Government IFMIS", "label": "NAMED_DATA", "score": 0.661499559879303, "start": 292, "end": 308, "probe_score": 0.2495, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "###### Who are included in UNHCR statistics?\n\n\n\n<mark>Refugees</mark> include individuals recognized under the\n1951 Convention relating to the Status of Refugees, its 1967\nProtocol, the 1969 Organization of African Unity (OAU)\nConvention Governing the Specific Aspects of Refugee\nProblems in Africa, those recognized in accordance with\nthe UNHCR Statute, individuals granted complementary\nforms of protection, <sup>(1)</sup> and those enjoying temporary\nprotection <sup>(2)</sup> . The refugee population also includes\npersons in refugee-like situations. <sup>(3)</sup>\n\n\n<mark>Asylum-seekers (with ‘pending cases’)</mark> are\nindividuals who have sought international protection\nand whose claims for refugee status have not yet been\ndetermined. Those covered in this report refer to\nclaimants whose individual applications were pending\nas at 30 June 2015, irrespective of when those claims\nmay have been lodged.\n\n\n<mark>Internally displaced persons (IDPs)</mark> are persons\nor groups of persons who have been forced to leave\ntheir homes or places of habitual residence, in particular\nas a result of, or in order to avoid the effects of armed\nconflict, situations of generalized violence, violations\nof human rights, or natural or man-made disasters, and\nwho have not crossed an international border. <sup>(4)</sup> For the\npurposes of UNHCR’s statistics, this population only\nincludes conflict-generated IDPs to whom the Office\nextends protection and/or assistance. The IDP population\nalso includes persons in an IDP-like situation. <sup>(5)</sup>\n\n\n<mark>Returned IDPs</mark> refers to those IDPs who were\nbeneficiaries of UNHCR’s protection and assistance\nactivities, and who returned to their area of origin or\nhabitual", "output": {"entities": {"named_data": [], "descriptive_data": ["UNHCR statistics"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000912", "page": 27, "chunk": 0, "title": "UNHCR Mid-Year Trends 2015 [EN/AR]", "pdf_url": "https://reliefweb.int/attachments/872bd683-cdf1-3536-99be-b0b8568e0569/2015-12-18_MYT_web_EMBARGOED.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR statistics", "label": "DESCRIPTIVE_DATA", "score": 0.5986561179161072, "start": 27, "end": 43, "probe_score": 0.9863, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**2**\n\n\n\n**Myth:**\n\n\nMost refugees want to be resettled.\n\n\n**Truth:**\n\n\nMost refugees want to return home. They want to live in their country\nin peace and safety. For those who cannot go home, UNHCR works with\n\nStates and NGOs to protect them and their families. Resettlement is for\n\nrefugees who have no other solution.\n\n\nnot wants.\n\nResettlement is about needs,\n\n\nUNHCR Projected Global Resettlement Needs 2011", "output": {"entities": {"named_data": ["UNHCR Projected Global Resettlement Needs 2011"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000480", "page": 3, "chunk": 0, "title": "UNHCR Projected Global Resettlement Needs 2011: Including Overview of UNHCR Resettlement Achievements in 2009, Operational Challenges and Strategic Directions for 2010-2011", "pdf_url": "https://reliefweb.int/attachments/449d854c-7f39-3307-82e8-ec7205bc277b/43BAF719A848B0B8C1257757004486ED-UNHCR_Jul2010.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR Projected Global Resettlement Needs 2011", "label": "NAMED_DATA", "score": 0.6960073709487915, "start": 366, "end": 412, "probe_score": 0.9623, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["M&E data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011866", "page": 29, "chunk": 2, "title": "Uganda - Bujagali Hydropower Project : environmental assessment (Vol. 4 of 5) : Environmental impact statement", "pdf_url": "https://documents.worldbank.org/curated/en/363601468111532138/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "M&E data", "label": "VAGUE_DATA", "score": 0.5883201956748962, "start": 530, "end": 538, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "d) Support to LGs in the LGs/communities hosting refugee for improved planning, land tenure security\n\n\n\nand infrastructure investments to benefit both refugees and host communities: **US$60 million.**\n\nThe table provides the summary of the funds allocation under the three investments areas (a) – (c) above\nwhich will be funded under the Program.\n\n**Table 6:** **USMID AF Disbursement Projections over 5-year Period**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|No|Description|Total<br>funding<br>(US$ mn)|% of<br>total<br>funding|Project Disbursements (US$ millions)|Col6|Col7|Col8|Col9|\n|---|---|---|---|---|---|---|---|---|\n|**No**|**Description**|**Total**<br>**funding**<br>**(US$ mn)**|**% **<br>**of**<br>**total**<br>**funding**|**Year 1**<br>**FY18/19**|**Year 2**<br>**FY19/20**|**Year 3**<br>**FY20/21**|**Year 4**<br>**FY21/22**|**Year 5**<br>**FY22/23**|\n|**_A. _**<br>**_Funds for Infrastructure Development in Local Governments_**|**_A. _**<br>*", "output": {"entities": {"named_data": ["USMID AF Disbursement Projections"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000006", "page": 23, "chunk": 0, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents.worldbank.org/curated/en/143681526614252328/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "USMID AF Disbursement Projections", "label": "NAMED_DATA", "score": 0.6539468169212341, "start": 363, "end": 396, "probe_score": 0.1247, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000041", "page": 62, "chunk": 2, "title": "Jordan - Community Infrastructure Project", "pdf_url": "http://documents1.worldbank.org/curated/en/294581468773394111/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "The Costs of Fuelling Humanitarian Aid\n\n## **Preface**\n\n\nThe Moving Energy Initiative (MEI) is an international consortium seeking to sustainably\nincrease access to energy for displaced people and to improve how energy is dealt with in\nhumanitarian situations. It was formally inaugurated in 2015 as a partnership between Energy\n4 Impact, Practical Action, the UN Refugee Agency (UNHCR), the Norwegian Refugee Council\nand Chatham House. Funding for this publication, and for the wider activities of the MEI, has\ncome from the UK Department for International Development (DFID).\n\n\nWhen the MEI published the report _Heat, Light and Power for Refugees_ in 2015, the consortium\nfelt it had addressed a fundamental gap in analysis about energy needs in humanitarian settings.\nThis was the first publication that attempted to establish the amount of energy used by forcibly\ndisplaced people around the world and the amount that they paid for it. Since then, much\nhas been achieved. The consortium is actively enabling market-based energy provision, and\nimproving energy access in refugee camps in Burkina Faso and Kenya, as well as in areas\naffected by large-scale migration in northern Jordan. This work – and the ‘learning by doing’\nthat is fundamental to this process – remains the central piece of the MEI.\n\n\nHowever, a fundamental area of concern – energy use by humanitarian agencies themselves –\nwas not analysed extensively in the original MEI research. Our initial publication had intended\nto cover the energy use of refugees and the agencies that served them, but the data on the latter\nwere too patchy to generate meaningful projections. This publication addresses that shortcoming\nby focusing on survey data from our three focus countries. While a global estimate is still out\nof reach until data collection and standardization improve, we hope that this study advances\nunderstanding not only of the problem of diesel dependency but also of the potential solutions.\nThe aim of this paper is to help humanitarian agencies understand their use of, and spending\non", "output": {"entities": {"named_data": [], "descriptive_data": ["survey data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000796", "page": 3, "chunk": 0, "title": "The Costs of Fuelling Humanitarian Aid", "pdf_url": "https://reliefweb.int/attachments/7516c1a4-d5d8-3887-9afb-b9d2548a069e/2018-12-10-Costs-Humanitarian-Aid2.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "DESCRIPTIVE_DATA", "score": 0.6516262888908386, "start": 1703, "end": 1714, "probe_score": 0.3565, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 21\nNo. of School age children 3760 2.11 1.06 1 7\nAge of Head 3760 49.16 13.17 18 110\nHead female 3760 0.12 0.32 0 1\nHead Muslim 3760 0.86 0.35 0 1\nHead's education secondary or above 3760 0.33 0.47 0 1\n<u>Head's occupation (professional=1)</u> <u>3760</u> <u>0.09</u> <u>0.28</u> <u>0</u> <u>1</u>\n\n\nData Source: National Household Survey on Corruption (NHSC), 2010", "output": {"entities": {"named_data": ["National Household Survey on Corruption"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005798", "page": 54, "chunk": 1, "title": "wps6671", "pdf_url": "https://local/prwp/wps6671.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "National Household Survey on Corruption", "label": "NAMED_DATA", "score": 0.9089929461479187, "start": 314, "end": 353, "probe_score": 0.9893, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "X\n###### Who are included in the statistics?\n\n\n\n**Refugees** include individuals\nrecognized under the 1951\nConvention relating to the Status\nof Refugees; its 1967 Protocol; the\n1969 OAU Convention Governing\nthe Specific Aspects of Refugee\nProblems in Africa; those\nrecognized in accordance with\nthe UNHCR Statute; individuals\ngranted complementary forms of\nprotection; <sup>**(38)**</sup> or, those enjoying\ntemporary protection. <sup>**(39)**</sup> The\nrefugee population also includes\npeople in a refugee-like situation. <sup>**(40)**</sup>\n\n\n**Internally displaced persons**\nare people or groups of individuals\nwho have been forced to leave\ntheir homes or places of habitual\nresidence, in particular as a result\nof, or in order to avoid the effects\nof armed conflict, situations of\ngeneralized violence, violations of\nhuman rights, or natural/humanmade disasters, and who have not\ncrossed an international border. <sup>**(41)**</sup>\nFor purposes of UNHCR’s statistics,\nthis population only includes\nconflict-generated IDPs to whom\nthe Office extends protection and/\nor assistance. The IDP population\nalso includes people in an IDP-like\nsituation. <sup>**(42)**</sup>\n\n\n**Asylum-seekers** are individuals\nwho have sought international\nprotection and whose claims for\nrefugee status have not yet been\ndetermined. Those covered in\n\n\n\nthis report refer to claimants\nwhose individual applications\nwere pending at the end of 2010,\nirrespective of when they may have\nbeen lodged.\n\n\n**Stateless persons** are individuals\ndefined under international law as\npersons who are not considered as\nnationals by any State under the\noperation of its law. In other words,\nthey do not possess the nationality\nof any State.", "output": {"entities": {"named_data": ["UNHCR’s statistics"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000915", "page": 18, "chunk": 0, "title": "UNHCR Global Trends 2010", "pdf_url": "https://reliefweb.int/attachments/87c9610a-752f-3553-862d-f771e53bb7f4/4dfa11499.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR’s statistics", "label": "NAMED_DATA", "score": 0.6416768431663513, "start": 953, "end": 971, "probe_score": 0.9816, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Table 4.1: The Prosperity Gap in 2019 – By Regions, by Income Groups, and for Selected**\n**Countries**\n\n\n\n**Prosperity Gap,**\n**Multiple by Which**\n**Income Must Increase**\n\n\n\n**Share of Population**\n\n**below Prosperity**\n\n**Threshold, %**\n\n\n\n**Millions of People**\n\n**below Prosperity**\n\n**Threshold**\n\n\n\nLow income 12.4 99.2 663\nLower middle income 6.8 98.3 2,864\nUpper middle income 3.1 85.9 2,463\nHigh income 0.9 18.9 234\nEast Asia & Pacific 3.2 90.0 1,893\nEurope & Central Asia 2.5 75.5 374\nLatin America & Caribbean 3.5 81.1 521\nMiddle East & North Africa 5.0 93.8 370\nSouth Asia 6.7 99.1 1,820\nSub-Saharan Africa 11.4 98.8 1,094\nRest of the world 0.8 13.9 153\nBurkina Faso 9.3 98.1 20\nBangladesh 6.5 99.4 162\nBolivia 2.5 76.3 9\nBrazil 3.6 77.7 164\nChina 2.8 88.5 1,246\nColombia 4.2 85.8 43\nGermany 0.5 7.7 6\nEthiopia 8.2 99.6 112\nFrance 0.6 9.8 7\nIndonesia 5.2 98.1 265\nIndia 6.9 99.1 1,354\nJapan 0.8 16.5 21\nMali 7.3 99.5 20\nNigeria 10.1 99.9 201\nPeru 3.4 88.7 29\nUnited States 0.9 11.0 36\n<u>South Africa</u> <u>7.8</u> <u>88.1</u", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000675", "page": 32, "chunk": 0, "title": "idu0325015fc0a4d6046420afe405cb6b6a87b0b", "pdf_url": "https://local/prwp/idu0325015fc0a4d6046420afe405cb6b6a87b0b.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Provide on-the-job training and support to the focal points at the public funds for\nimplementation\n➢❨¢ Conduct the NHA survey based on the new SHA2.0 and using the NHAPT\n➢❨¢ Analyze results\n➢❨¢ Produce an NHA report and disseminate its findings in a national seminar to key\nstakeholders in the country.\n\nB. Grant Execution and Implementing Agency\n\nThe financing instrument for this activity is a grant-Based Bank Executed on Behalf of the Recipient\n(BEBR) for a proposed amount of US$383,150.\n\nThe need for BEBR is based on the Bank team assessment of the situation and on the request of the\nMoPH to mitigate potential risks and delays in implementation. More specifically, to mitigate the\nrisk associated with the stalemate in government as a result of the current political situation, and the\nconstrains this may have in approvals and project implementation. Also to avoid the following:\nslow disbursement due to the flow of funds➢❨ mechanism between MOF and MoPH; lack of\nexperienced and dedicated FM specialists; lack of accounting system to record and produce\nfinancial reports, weak internal control system, and insufficient procurement capacity.\n\nThe MoPH through the Statistics Department will be responsible for the overall implementation of\nthe program. The SD will build on its strong collaboration with CAS) as CAS is expected to be\nengaged in the intended development of national set of indicators, as well as in the NHA surveys,\n\n\nPage 5 of 7", "output": {"entities": {"named_data": ["NHAPT"], "descriptive_data": ["NHA surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000046", "page": 4, "chunk": 1, "title": "Project Information Document (Concept Stage) - Lebanon MoPH Statistical Capacity Building Project - P161766", "pdf_url": "http://documents.worldbank.org/curated/en/804431474323190796/pdf/PIDC90504.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NHAPT", "label": "NAMED_DATA", "score": 0.6780709624290466, "start": 165, "end": 170, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "NHA surveys", "label": "DESCRIPTIVE_DATA", "score": 0.6382866501808167, "start": 1431, "end": 1442, "probe_score": 0.0977, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nBeirut Housing Rehabilitation and Cultural and Creative Industries Recovery (P176577)\n\n\n**Figure 3.** Attention received by damaged building in Saifi, Rmeil and Medawar districts.\n\n\nSource: UN-Habitat\n\n\n**9.** **The lack of coordinated policies and support systems for property owners and occupants has rendered**\n**housing conditions contingent upon the owners’ ability or willingness to pay for necessary works.** <sup>**97**</sup> A large share\nof Beirut’s housing stock is deteriorating and in need of renovation and maintenance works. Cost represents a\nmajor impediment for preservation, as there are neither incentives in place for property owners or occupants to\nmaintain their housing units and buildings nor a monitoring system or other compliance mechanisms to enforce\na certain standard for housing conditions. For instance, despite Lebanon being an earthquake-prone country, a\nsignificant number of buildings do not have appropriately secure and solid structures that could withstand any\nhazard, such as seismic. According to an assessment conducted in eight neighborhoods within Beirut city by UNHabitat, in seven neighborhoods between 30 and 62 per cent of buildings need major repair or emergency\nintervention to their exterior walls, windows, doors and balconies (see figure 4). <sup>98</sup>\n\n\n**Figure 4.** Buildings in need of major repair/emergency interventions in their exterior conditions across eight profiled\n\nneighborhoods in Beirut City.\n\n\n97 UN-Habitat, “Guide for Mainstreaming Housing in Lebanon’s National Urban Policy.”\n98 UN-Habitat (2021). _Beirut City Profiles 2021_ .\n\n\nPage 53 of 66", "output": {"entities": {"named_data": [], "descriptive_data": ["assessment conducted in eight neighborhoods within Beirut city"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 58, "chunk": 0, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "assessment conducted in eight neighborhoods within Beirut city", "label": "DESCRIPTIVE_DATA", "score": 0.7919124960899353, "start": 1060, "end": 1122, "probe_score": 0.4752, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " monitored by FAO; (iii) the number of locations monitored\nmonthly for water quality is the prime responsibility of LRA. In addition, discharged treated\nwastewater will be monitoried monthly in accordance with the Lebanese standards (Decision\n8/1/2001) as further explained in the safeguards documents.\n\n\n54. In addition, the LRA currently has a sustained – albeit limited—monthly monitoring of ten\nlocations in the upper Litani River Basin for selected indicators <sup>35</sup> . It uses a simple Water Quality\nIndex (WQI), which presents the advantage of communicating water quality information in an\nunderstandable way for all stakeholders. The WQI summarizes a large amount of water quality data\nscores, reported as a total number between 1 and 100, with (i) 90-100 as excellent, (ii) 75-90 as good,\n\n\n\n34 Ministries of Environment, Energy and Water, Industry, Agriculture, Public Health, Interior, and Municipalities; the Council for Development and\nReconstruction; the BWE; the LRA; the National Council for Scientific Research; and the Municipalities of Zahlé, Baalbeck, Ferzol, Marj, Anjar, and Jeb\nJennin.\n35 Ammonia (NH3), Chlorine (Cl-), Conductivity, Dissolved Oxygen (DO), Nitrate (NO3-), Nitrite (NO2-), pH, Phosphate (PO43-), Sulfate (SO42-), and Total\n\n\n\n35 Ammonia (NH3), Chlorine (Cl-), Conductivity, Dissolved Oxygen (DO), Nitrate (NO3-), Nitrite (NO2-), pH, Phosphate (PO43-), Sulfate (SO42-), and Total\n\nDissolved Solids (TDS).\n\n\n\n-), pH, Phosphate (PO4\n\n\n\n15", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["water quality data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000036", "page": 23, "chunk": 1, "title": "Lebanon - Lake Qaraoun Pollution Prevention Project", "pdf_url": "http://documents1.worldbank.org/curated/en/279341468589482380/pdf/PAD860-PAD-P147854-R2016-0133-1-Box396255B-OUO-9.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "water quality data", "label": "VAGUE_DATA", "score": 0.7037004828453064, "start": 681, "end": 699, "probe_score": 0.0703, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " from<br>the activities<br>in support of<br>community<br>tourism<br> <br>UWA will compile<br>information based on<br>activity reports.<br> <br>UWA<br>|Community ecotourism enterprises<br>supported<br>This indicator measures the<br>number of community-<br>based ecotourism projects<br>supported under<br>Component 2.1.<br>This indicator measures the<br>transformative capacity of<br>resilience through<br>enhancing economic<br>opportunities for<br>communities.<br>Annual<br> <br>Reports from<br>the activities<br>in support of<br>community<br>tourism<br> <br>UWA will compile<br>information based on<br>activity reports.<br> <br>UWA<br>|Community ecotourism enterprises<br>supported<br>This indicator measures the<br>number of community-<br>based ecotourism projects<br>supported under<br>Component 2.1.<br>This indicator measures the<br>transformative capacity of<br>resilience through<br>enhancing economic<br>opportunities for<br>communities.<br>Annual<br> <br>Reports from<br>the activities<br>in support of<br>community<br>tourism<br> <br>UWA will compile<br>information based on<br>activity reports.<br> <br>UWA<br>|Community ecotourism enterprises<br>supported<br>This indicator measures the<br>number of community-<br>based ecotourism projects<br>supported under<br>Component 2.1.<br>This indicator measures the<", "output": {"entities": {"named_data": [], "descriptive_data": ["activity reports"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000043", "page": 58, "chunk": 1, "title": "Uganda - Investing in Forests and Protected Areas for Climate-Smart Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/304401587952865863/pdf/Uganda-Investing-in-Forests-and-Protected-Areas-for-Climate-Smart-Development-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "activity reports", "label": "DESCRIPTIVE_DATA", "score": 0.6427973508834839, "start": 117, "end": 133, "probe_score": 0.0097, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "5\n# **I. Basic policy instruments** **and framework for education** **in complex emergencies**\n\n\n\nPart One describes the basic policy instruments in which the rights of children and\nyoung adults to education are endorsed,\nincluding the 1951 Convention Relating to\nthe Status of Refugees. The Convention on\nthe Rights of the Child,which was adopted\nby the General Assembly of the United\nNations in 1989, has become one of the\nmost useful tools to assess and advocate\nfor the needs of children in general,including those children and young adults in\nwar-affected countries.\n\n\n**I.1 The Convention on the**\n\n**Rights of the Child,1989**\n\n\nThe Convention on the Rights of the Child <sup>1</sup> [^1: UNICEF, _Implementation handbook for the_\n_Convention on the Rights of the Child_, prepared\nby R. Hodgkin and Peter Newell, Geneva,\nUNICEF, 1998. (Further reference to the CRC is\nfrom the same source.)]\n(CRC) has gained widespread ratification\nby States Parties. In 1997, almost all States\nhad signed the CRC,which establishes that\nchildren under 18 years of age (Article 1)\nhave specific rights without discrimination\nof any kind. This is particularly relevant to\nrefugee children because it establishes\nbroad standards and may be used as the primary basis for protecting them. <sup>2</sup> [^2: UNHCR, _Refugee children: guidelines on protec-_\n_tion and care_, Geneva, UNHCR, 1994, p. 19.] However,\nthis only applies when a State is a party to\nthe CRC, and not to another treaty concerned with refugees. The convention tries\nto take into consideration all aspects of the\nchild’s life, from health and education to\nsocial and political rights. According to\nUNHCR’s Policy on Refugee Children\n(1993), the CRC ‘constitutes a normative\nframe of reference for UNHCR’s action’ on\nbehalf of refugee children. This section", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001362", "page": 4, "chunk": 0, "title": "Rapid Educational Response in Complex Emergencies: A Discussion Document", "pdf_url": "https://reliefweb.int/attachments/d30e5d86-968b-30df-84b9-1d2acbfcba7a/3B6488948F387065C1256DFF004C07D9-UNHCR_educ.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\n**radically after February 24, 2022.**\nUp until 2021, Ukrainians in Poland were\nmostly men (close to two-thirds), who came\nfor work-related reasons, often leaving their\nfamilies back in Ukraine. The onset of the\nfull-scale conflict in Ukraine triggered the\narrival of individuals displaced by the war.\nThose were primarily women and children,\nwith men in Ukraine being mobilized for\nthe war effort. Social insurance data does\nnot reflect the full extent of the change,\nshowing only workers, without children and\nadults outside of employment.\n\n\n\n**Chart 3. Number of Ukrainians registered in Poland for social insurance by sex**\n\n\n2021 Q4 2022 Q4 2023 Q4 2024 Q2\n\n\n\nNumber of insured\nmen with Ukrainian\ncitizenship\n\n\n\nNumber of insured\nwomen with Ukrainian\ncitizenship\n\n\n\nNumber of insured\nwith Ukrainian\ncitizenship\n\n\n\nSource: Deloitte own elaboration based on ZUS data.\n\n\n3 Employed person is a person, who during the reference week worked for at least 1 hour for pay or profit, including contributing family workers; had a certain job\nattachment; or produced agricultural goods for sale or barter. A definition according to the Labour Force Survey: <u>https://ec.europa.eu/eurostat/statistics-explained/</u>\n<u>index.php?title=Glossary:Employed_person_-_LFS</u>\n\n\n08\n\n\n\nSource: Deloitte own elaboration based on the PESEL database as of September 2024.\n\n\n4 Available in the repository maintained by the government <u>https://dane.gov.pl/pl/dataset/2715</u> as well as UNHCR data portal <u>https://app.powerbi.com/</u>\n<u>view?r=eyJrIjoiODhkOGZiMzctZTliMi00NzA5LTgyM2QtZGZh", "output": {"entities": {"named_data": ["ZUS data", "PESEL database", "UNHCR data portal"], "descriptive_data": ["Social insurance data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 4, "chunk": 2, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Social insurance data", "label": "DESCRIPTIVE_DATA", "score": 0.8193688988685608, "start": 400, "end": 421, "probe_score": 0.9986, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "ZUS data", "label": "NAMED_DATA", "score": 0.8635835647583008, "start": 862, "end": 870, "probe_score": 0.9734, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PESEL database", "label": "NAMED_DATA", "score": 0.8764667510986328, "start": 1319, "end": 1333, "probe_score": 0.9802, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHCR data portal", "label": "NAMED_DATA", "score": 0.5786138772964478, "start": 1471, "end": 1488, "probe_score": 0.9645, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n\n\nnegative perceptions of Ukrainian refugees in some\nhost communities including perceived overuse of\nhealth services and preferential treatment <sup>6</sup> [^6: Kerusauskaite, I., Nimkar, R., Mulloy, L., Slota, A. (2023). Risks to Community Cohesion between Ukrainian Refugees and Host\nCommunities in Central Europe. Community Cohesion in Central Europe project.] . As the\nrefugees stay longer, sustainable solutions to\nmeeting health needs of refugees and host\ncommunities, including sustainable financing,\nrefugee data integration, integration of the refugee\nhealth workforce, and enhanced service delivery\nincluding mental health services, are critical.\n\n\nThrough regional multi-agency collaboration,\nmultisector needs assessments have been\nconducted in refugee-receiving countries since\n2022 to collect information on the needs of\nrefugees, including those related to health, nutrition\nand mental health and psychosocial support. These\nassessments support partners’ understanding of the\nlevel of access to essential services among\nrefugees and outcomes enable governments and\npartners to identify priorities for the response. In\n2024, a social-economic lens was added in\nassessing the needs of refugees in the SocioEconomic Insights Study (SEIS) conducted in ten\ncountries (Bulgaria, Czechia, Estonia, Hungary,\nLatvia, Lithuania, Poland, Republic of Moldova,\nRomania, and Slovakia).\n\n\n# Methodology\n\nThe regional analysis is grounded in consolidated\ndata from the Socio-Economic Insights Survey\n(SEIS), conducted across ten countries: Bulgaria,\nCzechia, Estonia, Hungary, Latvia, Lithuania, Poland,\nRepublic of Moldova, Romania, and Slovakia. Data\nfor the country-specific SEISs were collected\nthrough in-person interviews from May to July 2024.\n\n\nThe total sample size comprises **8,720 households**\nand **19,803 household members**, with respondents\nproviding information on behalf of all individuals\nwithin their households.\n\n\n**COUNTRY** **SAMPLE SIZE 2023** **SAMPLE SIZE 2024**\n\n\n<u>Bulgaria</u> <u>1,054</", "output": {"entities": {"named_data": ["SocioEconomic Insights Study", "Socio-Economic Insights Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000004", "page": 5, "chunk": 0, "title": "NAVIGATING HEALTH AND WELL BEING CHALLENGES FOR REFUGEES FROM UKRAINE   2nd Edition", "pdf_url": "https://local/jad_paddy_docs/navigating health and well-being challenges for refugees from ukraine - 2nd edition.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SocioEconomic Insights Study", "label": "NAMED_DATA", "score": 0.7322799563407898, "start": 1286, "end": 1314, "probe_score": 0.9778, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Socio-Economic Insights Survey", "label": "NAMED_DATA", "score": 0.7769930362701416, "start": 1540, "end": 1570, "probe_score": 0.9908, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEmergency Food Security Project (P178936)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPage 5 of 54", "output": {"entities": {"named_data": ["Emergency Food Security Project"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 9, "chunk": 0, "title": "Jordan - Emergency Food Security Project", "pdf_url": "http://documents.worldbank.org/curated/en/486071652556836130/pdf/Jordan-Emergency-Food-Security-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Emergency Food Security Project", "label": "NAMED_DATA", "score": 0.5885877013206482, "start": 19, "end": 50, "probe_score": 0.0133, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Chapter 5\n\n\n\n\n\n**3. Expand access**\n**to third country**\n**solutions.**\n\n\n**4. Support**\n**conditions in**\n**countries of**\n**origin for return**\n**in safety and**\n**dignity.**\n\n\n\n3.1 Refugees in\nneed have access\nto resettlement\nopportunities in an\nincreasing number of\ncountries.\n\n\n3.2 Refugees have\naccess to complementary\npathways for admission\nto third countries.\n\n\n4.1 Resources are made\navailable to support the\nsustainable reintegration\nof returning refugees by\nan increasing number of\ndonors.\n\n\n4.2. Refugees are able\nto return and reintegrate\nsocially and economically.\n\n\n\n3.1.1. Number of refugees who\ndeparted on resettlement from\nthe host country\n\n\n3.1.2. Number of countries\nreceiving UNHCR resettlement\nsubmissions from the host\ncountry\n\n\n3.2.1. Number of refugees\nadmitted through complementary\npathways from the host country\n\n\n4.1.1. Volume of ODA provided\nto, or for the benefit of, refugee\nreturnees in the country of origin\n\n\n4.1.2. Number of donors\nproviding ODA to, or for the\nbenefit of, refugee returnees in\nthe country of origin\n\n\n4.2.1. Number of refugees\nreturning to their country of\norigin\n\n\n4.2.2. Proportion of returnees\nwith legally recognized\ndocumentation and credentials\n\n\n\nAdministrative Records\n\n\n(processed by UNHCR)\n\n\nAdministrative Records\n\n\n(processed by UNHCR)\n\n\nAdministrative Records\n\n\n(OECD and UNHCR)\n\n\nAdministrative Records\n\n\n(OECD Financing for Refugee\nSituations Survey 2020)\n\n\nAdministrative Records\n\n\n(OECD Financing for Refugee\nSituations Survey 2020)\n\n\nAdministrative Records\n\n\n(UNHCR)\n\n\nHousehold surveys /\nadministrative records\n\n\n(UNHCR)\n\n\n\n\n\n74", "output": {"entities": {"named_data": ["OECD Financing for Refugee\nSituations Survey 2020", "OECD Financing for Refugee\nSituations Survey 2020"], "descriptive_data": ["Administrative Records", "Household surveys /\nadministrative records"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000803", "page": 37, "chunk": 0, "title": "2021 Global Compact on Refugees Indicator Report", "pdf_url": "https://reliefweb.int/attachments/75fd0942-6cc3-3825-a32b-0013afceb78e/2021_GCR-Indicator-Report_spread_web.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Administrative Records", "label": "DESCRIPTIVE_DATA", "score": 0.5200790166854858, "start": 1208, "end": 1230, "probe_score": 0.3938, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "OECD Financing for Refugee\nSituations Survey 2020", "label": "NAMED_DATA", "score": 0.7910670638084412, "start": 1374, "end": 1423, "probe_score": 0.8992, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "OECD Financing for Refugee\nSituations Survey 2020", "label": "NAMED_DATA", "score": 0.5932977795600891, "start": 1453, "end": 1502, "probe_score": 0.872, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Household surveys /\nadministrative records", "label": "DESCRIPTIVE_DATA", "score": 0.7480160593986511, "start": 1541, "end": 1583, "probe_score": 0.9064, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "* **Female**\n\n\n**70.74**\n\n**BC44**\n\n**_6064_**\n4044\n\n**30.24**\n\n**20.24**\n\n**1&14**\nw 7\n\n**20** 10 0 10 **21.**\n\n**OerCent**\n\n\n\nI **Under-5** mortality **rate (per** 1,000)\n\n\n\nI 2501 2w\n\n\n\n2w\n\n\n\n**_(US$_** _miiiions)_\nNet ODA and official aid\n_Top_ 3 donors (in 2004):\n\nUnited States\nUnited Kingdom\nGermany\n\n\nAid _(Oh_ of GNI)\nAid per capita (US$)\n\n\n**Long-Term Economic Trends**\n\n\nConsumer prices (annual _Oh_ change)\nGDP implicit deflator (annual _Oh_ change)\n\n\nExchange rate (annual average, iocai per US$)\nTerms of trade index (2000 = 100)\n\n\nPopulation, mid-year (millions)\nGDP (US$ millions)\n\n\n\n**1980**\n\n\n212\n\n\n19\n4\n15\n\n\n3.4\n6\n\n\n4.5\n4.4\n\n\n2.1\n131\n\n\n\n37.7\n7,269\n\n\n58.9\n11.9\n6.0\n29.2\n\n80.0\n9.8\n14.5\n\n\n7.6\n11.9\n10.8\n\n\n\n**-20**\n\n\n\n**80** **95** **W** **_05_**\n\n\n\n1990 2000\n\n\n1,016 693\n\n\n50 130\n35 11\n47 39\n\n\n6.5 6.9\n20 11\n\n\n5.2 0.7\n3.9 6.0\n\n\n2.1 6.1\n151 100\n\n\n51.2 64.3\n12,083 7,845\n\n(% _of_ **_GDP)_**\n\n51.9 47.7\n11.6 12.4\n5.1 5", "output": {"entities": {"named_data": [], "descriptive_data": ["Terms of trade index"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009715", "page": 80, "chunk": 2, "title": "Ethiopia - Urban Water Supply And Sanitation Project", "pdf_url": "https://documents.worldbank.org/curated/en/218751468023442647/pdf/391190ET0IDA1R20071006911.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Terms of trade index", "label": "DESCRIPTIVE_DATA", "score": 0.7417766451835632, "start": 510, "end": 530, "probe_score": 0.9419, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "A most interesting feature of the _Ser Maestro_ assessment, as mentioned, is that teachers’\n\n\nknowledge is tested against a series of “curricular areas” within each subject. Such a level of\n\n\ngranularity of information enables the identification of very specific knowledge areas where\n\n\nteachers display cognitive gaps. Data from the _Ser Maestro_ identify the share of correct and\n\n\nincorrect teacher responses in the assessments. The specificity of this information enables\n\n\npersonalized teacher development programs to be designed based on actual needs and knowledge\n\n\ngaps (table 2).\n\n\n10", "output": {"entities": {"named_data": ["Data from the _Ser Maestro_"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002385", "page": 11, "chunk": 0, "title": "using student and teacher assessments to design more pertinent in service teacher training the case of ecuador", "pdf_url": "https://local/prwp/using-student-and-teacher-assessments-to-design-more-pertinent-in-service-teacher-training-the-case-of-ecuador.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data from the _Ser Maestro_", "label": "NAMED_DATA", "score": 0.7048479914665222, "start": 320, "end": 347, "probe_score": 0.9226, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Once again, Figure 13 groups interventions according to the actor whose behavior they primarily aim\nto influence. But in contrast to the meta-analyzes visualized in Figure 4 in section 3, it only uses\nevidence derived from RCTs and not from quasi-experiments. Since – as already outlined in the\nintroduction – RCTs are generally considered to be even more rigorous than quasi-experiments, the\nobjective is to determine whether this move to even more rigor changes any substantial results or\nconclusions. Of course, forgoing the evidence from quasi-experimental studies reduces the number\nof interventions that can be incorporated into the meta-analysis. However, the reduction in the\nnumber of interventions is relatively small: The meta-analysis visualized in Figure 13 draws on 23\ninterventions, i.e. only four less than the one of Figure 4. Eight of 23 interventions that utilize RCTs\nfall into the “teachers” category, ten belong to the “schools/school administrations” group, and four\nare centered on households. As was already the case for the broader set of evidence, a meta-analysis\nof community-focused interventions on composite learning outcomes is rendered futile because only\none intervention falls into the “communities” category.\n\n\nFigure 13 shows that the results from a meta-analysis that only uses evidence derived from RCTs are\nvery similar to those derived for the full sample of rigorously evaluated education-related interventions\nin South Asia. As before, all three groups of interventions for which a meta-analysis of impacts on\nchildren’s average overall test scores is feasible have a statistically significant impact on this outcome\nvariable. Moreover, at 0.17, 0.22 and 0.04 standard deviations, the effects of teacher-, school- and\nhousehold-centric interventions are similar or identical to the ones identified for the sample that\nincluded both RCTs and quasi-experiments.\n\n\nWhile before interventions were always grouped according to the actor they primarily target, this is no\nlonger", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006418", "page": 70, "chunk": 0, "title": "wps7362", "pdf_url": "https://local/prwp/wps7362.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " students that participated in the study was small (approximately 1%), limiting the statistical\nanalysis and the possibility of disaggregating results by this stratum.\n\n\ny **ERCE 2019:** The same questions about country of birth were included in the family and student\n\nsurveys. Asking students about their country of birth and that of their parents improved the availability\nof information and allowed disaggregating the test results by first- and second-generation migrants.\nStatistically significant differences were found in favour of students born in the country where they took\nthe test for all the grades and subjects assessed (Treviño et al., 2015).\n\n\ny **ERCE 2025** : LLECE is currently coordinating with the participating countries to develop technical guidelines\n\nand instruments to ensure the inclusion of children on the move in selected ERCE participating countries.\nIn particular, the assessment design considers oversampling in schools with a high proportion of immigrant\nstudents to allow comparison based on that stratum. Additionally, the background questionnaires will\ninclude new modules, one of them explicitly focused on human mobility. This module will collect information\nthat will allow access to more comprehensive data on the transnational mobility of the student, bullying and\ndiscrimination associated with student mobility, classroom diversity, and other associated factors that could\nbe related to the learning outcomes of displaced students. The dimensions to be included in this new\nmodule will be confirmed after the pilot studies that will take place in all participating countries between\nAugust 2023 and June 2024.\n\n\nThe adjustments taken by LLECE to promote data inclusion of children on the move is a good practice that\nreflects a comprehensive technical effort to respond to the regional need to better understand the learning\noutcomes of children on the move, mainly displaced Venezuelans. Further, it highlights that international\nlearning assessments hold the potential and technical capacity to promote refugee data inclusion, and to fill\nthe global gap in information about refugees’ learning outcomes.\n\n\n**46**", "output": {"entities": {"named_data": [], "descriptive_data": ["family and student\n\nsurveys"], "vague_data": ["refugee data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000382", "page": 45, "chunk": 1, "title": "Paving pathways for inclusion: a global overview of refugee education data", "pdf_url": "https://reliefweb.int/attachments/31f00be7-0481-4224-80ce-378c049a02d4/Paving%20pathways%20for%20inclusion%20--%20a%20global%20overview%20of%20refugee%20education%20data.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "family and student\n\nsurveys", "label": "DESCRIPTIVE_DATA", "score": 0.8855420351028442, "start": 250, "end": 277, "probe_score": 0.0378, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "refugee data", "label": "VAGUE_DATA", "score": 0.6972494125366211, "start": 2049, "end": 2061, "probe_score": 0.106, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "local governments on CERC activities. Finally, the MoH collaborated with the MoES and cultural leaders to deliver\nadolescent and youth friendly health services to higher education schools and communities, respectively. Some of\nthese relationships have been established and are continuing beyond the project period. **Fostering multisectoral**\n**action in results driven by various sectors is critical and needs to be incorporated in the project design and nurtured**\n**intentionally throughout project implementation.**\n\n\n88. **The successful nation-wide scale up of RBF required adequate preparatory work, including local expertise,**\n**routine analysis and sharing of program data with stakeholders.** The investments in RBF were substantial to enable\nnational-wide scale up of this innovation that had been implemented in Uganda as pilots since 2003 and some\nstakeholders were skeptical about whether this was the best use of the resources. The task team and the MoH rolled\nout elaborate preparatory work including sensitization of the districts, development of a harmonized national RBF\nframework, and training of trainers reaching over 100, and using data from the RBF program to advocate for support\nto the program, and ultimately, it’s mainstreaming in the government’s own PHC grant systems as part of the UgIFT\nProgram from July 1, 2023. **Any future major innovation in RBF will benefit from robust preparatory work, including**\n**training of adequate numbers of local experts, and baseline assessment.**\n\n\n89. **The CERC is essential in the timely response to public health emergencies and protecting the health, health**\n**services, and the economy.** The CERC helped to avert the EVD threat in 2019, and to respond to the COVID-19\noutbreak in 2020. Being a novel instrument, inclusion of the CERC in the project and its subsequent activation in 2019\nwas challenging and was slowed by delayed buy in by key stakeholders", "output": {"entities": {"named_data": [], "descriptive_data": ["data from the RBF program"], "vague_data": ["program data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002790", "page": 39, "chunk": 0, "title": "Uganda - Reproductive, Maternal and Child Health Services Improvement Project", "pdf_url": "https://documents.worldbank.org/curated/en/099060424111012280/pdf/BOSIB146703d8a027183911b77a6a7a9a3e.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "program data", "label": "VAGUE_DATA", "score": 0.5971726179122925, "start": 670, "end": 682, "probe_score": 0.2488, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from the RBF program", "label": "DESCRIPTIVE_DATA", "score": 0.8424317240715027, "start": 1156, "end": 1181, "probe_score": 0.7606, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " loss accounted for an economic loss worth US$1.2 billion. Wetland degradation\naccounted for an average of US$1.5 million of the value of wetlands, and soil nutrient loss from erosion\nwas US$625 million per year. Poverty has mainly been linked to massive natural resource degradation\nthrough unsustainable exploitation. The reduction in agricultural productivity is worsening poverty\nespecially among agriculture-dependent people and in areas where the degradation of land is the highest\nwith limited interventions. As Figure 1 shows, areas of Busoga, Bukedi, and Kigezi continued to experience\nextreme and increasing poverty levels largely attributed to land and natural resource degradation. There\nhave been limited or inadequate interventions in natural resource management and adaptation to the\nimpacts of climate change in these regions. While poverty levels in Karamoja, West Nile, and the North\nremain high, they are declining due to investments in poverty reduction, natural resource management,\nand climate change adaptation. Without adequate action, social and economic losses are expected to be\nmore pronounced in the marginalized regions of the country where the declining resilience of rural\nhouseholds would have devastating impacts on agricultural productivity, food security, incomes, and\npoverty reduction.\n\n\n1 Uganda National Household Survey (2016/17)\n2 Between 2012/13 and 2016/17 there was drought, crop and livestock pest and disease outbreaks, floods, and storms that\nresulted in sharp changes in prices. These events were more prevalent among the rural areas except for sharp changes in prices\nof commodities that were highly ranked in the urban areas. The prevalence of drought was almost universal except in the\nsubregions of Elgon and Kigezi. Sharp changes in prices were most common in the subregions of Lango, Central II, and Karamoja.\nBukedi subregion was the most hit by crop pests and diseases followed by Lango, while Karamoja was the most affected by\nlivestock diseases (100 percent). Teso subregion was affected by storms and floods.\n\n\nPage 7 of 81", "output": {"entities": {"named_data": ["Uganda National Household Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000001", "page": 12, "chunk": 1, "title": "Uganda - Climate Smart Agricultural Transformation Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099050012052240654/pdf/BOSIB05e6fc47e0770aeec00ad5e11774f2.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Uganda National Household Survey", "label": "NAMED_DATA", "score": 0.9133508801460266, "start": 1328, "end": 1360, "probe_score": 0.9772, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "; Geographically-<br>targeted discount; means-<br>tested discount|2001|Prokopy 2002|\n|Nepal<br>(Kathmandu)|Subsidy on public taps; IBT with<br>10m3 first block|Uniform volumetric tariff;<br>IBT with 7m3 first block;<br>Slum discount; Means-<br>tested discount|2001|Pattanayak and Yang<br>2002; Pattanayak et al.,<br>2001|\n|Nicaragua<br>(Managua)|IBT with slum discount||1995|Walker et al. 2000.|\n|Panama<br>(Panama City<br>& Colon)|IBT with slum and pensioner<br>discount|<br>|1998|Walker et al. 2000.|\n|Paraguay<br>(Urban areas)|Discount for means tested<br>households (housing<br>characteristics)|IBT with 15 and 5 m3 first<br>block; geographically<br>targeted discount; means<br>tested discount|2001|Robles 2001|\n|Sri Lanka|IBT||2003|Pattanayak and Yang<br>2005; Pattanayak et al.,<br>2004; Brocklehurst 2004|\n|Uruguay||Means-tested exemption of<br>fixed charge||Ruggeri-Laderchi 2003|\n|Venezuela<br>(Merida)|IBT with slum discount||1996|Walker et al. 2000.|\n\n\nNotes:\nData from the sources was reanalyzed in many cases in order to create comparable analysis across cases. Thus, the results\nreported in the base study will not necessarily mirror the results reported in this book.\n*= Analysis assumes all the eligible households are receiving the subsidy", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Data from the sources"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003091", "page": 23, "chunk": 1, "title": "wps38780rev0pdf", "pdf_url": "https://local/prwp/wps38780rev0pdf.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data from the sources", "label": "VAGUE_DATA", "score": 0.7087452411651611, "start": 971, "end": 992, "probe_score": 0.7388, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "100\n\n\n80\n\n\n60\n\n\n40\n\n\n20\n\n\n0\n\n\n\n_(c) QGC method_\n\n\n0 20 40 60 80 100\n\nQGC\n\n\n\nSource: own estimates based on SEDLAC data (CEDLAS and the\nWorld Bank) and the Global Economic Prospectus (GEP). Note: The\nfigure shows poverty nowcasts on the horizontal axis and actual poverty\nrates in vertical axis for all countries for which data is available in 20052014. The 45 degree line shows actual poverty. Countries included are:\nArgentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Dominican\nRepublic, Ecuador, Honduras, Mexico, Panama, Peru, Paraguay, El\nSalvador, and Uruguay. Guatemala and Nicaragua are excluded due to\ndata limitations. A simple interpolation was applied when country data\nwere not available for a given year (see table 1 for a description of the\ndata gap and comparability across years). PE refers to Poverty-growth\nElasticity method; NDG refers to Neutral Distribution Growth method;\nand QGC refers to Quantile Growth Contribution method. The figure\nassumes a pass-through θ=1 for the NDG and QGC methods. All past\ninformation is obtained from periods -1 and -2 when nowcasting poverty\nin moment 0 under de PE and QGC methods. The number of quantiles\nis q=20 under the QGC method.\n\n\n30", "output": {"entities": {"named_data": ["SEDLAC data", "Global Economic Prospectus"], "descriptive_data": [], "vague_data": ["country data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007087", "page": 31, "chunk": 0, "title": "wps8104", "pdf_url": "https://local/prwp/wps8104.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEDLAC data", "label": "NAMED_DATA", "score": 0.8993198275566101, "start": 107, "end": 118, "probe_score": 0.9985, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Global Economic Prospectus", "label": "NAMED_DATA", "score": 0.5177391767501831, "start": 155, "end": 181, "probe_score": 0.9982, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "country data", "label": "VAGUE_DATA", "score": 0.7331326007843018, "start": 674, "end": 686, "probe_score": 0.9726, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the temporary rental of housing by displaced owners is projected\nat US$173.3 million for the same period. <sup>93</sup> [^93: RDNA]\n\n**7.** **Units and buildings remaining in need of repair are mainly those that are severely damaged, requiring**\n**more costly structural works, encompassing historic including heritage-grade buildings.** The wide national and\ninternational immediate response mostly focused on the less damaged units due to the technical complexity of\naddressing severely damaged units. As of 25 February 2021, 5,777 buildings remain with low or cosmetic damage\n(L1 damage level), 1,881 buildings with major but not structural damage (L2 level), and 1,093 with structural\ndamage (L3 level).\n\n**8.** **Most of the impacted residential buildings with cultural heritage value are still unattended and remain**\n**in precarious condition, requiring rehabilitation to allow habitability (see figure 3).** So far early recovery efforts\nhave focused on addressing affected residential buildings that suffered minor damage <sup>94</sup> [^94: Buildings with less than 10 percent of physical damage.] due to a lack of leadership\nfrom the authorities, as well as funds, capacity, and time required to assume the complex rehabilitation works of\nthe most severely damaged buildings during what was considered the “humanitarian phase”. According to the\nUN-Habitat damage inventory for all the buildings within the blast affected area of damaged buildings,\napproximately 25 buildings have not received any type of rehabilitation assistance yet, 20 have been propped but\nnot rehabilitated, 50 buildings are still under rehabilitation, and 80 have been completely rehabilitated. According\nto the DGA, 80 percent of the 640 heritage buildings which were damaged by the blast are of residential use.\nAmong these buildings, UNESCO interventions have focused on securing the most severely damaged buildings\nusing international and DGA standards <sup>95</sup>, with", "output": {"entities": {"named_data": ["UN-Habitat damage inventory"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 57, "chunk": 1, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UN-Habitat damage inventory", "label": "NAMED_DATA", "score": 0.9135842323303223, "start": 1357, "end": 1384, "probe_score": 0.0131, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " private hospitals, or public hospitals) and also take into consideration other factors such\nas voucher redemption rate, uptake and utilization of the services in the package, and inflation.\nThe costing methodology should not rely on an idealized approach (100 percent antenatal\nattendance and deliveries) but consider pragmatic issues likely to influence service uptake and\nutilization.\n\n5. _The importance of putting in place a sound claims processing and data management_\n_system which generates timely information for regular monitoring of implementation._\n\n\n6. _It is imperative to commence verification of quantity and quality of services immediately_\n_after VMA quarterly reports are drafted_ . In this project, the VMA’s quarterly report had to go\nthrough several review processes before the IVEA could begin verification. The draft report\nshould have been given to the IVEA to commence the verification while the VMA draft report\nunderwent its review process. In the RHVP, the IVEA quarterly reports came late and thus did\nnot provide timely recommendation to the VMA. All the same, the IVEA verification of the\nservices formed the basis for disbursement.\n\n7. _Private VSPs should maintain proper service delivery records_ and should be encouraged\nto submit monthly service delivery statistics to the respective district health management office\nin order for the statistics to be captured in the national Health Management Information System\n(HMIS).\n\n\n23", "output": {"entities": {"named_data": [], "descriptive_data": ["monthly service delivery statistics"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019778", "page": 31, "chunk": 1, "title": "Uganda - Reproductive Health Vouchers in Western Uganda Project", "pdf_url": "https://documents.worldbank.org/curated/en/898221468113336731/pdf/955690ICR00PUB0rs0in0Western0Uganda.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "monthly service delivery statistics", "label": "DESCRIPTIVE_DATA", "score": 0.7142770290374756, "start": 1267, "end": 1302, "probe_score": 0.0017, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "an MFA quota in the US (prior to 2005) and a weighted average of the presence of MFA quotas\n\n\non competitor countries exporting that product to the US. The effect of the average MFA quota\n\n\nimposed on the rest of the world is insignificant. <sup>39</sup> Importantly, accounting for competition from\n\n\nother countries with preferential access to the US reduces only slightly the magnitude of the impact\n\n\nof AGOA on apparel products though the impact on GSP LDC products becomes insignificant. <sup>40</sup>\n\n\nOur evidence so far shows that the estimated impact of AGOA on apparel increases over\n\n\ntime after its enactment 2001 but flattens after 2005. We conjecture that the MFA end in 2005\n\n\nunleashed the exports of apparel from China and other Asian countries which mitigated\n\n\nsubstantially the positive impact of AGOA on apparel exports for African countries. The\n\n\ninteresting question is whether this lack of durability in the AGOA apparel impacts is heterogenous\n\n\nacross countries, as was hinted at in Section 4 by the differential raw data patterns across four\n\n\ngroups of countries. We re-estimate Eq. (1) allowing the coefficient on the AGOA apparel term to\n\n\nvary across years and sub-regions: Central and West Africa, East Africa, and Southern Africa. We\n\n\nplot the corresponding coefficient estimates and 95 percent confidence intervals in Figure 3.\n\n\nThere is a clear difference across sub-regions in the temporal response to AGOA and to\n\n\nthe end of the MFA. <sup>41</sup> For Central and West Africa, the impacts of AGOA on apparel exports to\n\n\nthe US are mostly insignificant, and there are even signs of a negative impact in the early years.\n\n\n39 Surprisingly, the effect of the own country-product quota dummy is positive and significant. This may reflect the fact that the\nMFA quota is endogenous to the export flows, i.e. it was more likely to be imposed when a country-product had experienced\nsignificant", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["raw data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000068", "page": 28, "chunk": 0, "title": "are trade preferences a panacea the export impact of the african growth", "pdf_url": "https://local/prwp/are-trade-preferences-a-panacea-the-export-impact-of-the-african-growth.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "raw data", "label": "VAGUE_DATA", "score": 0.6332895159721375, "start": 1042, "end": 1050, "probe_score": 0.8098, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "systems. The PHP would provide US$ 785,000 for technical support and US$ 1.34 million for project\nmanagement. The total cost o f the PHP i s US$ 34.2 million, o f which IDA would extend US$ 32 million.\nThe Government would provide US$ 2.2 million. The Government i s likely to approach bilateral donors\nto secure additional funds to provide housing for the remaining Puttalam IDPs once the PHP demonstrates\nsuccess.\n\n\n**3** **Key Performance Indicators**\n\n\n_9._ Expected key performance indicators include:\n\n\nNumber o f housing units constructed and occupied within specified time and allocated budget;\nNumber o f families provided safe drinlung water; and\nNumber o f settlement plans designed and implemented.\n\n. . .\n\n**4** **Project Components**\n\n\n**Component One:** Housing Assistance (U$ 16.1 million)\n\n\n10. IDA funds would be apportioned across the 141 refugee camps in Puttalam in proportion to the\nhousing caseload. The Puttalam Project Unit (PPU) ranked refugee camps using three social criteria, i.e.,\n(i) percentage o f temporary thatched houses in each camp; (ii) percentage o f IDP households who\npossessed land in each camp; and (iii) percentage - f households that opted to settle in Puttalam as\nrecorded in the United Nations High Commissioner for Refugees (UNHCR) supervised census o f IDPs\nliving in refugee camps in Puttalam in April, 2006.\" The socially ranked camps were then screened in\nterms o f three environmental indicators, i.e., proclivity to flooding, land surface and quality o f\nenvironment. The ranking o f refugee camps was done with the intent to phase the PHP over four years.\nAll 141 refugee camps would be covered.\n\n\n11. A household within a refugee camp would have to meet certain criteria to be entitled to", "output": {"entities": {"named_data": [], "descriptive_data": ["census o f IDPs"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000023", "page": 8, "chunk": 0, "title": "Sri Lanka - Puttalam Housing Project", "pdf_url": "http://documents1.worldbank.org/curated/en/194731468104646411/pdf/38147core.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "census o f IDPs", "label": "DESCRIPTIVE_DATA", "score": 0.845741868019104, "start": 1291, "end": 1306, "probe_score": 0.8104, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n\n### **Child health,** **vaccination and** **nutrition**\n\n\n\n\n\n\n\n\n\nTimely initiation\nof breastfeeding\n(within one hour\n<u>of delivery)</u>\n\nExclusive\nbreastfeeding\n<u>under 6 months</u>\n\n\n\n0-23\n153/274 57%\nmonths\n\n\n0-5\n15/38 37%\nmonths\n\n\n\n\n- Excluding Estonia, Hungary\n\n\nBreastfeeding practices for infants and young\nchildren directly influence their nutritional health\nduring the first two years of life and play a crucial\nrole in child survival. From the survey results, the\nproportion of children 0-23 months who had timely\ninitiation of breastfeeding was 57% and the rate of\nexclusive breastfeeding for the first six months of\nlife was 37% in the region. Data need to be\ninterpreted with caution given the very low number\nof respondents.\n\n\nTwo doses of measles vaccine are recommended\nfor optimal protection against measles; the survey\nassessed therefore first and second dose measles\nvaccination coverage in children aged 9 months to\n5 years. In average, 83% of children received at\nleast one measles vaccine, similar to results from\n2023 when 84% of children had received at least\none dose. Coverage was lowest in Romania with\n71% where respondents reported also greater\n\n\n\nconstraints in accessing health services. Vaccine\ncoverage increased notably in Moldova, Czechia\nand Bulgaria compared to 2023. In comparison,\nmeasles vaccination coverage within Ukraine\nreached 92% for the 1st dose of measles vaccine\nand 87% for second dose <sup>8</sup> (WHO, 2023).\n\n\nRegionally, only 54% of all children received the\nrecommended second measles vaccine.\nVaccination coverage is below the 95% target\nrequired to interrupt community transmission of\nmeasles.\n\n\n**<u>% OF CHILDREN RECEIVED AT LEAST ONE MEASLES</u>**\n**VACCINE**\n\n\n2023 2024\n\n\n\nData need to be interpreted", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey results"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000004", "page": 17, "chunk": 0, "title": "NAVIGATING HEALTH AND WELL BEING CHALLENGES FOR REFUGEES FROM UKRAINE   2nd Edition", "pdf_url": "https://local/jad_paddy_docs/navigating health and well-being challenges for refugees from ukraine - 2nd edition.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey results", "label": "VAGUE_DATA", "score": 0.606472373008728, "start": 527, "end": 541, "probe_score": 0.993, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " camps. It was estimated that twice as many were in urban\ncentres. Kenya had over 3,500 Ethiopians belonging to this group residing in urban areas.\nBecause of a border conflict between Eritrean and Ethiopia, the implementation of cessation\nof status was delayed in Sudan. Between December 2000 and March 2001, UNHCR was\nable to assist the return of more than 10,000 Ethiopian refugees affected by the decision.\nRefugees who opted to remain in Sudan or Kenya were advised to approach governments\nin their countries of asylum to authorise their continued stay in those countries through\nregular immigration channels or to have their claim for continued asylum assessed. Between\n1993 and 1998, more than 70,000 Ethiopian refugees in Sudan and some 50,000 in Kenya\nwere assisted to return home. Nearly 30,000 Ethiopian refugees remain in the Horn of\nAfrica region. Political tensions in Ethiopia during 2001 provoked small-scale movements of\nEthiopian refugees, mainly students, to neighbouring countries.\n\n### **IV. The Great Lakes region**\n\n**Refugee Population in the Great Lakes region**\n_(Statistics as at 1st January 2002, by country of asylum, including refugees not assisted by UNHCR)_\n\nUnited. Rep of Tanzania 668,082 Rwanda 34,267\nDem. Rep. of Congo 362,012 Burundi 27,896\nRepublic of Congo 110,724\n\n\n11", "output": {"entities": {"named_data": [], "descriptive_data": ["Refugee Population in the Great Lakes region", "Statistics as at 1st January 2002"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000498", "page": 10, "chunk": 1, "title": "UNHCR Africa Fact Sheet Jun 2002", "pdf_url": "https://reliefweb.int/attachments/471decc6-7111-3318-a484-6e8941b7e9e5/58B1D6BED720162285256C8A0072930A-unhcr-afr-30jun.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Refugee Population in the Great Lakes region", "label": "DESCRIPTIVE_DATA", "score": 0.5562531352043152, "start": 1041, "end": 1085, "probe_score": 0.8986, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Statistics as at 1st January 2002", "label": "DESCRIPTIVE_DATA", "score": 0.6797003746032715, "start": 1090, "end": 1123, "probe_score": 0.8028, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012073", "page": 62, "chunk": 2, "title": "Ethiopia - Fifth Telecommunications Project", "pdf_url": "https://documents.worldbank.org/curated/en/379241468252322923/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " shows teachers\nrespond to family income when building expectations of student outcomes, and these expectations\nin turn impact educational attainment (Gershenson, Holt, and Papageorge 2016). The effects of\nteacher expectations on student outcomes may even start as early as kindergarten (Speybroeck et al.\n2012).\n\n\nSuch stereotyping presents a typical example of a mental model (World Bank 2014). By shaping their\nopinion of a certain socioeconomic class, teachers contribute to a cycle whereby both the teacher and\nthe students themselves underestimate the ability of a poor student (Guyon and Huillery 2014).\nTeachers might directly or indirectly convey their biased expectations of student ability by modifying\nhow they teach, evaluate, and advise stigmatized students, or those students may modify their own\nexpectations and behavior to conform with teacher bias (Ferguson 2003; Jussim and Harber 2005;\nLareau 2011; Lareau and Weininger 2008).\n\n### 4. Caveats\n\nThere are two key limitations to this work. We discuss each in turn:\n\n\n_Sampling_ **:** In this work the emphasis was on external validity. To this end, over 16,000 teachers across\neight countries and five regions were interviewed. However, to achieve this breadth of coverage, the\nteam had to leverage ongoing data collection. As such, the size of the sample and the precise sampling\nstrategy do not match across all countries. Despite this, the total sample size for each country ranges\nbetween 200 teachers in Zanzibar and more than 9,600 teachers in Pakistan. The number of schools\nvisited in each country ranges from 94 in Zanzibar to more than 3,000 in Pakistan (details in Table\n1). As such, sample sizes by country are defensible though not nationally representative.\n\n\n10", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["ongoing data collection"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007388", "page": 11, "chunk": 1, "title": "wps8454", "pdf_url": "https://local/prwp/wps8454.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "ongoing data collection", "label": "VAGUE_DATA", "score": 0.5542400479316711, "start": 1268, "end": 1291, "probe_score": 0.0029, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "types of programs was done randomly, they were quite comparable. In our conversations with\nthe director of the SERP program as well as with the SERP facilitators, we found that they were\nkeen to work on their own, but did not always speak the local language fluently. <sup>23</sup> [^23: In these instances, they were paired with individuals from within the SERP team who had a stronger grasp of\nHindi.] As a result,\nthey were generally given strictly defined and narrow tasks to perform in a specific amount of\ntime, with clear deliverables.\n\n\nA Comparison of Facilitators’ Characteristics\n\n\nWe consistently find a distinct difference between the observable characteristics of external and\ninternal facilitators. External facilitators were younger and more educated than local facilitators\n(Table 3, Panel A). They had fewer children, were less likely to own land and were less reliant\non agriculture as a source of income (Table 3, Panel A). Our qualitative observations of these\nfacilitators confirmed these patterns. We observed that the facilitators from Andhra Pradesh\nspoke up to three languages (Hindi, Telugu and English) and talked, freely and unprompted,\nabout their own personal path out of poverty and their professional experiences. They presented\nthemselves as a group of disciplined anti-poverty professionals whose best qualifications were\ntheir own personal journeys of transformation. In rural Rajasthan they stood out for their\ndistinctive way of talking and dressing as well as for their confident demeanor. This was not seen\nin the case of the local facilitators, who appeared to fit in much more easily with the prevailing\nnorms.\n\n\nIn our survey data, however, we do not find an “experience gap”: both external and internal\nfacilitators seemed to have similar number of years of experience (Table 3, Panel A). There were\nhowever, significant differences in reported income (Table 3, Panel A). According to official\npolicy, external facilitators were paid Rs. 1,000 per day, and worked for 30 - 45 days at a stretch", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006991", "page": 12, "chunk": 0, "title": "wps7996", "pdf_url": "https://local/prwp/wps7996.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7526588439941406, "start": 1662, "end": 1673, "probe_score": 0.8021, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " surroundings are safe; the Southern\nstates are considered safer than the north. In addition, a lack of clarity regarding responsibilities and governance\nstructures for the design and implementation of protocols for responding to sexual harassment in public transport\nlimits the possibility of appropriately responding to survivors. Sexual harassment constitutes a barrier to gender\nequality, and directly impacts women’s access to economic opportunities. According to data from the International\nLabor Organization, a lack of safe transport reduces the probability of women accessing economic opportunities by\n16.5 percent.\n\n\n15 In 2020, the regional rate was 18.7 fatalities per 100,000 inhabitants, which is higher than the national rate (15.5) (DATASUS data).\n16 Looking at the formal jobs of the Region, 69 percent of the people that receive more than ten minimum wages, on average, are men. Meanwhile,\n94 percent of indigenous or black women receive less than 3 minimum wages. Data Source: RAIS, 2019.\n17 Gender-disaggregated mobility data for Foz do Río Itajaí were collected during the preparation of the Stakeholder Engagement Plan and other\nproject-related documents.\n18 Data derived from PNAD-Contínua (2019) State of Santa Catarina.\n19 Haydée Svab, Marina Kohler Harkot, and Beatriz Moura Dos Santos, _A Baseline Study of Gender and Transport in Sao Paulo, Brazil: Present Initiatives_\n_to Improve Women’s Mobility (English)_ (Washington, DC: World Bank, 2021).\n20 _Brazil - Improving Mobility and Urban Inclusion in the Amazonas Corridor in Belo Horizonte Project_ (Washington, DC: World Bank).\n21 Data reflect cases of harassment in public spaces without disaggregation. However, given the trend in Brazil and the Region, it can be inferred\n<u>that in the Santa Catarina Region, more women are also survivors of sexual harassment.</u>\n\n\nPage 11 of 77", "output": {"entities": {"named_data": ["DATASUS data", "RAIS", "PNAD-Contínua"], "descriptive_data": ["data from the International\nLabor Organization", "Gender-disaggregated mobility data for Foz do Río Itajaí"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000182", "page": 15, "chunk": 2, "title": "Brazil - Integrated Sustainable Mobility Project in the Foz do Rio Itajaí Region", "pdf_url": "https://documents1.worldbank.org/curated/en/099032624162515430/pdf/BOSIB-60d57288-4e09-4519-ae6c-ffdc0037e0b1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from the International\nLabor Organization", "label": "DESCRIPTIVE_DATA", "score": 0.6848661303520203, "start": 469, "end": 515, "probe_score": 0.9798, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "DATASUS data", "label": "NAMED_DATA", "score": 0.8314249515533447, "start": 749, "end": 761, "probe_score": 0.9555, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "RAIS", "label": "NAMED_DATA", "score": 0.6682130694389343, "start": 996, "end": 1000, "probe_score": 0.9978, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Gender-disaggregated mobility data for Foz do Río Itajaí", "label": "DESCRIPTIVE_DATA", "score": 0.6577163934707642, "start": 1011, "end": 1067, "probe_score": 0.9579, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "PNAD-Contínua", "label": "NAMED_DATA", "score": 0.7534900903701782, "start": 1199, "end": 1212, "probe_score": 0.9572, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\n**Figure 3: Implementation Arrangements**\n\n\n**B. Results Monitoring and Evaluation Arrangements**\n\n\n73. **The proposed SNSOP will develop a comprehensive M&E framework and plan, building on the existing ones**\n**under the SSSNP.** The SNSOP will employ an innovative M&E system that relies primarily on electronic data collection to\nbe stored and managed in the MIS, building on the M&E system using the Geo-Enabling Initiative for Monitoring and\nSupervision (GEMS) developed under SSSNP to allow for real time data collection and analysis, thus improving the\nefficiency and reducing cost of M&E. M&E activities will also be embedded in project activities where possible to minimize\nthe burden on field-based staff. These flexible, remote arrangements allow the M&E system to adapt to various\ncircumstances in South Sudan’s FCV context. Key M&E activities will include Registration Lessons Learned surveys that\nwill assess the effectiveness of targeting and registration and identify areas for improvement. These surveys will provide\nbaseline information on key demographics and socioeconomic indicators that will be tracked over the course of the\nproject. There will also be Post Distribution Monitoring to monitor project implementation, mainly on payments under\ncomponents 1 and 2. LIPW and complementary social measure activities will be routinely monitored to ensure quality\nand assess results. Citizen engagement indicators will be monitored routinely, and the M&E plan will ensure the use of\ndiverse tools and methods (i.e., surveys, Focus Group Discussions, Key Informant Interviews) to develop a strong feedback\n\n\nPage 35 of 74", "output": {"entities": {"named_data": [], "descriptive_data": ["Registration Lessons Learned surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 39, "chunk": 0, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Registration Lessons Learned surveys", "label": "DESCRIPTIVE_DATA", "score": 0.7949617505073547, "start": 962, "end": 998, "probe_score": 0.0788, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " (2024) Hosts (2023)\n\n\n96%\n92%\n86%\n\n\n\nOverall\n\n\nMale\n\n\nFemale\n\n\nWith severe psychological\n\ndistress\n\n\nWith a disability\n\n\nSource: Survey data, SAG estimates\n\n\n\n64%\n\n\n67%\n\n\n63%\n\n\n57%\n\n\n\n72%\n\n\n\n\n\n49%\n\n\n\n\n\n\n\nTechnical or\n\nVocational\n\n\n\nBachelor's Master's Doctoral\n\n\n\n30%\n\n\n\nLower\nsecondary or\n\nbelow\n\n\n\nSource: Survey data, SAG estimates\n\n\n\n**11**", "output": {"entities": {"named_data": [], "descriptive_data": ["Survey data", "Survey data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 10, "chunk": 1, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Survey data", "label": "DESCRIPTIVE_DATA", "score": 0.5962149500846863, "start": 130, "end": 141, "probe_score": 0.9985, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Survey data", "label": "DESCRIPTIVE_DATA", "score": 0.5031179189682007, "start": 309, "end": 320, "probe_score": 0.9994, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "∗ ≥Θ𝜃𝜃\n\n\n\n**𝑤** <sup>**𝑖**</sup> ∗ < Θ𝜃𝜃\n\n**𝑖** 𝑖𝑖∗ ≥Θ𝜃𝜃\n\n\n\n<u>𝐼𝐼</u>\n\n<u>2 ∑𝑖𝑖=1</u> <u>𝜶𝜶𝑖𝑖 �𝜃𝑖𝜃</u> 𝑖 − 𝜃𝑖𝜃∗\n\n~~𝐼~~\n\n\n\nNote that because every vehicle trade consists of two trade legs and since our algorithm identifies the first\n\n\nleg of any vehicle trade, the share of trades that we identify is multiplied by two.\n\nUnder the null hypothesis that is, in excess of what one would expect under𝜑𝜑 = 0, since 𝜑𝜑 captures the excess clustering of trades at particular trade sizes, H0.\n\nWe set provides little evidence of a vehicle trade. Θ𝜃𝜃 to 0.05 to remove trades which are relatively common across the entire data set, so 𝑛𝑛𝑖𝑖 = 2\n\nGiven that hypotheses testing literature (Efron (2007), Wakefield, J. (2007)), which has been extensively applied to 𝐼𝐼is large, it is important to recognize there are 𝐼𝐼 hypotheses, relating our approach to the multiple\n\n\ngenomic sequencing and chromosome segmentation. However, in this literature, because of\n\n12", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data set"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000247", "page": 14, "chunk": 1, "title": "decrypting new age international capital flows", "pdf_url": "https://local/prwp/decrypting-new-age-international-capital-flows.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data set", "label": "VAGUE_DATA", "score": 0.537267804145813, "start": 612, "end": 620, "probe_score": 0.3438, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and a Compensation and\nReparation Authority (CRA). Previous experience suggests that any such process must be led and\nowned by the South Sudanese in order to open the road to sustainable peace. Correctly connecting\nthe dots between humanitarian and development programmes and frameworks will be equally\nimportant to support this process.\n\nDespite recent achievements, the long road to peace has only just begun. All parties will have to be\nfully engaged and committed to heal the wounds that have deepened or been opened during this\nconflict, and to ensure that South Sudanese citizens can live without fear and want.\n\n\n_For more information, contact the South Sudan Protection Cluster at_\n\n_<u>[protectionclustersouthsudan@gmail.com.](mailto:protectionclustersouthsudan@gmail.com)</u>_\n\n\n[69 Associated Press, “South Sudan: Ruling Party’s Leadership Secretariat Dissolved”, http://news.yahoo.com/south-sudan-](http://news.yahoo.com/south-sudan-ruling-partys-leadership-secretariat-dissolved-133441258.html)\n<u>[ruling-partys-leadership-secretariat-dissolved-133441258.html, 17 October 2015.](http://news.yahoo.com/south-sudan-ruling-partys-leadership-secretariat-dissolved-133441258.html)</u>\n70 Center for Civilians in Conflict, _Within and Beyond the Gates: The Protection of Civilians by the UN Mission in South_\n_Sudan_, October 2015, p. 22.\n71 During its 29th session on 2 July 2015, the Human Rights Council adopted a resolution (A/HRC/29.L8) requesting OHCHR\nto undertake a fact-finding mission and a comprehensive investigation into alleged serious violations and abuses", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000601", "page": 30, "chunk": 1, "title": "Protection Trends South Sudan No 6 | July-September 2015 - South Sudan Protection Cluster, November 2015", "pdf_url": "https://reliefweb.int/attachments/589205c5-62ff-3033-8221-c68e4b07017a/protection_trends_paper_no_6_jul-sep_2015_final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "EHNRI/<br>NNP/ Part<br>2.3/ Oper<br>Research /C5|||||Actual|||||||||\n|||||||||||||||||\n|Engage a firm to study CBN service<br>delivery skills of health extension<br>workers and community health<br>volunteers and make<br>recommendations for improvements|EHNRI|EHNRI/<br>NNP/ Part<br>2.3/ Oper<br>Research /C6|CQS|Lump sum|50,000.00|Post|Plan|12/3/2010||12/17/2010|1/14/2011|1/14/2011||||\n|Engage a firm to study CBN service<br>delivery skills of health extension<br>workers and community health<br>volunteers and make<br>recommendations for improvements|EHNRI|EHNRI/<br>NNP/ Part<br>2.3/ Oper<br>Research /C6|||||Actual|||||||||\n|||||||||||||||||\n|Engage a firm to assess CBN data,<br>data flow, and data utilization,<br>including data validation|EHNRI|EHNRI/<br>NNP/ Part<br>2.3/ Oper<br>Research /C7|CQS|Lump sum|50,000.00|Post|Plan|12/3/2010||12/17/2010|1/14/2011|1/14/2011||||\n|Engage a firm to assess", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["CBN data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020140", "page": 2, "chunk": 4, "title": "Ethiopia - Nutrition Project : procurement plan for goods for year 2010-2011", "pdf_url": "https://documents.worldbank.org/curated/en/922211468255281901/pdf/585070PROP0P101ement0Plan0201012011.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "CBN data", "label": "VAGUE_DATA", "score": 0.5775894522666931, "start": 671, "end": 679, "probe_score": 0.0267, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " institutions, (b) reestablishing access to basic services,\n(c) restoring productive capacities, and (d) nurturing effective partnership. <sup>65</sup> [^65: Partnership for Resilience and Recovery Framework.] Initial focus areas include\nYambio, Torit, Aweil, Wau, Rumbek, Bor, and Yei. The ECRP shares PfRR’s overall objective and contributes\nto three of PfRR’s four focus pillars. The ECRP complements PfRR as some of the ECRP’s target areas\nconstitute the ‘catchment areas’ of people returning from PfRR’s target urban centers. At the operational\nlevel, the ECRP will help develop the community development plans that can feed into PfRR’s broader\nResilience and Recovery Framework, or if they have already been developed by the PfRR partners, the\nproject will utilize them. The ECRP will also consult with the Champion Group formed by PfRR which\ncomprises key civil society organizations, utilize state-level resilience assessment and strategy where\nrelevant, and ensure that the project is part of the PfRR results matrix. Once PfRR’s resilience matrix is\ndeveloped, the project will look to harmonize it with the vulnerability index if feasible. IOM is an active\nmember of the PfRR Technical Engagement Group, which meets on a monthly basis to guide strategies,\npartnerships, and coordination within the partnership areas. Partnership with IOM therefore allows for\nmutually reinforcing synergies between the ECRP and programs under PfRR.\n\n\n49. **The project also complements ongoing local governance and service delivery projects in South**\n**Sudan.** Based on successful experience of sustainable O&M of water points in Torit and Rumbek, the\nNetherlands will scale up its Sustainable WASH for Resilience Program (in partnership with the United\nNations Children’s Fund in Rumbek, Torit, Bor, and Yambio) that leveraged supply chain operated by the\nprivate sector and civil society organizations (CSOs", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 31, "chunk": 1, "title": "South Sudan - Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/824121596765983121/pdf/South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nRoads and Employment Project (P160223)\n\n\n**ANNEX 1: DETAILED PROJECT DESCRIPTION**\n\n\n**COUNTRY : Lebanon**\n**Roads and Employment Project**\n\n\n1. The Project includes three components namely: (i) Road Rehabilitation and Maintenance; (ii)\nImproving Road Emergency Response Capacity; and (iii) Capacity Building and Implementation\nSupport.\n\n\n**Project Component 1: Roads Rehabilitation and Maintenance (US$185 million)**\n\n\n2. This component will include the rehabilitation and maintenance of 500 km of primary, secondary and\ntertiary roads, including road safety and spot improvement. The current road classification of the\nnetwork depends on the roads’ functional characteristics: A primary road is a road that connects two\nLebanese regions, a secondary road connects to districts or Casa, and a tertiary road connects towns\nwithin a Casa. The geometric characteristics of the roads, and particularly road width, is a function of\nits classification. While not all roads characteristics are based on the same standards, even within the\nsame category, the general width and observed/estimated road condition is according to table 1.1\nbelow. The ongoing visual survey will permit a better assessment of these characteristics and\nconditions.\n\n\n**Table 1.1. National Road Categories, Characteristics, and Observed Traffic and Road Condition**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Road Category|Definition|Width in<br>Meters|Traffic Range (ADT)|Roughness Range<br>(IRI)|\n|---|---|---|---|---|\n|Primary Road<br>|Links two Lebanese<br>Regions|14|>10,000, most sections in<br>the 20,000 to 30,000<br>range|4 to 5|\n|Secondary Road<br>|", "output": {"entities": {"named_data": [], "descriptive_data": ["visual survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 54, "chunk": 0, "title": "Lebanon - Roads and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/210611486651815142/pdf/Lebanon-Roads-Employment-PAD-P160223-01262017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "visual survey", "label": "DESCRIPTIVE_DATA", "score": 0.8794056177139282, "start": 1168, "end": 1181, "probe_score": 0.5105, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " centers assessed monthly<br>(using check list) treatment, isolation &<br>quarantine|Number of centers<br>assessed monthly|monthly<br>|<br>COVID-19<br>report<br> <br>|routine data<br>|MOPH<br>|\n|<br>Establishment of monitoring and<br>evaluation system for COVID-19 <br> <br>|Establishment of a COVID-<br>19 M&E system|once<br>|<br>COVID-19<br>report<br>|routine data<br>|MOPH<br>|\n\n\n\nPage 34", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["routine data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000039", "page": 38, "chunk": 1, "title": "Chad - COVID-19 Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/717781588366403375/pdf/Chad-COVID-19-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "routine data", "label": "VAGUE_DATA", "score": 0.5290613770484924, "start": 167, "end": 179, "probe_score": 0.0117, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Project** **Manaeem2nt** <sup>**and**</sup> <sup>million)</sup> administrative data appropriate, and clear in\n\n\n\ndefining the and\n**Innovative Activities**\n\n\n\nresponsibilities of all parties;\nNaCSA retains competent\n**(a) Capacity Building**\n\n\n\nstaff;\n\n                                             - Other governnent and donor\n**(b)** **Information and**\n\nsupport mobilized for\n\n\n\nsupport mobilized for\n**Sensitization**\ndecentralization to\ncomplement NaCSA efforts;\n(c) **Monitoring and**\n\n\n\n**Evaluation**\n\n\n\n**(d)** **Technical Assistance**\n\n\n(e) **Operating** Expenses\n\n\n\n-28", "output": {"entities": {"named_data": [], "descriptive_data": ["administrative data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009739", "page": 32, "chunk": 1, "title": "Uganda - Transport Rehabilitation Project (Vol. 1 of 2)", "pdf_url": "https://documents.worldbank.org/curated/en/219881468760234344/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "administrative data", "label": "DESCRIPTIVE_DATA", "score": 0.6927050352096558, "start": 64, "end": 83, "probe_score": 0.562, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "communities benefit from strengthened services and systems over time. For refugees,\nfostering their self-reliance and enhancing their skills and education while in exile also better\nprepares them for solutions, notably voluntary repatriation, and can make these solutions\nmore sustainable.\n\n\n50. Against this background, in support of efforts by host countries, and as appropriate,\ninterested States and relevant stakeholders will make available funding and capacity to:\ninclude refugees in national systems; expand and strengthen such systems for the benefit of\nhost communities and refugees; and support approaches that can be sustained over the\nmedium term, from a financial, economic, environmental, and social standpoint, until\nsolutions can be achieved.\n\n\n51. The following areas are of particular importance:\n\n\n**_2.1_** **_Education_**\n\n\n52. In line with national education planning and the sustainable development agenda, <sup>30</sup>\ninterested States and relevant stakeholders <sup>31</sup> will assist host countries to include refugee\nchildren and youth in national education systems, where appropriate, expanding and\nstrengthening them for the benefit of both local communities and refugees. Special efforts\nwill be made to minimize the time refugee children and youth spend out of school, ideally a\nmaximum of three months. Innovative financing mechanisms to increase investment in\neducation will also be explored.\n\n\n53. Specific actions to achieve this could include:\n\n\n - support to expand and/or enhance educational facilities and capacity (e.g. infrastructure;\nteaching staff; and including refugee data in education management information\nsystems); <sup>32</sup>\n\n - measures to meet the specific needs of refugee children and youth, especially girls, (e.g.\nthrough accelerated education and other flexible learning programmes, as well as\nadapted approaches to cope with psychosocial trauma) and overcome obstacles to their\nenrolment and attendance (e.g. safe transport; documentation; language and literacy\nsupport; and bridging programmes);", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["refugee data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000731", "page": 8, "chunk": 0, "title": "The global compact on refugees- Zero Draft (as at 31 January 2018)", "pdf_url": "https://reliefweb.int/attachments/6b1178fe-8952-3167-916e-efc4a8bcc1bb/Zero-Draft.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "refugee data", "label": "VAGUE_DATA", "score": 0.7172821164131165, "start": 1611, "end": 1623, "probe_score": 0.1258, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Food Programme (WFP), the United Nations Children’s Fund (UNICEF), the\nFood and Agriculture Organization, the Islamic Development Bank, the United States Agency for Development, and the\nNorwegian Refugee Council) which were mainly focused on providing food to vulnerable populations. At present, the\nscale and funding of SSN programs remains inadequate to protect most poor and vulnerable groups. According to the\nlatest available data, only 32.7 percent of the poorest 20 percent of households are covered by any SSN program. In\naddition, the Government’s share of spending in SSN is quite limited, as Djibouti only spends 0.18 percent of its GDP on\n\n\n10 Hallegatte et al, “Shockwaves: Managing the Impacts of Climate Change on Poverty”, World Bank, 2016.\n11 Wooden et al, “ _Impact of Weather Shocks on MENA Households_ ”, World Bank, 2014.\n12 _Djibouti’s First NDC_, August 2015, p2.\n\n\nPage 8 of 44", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["latest available data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000154", "page": 12, "chunk": 2, "title": "Djibouti - Integrated Cash Transfer and Human Capital Project", "pdf_url": "http://documents1.worldbank.org/curated/en/893891558231269265/pdf/Djibouti-Integrated-Cash-Transfer-and-Human-Capital-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "latest available data", "label": "VAGUE_DATA", "score": 0.6453527212142944, "start": 415, "end": 436, "probe_score": 0.011, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "6 percent and Gaza growing by 1.4 percent. It is important to note, however, that to a\nlarge extent, this is a base effect as the first half of 2018 was a particularly weak period.\n2 World Bank COVID-19\n3 Gender-based gaps in unemployment are stark, with female unemployment at 50 percent compared to male unemployment\nat 25 percent.\n[http://www.pcbs.gov.ps/Downloads/book2433.pdf (accessed October 27, 2019).](http://www.pcbs.gov.ps/Downloads/book2433.pdf)\n4 When considering nonmonetary measures of poverty, 58 percent of female-headed households (FHHs) compared to 41\npercent of male-headed households are in the bottom 40 percent. (Atamanov, A., and N. Palaniswamy. 2019. “Analysis of\nElectricity Sector Using Local Government Performance Assessment Data.”)\n5 Value added tax and import duties collected by the GoI on behalf of the PA should be transferred monthly based on an\narrangement instituted by the Paris protocol.\n6 Differences between both sides on additional deductions by Israel on account of PA payments to prisoners, averaging around\nUS$12 million per month, continue to be unresolved.\n\n\nPage 8 of 74", "output": {"entities": {"named_data": ["Local Government Performance Assessment Data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000132", "page": 11, "chunk": 2, "title": "West Bank and Gaza - Phase 1 of the Multiphase Programmatic Approach, Advancing Sustainability in Performance, Infrastructure and Reliability of Energy Sector Project", "pdf_url": "http://documents1.worldbank.org/curated/en/778661588298453505/pdf/West-Bank-and-Gaza-Phase-1-of-the-Multiphase-Programmatic-Approach-Advancing-Sustainability-in-Performance-Infrastructure-and-Reliability-of-Energy-Sector-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Local Government Performance Assessment Data", "label": "NAMED_DATA", "score": 0.7521072626113892, "start": 714, "end": 758, "probe_score": 0.9841, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " to return. Since September 2017, over 79,311 Burundians have been assisted by the United Nations High\nCommissioner for Refugees (UNHCR) to return, mostly from Tanzania. A similar number is estimated to have come back\nof their own volition. Available data suggests that returnees face severe difficulties to restore their livelihood. <sup>12</sup> [^12: See UNHCR 31 October 2019. “Voluntary Repatriation of Burundian Refugees” at _[data2.unhcr.org/en/documents/download/72174](https://data2.unhcr.org/en/documents/download/72174)_]\nAdditional inflows of both refugees and returnees are expected in 2020. <sup>13</sup> [^13: For instance, UNHCR contingency planning is for the refugee population to increase to up to 110,000 in 2020.]\n\n\n**Figure 1: Location and population of refugees in Burundi and number of Burundian refugees in neighboring countries**\n\n\n_Source: UNHCR. Data as of September 30, 2019._\n\n\n8 UNHCR (2018). Congolese Situation: Responding to the needs of displaced Congolese and Refugees. Annex – Burundi. Supplemental\nAppeal. _[http://reporting.unhcr.org/sites/default/files/2018%20congolese%20Situation%20SB%20-%20Burundi.pdf](http://reporting.unhcr.org/sites/default/files/2018%20congolese%20Situation%20SB%20-%20Burundi.pdf)_\n9 Three of the four proposed project target provinces (Muyinga, Ruyigi and Cankuzo) are among the most heavily environmentally\ndegraded in the country (World Bank, 2018).\n10 Refugees sell food assistance products that are less common in the host community such as rice and oil, in return for fresh vegetables\n(cassava and beans) (WFP/UNHCR 2014).\n11 See IOM May 2019, “Overview of the Humanitarian Situation of Internally Displaced Persons in", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Data as of September 30, 2019"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000110", "page": 13, "chunk": 1, "title": "Burundi - Integrated Community Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/644221583204472551/pdf/Burundi-Integrated-Community-Development-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data as of September 30, 2019", "label": "VAGUE_DATA", "score": 0.5810918211936951, "start": 874, "end": 903, "probe_score": 0.9997, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "literature on how firing costs can affect unemployment, depending on labor supply and\n\ndemand elasticities (see, e.g., Lyungquist 2002; Garibaldi and Violante 2005).\n\n\n\ndemand elasticities (see, e.g., Lyungquist 2002; Garibaldi and Violante 2005).\n\n\n\ndemand elasticities (see, e.g., Lyungquist 2002; Garibaldi and Violante 2005).\n\nThe fourth and final control in this study covers the ratio of private credit by deposit\n\nmoney to GDP, covering the years 2000 through 2016 and downloaded from the Financial\n\n\n\nThe fourth and final control in this study covers the ratio of private credit by deposit\n\nmoney to GDP, covering the years 2000 through 2016 and downloaded from the Financial\n\nDevelopment and Structure Database. This control helps identify the partial correlation\n\n\n\nmoney to GDP, covering the years 2000 through 2016 and downloaded from the Financial\n\nDevelopment and Structure Database. This control helps identify the partial correlation\n\nbetween unemployment and the incidence of the digital economy when the proxy for the\n\n\n\nDevelopment and Structure Database. This control helps identify the partial correlation\n\nbetween unemployment and the incidence of the digital economy when the proxy for the\n\nlatter is the share of the adult population that reports paying bills over the internet. In fact,\n\n\n\nbetween unemployment and the incidence of the digital economy when the proxy for the\n\nlatter is the share of the adult population that reports paying bills over the internet. In fact,\n\nas shown in the Appendix tables, in most of our estimation samples there is a positive\n\n\n\nlatter is the share of the adult population that reports paying bills over the internet. In fact,\n\nas shown in the Appendix tables, in most of our estimation samples there is a positive\n\ncorrelation between internet payments and bank credit.\n\n\n\ncorrelation between internet payments and bank credit. _D._ _Instrumental Variables_\n\n\n\n_D._ _Instrumental Variables_\n\n\n\n_D._ _Instrumental Variables_\n\nAs discussed further below, to further assess the partial correlation of", "output": {"entities": {"named_data": ["Financial\n\nDevelopment and Structure Database", "Development and Structure Database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001689", "page": 13, "chunk": 0, "title": "incidence of the digital economy and frictional unemployment international evidence", "pdf_url": "https://local/prwp/incidence-of-the-digital-economy-and-frictional-unemployment-international-evidence.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Financial\n\nDevelopment and Structure Database", "label": "NAMED_DATA", "score": 0.710548996925354, "start": 674, "end": 719, "probe_score": 0.9989, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Development and Structure Database", "label": "NAMED_DATA", "score": 0.6157302260398865, "start": 1039, "end": 1073, "probe_score": 0.9919, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "ESHS/OHS/GB V/VAC Codes of Conduct and Action Plan\nINSTA-PUMPS \nSevic-1- & l*stale2o \nr Ills\nENGINEERING \nSee \nCivi Engner \non\nLIMITED \nTc\n%a-Tech\nTHE ULTIMATE STAINLESS STEEL PUMP\nInsta-Pumps Eng. Ltd. P.o. Box 33248-00600, Nairobi. Tel:,(+254 20)4405273L4. Fax: (+254 02)8566183. Info@insta-pumps.com\nN IagCr s C \no f \nC Conduct\nManagers at all levels have a responsibility to uphold the company's commitment to implementing the\nESHS and OHS standards, and preventing and addressing GBV and VAC. This means that managers\nhave an acute responsibility to create and maintain an environment that respects these standards, and\nprevents GBV and VAC. Managers need to support and promote the implementation of the Company\nCode of Conduct. To that end, managers must adhere to this Manager's Code of Conduct and sign the\nIndividual Code of Conduct. This commits them to supporting the implementation of the CESMP and the\nOHS Management Plan, and developing systems that facilitate the implementation of the GBV and VAC\nAction Plan. They need to maintain a safe workplace, as well as a GBV-free and VAC-free environment\nat the workplace and in the local community. These responsibilities include but are not limited to:\nImplementation\n1. \nTo ensure maximum effectiveness of the Company and Individual Codes of Conduct:\ni. \nProminently displaying the Company and Individual Codes of Conduct in clear view at\nworkers' camps, offices, and in public areas of the work space. Examples of areas include\nwaiting, rest and lobby areas of sites, canteen areas and health clinics.\nii. \nEnsuring all posted and distributed copies of the Company and Individual Codes of Conduct\nare translated into the appropriate language of use in the work site areas as well as", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019042", "page": 0, "chunk": 0, "title": "Kenya - Urban Water and Sanitation OBA Fund for Low Income Areas Project : Resettlement Plan (Vol. 7 of 17) : Manager's code of conduct", "pdf_url": "https://documents.worldbank.org/curated/en/844011525462651941/pdf/Managers-code-of-conduct.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">Men (51%)<br>Women (49%)|**Hosts**<br>(KIHBS<br>2015)<br>Men (52%)<br>Women (48%)|**Hosts**<br>(KIHBS<br>2015)<br>Men (52%)<br>Women (48%)|\n||Gender|Gender|Gender|Gender|Gender|Gender|Gender|\n||Age|Below 18:<br>71%<br>Above 64:<br>0.6%|Below 18:<br>61%<br>Above 64:<br>0.4%|Below 18: 60%<br>Above 64: 0.4%|Below 18:<br>45%<br>Above 64:<br>1.8%|Below 18: 32%<br>Above 64:<br>0.7%||\n||Dependency<br>ratio|1.9|1.2|1.4|0.6|0.4||\n||Women-<br>headed<br>households|66%|56%|47%|41%|32%|➢ Women and girls’ empowerment programmes in camps and urban<br>areas can help alleviate barriers to accessing socioeconomic<br>opportunities and build and maintain human capital.<br>➢ Financial inclusion programmes coupled with entrepreneurship skills,<br>business training and cash grants targeting women, especially those<br>with young dependents, can be a starting point to unlock refugee<br>women’s socioeconomic potential.|\n||Improved<br>housing|5%|3%|8%|82%|78%|➢ Scaling up permanent shelters in Kalobeyei with", "output": {"entities": {"named_data": ["KIHBS", "KIHBS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000574", "page": 5, "chunk": 1, "title": "EHAGL Knowledge summary - Kenya, World Bank - UNHCR data and evidence collaboration (2016 - 2023)", "pdf_url": "https://reliefweb.int/attachments/54e5570f-4536-4b86-9b4f-aff433eef8ad/EHAGL%20Knowledge%20summary%20-%20Kenya%20WB-UNHCR%20data%20and%20evidence%20collaboration.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "KIHBS", "label": "NAMED_DATA", "score": 0.7097033858299255, "start": 40, "end": 45, "probe_score": 0.0011, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "KIHBS", "label": "NAMED_DATA", "score": 0.6568666100502014, "start": 97, "end": 102, "probe_score": 0.0006, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " centers assessed monthly<br>(using check list) treatment, isolation &<br>quarantine|Number of centers<br>assessed monthly|monthly<br>|<br>COVID-19<br>report<br> <br>|routine data<br>|MOPH<br>|\n|<br>Establishment of monitoring and<br>evaluation system for COVID-19 <br> <br>|Establishment of a COVID-<br>19 M&E system|once<br>|<br>COVID-19<br>report<br>|routine data<br>|MOPH<br>|\n\n\n\nPage 34", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["routine data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000124", "page": 38, "chunk": 1, "title": "Chad - COVID-19 Response Project", "pdf_url": "http://documents1.worldbank.org/curated/en/717781588366403375/pdf/Chad-COVID-19-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "routine data", "label": "VAGUE_DATA", "score": 0.5290613770484924, "start": 167, "end": 179, "probe_score": 0.0117, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", 2024, Ukrainian refugees\ngained an estimated 7% in earnings having\nshifted towards better paid occupations,\npre-war Ukrainians 5%, non-Ukrainian\nforeigners 4%, and Polish citizens 1%.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n**Ukrainian refugees have been slowly**\n**closing their wage gap to Polish**\n**citizens across all wage levels.** Once\nZUS administrative data on Ukrainian\nrefugees with employment contracts is\ndivided into employee cells based on\n380 poviats, 2 sexes, 7 age groups, and\n10 main occupational groups (including\n\n\n\nunallocated), the gap in social contributions\nbases towards Polish citizens narrows.\nThe largest group (16%) is positioned\nbetween 90% and 100% of Polish citizens\n(median 93%). This is an improvement over\ntwo years, when the majority (13%) situated\nbetween only 80% and 90% (median 82%). <sup>12</sup>\n\n\n\n12 Unfortunately, the data is available in a format that is not suitable for econometric modelling and thus these are only comparisons between thousands of employee\ncells and average social contributions bases.", "output": {"entities": {"named_data": ["ZUS administrative data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 8, "chunk": 1, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "ZUS administrative data", "label": "NAMED_DATA", "score": 0.7902922034263611, "start": 368, "end": 391, "probe_score": 0.9468, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "-and-</u>\n<u>salaries-by-occupations-for-october-2022,4,8.html</u>\n\n\nGUS (2024b). Education in the school year 2023/2024 (preliminary data),\nStatistical Office in Gdańsk, <u>https://stat.gov.pl/en/topics/education/education/</u>\n<u>education-in-the-school-year-20232024-preliminary-data,13,2.html</u>\n\n\nHeller, B. H., & Mumma, K. S. (2023). Immigrant integration in the United States:\nthe role of adult English language training. American Economic Journal: Economic\nPolicy, 15(3), 407-437.\n\n\nJaumotte, M. F., Koloskova, K., & Saxena, M. S. C. (2016). Impact of migration on\nincome levels in advanced economies. International Monetary Fund.\n\n\nKleiner, M. M., & Krueger, A. B. (2013). Analyzing the Extent and Influence of\nOccupational Licensing on the Labor Market. Journal of Labor Economics, 31(2),\nS173–S202. <u>https://doi.org/10.1086/669060</u>\n\n\n46\n\n\n\nLessem, R., & Sanders, C. (2020). Immigrant wage growth in the United States:\nThe role of occupational upgrading. International Economic Review, 61(2),\n941-972.\n\n\nLewandowski, P., Górny, A., Krząkała, M., & Palczyńska, M. (2025). The Role of Job\nTask Degradation in Shaping Return Intentions: Evidence from Ukrainian War\nRefugees in Poland. IBS working paper, 01/2025. <u>https", "output": {"entities": {"named_data": ["Education in the school year 2023/2024"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 23, "chunk": 2, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Education in the school year 2023/2024", "label": "NAMED_DATA", "score": 0.5518760681152344, "start": 82, "end": 120, "probe_score": 0.2256, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " coverage, labor productivity, quality and prices but for\n\n\nthe telecommunications sector. Ramamurti (1996) used analogous indicators in _output_, _coverage_\n\n\nand labor productivity for the four Latin American telecommunications firms of his study. Saal and\n\n\nParker (2001) used similar indicators for output, employment, quality and prices _,_ but for water and\n\n\nsewerage companies of England and Wales.\n\n\nThe countries analyzed were Argentina, Bolivia, Brazil, Chile, Colombia, El Salvador,\n\n\nGuatemala, Nicaragua, Panama, and Peru. The sample consists of unbalanced panel data that\n\n\nincludes 116 firms and 1,103 firm-year observations. Each of the firms included in the sample\n\n\ncontains at least one year of pre privatization data. In fact, 98 of the 116 firms have information for\n\n\nat least the previous three years.\n\n\n10 As quality indexes vary across countries, we collected the closest indexes in order to be able to compare\ntheir evolution across time, rather than the absolute level.\n\n\n_10 of 28_", "output": {"entities": {"named_data": [], "descriptive_data": ["unbalanced panel data"], "vague_data": ["pre privatization data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003149", "page": 9, "chunk": 1, "title": "wps3936", "pdf_url": "https://local/prwp/wps3936.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "unbalanced panel data", "label": "DESCRIPTIVE_DATA", "score": 0.8585556149482727, "start": 560, "end": 581, "probe_score": 0.5486, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "pre privatization data", "label": "VAGUE_DATA", "score": 0.5256949663162231, "start": 715, "end": 737, "probe_score": 0.9349, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " monitored\nseparately and reported by the utilities on a quarterly basis.\n\n\n91. **Gender.** A baseline survey conducted in one of the districts under the RWSSP confirmed several\ncommon gender-based challenges related to WSS access. Those include (a) time burden for women and\ngirls due to unreliable and unsafe water supplies; (b) poor water quality and healthcare responsibilities\nfor children; (c) physical, social, and health risks associated with collecting water or using open toilets; and\n(d) inequitable access to information, training, and opportunities for employment in water institutions,\nparticularly in technical and decision-making roles. The baseline assessment conducted in Vosse district\nconfirmed that water collection responsibility is mainly assigned to women regardless of the water source\ntype and distance to the source. In more than 87 percent of households, women are responsible for\nfetching water in almost all age categories, except for the age category of 6–17 years, where the share of\nboys and girls who fetch water is almost equal. In addition, due to the poor healthcare services and as\nmany households defer to home-based treatment, the time and emotional burden on mothers as main\ncaregivers increases (details on the baseline assessment across the identified gender gaps are provided in\nannex 1). Women spend time on boiling and settling water to reduce the risk of getting sick, but many are\nunaware of appropriate water storage and on-site purification practices. Women and girls face\nheightened physical and health risks associated with collecting water or using open toilets in schools and\nlack of menstrual hygiene facilities in social institutions. There are also wide gender gaps in employment\nin the water sector institutions. Global data show that, on average, women account for only 18 percent\nof total staff in water institutions and 23 percent of staff in engineering and managerial positions. Evidence\nfrom Europe and Central Asian countries show similar patterns. In Tajikistan, some of the reasons for\n\n\nPage 42 of 89", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Global data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000162", "page": 45, "chunk": 1, "title": "Tajikistan - Water Supply and Sanitation Investment Project", "pdf_url": "http://documents1.worldbank.org/curated/en/932351655916461178/pdf/Tajikistan-Water-Supply-and-Sanitation-Investment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Global data", "label": "VAGUE_DATA", "score": 0.844902515411377, "start": 1771, "end": 1782, "probe_score": 0.0397, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad COVID-19 Strategic Preparedness and Response Project (P173894)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Monitoring & Evaluation Plan: PDO Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **<br>|**Definition/Description **<br>|**Frequency **|**Datasource **|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|Number of designated laboratories with<br>COVID-19 functioning diagnostic<br>equipment, test kits, and reagents per<br>MOH guidelines|Number of existing<br>laboratories with effective<br>capacity for testing COVID-<br>19 <br>|quarterly<br>|MOPH report<br>|<br>routine data<br>|<br>MOH<br>|\n|<br>Percentage of targeted acute healthcare<br>facilities with isolation capacity <br>|<br>Number of available<br>targeted acute healthcare<br>facilities with isolation<br>capacity for COVID-19<br>patients as a percentage of<br>all the target acute<br>healthcare facilities.|weekly<br>|COVID-19<br>report<br> <br>|routine data<br>|MOPH<br>|\n|Number of suspected cases of COVID-19<br>cases reported and investigated based on<br>national guidelines|<br>Number of suspected<br>effectively cases tested <br>|weekly<br>", "output": {"entities": {"named_data": ["MOPH report"], "descriptive_data": [], "vague_data": ["routine data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000124", "page": 36, "chunk": 0, "title": "Chad - COVID-19 Response Project", "pdf_url": "http://documents1.worldbank.org/curated/en/717781588366403375/pdf/Chad-COVID-19-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "MOPH report", "label": "NAMED_DATA", "score": 0.527076244354248, "start": 634, "end": 645, "probe_score": 0.8265, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "routine data", "label": "VAGUE_DATA", "score": 0.6240779757499695, "start": 654, "end": 666, "probe_score": 0.8431, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Figure 13** : Gender gaps in school enrollments of cohabiting dependent children aged 5-14 by age and mother‘s marital status, rural and\nurban Mali 2006\n\n\nNote: The samples of current widows and current divorcees are left out given their smaller sample sizes. Note also that there are some small-sample problems with the married,\npreviously widowed group in urban areas -- the samples of boys and girls in each age group averaged about 10-15 observations, but were made missing when samples were below 10\nobservations.\nSource: 2006 Mali DHS.\n\n\n45", "output": {"entities": {"named_data": ["2006 Mali DHS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004912", "page": 46, "chunk": 0, "title": "wps5734", "pdf_url": "https://local/prwp/wps5734.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2006 Mali DHS", "label": "NAMED_DATA", "score": 0.6645892858505249, "start": 529, "end": 542, "probe_score": 0.9941, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".011 0.020 0.989 0.980 0.979 0.958\n45‐49 0.0030 0.0059 45 0.015 0.029 0.985 0.971 0.969 0.939\n50‐54 0.0058 0.0109 50 0.029 0.055 0.971 0.945 0.954 0.909\n55‐59 0.0081 0.0170 55 0.040 0.085 0.960 0.915 0.924 0.855\n<u>60‐64</u> <u>0.0171 0.0304</u> <u>60 0.086</u> <u>0.152</u> <u>0.914</u> <u>0.848</u> <u>0.884</u> <u>0.770</u>\nSource: Own calculations based on the Population and Housing Census 2015 and following\nthe methodology provided in United Nations (2002).\n\n_Estimation of expected economic costs_\n\n6. Estimating the expected economic costs basically entails predicting the direct and indirect cost of\nschooling at each education‐completion level. These costs include: (i) the household’s school‐related\nexpenses; (ii) the Government’s spending on the education of each child; and (iii) the opportunity cost of\nschooling, i.e., the child’s forgone earnings.\n\n7. The PDV of the expected economic costs that a representative child aged 5 incurs from going to\nschool during the ages of 5 to 17 is given by:\n\n\n\n16\n\n\n\n3\n#  e pri  e pub   1  dk  a\n\n\n\n3\n\n\n\n\n\n\n\n\n\n\n\n\n# 1  g 1  a  6", "output": {"entities": {"named_data": ["Population and Housing Census 2015"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000041", "page": 63, "chunk": 1, "title": "Jordan - Education Reform Support Program-for-Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/731311512702123714/pdf/Jordan-Educ-Reform-121282-JO-PAD-11142017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Population and Housing Census 2015", "label": "NAMED_DATA", "score": 0.8791608214378357, "start": 365, "end": 399, "probe_score": 0.9996, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " hygiene of 26 percent is\nreduced by 31 percent which, combined with a value of a statistical life of US$2,394 <sup>96</sup> and a\nsubproject effectiveness rate of 33 percent, would lead to annual benefits of US$6,735.\n\n     - The NPV of one five-Toilet VIP latrine is estimated at US$41,062 and the IRR is estimated at 24.5\npercent.\n\n\n5. **Investment in primary education classrooms**\n\n\n     - The construction cost per primary education classroom is assumed at US$14,446. The annual\ncost of O&M is estimated at US$350 per student <sup>97</sup> which, combined with an estimated 30\nstudents per classroom, leads to annual O&M cost of US$10,500.\n\n     - Benefits of improved access to primary educational facilities consist of (a) value of reduction in\nchild mortality and maternal deaths related to mother literacy and (b) value of increased\nincome per year of additional schooling. For each of these benefits, it is assumed that there will\nbe a 50 percent reduction in child mortality, 67 percent reduction in maternal deaths if a mother\nhas completed primary education, and a 10 percent increase in income per year of schooling\ncompleted. <sup>98</sup> With regard to (a), it is assumed that 11.70 school children lives are saved through\nthe mother’s education which, combined with a value of a statistical life of US$2,394 <sup>99</sup> and a\nsubproject effectiveness rate of 50 percent, would lead to annual benefits of US$14,008. With\nregard to (b), it is assumed that 0.05 maternal lives are saved through mother’s education\nwhich, combined with a value of a statistical life of US$2,394 and a subproject effectiveness of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 84, "chunk": 1, "title": "South Sudan - Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/824121596765983121/pdf/South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "18<br>Oct-19<br>Nov-20<br>Nov-21<br>Kutupalong RC|Oct-17<br>May-18<br>Oct-18<br>Oct-19<br>Nov-20<br>Nov-21<br>Kutupalong RC|Oct-17<br>May-18<br>Oct-18<br>Oct-19<br>Nov-20<br>Nov-21<br>Kutupalong RC|Oct-17<br>May-18<br>Oct-18<br>Oct-19<br>Nov-20<br>Nov-21<br>Kutupalong RC|\n\n\nSevere Acute Malnutrition (MAM) Moderate Acute Malnutrition (MAM) GAM Serious GAM Critical\n\n\nHowever, considering aggravating factors, including COVID-19’s effects on food security, nutrition, market\ndynamics and other morbidities, the prevalence could easily tip over to the highest category of “ **very**\n**high** / **critical”** (above 15% acute malnutrition), especially in the monsoon season. Therefore, the need for\nconcerted efforts, close monitoring and strengthening of the nutrition interventions as well as multisectoral efforts to address malnutrition cannot be overstated.\n\n\nChronic malnutrition (stunting) remains very high (above the >30 critical/very serious category) according\nto the WHO/UNICEF classification with fluctuating trends observed between 2017 and 2021. Older children\nare more stunted than the younger age group of 6-23 months. These findings align with the general\nobservation in nutrition surveys that acute malnutrition decreases with age while stunting increases with\nage (ISCG, May 2021). More efforts are needed to bring chronic malnutrition rate to acceptable levels.\n\n\n7", "output": {"entities": {"named_data": [], "descriptive_data": ["nutrition surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000446", "page": 6, "chunk": 11, "title": "Standardized Expanded Nutrition Survey: Executive Summary - Rohingya Refugee Camps, Cox’s Bazar, Bangladesh, October – November 2021", "pdf_url": "https://reliefweb.int/attachments/3ef29ac8-96e6-40d1-8e5e-3eec2cf61828/Refugee_SENS_Executive_Summary_2022_2_.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "nutrition surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8513031005859375, "start": 1187, "end": 1204, "probe_score": 0.8955, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on social development issues"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014032", "page": 24, "chunk": 0, "title": "Uganda - Structural Adjustment Credit Project", "pdf_url": "https://documents.worldbank.org/curated/en/506681468309344399/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on social development issues", "label": "VAGUE_DATA", "score": 0.581004798412323, "start": 1670, "end": 1703, "probe_score": 0.333, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the first stage, it\nadjusts for the non-random distribution\nof Ukrainian refugees across poviats,\nand in the second stage, it calculates\nthe models. These results can be\ninterpreted causally. The two previously\nmentioned instruments were used and\nyielded statistically significant results, as\nwell as passed statistical tests on their\nappropriateness for instrumenting the\nemployment share of Ukrainian refugees.\nOne instrument is the share of Ukrainian\nchildren in Polish schools, and the other is\nthe distribution of Ukrainian citizens across\nPoland in 2019, as recorded in declarations\n\n\n\nof intent to employ foreign workers. The\nresults are similar to the OLS estimation;\nhowever, when the second instrument is\nused without the first one, it gives a higher\nresult. Instrumental variables regressions\nshow that in 2023, a 1 percentage point\nhigher employment share of Ukrainian\nrefugees caused a PLN 70 higher wage\ngrowth (0.7 pp.) when instrumented by\nschool pupils' share, PLN 132 (1.4 pp.)\nwhen instrumented by 2019 Ukrainian\nworkers distribution, and PLN 75 (0.8 pp.)\nwhen both instruments were used. That\nsaid, the results should be treated with\ncaution, as the instruments used may not\nbe sufficiently exogenous to allow for fully\ncredible causal inference.\n\n\nThe early analysis by Gromadzki and\nLewandowski (2023), mentioned previously\nalso found a statistically significant effect\nof Ukrainian refugees on earnings. In their\nestimation, the share of the Ukrainian\nrefugee population had a small positive\nand statistically significant relationship with\nthe earnings of Polish women at a 0.1 level.\nTheir results for foreign women were\nalso positive, albeit smaller and lacking\nstatistical significance.\n\n\n\n2021, so the sample size is still growing.\nHowever, it is large enough to allow for\nsome cautious inference with 4.2 million\nPolish citizens in mid-2022 and 6.2 million\nin mid-2024. This has been combined with\naverage salaries in 128 occupational groups\nin GUS data for October 2022 (the most\nrecent data).", "output": {"entities": {"named_data": ["GUS data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 20, "chunk": 3, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "GUS data", "label": "NAMED_DATA", "score": 0.8980650305747986, "start": 1974, "end": 1982, "probe_score": 0.6318, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "satisfied two or more rainy seasons; - Progress reports submitted\n2b.3 100% of houses benefit by implementing partners;\nmarginalized population                 - Beneficiary assessments\ngroups (female headed                 - NaCSA M&E data\nhouseholds, disabled and their\nfamilies); and\n2b.4 100% of beneficiaries\nwere selected by beneficiary\ncommunities.\n\n\n**3.** Proiect Management and\nInnovative Activities - NaCSA administrative data - Qualified implementing\n\n                                  - Capacity building event partners available to provide\n**3(a)** **Capacities of** assessments; capacity building and IEC\n**communities,** **chiefdomns,** **and** 3a.1 At least 5 successful - Participatory project activities at all levels;\n**district authorities to select,** capacity building events completion reviews; - A qualified full-time M&E\n**implement and maintain** carried out each year; - IDA supervision missions specialist is provided to\n**projects established** **and** NaCSA by another donor\n**strengthened** agency\n\n**3(b)** **Information, Education** 3b. 1 At least 40% of HHs are - Beneficiary assessments; - Non-NSAP activities\n**and Communication** aware of program; - NaCSA adrninistrative data; undertaken by NaCSA do not\n3b.2 At least 60%of chlefdom                  - IDA aide-memoires and detract from NaCSA ability to\nand district governments project status reports; and implement project.\naware of NSAP coverage,\ntargeting, methodology, and\nresults; and\n3b.3 At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA", "output": {"entities": {"named_data": ["NaCSA M&E data", "NaCSA administrative data", "NaCSA adrninistrative data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015266", "page": 31, "chunk": 0, "title": "Kenya - Energy Sector Reform and Power Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/592221532724064535/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NaCSA M&E data", "label": "NAMED_DATA", "score": 0.8557507395744324, "start": 226, "end": 240, "probe_score": 0.0002, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "NaCSA administrative data", "label": "NAMED_DATA", "score": 0.7650092840194702, "start": 412, "end": 437, "probe_score": 0.0006, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "NaCSA adrninistrative data", "label": "NAMED_DATA", "score": 0.6916330456733704, "start": 1188, "end": 1214, "probe_score": 0.4531, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_\n\n<u>Gasoline</u> <u>Diesel</u> <u>Gasoline</u> <u>Diesel</u> <u>Gasoline</u> <u>Diesel</u> <u>Gasoline</u> <u>Diesel</u> <u>Gasoline</u> <u>Diesel</u>\n\nPhase 3 Oct-24 176 138 247 228 217 188 40% 66% 23% 36%\n\nPhase 4 Apr-25 176 138 346 377 268 256 40% 66% 23% 36%\n\nPhase 5 Oct-25 176 138 484 625 330 348 40% 66% 23% 36%\n\nPhase 6 Apr-26 176 138 406 474 23% 36%\n\n<u>Phase 7</u> <u>Oct-26</u> <u>176</u> <u>138</u> <u>500</u> <u>646</u> <u>23%</u> <u>36%</u>\n\n<u>Source: authors’ estimations.</u>\nNote: these estimations are based on data available as of May 2024 and are subject to changes in volatile variables. For example,\nchanges in the foreign exchange rate and global oil prices will undoubtedly have an impact on these estimations.\n\n\nThese subsidy removals would generate significant additional fiscal savings. If prices remain\nunchanged, total subsidy spending is projected to reach 3, 2.7 and 2.4 percent of GDP in 2024, 2025\nand 2026, respectively. The decline in oil prices and the smooth nominal depreciation expected in the\nmedium term would reduce subsidy spending as a share of GDP. In the second scenario, subsidy\nspending is expected to reach 3, 1.3 and 0.3 percent of GDP in 2024, 2025 and 2026, saving 0.05", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data available as of May 2024"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001567", "page": 9, "chunk": 1, "title": "idu1d4b66e6c170c6147691aaf4198a48cc7f79f", "pdf_url": "https://local/prwp/idu1d4b66e6c170c6147691aaf4198a48cc7f79f.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data available as of May 2024", "label": "VAGUE_DATA", "score": 0.7929784059524536, "start": 532, "end": 561, "probe_score": 0.9653, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "lines in the first years of primary school. <sup>13</sup> [^13: According to MOE data for the 2015‐2016 academic year, enrollment is similar for girls and boys.] Limited specialized in‐service training opportunities and\npedagogical support constrain KG teachers’ ability to structure learning around age‐appropriate and\nplay‐based activities that stimulate child development and early noncognitive skills. This, coupled with\na lack of an efficient quality assurance system for KGs means that there is no mechanism to monitor\nprogress or incentivize continuous quality improvements, and likely is restricting the ECE’s\ncontribution to children’s school readiness in the country. The 2014 Early Development Instrument,\nfor example, revealed that a quarter of children enrolled in public KG2 in Jordan are “not ready to\nlearn”, mainly due to inadequate levels of socioemotional development. As such, expanding access\nand ensuring quality in the provision of KG are likely to transform Jordanian and non‐Jordanian\nstudents’ ability to learn and succeed in school.\n\n12. **Poor student learning outcomes at all levels are a challenge in Jordan.** One in five students in\ngrade 2 cannot read a single word from a reading passage, while nearly half are unable to perform a\nsingle subtraction task correctly, thus lacking the foundational literacy and numeracy skills that enable\nfurther cognitive skill development. <sup>14</sup> [^14: Latest (2012) EGRA and EGMA scores for Jordan.] With a weak start, skills deficits compound such that by age 15,\ntwo‐thirds of students do not meet the most basic level of proficiency in mathematics, and half are\nbelow basic proficiency in reading and science, as measured by the 2015 Program for International\nStudent Assessment (PISA). Furthermore, learning outcome data show a reverse gender gap with girls\nperforming better than boys in reading, mathematics, and science. <sup>15</sup> [^15: PISA 2015] International comparisons place\nJordan in", "output": {"entities": {"named_data": ["MOE data", "2015 Program for International\nStudent Assessment"], "descriptive_data": [], "vague_data": ["learning outcome data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000041", "page": 11, "chunk": 0, "title": "Jordan - Education Reform Support Program-for-Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/731311512702123714/pdf/Jordan-Educ-Reform-121282-JO-PAD-11142017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "MOE data", "label": "NAMED_DATA", "score": 0.6684749722480774, "start": 77, "end": 85, "probe_score": 0.9723, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2015 Program for International\nStudent Assessment", "label": "NAMED_DATA", "score": 0.6974319219589233, "start": 1708, "end": 1757, "probe_score": 0.9959, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "learning outcome data", "label": "VAGUE_DATA", "score": 0.6706512570381165, "start": 1779, "end": 1800, "probe_score": 0.9547, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**_6.1 Flood Management_**\n\nThe regional government (Province/District) is ultimately responsible for flood\nmanagement and addressing flood damage, but PJT I plays a primary role, having\nresponsibility for O&M of flood protection infrastructure and for the Flood Forecasting\nand Warning System (FFWS). It coordinates activities of all relevant agencies and the\ngovernor, providing information concerning water levels. The FFWS at PJT I’s main\noffice is used to prevent or mitigate damage and to ensure public safety. Field data are\ntransferred to the master station every 30 minutes. Flood defense teams perform floodfighting activities. Information concerning river conditions and damage at every stage of\na flood is disseminated to people living near the river. Agreements exist between the\nprovince and the districts regarding how to manage floodwaters. According to\ninterviewees, damage due to floods has decreased significantly in the Brantas basin since\ntheir establishment. Thus, while floods remain to be a challenge in the basin, not least due\nto new threats such as indiscriminate forest logging in the upper watersheds (dealt with\nunder a different ministry), flood management has improved and can be seen as one of\nthe achievements of the past decade’s emphasis on institutional change in the basin.\n\n**_6.2 Water Quality_**\n\nFor water pollution control, final responsibility lies with the governor in accordance with\nGovernment Regulation (PP) 20/1990 on Water Pollution Control. Provincial Regulation\n5/2000, in the interest of the decentralizing authority, makes it possible for the Governor\nto delegate responsibility to the head of the Provincial Environmental Pollution Control\nOffice (Bapedalda). This agency coordinates all other agencies dealing with water\npollution control. The Provincial Public Works Service is responsible for domestic and\nmunicipal wastewater and installation of sanitation facilities and Provincial Industry\nService is considered responsible for industrial pollution control. Meanwhile, Law\n22/1999 further devolves authority to District governments and urban municipalities to\ndeal with their", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Field data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002825", "page": 22, "chunk": 0, "title": "wps3611", "pdf_url": "https://local/prwp/wps3611.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Field data", "label": "VAGUE_DATA", "score": 0.7040303349494934, "start": 517, "end": 527, "probe_score": 0.1481, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Thus, while interventions that aim to limit shock-related losses can be criticised for being insufficient by only\nreturning people to their pre-shock state of vulnerability, ‘[in] many contexts, like those faced with recurrent\npredictable shocks, improving the coverage, adequacy, quality, responsiveness, and comprehensiveness of\nregular social protection programmes can in itself help to reduce vulnerability and enhance long-term\nresilience’ (Devereux, Solórzano and Wright 2024: 14). The following section considers efforts to incorporate\npromotive elements within the PSNP. This will set up consideration of the programme’s performance in\nsupporting the needs of conflict-affected populations in areas of Amhara and Oromiya in sections 5 and 6.\n\n\n12", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000561", "page": 11, "chunk": 0, "title": "Can Social Protection Programmes Promote Livelihoods and Climate Resilience in Conflict‑Affected Settings? Evidence from Ethiopia’s Productive Safety Net Programme", "pdf_url": "https://reliefweb.int/attachments/52e51023-be1a-5cb4-a8d9-02b4718bea3a/BASIC_WP37.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<u>Hpa-An Environmental Scoping Report || NEAT+ || October 2019 | 34</u>\n\n\nmethods if they received training and it did not reduce their current income levels. Assessing\ninterest and potential uptake of programs which encourage sustainable practices and still\nprovide income should be scoped by NRC, for inclusion in their current farmer training programs.\n\n\n_Figure 22: Results from the NEAT+ environmental sensitivity analysis on low capacity to manage waste water._\n\n\n\n\n\n\n\n|Col1|Water and Wastewater Management|\n|---|---|\n|**Relevant NRC**<br>**Activities**|NRC Myanmar does not currently have active WASH programming in<br>Myanmar, but with global expertise, and through other activated core<br>competencies (shelter and settlements, livelihoods and food security, and<br>education) is positioned to incorporate and integrate relevant activities<br>into intervention strategies.|\n|**Mitigation tips**|● Protect open wells from contamination<br>● Encourage the replacement of open defecation with improved pit<br>latrines.<br>● Provide education about reusing household grey water<br>● Introduce grey water capture systems<br>● Gauge interest in permaculture training program|\n\n#### Climate Change/Climate Variability\n\nAll groups consulted, in addition to the results of the NEAT+, noted increasing climatic change\nand variability with negative consequences on livelihoods - particularly agricultural production.\nAll groups noted increased temperatures and more erratic rainfall patterns. Rainfall is becoming\nharder to predict, and residents noticed the overall amount of rainfall has decreased. For\nresidents of Sein Pa La, who mostly grow high-value tree crops such as rubber, durian, rambutan\nand other fruits, the early arrival of hot temperatures is causing the fruit to spoil before ripening.\nThere have also been issues with rubber tree plantations catching fire", "output": {"entities": {"named_data": ["NEAT+"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000284", "page": 33, "chunk": 0, "title": "Myanmar: Hpa-An Township - Environmental Scoping Report and Recommendations (October 2019)", "pdf_url": "https://reliefweb.int/attachments/20e741c1-3cf8-5dfc-98d3-347cb61d617f/NEAT-Myanmar-Environmental-Scoping-Report-Oct-2019.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NEAT+", "label": "NAMED_DATA", "score": 0.5934475064277649, "start": 1278, "end": 1283, "probe_score": 0.5696, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a v\nManufacturIng 5 7 3.7 4 7 5 0 / s \\\\t oo  Services 475 272 190 201\n\nPrfvate consumpffon 90 7 81 9 938 95 1 20\nGeneral govemment consumption 7 0 9 6 146 17.2 =c ~GDFDl\nImpons of goods and servrcea 39 7 23 6 33 4 373 -3GW_G_____\n\n\n_(average_ _annual growth)_ 1981-9 1991401 2000 2001 Growth ot exports and Imports (%)\n\nAgrutumre -0 6 -2 6 2 2 3 8 oo\nIndustry 0.1 -41 51 5 6 s0\nManUnacturIng 6.9 . .\nServices -5 7 -5.4 4 0 51 \nPrivate oonsumpffon -2 0 -19 10 4 100 -50\nGeneral govemment consumption -5.1 -0 2 41.3 27 9 -100\nGross domestic Investment -06 3 0 50 - EOpois -tr-ports\nImports of goods and services -2 2 -151 85 0 61 3\n\n\nNote 2001 data are pretirrinary eastliates\n'The diamonds show four Key Indicators in the country (in bold) conipared with itS income-group average It data are missing, the diantond wiUt be rrconrrlte\n\n\n-56", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["2001 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016971", "page": 60, "chunk": 2, "title": "Ethiopia - Pastoral Community Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/704891468771264645/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2001 data", "label": "VAGUE_DATA", "score": 0.7082152366638184, "start": 639, "end": 648, "probe_score": 0.0183, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " of public\nschools. <sup>7</sup>\n\n\n10. Prior to the onset of the Syrian crisis, Lebanon’s adjusted primary net enrollment rates\nwere slightly above the regional average at 96 percent. However, secondary net enrollment rates\nin Lebanon at 67 percent lagged behind the MENA average of 72 percent. Even when compared\nwith countries with similar level of development, Lebanon’s secondary net enrollment rate was\nsignificantly lower than the average of 81 percent. <sup>8</sup>\n\n\n11. Public education in Lebanon tends to serve the poor at low levels of quality. Public\nschools educate about 31 percent of students in Lebanon, despite being free. This revealed\npreference reflects the overall poor quality of public schools, particularly at the primary level,\nand has large and negative implications for the poor. The higher quality associated with private\nschools means that public-school students are likely to learn less and face more difficult job\nprospects upon graduation. This sets up inter-generational transmission of both lower learning\nlevels and lower income. <sup>9</sup> Public schools exhibit lower academic outcomes in international and\nnational assessments. The level of public school students was 10 percent lower than that of\nprivate schools in the 2011 Trends in International Mathematics and Science Study (TIMSS)\nresults. Indeed, based on the 2004 household survey, poverty and education are highly correlated\nin Lebanon.\n\n\n5 Lebanon’s inequality-adjusted HDI is 20.8 percent lower than its HDI, among the largest losses in the group of\ncountries in the high human development category.\n6 World Economic Forum’s 2013 Human Capital Index\n7 Further information about the level of private sector investments is expected from a forthcoming Education\nExpenditure Review.\n8 World Bank Ed Stats\n9 “Poverty, Growth and Income Distribution in Lebanon,” August 2008.\n\n\n3", "output": {"entities": {"named_data": ["Trends in International Mathematics and Science Study"], "descriptive_data": ["2004 household survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000099", "page": 11, "chunk": 1, "title": "Lebanon - Emergency Education System Stabilization Project", "pdf_url": "http://documents1.worldbank.org/curated/en/578481467991017996/pdf/PAD1190-PAD-P152848-PUBLIC-Box391435B-LB-EESSP-Final-PAD-for-printing.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Trends in International Mathematics and Science Study", "label": "NAMED_DATA", "score": 0.7560645341873169, "start": 1267, "end": 1320, "probe_score": 0.9973, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2004 household survey", "label": "DESCRIPTIVE_DATA", "score": 0.8910120725631714, "start": 1359, "end": 1380, "probe_score": 0.8236, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "- 6 \n\nother. Third, a local firm can also make a consortium with foreign firm(s). Fourth, it is\n\n\npossible that more than one foreign bidder submit a joint bid together. Finally, a foreign\n\n\nbidder may choose to participate in an auction alone.\n\n\nFigure 1. Classification of Joint Bidding\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nOur data on procurement auctions are collected from ODA-related infrastructure projects\n\n\nassisted by the Japanese Government and the World Bank. It contains 221 public contracts\n\n\nfor road, water and sewage, and electricity projects in 29 developing countries. In 221\n\n\nauctions, 862 firms and bidding consortia are identified ( see Estache and Iimi (2008) for\n\n\ndetails).\n\n\nThese firms and consortia were composed by 1,656 individual firms. <sup>4</sup> Local firms who\n\n\nparticipated—either solely or jointly—in the procurement process amount to 60 percent in\n\n\nthe road sector (Table 1). In the water and sewage sector the share of local firms reaches as\n\n\nmuch as 75 percent. By contrast, foreign firms are much dominant in the electricity sector;\n\n\nabout 70 percent of bidders come from abroad.\n\n\nThe probability of a firm making a bidding coalition is highest in electricity projects and\n\n\nlowest in road procurements. Half of firms choose to jointly bid in the former sector. The\n\n\n4 If a firm participates in more than one auction, they are double counted. We accounted for different names of a\nsingle firm in our sample data, but only at the primary level, meaning that it is accounted for if they are clearly\nthe same company (e.g., misspelling and abbreviation) or if a local firm clearly represents its parent company.\nHowever, we have _not_ taken into account the potential capital relationships between firms because of technical\ndifficulties. It is also ignored the possibility that some firms are intended to be subcontracted performance of\npart of the work by other firms.", "output": {"entities": {"named_data": [], "descriptive_data": ["data on procurement auctions"], "vague_data": ["sample data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003871", "page": 7, "chunk": 0, "title": "wps4664", "pdf_url": "https://local/prwp/wps4664.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on procurement auctions", "label": "DESCRIPTIVE_DATA", "score": 0.9369837045669556, "start": 308, "end": 336, "probe_score": 0.9815, "gold": "DATA_MENTION", "gold_tier": "flip"}, {"text": "sample data", "label": "VAGUE_DATA", "score": 0.6299030780792236, "start": 1427, "end": 1438, "probe_score": 0.9691, "gold": "DATA_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "```\n(i)  introduce computerization of accounts by December 31, 1994;\n\n(ii)  from 1995 onward, prepare quarterly financial\nreports to be used as a tool for improved financial forecasting and management information.\n\n(iii)  KNH shall implement a management accounting\nsystem by June 30, 1992.\n\n11. KNH shall, by June 30, 1992, introduce actual versus planned\nbudget analysis for all functional units and will provide to the\nAssociation detailed account of all major deviations.\n\n12.  KNH shall cost major medical services and increase fees with\nthe aim of full cost coverage for out-patients by 1995. KNH shall\nfurnish to the Association for review by March 31 of each year its\ndraft budget for the next year including its proposed fee structure\nand depreciation schedule.\n\nPersonnel Management\n\n13.  KNH shall:\n\n(i)  by March 31, 1992, complete the exercise of\ntransferring staff who have opted to remain with\nMOH, from KNH to MOH and resolve any differences\nin the number of staff working versus staff paid;\n\n(ii)  commencing March 1992, undertake quarterly reviews of authorized posts and abolish non-essential unfilled posts;\n\n(iii)  by June 30, 1992, adopt those recommendations of\nthe Department of Personnel Management Report on\nthe improvement of the Personnel and Training\nfunctions within the Hospital that would lead to\nan effective and efficient Personnel Training\nDepartment;\n\n(iv)  by June 30, 1992, establish a Manpower Information System comprising of, inter alia, personnel\nrecords, personnel statistics and personnel\nregistry; and\n\n(v)  revise its training projections in a systematic\nmanner by March 31 of each year to ensure that\nthe training programs remain consistent with the\noverall objectives of the hospital.\n\nMaterials/Drugs Management\n\n14.  KNH shall by June 30, 1992:\n\n(i)  undertake an inventory of existing stocks, write\noff obsolete items, bring prices to current price\nlevels, and bring records up to date;\n\n(ii)  introduce computerization of stock management;\n\n(", "output": {"entities": {"named_data": [], "descriptive_data": ["personnel\nrecords", "personnel statistics", "personnel\nregistry"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015000", "page": 5, "chunk": 0, "title": "Conformed Copy - C2310 - Health Rehabilitation Project - Project Agreement", "pdf_url": "https://documents.worldbank.org/curated/en/574091468273346706/pdf/DC4173B821D73FD685256F0200814022.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "personnel\nrecords", "label": "DESCRIPTIVE_DATA", "score": 0.8275719881057739, "start": 1479, "end": 1496, "probe_score": 0.0406, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "personnel statistics", "label": "DESCRIPTIVE_DATA", "score": 0.7867317199707031, "start": 1498, "end": 1518, "probe_score": 0.0004, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "personnel\nregistry", "label": "DESCRIPTIVE_DATA", "score": 0.8016021847724915, "start": 1523, "end": 1541, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**_0_**\n\n\n**_0_**\n\n\n\nNet change in anemia levels (as measured through blood test indicators) of children 0-5 years old\n\n(target: 2-15%).\nBaseline data for children brought regularly to health centers for preventive care will be collected\nthrough the application process. M O H and UNRWA still have to confirm that the children\nbrought to health clinics to check nutritional status will have a general checkup; this i s not yet\nguaranteed but i s feasible should both agencies agree.\n\n\n\nI t can be presumed that the last three years of _intifada_ and closures have had a negative effect on the\nvaccination rates, though there has been no reliable data since 2001. Therefore, the only possibility\nfor the baseline would be to collect data from the beneficiary households. The risk i s that they might\nnot be able to provide exact records for their children. One possible solution would be to design a\nform for each child and let the households collect the missing data from the primary health care\n(PHC) clinics where immunization occurred. For this to occur, agreement would have to be reached\nbetween the PHC departments in M O H and UNRWA. The households also must be made aware that\nthey have to submit a vaccination booklet every time their child visits a health clinic. In so doing,\nvaccination monitoring would be possible during implementation vis-&vis nutrition checkups.\n(ii) <sup>**Education Grants.**</sup> <sup>The following outcome indicators will be used:</sup>\n\n\n\n**_0_**\n\n\n**_0_**\n\n\n**_0_**\n\n\n\nNet change in school attendance (target: 2-5%)\nNet change in school dropout (target: 24%)\nNet change in school enrollment (target: 1-5%)\nNet change in transition rate, especially grades TBD (target: > or", "output": {"entities": {"named_data": [], "descriptive_data": ["data from the beneficiary households"], "vague_data": ["Baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000047", "page": 31, "chunk": 0, "title": "West Bank and Gaza - Social Safety Net Reform Project", "pdf_url": "http://documents1.worldbank.org/curated/en/326701468762010863/pdf/27761.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Baseline data", "label": "VAGUE_DATA", "score": 0.5372747778892517, "start": 137, "end": 150, "probe_score": 0.0529, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "data from the beneficiary households", "label": "DESCRIPTIVE_DATA", "score": 0.5592045783996582, "start": 732, "end": 768, "probe_score": 0.313, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "- 9 \n\n15. Three connectivity variables are constructed using spatial software based on road user\n\n\ncosts and maritime transport costs: The first is transport costs to bring goods to Moroni,\n\n\ndenoted by _COSTMORONI_ . This measures the accessibility to the primary market. The second\n\n\nvariable is transport costs to bring goods to a large city with a population of 7,500 or more\n\n( _COSTCITY_ ). Major towns in each island are taken into account. <sup>3</sup> [^3: Twenty-one cities and towns were identified among a total of 302 populated areas: Adda Daoueni, Barakani,\nBazimini, Dindri, Domoni, Fomboni, Iconi, Jimlime, Koni Djodjo, Mbeni, Mirontsi, Moroni, Moya, Mremani,\nMutsamudu, Ngadzale, Ongodjou, Ouani, Ounkazi, Sima and Tsembehou.] This is expected to represent\n\n\nthe market accessibility at a more local level within each island.\n\n\n16. Finally, the Market Access Index ( _MAI_ ) is computed as an integral measure of all kinds\n\n\nof market accessibility. Formally, it is often defined by the average market size inversely\n\n\nweighted by transport difficulties. The idea basically follows Tobler’s first law of geography:\n\n\n“everything is related to everything else, but near things are more related than distant things\n\n\n(Tobler 1970).”\n\n\n𝑀𝐴𝐼� ��∑� 𝑌�⁄𝑑���max 𝑀𝐴𝐼� (2)\n\n\nwhere _Ym_ represents the size of market at _m_, which is measured by the population that does\n\nnot engage in agricultural production. <sup>4</sup> [^4: It is estimated by the population multiplied by the share of non-agricultural households, which is calculated by\nsubregion, using the same household survey.] _dim_ measures transportation costs between location _i_\n\n\nand destination _m_ . The index is normalized to zero to one. It is clear that Moheli is\n\n\nparticularly disconnected from the rest of the country, while Grande Comore, especially\n\n\naround Moroni, has relatively good market accessibility ( **Figure 11** )", "output": {"entities": {"named_data": [], "descriptive_data": ["household survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000514", "page": 10, "chunk": 0, "title": "hidden treasures in the comoros the impact of inter island connectivity improvement on agricultural production", "pdf_url": "https://local/prwp/hidden-treasures-in-the-comoros-the-impact-of-inter-island-connectivity-improvement-on-agricultural-production.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household survey", "label": "DESCRIPTIVE_DATA", "score": 0.843630850315094, "start": 1574, "end": 1590, "probe_score": 0.5729, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "- The Bank team will undertake a limited evaluation of the Project, in close coordination\n\nwith MOMA and other Jordanian stakeholders and with the Center for Conflict, Security\nand Development (CCSD) within the Bank. This will involve surveys of beneficiary\nhouseholds and other key stakeholders at key points during the life of the Project. The\nevaluation design could employ appropriate evaluation techniques to estimate Projectspecific benefits and impacts. Further, based on availability of resources, the use of geomapping technology will be explored to gather disaggregated information on socioeconomic conditions in Project areas, as well as for timely knowledge sharing of special\nneeds in the changing demographic landscape of Northern Jordan.\n\n**C.** **Sustainability**\n\n\n52. In light of the fiscal constraints that Jordan faces and the central government’s inability to\nincrease its annual budget transfers to municipalities, there is a risk that participating\nmunicipalities will not be able to sustain the level of services they will provide through the\nProject’s funds beyond the Project’s duration. However, given the focus during the Project’s\ninitial phase on investing in infrastructure needs that have remained largely unmet over the past\ntwo years, it is expected that the return on these investments will extend beyond the Project’s\nlifetime, mitigating any need for sustaining the investment levels made possible through the\nProject’s financing. Investments in local development projects are also expected to contribute to\nexpanding the municipalities’ revenue base.\n\n53. Financial and capacity constraints within municipalities may pose further challenges to\nthe sustainability of the Project’s investments. Additional design features have been put in place\nto augment operation and maintenance of Project investments. For example, the Project's\ndelegation of the use of funds to the municipalities in combination with multipronged technical\nassistance to support their performance in key areas such as engineering, FM, procurement,\nparticipatory planning and social accountability will strengthen local capacity beyond the life of\nthe Project. Improvements in transparency and participation (including public participation in the\nplanning", "output": {"entities": {"named_data": [], "descriptive_data": ["surveys of beneficiary\nhouseholds"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000026", "page": 25, "chunk": 0, "title": "Jordan - Emergency Services and Social Resilience Project", "pdf_url": "http://documents.worldbank.org/curated/en/532171468273353365/pdf/PAD7230P1476890AD0October0100final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "surveys of beneficiary\nhouseholds", "label": "DESCRIPTIVE_DATA", "score": 0.9282124042510986, "start": 235, "end": 268, "probe_score": 0.0131, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " substantial differences in\n\n\nthe coresidency rates, and provide evidence on both father-son and mother-daughter links\n\n\nin educational persistence.\n\n\n**3.** **Data** **and** **Variables**\n\n\nWe use two rich data sets particularly suited for the analysis of the extent of coresident\n\n\n15They provide an extensive analysis of alternative econometric approaches for selection correction. Their\nfindings indicate that the inverse probability weighted estimator is the most reliable to tackle coresident\nsample selection bias among a number of approaches including Heckman selection correction.\n\n\n7", "output": {"entities": {"named_data": [], "descriptive_data": ["rich data sets"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006640", "page": 9, "chunk": 1, "title": "wps7608", "pdf_url": "https://local/prwp/wps7608.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "rich data sets", "label": "DESCRIPTIVE_DATA", "score": 0.5273287892341614, "start": 202, "end": 216, "probe_score": 0.148, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nGreater Beirut Public Transport Project (P160224)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Indicator Name|Core|Unit of<br>Measure|Baseline|End Target|Frequency|Data Source/Methodology|Responsibility for<br>Data Collection|Col10|\n|---|---|---|---|---|---|---|---|---|---|\n||**Name:**Number of<br>passengers per weekday<br>using the formal public bus<br>(BRT and regular buses).||Number<br>(Thousand)|0.00|300.00|Biannual<br>|The RPTA will collect the<br>number of passengers from<br>bus operators and from the<br>mirror system and provide<br>the information to CDR<br>|CDR/the RPTA<br> <br> <br> <br>Private operators<br>|CDR/the RPTA<br> <br> <br> <br>Private operators<br>|\n||Percentage of female<br>ridership in the formal<br>public bus system (BRT and<br>regular buses) per weekday <br>||Percentage|0.00|40.00|Annual<br>|Information about female<br>PT users will be obtained<br>through surveys by RPTA<br>and operators.<br>|CDR/the RPTA<br>|CDR/the RPTA<br>|\n||<br>Description:This indicator measures the daily average passenger ridership of the system (all BRT and regular bus services). This indicator will reflect the number of direct<br>", "output": {"entities": {"named_data": [], "descriptive_data": ["surveys by RPTA"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000022", "page": 46, "chunk": 0, "title": "Lebanon - Greater Beirut Public Transport Project", "pdf_url": "http://documents.worldbank.org/curated/en/471241521338566907/pdf/PAD-final-02262018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "surveys by RPTA", "label": "DESCRIPTIVE_DATA", "score": 0.7961040139198303, "start": 898, "end": 913, "probe_score": 0.9142, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ").\n\n\n  - There is no information available on accommodation for\nchildren with their families in reception facilities.\n\n\n- For Italy, the calculation is based on the estimated 7,272 UASC registered in reception\naccording to the Ministry of Labour and Social Policies.\n\n3\n\n\n\nGreece\n\n\n\n**37%** **52%** **10%**\n\n\n\nBulgaria **33%** **36%** **30%**\n\n\n_Source:_ _<u>Hellenic Police, EKKA, Bulgarian State Agency for Refugees</u>_\n\n\nThe majority of UASC who arrived in Italy, Greece and Bulgaria\nbetween January and June 2019 were between 15 and 17 years\nold (86% overall). Age disaggregated data on children arriving to\nSpain is not available.\n\n\nUnaccompanied and Separated Children – Age breakdown\n\n\n0 - 4 years 5 - 14 years 15 - 17 years\n\n\nGreece **1%** **16%** **83%**\n\n\nItaly **1%** **6%** **93%**\n\n\nBulgaria **16%** **84%**\n\n\nSex Breakdown of Children by Country of Arrival\n\n\nOverall, the proportion of boys among arrivals remains high\n\n- nearly two-thirds of children who arrived through various\nMediterranean routes in the first half of 2019 were boys. Yet,\nthe proportion of girls arriving to Greece in the same period was\nsignificant - 42% of all child arrivals. This is due to the fact that\nchildren arriving to Greece are primarily accompanied, and the\nproportion of girls among accompanied children is overall much\nhigher as compared to children who travel alone.\n\n\nBOYS GIRLS\n\nGreece **58%** **42%**\n\n\nSpain **93%** **7%**\n\n\nItaly* **94%** **6%**\n\n\nBulgaria **83%** **17%**\n\n\n_Source:_ _", "output": {"entities": {"named_data": [], "descriptive_data": ["Age disaggregated data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001302", "page": 2, "chunk": 2, "title": "Refugee and Migrant Children in Europe: Accompanied, Unaccompanied and Separated: Overview of Trends (January - June 2019)", "pdf_url": "https://reliefweb.int/attachments/c8fecd47-8900-3b56-ba3b-f56e93921fb0/72643.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Age disaggregated data", "label": "DESCRIPTIVE_DATA", "score": 0.7989518046379089, "start": 566, "end": 588, "probe_score": 0.2833, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on social development issues"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000121", "page": 24, "chunk": 0, "title": "Sierra Leone - HIV/AIDS Response Project", "pdf_url": "http://documents1.worldbank.org/curated/en/710911468776784140/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on social development issues", "label": "VAGUE_DATA", "score": 0.581004798412323, "start": 1670, "end": 1703, "probe_score": 0.333, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " for the country and the climate, and how best to deal\nwith the operations and maintenance issues for school upkeep.\n\n\nThe list of sites for the Phase I schools follows. Note that the first year sites are fixed while there\nmay be some adjustments on the second year sites.", "output": {"entities": {"named_data": [], "descriptive_data": ["list of sites for the Phase I schools"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000149", "page": 32, "chunk": 2, "title": "Rwanda - Community Reintegration and Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/848391468777982563/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "list of sites for the Phase I schools", "label": "DESCRIPTIVE_DATA", "score": 0.5663033723831177, "start": 123, "end": 160, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Figure A17: Robustness changing treatment definition, VAT outcomes\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n(a) Amounts withheld\n\n\n\n(b) Effective tax rate\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n(c) Pr(Unrefunded=1)\n\n\n\n(d) Unrefunded balance\n\n\n\n_Note:_ This panel of figures plots the βt for dynamic DiD coefficients from Equation 1 for compliance effects of the reform adapted\n\nto four different treatment and control groups. The dark navy square markers correspond to our baseline preferred specification where\n\nthe treatment group is defined as those firms with a DCC usage-to-tax liability ratio above the 75th percentile of the usage distribution\n(DCC ⩾ p75|DCC = 1), and the control group is based on firms with usage below the 25th percentile (DCC ⩽ p25|DCC = 1).\n\nThe circle ocher-colored markers come from regressions where the treatment group is firms with a DCC usage-to-tax liability ratio above\nthe median of the usage distribution (DCC ⩾ p50|DCC = 1), and the control group is based on firms with usage below the median\n(DCC < p50|DCC = 1). The diamond olive-colored markers come from regressions where the treatment group is firms with some\nDCC usage (DCC = 1|withholding = 1), while control firms are those with any other type of withholding different from DCC,\nlike the government or large taxpayers (DCC = 0|withholding = 1). The orange triangle markers come from regressions\nwhere treatment firms are those with some DCC usage (DCC = 1|withholding = 1), while control firms are those without\nany sort of withholding (DCC = 0|withholding = 0). Every model is based on a quarterly balanced panel of firms filling VAT\n\nevery quarter between 2015q1-2018q4. Regressions also include firm-fixed effects and quarter-fixed effects interacted with industry and\n\nfirm’s size (measured", "output": {"entities": {"named_data": [], "descriptive_data": ["quarterly balanced panel of firms"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001210", "page": 57, "chunk": 0, "title": "idu1159620611a9821440d189681c5d134f6a158", "pdf_url": "https://local/prwp/idu1159620611a9821440d189681c5d134f6a158.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "quarterly balanced panel of firms", "label": "DESCRIPTIVE_DATA", "score": 0.8305470943450928, "start": 1539, "end": 1572, "probe_score": 0.9131, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "11. The WFP has carried out lengthy assessments before deciding to switch from the paper\nfood voucher modality to the pre-paid electronic voucher. WFP finds that the electronic voucher\nis appropriate in Lebanon because of the favorable financial environment and high assessment\nratings in comparison with other MENA countries. The electronic system allows WFP to track\ntransactions, to gather data on the frequency the cards are used, and for which commodities.\n\n\n12. WFP has signed a partnership agreement in September 2013 with MasterCard, and the\nlocal bank, Banque Libano-Fran `ҫ` aise (BLF). BLF has been selected as the service provider to\ndevelop and implement the prepaid card system for registered Syrian refugees. The system will\nenable the beneficiaries to purchase food commodities at shops preselected by WFP. The\ncontracted shops opened accounts with the partner bank and installed Points of Sale (POS) in\ntheir businesses. WFP has contracted roughly 285 shops all over Lebanon. Each beneficiary\nhousehold registered with a unique UNHCR Case Number will receive a Card. The Card will be\nreloaded on a monthly basis, on the 5th of the month, to cover food needs. The monthly credit to\nbe received will be US$30 for each family member registered with UNHCR.\n\n\n13. The project will rely on WFP to provide technical assistance in implementing the prepaid\nE-card voucher system for the extremely poor Lebanese households, especially those affected by\nthe Syrian crisis. The NPTP will collaborate with WFP to provide all the necessary\ndocumentation to distribute the e-card food voucher benefit on a monthly basis.\n\n\n14. The NPTP will provide a file of eligible beneficiaries (Household Registry Statement)\nonce or twice a month to WFP based on the agreed on criteria between NPTP and WFP. The\nHousehold Registry statement includes the NPTP household registration number, the family size,\nthe date of birth of the family head, gender of the household head, and relevant distribution SDC.\nThe NPTP beneficiary file is imported into", "output": {"entities": {"named_data": ["NPTP beneficiary file"], "descriptive_data": ["file of eligible beneficiaries", "Household Registry Statement", "Household Registry statement"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000047", "page": 38, "chunk": 0, "title": "Lebanon - Emergency National Poverty Targeting Program Project", "pdf_url": "http://documents.worldbank.org/curated/en/810511467987899324/pdf/PAD1030-ENGLISH-P149242-PUBLIC-FINAL-LEB-ENPTP-English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "file of eligible beneficiaries", "label": "DESCRIPTIVE_DATA", "score": 0.6896436810493469, "start": 1653, "end": 1683, "probe_score": 0.696, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Household Registry Statement", "label": "DESCRIPTIVE_DATA", "score": 0.5406385064125061, "start": 1685, "end": 1713, "probe_score": 0.4386, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Household Registry statement", "label": "DESCRIPTIVE_DATA", "score": 0.6091087460517883, "start": 1802, "end": 1830, "probe_score": 0.0097, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "NPTP beneficiary file", "label": "NAMED_DATA", "score": 0.6472800970077515, "start": 2000, "end": 2021, "probe_score": 0.2304, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<u>No. of treated</u>\ncountries\n\nNo. of control\ncountries\n\n\n\nNo. of controls\nwith\n<u>repetitions</u>\n\n\n\n<u>10</u> <u>10</u> <u>5</u> <u>5</u>\n\n\n10 10 7 7\n\n\n79 100 32 35\n\n\n\n_<u>Source:</u>_ <u>Own calculations based on the data described in the text.</u>\n\n\n\n_Notes_ : _p_ values in parentheses. In the upper row, they are estimated assuming independent observations,\nwhereas in the lower row, they are estimated assuming perfect correlations of repeated observations in\ncontrol countries.\n\n\n**<<B>>** _Dynamic panel methods_\n\n\nNext, we estimate the effect of democratization on protection using dynamic panel\n\n\nmodels. Specifically, we employ a dynamic D-in-D regression to control for the well\n\nknown persistence of agricultural protection. However, because the lagged dependent\n\n\nvariables in a fixed effects specification are mechanically correlated with the error term\n\n\nfor _N > T_, we also use a first difference Generalized Method of Moments (GMM)\n\n\nestimator (see Arellano and Bond 1991). The inclusion of a lagged protection variable on\n\n\nthe right-hand side may help to attenuate omitted variables bias because it captures\n\n\naccumulated (unobserved) factors that affect actual protection.\n\n\nTo reduce bias due to the contemporaneous presence of both fixed effects and the\n\n\nlagged dependent variable, we do not include countries for which fewer than 20 years of\n\n\ndata are available in the dynamic D-in-D regressions. In addition, to render the regressions\n\n\nmore comparable across dynamic estimators, the dynamic D-in-D specification does not\n\n\ninclude the continental-year interaction terms used in the static D-in-D regressions. <sup>26</sup>\n\n\nThe results of these additional regressions are", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data described in the text"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005491", "page": 26, "chunk": 0, "title": "wps6336", "pdf_url": "https://local/prwp/wps6336.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data described in the text", "label": "VAGUE_DATA", "score": 0.7723750472068787, "start": 222, "end": 248, "probe_score": 0.9956, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nBeirut Housing Rehabilitation and Cultural and Creative Industries Recovery (P176577)\n\n\n\n|Of which, are youth|Number of youth aged<br>between (18 -35 years old)<br>including cultural<br>practitioners, individuals in<br>cultural entities and<br>additional workers involved<br>in the implementation of<br>the cultural productions.|Quarterly|Progress,<br>Monitoring<br>and<br>Evaluation<br>Reports.<br>Estimates by<br>Project<br>Management<br>Team.|Number of youths will<br>be determined by<br>disaggregating the<br>beneficiary data of the<br>progress reports|Project Management<br>Team/UN-Habitat|\n|---|---|---|---|---|---|\n|Cultural entities supported in cultural<br>production work|Number of cultural entities<br>(grant recipients) defined as<br>local cultural<br>institutions/centers/associat<br>ions of a non-profit nature,<br>formal, based in Beirut. The<br>definition also includes<br>informal non-profit<br>associations such as local<br>“collectives”, based in<br>Beirut, with at least 1.5<br>years of experience or a<br>good track record in the CCI.|<br>Quarterly<br>|Progress,<br>Monitoring<br>and<br>Evaluation<br>Reports. Esti<br>mates by<br>Project<br>Management<br>Team<br>|Number of cultural<br>entities", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["beneficiary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 41, "chunk": 0, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "beneficiary data", "label": "VAGUE_DATA", "score": 0.6663320660591125, "start": 532, "end": 548, "probe_score": 0.238, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "used to identify the effects of any non-discriminatory policies on the side of exporters and\nimporters, following Heid _et al_ . (2015), which to some extent are present in this case. <sup>22</sup>\n\n\n**4.2** **Robustness Checks**\n\nSeveral robustness checks are performed, mainly by including several additional control variables as\n\nadditional policy variables such as the ones developed by ECIPE’s Digital Trade Restrictiveness Index\npart of the C ∗intl𝑜 **𝑜** term. More specifically, using equation (2), each regression model includes\n(DTRI), the OECD Digital Services Trade Restrictiveness Index (Digital STRI), as well as the WEF\nTechnology Readiness Indicator. The first two variables are estimated on the importers side (country\n_d_ ), whereas the latter is estimated on the side of the exporter (country _o_ ). Finally, as said above, the\nstudy adopts a panel series and re-estimates the baseline regression equation (1) and (2), including\nby using alternative trade data from the ITPD-E.\n\n\n**5.** **Results**\n\nThe results of the baseline regressions following equation (1) are reported in Table 3. Column 1-7\nfollow the sectoral groupings as presented in Annex Table A2. In order to enhance readability of the\n\nseparate table, which can be found in Annex Table A3. <sup>23</sup> Moreover, Table 3 first reports the\nmain variable of interests, the results from the GRAV𝑜 **𝑜** and C ∗intl𝑜 **𝑜** vectors are featured in a\npotential multicollinearity concerns that may arise by entering them simultaneously, even though\ncoefficient results of CB and DR under MODEL𝑜 **𝑜** when entered separately in order to avoid\ncountries", "output": {"entities": {"named_data": ["ITPD-E"], "descriptive_data": [], "vague_data": ["alternative trade data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002026", "page": 27, "chunk": 0, "title": "regulating personal data data models and digital services trade", "pdf_url": "https://local/prwp/regulating-personal-data-data-models-and-digital-services-trade.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "alternative trade data", "label": "VAGUE_DATA", "score": 0.5688148140907288, "start": 957, "end": 979, "probe_score": 0.9449, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "ITPD-E", "label": "NAMED_DATA", "score": 0.8599969744682312, "start": 989, "end": 995, "probe_score": 0.8921, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "s fight for its people. Strategies for refugee and\ndiaspora engagement, Ukraine Forum, Chatham House, February.\n\n\nUNHCR (2023). Poland: Multi-Sector Needs Assessment — Results Overview\n(MSNA 2023), October, <u>https://data.unhcr.org/fr/documents/details/104427</u>\n\n\nUNHCR (2025a). Poland: Socio-Economic Insights Survey in Poland - Results\n\n\n\nAnalysis (SEIS 2024). UNHCR, October, <u>https://data.unhcr.org/en/documents/</u>\n<u>details/115045</u>\n\n\nUNHCR (2025b). High employment rates, but low wages: a poverty assessment\nof Ukrainian refugees in neighboring countries, Regional Refugee Response for\nthe Ukraine Situation, Regional Bureau for Europe, UNHCR.\n\n\nUNHCR (2025c). Ukraine Multi-year Strategy 2025 – 2027, UNHCR, November.\n\n\nUrban M. (2022). Refugees will lift economy's potential, but challenges remain,\nResearch Briefing | Poland. Oxford Economics, <u>https://www.oxfordeconomics.</u>\n<u>com/resource/refugees-in-poland-will-lift-economys-potential-but-challenges-</u>\n<u>remain/</u>\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n47", "output": {"entities": {"named_data": ["Socio-Economic Insights Survey in Poland"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 23, "chunk": 5, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Socio-Economic Insights Survey in Poland", "label": "NAMED_DATA", "score": 0.5688410401344299, "start": 290, "end": 330, "probe_score": 0.0851, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ",700\n700 stateless persons in \n stateless persons in 1919 coun-\n coun-\ntries acquired nationality during \ntries acquired nationality during \n2013\n2013. This figure is likely to be re-\n. This figure is likely to be re-\nvised upwards as final annual statis-\nvised upwards as final annual statis-\ntical data become available.\ntical data become available. „\nCountries with known populations without reliable data\nFig. 16\nNumber of countries reporting statistics \non stateless persons  | 2004-2013\n‘04\n‘05\n‘06\n‘07\n‘09\n‘10\n‘11\n‘12\n‘13\n‘08\nCountries with reliable data\n30\n58\n49\n65\n11\n22\n19\n20\n48\n60\n54\n64\n14\n21\n17\n21\n72\n75\n17\n19\n31\nUNHCR Global Trends 2013", "output": {"entities": {"named_data": [], "descriptive_data": ["statis-\ntical data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001229", "page": 30, "chunk": 4, "title": "UNHCR Global Trends 2013: War's Human Cost", "pdf_url": "https://reliefweb.int/attachments/bccf108d-67b2-3a0c-9f57-b3c1e40ca740/Global_Trends_report_2013_V07_web_embargo_2014-06-20.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statis-\ntical data", "label": "DESCRIPTIVE_DATA", "score": 0.5534530282020569, "start": 286, "end": 304, "probe_score": 0.418, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "in accordance with this MOU, UNHCR has deployed 18 support staff in 2014 to the Asylum Service\n(including the COI Department and Regional Asylum Offices), to assist with its quality assurance activities. It should also be noted that the Asylum Service regularly produces detailed, accurate and reliable\nstatistical data and analysis. In order to maintain the progress made to date, EU MS and institutions\nneed to continue support, including through UNHCR, to the Asylum Service.\n\n\nThe processing time for adjudicating applications for international protection has improved significantly. While there are still unprocessed cases pending appeal for more than seven years under the\n“old procedure” operated by the police, the average time in all RAOs from registration to issuance of\nfirst instance decision is 90 days, while the average time from the appeal to the issuance of an appeal\ndecision is 49 days. <sup>103</sup> [^103: These figures represent the average processing time, according to official data by the Asylum Service.] Processing times for applications lodged in administrative pre-removal detention take on average slightly more than 100 days for both first and second instance.\n\n\nImprovements in the quality of the decision-making process have also had an impact on protection\nrates. While under the old system operated by the police, protection rates ranged between 0.86 per\ncent and 2.05 per cent from 2005 to 2014, the new asylum procedure has a first instance recognition\nrate of 17.2 per cent for refugee status and a 7.6 per cent protection rate for subsidiary protection.\nThe average rejection rate is still higher than in a number of other EU MS, and stands at 75.2 per cent.\nIt should be noted, however, that the protection rate for Syrians is 99.5 per cent, Eritreans 79.7 per\ncent, Somalis 66 per cent, Afghans 61.9 per cent, and Ethiopians 61.4 per cent (all figures as of August\n2014).\n\n\nThe appeal stage comprises an administrative examination on issues of fact and", "output": {"entities": {"named_data": [], "descriptive_data": ["official data by the Asylum Service"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000978", "page": 25, "chunk": 0, "title": "UNHCR observations on the current situation of asylum in Greece December 2014", "pdf_url": "https://reliefweb.int/attachments/91397b95-4179-3370-a136-8ab10908966d/54cb3af34.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.5698307156562805, "start": 303, "end": 319, "probe_score": 0.5496, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "official data by the Asylum Service", "label": "DESCRIPTIVE_DATA", "score": 0.858104407787323, "start": 994, "end": 1029, "probe_score": 0.8592, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " appeals and\nclaims received by households.\n\n42. With respect to the implementation arrangements of the e-card food voucher, the\nfollowing arrangements have been agreed upon: (i) WFP will conduct training for NPTP field\nwork coordinators and social workers, including on assessments, distribution, monitoring and\nhousehold visits; (ii) NPTP will be responsible for distribution and training of beneficiaries on\nthe use of the e-card, as well as assessing and monitoring of food security indicators; (iii) WFP\nwill provide the _Banque Libano-Française_ (BLF) with the necessary information/data based on\nthe NPTP database and operations for the production, activation and loading of e-cards; (iv)\nWFP will in turn share reports from the bank on transactions and spending patterns; and (v) WFP\nand its identified partner(s) will continue to support NPTP through joint reporting and\nmonitoring in the field. (For more details on the business processes and implementation, see\nAnnex II).\n\n\n**B.** **Results Monitoring and Verification**\n\n\n43. The results monitoring framework assesses progress towards the PDO through key\nindicators, focusing on expanding the coverage and social assistance of the NPTP. Specifically,\nthe project will monitor the number of direct project beneficiaries of education, health and e-card\nfood vouchers. All data will be collected disaggregating by gender to be able to monitor\nparticipation by women and girls. In addition, intermediate indicators will monitor program\nawareness and efficiency in terms of timing between application and eligibility notification, over\nthe life of the project.\n\n44. A computerized modular MIS, developed under the first phase of the NPTP, is the central\npiece of the monitoring and evaluation (M&E) system and includes a module to register\napplicant households in the NPTP database, record the results of their eligibility assessment\n\n\n14", "output": {"entities": {"named_data": ["NPTP database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000047", "page": 24, "chunk": 1, "title": "Lebanon - Emergency National Poverty Targeting Program Project", "pdf_url": "http://documents.worldbank.org/curated/en/810511467987899324/pdf/PAD1030-ENGLISH-P149242-PUBLIC-FINAL-LEB-ENPTP-English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NPTP database", "label": "NAMED_DATA", "score": 0.7947211861610413, "start": 607, "end": 620, "probe_score": 0.073, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**D. Financial Management Arrangements**\n\n**_Budgeting_**\n\n10. The budgeting process, from development to execution and control, will rely on WFP and\nFAO budgeting arrangements, which are deemed acceptable to the World Bank for the purposes\nof the proposed project.\n\n\n**_Accounting, Internal Control, and Internal Auditing_**\n\n\n11. The PIU for EAPSP will be responsible for consolidating accounting information\nsubmitted by WFP and FAO. Each supplier will maintain a separate account (International\nPublic Sector Accounting Standards accrual basis or any other acceptable accounting standard)\nin its records—a complete, true, and faithful record of all of the advances from proceeds of the\nfinancing and of all the expenditures paid from such advances.\n\n12. The project’s internal control and internal audit arrangements will rely on the\narrangements of the implementing entity identified by the government (in this case, the PIU for\nthe EAPSP), complemented by WFP- and FAO-related procedures for the day-to-day\nmanagement of project activities.\n\n**_Funds Flow and Disbursements_**\n\n\n13. Upon project effectiveness, applications for withdrawal of proceeds will be prepared by\nthe government and submitted to IDA. The special World Bank disbursement procedures will be\nused to establish a Blanket Commitment to allow the amount to be advanced. Funds withdrawn\nfrom the IDA credit account will be deposited directly into the UN bank accounts provided by\nFAO and WFP for their respective project components.\n\n\n14. The amount advanced will be documented through the quarterly unaudited IFRs as actual\nexpenditures are incurred by the WFP and FAO. Figure A3.1 diagrams the flow of funds.\n\n\n36", "output": {"entities": {"named_data": [], "descriptive_data": ["quarterly unaudited IFRs"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000007", "page": 45, "chunk": 0, "title": "Chad - Emergency Food and Livestock Crisis Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/179061468215115488/pdf/PAD11010PAD0P1010Box385329B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "quarterly unaudited IFRs", "label": "DESCRIPTIVE_DATA", "score": 0.7658491730690002, "start": 1563, "end": 1587, "probe_score": 0.4981, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and highest incomes.\nDetails are available in the Online Technical Appendix.\n\n27 Note that the GUS (2024) data for the host population is not exactly comparable, as it does not include microenterprises, it covers an earlier period and focuses on\ngross and average wages.\n\n\n28\n\n\n\n28 Lessem and Sanders (2020) modelled immigrant wage growth in the United States, finding that in a counterfactual model eliminating barriers to occupational entry\nwould lead to only small earnings increase for the average immigrant, but a substantial increase for the most highly skilled.\n\n\n29", "output": {"entities": {"named_data": ["GUS (2024) data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 14, "chunk": 4, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "GUS (2024) data", "label": "NAMED_DATA", "score": 0.8045365214347839, "start": 96, "end": 111, "probe_score": 0.2908, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 1 _ Г\n\n\n\nу '`\n\n\n\n_\n\n\n```\n ц\n\n```\n\n\n\n - _L а - и л _ 1 _ _,\n\n\n\nj.\n\n\n\n_ _ \n\n```\nг\n\n```\n\n```\n�\n\n```\n\n\n® Л\n\n\n```\n�\n```\n\n: П\n\n\n\n. V:\n\n\n\n(\n\n\n\n{\n\n\n\n. ......... .....                                                                                                                                  - ��,                                                                                                                                  - р ::_                                                                                                                                  - .:... �� <sup>�</sup> <sup>:</sup> <sup>И</sup>\n\n- r I` ;. г\n\n\n```\n�\n\n```\n\n\nr I` ;., г\n\n\n\n\n- <sup>-.</sup> ГЬ - - - - .-. ., - - .4'\n\n\n```\n�\n\n```\n\n\n\n  - .4'  - 1... . ..\n\nу '\n```\nС\n\n```\n\n\n'\n```\nС\n```\n\n. _                  \n\n```\n                                                           С\n```\n\n... _... ��� i_ . �� _  - >._  ��                           -                           \n\n```\nу\n\n```\n\n\n7\n\n```\n�\nг �\n```\n\n_ L'\n```\n          С\n\n```\n\n```\nх х � х х х х � х х х\n```\n\nг _ ь r        - 1        - _ а г i, �а r`i га г 1 _n_1 г ` а\nr - y м\n\nг <sup>,</sup> а г r г i г <sup>`</sup> у г i rv г <sup>��</sup> г г 1 �а г <sup>-1</s", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017645", "page": 17, "chunk": 1, "title": "Ethiopia - Oromia Forested Landscape Proejct - Audit Report July 7, 2019", "pdf_url": "https://documents.worldbank.org/curated/en/750471582557655346/pdf/Ethiopia-Oromia-Forested-Landscape-Proejct-Audit-Report-July-7-2019.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Economic Survey of Syrian Refugees in the Kurdistan Region of Iraq, April 2014**\n\n## **CONCLUSIONS**\n\n\nThe main purpose of this assessment was to provide an overview of the livelihoods strategies developed by Syrian\nrefugees living within camps throughout KRI, while evaluating the relative importance of CFW within their incomegenerating activities. This report aimed at understanding how Syrian refugees are fulfilling their basic needs and how\nthat relates to their income-generating activities, if any.\n\n\nAs presented above, nearly half (47%) of households had no source of cash/income in the 30 days preceding the\nassessment. Furthermore, only 20% of interviewees reported to fully be able to meet their household needs with their\nsource of income, which signifies that 80% are not or not fully (65%) able to. This in turn will contribute to the need to\naccrue debt and it will be crucial to see what mechanisms could be implemented to ensure the most vulnerable\nhouseholds do not worsen their situation. CFW activities are reported as the most important source of income for\nrefugees living in camps (53% reported it as their main income source), but some significant inequalities remain hitherto\nwhen it comes to CFW hiring process, as shown by the fact that less than half (43%) of households reported having\nbeen hired since their arrival in the camps and only 12% of women were ever engaged in CFW activities. There is room\nfor improvement as most organisations seek to render the processes more equitable and transparent. This should also\nextend to other programmes oriented towards vocational training, with English classes, computer training and adult\nliteracy classes offering equal opportunities to both men and women <sup>15</sup> [^15: Most FGD recommended the above mentioned vocational trainings, regardless of gender.] . Finally, comparing the situation between all the\ncamps allows to point out the most pressing need for livelihood assistance programmes in Gawilan, Darashakran and\nBasirma camps.\n\n\nA consistent picture true for all the refugee camps emerges from", "output": {"entities": {"named_data": ["Economic Survey of Syrian Refugees"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000688", "page": 23, "chunk": 0, "title": "Economic Survey of Syrian Refugees in the Kurdistan Region of Iraq, April 2014", "pdf_url": "https://reliefweb.int/attachments/65990d0d-ded7-3935-8405-bcfdd2df666c/REACHInitiative_KRISyrianRefugeesEconomicSurvey_validated.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Economic Survey of Syrian Refugees", "label": "NAMED_DATA", "score": 0.8867298364639282, "start": 2, "end": 36, "probe_score": 0.9053, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". The calculated household weight was\nthen applied to each individual within the\nhousehold. The table below shows the data used\nand resulting weights. The calculated household\nweight was also applied to each individual within\nthe household.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|800|79%|61,301|50%|\n|---|---|---|---|\n|69|7%|6,126|5%|\n|113|11%|51,740|42%|\n\n\n\n\n\n\n\n\n\n\n\n\n\n12\n\n\n\nSOCIO-ECONOMIC INSIGHTS SURVEY FINAL REPORT, ROMANIA 2024", "output": {"entities": {"named_data": ["SOCIO-ECONOMIC INSIGHTS SURVEY"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001333", "page": 12, "chunk": 1, "title": "Romania Socio-Economic Insights Survey (SEIS) 2024 - Final Report", "pdf_url": "https://reliefweb.int/attachments/cd5961a4-039a-582e-8b9a-1a66f308a256/Romania%20Socio-Economic%20Insights%20Survey%202024%20-%20Final%20Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SOCIO-ECONOMIC INSIGHTS SURVEY", "label": "NAMED_DATA", "score": 0.8790660500526428, "start": 363, "end": 393, "probe_score": 0.9864, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nPromoting Financial Inclusion Policies and Regulations in Jordan ( P163719 )\n\n\n<u>Implementing Agency(MNIS)</u>\n\n\n**B. Introduction and Context**\nCountry Context\n\n   - **Economic growth has been sluggish in Jordan** . GDP growth slowed to an average of 2.6 percent between 2010\n\nand 2013, following a strong performance of 6.5 percent between 2000 and 2009. Real GDP growth was 2.4\npercent in 2015, and GDP in 2016 is expected to have further decelerated.\n\n   - **Ongoing conflict in Syria and large influx of refugees** [1] **have adversely affected Jordan’s economy** .\n\nUnemployment remains high: estimates increased from 11.9 percent in 2014 to 15.1 percent in the first three\nquarters of 2016[2] with youth and women particularly affected (35.5 percent and 23.9 percent\nrespectively)[3]. The refugee crisis is also weighing on the public finances where public debt to GDP increased\nfrom 89 percent in 2014 to 93 percent in 2016.\n\n   - **The economic situation in Jordan calls for innovative approaches to stimulate economic growth and job**\n\n**creation.** In that respect, an inclusive financial system can play a critical role in job creation, poverty reduction\nand overall sustainable economic growth. Moreover, a recent IMF and NBER Working Paper[4] provides\nevidence on direct linkages between financial inclusion and GDP growth. At the microeconomic level,\nindividuals who have access to and use formal financial services are able to start and expand businesses (hence\ncreating jobs in addition to self-employment), invest in education, manage risks, and absorb financial shocks.\n\n\n[1] United Nations Higher Commissioner for Refugees (UNCHR) estimates there are approximately 655,496 Syrian\nrefugees in Jordan as of January 2017.\n\n\n[2] The World Bank, Jordan Economic Monitor, Fall 2016.", "output": {"entities": {"named_data": ["Jordan Economic Monitor"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000013", "page": 2, "chunk": 0, "title": "Jordan - Promoting Financial Inclusion Policies and Regulations in Jordan Project : Project Information Document (Concept Stage) - Promoting Financial Inclusion Policies and Regulations in Jordan - P163719", "pdf_url": "http://documents.worldbank.org/curated/en/280421491408992654/pdf/IL-AISPID-CP-P163719-04-05-2017-1491408966691.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Jordan Economic Monitor", "label": "NAMED_DATA", "score": 0.704090416431427, "start": 1781, "end": 1804, "probe_score": 0.6974, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". About 45 percent of all children\naged 6-59 months in the Palestine Territory are suffering from chronic malnutrition (stunting):’ and 36\n\n\n\n**16**\n\n\n**17**\n\n\n**18**\n\n\n19\n\n\n**20**\n\n\n\n_Nutritional_ **_Assessment_** _of_ **_the_** **_West Bank_** & _Gaza Strip_ by Johns Hopkins University/Al Quda University and financed by\nUSAID through CARE International, September 2002.\n\nUniversity of Geneva, 2002.\n\nAn interview was conducted in April 2002 with a representative from Terre des Hommes (Ard El Insan), an NGO in the\nGaza Strip working with malnourished children. In the four clinics run by Terre des Hommes, 5,704 malnourished children\nwere treated in 2001 in comparison with 2,528 in 2000. The Medical Director of Terre des Hommes reported that many\nchildren below the age of two are malnourished, because they are consistently fed only with tea and bread.\n\nA joint USAID/John Hopkins University study on nutrition published in September, 2002 and a Nutrition Survey (NS-2002)\njointly conducted by PCBS, the Ministry of Health, UNICEF, and the Institute of Community and Public Health at Bir Zeit\n\nUniversity during the period March 23-June 30,2002.\nStunting (low height for age) i s an indicator of chronic inadequate nutrient intake due to one or more factors, including food\nscarcity, food distribution pattems within households, and lack of knowledge of proper infantkhild feeding practices. The\n\n\n22", "output": {"entities": {"named_data": ["Nutrition Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000047", "page": 25, "chunk": 2, "title": "West Bank and Gaza - Social Safety Net Reform Project", "pdf_url": "http://documents1.worldbank.org/curated/en/326701468762010863/pdf/27761.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Nutrition Survey", "label": "NAMED_DATA", "score": 0.7067126631736755, "start": 954, "end": 970, "probe_score": 0.9941, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**COLOMBIA** | October 2024\n\n\n**Methodology**\n\n\nBetween June and July 2024, the Protection Cluster and the Protection sector of the GIFMM participated, together with\nthe Areas of Responsibility (AoR) gender-based violence, child protection, mine action and the sub-group on trafficking and\nsmuggling, in the humanitarian programming workshops for the update of the Community Priority Response Plan (PRPC)\nwith the intention of deepening protection issues in the territories prioritized by the Humanitarian Country Team. This\nparticipation in the territory complemented the review of official data extracted mainly from the Ombudsman's Office\n(Early Warnings); new victimizing events registered by the Victims Unit (UARIV) and indicators for monitoring the situation\nof vulnerability derived from forced internal displacement (Vulnerability Overcoming Indicator). The analysis was based on\nthe Protection Analysis Framework (PAF) and on quantitative and qualitative data from the territorial teams of the\nProtection Cluster and the Protection sector, as well as from partners of the protection coordination structure in the\ncountry, with whom it was possible to deepen the analysis of risks in the territories most affected by the overlapping\nhumanitarian emergencies in Colombia. It should be noted that the Protection Cluster and the Protection Sector carry out\nprotection monitoring missions and hold bimonthly meetings with the territorial teams, which enrich the protection\nanalysis presented in this document.\n\n\n**Limitations**\n\n\nThe qualitative data is limited to areas where the Protection Cluster and the Protection sector have territorial teams.\nIntegrated information is available for the Pacific Axis, the Border with Venezuela axis, and capital cities. The south-east of\nthe country has a limited presence of protection actors, which is why the related information is mainly official.", "output": {"entities": {"named_data": ["Early Warnings", "Vulnerability Overcoming Indicator"], "descriptive_data": [], "vague_data": ["quantitative and qualitative data", "qualitative data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000314", "page": 16, "chunk": 0, "title": "Colombia: Protection Analysis Update - Trend analysis on Protection Risks related to the armed conflict and natural disasters (October 2024)", "pdf_url": "https://reliefweb.int/attachments/255e4c26-c596-41c2-a53c-8b7862e579d7/pau24_protection_analysis_update_colombia_oct-24_english_revfinal.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Early Warnings", "label": "NAMED_DATA", "score": 0.5675543546676636, "start": 643, "end": 657, "probe_score": 0.0831, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Vulnerability Overcoming Indicator", "label": "NAMED_DATA", "score": 0.6448504328727722, "start": 826, "end": 860, "probe_score": 0.1301, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "quantitative and qualitative data", "label": "VAGUE_DATA", "score": 0.6654642820358276, "start": 936, "end": 969, "probe_score": 0.4727, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "qualitative data", "label": "VAGUE_DATA", "score": 0.5527065396308899, "start": 1539, "end": 1555, "probe_score": 0.2572, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda: Roads and Bridges in the Refugee Hosting Districts Project (P171339)\n\n\nDATASHEET\n\n\n|Country(ies)|Project Name|Col3|\n|---|---|---|\n|Uganda|Uganda: Roads and Bridges in the Refugee Hosting Districts/Koboko-Yumbe-Moyo Road<br>Corridor Project|Uganda: Roads and Bridges in the Refugee Hosting Districts/Koboko-Yumbe-Moyo Road<br>Corridor Project|\n|Project ID|Financing Instrument|Environmental and Social Risk Classification|\n|P171339|Investment Project<br>Financing|High|\n\n\n\n\n\n\n|[ ] Multiphase Programmatic Approach (MPA)|✓<br>[ ] Contingent Emergency Response Component (CERC)|\n|---|---|\n|[  ] Series of Projects (SOP)|[  ] Fragile State(s)|\n|[  ] Performance-Based Conditions (PBCs)|[  ] Small State(s)|\n|[  ] Financial Intermediaries (FI)|[✓] Fragile within a non-fragile Country|\n|[  ] Project-Based Guarantee|[  ] Conflict|\n|[  ] Deferred Drawdown|[✓] Responding to Natural or Man-made Disaster|\n|[  ] Alternate Procurement Arrangements (APA)|[  ] Hands-on Enhanced Implementation Support (HEIS)|\n\n\n\n\n\n\n\n\n\n\n\nPage 1 of 80", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 5, "chunk": 0, "title": "Uganda - Roads and Bridges in the Refugee Hosting Districts/Koboko-Yumbe-Moyo Road Corridor Project", "pdf_url": "http://documents.worldbank.org/curated/en/834931600048847296/pdf/Uganda-Roads-and-Bridges-in-the-Refugee-Hosting-Districts-Koboko-Yumbe-Moyo-Road-Corridor-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_Birth order and family size_\n\n\n38. A number of questions were asked in an effort to form a picture of the family\nbackground of the young people interviewed, including their birth order, number of\nsiblings, father‟s occupation and the child‟s level of education. Unfortunately the\ninformation available on many of these questions is incomplete, making it difficult to\ncross tabulate or to draw any precise conclusions from the findings.\n\n\n39. With regard to birth order, information was available for just 59 of the 110 boys\nincluded in the analysis. The findings appear to support the notion that it is generally\nthe oldest son who makes the journey (i.e. 43 of the 59 recorded). The others for\nwhom information was available were either the second son (eight cases), often\nfollowing the death or disappearance of the older brother. Family size was generally\nquite small (two or three children), with larger family sizes (six to eight children) in\nthe minority.\n\n\n_Place of birth_\n\n\n40. The large majority (100) of the 110 boys were born in Afghanistan, with just\nseven born in Iran and three in Pakistan. The ten boys born outside Afghanistan\nwere in Turkey and Greece at the time of interview.\n\n\n41. Information on the province of birth was available for 80 of the 100 boys born\nin Afghanistan. They originated from 19 of the country‟s 34 provinces. Almost a third\nof the boys for whom information was available (24) were born in Ghazni, with\nseven each from Nangarhar and Kabul, five from Laghman, and four each from\nBaghlan, Logar and Day Kundi. <sup>10</sup> [^10: When compared to the total population by province, no significant pattern could be determined since\nthey include relatively heavily populated provinces such as Kabul, Ghazni and Nangarhar, as well as\nsparsely populated provinces like Laghman, Logar and Day Kundi.]\n\n\n42. Smaller numbers were born in Bamyan, Balkh, Uruzgan and Hirat (three each", "output": {"entities": {"named_data": [], "descriptive_data": ["total population by province"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000844", "page": 12, "chunk": 0, "title": "Trees only move in the wind: A study of unaccompanied Afghan children in Europe", "pdf_url": "https://reliefweb.int/attachments/7c7122e3-e385-3032-b2b3-02617da54340/CA4C0DC9301894C3C1257742000DDBC0-Full_Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "total population by province", "label": "DESCRIPTIVE_DATA", "score": 0.5816812515258789, "start": 1592, "end": 1620, "probe_score": 0.843, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "</u>_ .\nAccording to the latest Annual School Census, public schools enroll 30 thousand refugee students (in 1,681 schools)\nand 280 thousand IDPs (in 1,852 schools). While IDP children are concentrated in three Darfur states (68 percent of\n\n\nPage 14 of 40", "output": {"entities": {"named_data": ["Annual School Census"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000024", "page": 18, "chunk": 2, "title": "Sudan - Basic Education Emergency Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/208261588781212409/pdf/Sudan-Basic-Education-Emergency-Support-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Annual School Census", "label": "NAMED_DATA", "score": 0.8345101475715637, "start": 32, "end": 52, "probe_score": 0.9861, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "</sup>\n\n\n\nversions of the Global Procurement <sup>Plan and the following year's</sup> <sup>annual</sup> <sup>procurement</sup> <sup>plan.</sup> <sup>Participating</sup>\n\n\n\nService Providers will be required <sup>to</sup> <sup>include</sup> <sup>procurement</sup> <sup>plans in</sup> <sup>their subproject proposals.</sup> <sup>The</sup>\n\n\n\ntechnical team reviewing community <sup>subproject proposals must ensure adequacy of a</sup> <sup>sub-project</sup>\n\n\n\nprocurement plan before the <sup>proposal</sup> <sup>is</sup> <sup>approved.</sup> <sup>Each</sup> <sup>quarter,</sup> <sup>NaCSA will</sup> <sup>submit</sup> <sup>to IDA a</sup>\n\n\n\nprocurement monitoring report <sup>as part of the Financial</sup> <sup>Management Report (FMR),</sup> <sup>to show how</sup> <sup>each</sup>\n\n\n\ncontract on the procurement <sup>plan</sup> <sup>has progressed.</sup> <sup>The POM</sup> <sup>will include</sup> <sup>sample formats</sup> <sup", "output": {"entities": {"named_data": [], "descriptive_data": ["procurement monitoring report"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020909", "page": 45, "chunk": 6, "title": "Kenya - Livestock Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/970171468277158233/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "procurement monitoring report", "label": "DESCRIPTIVE_DATA", "score": 0.8535922765731812, "start": 641, "end": 670, "probe_score": 0.0289, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " opportunities for Jordan to\n\nparticipate in shaping and influencing the global agenda through knowledge sharing with SSBs, which can have\na significant impact on how the global financial system helps or hinders financial inclusion.\n\n   - **Sub-component 2.2:** Organizing technical workshops on priority areas that would support Jordan meet its\n\nMaya Declaration commitments. This could potentially include the following topics: Development of Digital\nFinancial Services; Building and Analyzing Financial Inclusion Data; Consumer Protection and Financial Literacy;\nCross Border Remittances; Anti-Money Laundering/Combating the Financing of Terrorism (AML/CFT).\n\n   - **Sub-component 2.3:** Supporting the sharing of experience learned on regulatory sandboxes[1], accelerators\n\nand hubs from across the World. This sub-component will cover the expenses related to study tours, training\nand workshops.\n\n\n   - **Component 3: Establishing regulatory sandbox to facilitate the development and adoption of innovative**\n\n**financial technology (US$350,000).**\n\n\n   - CBJ is seeking to leverage RegTech[1] approaches to enhance the effectiveness of its regulatory and\n\nsupervisory arrangements and, ultimately, facilitate the adoption of innovative financial technology.\nSupporting the development of eKYC as well would enhance financial inclusion and make it easier particularly\nfor women due to mobility and other factors[2]. In addition, eKYC will be an effective inclusive tool by building\nan up-to-date database which would also include refugees. This will ensure higher integrity standards in the\nfinancial system and will provide the regulator with enhanced monitoring tools. Eventually, it will allow the\nimplementation of efficient and risk-based AML/CTF.\n\n\nApr 05, 2017 Page 8 of 11", "output": {"entities": {"named_data": [], "descriptive_data": ["up-to-date database"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000013", "page": 7, "chunk": 1, "title": "Jordan - Promoting Financial Inclusion Policies and Regulations in Jordan Project : Project Information Document (Concept Stage) - Promoting Financial Inclusion Policies and Regulations in Jordan - P163719", "pdf_url": "http://documents.worldbank.org/curated/en/280421491408992654/pdf/IL-AISPID-CP-P163719-04-05-2017-1491408966691.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "up-to-date database", "label": "DESCRIPTIVE_DATA", "score": 0.5298233032226562, "start": 1490, "end": 1509, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "</sup>\n\n\n\nversions of the Global Procurement <sup>Plan and the following year's</sup> <sup>annual</sup> <sup>procurement</sup> <sup>plan.</sup> <sup>Participating</sup>\n\n\n\nService Providers will be required <sup>to</sup> <sup>include</sup> <sup>procurement</sup> <sup>plans in</sup> <sup>their subproject proposals.</sup> <sup>The</sup>\n\n\n\ntechnical team reviewing community <sup>subproject proposals must ensure adequacy of a</sup> <sup>sub-project</sup>\n\n\n\nprocurement plan before the <sup>proposal</sup> <sup>is</sup> <sup>approved.</sup> <sup>Each</sup> <sup>quarter,</sup> <sup>NaCSA will</sup> <sup>submit</sup> <sup>to IDA a</sup>\n\n\n\nprocurement monitoring report <sup>as part of the Financial</sup> <sup>Management Report (FMR),</sup> <sup>to show how</sup> <sup>each</sup>\n\n\n\ncontract on the procurement <sup>plan</sup> <sup>has progressed.</sup> <sup>The POM</sup> <sup>will include</sup> <sup>sample formats</sup> <sup", "output": {"entities": {"named_data": [], "descriptive_data": ["procurement monitoring report"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017338", "page": 45, "chunk": 6, "title": "Uganda - Third Structural Adjustment Credit", "pdf_url": "https://documents.worldbank.org/curated/en/730711468317931990/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "procurement monitoring report", "label": "DESCRIPTIVE_DATA", "score": 0.8535922765731812, "start": 641, "end": 670, "probe_score": 0.0289, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Because we are taking the log of the determinant, the log is equal to the sum of the log of each of the\neigenvalues. If we let the eigenvalues be given by I, the log likelihood function can then be written as\n\n\n\n<u>��</u> <sup>𝑙𝑛𝜎�</sup> <sup>�</sup> <u>��</u>\n\n\n\n<u>��</u> <sup>∑</sup> ���� 𝑙𝑛�𝛾�� - ���\n\n\n\n��� <sup>�</sup> <sup>�𝑦�𝑋�𝛽�</sup> �𝑉����𝑦�𝑋�𝛽� (5)\n\n\n\n𝑙𝑛𝐿��\n\n\n\n\n<u>�</u>\n\n\n\n\n<u>�</u> <u>�</u>\n\n- <sup>𝑙𝑛2𝜋�</sup> \n\n\nWith the aggregated variance matrix for Brazil having 5,434 rows and columns, the calculation can take\nseveral minutes. One of the ways to speed this up is to compute a grid of eigenvalues, say for equal to\n0 to 0.9 with a step of 0.1, and the same for . Then we could use bilinear interpolation on this grid of\neigenvalues to approximate the log of the Jacobian for any pair of  and . In our program written in R,\nwe create this as an option, but generally computed the exact Jacobian instead of the approximate\nJacobian.\n\n\nOnce the parameters are estimated, it is then possible to compute the predicted value at the aggregated\nlevel of the dependent variable, and subtracting that from the actual value of the dependent variable\nleaves the residual. We can use this residual to make the prediction at the disaggregated level perfectly\nsum to the actual value of the dependent variable at the aggregated level. The residual value can be\ntreated as a “fixed effect” for the", "output": {"entities": {"named_data": [], "descriptive_data": ["aggregated variance matrix for Brazil"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000482", "page": 10, "chunk": 0, "title": "generating gridded agricultural gross domestic product for brazil a comparison of methodologies", "pdf_url": "https://local/prwp/generating-gridded-agricultural-gross-domestic-product-for-brazil-a-comparison-of-methodologies.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "aggregated variance matrix for Brazil", "label": "DESCRIPTIVE_DATA", "score": 0.6909230351448059, "start": 438, "end": 475, "probe_score": 0.9319, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n#### **Model calibration**\n\n\n\nWe introduce a positive productivity\nshock into the Deloitte D.Climate\nmodel, reflecting empirical findings that\nrefugee inflows coincided with stronger\nlabour-market outcomes, to offset any\npotential adverse effects. Although higher\nemployment rates among Ukrainian\nrefugees correlate with improved job and\nwage outcomes for Polish citizens, we take\na deliberately conservative approach in\nour general equilibrium simulations. While\ndescriptive statistics and econometric\nestimates point in a positive direction, the\navailable data remain too sparse for firm\n\n\n**Chart 31. Labour market activity rates**\n\nWomen in 15-64 age group\n\n\n\nconclusions. <sup>31</sup> [^31: Deloitte has not received data that would be detailed as to citizenship, poviat, sex, age group, occupational group, and ZUS insurance code that would be suitable\nfor econometric approach.] On the other hand, a default\nDeloitte D.Climate model estimation is\nin line with the previously mentioned\ncanonical model. This yields a 1.35%\ndecrease in wages and a 0.4 percentage\npoint increase in the unemployment rate,\nwhich is implausible. Therefore, a positive\nmarginal productivity of labour shock has\nbeen added to the model and calibrated to\neliminate the impact on the unemployment\nrate throughout the simulation years of\n2022, 2023, and 2024. While it is possible\nthat the unemployment rate could fall\ndespite the influx of Ukrainian refugees due\n\n\n\nto factors other than productivity growth,\nthis is unlikely. Any negative impact could\nonly arise if other workers left the labour\nforce or reduced their working hours. No\nevidence of this is seen in recent Eurostat’s\nLabour Force Survey data for the Polish\neconomy, where activity rates continued\nto grow, while the average number of usual\nweekly hours worked in full- and parttime employment remained fairly stable,\nparticularly for women (who should be\ncloser substitutes for Ukrainian refugees,\nmost of whom are also women; see charts\nbelow).\n\n\n\nAnalysis of the impact of refugees from", "output": {"entities": {"named_data": ["Eurostat’s\nLabour Force Survey data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 21, "chunk": 0, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Eurostat’s\nLabour Force Survey data", "label": "NAMED_DATA", "score": 0.5649102330207825, "start": 1729, "end": 1764, "probe_score": 0.9924, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".html.](http://www.unhcr.org/54cf9a8f9.html)\n\n**(59)** Excludes data that were reported as unknown or unclear.\n\n\n\n15 per cent mark in Brazil, Bosnia and Herzegovina,\nIsrael, and Serbia and Kosovo (S/RES/1244 (1999)). <sup>**(57)**</sup>\n\n\nLocation\n\nThe geographic location of refugees is traditionally classified as urban, rural or various/unknown\nif this location remains unclear. Even though the\nnational definitions of ‘urban’ and ‘rural’ can differ between countries, UNHCR is consistent in\nthe classification of such refugee locations. The\ndistinction between the two locations is important to understand the diverse needs of refugees\nin a given geographic location. In addition to the\nurban-rural distinction, UNHCR collects data on\nthe type of accommodation in which individuals\nreside. This is classified into six main categories:\nplanned/managed camp, self-settled camp, collective centre, reception/transit camp, individual\naccommodation (private), and various/unknown if\nthe information is unknown or unclear. <sup>**(58)**</sup>\n\nInformation on the geographic location of\nrefugees was reported for 12.2 million out of\nall refugees under UNHCR’s mandate (85%). <sup>**(59)**</sup>\nThis high proportion is the direct result of\nUNHCR’s efforts to collect detailed location information. It is interesting to note that while the\naccommodation type and the geographic location\nof some refugees remain unknown, the uncertainty in the data is gradually decreasing. At the\nend of 2014, the exact accommodation type was\nunknown for 17 per cent of the world’s refugees.\nThis compares to 19 per cent in 2013, 20 per cent\nin 2012, and 26 per cent in 2011.\n\nBased on available evidence", "output": {"entities": {"named_data": [], "descriptive_data": ["data on\nthe type of accommodation"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000809", "page": 40, "chunk": 1, "title": "UNHCR Global Trends: Forced Displacement in 2014", "pdf_url": "https://reliefweb.int/attachments/770fdfd8-d5c3-3438-a25c-1f02a52df5b9/556725e69.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on\nthe type of accommodation", "label": "DESCRIPTIVE_DATA", "score": 0.6464569568634033, "start": 731, "end": 764, "probe_score": 0.1013, "gold": "NON_MENTION", "gold_tier": "human-final"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "** prior action **_5,_** PRSC **9** prior action **7).**\n\n\n20. **Component** 2.2 **Education:** i) improve the equitableness of teacher deployment\nand ii) improved accountability of head teachers (PRSC **8** prior action **6,** PRSC **9** prior\naction **8,** PRSC **10** trigger **7).**\n\n\n21. **Component** **2.3** **Water** **and Sanitation:** i) increase the functionality of rural\nwater facilities and Water for Production (WfP) facilities; and ii) improve the levels of\nsanitation and hygiene (PRSC **8** prior action **7,** PRSC **9** prior action **9).**\n\n\n22. **Component** **2.4** **Transport:** i) help ensure stable funding for road maintenance\nand increased quality of the maintenance work **by** year-by-year monitoring of road\nquality **by** first generating national, district and sub-district data on the quality of roads,\nstarting with the set of baseline data, and establishing a monitoring and evaluation\nframework to systematically track improvements in the sector; and ii) improve\ntransparency and accountability in the roads subsector (Uganda National Roads\nAuthority-UNRA) which would seek to obtain procurement accreditation from PPDA\nand begin implementation of an independent and parallel bid evaluation process (PRSC **8**\nprior action **8,** PRSC **9** prior action **10,** PRSC10 trigger **8).**\n\n\n**1.5** **", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017959", "page": 21, "chunk": 1, "title": "Uganda - Eighth and Ninth Poverty Reduction Credits Project : Uganda - Eighth and Ninth Poverty Reduction Credits Project", "pdf_url": "https://documents.worldbank.org/curated/en/772461468113066085/pdf/ICR29590P101230C0disclosed020250140.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "baseline data", "label": "VAGUE_DATA", "score": 0.6472479701042175, "start": 863, "end": 876, "probe_score": 0.1244, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Map 2. Number of households evicted outside IDP sites by district, January–\nOctober 2023\n\n\nSource: UNHCR (unpublished)\n\n\nData from NPC responders showed that household eviction numbers outside IDP sites in\n2023 were highest in Amran, At Ta’iziyah (Ta’iz governorate), Dhamar City (Dhamar), Sa’dah,\n(Sa’dah) and Sanhan wa Bani Bahlul (Sana’a).\n\nFigure 3. Districts with the highest number of households evicted outside IDP\nsites, January–October 2023\n\n\nSource: NPC (unpublished)\n\n\n### **KEY FINDINGS**\n\n\n- There is an increasing trend of private landowners requesting IDPs to vacate their land for\ntheir own use and purposes, often owing to property speculations.\n\n- Similarly, in light of the prospects of peace and economic recovery, the authorities are\nincreasingly claiming back land and reinstating services in public buildings, such as the\nschools and health centres that IDPs are using as collective centres.\n\n- Many IDPs not living in IDP sites but renting flats or houses are being evicted because of\ntheir inability to pay rent. This trend is worsening with increasing inflation, unemployment,\nand livelihood losses (Consultation session with NPC responders 29/08/2023).\n\n- Forced evictions in Yemen overall have increased by an estimated 10% in 2023 compared\nto 2022. From January–October 2023, the NPC and CCCM responders recorded\nthe eviction of or eviction threats to close to 61,400 individuals. The data showed the\nhighest numbers in Ma’rib and Ta’iz in the areas under the control of the Internationally\nRecognized Government of Yemen (IRG). In the areas controlled by the de-facto authority\n(DFA) in the north of Yemen (also known as the Houthis), the highest numbers were in\nAd Dali, Al Bayda, Al Hodeidah, Al Jawf, Amanat Al Asimah, Amran, Dhamar,", "output": {"entities": {"named_data": [], "descriptive_data": ["Data from NPC responders"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001681", "page": 2, "chunk": 0, "title": "National Protection Cluster and ACAPS Thematic: Yemen - Forced evictions analysis (28 December 2023)", "pdf_url": "https://www.acaps.org/fileadmin/Data_Product/Main_media/20231228_ACAPS_Yemen_analysis_hub_forced_evictions_analysis.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data from NPC responders", "label": "DESCRIPTIVE_DATA", "score": 0.8220587372779846, "start": 121, "end": 145, "probe_score": 0.9587, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n# **Background**\n\nOver three years have elapsed since the start of the full-scale invasion of Ukraine, an event which has led to\nthe largest displacement crisis in Europe since World War II. As of the end of 2024, 6.3 million refugees from\n[Ukraine were recorded across Europe, close to 2 million of whom are located in ten Regional Refugee](https://www.unhcr.org/europe/publications/regional-refugee-response-plan-2025-2026)\n<u>[Response Plan](https://www.unhcr.org/europe/publications/regional-refugee-response-plan-2025-2026)</u> countries: Bulgaria, Czechia, Estonia, Hungary, Latvia, Lithuania, Poland, Republic of Moldova,\nRomania, and Slovakia. This report aims to assess the livelihood situation of this population based on the 2024\nround of data collected by the Socio-Economic Insights Survey (SEIS), which received responses from 8,723\nhouseholds containing 19,803 individuals. Figures for 2023 are derived from a similar exercise <sup>7</sup> [^7: The MSNA, which ran in 7 countries: Bulgaria, Czech Republic, Hungary, Republic of Moldova, Poland, Romania, and Slovakia] conducted in\n2023.\n\n# **Key findings**\n\n**Refugee poverty rates remain high, albeit improved from 2023**\n\n\nThe 2024 SEIS equivalized <sup>8</sup> disposable income data indicates that just over one in five refugees (23%) residing\nin the region are living in poverty <sup>9</sup> . This figure is almost double that of host country nationals (12%), implying a\nlarge gap in economic vulnerability. Compared to 2023, poverty rates have decreased substantially (from\n36% <sup>", "output": {"entities": {"named_data": ["Socio-Economic Insights Survey", "MSNA", "2024 SEIS"], "descriptive_data": [], "vague_data": ["disposable income data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 3, "chunk": 0, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Socio-Economic Insights Survey", "label": "NAMED_DATA", "score": 0.8634694814682007, "start": 879, "end": 909, "probe_score": 0.9956, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "MSNA", "label": "NAMED_DATA", "score": 0.5305766463279724, "start": 1071, "end": 1075, "probe_score": 0.9978, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2024 SEIS", "label": "NAMED_DATA", "score": 0.6029497981071472, "start": 1301, "end": 1310, "probe_score": 0.9978, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "disposable income data", "label": "VAGUE_DATA", "score": 0.6797005534172058, "start": 1336, "end": 1358, "probe_score": 0.9316, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n\n**<u>UKRAINE REFUGEE VS HOST GROSS MONTHLY WAGES, EUR/MONTH</u>**\n\n\nMinimum wage (2024) Refugee mean wage (2023) Refugee mean wage (2024) Host mean wage (2024)\n\n\n2,500\n\n\n2,000\n\n\n1,500\n\n\n1,000\n\n\n500\n\n\n\n0\n\n\n\nBulgaria Czechia Estonia Hungary Latvia Lithuania Moldova Poland Romania Slovakia Region\n\n\n\nNote: Mean wages have been estimated by dividing household employment income by the total number of working hours and then computing a\nweighted average across households with weights proportional to total working hours. As the survey asked for net income, weighted means were then\nconverted to gross amounts for comparability based on host country tax rates.\n\n\nSource: Survey data, Eurostat, SAG estimates\n\n\nSimilar to its impact on employment status, education seems to have a much less pronounced effect on wage\npremiums for refugees compared to hosts, also suggesting the presence of underemployment. While,\naccording to Eurostat data and SAG estimates, a local with an advanced degree can expect to earn nearly 80%\nmore than someone with only lower secondary education <sup>18</sup> [^18: The difference in median wages by highest education level attained. Weighted equivalently to refugee weights for comparability], the same wage gap <sup>19</sup> for Ukrainians stands as just\n16% based on survey data.\n\n\nSkills-job mismatching also becomes evident when analyzing the current employment of refugees compared to\ntheir pre-war employment in Ukraine, as nearly 60% have transitioned to entirely different economic sectors.\nThis phenomenon is more pronounced among women, with 63% having shifted to roles outside their previous\nemployment background, compared to 50% of men. One possible explanation for this discrepancy is the higher\nproportion of men employed in sectors like construction and IT prior to displacement. These fields often\ndemand fewer country-specific qualifications, such as proficiency in the local", "output": {"entities": {"named_data": ["Eurostat data"], "descriptive_data": ["Survey data"], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 12, "chunk": 0, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Survey data", "label": "DESCRIPTIVE_DATA", "score": 0.5762583017349243, "start": 775, "end": 786, "probe_score": 0.9977, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Eurostat data", "label": "NAMED_DATA", "score": 0.5911056399345398, "start": 1030, "end": 1043, "probe_score": 0.9991, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.5334487557411194, "start": 1403, "end": 1414, "probe_score": 0.9928, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "REGIONAL SUMMARIES I **EAST AND HORN OF AFRICA AND THE GREAT LAKES** REGIONAL SUMMARIES I **EAST AND HORN OF AFRICA AND THE GREAT LAKES**\n\n\n##### KEY ACHIEVEMENTS AND IMPACT\n\n\n\nUNHCR also submitted 9,179 resettlement\ncases from the region for resettlement\nconsideration to third countries,\n62% fewer than in 2019.\n\n\nEnsuring protection and durable\nsolutions for IDPs\n\nThe 2019 “Policy on UNHCR’s\n<u>engagement in situations of internal</u>\n<u>displacement” continued to guide</u>\nUNHCR’s coordination responsibilities\nand operational response for IDPs in\nBurundi, Ethiopia, Somalia, South Sudan\nand Sudan. UNHCR’s protection\nmonitoring was, however, significantly\nhampered by the pandemic.\n\n\nIn Burundi, broad-based consultations\nundertaken by the UNHCR-led Protection\nCluster informed a new road map for\nstrengthening IDP protection. In Ethiopia,\nUNHCR extended its leadership role\nin the protection and other clusters to\nthe Tigray region, in response to\ndisplacements following the outbreak\nof conflict in November 2020. In Somalia,\nUNHCR’s IDP response focused on\nremote protection monitoring, community\nengagement and risk communication.\n\n\nIn South Sudan, UNHCR significantly\nscaled up shelter and other support for\nIDPs affected by local violence, flooding\nand COVID-19. In Sudan, UNHCR\nincreased its information management\ncapacity to support the Protection\nCluster with protection monitoring and\noperational responses, as well as in the\nDurable Solutions Working Group.\n\n\nIn Ethiopia, while there was minimal\nprogress in gaining access to the\ndisplaced populations affected by the\nconflict in Tigray despite coordinated\nadvocacy by UNHCR, humanitarian\npartners and donors, UNHCR provided\nprotection and assistance to\n400,000 IDPs across other parts\nof Ethiopia.\n\n\n\nSafeguarding access to protection\nand asylum\n\nUNHCR urged countries in the region\nto uphold the right to seek asylum as\npandemic-related border closures\nhampered access to both territory and\nasylum procedures. UNHCR appealed for\nspecial measures to allow asylum-seekers", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000458", "page": 3, "chunk": 0, "title": "UNHCR Global Report 2020: East and Horn of Africa and the Great Lakes", "pdf_url": "https://reliefweb.int/attachments/40dd000c-fde0-3f57-96fa-709364666310/UNHCR%20Global%20Report%202020%20-%20East%20and%20Horn%20of%20Africa%20and%20the%20Great%20Lakes.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", the number of DCEs\nthat could contribute to refugee education data\ninclusion is limited due to the lack of questionnaires\nthat simultaneously provide information on the\n\n\n\nprotection status of respondents and their educational\nsituation. There is an absence of questions that would\nallow for the identification of refugees with only 418\n(38%) questionnaires (331 DCE or 45%) having any\nform of refugee identification questions. Further,\nonly two questionnaires reviewed included the full\nset of questions recommended by the International\nRecommendations on Refugee Statistics developed by\nthe Expert Group on IDO, Refugee and Statelessness\nStatistics.\n\n\nOn education, the findings echo earlier work,\nshowing that data on access to education (e.g. 341\nquestionnaires with information on access to schools)\nis far more common than data on other aspects,\nsuch as safety (31 questionnaires) and quality (167\nquestionnaires) (summarized in Figure 1). Further, many\nof the data limitations on these aspects of education\nare a result of the absence of refugee identification\nquestions and the lack of inclusion of refugees as a\ntarget population. The educational indicators covered\ndiffer depending on the target population of the\nDCE. However, indicators on educational attainment,\nattendance, and literacy are relatively common\nacross DCEs, regardless of their target populations.\nIn sum, there are low levels of inclusion of refugees\nin education data systems and steps to ensure wider\ninclusion – both within samples and by including\nrefugee identification questions within existing\nsurveys – would enrich our understanding of refugee\neducation.\n\n\n\n**Figure 1:** Overview of the number of questionnaires covering different education areas by target population and presence\nof refugee identification questions\n\n\n**There is very little data on refugee education beyond access to schools and quality learning conditions.**\n**However, inclusion in existing data collection exercises has the potential to increase the amount of data.**\n\n\nAccess to schools\n\n\nSafe learning environment\n\n\nQuality learning conditions\n\n\n\nAccess to progressions\n\n\nAccess to higher education\n\n\n\n0 100 200 300 400 500 600 700", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["refugee education data", "data on access to education"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000382", "page": 6, "chunk": 1, "title": "Paving pathways for inclusion: a global overview of refugee education data", "pdf_url": "https://reliefweb.int/attachments/31f00be7-0481-4224-80ce-378c049a02d4/Paving%20pathways%20for%20inclusion%20--%20a%20global%20overview%20of%20refugee%20education%20data.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "refugee education data", "label": "VAGUE_DATA", "score": 0.586631178855896, "start": 46, "end": 68, "probe_score": 0.2529, "gold": "NON_MENTION", "gold_tier": "human-final"}, {"text": "data on access to education", "label": "VAGUE_DATA", "score": 0.5661741495132446, "start": 715, "end": 742, "probe_score": 0.3534, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEnhancing Community Resilience and Local Governance Project Phase II (P177093)\n\n\nclimate-resilient approaches, including risk assessments, to identify safe locations and elevated building\nstructure options to reduce flood and other disaster risks. The participatory planning process will\nbe supported under Component 2. All _payams_ and _bomas_ within the target counties will be eligible for\nfunding.\n\n\n33. To ensure flexibility, the project can also mobilize resources rapidly to respond to COVID-19 needs\nby funding handwashing facilities at public markets, places of worship, public transportation hubs,\ncommunal water points, women- and girl-friendly spaces, and other densely populated locations. Such\ninvestments will be coupled with hygiene promotion and COVID-19 awareness raising/communication to\nbe financed under Component 2. Communities’ priorities will be validated through local service mapping\nto avoid overlaps and to maximize the use of limited resources by consolidating common priorities among\nneighboring communities, where possible. Community labor will be used, to the extent possible, to\ngenerate income opportunities. The project will establish harmonized salary levels, to the extent possible,\nwith the planned Productive Safety Net for Socioeconomic Opportunities Project (PSNSOP, P177663) _._\n\n\n34. **Geographic targeting.** The selection of counties is guided by four principles: (a) vulnerability, (b)\nfeasibility, (c) equity, and (d) continuity (see Figure 2). The project will continue to target the 10 counties\nwhere ECRP-I has started implementation to consolidate the envisioned development gains in these\nlocations. <sup>48</sup> As indicated in Table 1, ECRP-II will scale up to include refugees in the two refugee-hosting\ncounties that were already targeted under ECRP-I <sup>49</sup> and two new flood-prone vulnerable counties to\nsupport Subcomponent 1", "output": {"entities": {"named_data": [], "descriptive_data": ["local service mapping"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000028", "page": 25, "chunk": 0, "title": "South Sudan - Second Phase of the Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/543171647442225562/pdf/South-Sudan-Second-Phase-of-the-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "local service mapping", "label": "DESCRIPTIVE_DATA", "score": 0.6748040914535522, "start": 907, "end": 928, "probe_score": 0.4356, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "satisfied two or more rainy seasons; - Progress reports submitted\n2b.3 100% of houses benefit by implementing partners;\nmarginalized population                 - Beneficiary assessments\ngroups (female headed                 - NaCSA M&E data\nhouseholds, disabled and their\nfamilies); and\n2b.4 100% of beneficiaries\nwere selected by beneficiary\ncommunities.\n\n\n**3.** Proiect Management and\nInnovative Activities - NaCSA administrative data - Qualified implementing\n\n                                  - Capacity building event partners available to provide\n**3(a)** **Capacities of** assessments; capacity building and IEC\n**communities,** **chiefdomns,** **and** 3a.1 At least 5 successful - Participatory project activities at all levels;\n**district authorities to select,** capacity building events completion reviews; - A qualified full-time M&E\n**implement and maintain** carried out each year; - IDA supervision missions specialist is provided to\n**projects established** **and** NaCSA by another donor\n**strengthened** agency\n\n**3(b)** **Information, Education** 3b. 1 At least 40% of HHs are - Beneficiary assessments; - Non-NSAP activities\n**and Communication** aware of program; - NaCSA adrninistrative data; undertaken by NaCSA do not\n3b.2 At least 60%of chlefdom                  - IDA aide-memoires and detract from NaCSA ability to\nand district governments project status reports; and implement project.\naware of NSAP coverage,\ntargeting, methodology, and\nresults; and\n3b.3 At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA", "output": {"entities": {"named_data": ["NaCSA M&E data", "NaCSA administrative data", "NaCSA adrninistrative data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019286", "page": 31, "chunk": 0, "title": "Kenya - Program Loan Project", "pdf_url": "https://documents.worldbank.org/curated/en/862591468046803369/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NaCSA M&E data", "label": "NAMED_DATA", "score": 0.8557507395744324, "start": 226, "end": 240, "probe_score": 0.0002, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "NaCSA administrative data", "label": "NAMED_DATA", "score": 0.7650092840194702, "start": 412, "end": 437, "probe_score": 0.0006, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "NaCSA adrninistrative data", "label": "NAMED_DATA", "score": 0.6916330456733704, "start": 1188, "end": 1214, "probe_score": 0.4531, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Global Refugee Youth Consultations**\n\nFinal Report\n\n31\n\n\nGenerate data and evidence\non refugee youth to promote\naccountability to youth\n\n\nHumanitarian actors must gather quality disaggregated\n\ndata on youth as well as on their needs, priorities,\n\nskills, and contributions; this is essential for plan\nning and designing youth programming and being\n\naccountable to youth.\n\n\nGRYC participants emphasised the importance of collecting and\nsharing accurate demographic data about youth in order to make youth\nand their needs more visible, enable better budgeting and planning for\ninclusive youth-focused programmes, and foster accountability. They\nalso emphasised that young refugees themselves can play a key role in\ngathering data and evidence on youth in refugee contexts when given\nthe support, training, and opportunity.\n\n\n**Generating data on refugee youth**\n**and promoting accountability includes:**\n\n- <sup>Collecting accurate disaggregated sex and age data on Refugee</sup>\nYouth as a specific demographic category with distinct needs;\n\n- <sup>Supporting Refugee Youth-led research, and youth-led evaluations</sup>\nof programmes aimed at and including youth;\n\n- <sup>Supporting ongoing research and the pursuit of evidence relevant</sup>\nto developing effective youth-appropriate programmes and services\nfor refugees;\n\n- <sup>Assessing specific youth needs by consulting and mobilising</sup>\nRefugee Youth wherever they are;\n\n- <sup>Organising comprehensive campaigns to reach out to unregistered</sup>\nRefugee Youth;\n\n- <sup>Creating common open spaces for youth and humanitarian</sup>\nactors to meet and listening to their voices to make youth\nprogramming relevant;\n\n- <sup>Planning and budgeting in consultation with youth to ensure</sup>\ntransparency; and\n\n- <sup>Encouraging donors to require disaggregated data on youth from</sup>\nhumanitarian actors.\n\n\n\n\n\nHow can we work with youth\n\nif we", "output": {"entities": {"named_data": [], "descriptive_data": ["disaggregated sex and age data"], "vague_data": ["disaggregated\n\ndata", "demographic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000282", "page": 32, "chunk": 0, "title": "We Believe in Youth, Global Refugee Youth Consultation Final Report, September 2016", "pdf_url": "https://reliefweb.int/attachments/207c6152-063e-3afd-bc88-7dc1500f5c6f/2200-WRC-Youth-Report-LR.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "disaggregated\n\ndata", "label": "VAGUE_DATA", "score": 0.5430139899253845, "start": 180, "end": 199, "probe_score": 0.0016, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "demographic data", "label": "VAGUE_DATA", "score": 0.6335040330886841, "start": 454, "end": 470, "probe_score": 0.1033, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "disaggregated sex and age data", "label": "DESCRIPTIVE_DATA", "score": 0.6501411199569702, "start": 933, "end": 963, "probe_score": 0.0289, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Annex 2: Detailed Project Description**\n\n\n**Chad: Safety Nets Project**\n\n\n1. **The PDO** is to pilot cash transfers and cash-for-work interventions to the poor and lay\nthe foundations of an adaptive safety nets system.\n\n\n2. **The project proposes to focus on the development of a SSN delivery system that will**\n**initially include two interventions:** a CfW program in urban and peri _-_ urban areas of the capital\ncity, N'Djamena, and a CT program in rural areas. Both programs will strive to reach the poorest\nhouseholds (at least 40 percent of the food poverty gap in the respective regions). These two\nprograms would also offer accompanying measures to the beneficiary households, concentrating\non behavior change communication and nutrition and hygiene education for mothers in the CT\nprogram; and basic financial literacy and savings for the CfW program.\n\n\n3. **The project will also support the incremental development of key administrative**\n**systems** such as a targeting and data collection system, a social registry, a payment system, a\ngrievance system, and a computerized MIS. These systems will be developed and tested in the\ntwo pilot programs and will allow effective management and coordination of safety net programs\nas they are scaled up in the future.\n\n\n4. **The intention is to build an ‘adaptive’ safety net system.** The project will support\ndevelopment and use of critical service delivery instruments and institutional arrangements\nessential to building a safety net system that will ultimately be capable of expanding program\ncoverage in response to shocks, especially for households vulnerable to climatic and seasonal\nshocks and temporary food-insecurity. The expansion can be achieved by: (a) increasing the\nlevel of transfer given to current beneficiaries; (b) expanding the number of beneficiaries of the\nCT or the CfW programs only for specified period of time; and, in a later phase;", "output": {"entities": {"named_data": [], "descriptive_data": ["social registry"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000028", "page": 38, "chunk": 0, "title": "Chad - Safety Nets Project", "pdf_url": "http://documents1.worldbank.org/curated/en/221251471265217930/pdf/Project-Appraisal-Document-PAD-disclosable-version-P156479-08122016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "social registry", "label": "DESCRIPTIVE_DATA", "score": 0.7865118384361267, "start": 1015, "end": 1030, "probe_score": 0.027, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "required for local government involvement, and arrangements for maintenance, monitoring and\nevaluation (M&E). Social capital enhancing activities would be a mandatory part of all sub-projects, and\nwould be tailored to support activities chosen by the communities.\n\nSupport to Decentralized Government Structures. Most local administrations are beginning\nto operate again with a limited number of staff and other inputs. District and chiefdom authorities are\nvery weak, however, and lack the financial and human resources needed to address their concerns and\npnorities effectively. NGOs have demonstrated their ability to implement successful community-based\nsocial and economic projects and have played a key role in shelter reconstruction activities. With the\ngradual strengthening of local government capacity, partnerships between community groups and local\nauthorities are expected to increase. Upon completion of initial training, district and chiefdom authorities\nwould be required to demonstrate that they have used the training by showing that there have been some\nimprovements in their community. For instance, at the end of each training session, district authorities\nwould be required to develop a simple action plan that specifies some activities that NSAP or other\npartners could support. District and chiefdom authorities would also gain experience in implementing,\nsupporting or overseeing community development activities.\n\nHealth. The unfavorable health indicators in Sierra Leone can be attributed to several factors.\nHigh fertility, female genital mutilation and the presence of HIV/AIDS increase morbidity and mortality\nrisks for women and children. Many risk factors that have contributed to HIV/AIDS epidemics in other\nAfrican countries have long been present in Sierra Leone, and the protracted conflict has created the\nconditions for explosive growth in HIV/AIDS infection rates. The Centers for Disease Control carried\nout a survey in 2002 which found the HIV prevalence among adults (aged 1549) to be 6.1 %; in\nFreetown, 4% in rural areas and 4.9% nationwide. In response to the crisis, Government has developed\na multi-sector HIV/AIDS Program, which is being supported by various", "output": {"entities": {"named_data": [], "descriptive_data": ["survey in 2002"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009511", "page": 10, "chunk": 0, "title": "Uganda - Road Development Program (Phase 2) Project : resettlement action plan", "pdf_url": "https://documents.worldbank.org/curated/en/206241468760491175/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey in 2002", "label": "DESCRIPTIVE_DATA", "score": 0.6400850415229797, "start": 1950, "end": 1964, "probe_score": 0.9708, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "output": {"entities": {"named_data": [], "descriptive_data": ["random survey"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020575", "page": 16, "chunk": 0, "title": "Kenya - Financial Sector Adjustment Credit Project", "pdf_url": "https://documents.worldbank.org/curated/en/948761468277745732/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7714613080024719, "start": 379, "end": 395, "probe_score": 0.582, "gold": "NON_MENTION", "gold_tier": "human-final"}, {"text": "random survey", "label": "DESCRIPTIVE_DATA", "score": 0.7173007130622864, "start": 1487, "end": 1500, "probe_score": 0.012, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".68]\n\nMale 0.05*** 0.105*** 0.118*** 0.091*** 0.032*** -0.004*** -0.011**\n\n[22.89] [16.55] [22.09] [16.45] [6.75] [-1.14] [-1.96]\n\nBlack –0.095*** -0.072*** -0.072*** -0.075*** -0.104*** -0.104*** -0.104***\n\n[–28.63] [-6.46] [-7.96] [-8.68] [-13.99] [-18.31] [-12.28]\n\nOther race –0.03*** -0.007 -0.02 -0.034* -0.036** -0.023** -0.015\n\n[–4.49] [-0.27] [-0.94] [-1.73] [-2.42] [-2.08] [-1.18]\nPseudo R-square 0.09 0.07 0.07 0.06 0.05 0.05 0.04\nObservations 181,222 16,988 28,212 29,177 39,206 44,884 22,755\nObserved\n0.464 0.677 0.599 0.514 0.442 0.365 0.308\n<u>probability</u>\n\n***, **, * denote statistical significance at the 1%, 5% and 10% confidence levels, respectively.\n_Note_ : Analysis from smoking histories from the 1978, 1979, 1980, 1983, 1985, 1987, 1988, 1990", "output": {"entities": {"named_data": [], "descriptive_data": ["smoking histories"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002636", "page": 23, "chunk": 3, "title": "wps3362", "pdf_url": "https://local/prwp/wps3362.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "smoking histories", "label": "DESCRIPTIVE_DATA", "score": 0.7687402963638306, "start": 698, "end": 715, "probe_score": 0.8779, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Appendix 2: Details of Sampling Procedure**\n\n\nSampling protocols for inside and outside the market were different:\n\n- For Danktopa market, we used a precise map of the market made by the public company\n\n\nmanaging markets in Benin (SOGEMA). This map allowed to divide geographically the\n\n\nmarket in small areas. We then randomly selected areas in the markets in which 50% of the\n\n\nbusinesses (with fixed location) where sampled for the survey. <sup>16</sup> [^16: Few areas were excluded from the sampling frame because they almost exclusively included businesses selling\nillegal products (i.e. taint oil, medicine, and voodoo products) or by large formal businesses.]\n\n- For other neighborhoods of Cotonou, we were able to obtain detailed maps of each of the\n\n\n144 neighborhoods in Cotonou. Those maps allowed the easy identification of _ilots_ (blocks),\n\n\nthe official administrative unit within a neighborhood. We used this administrative unit as\n\n\na reference for the listing survey sampling. We then used information given by the tax\n\n\nadministration (and confirmed by the survey company) in order to characterize\n\n\nneighborhoods as high or low firm density areas. We randomly sampled 38% of _ilots_ in\n\n\nhigh density neighborhoods and 10% of the _ilots_ in low density neighborhoods. In each _ilots_\n\n\n68% of businesses where sampled for the survey in average.\n\n\nOverall, 19,246 businesses were listed. The listing survey allowed us to estimate the total\n\n\nnumber of businesses operating in Cotonou (with a fixed location, excluding international and\n\n\nnationwide businesses and liberal professions) to approximately 68,500, including around 5,000\n\n\nin Dantokpa market. <sup>17</sup> [^17: Some sections of Dantokpa market were not included in the listing survey. Therefore, the total number of\nfirms in Dantokpa is probably significantly higher.] Among those 19,246 businesses, 9,938 businesses were randomly\n\n\nselected to be surveyed. 7,945 (80%) businesses were successfully surveyed,", "output": {"entities": {"named_data": [], "descriptive_data": ["precise map of the market", "listing survey", "listing survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006903", "page": 55, "chunk": 0, "title": "wps7900", "pdf_url": "https://local/prwp/wps7900.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "precise map of the market", "label": "DESCRIPTIVE_DATA", "score": 0.6296395659446716, "start": 151, "end": 176, "probe_score": 0.6603, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "listing survey", "label": "DESCRIPTIVE_DATA", "score": 0.5743234753608704, "start": 973, "end": 987, "probe_score": 0.8137, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "listing survey", "label": "DESCRIPTIVE_DATA", "score": 0.5326434969902039, "start": 1414, "end": 1428, "probe_score": 0.7685, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nLebanon Health Resilience Project (P163476)\n\n\n\n\n\n\n\n\n\n\n\n\n\nPage 5 of 54", "output": {"entities": {"named_data": ["Lebanon Health Resilience Project"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000108", "page": 7, "chunk": 0, "title": "Lebanon - Health Resilience Project", "pdf_url": "http://documents1.worldbank.org/curated/en/616901498701694043/pdf/Lebanon-Health-PAD-PAD2358-06152017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Lebanon Health Resilience Project", "label": "NAMED_DATA", "score": 0.552203357219696, "start": 19, "end": 52, "probe_score": 0.0284, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the indicators that define GDP at market (or purchasers’) prices from the\n\n\nexpenditure side (domestic final demands, exports, and imports), disaggregated tax\n\n\npayments, and items in the balance of payments related to factor incomes and current\n\n\ntransfers. Consistency between receiving and paying accounts is assured thanks to the fact\n\n\nthat a single SAM entry applies to both; e.g. government consumption in the national\n\n\n7 For example, see European Commission et al. (2009, Chapter 28).\n\n\n8 More specifically, the data shown are the weighted average of macro SAMs for the 17 low‐income countries\nfor which sufficient information was available in cross‐country databases. Each SAM was weighted by its share\nof GDP at market prices at current US dollars for the countries included.\n\n\n‐9‐", "output": {"entities": {"named_data": [], "descriptive_data": ["cross‐country databases"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007231", "page": 10, "chunk": 1, "title": "wps8273", "pdf_url": "https://local/prwp/wps8273.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "cross‐country databases", "label": "DESCRIPTIVE_DATA", "score": 0.8458151817321777, "start": 654, "end": 677, "probe_score": 0.2787, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "UNHCR MID-YEAR POST DISTRIBUTION MONITORING REPORT - 2024\n\n\nRegarding the impact of cash assistance on the need to resort to risky or harmful activities, 53 per cent of\nrespondents stated that they do not normally engage in such activities, 46 per cent reported that the cash\nassistance at least slightly reduced their need to resort to these risky activities, while one per cent of respondents\nstated that the cash assistance had not reduced their need to engage in these activities at all. The extent of impact\non reducing risky or harmful activities is shown in Figure (5).\n\n\n**Figure 5: Reduced the need to resort to risky or harmful activities**\n\n\n\n\n\nRegarding the effects of cash assistance on household dynamics, survey results showed that the assistance has\npositively impacted relations within beneficiary households as reported by 77 per cent of respondents.\nHowever, 20 per cent of respondents mentioned that it had no impact on the relations within their households,\nwhile a small proportion (2.7 per cent) mentioned that it negatively impacted the relations within the\nhouseholds.\n\n**Figure 6** **_:_** **How cash assistance has impacted relations within household**\n\n\n\n\n\nWhen asked about disagreements on how to use the cash assistance within the household, 92 per cent of\nrespondents reported no disagreements, while 7 per cent of respondents reported that they discussed the matter\nbut eventually came to an agreement. Only 1 per cent of respondents stated they disagreed a lot on the spending\ndecisions.\n\n\nRegarding decision-making on spending the cash assistance, a sizable proportion (63 per cent) of respondents\nreported that the female head of household was responsible for making decisions while 21 per cent by the male\nhead of household. The breakdown of decision makers and the disaggregation by the head of household is\nshown in figure (7).\n\n\n12", "output": {"entities": {"named_data": ["UNHCR MID-YEAR POST DISTRIBUTION MONITORING REPORT"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000992", "page": 11, "chunk": 0, "title": "Mid-Year Post-Distribution Monitoring Report of UNHCR’s Multi-Purpose Cash Assistance to Refugees in Egypt, September 2024", "pdf_url": "https://reliefweb.int/attachments/9543af9b-5171-46cd-a644-232432ee2f4b/MPCA%20PDM-Mid%20Year%202024-Final%20Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR MID-YEAR POST DISTRIBUTION MONITORING REPORT", "label": "NAMED_DATA", "score": 0.558049738407135, "start": 0, "end": 50, "probe_score": 0.9985, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", and</sup>\n\nassociated infrastructure services, and taking maximum <sup>advantage of the increased transit</sup>\ntraffic to Ethiopia.\n\n    - Human development and poverty reduction, <sup>focusing on: (a) quickly reversing the</sup>\nextremely low enrollment rate in education; (b) addressing <sup>the overwhelming needs in</sup>\nhealth (AIDS and tuberculosis crises); and (c) preparing <sup>a possible program of assistance</sup>\nfor vulnerable groups to cushion the impact of adjustment <sup>and the inevitable decline</sup>\nanticipated in real wages.\n\n    - Mobilizing donor support for Djibouti through <sup>demonstrated improvements in the policy</sup>\nand govemance environment and implementation, and <sup>aid coordination around well-</sup>\narticulated sectoral strategies.\n\nThe project directly supports the second element <sup>of the CAS strategy and indirectly the first element.</sup>\n\n\n2. **Potential Sources of Growth**\n\nA major element in Djibouti's development strategy <sup>is its human resource base given that the country</sup>\nhas very few natural resources. Its growth strategy <sup>depends on its human resource base and</sup>\nexploiting its strategic location, i.e., the port serving <sup>the region, particularly Ethiopia. To increase</sup>\n\nthe benefits from the port, Djibouti needs to become a <sup>cost-effective competitor; and a key element in</sup>\nthis is to increase the productivity of its workforce. Thus, <sup>improved quality of the human resource</sup>\nbase is essential for Djibouti to improve its revenues <sup>from the port. In addition, Djibouti'", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000090", "page": 37, "chunk": 1, "title": "Albania - Emergency Road Repair Project", "pdf_url": "http://documents1.worldbank.org/curated/en/543691468740389779/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nLower secondary completed 0.461 0.454 0.545 0.398 0.444 0.359 0.588 0.508\nSome or completed upper secondary 0.700 0.690 0.790 0.604 0.607 0.343 0.761 0.521\nPost-primary TVET 0.874 0.850 0.894 0.457 0.858 NS 0.979 0.355\nPost-secondary TVET 1.119 1.088 1.154 0.578 1.105 0.320 1.171 0.414\nHigher/tertiary level of education 1.708 1.686 1.669 1.304 1.616 0.935 1.653 1.022\nData on educational level missing NS NS NS NS 0.320 NS 0.470 0.331\n**Secondary versus primary completed**\nLower secondary versus primary 0.090 0.076 0.200 -0.095 0.214 0.036 0.285 0.098\n<u>Upper secondary versus primary</u> <u>0.329</u> <u>0.312</u> <u>0.445</u> <u>0.111</u> <u>0.377</u> <u>0.020</u> <u>0.458</u> <u>0.111</u>\n<u>Source: Tsimpo and Wodon (2020b). Note: NS means not statistically significant.</u>\n\n**Cost-benefit analysis for school construction**\n\n5. **The cost benefit analysis of investments in lower secondary school completion is based on estimates of wage**\n**earnings and data for both investment and recurrent costs.** Earnings gains are based on results from Tables 5.2\nand 5.3. Cost data", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Cost data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000060", "page": 94, "chunk": 1, "title": "Uganda - Secondary Education Expansion Project", "pdf_url": "http://documents1.worldbank.org/curated/en/406361595815248191/pdf/Uganda-Secondary-Education-Expansion-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Cost data", "label": "VAGUE_DATA", "score": 0.673726499080658, "start": 1077, "end": 1086, "probe_score": 0.6489, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nprior to 2003 up to 2005, _Arab_ ethnicity averages 9%, and changes to 24% for those arrived in the first\nhalf of 2006, 44% in the first half of 2007, and 14 % in the second half of 2008. The proportion of _Turkmen_\narriving prior to 2003 and up until 2005 averages at 12%, however 43% arrived in the first half of 2006.\nAmong those who arrived in the first half of 2008, _Turkmen_ account for only 1%.\n\n4 Prior to 2003, 83% of arrivals were registered as Other/No Data with regard to ethnic group. This dropped in 2003 and until 2005\nthe average was 41%. It then dropped again to an average of 7% for the rest of the charted period.\n5 Before 2003, the ethnicity of 84% of the population was unknown. Between 2006 and 2008, this figure averages 3% until second\nhalf of 2008 where it increases to 30% again.\n\n\n31 - Iraq Refugees Registration Data Comparative Analysis, 2007-2008.", "output": {"entities": {"named_data": ["Iraq Refugees Registration Data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000921", "page": 31, "chunk": 1, "title": "Iraq refugees registration data analysis, 2007-2008", "pdf_url": "https://reliefweb.int/attachments/88aacba6-1a79-3aa6-b66b-ffbb4aac6343/241DAEC1BFE309914925761C000B2814-Full_Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Iraq Refugees Registration Data", "label": "NAMED_DATA", "score": 0.7609204053878784, "start": 815, "end": 846, "probe_score": 0.9833, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "letion**<br>**Measurement**|---|---|---|---|---|\n|**Comments**|RFP for Consultants to prepare Guideline issued and closing this week|RFP for Consultants to prepare Guideline issued and closing this week|RFP for Consultants to prepare Guideline issued and closing this week|RFP for Consultants to prepare Guideline issued and closing this week|RFP for Consultants to prepare Guideline issued and closing this week|\n\n\n|Action Description|Identify needs and develop local DRM and emergency plan (building on woreda risk profile)|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Source**|**DLI#**|**Responsibility**|**Timing**|**Timing Value**|**Status**|\n\n\n6/10/2019 Page 3 of 19", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008962", "page": 2, "chunk": 3, "title": "Disclosable Version of the ISR - Ethiopia Urban Institutional and Infrastructure Development Program - P163452 - Sequence No : 03", "pdf_url": "https://documents.worldbank.org/curated/en/168081560141511584/pdf/Disclosable-Version-of-the-ISR-Ethiopia-Urban-Institutional-and-Infrastructure-Development-Program-P163452-Sequence-No-03.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "d tariff (EU) _t−_ 1 -0.002 -0.009 -0.009 -0.010 -0.013 -0.013\n(0.012) (0.013) (0.013) (0.008) (0.009) (0.009)\n∆Faced tariff (USA) _t−_ 1 -0.003 -0.003 -0.003 -0.003\n(0.005) (0.005) (0.003) (0.003)\n∆Import (firm) 0.006 0.045***\n(0.018) (0.015)\n\n\nFixed effect\n\n\nYear Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes\nFirms-Industry Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes\n\n\nObservations 25,821 25,821 25,759 25,112 25,112 51,144 51,144 51,041 50,037 50,037\nNumber of units 10,647 10,647 10,618 10,402 10,402 17,972 17,972 17,927 17,622 17,622\n\n\nTable 4: Export market destinations (baseline model)\n\n\nNote: Standard errors clustered at the industry level in parentheses. In the baseline specification the sample is composed\nby FTZ (control group) and Non-RED (treated group). In the alternative specification (1) the sample is composed by RED\n(control group) and Non-RED (treated group).\n\n\n14", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006301", "page": 16, "chunk": 2, "title": "wps7231", "pdf_url": "https://local/prwp/wps7231.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "TA will be delivered to regularly<br>update COVID-19 response plans<br>and to evaluate gaps in the<br>country’s response.<br> <br>Directors from units with leading<br>roles in the COVID-19 National<br>Action Plan will be supported with<br>TA.<br>|All relevant departments of the<br>MOPH will participate in capacity<br>building activities.<br> <br>The OneHealth approach is used to<br>address human and animal health<br>needs. This means that other<br>relevant ministries will also benefit<br>from this support.<br>|\n|Workforce development.|<br>Clinical training will focus<br>exclusively on infection prevention|<br>Capacity building covers a wide<br>range of themes but focuses|\n\n\n\nPage 17", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000039", "page": 21, "chunk": 2, "title": "Chad - COVID-19 Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/717781588366403375/pdf/Chad-COVID-19-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "missing. By contrast, all bilateral positions of a reporting country (source or destination) are, in\n\n\nprinciple, observed. Since BIS reporting countries generally itemize every counterparty country on\n\n\nwhich its banks hold or owe an active (positive) position, any missing observation is most likely a true\n\n\nzero and we code it as such. This procedure could underestimate the number and value of active links\n\n\nfor those reporting countries that do not require banks to report the complete breakdown of all\n\n\ncounterparty countries when positions are small enough.\n\n\nAnother point concerns the handling of a change in reporting in 2012. Countries historically\n\n\nreported positions expressed in U.S. dollars rounded to the closest million. Thus, positions below\n\n\nUS$0.5 million (a low threshold in the context of country-to-country investment) were reported as\n\n\nzero. When decimal reporting was introduced in the second quarter of 2012, hundreds of links below\n\n\nUS$0.5 million started to be reported as positive, leading to an artificial jump in the number of active\n\n\nlinks in 2012. Although this jump does not affect our analysis of the intensive margin (because the\n\n\nvalue of these links is so small), it could bias the analysis of the extensive margin. We offset this break\n\n\nin the series by setting all links below US$0.5 million to zero. This ensures that all reported loans and\n\n\ndeposits are subject to a constant reporting threshold throughout the sample period.\n\n\n**A.2. Portfolio Investment**\n\n\nFor portfolio investment, we rely on the CPIS database from the International Monetary Fund (IMF).\n\n\nThe CPIS is a voluntary data collection exercise that assembles data on countries’ international\n\n\nholdings of equities and long-term and short-term debt securities. Countries report data on: (i) their\n\n\nholdings of portfolio investment assets issued by residents in other countries, and (ii) their portfolio\n\n\ninvestment liabilities issued by domestic residents and held by residents in other countries. No\n\n\naggregation is needed because the", "output": {"entities": {"named_data": ["CPIS database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000115", "page": 35, "chunk": 0, "title": "bilateral international investments the big sur", "pdf_url": "https://local/prwp/bilateral-international-investments-the-big-sur.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "CPIS database", "label": "NAMED_DATA", "score": 0.915439784526825, "start": 1554, "end": 1567, "probe_score": 0.9368, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\n\n\n\n\n\n\n\n|Col1|selected to receive SNSOP<br>who are refugees, defined<br>as forcibly displaced HHs<br>originating from a country<br>other than South Sudan and<br>registered as refugees in<br>South Sudan by the UNHCR.<br>A household will be<br>considered as a beneficiary<br>household if it is both<br>enrolled in the project and<br>have received a cash<br>transfer, at least for one<br>payment cycle.|measured at<br>least on a<br>quarterly<br>basis<br>including<br>through<br>missions and<br>ISRs|beneficiary<br>registration<br>and payment<br>data|beneficiary data during<br>targeting and<br>registration. The<br>payment service<br>provider will collect<br>payment data and<br>share with the<br>implementing partner.|Col6|\n|---|---|---|---|---|---|\n|Beneficiary households of social safety<br>net programs- Host Communities|The number of total<br>beneficiaries households<br>that are selected to receive<br>SNSOP who are from host<br>communities, defined as<br>local population groups<br>living in counties with a high<br>concentration of refugees. A<br>household will be<br>considered as a beneficiary<br>household if it is both<br>enrolled in the project and<br>have received a cash<br>transfer, at least for one<br>payment", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["beneficiary data", "payment data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 56, "chunk": 0, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "beneficiary data", "label": "VAGUE_DATA", "score": 0.5990036129951477, "start": 639, "end": 655, "probe_score": 0.1255, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "payment data", "label": "VAGUE_DATA", "score": 0.6443750858306885, "start": 748, "end": 760, "probe_score": 0.0977, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "3\n\n\n**2. Project development objective** (see Annex 1)\n\nThe objective of the project is to enhance the quality of education and to increase enrollment in\nprimary schools.\n\n\n**3. Key performance indicators:** (see Annex 1)\n\nThe key performance indicator is an increased number of students enrolled in grades 1-9, especially\namong girls.\n\n\nB. **STRATEGIC CONTEXT**\n\n\n**1. Sector-related Country Assistance Strategy (CAS) goal supported by the project** (see Annex 1)\n\n\n**Document number:** P 7403 DJI **Date of latest CAS discussion:** (scheduled for) 12/19/00\n\nThe CAS has been prepared in the context of the country's economic difficulties and deepening\npoverty. Despite Djibouti's relatively high nominal per capita income (US$790 versus an average of\nUS$510 for Sub-Saharan Africa, and US$100 for Ethiopia), Djibouti has one of the poorest social\nindicators in the world (poverty, illiteracy, maternal and infant mortality, and morbidity), according to\nthe UNDP Human Development Index, ranking 157th among 174 countries.\n\n\nThe Republic of Djibouti has very few natural resources and the economy is mainly dependent on the\nport, external financial assistance, the French military and associated services. However, with the\n\ndecreased amount of external assistance, and deepening structural problems, the country has suffered\neconomic stagnation over the past decade and a half. As a result, per capita Gross Domestic Product\n(GDP) declined by 50% in real terms since 1985. The switch of Ethiopia's transit traffic from Assab in\nEritrea to Djibouti in mid-1998 and the consequent four-fold increase in port traffic has opened new,\nas yet not fully exploited, opportunities for investment and growth. Djibouti's open economic policies\nand relative stability, characterized by a liberal trade policy and exchange system, which operates free\n\nof capital or", "output": {"entities": {"named_data": ["UNDP Human Development Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000170", "page": 6, "chunk": 0, "title": "Albania - Water Supply Urgent Rehabilitation Project", "pdf_url": "http://documents1.worldbank.org/curated/en/949361468742522118/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNDP Human Development Index", "label": "NAMED_DATA", "score": 0.8519672155380249, "start": 959, "end": 987, "probe_score": 0.9988, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nsystems under preparation in Zarqa and Russeifa, and pilot initiatives in Irbid; (ii) integrated solid waste\nmanagement systems, including transfer stations such as in Mafraq; and (iii) other urban regeneration\nand upgrading, such as parks, public areas and green spaces, but also other strategic public assets that\ncan facilitate compact urban growth or attract private investments, e.g., the Zarqa river rehabilitation,\nMafraq railway park, and Russeifa phosphate mountains.\n\n\nb. _In ‘lagging regions’,_ this may include investments in (i) basic infrastructure and service delivery such as\n\nwater supply and sanitation, solid waste disposal and recycling facilities, and electricity networks to\nimprove access and quality of basic services; and (ii) connecting infrastructure such as roads and\ntransportation networks to integrate ‘lagging regions’ into the economy and connect then with urban\n‘growth hubs’, beyond an isolated focus on dedicated industrial zones. The recently adopted\nGovernorate Investment Plan would provide the basis for identifying, prioritizing and selecting critical\ninvestments under a comprehensive Framework for Integrated Territorial Development. Investments to\nincrease connectivity would be informed by the Trucking Operator Survey recently completed as part of\nthe JIT to inform Program identification. <sup>7</sup>\n\n\n**E. Initial Environmental and Social Screening**\n\n\n25. An Environmental and Social Management System Analysis (ESSA) of the central organizations and ministries\ninvolved with the program, such as MoMA, as well as the regional and municipal level organizations will be\nundertaken. The ESSA will assesses the environmental and social impacts and risks likely to be associated with the\nprogram and will examine Jordan’s existing environmental and social management systems for municipal\n\n\n7 Interdisciplinary Research Consultants, Jordan Local Development in Lagging Regions, Survey of Truck Operators. Final Report,\nFebruary 2018.\n\n\nMay 07, 2018 Page 10 of 12", "output": {"entities": {"named_data": ["Trucking Operator Survey", "Survey of Truck Operators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000053", "page": 9, "chunk": 1, "title": "Concept Stage Program Information Document (PID) - Jordan Urban and Municipal Program for Balanced and Inclusive Growth - P166577", "pdf_url": "http://documents.worldbank.org/curated/en/878311529722635771/pdf/Concept-Stage-Program-Information-Document-PID-Jordan-Urban-and-Municipal-Program-for-Balanced-and-Inclusive-Growth-P166577.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Trucking Operator Survey", "label": "NAMED_DATA", "score": 0.8572107553482056, "start": 1240, "end": 1264, "probe_score": 0.9298, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Survey of Truck Operators", "label": "NAMED_DATA", "score": 0.7256709933280945, "start": 1926, "end": 1951, "probe_score": 0.9437, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "AGE OF PW SUB-PROJECTS**<br>**SELECTED AND IMPLEMENTED FOLLOWING**<br>**CBPWMG/RANGE MANAGEMENT**<br>**GUIDELINES **|75<br>|75|77.5<br>||\n||RAW DATA<br>SOURCES|||||PWLR report<br>|\n||Comments|||||On page 41 fig. 6|\n|17|**PERCENTAGE OF PSNP JOINT ACTION PLANS**<br>**DEVELOPED THROUGH ESAP THAT ARE**<br>**IMPLEMENTED**|**PERCENTAGE OF PSNP JOINT ACTION PLANS**<br>**DEVELOPED THROUGH ESAP THAT ARE**<br>**IMPLEMENTED**|5.5|30|18.3||\n||RAW DATA<br>SOURCES||||ESAP monitoring<br>data||\n||Comments||||19 woredas||", "output": {"entities": {"named_data": [], "descriptive_data": ["ESAP monitoring"], "vague_data": ["RAW DATA", "RAW DATA"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012431", "page": 64, "chunk": 1, "title": "Ethiopia - Phase Four of the Productive Safety Nets Project : Joint Review and Implementation Support Mission - June 4-14, 2018", "pdf_url": "https://documents.worldbank.org/curated/en/401321540964046896/pdf/Aide-Memoire-ET-Productive-Safety-Nets-Project-4-PSNP-4-P146883.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "RAW DATA", "label": "VAGUE_DATA", "score": 0.6226791143417358, "start": 140, "end": 148, "probe_score": 0.0092, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "RAW DATA", "label": "VAGUE_DATA", "score": 0.5868107676506042, "start": 435, "end": 443, "probe_score": 0.0027, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "ESAP monitoring", "label": "DESCRIPTIVE_DATA", "score": 0.5344875454902649, "start": 458, "end": 473, "probe_score": 0.3284, "gold": "NON_MENTION", "gold_tier": "human-final"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Theme|Sub-­Theme|QUESTIONS FOR THE HOUSEHOLD SURVEY|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|Theme|Sub-Theme|#|Questions|Answer options|Responding<br>population|\n|Housing, Land and Property|Assets left<br>behind|K1|Did your household leave any assets in<br>your place of origin?|1. Yes<br>2. No|Iraqis displaced after<br>Dec. 2013<br>Syriansdisplaced|\n|Housing, Land and Property|Assets left<br>behind|K2_1|Which of the following assets did your<br>household leave in your place of origin?|1. housing<br>2. non agricultural land<br>3. agricultural land/livelisctock/farm equipment<br>4. business assets<br>5. jewelry/savings/cash<br>6. car(s)<br>7. other<br>8.prefernottoanswer|All<br>With assets behind|\n|Housing, Land and Property|Assets left<br>behind|K2_3|[if yes] Did you leave {asset} in the care|<br>     o1. Yes<br>2.No|All<br>Withassetsbehind|\n|Housing, Land and Property|Assets left<br>behind|K2_4|Do you have proof of ownership to<br>reclaimorrecover{asset}?|<br>1. Yes<br>2.No|<br>All<br>Withassetsbehind|\n|Housing, Land and Property|Assets in<br>", "output": {"entities": {"named_data": [], "descriptive_data": ["HOUSEHOLD SURVEY"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001035", "page": 71, "chunk": 0, "title": "Displacement as challenge and opportunity - Urban profile: Refugees, internally displaced persons and host community, Erbil Governorate, Kurdistan Region of Iraq - April 2016 [EN/AR/KU]", "pdf_url": "https://reliefweb.int/attachments/9dc591a5-d36a-3b63-8d5c-f93ed9b6226f/ErbilUrbanProfilingApril2016English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "HOUSEHOLD SURVEY", "label": "DESCRIPTIVE_DATA", "score": 0.7357485890388489, "start": 36, "end": 52, "probe_score": 0.2633, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Italy).<br>23<br><br><br>|**Table 2. Origin of asylum applications lodged in 43 industrialized countries, 2006 and 2007**<br>Covering 43 countries which provided monthly data to UNHCR (excluding Italy).<br>23<br><br><br>|**Table 2. Origin of asylum applications lodged in 43 industrialized countries, 2006 and 2007**<br>Covering 43 countries which provided monthly data to UNHCR (excluding Italy).<br>23<br><br><br>|**Table 2. Origin of asylum applications lodged in 43 industrialized countries, 2006 and 2007**<br>Covering 43 countries which provided monthly data to UNHCR (excluding Italy).<br>23<br><br><br>|**Table 2. Origin of asylum applications lodged in 43 industrialized countries, 2006 and 2007**<br>Covering 43 countries which provided monthly data to UNHCR (excluding Italy).<br>23<br><br><br>|\n|Origin<br>|2006<br>|2007<br>|Total<br>|Annual<br>change<br>|Share<br><br>|Share<br><br>|Rank<br><br>|Rank<br><br>|\n|Origin<br>|2006<br>|2007<br>|Total<br>|Annual<br>change<br>|2006<br><br>|2007<br><br>|2006<br>|2007<br>|\n|Iraq<br>|22,908<br>|45,247<br>|68,155<br>|98%<br>|8.2<br> <br", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["monthly data", "monthly data", "monthly data", "monthly data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001058", "page": 13, "chunk": 1, "title": "Asylum levels and trends in industrialized countries, 2007", "pdf_url": "https://reliefweb.int/attachments/a0f955c8-b460-3603-b1cc-8d2ccc064a5f/BF4CF8525B21A81049257410001BC61A-Full_Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "monthly data", "label": "VAGUE_DATA", "score": 0.6292732954025269, "start": 163, "end": 175, "probe_score": 0.9529, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "monthly data", "label": "VAGUE_DATA", "score": 0.5691385865211487, "start": 358, "end": 370, "probe_score": 0.9692, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "monthly data", "label": "VAGUE_DATA", "score": 0.5445142984390259, "start": 553, "end": 565, "probe_score": 0.9516, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "monthly data", "label": "VAGUE_DATA", "score": 0.5197250843048096, "start": 748, "end": 760, "probe_score": 0.8996, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2.2. Provision of technical assistance and capacity building services to MoE, Teachers Service\nCommission (TSC), Kenya National Examinations Council (KNEC), Kenya Institute of\nCurriculum Development (KICD), and other relevant agencies to, _inter alia:_ (a) carry out a\nnational survey on child development and pre-primary school quality assurance standards and\ntools; (b) develop standard tools for appraisal for teachers in pre-school; (c) assist evaluation\nand quality assurance of the CBC and CBA including adapting CBC for Special Needs\nEducation (SNE) and digitizing CBC for selected grades; ( d) assist teachers in primary schools\nto access and utilize the online portal for formative learning assessments; ( e) develop\nimplementation guidelines for school meals and nutrition policy; (f) monitor the School-Based\nTeacher Support (SBTS) initiative; (g) support activities for out of school children; (h) support\nthe capacity of Kenya National Examinations Council (KNEC) to conduct and disseminate a\nNational Assessment System for Monitoring Learner Achievement (NASMLA) for grade 3\nlearners; (i) analyze TP AD data in target schools for lessons coverage; G) conduct assessments\nto measure teacher proficiency; (k) provide scholarship and mentorship services, and refugee\neducation services; (1) digitize curriculum for all grades, including SNE; (m) develop a costed\nten-year operational plan for teacher workforce projections by grades and learning areas, and\n(n) carry out teacher support and data management.\n\n\n2.3. Carrying out a program of activities designed to strengthen education system capacity, such\nprogram to include: (a) strengthening gender responsive planning and policy development for\nsystem wide impact, including through reviewing teacher recruitment, management, and\ndevelopment processes, and developing an action plan to address identified gender\ngaps/inequalities; (b) training of county directors of education, KICD and KNEC, to integrate", "output": {"entities": {"named_data": ["TP AD data"], "descriptive_data": ["national survey on child development"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000814", "page": 3, "chunk": 0, "title": "Official Documents- Amendment Letter to the Financing Agreement and Grant Agreement for Credit 7067-KE, Grant D991-KE, GPE Grant TF0C0306 and TF0C0307.pdf", "pdf_url": "https://documents.worldbank.org/curated/en/099021826105532670/pdf/P176867-db30a139-4314-4a1e-8929-72e690e4f815.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "national survey on child development", "label": "DESCRIPTIVE_DATA", "score": 0.5427783727645874, "start": 269, "end": 305, "probe_score": 0.0952, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "TP AD data", "label": "NAMED_DATA", "score": 0.7398223280906677, "start": 1111, "end": 1121, "probe_score": 0.4435, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " quality and condition of the network.|<br>Description:The visual survey involves camera recording of road network condition, in addition to other visual measures. The collected data will then be decoded in<br>accordance of a road inspection manual that associates various aspects of the recording with a rating of the quality and condition of the network.|<br>Description:The visual survey involves camera recording of road network condition, in addition to other visual measures. The collected data will then be decoded in<br>accordance of a road inspection manual that associates various aspects of the recording with a rating of the quality and condition of the network.|\n|<br>|**Name:**Number of wheel<br>loaders purchased||Number|0.00|15.00|Bi‐Annual<br>|Progress report compiled by<br>CDR. Bank implementation<br>support mission.<br>|CDR<br>|\n|<br>|<br>Description:Necessary equipment for emergency road repairs.|<br>Description:Necessary equipment for emergency road repairs.|<br>Description:Necessary equipment for emergency road repairs.|<br>Description", "output": {"entities": {"named_data": [], "descriptive_data": ["visual survey", "visual survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 49, "chunk": 8, "title": "Lebanon - Roads and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/210611486651815142/pdf/Lebanon-Roads-Employment-PAD-P160223-01262017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "visual survey", "label": "DESCRIPTIVE_DATA", "score": 0.5861364006996155, "start": 59, "end": 72, "probe_score": 0.9932, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "visual survey", "label": "DESCRIPTIVE_DATA", "score": 0.5179268717765808, "start": 377, "end": 390, "probe_score": 0.9932, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " of PAPs ................................................................................................................... 26\n\n\n3.3 Socio-Economic Survey of PAPs ................................................................................................. 27\n\n\n3.3.1 Ziwa La Ngombe ..................................................................................................................... 27\n\n\n**6 |** P a g e", "output": {"entities": {"named_data": ["Socio-Economic Survey of PAPs"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008332", "page": 5, "chunk": 7, "title": "Kenya - Informal Settlements Improvement Program Project : resettlement plan (Vol. 3 of 9) : Resettlement action plan for infrastructure improvement projects in Mkomani, Ziwa la Ng'ombe, Jomvu kuu, and Jomvu Mikanjuni informal settlements, Mombasa country", "pdf_url": "https://documents.worldbank.org/curated/en/128111468041383436/pdf/RP10590V30AFR000Box379875B00PUBLIC0.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Socio-Economic Survey of PAPs", "label": "NAMED_DATA", "score": 0.6356282830238342, "start": 134, "end": 163, "probe_score": 0.0004, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "br>|\n|20-29<br>|33<br>|41.3<br>|\n|30-39<br>|17<br>|21.3<br>|\n|40-49<br>|19<br>|23.8<br>|\n|50-59<br>|5 <br>|6.3<br>|\n|60+<br>|2 <br>|2.5<br>|\n|Position in a HH|||\n|Mother<br>|55<br>|68.8<br>|\n|Household head<br>|22<br>|27.5<br>|\n|Children|3|3.8|\n\n\n\n**_3.2 Exisiting sources and types/forms of energy utilized for cooking_**\nMost respondents (over 30%) use bio-energy including firewood, crop\nresidues and charcoal as the main forms of energy for cooking in the refugee\nsettlement surveyed (Table 3.2). The other forms of energy used include,\ncrop residues particularly from maize, beans and cassava following\nharvesting. Less than 2% of the refugees use electricity, paraffin, biogas,\nand briquettes for cooking energy. Although fire wood is mostly used to cook\nfood in all the seasons, refugees also use charcoal, briquettes, crop residues\nand paraffin to cook during the rainy season (Figure 3.1). Most of firewood\nand charcoal used to cook are majorly obtained from the already depleted\n\n\n14", "output": {"entities": {"named_data": [], "descriptive_data": ["refugee\nsettlement surveyed"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000735", "page": 12, "chunk": 1, "title": "Final Report: Understanding the Dynamics for Utilization of Household Cooking Energy in Kyangwali Refugee Settlement", "pdf_url": "https://reliefweb.int/attachments/6bf7ec54-c070-3f64-9341-3f4f3d1f4edf/64189.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "refugee\nsettlement surveyed", "label": "DESCRIPTIVE_DATA", "score": 0.8929223418235779, "start": 460, "end": 487, "probe_score": 0.9652, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " provided with a prepaid electronic\nvoucher (e-card) to meet their monthly food needs. <sup>37</sup> Each month WFP delivers vouchers worth\nUS$30 to every Syrian refugee in Lebanon who qualifies for food assistance. Beneficiaries are\nnot obliged to spend the full amount at once, which means they can use it whenever they need, as\nlong as they spend the amount within the month. These vouchers can be exchanged for food\nitems of their choice in any of approximately 285 WFP contracted shops throughout Lebanon.\nVouchers were adopted as the primary modality of assistance in Lebanon as the local market is\nmore than capable of providing sufficient food for the host and refugee populations alike. Thus\nthere is no need to import large quantities of food. Instead, the vouchers, and now the e-cards,\nprovide vulnerable Syrian refugees with the means to access the Lebanese market themselves.\n\n10. In early 2013, WFP began working to shift modality from the paper voucher system to a\nnew, electronic, pre-paid voucher system. Following several months of planning and research,\nWFP signed a partnership agreement in September 2013 with MasterCard and a local bank. The\nfirst 1,908 credit card-style e-cards (for 10,306 beneficiaries) were distributed in a successful\npilot scheme in South Lebanon. In October 2013, a general roll out followed for the entire\ncaseload in Beirut, Mt Lebanon and the South, some 140,000 beneficiaries.\n\n\n36 In cases where a new applicant is ranked as one of the poorest 50,000 beneficiaries using the NPTP database, she/he will\nreceive all NPTP benefits including the e-card food voucher.\n37 Eligible families are registered by UNHCR and based on a vulnerability criteria agreed by WFP and UNHCR.\n\n\n27", "output": {"entities": {"named_data": ["NPTP database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000047", "page": 37, "chunk": 1, "title": "Lebanon - Emergency National Poverty Targeting Program Project", "pdf_url": "http://documents.worldbank.org/curated/en/810511467987899324/pdf/PAD1030-ENGLISH-P149242-PUBLIC-FINAL-LEB-ENPTP-English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NPTP database", "label": "NAMED_DATA", "score": 0.9065791964530945, "start": 1527, "end": 1540, "probe_score": 0.0035, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "This confirms that the Recipient is authorizing such persons to accept Secure Identification\nCredentials (SIDC) and to deliver the Applications and supporting documents to the Bank by electronic\nmeans. In full recognition that the Bank shall rely upon such representations and warranties, including\nwithout limitation, the representations and warranties contained in the _Terms and Conditions of Use of_\n_Secure Identification Credentials in connection with Use of Electronic Means to Process Applications and_\n_Supporting Documentation_ (“Terms and Conditions of Use of SIDC”), the Recipient represents and\nwarrants to the Bank that it will cause such persons to abide by those terms and conditions.]\n\nThis Authorization replaces and supersedes any Authorization currently in the Bank records with\nrespect to this Agreement.\n\n\n[Name], [position] Specimen Signature: ____________________\n\n[Name], [position] Specimen Signature: ____________________\n\n[Name], [position] Specimen Signature: ____________________\n\n\nYours truly,\n\n\n/ signed /\n\n\n______________\n\n[Position] <sup>1</sup>\n\n\n1 Instruction to Bank staff: please forward this letter to the Country Lawyer for further processing (Recipient: please\ndo not delete this note).", "output": {"entities": {"named_data": [], "descriptive_data": ["Bank records"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003569", "page": 6, "chunk": 0, "title": "Official Documents- Disbursement and Financial Information Letter for Additional Financing GFF Grant TF0D2458 and for MDTF Grant TF0D2443.pdf", "pdf_url": "https://documents.worldbank.org/curated/en/099071326105035439/pdf/P175167-d4df91fe-7c33-4560-ae76-ff7898fb9375.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Bank records", "label": "DESCRIPTIVE_DATA", "score": 0.7515029311180115, "start": 781, "end": 793, "probe_score": 0.0028, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "output": {"entities": {"named_data": [], "descriptive_data": ["household expenditure survey data", "data from the Household Survey"], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000038", "page": 38, "chunk": 1, "title": "Africa - Multi - Country HIV/AIDS Program for the Africa Region (Ethiopia and Kenya)", "pdf_url": "http://documents1.worldbank.org/curated/en/287591468768313907/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household expenditure survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8699104189872742, "start": 565, "end": 598, "probe_score": 0.7323, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.5808603167533875, "start": 870, "end": 881, "probe_score": 0.1461, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from the Household Survey", "label": "DESCRIPTIVE_DATA", "score": 0.5346028804779053, "start": 1978, "end": 2008, "probe_score": 0.1121, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and middle\nPrivate sector share in middle schools.\nschools increases to 12%.\n\n\nHigher promotion rates at the Promotion rates at the end of Year books and reports. Assumes enough space at the\nend of the primary school the primary cycle should rise middle schools to\ncycle. from 36% in 1999 to 83% in accommodate the primary\n2010. cycle graduates.\nIncrease participation of girls Enrollment rate for girls Random surveys of Economic situation worsens\nand children from poorer increases faster than boys. school students making it more difficult to\ngroups More children from poorer including a baseline in provide incentives to the poor\ngroups in school. 2001 and follow up to attend.\nsurveys in 2005 and\n2010.", "output": {"entities": {"named_data": [], "descriptive_data": ["Random surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017462", "page": 29, "chunk": 1, "title": "Kenya - Agricultural Sector Management Project", "pdf_url": "https://documents.worldbank.org/curated/en/738711468047699881/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Random surveys", "label": "DESCRIPTIVE_DATA", "score": 0.5383497476577759, "start": 405, "end": 419, "probe_score": 0.2766, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">CFS is<br>launching a|CFS local offices<br>produce simple reports<br>by region on<br>attendance to schools<br>and health centers<br>rehabilitated/built by<br>the<br>project. Information<br>will be collected from<br>schools and health<br>centers (enrollment<br>lists and patient logs) to<br>calculate utilization;<br>utilization of other<br>community<br>infrastructure will be<br>determined on the<br>basis of representative|CFS<br>|\n\n\nPage 42", "output": {"entities": {"named_data": [], "descriptive_data": ["patient logs"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000112", "page": 46, "chunk": 1, "title": "Chad - Refugees and Host Communities Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/658761536982256019/pdf/PAD2809-PAD-PUBLIC-disclosed-9-12-2018-IDA-R2018-0286-1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "patient logs", "label": "DESCRIPTIVE_DATA", "score": 0.7857341170310974, "start": 271, "end": 283, "probe_score": 0.1322, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Table 2 and Table 4 (evaluated at the median). The marginal e¤ects con…rm the conclusion that\n\n\nthe IV estimates of the e¤ects of the land restrictions on wages are substantially larger compared\n\n\nto the OLS estimates; the marginal e¤ects are -0.46 (OLS, column (5) Table 2) and -1.41 (column\n\n\n(1) in Table 4). This substantial increase in the estimated e¤ect of land restrictions on wages\n\n\nafter instrumentation is indicative of the importance of unobserved positive productivity as the\n\n\nmain source of omitted variables bias as discussed in details earlier.\n\n\n6.3. Additional Robustness Checks: Can Long Run Adverse E¤ects of Early-Age\n\n\nMalaria Exposure Drive the Results?\n\n\nAlthough we control for education, age, and current malaria infection rates in the IV re\n\ngressions, one might still worry that they might not be adequate controls for potential long term\n\n\ne¤ects of early-age malaria on health and education. For example, if a signi…cant proportion of the\n\n\nindividuals in our sample belong to age cohorts that were a¤ected by malaria prevalence during\n\n\n1937-1941, then they are likely to have lower educational attainment and adverse health status.\n\n\nWe have reasonably good controls for education, as both individual and DSD level indicators of\n\n\neducation are used in the IV regressions. However, the Sri Lanka HIES 2002 lacks good measures\n\n\nof health of the individuals. To check if our results are driven by long term negative e¤ects of\n\n\nearly-age malaria, we perform robustness checks by excluding early age malaria cohorts from the\n\n\nsample, those born before 1947, 1950, and 1960 respectively. The oldest person in our sample\n\n\nis born in 1937 and the youngest in 1981. The results from estimating the IV regressions using\n\n\nthe three subsamples are reported in Table 5. It is reassuring that the estimates are consistent\n\n\nwith the", "output": {"entities": {"named_data": ["Sri Lanka HIES 2002"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004647", "page": 28, "chunk": 0, "title": "wps5461", "pdf_url": "https://local/prwp/wps5461.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Sri Lanka HIES 2002", "label": "NAMED_DATA", "score": 0.8845551609992981, "start": 1320, "end": 1339, "probe_score": 0.9986, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEnhancing Community Resilience and Local Governance Project Phase II (P177093)\n\n\n**B. Introduction and Context**\n\nCountry Context\n\n1. **South Sudan has been beset by decades of armed conflicts and ranks as one of the least developed countries in**\n**the world today.** Southern Sudan, as the region was called before independence, has been marred by conflict since 1955,\njust a year before Sudan attained its independence from British colonial rule. The region experienced systematic\nmarginalization and underdevelopment under both British and Sudanese rule, inhibiting it from developing its physical\nand human capital. Consequently, at its independence in July 2011, South Sudan ranked almost at the bottom of the global\ndevelopment indicators with little infrastructure, basic services provided almost entirely through humanitarian aid, and\nan economy completely dependent on oil. Renewed civil conflict broke out in December 2013 and has only recently\nsubsided with the formation of the Transitional Government of National Unity in February 2020, pursuant to the terms of\nthe September 2018 Revitalized Agreement on the Resolution of the Conflict in the Republic of South Sudan (R-ARCSS). <sup>1</sup> [^1: IGAD: https://igad.int/programs/115-south-sudan-office/1950-signed-revitalized-agreement-on-the-resolution-of-the-conflict-in-south-sudan]\nPeace remains fragile, and implementation of several key provisions of the R-ARCSS – such as the unification of armed\nforces of different factions, disarmament, demobilization and reintegration of ex-combatants, and transitional justice –\nremain stalled. While the national-level ceasefire is largely holding, violent events persist across the country, often with\nlinks to national actors and dynamics. Violent events and fatalities were twice the level in 2020 compared to 2019. Jonglei,\nthe Greater Pibor Administrative Area, Warrap, Lakes, and the Equatoria regions have all seen recent violence. <sup>2</sup> <mark>As a result</mark>\n<mark>of decades of insecurity, nearly 8.3 million people of the estimated 14", "output": {"entities": {"named_data": [], "descriptive_data": ["global\ndevelopment indicators"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000027", "page": 2, "chunk": 0, "title": "Concept Project Information Document (PID) - Enhancing Community Resilience and Local Governance Project Phase II - P177093", "pdf_url": "http://documents.worldbank.org/curated/en/538641629099997119/pdf/Concept-Project-Information-Document-PID-Enhancing-Community-Resilience-and-Local-Governance-Project-Phase-II-P177093.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "global\ndevelopment indicators", "label": "DESCRIPTIVE_DATA", "score": 0.6823084354400635, "start": 735, "end": 764, "probe_score": 0.9737, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**7. Implementation Issues, Costs and Local Employment Benefits**\n\n\nThe results in Section 4 indicate that coordinated upgrading of the Sub-Saharan\n\n\nroad network is likely to generate a very large expansion of interregional trade.\n\n\nPiecemeal, local improvements do not have the same potential, because the cost\n\n\ncalculations of interregional shippers will be dominated by conditions in the lowest\n\nquality network links. The success of upgrading would depend on smooth traffic flow\n\n\nover the whole network, with minimal delays at national borders and open roads within\n\n\ncountries. We recognize that implementation of such a program would be difficult, but\n\n\nour results suggest that the potential payoff is sufficiently high to warrant a serious\n\n\ndiscussion.\n\n\nIn this section, we offer some preliminary thoughts about appropriate institutional\n\n\narrangements and administrative measures, along with the associated costs. We present\n\n\nestimates of direct and indirect benefits for the rural poor generated by upgrading and\n\n\nmaintaining the road system. We also provide rough estimates of the costs associated\n\n\nwith administration of a trans-African network. We recognize the uncertainty in these\n\n\nestimates, but for the present purposes we are interested in orders of magnitude, not\n\n\nprecise figures. We have already estimated maintenance costs from our econometric\n\n\nanalysis of projects in the ROCKS database.\n\n\n**7.1 Overall Organization and Financing** .\n\n\nCoordinated upgrading and maintenance of the network could be accomplished by\n\n\nan all-Africa convention on overland trade, implemented in collaboration with\n\n\nmultilateral and bilateral donors, that would cover 5 years of upgrading and 10 years of\n\n\n37", "output": {"entities": {"named_data": ["ROCKS database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003310", "page": 37, "chunk": 0, "title": "wps4097", "pdf_url": "https://local/prwp/wps4097.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "ROCKS database", "label": "NAMED_DATA", "score": 0.9093854427337646, "start": 1406, "end": 1420, "probe_score": 0.8559, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ",508 households,\ngiving an average irrigable area of 1.82 ha per household. Crops include cotton,\nmaize, sunflower, sorghum, teff, haricot bean, pepper and rice in the wet season;\nand maize, sunflower, haricot bean, onion and rice in the dry season. The major\nenvironmental health concerns in the area are water-related diseases such as\nmalaria, typhus, and schistomiasis. Environmentally sensitive areas that are\nlocated close to the Megech irrigation project areas include the Megech River, Lake\nTana, and a 300 ha closed wetland system. The Megech River is a small seasonal\nriver which is used as a spawning site for Lake Tana fish species of which the\ndominant are _Barbus_ spp., _Oreochromis_ spp., and _Clarius_ spp. Parts of the Lake\nTana margin are important wetland habitat, especially for birds.\n\nThe population size, as projected from the 1994 Census, was 26,880 in 1997, of\nwhich about are14,021 economically active. The majority of the populations belong\nto the Amhara ethnic group. The available social services in the command area\ninclude: 6 primary schools with 27 teachers, one junior secondary school with 2\nteachers, one health post with two health assistants, grain mills (one grain mill for\nevery 1519 households). The gross enrolment ratio in education in Megech\ncommand area, at 8%, is reported to be among the lowest in the Amhara Region.\nNo household has access to clean water, and there is no electric power supply in\nthe command area. The main source of energy is fuel wood. Access roads are\nconstrained by the lack of bridges across the Megech River. During the 1994 and\n1997 period, 2220 households were affected by food deficit.\n\n\nENVIRONMENTAL RESOURCES MANAGEMENT 7 ETHIOPIA EIDP ESMF", "output": {"entities": {"named_data": ["1994 Census"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012796", "page": 12, "chunk": 1, "title": "Ethiopia - Irrigation and Drainage Project : environmental assessment (Vol. 1 of 6) : Environmental and social management framework", "pdf_url": "https://documents.worldbank.org/curated/en/422331468275112363/pdf/E27550v10P1253101public10BOX358335B.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1994 Census", "label": "NAMED_DATA", "score": 0.8522201776504517, "start": 850, "end": 861, "probe_score": 0.9626, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " in armed conflict may facilitate substantial population**\n**movement.** About 1.2 million people have returned from displacement within and outside of South Sudan since 2016 to\ndate. Among them, over 534,000 people (45 percent) returned since the signing of the revitalized peace agreement in\nSeptember 2018 until March 2019. <sup>13</sup> [^13: IOM DTM] This demonstrates that more people returned in a shorter period of time since the\nsigning of the agreement. According to both the UNHCR and IOM’s recent intention surveys, major pull factors for return\nare improved security, family reunification, access to basic services, and livelihood opportunities. For refugees, 30 percent\nof them in neighboring countries consider returning but majority are waiting to see how the situation unfolds. Slightly\nhigher numbers of IDPs have longer term return intentions to home areas. The prevailing security and basic living\nconditions are not yet conducive to more widespread return movements among both populations, however. In addition,\nthere have been new/secondary displacements triggered by intensifying inter-communal clashes in areas such as Unity,\nWarrap, Lakes, Western Bahr-el-Ghazal, Central Equatoria and Jonglei. <sup>14</sup> [^14: UNMISS (August 2019) ( _Mimeo_ )] Population movement thus remains volatile,\nwhere temporary visits by single family members to look after assets and property in home areas predominate. Should\nthe unity government be formed in November 2019 and security situation improve, however, the return of some of the\n4.2 million displaced (both refugees and IDPs) is likely to accelerate.\n\n9. **Unlike in other countries where significant numbers of returnees gravitate to major cities, in South Sudan the**\n**evidence suggests that IDPs and refugees are likely to return to their original villages or in their vicinity.** Existing data\nshows that a large majority (87 percent) of IDP and refugee returns are primarily to areas of habitual residence while\nrelocations to third areas is quite", "output": {"entities": {"named_data": ["IOM DTM"], "descriptive_data": ["intention surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000014", "page": 4, "chunk": 1, "title": "Concept Project Information Document (PID) - South Sudan Enhancing Community Resilience and Local Governance Project - P169949", "pdf_url": "http://documents.worldbank.org/curated/en/294881573571217860/pdf/Concept-Project-Information-Document-PID-South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project-P169949.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "IOM DTM", "label": "NAMED_DATA", "score": 0.7504343390464783, "start": 347, "end": 354, "probe_score": 0.9374, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "intention surveys", "label": "DESCRIPTIVE_DATA", "score": 0.7159473896026611, "start": 509, "end": 526, "probe_score": 0.8434, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the male head of the family.\n\n\nWhile at the time of issuance of this brief road conditions still do not allow the continuation of the\nrelocation, it is expected that the operation will resume at the end of the rainy season in October or\nNovember.\n\n\n_New arrivals collect water at the UNHCR-supported Korsi area, near Birao (Vakaga prefecture). UNHCR/Josselin_\n_Bremau_\n\n**Preserving the civilian and humanitarian character of asylum and of refugee sites** . The unstable\nsecurity situation in the Prefectures Sudanese refugees have arrived, as well as the porosity of the\nborder between CAR and Sudan in these remote areas, have triggered significant risks of infiltration\nand presence of armed elements, linked to the fighting ongoing in Sudan. The presence of armed\nelements has been detected since the end of May in Am-Dafock. In addition, according to findings of\nprotection monitoring, the RSF and affiliated armed elements patrol and control the Sudan side of Am\n\nUNHCR 7", "output": {"entities": {"named_data": [], "descriptive_data": ["findings of\nprotection monitoring"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000485", "page": 6, "chunk": 1, "title": "UNHCR CAR: Protection brief Sudan situation - September 2023", "pdf_url": "https://reliefweb.int/attachments/453b8ef6-c34e-4318-9747-569c011ae3b9/Protection%20brief%20Soudan%20situation%20CAR%20septembre%202023.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "findings of\nprotection monitoring", "label": "DESCRIPTIVE_DATA", "score": 0.830222487449646, "start": 857, "end": 890, "probe_score": 0.0041, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Recommendations**\nPaving pathways for inclusion: A global overview of refugee education data\n\n##### ~~Paving pathways for inclusion~~\n## ~~A global overview of~~ ~~refugee education data~~\n\n\n**4**", "output": {"entities": {"named_data": [], "descriptive_data": ["refugee education data", "refugee education data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000382", "page": 3, "chunk": 0, "title": "Paving pathways for inclusion: a global overview of refugee education data", "pdf_url": "https://reliefweb.int/attachments/31f00be7-0481-4224-80ce-378c049a02d4/Paving%20pathways%20for%20inclusion%20--%20a%20global%20overview%20of%20refugee%20education%20data.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "refugee education data", "label": "DESCRIPTIVE_DATA", "score": 0.6279153823852539, "start": 72, "end": 94, "probe_score": 0.5337, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "refugee education data", "label": "DESCRIPTIVE_DATA", "score": 0.5659859776496887, "start": 166, "end": 188, "probe_score": 0.3465, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " can be used both to\nhelp those who need assistance the most and to hold\nrelevant parties accountable to their commitments.\n\nIn general, the quality of demographic data tends\nto be highest in countries where UNHCR has an operational role, undertakes registration and primary\ndata collection, and has been engaged for a year\nor more. For some populations – mostly in developing countries – UNHCR has additional demographic\nand socio-economic information, including date\nand place of birth, language, occupation, civil status, religion, and education level. In locations where\ngovernments are exclusively responsible for data\ncollection, comprehensive disaggregated data on\nrefugees, IDPs, and others of concern often are lacking or unavailable.\n\n\nUNHCR Global Trends 2015 **51**", "output": {"entities": {"named_data": [], "descriptive_data": ["disaggregated data"], "vague_data": ["demographic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001367", "page": 49, "chunk": 1, "title": "UNHCR Global Trends: Forced Displacement in 2015", "pdf_url": "https://reliefweb.int/attachments/d39729ec-75aa-3628-89e5-6ae32a617930/576408cd7.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "demographic data", "label": "VAGUE_DATA", "score": 0.6215022802352905, "start": 152, "end": 168, "probe_score": 0.0183, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "disaggregated data", "label": "DESCRIPTIVE_DATA", "score": 0.5616229176521301, "start": 650, "end": 668, "probe_score": 0.0379, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a negative\n\n\namenity. Kurschner Rauck and Kvasnicka (2018) compare rents in counties with high vs.¨ low inflows\n\nover a ten-year period. While rents in both types of cities followed a similar trajectory before the\n\ninflow, rents in high-inflow areas decreased disproportionately after the inflow. Complementary\n\n\nevidence is provided for refugee shelters in Berlin by Hennig (2021). He shows that the location of\n\n\nshelters is unrelated to neighborhood characteristics; after the shelters were established, rental prices\n\n\nin the vicinity of the shelters decreased. Kurschner Rauck (2020) finds similar effects for sale prices¨\n\n\nin the whole of Germany: house prices in the vicinity of refugee reception centers dropped relative\n\n\nto prices of comparable houses in areas without a center. These findings are consistent with results\n\nfrom a choice experiment by Liebe et al. (2018), who show that large parts of the sample oppose a\n\n\nreception center in their vicinity.\n\n\nOf particular interest for policy is the effect of the refugee inflow on crime. Thus far, there is no\n\n\nevidence that the asylum seekers affected violent crimes in general, or any crimes that are directed\n\n\ntowards natives (Huang and Kvasnicka, 2019), although there is evidence of an increase in non-violent\n\n\nproperty crime, petty crime, and drug offenses (Gehrsitz and Ungerer, 2017, Dehos, 2021).\n\n\nSeveral studies document a shift in political preferences. Mader and Schoen (2019) use panel data\n\nto document a shift in voters’ perceptions of different parties. In particular, conservative voters\n\n\nshowed less support for the CDU after the government’s decision to admit a large number of asylum\n\nseekers. The effects on voting outcomes are mixed. Whereas Schaub et al. (2021) find no effect of\n\n\nthe local presence of asylum seekers on voting outcomes in the federal elections, Bredtmann (2020)\n\n\ndocuments small effects on right-wing voting in the state election in Rhineland-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["panel data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000449", "page": 13, "chunk": 1, "title": "forced migration social cohesion and conflict the 2015 refugee inflow in germany", "pdf_url": "https://local/prwp/forced-migration-social-cohesion-and-conflict-the-2015-refugee-inflow-in-germany.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "panel data", "label": "VAGUE_DATA", "score": 0.6250520348548889, "start": 1463, "end": 1473, "probe_score": 0.9298, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Child centered<br>DRR, and with focus on hazards and potential risks on children during flooding,<br>Minimum Preparedness Actions (MPAs) recommended both structural and non-<br>structural inclusive of capacity development to enhance the level of emergency<br>preparedness in schools prone to recurrent flooding.<br>(source: District Education office, UNICEF, Save the Children and  HCTT  Need<br>assessment survey)|**Needs and Priorities:**<br>•<br>Repair and Maintenance of the schools/learning centres. The Directorate of<br>Primary Education (DPE) has allocated limited budget for education in emergency.<br>•<br>Education kits and materials to the affected learners (khata, pencils, eraser,<br>sharpener, school bag and umbrella) at home and in shelters.<br>•<br>Community (such as SMCs) mobilization for learning continuity at home and in<br>shelters especially for affected and vulnerable children including children with<br>disabilities..<br>•<br>Rolling out upazila education emergency preparedness plans<br>•<br>Teacher’s orientation for education in emergency.<br>•<br>Within the framework of school safety and security protocols under Child centered<br>DRR, and with focus on hazards and potential risks on children during flooding,<br>Minimum Preparedness Actions (MPAs) recommended both structural and non-<br>structural inclusive of capacity development to enhance the level of emergency<br>preparedness in schools prone to recurrent flooding.<br>(source: District Education office, UNICEF, Save the Children and  HCTT  Need<br>assessment survey)|\n|**Health**|**Health**|**Health**|\n|**_Impacts_*", "output": {"entities": {"named_data": [], "descriptive_data": ["assessment survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001664", "page": 9, "chunk": 3, "title": "Impact of the monsoon & COVID-19 containment measures: Shelter and infrastructure damage in the Rohingya refugee camps | Flash report – 20 August 2020", "pdf_url": "https://reliefweb.int/sites/reliefweb.int/files/resources/nawg_monsoon_flood_preliminary_impact_and_kin_20200725_final_draft.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "assessment survey", "label": "DESCRIPTIVE_DATA", "score": 0.6259760856628418, "start": 397, "end": 414, "probe_score": 0.0374, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000022", "page": 62, "chunk": 2, "title": "Albania - Microcredit Project", "pdf_url": "http://documents1.worldbank.org/curated/en/192291468767658763/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda Secondary Education Expansion Project (P166570)\n\n\n_Description:_ Local Government School Inspections;\n\n_Oversight:_ There is sufficient controls in LG accounting instructions to ensure efficient spending.\nInternal audit verifies delivery of services and OAG carries out external audits on an\nannual basis.\n\n\n_(iii)_ _Employee related expenses of Secondary education functions of all district local governments_\n_Type:_ Recurrent Budget;\n_Vote:_ 500-800;\n_Description:_ Staff Salaries for Secondary Teachers: Pay and allowances for districts/LG employees of\nthe School Education Department;\n_Oversight:_ Salaries are subject to overall payroll controls which are considered adequate with\nPersonnel records being maintained at LGs, Ministry of Public Service and regional centers\nthrough the Integrated Payroll & Pension System (IPPS).\n\n**Disbursement and Funds Flow Arrangements:**\n\n15. A results-based financing modality will be used for agreed project components whereby funds will be\ndisbursed into the designated accounts at the Bank of Uganda. Given that funds will be disbursed using a PBC\napproach, it will work as follows:\n\n   - A set of PBCs for each year of the project will be determined.\n\n   - For each subsequent year, as the respective PBCs are met, IDA will disburse to the Government DA upon\nachievement of results under respective PBCs - independently verified.\n\n   - A possibility to disburse some funds before results have been achieved has been built into the project to\nhelp provide funds for the government to achieve a set of PBC values or TA costs not linked to any\nindicator.\n\n16. Once the MoES has approved the assessment results by an independent assessment agency through an\nagreed verification protocol and the amounts to be disbursed for each of the PBCs determined, IDA will be\nnotified. Once the World Bank is satisfied, the total amount linked to each of the PBCs for the FY will be disbursed\nfrom the World Bank to the Go", "output": {"entities": {"named_data": [], "descriptive_data": ["Personnel records"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 89, "chunk": 0, "title": "Uganda - Secondary Education Expansion Project", "pdf_url": "http://documents.worldbank.org/curated/en/406361595815248191/pdf/Uganda-Secondary-Education-Expansion-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Personnel records", "label": "DESCRIPTIVE_DATA", "score": 0.8012112975120544, "start": 713, "end": 730, "probe_score": 0.001, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "THE ROLE OF HOUSING SUPPORT AND EMPLOYMENT FACILITATION IN ECONOMIC VULNERABILITY OF REFUGEES FROM UKRAINE\n\n\n**<u>SHARE OF YOUNG UKRAINIANS (AGED 15 TO 24) WHO ARE NOT ENGAGED IN EMPLOYMENT, EDUCATION, OR TRAINING</u>**\n**(NEET) BY COUNTRY, %** <sup>**1,2,3**</sup>\n\n\nHost country Refugees, excluding online education Refugees\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nBulgaria Czechia Hungary Moldova Poland Romania Slovakia Region\n\n\n\n1. Data reported by the national statistics service was used as a\nreference for Moldova\n\n2. With the exception of Poland and the Czech Republic, the reliability\nof data by country is hindered by a relatively low number of\nobservations\n\n[3. Host country data is based on indicators reported by the OECD for](https://data.oecd.org/youthinac/youth-not-in-employment-education-or-training-neet.htm)\n[2022](https://data.oecd.org/youthinac/youth-not-in-employment-education-or-training-neet.htm)\n\n\n**<u>UKRAINE REFUGEE YOUTH ACTIVITY BY AGE</u>**\n\n\n\n**The gender divide: female – led households are**\n**more economically vulnerable than their male –**\n**led counterparts**\nThe share of households that are composed of\nfemale only adults with or without children\nconstitute 65% of the total sample across the\nregion. Compared to households with male only\nadults, the vast majority of which are without\nchildren, they are 51% more likely to find themselves\nbelow the poverty line.\n\n\n**<u>DISTRIBUTION OF HOUSEHOLDS BY GENDER OF</u>**\n**ADULTS, %**\n\n\n\nNEET\n\n\n15", "output": {"entities": {"named_data": [], "descriptive_data": ["Data reported by the national statistics service"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 8, "chunk": 0, "title": "3", "pdf_url": "https://local/jad_paddy_docs/3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data reported by the national statistics service", "label": "DESCRIPTIVE_DATA", "score": 0.8939626812934875, "start": 432, "end": 480, "probe_score": 0.9647, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_Figure [9]: Non-food related coping strategies_\n\n\n<u>PRS</u>\n\n\nDuring an UNRWA assessment in October 2013, participants in 16FGDS indicated the following coping\nmechanisms:\n\n\n  - Reducing essential non-food items such as electricity, water, and transportation, acquiring drinking\nwater from the public tap instead of buying water bottles, and sharing accommodation with other\nfamilies. This had forcibly led many families to live in collective shelters with separators between one\nfamily and another. As a result, this had created lack of privacy as several PRS individuals reported.\n\n  - Sleeping on mattresses instead of beds and borrowing money from other PRS families were also\nnoted.\n\n\n_Debt_\n\n\n  - Oxfam19 found that Syrian refugee household debt was USD 454. This positively correlated with length\nof residency. In Tripoli the average debt was over USD 815 (average residency in Lebanon over 15\nmonths) while in Beirut this was USD 153 per household.\n\n  - The VASyR found that 75% of households had debts and 70% reported borrowing money or receiving\ncredit during the three months before the survey was conducted. The average amount of debt was USD\n600, but half of the interviewed households owed USD 200 or less. Loans were mainly provided by\nfriends or relatives to buy food (81%), pay the rent (52%) or cover health expenses (25%). (Figure 10).\nHouseholds registered longer ago were significantly more likely to have higher amounts of debts.\n\n\n19Oxfam _2014) Winterization 2013-14 Baseline Report. February\n\n23", "output": {"entities": {"named_data": ["16FGDS", "VASyR"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000617", "page": 22, "chunk": 0, "title": "MSNA sector chapters - Basic needs", "pdf_url": "https://reliefweb.int/attachments/5ad2f3e6-32d7-35d0-bc93-27ca53c5d55b/BASIC%20NEEDS%20CHAPTER%20-%20FINAL%20April%2022.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "16FGDS", "label": "NAMED_DATA", "score": 0.6225646734237671, "start": 124, "end": 130, "probe_score": 0.8028, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "VASyR", "label": "NAMED_DATA", "score": 0.6264471411705017, "start": 968, "end": 973, "probe_score": 0.0001, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "</sup>\n\n\n\nversions of the Global Procurement <sup>Plan and the following year's</sup> <sup>annual</sup> <sup>procurement</sup> <sup>plan.</sup> <sup>Participating</sup>\n\n\n\nService Providers will be required <sup>to</sup> <sup>include</sup> <sup>procurement</sup> <sup>plans in</sup> <sup>their subproject proposals.</sup> <sup>The</sup>\n\n\n\ntechnical team reviewing community <sup>subproject proposals must ensure adequacy of a</sup> <sup>sub-project</sup>\n\n\n\nprocurement plan before the <sup>proposal</sup> <sup>is</sup> <sup>approved.</sup> <sup>Each</sup> <sup>quarter,</sup> <sup>NaCSA will</sup> <sup>submit</sup> <sup>to IDA a</sup>\n\n\n\nprocurement monitoring report <sup>as part of the Financial</sup> <sup>Management Report (FMR),</sup> <sup>to show how</sup> <sup>each</sup>\n\n\n\ncontract on the procurement <sup>plan</sup> <sup>has progressed.</sup> <sup>The POM</sup> <sup>will include</sup> <sup>sample formats</sup> <sup", "output": {"entities": {"named_data": [], "descriptive_data": ["procurement monitoring report"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000013", "page": 45, "chunk": 6, "title": "West Bank and Gaza - Education Action Project", "pdf_url": "http://documents1.worldbank.org/curated/en/137371468765334508/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "procurement monitoring report", "label": "DESCRIPTIVE_DATA", "score": 0.8535922765731812, "start": 641, "end": 670, "probe_score": 0.0289, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " program\ndesign.\n\n\nAmong the measures proposed by the studies to address these land issues are: (i) the regularization of\nresidential encroachment on state lands; and (ii) and the sub-division o f lands held in the name o f parents\n\n- f potential beneficiaries. In the East, the survey suggests that the former measure could consolidate the\nproperty claims o f over 60% - f non-owners while the latter could do the same for over 30%. The\ncorresponding proportions in the North are 45% and **25%** respectively. The program design includes a\ncommitment o f the GoSL to address these and other related issues through an accelerated program of\nengagement o f land issues executed by eight mobile District Land Task Forces (LTFs) operating on\ncontract over a nine month period. Villages where selection o f NEHRP beneficiaries takes place before\nthe LTFs complete their work will be revisited to allow beneficiaries who have their ownership\nsubsequently regularized to have access to the program.\n\n\n_Institutional Capacity:_ The lack o f adequate institutional capacity to manage large-scale reconstruction\nprograms remains an important concem. Program implementation requires partnerships at various levels.\nCommunity based organizations can be used to validate damage assessment, and the identification of\nbeneficiaries through “community listing”. It i s therefore necessary to strengthen the capacity, institutions\n\nand arrangements at the divisional level, and promote private sector partnerships. Contractual staff will\n\n\n**_l9_** Many officials at the central, provincial and district levels did not agree with the findings o f the survey arguing\nthat it had overstated the extent o f households that would have difficulty in demonstrating ownership of land.\n\n\n17", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000115", "page": 22, "chunk": 1, "title": "Sri Lanka - North East Housing Reconstruction Program", "pdf_url": "http://documents1.worldbank.org/curated/en/672131468763807868/pdf/304360LK.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey", "label": "VAGUE_DATA", "score": 0.5276320576667786, "start": 1635, "end": 1641, "probe_score": 0.0, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Independent Evaluation Group (IEG)** Implementation Completion Report (ICR) Review\nUG-KIIDP 2 (P133590)\n\n\nIn the **Directorate of Engineering and Technical Services** : the following outputs were achieved (not all had\ntargets):\n\n\n   - 62 staff were trained and obtained Project Management Professional certification and 50 others on\n\nother aspects of project management\n\n   - 3 staff were recruited\n\n   - procured software to develop an asset register\n\n   - developed Multi-Modal Transport Master Plan and mapped the following:\n\n`o` 2,523 suitable locations for motorcyclists (boda-boda) stages to guide streamlining its mobility\n\nin Kampala;\n\n`o` accident crash locations to improve road safety;\n\n`o` roads and junctions to optimize improvements and upgrading.\n\n\nin the **Directorate of Physical Planning**\n\n\n   - Procured software such as \"iROADS,\" an asset management software to manage road inventory; a\n\nCity Address Model (CAM) software to assist in road naming, addressing, and city navigation, an\nupdated the city's Geographic Information System (GIS) software to improve traffic safety data\ncollected. This resulted in the following (no targets were reported):\n\n`o` assigned 373,826 house numbers, **exceeding** the target of 314,000\n\n`o` named and approved 7,246 roads, **almost** **achieving** the target of 7,481\n\n   - For the following outputs, no targets were determined beforehand but reported as meeting needs:\n\n`o` Recruited 15 staff/consultants\n\n`o` installed 12,555 house number plate\n\n`o` installed 3,437 road signs\n\n\nIn the **Directorate of Revenue** (no targets were reported):\n\n\n   - 1,651,292 residents used the SMS mobile phone platform to pay bills and provide client feedback,\n\nexceeding the target of 386,522 residents. This was equivalent to 29.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["traffic safety data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002227", "page": 8, "chunk": 0, "title": "Uganda - UG-KIIDP 2", "pdf_url": "https://documents.worldbank.org/curated/en/099050324175020398/pdf/P1335901f69c440b41b63012e0e268cad14.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "traffic safety data", "label": "VAGUE_DATA", "score": 0.509192705154419, "start": 1082, "end": 1101, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the sensitivity of the EIRR to the\nmain elements of the economic cash-flows. The variables tested were: (i) investment costs; (ii) operating\ncosts; and (iii) water demand. The outcome of the scenarios is given in Table 4.5, which also provides the\nswitching values of the variables. The project is markedly sensitive to the reduction of water demand,\nwhich exhibits the lowest switching value. This primarily affects the sub-component devoted to the\ndevelopment of access. The very strong demand of rural households for service connections could,\nhowever, mitigate this risk.\n\n\n**Table 4.5: Results of the Sensitivity Analysis**\n\n\n\n\n\n\n\n|Scenario|EIRR|NPV @ 6% (US$<br>million)|Switching value|\n|---|---|---|---|\n|Base scenario|7.4%|5.16||\n|Investment cost increase 20%|5.6%|-1.76|14.7%|\n|O&M cost increase 20%|6.8%|2.90|43.5%|\n|Overall demand decrease 20%|4.6%|-4.87|10.1%|\n|Combined Investment cost increase<br>10%, O&M cost increase 10%, Overall<br>demand decrease 10%|4.9%|-4.24||\n\n\n**GHG Emissions**\n\n\n10. The CBA allows to compare the thermal energy consumption of water facilities in the with/without\nproject scenarios. The baseline data are estimated from the thermal energy consumption of existing\nfacilities, while the “with” project scenario accounts for changes resulting from (a) the additional thermal\nenergy consumption generated by the new piped systems, which is quite low, as all mini-AEP and  percent\nof the AEP will use solar pumping", "output": {"entities": {"named_data": [], "descriptive_data": ["thermal energy consumption of existing\nfacilities"], "vague_data": ["baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000106", "page": 60, "chunk": 1, "title": "Mauritania - Water and Sanitation Sectoral Project", "pdf_url": "http://documents1.worldbank.org/curated/en/605151585879430844/pdf/Mauritania-Water-and-Sanitation-Sectoral-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "baseline data", "label": "VAGUE_DATA", "score": 0.5516272783279419, "start": 1131, "end": 1144, "probe_score": 0.0006, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "thermal energy consumption of existing\nfacilities", "label": "DESCRIPTIVE_DATA", "score": 0.5271643996238708, "start": 1168, "end": 1217, "probe_score": 0.0005, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nSOE portfolio.\n\n\n**Component 2: Improving quality of public investment in selected sectors (US$5.5 million)**\n\n\n39. This component aims to address some key bottlenecks in the maturation, programming,\nbudgeting, and execution monitoring processes of public investment activities. MINEDUB and\nMINSANTE will be major beneficiaries of this component to be implemented under the leadership of\nMINEPAT. This component will consist of the following subcomponents:\n\n\n     - **Subcomponent 2.1: Strengthening public investment budget programming and**\n**budgeting.** The subcomponent will provide support to enhance the PIB preparation\nprocess by (a) defining and implementing public investment management, in particular\ninvestment project programming, preparation and selection (policy note/decree/order on\na new Project Investment Management (PIM) cycle <sup>26</sup> and stocktaking of existing\ninvestment projects to identify projects to be supported from appraisal to selection or to\nbe cancelled); (b) defining and establishing ICT-based solution for the management of\ninformation of public investment project preparation and piloting performance contracting\nfor the Cellules PBBS of MINEDUB and MINSANTE and for the MINEPAT/ _Direction de la_\n\n\n25 BOOST is a Bank-wide collaborative effort launched in 2010 to facilitate access to budget data and promote\neffective use for improved decision-making processes, transparency and accountability, deployed in about 40\ncountries so far. It provides user-friendly platforms where all expenditures data can be easily accessed and used by\nresearchers, government officials and citizens.\n26 Strategic guidance, programming, appraisal, project selection in program budgets preparation, implementation, and\nevaluation and audit.\n\n\nPage 22 of 93", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["budget data", "expenditures data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000044", "page": 25, "chunk": 1, "title": "Cameroon - Strengthening Public Sector Effectiveness and Statistical Capacity Project", "pdf_url": "http://documents1.worldbank.org/curated/en/305621511406035802/pdf/CAMEROON-PAD2-11012017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "budget data", "label": "VAGUE_DATA", "score": 0.548147976398468, "start": 1330, "end": 1341, "probe_score": 0.0, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "expenditures data", "label": "VAGUE_DATA", "score": 0.5902591347694397, "start": 1526, "end": 1543, "probe_score": 0.0001, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nIntegrated Cash Transfer and Human Capital Project (P166220)\n\n\n35. To support the country’s decentralization process, the project will also seek to build the institutional capacity of\nthe Ministry of Decentralization and regional councils to carry out investments in basic social services infrastructure—\nthorough community-driven investments and otherwise—with the ultimate goal of improving the quality of services to\nstrengthen human capital.\n\n\n**Component 4: Project Management (US$1.3 million)**\n\n36. The component will support activities related to project management and coordination through SEAS. The\ncomponent would finance: (i) consultant (non-civil servant) salaries; (ii) purchase of equipment and operating costs for\nproject implementation and supervision; (iii) financial management including regular internal audits and annual external\naudits; and (iv) training, workshops, knowledge-exchange and South-South learning activities, communications, and\nother events related to project implementation and supervision.\n\n**Gender**\n\n37. The project has identified a number of gender-related gaps between men and women. First, women, who are\ngenerally the primary care-givers for infants and children, lack information on beneficial practices related to child\nnutrition, parenting practices, and child stimulation. For example, the proportion of women with children less than six\nmonths of age practicing exclusive breastfeeding is among the lowest in the world, at 12 percent, due to social and\ncultural norms and lack of awareness not only about the benefits of breastfeeding but also of methods and practices that\nare critical to establishing breastfeeding over the long-term. <sup>18</sup> Second, women are disproportionately vulnerable to\npoverty and economic shocks, and face a lack of economic opportunity – for example, unemployment is higher among\nwomen (49 percent) than men (34 percent). Third, as noted in the SCD, girls are much less likely than boys to continue\ntheir education", "output": {"entities": {"named_data": ["SCD"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000063", "page": 19, "chunk": 0, "title": "Djibouti - Integrated Cash Transfer and Human Capital Project", "pdf_url": "http://documents1.worldbank.org/curated/en/419881558381476102/pdf/Djibouti-Integrated-Cash-Transfer-and-Human-Capital-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SCD", "label": "NAMED_DATA", "score": 0.8124404549598694, "start": 1950, "end": 1953, "probe_score": 0.9563, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_migrants’ transfers_, which are a capital account transfer reflecting the movement of assets by a\n\nmigrant from one country to another when he or she migrates (IMF 1993). The World Bank\n\ncombines workers’ remittances and compensation of employees together to form the remittance\n\nmeasure reported in its World Development Indicators, and this has been the definition of\n\nremittances used in a number of studies in the literature (e.g. Catrinescu et al. 2009). <sup>3</sup> [^3: There has been some debate over this definition with Barajas et al. (2009) just using workers’ remittances, and Guiliano and\nRuiz-Arranz (2009) using the sum of all three components, but then making adjustments on a country-by-country basis.]\n\n\nHowever, in practice it often proved difficult to separate transfers made by migrant workers from\n\ntheir employment income from a number of other transfers. The Balance of Payments Manual 6\n\n(BPM6) therefore replaced the category of _workers’ remittances_ with _personal transfers_ which\n\nconsist of “all current transfers in cash or in kind made or received by resident households to or\n\nfrom nonresident households” (IMF 2009, p. 20). Personal remittances in the World\n\nDevelopment Indicators (and Figure 1) are then the sum of these personal transfers and\n\ncompensation of employees.\n\n\nThe underlying data that feeds into these aggregates comes from central banks in each individual\n\ncountry. They typically require banks, money transfer operators and other institutions to provide\n\nreports on the transactions they process (Orozco 2006). However, in many cases the coverage of\n\nthis reporting has been partial. De Luna Martínez (2005) reports on a survey of central banks in\n\n40 developing countries that took place in 2004. He finds that 90 percent of the countries\n\ncollected remittance data from commercial banks, but such data were collected in only 65\n\npercent of the countries in which credit unions and exchange houses processed remittances, in\n\nonly 38 percent of the countries in which money transfer operators processed remittances, and in\n\nonly 35 percent", "output": {"entities": {"named_data": ["World Development Indicators"], "descriptive_data": ["survey of central banks"], "vague_data": ["remittance data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005974", "page": 11, "chunk": 0, "title": "wps6856", "pdf_url": "https://local/prwp/wps6856.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Development Indicators", "label": "NAMED_DATA", "score": 0.7246904373168945, "start": 305, "end": 333, "probe_score": 0.9758, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey of central banks", "label": "DESCRIPTIVE_DATA", "score": 0.8316744565963745, "start": 1676, "end": 1699, "probe_score": 0.9758, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "remittance data", "label": "VAGUE_DATA", "score": 0.6566886901855469, "start": 1806, "end": 1821, "probe_score": 0.2735, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Graph 1:** **Aluminium and Copper Prices between December 2003** - **2008**\n\n**AIwnlnum** _@mt)_ **Copper** **_(%lmt)_**\n**3m** ~. .... . . **I . .** ... ... . ... **. . I . .**,...”\n\n\n**I** %m **1,000**\n**k 4 3** **Ree-04** **DaM** **Der46** **k - 0 1** **k c 4 8** DE-^ --a( **DEM** **use-06** **b.07** **DE-**\n\nSource: Commodities Market Review, World Bank, November 2008\n\n\n\nThe construction contract for Olkaria I1 3rd Unit generating plant provides for a price\n\n\n\n13. The construction contract for Olkaria I1 3rd Unit generating plant provides for a price\nadjustment based on a set o f formulae that take into account changes in the price indices\n(from source countries) o f key inputs in proportion to their relative contribution to the total\ncost. The formulae also take into account the relative changes in the foreign exchange rates\nbetween the currency o f the country where the corresponding input is sourced and the\npayment currency. The effect o f the price adjustment may therefore be to increase or\ndecrease the cost o f the contract up to a limit o f plus or minus 15 percent o f the contract’s\nbase price. However, since many components o f this contract are already beyond the\nmanufacturing stage, the prospect for downward price adjustment i s limited. Conversely,\n\n\n\nsince most components were manufactured while high prices", "output": {"entities": {"named_data": [], "descriptive_data": ["Aluminium and Copper Prices"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018370", "page": 35, "chunk": 0, "title": "Kenya - Energy Sector Recovery Project : additional financing", "pdf_url": "https://documents.worldbank.org/curated/en/799381468048272765/pdf/472620PJPR0KE0101Official0Use0Only1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Aluminium and Copper Prices", "label": "DESCRIPTIVE_DATA", "score": 0.5064482688903809, "start": 15, "end": 42, "probe_score": 0.8793, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on social development issues"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016139", "page": 24, "chunk": 0, "title": "Kenya - Small Scale Industry Project", "pdf_url": "https://documents.worldbank.org/curated/en/649901468046861472/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on social development issues", "label": "VAGUE_DATA", "score": 0.581004798412323, "start": 1670, "end": 1703, "probe_score": 0.333, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " picking by current deterioration of economic conditions.\nIndeed, South Hebron represents one of the poorest governorates in the West Bank and suffers from the\nhighest unemployment rate. According to a census carried out by the ESIA team - about 132 waste pickers\nderive their livelihood from recycling, primarily metal, plastic and glass. Of these, about 44 pickers work full\ntime at the dump site, while the remaining joined their relatives and friends on weekends and holidays,\nespecially when schools was out for summer break. About 36 percent of the waste pickers are children under\nthe age of 16, 32 percent are youth (16-20) and the remaining are adults. Although women do not work at the\ndumpsite they play a key role separating, cleaning, and repairing the collected items for recycling.\n\nApart from Yatta, the project also seeks to rehabilitate a number of other uncontrolled dump sites. These 16\ndumpsites, a number of which already closed, are in remote locations and of a much smaller scale. Issues\nrelated to land ownership and waste pickers at these sites arise as well. The main risk arising from shutting the\nYatta dump site is therefore the loss of income for some of the poorest households in the community. In this\nparticular context compensation is understood in a broad sense and includes a number of non-monetary\nmeasures. The ARAP was prepared to this end and includes mitigation actions as follows:\n\nI. Formalize waste picking/separating through a pilot recycling plant at the landfill. This will provide\nemployment with better working conditions (minimize health hazards, reliable income, safe working\nenvironment, etc). Workers registration would be required thereby restricting child labor.\nII. Give current waste pickers preferential treatment for hiring under the formalized system. Some of the\nwaste pickers may be employed at the proposed recycling processing facility at the proposed Hebron\nWaste Transfer Station and at the Landfill facilities.\nIII. Provide appropriate training/skills development for both waste pickers and the women in", "output": {"entities": {"named_data": [], "descriptive_data": ["census carried out by the ESIA team"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000056", "page": 59, "chunk": 1, "title": "Middle East and North Africa - Output-Based Aid Pilot Solid Waste Management Project", "pdf_url": "http://documents1.worldbank.org/curated/en/388311468275943106/pdf/84657-PAD-P132268-Project-Commitment-Paper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "census carried out by the ESIA team", "label": "DESCRIPTIVE_DATA", "score": 0.8170770406723022, "start": 202, "end": 237, "probe_score": 0.0002, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "outcomes for all education and skill levels.\n\n\n_Policy recommendation for government_\n\n\n     - As part of the ongoing review of the curriculum, include learning of core skills such as\nlanguages and provide for auxiliary introduction to vocational courses in secondary school to\nease transition to vocational training for students who may not complete secondary education.\nIn addition, encourage vocational training institutions to introduce a mix of short and long-term\ncourses to meet the needs of both older students (16 years and above) who are ready to join\nthe labour market and younger students who need a combination of general schooling and\nvocational training. This way, children are not tempted and presented with perverse incentives\nto prematurely join the labour market while too young, risking exploitation and being locked in\nlow-value jobs.\n\n\n_Programmatic recommendation for UNHCR and development partners_\n\n\n     - Support government with technical assistance to revise and implement the new curriculum.\n\n     - Support refugees to undertake bridging programs including language courses and other soft\nskills needed to improve learners’ chances of being employed by others or becoming selfemployed.\n\n\n**It is essential to address risk factors at school and improve the low transition rate from primary**\n**to secondary school.** Results from the survey show that for both refuges and Ugandans, higher\neducation levels are associated with better employment outcomes. Yet secondary school completion\nrates remain low for refugees, while that for nationals is declining. The transition to secondary school is\nlimited by several main factors, including poor performance on the primary school leaving examination\ndue to inadequate exam preparation and a poor learning environment as well as splitting their time\nbetween schooling and supporting their families to earn a living and/or perform house chores. Other\nfactors driving school dropout include the inability to afford tuition and low morale when teachers hold\nback students from taking the exam so that they will not fail.\n\n\nOverall, prevention measures taken to address risk factors associated with failure at school and early\nschool dropout can have positive impacts on employment outcomes, considering the fact that", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000772", "page": 11, "chunk": 0, "title": "UNHCR Uganda - Knowledge Brief: Improving employment outcomes for refugees - July 2021", "pdf_url": "https://reliefweb.int/attachments/71676935-b98d-36fe-b2fb-455f46699475/UNHCR%20Uganda%20Knowledge%20Brief%20Jul2021.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "schooling variables, then, in absence of the unobserved component of natural ability and\n\n\nthe number of years a student has attended his or her current school, competency, θ _i,j_, can\n\n\nbe thought of as a random variable conditionally distributed on the household and\n\n\nschooling variables, gender, and grade level.\n\n\n###### (4) θ j,i | h j,i, s j,iP, s Ej f, j,i,g j,i ~ f θ( h j,i, s j,iP, s Ej f, j,i,g j,i )\n\n\n\n_j,iP_ _,_ **_s_** _Ej_ _f,_ _j,i_ _,g_ _j,i_ _~_ _f_ θ( **_h_** _j,i_ _,_ **_s_** _j,iP_\n\n\n\nθ _j,i_ _|_ **_h_** _j,i_ _,_ **_s_** _j,iP_ _,_ **_s_** _Ej_ _f,_ _j,i_ _,g_ _j,i_ _~_ _f_ θ( **_h_** _j,i_ _,_ **_s_** _j,iP_ _,_ **_s_** _Ej_ _f,_ _j,i_ _,g_\n\n\n\nIt is assumed that the conditional expected competency can be expressed as a linear\n\n\nfunction of these conditioning variables. If ξ 0, ξ 3, and ξ 4 are scalars and ξ 1 is a column\n\n\n\nmatrix with a number of elements equal to the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004381", "page": 16, "chunk": 0, "title": "wps5189", "pdf_url": "https://local/prwp/wps5189.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "DJIBOUTI\nSchool Access and Improvement Program\n\n\n**Project Appraisal Document**\n\n\nMiddle East and North Africa Region\n\nMNSHD\n\n\n\nDate: November 17, 2000 Team Leader: Qaiser M. Khan\n\n\n\nCountry Director: Inder K. Sud Sector Director: Baudouy\nProject **ID:** P044585 Sector(s): EP - Primary Education, ES - Secondary\n\n\n\n. Education\nLending Instrument: Adaptable Program Loan <sup>(APL)</sup> Theme(s): Education; Gender and development\n\n\n\nPoverty Targeted Intervention: N\n\n\n\nProgram Fin ncing Data\n\n\n\nEstimated\nAPL Indicative Financing Plan Implementation Period (Bank FY) Borrower\n\n\n\n**IBRD** Others **Total** **COMMITMENT** **Closing**\n**US$** m % US$ m US$ m Date Date\nAPL 1 10.00 75.8 3.20 13.20 03/31/2001 06/30/2005 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\n________________ Education\n\n\n\nAPL 2 10.0 65.8 5.20 15.20 07/01/2005 06/30/2008 Republic of\n\n\n\nLoan/ Credit Djibouti\n\n\n\nCredit Ministry of\n\n\n\ni_________ ________________ Education\n\n\n\nAPL 3 10.00 41.0 14.40 24.40 07/01/2008 06/30/2011 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\nEducation\n\n\n\nTotal 30.00 22.80 52.80\nProject Financing Data Credit\nFor Loans/Credits/Others: Amount (US$m): 10.0\n\n\n\nProposed Terms: Standard Credit\n\n\n\nGrace period (years): 10 Years to maturity: 40\nCommitment fee: 0.50% (0% for FY01) Service charge: 0.75", "output": {"entities": {"named_data": ["Project Financing Data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012073", "page": 4, "chunk": 0, "title": "Ethiopia - Fifth Telecommunications Project", "pdf_url": "https://documents.worldbank.org/curated/en/379241468252322923/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Project Financing Data", "label": "NAMED_DATA", "score": 0.5102046728134155, "start": 1106, "end": 1128, "probe_score": 0.1169, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "prolonged destruction and devastation caused by the civil war and prolonged conflict. The system\nfaced major bottlenecks, both technical and institutional in nature as well as large gaps and\nweaknesses in the quality of data. Even when data exists, they are not shared and are not conducive\nto policy analysis and evidence based decision making. As a result, the SMP concluded among\nother things, that there is a need to strengthen the capacities of the line ministries to provide better\ndata for informed policy on the key economic and poverty analysis issues by improving the\ninformation database and the staff analytical skills.\n\nToday, the weak statistical system continues to persist, both at the central level as well as at sector\nministries➢❨ level. The Ministry of Public Health (MoPH) is no exception. The MoPH statistical\nsystem has limited capacity to generate adequate flow of data to support decision making towards\nachieving equity and efficiency in the health sector, largely due to lack of personnel and a\nfragmented information system. As such, the MoPH is requesting Bank➢❨ s assistance to\nstrengthen the capacity of the Statistics Department (SD) by putting in place an effective and\nefficient statistical system that will foster evidence-based policy making and effective monitoring of\nthe health sector.\n\n\n**Relationship to CAS/CPS/CPF**\nData availability and access to information were identified in the 2015 SCD as foundational\nconstraints that impact evidence-based policy, and stands in the way of an informed population in\nLebanon. The SCD identifies deficiencies in the timeliness of data, its reliability due to weak overall\nstatistical capacity, and inadequate data coverage in key areas such as poverty, income distribution,\nand economic measurements. The SCD further defines data availability as one of the cross-cutting\nareas for the program.\n\nConsequently, the Lebanon CPF (FY2016-2021) recognizes the need for strengthening data\ncollection and analysis to improve the debate on policy reforms. Accordingly, the objectives of the\nCPF are underpinned by the cross-cutting theme of governance", "output": {"entities": {"named_data": [], "descriptive_data": ["information database"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000046", "page": 1, "chunk": 0, "title": "Project Information Document (Concept Stage) - Lebanon MoPH Statistical Capacity Building Project - P161766", "pdf_url": "http://documents.worldbank.org/curated/en/804431474323190796/pdf/PIDC90504.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "information database", "label": "DESCRIPTIVE_DATA", "score": 0.5553613901138306, "start": 578, "end": 598, "probe_score": 0.0057, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "sup>recently</sup> <sup>come</sup> <sup>under Government control.</sup>\n\n\n\n**2.** **Main sector** issues **and** <sup>**Government strategy:**</sup>\n\n\n\n_Sector Issues._\n_Poverty in Sierra Leone._ Sierra <sup>Leone has</sup> <sup>the lowest</sup> <sup>Human Development Index</sup> <sup>**in**</sup> <sup>the world</sup>\n\n\n\nand has a GNP per capita <sup>of only US$130</sup> <sup>compared</sup> <sup>to the average</sup> <sup>for Sub-Saharan</sup> <sup>Africa</sup> <sup>of $470.</sup>\n\n\n\nOver 82% of the population <sup>currently</sup> <sup>lives below</sup> <sup>the poverty line and life expectancy is only</sup> <sup>38 years.</sup>\n\n\n\nFertility, infant and child <sup>mortality are</sup> <sup>high</sup> <sup>and over</sup> <sup>a third</sup> <sup>of children and</sup> <sup>a fourth</sup> <sup>of adults</sup> <sup>are</sup>\n\n\n\nmalnourished. The pnmary <sup>school enrollment</s", "output": {"entities": {"named_data": ["Human Development Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011239", "page": 7, "chunk": 1, "title": "Ethiopia - Ethiopian Electric Light and Power Authority Project", "pdf_url": "https://documents.worldbank.org/curated/en/321691468034740109/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Human Development Index", "label": "NAMED_DATA", "score": 0.6837996244430542, "start": 251, "end": 274, "probe_score": 0.0779, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nRoads and Employment Project (P160223)\n\n\n12. Lebanon is primarily a mountainous country and has been recently witnessing more extreme weather\nwith shorter yet more severe winters and snow periods. MPWT has currently insufficient number of\nvehicles particularly for snow removal, and most the existing equipment is outdated with an average\nage of 20 years. MPWT has currently 60 wheel loaders, 25 snow blowers, and 7 salt spreaders and is\nhaving difficulty deploying them timely to all mountain roads and regions in Lebanon during extreme\nweather and snow events which can cover up to 70 percent of Lebanon national and local road\nnetworks during winter season. This results in some mountain villages and towns, and some primary\nroads and highways such as the Beirut‐Damascus Highway, being inaccessible for substantial periods\nof time.\n\n\n13. In addition to the purchase of vehicles, this component will assist MPWT revise its winter and snow\nemergency procedures to better plan, communicate, deploy, and respond to winter and snow\nemergencies. Given its strong linkages to the climate change agenda, this component could benefit at\nlater stages from additional support from disaster risk management and climate adaptation funds.\n\n\n**Project Component 3: Capacity Building and Implementation Support (US$7.5 million)**\n\n\n14. This component will finance consultancy services, and related software and IT equipment, to support\nthe following subcomponents:\n\n\n15. **Subcomponent 1.** Strengthen national road asset management (US$2 million). This subcomponent\nwill finance the creation of a road asset database for the trunk network in Lebanon, the collection of\nthe basic information for the database (such as road condition visual surveys, IRAP assessment of road\nsafety, and traffic counts on select road sections), and the revision of design and maintenance\nstandards to reflect changing climate conditions, particularly related to drainage and slope\nstabilization. This subcomponent will also finance the preparation of routine maintenance manual for\nsmall contractors, and", "output": {"entities": {"named_data": [], "descriptive_data": ["road asset database", "road condition visual surveys", "IRAP assessment of road\nsafety", "traffic counts"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 57, "chunk": 0, "title": "Lebanon - Roads and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/210611486651815142/pdf/Lebanon-Roads-Employment-PAD-P160223-01262017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "road asset database", "label": "DESCRIPTIVE_DATA", "score": 0.8533859252929688, "start": 1605, "end": 1624, "probe_score": 0.0216, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "road condition visual surveys", "label": "DESCRIPTIVE_DATA", "score": 0.9172765016555786, "start": 1725, "end": 1754, "probe_score": 0.5645, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "IRAP assessment of road\nsafety", "label": "DESCRIPTIVE_DATA", "score": 0.6439751386642456, "start": 1756, "end": 1786, "probe_score": 0.161, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "traffic counts", "label": "DESCRIPTIVE_DATA", "score": 0.5720629096031189, "start": 1792, "end": 1806, "probe_score": 0.3296, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " The sustainability of the sanitation measures will be carefully assessed from the point of view\nof good practices, cost effectiveness, affordability and the Djibouti water shortage environment.\n\n\n6. **Social**\n\n\n_6.1 Summarize key social issues relevant to the project objectives, and specify the project's social_\n_development outcomes._\n\n\nDjibouti is a small country and many key social issues were identified in the 1997 Poverty\n\nAssessment. The issues raised included the percentage of the population classified as poor in 1996\n(50-80% reaching the upper-bound when refugees, nomads and homeless are taken into account); large\nnumbers of refugees, nomads, and homeless populations; the majority of the poor live in urban areas\n(85%) even if the incidence of extreme poverty is overwhelmingly rural. Urban households can take\nadvantage of safety nets derived from the commodity market and services, and job opportunities are\nnot available in rural areas. The key problems faced by children include: (a) the high number of street\nchildren who have fled war ravaged Somalia and Ethiopia; (b) late entrance into school by poorer\nchildren (one out of four starts school at age 9 and leaves school at age 14); (c) health issues (diarrhea\n\nand malnutrition) are a leading cause of death for children under age 5. Other problems affecting the\nwhole population include respiratory infections on the increase (due to malnutrition); endemic health\nproblems (AIDS, tuberculosis, malaria, cholera); the widespread practice of Female Genital Mutilation\n(FGM); sanitation costs are high for poorer households not connected on the main water network as", "output": {"entities": {"named_data": ["1997 Poverty\n\nAssessment"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012423", "page": 23, "chunk": 1, "title": "Uganda - Fourth Education Project", "pdf_url": "https://documents.worldbank.org/curated/en/400811468309309803/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1997 Poverty\n\nAssessment", "label": "NAMED_DATA", "score": 0.810173511505127, "start": 420, "end": 444, "probe_score": 0.0723, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "rates, the project also displayed a large modified internal rate of return (MIRR), namely\n38 percent (see Annex 4).\n\n\nThe robustness of the results was tested at a higher social discount rate (10%), for\ndifferent estimates of program coverage, different fractions of the benefits attributable to\nthe Bank project (rather than to projects supported by partner organizations, such as\nUNICEF), as well as by providing a range for the size of the impact of different\nnutritional interventions on mortality and lifetime earnings suggested by the evidence.\nEven under the most conservative assumptions, the values for the B/C ratio and the NPV\nwere 3, and US$ 44 million, respectively (see Annex 4).\n\n\nThe ex-post overall project B/C ratio is lower than the intervention-specific B/C ratios\ncited by the PAD. <sup>14</sup> [^14: For instance, the BCR for vitamin A supplementation in Rajkumar et al. (2012) is 12.5 and that for iron\nand folate supplementation in pregnant women is 8.1.] Key contributors to the difference likely include the measurement of\nbenefits in the ex-post analysis.\n\n\nWhereas the B/C ratios cited in the ex-ante analysis are for more narrowly targeted\nnutrition-related programs, the Ethiopia Nutrition ICRR project was comprised of a\nbroader package of interventions (possibly interacting with one another), and had a strong\ncapacity building and strengthening component not present in the programs cited by the\nPAD.\n\n\nThe ex-post results may underestimate the real benefit and efficiency of the project for\nthree reasons. First, even for the baseline benefit cost analysis calculations, conservative\nassumptions were chosen when the evidence or project data presented a range. Second,\nthe analysis did not include the benefits of nutritional interventions that were likely part\nof the project, but for which sufficient information to estimate program coverage was not\navailable. The benefits of programs that provide key micronutrients such as iodine for\npregnant women and children, or zinc and iron for children under two are", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["project data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019152", "page": 40, "chunk": 0, "title": "Ethiopia - Nutrition Project", "pdf_url": "https://documents.worldbank.org/curated/en/853931468272425486/pdf/ICR000032010IC0800PUBLIC0Box391431B.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "project data", "label": "VAGUE_DATA", "score": 0.6893093585968018, "start": 1665, "end": 1677, "probe_score": 0.5609, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_</sup> <sup><u>(</u></sup> <sup>_<u>q</u>_</sup> <sup><u>)</u></sup> _≥_ _<u>π</u>_, which holds if <sup>_<u>S</u>_</sup> <sup><u>(</u></sup> <sup>_<u>q</u>_</sup> <sup><u>)</u></sup>\n\n2 2\n\n\n\n\n<sup><u>(</u></sup> <sup>_<u>q</u>_</sup> <sup><u>)</u></sup> _≥_ _π_ . For cooperation\n\n2\n\n\n\nto be achievable, the DICC of both parties must hold. Then, combining equations _DICCs_ <sup>_m_</sup>\n\n\n\nand _DICCb_ <sup>_m_</sup> we get: _<u>δ</u>_ <sup>_IA_</sup> =\n\n\n\n_c_ ( _q_ ) _−c_ ( _<u>q</u>_ <u>)+</u> _<u>u</u>_\n_V_ ( _q_ ) _−c_ ( _<u>q</u>_ <u>)</u> _−π_ <sup>.</sup> <sup>Recalling", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005670", "page": 42, "chunk": 12, "title": "wps6521", "pdf_url": "https://local/prwp/wps6521.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "also be provided to properly levy, collect and account for local duties and taxes. NaCSA staff would be\ngiven an opportunity to visit Community Driven Development Projects in comparable countries to\ncapitalize on their experiences. Regional and district line ministry staff would be trained in community\nmobilization, conflict resolution, social capital building, and technical appraisal skills.\n\n\n(b) Substantial IEEC activities linked to the various sub-projects are envisaged. These activities\nwould be undertaken using existing IEC materials endorsed by the various line ministries. For example,\nin the case of the rehabilitation of a health post, IEC messages could be envisaged to inform the\npopulation on the proper use of insecticide treated bed nets as a means of preventing malaria.\n\n\n(c) Monitoring and evaluation at the community, district, regional and central levels would be\ngiven high priority, and linked regularly and directly with NaCSA decision making on NSAP policy,\nstrategy and operational matters. These activities would be directly undertaken, or commissioned by,\nstaff of NaCSA's Planning, Monitoring and Evaluation Directorate. The Project Design Matrix (logical\nframework, Annex 1) would form the basis for monitoring NSAP outputs, outcomes and impact. An\nassessment of project status would accompany each NaCSA work program and budget submitted\nsemi-annually to the NaCSA Board. Other M&E activities would include a pre-project Social\nAssessment; establishment of NSAP baseline data (in conjunction with the collection of data for the\nCRRP Implementation Completion Report); social assessments during implementation; annual technical\naudits; beneficiary assessments; incorporation of NaCSA into GOSL's semi-annual public expenditure\ntracking surveys (PETS); and independent impact assessments.\n\n\nIn addition to conventional sub-project monitoring and evaluation (incorporated in the\nsub-project cycle as outlined in the Operations Manual), a pilot participatory monitoring and evaluation\nsystem would be introduced in a representative sample of the predominant types of CDP sub-projects.\nBeneficiary communities would identify quantitative and qualitative indicators", "output": {"entities": {"named_data": [], "descriptive_data": ["NSAP baseline data", "public expenditure\ntracking surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020455", "page": 36, "chunk": 0, "title": "Ethiopia - Fifth Telecommunications Project", "pdf_url": "https://documents.worldbank.org/curated/en/942071468275712137/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NSAP baseline data", "label": "DESCRIPTIVE_DATA", "score": 0.5252031087875366, "start": 1493, "end": 1511, "probe_score": 0.1181, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "public expenditure\ntracking surveys", "label": "DESCRIPTIVE_DATA", "score": 0.7033143043518066, "start": 1743, "end": 1778, "probe_score": 0.481, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "-19 shocks than their Ugandan\ncounterparts and have been slower to recover. <sup>8</sup> Female refugees were more likely to stop working following COVID-19\nlockdowns than Ugandan nationals or male refugees. While there was no difference based on gender, refugee businesses\nwere less likely to continue operating after COVID-19 shocks than those of Ugandan nationals. Compared to less than a\nquarter of Ugandan households, at least half of refugee households borrowed money to cope with the impacts of the\nCOVID-19 emergency. Preliminary evidence suggests that many refugees in urban areas moved to rural areas during\nlockdown and the subsequent months, due to difficulties of paying rent with reduced income. Under these intense\npressures, refugees are ten times more likely to suffer from depression. <sup>9</sup>\n\n\n**B. Sectoral and Institutional Context**\n\n\n7. **Uganda has the highest proportion of women’s business ownership in the Africa region.** The 2020 Mastercard\nGlobal Index of Women Entrepreneurs estimated that women own nearly 40 percent of all businesses. <sup>10</sup> Earlier surveys\nhave presented more varied estimates, suggesting female-owned enterprises make up between 23–44 percent of all\nbusinesses. <sup>11</sup> MSMEs are critical to the economic growth. They employ nearly 2.5 million people, 90 percent of all private\nsector employees, produce 80 percent of manufactured products, and generate 20 percent of GDP. <sup>12</sup>\n\n8. **Yet most women-led firms never grow past the micro level, while male-owned firms are twice as likely to move**\n**from micro to small size** . Estimates from various surveys suggest that 80–94 percent of all women-owned firms in Uganda\n\n\n5 United Nations High Commissioner for Refugees (UNHCR) and the Office of", "output": {"entities": {"named_data": ["2020 Mastercard\nGlobal Index of Women Entrepreneurs"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 12, "chunk": 1, "title": "Uganda - Generating Growth Opportunities and Productivity for Women Enterprises Uganda Project", "pdf_url": "http://documents.worldbank.org/curated/en/527091655323259747/pdf/Uganda-Generating-Growth-Opportunities-and-Productivity-for-Women-Enterprises-Uganda-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2020 Mastercard\nGlobal Index of Women Entrepreneurs", "label": "NAMED_DATA", "score": 0.8029432892799377, "start": 959, "end": 1010, "probe_score": 0.998, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nBuilding Resilient and Responsive Health Systems (P179698)\n\n\n**Monitoring & Evaluation Plan: PDO Indicators by PDO Outcomes**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Outcome 1: Improve utilization of quality primary health care services|Col2|\n|---|---|\n|**Percentage of women receiving postnatal care within 48 hours (Percentage)  **|**Percentage of women receiving postnatal care within 48 hours (Percentage)  **|\n|Description <br>|Numerator: Number of women receiving postnatal care after delivery within 48 hours.<br>Denominator: Total number of expected live births during the reporting period <br>|\n|Frequency <br>|<br> Every six months <br>|\n|Data source <br>|KHIS|\n|Methodology for Data<br>Collection <br>|Routine Health Management Information System  (HMIS) data collection|\n|Responsibility for Data<br>Collection <br>|MoH <br>|\n|**Percentage of women receiving postnatal care within 48 hours in the 10 selected counties (Percentage)  **|**Percentage of women receiving postnatal care within 48 hours in the 10 selected counties (Percentage)  **|\n|Description <br>|<br>Numerator: Number of women, in the 10 selected counties, receiving postnatal care after delivery within 48 hours.<br>Denominator: Total number of expected live births, in the 10 selected counties, during the reporting period <br>|\n|Frequency <br>|Every six months <br>|\n|Data source <br>|KHIS|\n|Methodology for Data<br>Collection <br>|Routine  HMIS data collection|\n|Responsibility for Data<br>Collection <br>|MoH <br>", "output": {"entities": {"named_data": ["KHIS", "KHIS"], "descriptive_data": ["Routine  HMIS data collection"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000000", "page": 35, "chunk": 0, "title": "Kenya - Building Resilient and Responsive Health Systems Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099022324094562763/pdf/BOSIB1554c314c0a2187c019d7e85bc2a91.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "KHIS", "label": "NAMED_DATA", "score": 0.711502194404602, "start": 678, "end": 682, "probe_score": 0.1122, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "KHIS", "label": "NAMED_DATA", "score": 0.5985647439956665, "start": 1377, "end": 1381, "probe_score": 0.9699, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Routine  HMIS data collection", "label": "DESCRIPTIVE_DATA", "score": 0.5344026684761047, "start": 1424, "end": 1453, "probe_score": 0.3479, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "ر\n\n.المتوقع للمشروع\n\n\nج) إيجاد أساس لتقييم المشروع فيما يتعلق بتحقيق الهدف التنموي ا .إلجمالي\n\n\nد) إقامة شراكات عمل مع مراكز الرعاية الصحية األولية، مكتب رئيس الوزراء المسؤول عن البرنامج الوطني الستهداف\nاألسر األكثر فقراً، المستشفيات (دائرة العيادات الخارجية) بغرض جمع و/أو الوصول إلى البيانات ذات الصلة\n\nلستفادة المثلى من مخرجات الم تابعة والتقييم لكل مكون ومكون فرعي بموجب خطة متكاملة للمتابعة **ا** لتحقيق\n\n.والتقييم\n\n\nهـ) تنظيم جمع البيانات من عدة أطراف معنية وتيسير التحقق والتحليل للبيانات/المعلومات المستلمة من مختلف األطراف\n\n.المعنية\n\n\nو) التواصل مع الجهات المنفذة والشركاء الضروريين لتنفيذ األنشط ة الفنية الرئيسية (مسح المرافق، تقييمات\n\n).المستفيدين،...الخ\n\n\n.ز) إصدار تقارير", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000135", "page": 50, "chunk": 2, "title": "Lebanon - Emergency Primary Healthcare Restoration Project", "pdf_url": "http://documents1.worldbank.org/curated/en/797281467998531842/pdf/PAD1205-ARABIC-PAD-PP152646-PUBLIC-Box393206B.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " which 80% was\nused for productive purposes. The nonproductive items were primarily food, transport, and housing\nrent, which were not considered to be developmental uses but are essential for households who do not\nhave a permanent place to live.\n\n**Subcomponent 1: Rehabilitation of Community Infrastructure**\n**(funded through an ongoing Ethiopian Social Rehabilitation and Development Fund Project)**\n\nThe major objective of this subcomponent was to rehabilitate, reconstruct, equip, and furnish the\ndamaged or destroyed social infrastructure at the community level and resume the delivery of basic\nservices. Activities under this component were designed to rapidly rehabilitate and reconstruct\ndestroyed and damaged community infrastructure in the education, health, and water supply sectors\n\n\n38", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020767", "page": 47, "chunk": 2, "title": "Ethiopia - Emergency Recovery Project", "pdf_url": "https://documents.worldbank.org/curated/en/962071468774678728/pdf/ICR350.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". This suggests that FDI is more likely to flow into high risk countries—\nparticularly those with large economies—than PPI. The role of extractive industries and the\nrelative value of tradable investments may explain the lower sensitivity of FDI to sovereign risk\nthan that of PPI.\n\n\nFor conflict-affected countries, data on numbers of PPI transactions successfully transacted\nwithin nine years of a conflict ending illustrate how difficult it is for these countries to attract\nprivate infrastructure investments of any form. Very few investments took place in the first five\nyears after conflict ended, and nearly all of those investments were in the telecommunications\nsector—primarily in mobile telephony. Energy investments took six or seven years to mobilize\nand came primarily in electricity generation—investments that are often characterized by\nsovereign-backed power purchase agreements, dollar denominated transfers and an asset\nfootprint that is much easier to protect from attack than a distribution network.\n\n\n20", "output": {"entities": {"named_data": [], "descriptive_data": ["data on numbers of PPI transactions"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005706", "page": 21, "chunk": 1, "title": "wps6569", "pdf_url": "https://local/prwp/wps6569.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on numbers of PPI transactions", "label": "DESCRIPTIVE_DATA", "score": 0.8591623902320862, "start": 317, "end": 352, "probe_score": 0.7553, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Public Disclosure Copy\n\n\n**The World Bank** Implementation Status & Results Report\nKenya: Adaptation to Climate Change in Arid and Semi-Arid Lands (KACCAL) (P091979)\n\n\n**Global Environmental Objective Indicators**\n\n\nPHINDGEOTBL\n\n Number of District management plans with concrete climate risk management activities reflected in the budget(Number,\nCustom)\n\n\nBaseline Actual (Previous) Actual (Current) End Target\n\n\nValue\n0.00 0.00 0.00 4.00\n\n\nDate\n30-Jun-2012 31-Mar-2013 12-May-2015 31-Oct-2016\n\n\nPHINDGEOTBL\n\n\n Percentage of Community adaptation projects rated satisfactory or better by participating communities(Percentage, Custom)\n\n\nBaseline Actual (Previous) Actual (Current) End Target\n\n\nValue\n0.00 0.00 0.00 75.00\n\n\nDate\n30-Jun-2012 31-Mar-2013 12-May-2015 31-Oct-2016\n\n\nOverall Comments\n\n\n**Intermediate Results Indicators**\n\n\nPHINDIRITBL\n\n\n Climate risk profiles developed and used for district management plans (Number, Custom)\n\n\nBaseline Actual (Previous) Actual (Current) End Target\n\n\nValue 0.00 0.00 0.00 4.00\n\n\nDate 30-Jun-2012 31-Mar-2013 12-May-2015 31-Oct-2016\n\n\nPHINDIRITBL\n\n\n Methodology and tool for screening agricultural investment programs for climate risk developed (Number, Custom)\n\n\nBaseline Actual (Previous) Actual (Current) End Target\n\n\nValue 0.00 0.00 0.00 1.00\n\n\nDate 30-Jun-2012 31-Mar-2013 12-May-2015 31-Oct-2016", "output": {"entities": {"named_data": ["Global Environmental Objective Indicators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014628", "page": 3, "chunk": 0, "title": "Kenya - Kenya: Adaptation to Climate Change in Arid and Semi-Arid Lands (KACCAL) : P091979 - Implementation Status Results Report : Sequence 07", "pdf_url": "https://documents.worldbank.org/curated/en/549791468253782097/pdf/ISR-Disclosable-P091979-06-25-2015-1435234132122.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Global Environmental Objective Indicators", "label": "NAMED_DATA", "score": 0.5225445032119751, "start": 170, "end": 211, "probe_score": 0.4871, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*|**20.375.000**<br>** 288.100**<br>** 3.862.100 24.525.200**|**   20.886.800**<br>** 441.100**<br>** 4.406.400 25.734.700**|**1.209.500 5%**|\n\n\n\n**Estimación de la composición**\n**demográfica de las personas**\n**desplazadas a través de**\n**las fronteras**\n\n\nAl final de cada año, ACNUR compila los datos\nglobales sobre la distribución combinada por sexo y\nedad de las poblaciones de interés bajo su mandato.\nLa disponibilidad de los datos demográficos varía en\ngran medida según el grupo de población y el país\nde asilo. Por ejemplo, a fines de 2021, se dispone\nde datos demográficos por edad y sexo del 84% de\n\n\n\nlas personas refugiadas y del 42% de las personas\nvenezolanas desplazadas en el extranjero.\n\n\nEs posible utilizar modelos estadísticos para\ndeterminar la distribución por sexo y edad de los\ndatos demográficos faltantes de estas poblaciones,\nlo que ayuda a subsanar estos vacíos de información\ncon estimaciones. <sup>**41**</sup> Mediante este enfoque, se estima\nque el 42% de todas las personas refugiadas y\nvenezolanas desplazadas en el extranjero a fines de\n2021 eran niñas y niños. Esto varía según la región", "output": {"entities": {"named_data": [], "descriptive_data": ["datos demográficos por edad y sexo"], "vague_data": ["datos\nglobales"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000438", "page": 14, "chunk": 3, "title": "Tendencias Globales Desplazamiento Forzado en 2021", "pdf_url": "https://reliefweb.int/attachments/3d95f2e6-bff0-42bb-be25-6e0ab366bfb0/SP.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "datos\nglobales", "label": "VAGUE_DATA", "score": 0.6853201985359192, "start": 299, "end": 313, "probe_score": 0.2071, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "datos demográficos por edad y sexo", "label": "DESCRIPTIVE_DATA", "score": 0.7935205698013306, "start": 566, "end": 600, "probe_score": 0.0538, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "output": {"entities": {"named_data": [], "descriptive_data": ["random survey"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000097", "page": 16, "chunk": 0, "title": "West Bank and Gaza - Second Community Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/573471468763473544/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7714613080024719, "start": 379, "end": 395, "probe_score": 0.582, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "random survey", "label": "DESCRIPTIVE_DATA", "score": 0.7173007130622864, "start": 1487, "end": 1500, "probe_score": 0.012, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "#### **MONITORING, EVALUATION AND LEARNING**\n\n\n\nUNHCR and WFP will monitor global progress on\nthe implementation of this Joint Strategy. Within\n4-6 years of the start of the implementation of this\nStrategy, an evaluation of its results will be commissioned by the evaluation mechanisms of WFP and\nUNHCR jointly. The Joint Strategy will be evaluated\non the extent to which it has contributed to a sustained improvement in refugees’ ability to meet their\n#### **PARTNERSHIPS**\n\nIn order to deliver this Joint Strategy, UNHCR and\nWFP will work in partnership with a wide range of\ndifferent stakeholders including but not limited to: refugees; host communities; governments of countries\nof asylum; humanitarian and development donors;\nwider UNCTs; academic and research institutions;\n#### **ASSUMPTIONS**\n\nThe success of the Joint Strategy rests on three\nover-arching assumptions:\n\n\n- **●** **Sufficient commitment from the governments of**\n**countries of asylum:** Host governments need to\nsupport the focus on self-reliance and engage in\nconstructive policy dialogue on adapting legal and\npolicy frameworks to allow for greater opportunities for refugees.\n\n\n- **●** **Adequate investment and flexibility from donors:**\nThe promotion of self-reliance will require a\nsignificant, upfront investment that is sustained\nfor a number of years. This will imply working\nacross the humanitarian-development nexus, and\ntherefore ensuring that the donor community\nprovides States, UNHCR and WFP with adequate,\n\n###### **LIST OF KEY ACRONYMS**\n\n\n**FAO** Food and Agricultural Organization of the\nUnited Nations\n**ILO** International Labour Organization\n**JAM** Joint Assessment Missions\n**JPA** Joint Plan of Action\n**MOU** Memorandum of Understanding\n**NGO** Non-Governmental Organization\n**UN**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001061", "page": 13, "chunk": 0, "title": "WFP-UNHCR Joint Strategy on Enhancing Self-Reliance in Food Security and Nutrition in Protracted Refugee Situations", "pdf_url": "https://reliefweb.int/attachments/a126d334-754c-334f-bb65-9edf236d507e/77843.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n\n\n**<u>ACCOMMODATION QUALITY BY POVERTY GROUP</u>**\n\n\nIncome above the poverty line Income below the poverty line\n\n\n\n**<u>LIVING CONDITIONS BY POVERTY GROUP</u>**\n\n\nIncome above the poverty line Income below the poverty line\n\n\n\nwalking in\nneighbourhood\n\n\n\nNot reporting\n\nfeeling safe\n\n\n\nUnable to\nstore or cook\n\nfood\n\n\n\nInsufficient\n\nprivacy\n\n\n\nLacking\nseparate\nshowers or\n\ntoilets\n\n\n\nleave\naccommodation\n\n\n\nFeeling under\n\n\n\npressure to\n\n\n\nLiving in\ncollective\n\nhousing\n\n\n\nafter dark\n\n\n\nSource: Survey data, SAG estimates\n\n\n**<u>POVERTY EFFECTS ON HEALTHCARE ACCESS</u>**\n\n\nIncome above the poverty line Income below the poverty line\n\n\n\nSource: Survey data, SAG estimates\n\n\n**<u>FOOD COPING STRATEGY OVER LAST 7 DAYS BY POVERTY</u>**\n**GROUP**\n\n\nIncome above the poverty line Income below the poverty line\n\n\n\n\n\n\n\nHad to reduce\n\nessential\n\nhealth\nexpenditures\nin last 30 days\n\n\n\nUnable to\nobtain needed\n\nhealthcare in\n\n\n\ndays\n\n\n\nCould not\nafford hospital\n\nor clinic fee in\n\nlast 30 days\n\n\n\nessential\n\n\n\nthe last 30\n\n\n\nHad to skip a\n\nmeal\n\n\n\nAdults had to\n\n\n\neat less to\nfeed small\n\n\n\nHad to borrow\n\n\n\nmoney for\n\n\n\n(including\n\n\n\nfood\n\n\n\ndrugs)\n\n\n\nchildren\n\n\n\nNote: Percentages of those that could not afford clinic fees are as\nshare of those not able to access healthcare in the last 30 days\n\n\nSource: Survey data, SAG estimates\n\n\n\nSource: Survey data, SAG estimates\n\n\n\n**Employment remains closely associated with significantly lower poverty rates, but size of**\n**employment income is key**\n\n\nJust like in the case of 2023 data, the current survey round suggests a strong link between employment and\npoverty. Whereas for individuals living in households with no one employed the poverty rate stands at a\nstaggering 62%, it drops to 10% for those with at least one person working. That", "output": {"entities": {"named_data": [], "descriptive_data": ["Survey data"], "vague_data": ["2023 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 7, "chunk": 0, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Survey data", "label": "DESCRIPTIVE_DATA", "score": 0.5389323830604553, "start": 602, "end": 613, "probe_score": 0.9939, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2023 data", "label": "VAGUE_DATA", "score": 0.6245505213737488, "start": 1625, "end": 1634, "probe_score": 0.9751, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Annex 1:** **Project** **Design** **Summary**\n\n**SIERRA LEONE:** **NATIONAL** **SOCIAL ACTION** **PROJECT**\n\n\n. **Hierarchy o.Qbijctives -'**  - . **diator** **r**, t **,P** **jCitidaI** **r!** **As's-umptIons,Y-**\n**Sector-related** **CAS** **Goal:** **Sector** **Indicators:** **Sector/ country reports:** **(from** **Goal** **to Bank** **Mission)**\nMitigate the risk of renewed 1. National conflict/security- - UNHCR/OCHA reports - Continued peace and\n**conflict** **and lay foundation** related indicators - Household Income and regional security\n**for** **poverty reduction and** 2. Inter-regional disparities in Expenditure Surveys - Economic and political\n**improvements** **in nutrition,** I-PRSP & PRSP core - PETS surveys stability\n**health, education** **and** indicators - Strategic Planning and\n**targeting** **the rural** 3. Inter-regional disparities in Action Process (SPP) reports\n**population,** women **and** Popular Benchmarks\n**children.**\n\n\n**Project** **Development** **Outcome** **/** **Impact** **Project reports:** **(from** *", "output": {"entities": {"named_data": ["Inter-regional disparities in Expenditure Surveys", "PETS surveys"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000151", "page": 29, "chunk": 0, "title": "Bosnia and Herzegovina - Third Electric Power Reconstruction Project", "pdf_url": "http://documents1.worldbank.org/curated/en/873371468767980151/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Inter-regional disparities in Expenditure Surveys", "label": "NAMED_DATA", "score": 0.5622888207435608, "start": 590, "end": 639, "probe_score": 0.0005, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PETS surveys", "label": "NAMED_DATA", "score": 0.6322475075721741, "start": 721, "end": 733, "probe_score": 0.0465, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " C. Lundblad (2017) “Taper Tantrums: QE, Its Aftermath, and\n\nEmerging Market Capital Flows.” NBER Working Paper No. 23474.\nChui, M., I. Fender, and V. Sushko (2014). “Risks Related to EME Corporate Balance Sheets:\n\nThe Role of Leverage and Currency Mismatch.” BIS Quarterly Review September\n2014, Bank for International Settlements.\nClaessens, S., H. Tong, and S.-J. Wei (2012). “From the Financial Crisis to the Real Economy:\n\nUsing Firm-level Data to Identify Transmission Channels.” _Journal of International_\n_Economics_ 88 (2), 375-387.\nClaessens, S. and S. Schmukler (2007). “International Financial Integration through Equity\n\nMarkets: Which Firms from which Countries Go Global?” _Journal of International Money_\n_and Finance_ 26 (5), 788-813.\nde la Torre, A., M.S. Martinez Peria, and S. Schmukler (2010). “Bank Involvement with SMEs:\n\nBeyond Relationship Lending.” _Journal of Banking and Finance_ 34 (9), 2280-2293.\nDidier, T., R. Levine, and S. Schmukler (2015). “Capital Market Financing, Firm Growth, Firm\n\nSize Distribution.” NBER Working Paper 20336 and World Bank Policy Research\nPaper 7353.\n\n\n32", "output": {"entities": {"named_data": [], "descriptive_data": ["Firm-level Data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007344", "page": 34, "chunk": 2, "title": "wps8405", "pdf_url": "https://local/prwp/wps8405.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Firm-level Data", "label": "DESCRIPTIVE_DATA", "score": 0.5585487484931946, "start": 434, "end": 449, "probe_score": 0.053, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nPromoting Financial Inclusion Policies and Regulations in Jordan ( P163719 )\n\n\nBank Universal Financial Access (UFA) data portal estimates that 0.8 million adults can be reached by the\ncountry opportunity of drafting and implementing the NFIS[1]. Affordable access to and use of financial\nservices helps young, women and small business owners (including those in the remote areas) generate\nincome, manage irregular cash flow, invest in opportunities, strengthen resilience to downturns, and work\ntheir way out of poverty.\n\n   - **The Project’s objective is aligned with the World Bank’s Twin Goals and global initiative to provide universal**\n\n**financial access around the world by 2020.** Financial inclusion - access and usage of quality financial services,\nincluding credit, savings, payments and insurance - is an enabler and a catalyst for achieving the Bank Group's\ngoals of ending extreme poverty by 2030 and boosting shared prosperity for the bottom 40 percent of the\npopulation in all developing countries.\n\n\n[1] http://ufa.worldbank.org/country-progress/jordan\n\n\n**C. Project Development Objective(s)**\nProposed Development Objective(s)\nThe project development objective is to support the implementation of the National Financial Inclusion Strategy (NFIS)\nin Jordan.\n\n\nKey Results\n\n   - Progress towards achieving the project’s objectives will be measured by a series of quantitative and qualitative\n\nindicators at the PDO level and at the intermediate level.\n\n   - The Financial Inclusion Monitoring and Evaluation (M&E) framework that will be developed under Component\n\n1, will include relevant NFIS indicators[1] and will track the implementation of NFIS and monitor progress and\nimpact. The framework will be segmented by intermediate outcomes, outcomes and national headline\nprogress. These indicators are meant to measure national progress, which has contributing factors beyond the\nscope of this project. Thus, this project will _only_ track national financial inclusion progress and will", "output": {"entities": {"named_data": ["Bank Universal Financial Access (UFA) data portal"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000013", "page": 5, "chunk": 0, "title": "Jordan - Promoting Financial Inclusion Policies and Regulations in Jordan Project : Project Information Document (Concept Stage) - Promoting Financial Inclusion Policies and Regulations in Jordan - P163719", "pdf_url": "http://documents.worldbank.org/curated/en/280421491408992654/pdf/IL-AISPID-CP-P163719-04-05-2017-1491408966691.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Bank Universal Financial Access (UFA) data portal", "label": "NAMED_DATA", "score": 0.531749963760376, "start": 98, "end": 147, "probe_score": 0.2098, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018213", "page": 19, "chunk": 1, "title": "Kenya - Smallholder Agricultural Credit Project", "pdf_url": "https://documents.worldbank.org/curated/en/789431468272713668/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7292463183403015, "start": 272, "end": 283, "probe_score": 0.8771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " million. Given the ongoing conflicts in Iraq and\nSyria, however, it is likely that these numbers will\nchange for reporting on the full year.\n\n\n**14** The Internal Displacement Monitoring Centre estimated the global\nnumber of persons displaced by armed conflict, generalized violence,\nor human rights violations at the end of 2015 to be some 40.8 million.\n\n**15** As in Myanmar (35,000), Nigeria (20,500), South Sudan (105,000),\nand Ukraine (800,000).\n\n**16** The large number of registered IDPs in Colombia comes from\nthe total cumulative figure from the Victims’ Registry which\ncommenced in 1985\n\n\n\n20 u n h c r > **m i d - y e a r t r e n d s** **2 0 1 6**", "output": {"entities": {"named_data": ["Victims’ Registry"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001232", "page": 19, "chunk": 1, "title": "UNHCR Mid-Year Trends 2016", "pdf_url": "https://reliefweb.int/attachments/bd4cde9b-006d-3a90-9480-0feece6c9207/58aa8f247.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Victims’ Registry", "label": "NAMED_DATA", "score": 0.8589398860931396, "start": 556, "end": 573, "probe_score": 0.9935, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "3\n\n\n**2. Project development objective** (see Annex 1)\n\nThe objective of the project is to enhance the quality of education and to increase enrollment in\nprimary schools.\n\n\n**3. Key performance indicators:** (see Annex 1)\n\nThe key performance indicator is an increased number of students enrolled in grades 1-9, especially\namong girls.\n\n\nB. **STRATEGIC CONTEXT**\n\n\n**1. Sector-related Country Assistance Strategy (CAS) goal supported by the project** (see Annex 1)\n\n\n**Document number:** P 7403 DJI **Date of latest CAS discussion:** (scheduled for) 12/19/00\n\nThe CAS has been prepared in the context of the country's economic difficulties and deepening\npoverty. Despite Djibouti's relatively high nominal per capita income (US$790 versus an average of\nUS$510 for Sub-Saharan Africa, and US$100 for Ethiopia), Djibouti has one of the poorest social\nindicators in the world (poverty, illiteracy, maternal and infant mortality, and morbidity), according to\nthe UNDP Human Development Index, ranking 157th among 174 countries.\n\n\nThe Republic of Djibouti has very few natural resources and the economy is mainly dependent on the\nport, external financial assistance, the French military and associated services. However, with the\n\ndecreased amount of external assistance, and deepening structural problems, the country has suffered\neconomic stagnation over the past decade and a half. As a result, per capita Gross Domestic Product\n(GDP) declined by 50% in real terms since 1985. The switch of Ethiopia's transit traffic from Assab in\nEritrea to Djibouti in mid-1998 and the consequent four-fold increase in port traffic has opened new,\nas yet not fully exploited, opportunities for investment and growth. Djibouti's open economic policies\nand relative stability, characterized by a liberal trade policy and exchange system, which operates free\n\nof capital or", "output": {"entities": {"named_data": ["UNDP Human Development Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000147", "page": 6, "chunk": 0, "title": "Rwanda - Human Resources Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/837731468759911848/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNDP Human Development Index", "label": "NAMED_DATA", "score": 0.8519672155380249, "start": 959, "end": 987, "probe_score": 0.9988, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nKhyber Pakhtunkhwa Human Capital Investment Project (P166309)\n\n\nprovided by the E&SED itself through its existing unit for such initiatives. For Girls Community Schools,\nimplementation at the district level will be carried out by the Elementary and Secondary Education\nFoundation. For all other interventions, the DEOs will lead implementation. In the health sector, the\nDistrict Health Officers (DHOs) will be the implementation lead for all activities. District level oversight\nwill be provided by Deputy Commissioners (DCs). Being the government lead in the district for primary\nhealthcare, the DHO will be well placed to both drive implementation and ensure effective coordination\nwith the department of health and the PMU.\n\n\n**B. Results Monitoring and Evaluation Arrangements**\n\n\n59. **A detailed M&E framework has been prepared for the project.** It builds upon the results chain\nin Figure 1 in this document and includes indicators which are currently used by both Department of\nHealth and the E&SED. Specific indicators were included to consider interventions targeting girls. In order\nto provide additional information on the impact of project interventions on targeted population, social\nassessments will be incorporated in the overall monitoring of the project. Any data on refugees will be\ncollected through specialized surveys that will be conducted by entities with prior experience soliciting\ninformation from vulnerable groups with regard to project activities and will be coordinated with the\nCommissioner for Afghan Refugees and UNHCR. <sup>27</sup> [^27: Preliminary discussions have been held with the KP and Islamabad-based teams of the UNHCR to gauge the possibility that\nthey would be involved in this aspect of monitoring for the project.]\n\n\n**C. Sustainability**\n\n\n60. **The GoKP owns the project and the interventions support the implementation of the education**\n**and health blueprints for the province.** The project responds to the needs of the GoKP to deliver quality\neducation and health services to the province’s population including refugees. The project complements", "output": {"entities": {"named_data": [], "descriptive_data": ["specialized surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000126", "page": 27, "chunk": 0, "title": "Pakistan - Khyber Pakhtunkhwa Human Capital Investment Project", "pdf_url": "http://documents1.worldbank.org/curated/en/730431593223315167/pdf/Pakistan-Khyber-Pakhtunkhwa-Human-Capital-Investment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "specialized surveys", "label": "DESCRIPTIVE_DATA", "score": 0.7845326662063599, "start": 1340, "end": 1359, "probe_score": 0.1315, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSPF: Improved Livelihoods for Internally Displaced Persons in Azerbaijan (P178125)\n\n\nwill recruit an environmental and social specialist for the purposes of the project and all PIU and\nfield staff will undergo training on relevant aspects of the ESF at project initiation.\n\n34. **The SCRI team has not yet implemented projects under the World Bank’s new**\n**procurement framework.** The team will be supported with training and assistance from WB\nprocurement staff in the implementation of the project procurement strategy for development\n(PPSD) which was developed during project preparation.\n\n\n**B. Results Monitoring and Evaluation**\n\n\n35. **The PIU within SCRI will be responsible for monitoring and evaluating the outcomes of**\n**the project** **against agreed indicators as set out in the Results Framework.** A consultant will be\nhired as an M&E Specialist to undertake and coordinate this work and to report on results\nindicators. The M&E Specialist will collect baseline data, which will enable the Committee to\ncompare the before and after situation for project participants. Data after training program\ncompletion will be collected by the M&E Specialist and if additional data collection support is\nneeded, SCRI will engage the staff of its Monitoring Department and the M&E Specialist will\nprovide staff with the needed training and quality assurance supervision. Participants in civic\nengagement and social cohesion training will be tested on their knowledge and tracked to assess\nwhether they are more active in their communities as a result of the training. Special emphasis\nwill be placed on assessing the difference in project benefits between male and female\nparticipants and for persons with disabilities. The PIU will prepare semi-annual reports to provide\na summary of implementation progress on project activities and cross-cutting functions (FM,\nProcurement, and Environmental and Social Risk Management) of the project.\n\n36. **Baseline data that is collected on income and", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000007", "page": 19, "chunk": 0, "title": "Azerbaijan - State and Peacebuilding Fund (SPF) : Improved Livelihoods for Internally Displaced Persons in Azerbaijan Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099730012222232813/pdf/P1781250bdd2b50b0b9720d5c17632331c.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "baseline data", "label": "VAGUE_DATA", "score": 0.6666433811187744, "start": 990, "end": 1003, "probe_score": 0.0568, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "##### RESEARCH\n#### QUESTION 1.\n\n\n#### What are the THE EVIDENCE PRESENTED IN THIS REPORT CONFIRMS THAT CHILD PROTECTION CONCERNS\n\nIN EMERGENCY CONTEXTS PRESENT SERIOUS THREATS TO LIFE AND WELLBEING.\n\nThis report presents quantitative and qualitative data on the threats, scale, scope and variation in child protection concerns. This is\n#### serious threats followed by information on which children are most vulnerable to each specific threat, acknowledging that risks are not evenly distributed.\n\nGender, disability, location, socioeconomic status and other factors are often predictors of the kind of risks children will face during and\nafter emergencies. Further, the report describes the urgency of the response and specifies actions that should be taken.\n#### to life and\n\nFindings on the threats to life and wellbeing resulting from each form of violence against children clarify the role child protection actors\nplay in ensuring the humanitarian system meets its overall goals. <sup>29</sup> Evidence presented underscores the essential role of child protection\nas stand-alone sector and the importance of tailored interventions to prevent and respond to the risks faced by children.\n#### wellbeing that\n\n\nn n The nature and scale of the threat;n\n#### child protection\n\nn n Who the most vulnerable children are;n\n\n\nn n The urgency of response and suggested actions.\n#### interventions\n\nThe research presented here focuses on child protection concerns posing an immediate threat to life and wellbeing.\n#### can address? Not all the negative outcomes of the various needs are immediately life-threatening, but many have a significant and detrimental long\n\n\nThis report presents quantitative and qualitative data on the threats, scale, scope and variation in child protection concerns. This is\nfollowed by information on which children are most vulnerable to each specific threat, acknowledging that risks are not evenly distributed.\nGender, disability, location, socioeconomic status and other factors are often predictors of the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["quantitative and qualitative data", "quantitative and qualitative data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001360", "page": 10, "chunk": 0, "title": "A matter of Life and Death: Child Protection programming’s essential role in ensuring child wellbeing and survival during and after emergencies", "pdf_url": "https://reliefweb.int/attachments/d2c273e6-b3b1-323b-b226-b51d7ed0be12/A_Matter_of_life_and_death_LowRes.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "quantitative and qualitative data", "label": "VAGUE_DATA", "score": 0.6681249737739563, "start": 222, "end": 255, "probe_score": 0.9412, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "quantitative and qualitative data", "label": "VAGUE_DATA", "score": 0.6304172277450562, "start": 1684, "end": 1717, "probe_score": 0.9596, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nAgricultural Employment Support for Refugees and Turkish Citizens through Enhanced Market Linkages (P171543)\n\n\n|Indicator Name|PBC|Baseline|End Target|\n|---|---|---|---|\n|(soft/life skills) training (Number)<br>||||\n\n\n\n\n\n\n\n|RESULT_FRAME_TBL_IO|Col2|Col3|Col4|\n|---|---|---|---|\n|<br> <br>**Indicator Name**<br>|<br>**PBC**<br>|<br>**Baseline**|<br>**End Target**|\n|**Enhancing employment opportunities through contract farming**|**Enhancing employment opportunities through contract farming**|**Enhancing employment opportunities through contract farming**|**Enhancing employment opportunities through contract farming**|\n|Number of employers receiving formalization support (Number)||0.00|3,000.00|\n|Contracts signed with formal employment support condition<br>(Number)||0.00|5,000.00|\n|Standard contracts developed in line with international best<br>practices (Text)||Contracts are including basic articles|Standard contracts developed in line with international<br>best practices|\n|Number of trainings delivered (Number)||0.00|1,370.00|\n|Agriculture employment database established (Text)||No system|System functional|\n|Number of workers registered in the employment database<br>(Number)||0.00|30,000.00|\n|Number of employers formalized (Number)||0.00|500.", "output": {"entities": {"named_data": ["Agriculture employment database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000114", "page": 46, "chunk": 0, "title": "Turkey - Agricultural Employment Support for Refugees and Turkish Citizens through Enhanced Market Linkages Project", "pdf_url": "http://documents1.worldbank.org/curated/en/671481617301015363/pdf/Turkey-Agricultural-Employment-Support-for-Refugees-and-Turkish-Citizens-through-Enhanced-Market-Linkages-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Agriculture employment database", "label": "NAMED_DATA", "score": 0.6072691679000854, "start": 1060, "end": 1091, "probe_score": 0.0645, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020104", "page": 19, "chunk": 1, "title": "Kenya - Geothermal Development and Energy Pre-Investment Project", "pdf_url": "https://documents.worldbank.org/curated/en/919511468285057714/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7292463183403015, "start": 272, "end": 283, "probe_score": 0.8771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank** Implementation Status & Results Report\nOne WASH—Consolidated Water Supply, Sanitation, and Hygiene Account Project (One WASH—CWA) (P167794)\n\n\n\nComments **:**\n\n\n\nThe indicator measures accessibility and use of the water resources monitoring system. It measures the\nuse of the water resource data (meteorology, hydrology and groundwater) to inform design and\n<u>management of water supply systems delivered under the Project.</u>\n\n\n\n**Intermediate Results Indicators by Components**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n12/3/2021 Page 6 of 11", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["water resource data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007709", "page": 5, "chunk": 0, "title": "Disclosable Version of the ISR - One WASH?Consolidated Water Supply, Sanitation, and Hygiene Account Project (One WASH?CWA) - P167794 - Sequence No : 05", "pdf_url": "https://documents.worldbank.org/curated/en/099900012032130899/pdf/Disclosable0Ve0794000Sequence0No005.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "water resource data", "label": "VAGUE_DATA", "score": 0.6542684435844421, "start": 294, "end": 313, "probe_score": 0.2032, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "required for local government involvement, and arrangements for maintenance, monitoring and\nevaluation (M&E). Social capital enhancing activities would be a mandatory part of all sub-projects, and\nwould be tailored to support activities chosen by the communities.\n\nSupport to Decentralized Government Structures. Most local administrations are beginning\nto operate again with a limited number of staff and other inputs. District and chiefdom authorities are\nvery weak, however, and lack the financial and human resources needed to address their concerns and\npnorities effectively. NGOs have demonstrated their ability to implement successful community-based\nsocial and economic projects and have played a key role in shelter reconstruction activities. With the\ngradual strengthening of local government capacity, partnerships between community groups and local\nauthorities are expected to increase. Upon completion of initial training, district and chiefdom authorities\nwould be required to demonstrate that they have used the training by showing that there have been some\nimprovements in their community. For instance, at the end of each training session, district authorities\nwould be required to develop a simple action plan that specifies some activities that NSAP or other\npartners could support. District and chiefdom authorities would also gain experience in implementing,\nsupporting or overseeing community development activities.\n\nHealth. The unfavorable health indicators in Sierra Leone can be attributed to several factors.\nHigh fertility, female genital mutilation and the presence of HIV/AIDS increase morbidity and mortality\nrisks for women and children. Many risk factors that have contributed to HIV/AIDS epidemics in other\nAfrican countries have long been present in Sierra Leone, and the protracted conflict has created the\nconditions for explosive growth in HIV/AIDS infection rates. The Centers for Disease Control carried\nout a survey in 2002 which found the HIV prevalence among adults (aged 1549) to be 6.1 %; in\nFreetown, 4% in rural areas and 4.9% nationwide. In response to the crisis, Government has developed\na multi-sector HIV/AIDS Program, which is being supported by various", "output": {"entities": {"named_data": [], "descriptive_data": ["survey in 2002"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000052", "page": 10, "chunk": 0, "title": "Croatia - Municipal Environmental Infrastructure Project", "pdf_url": "http://documents1.worldbank.org/curated/en/367181468770702078/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey in 2002", "label": "DESCRIPTIVE_DATA", "score": 0.6400850415229797, "start": 1950, "end": 1964, "probe_score": 0.9708, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " agencies, have developed a consolidated\nPDM data collection tool to produce unified GCA\nPDM reports on a monthly basis to capture issues\nrelated to cash processes, and on a quarterly\nbasis to capture impacts of cash assistance. It is\nrefreshing to see in the tool a focus on impact\nas well as coping strategy indicators for different\n\n\n\nsectors, such as shelter or health. It is hoped that\nonce data collected is systematically analyzed,\nand the findings presented in a user-friendly way\nand regularly published for the wider public, this\ninitiative will contribute to redress one of the key\nshortcomings found by this review – the scant\navailability of good quality monitoring data on cash\nexpenditure and, critically, on outcomes.\n\n\nTo further enhance understanding of outcomes in\nthis context, there is also scope for capitalizing on\nthe qualitative analytical capacity being developed\nat Field Offices level. Some of the quantitative\nfindings that will emerge from the GCA PDM, on\nprotection and other sectoral issues, could be\nfurther investigated through qualitative analysis to\nstrengthen understanding of outcomes (and other\ndynamics) in different sectors.\n\n##### **Protection outcomes of** **multipurpose cash**\n\n\nSince the start of the response to the refugee\nand migrant crisis in Greece, cash has been\nincreasingly scaled up to replace in-kind food and\nnon-food assistance. According to key informants\ninterviewed, the shift to cash was overwhelmingly\nperceived as an appropriate and dignified form of\nassistance, particularly in light of the operational\ncontext where the cash response is taking place –\na developed, European country.\n\n\nFindings of available PDM exercises capture\npositive perceptions of safety among cash\nbeneficiaries living in sites. Mercy Corps PDM of\nOctober 2017 found 75% of respondents stating\nan improved sense of safety linked to cash\nassistance, with persons of concern receiving the\nfull MEB having a more enhanced sense of safety\ncompared to recipients of the partial MEB (Mercy\nCorps Greece, 2017). The IRC PDM of August 2017\nreported similar findings, with 76% of respondents\nclaiming", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["monitoring data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000390", "page": 12, "chunk": 1, "title": "Greece Case Study: Multi-purpose Cash and Sectoral Outcomes", "pdf_url": "https://reliefweb.int/attachments/33b69c07-e2c4-31fe-bb36-4bf71fc2edba/5b2cfa1f7.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "monitoring data", "label": "VAGUE_DATA", "score": 0.7229797840118408, "start": 668, "end": 683, "probe_score": 0.072, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nIntegrated Sustainable Mobility Project in the Foz do Rio Itajaí Region (P178557)\n\n\nrecommendations brought up during the citizen engagement round of consultations are included in the basic designs.\nThe BRT system and the pedestrian/cyclist corridors in Balneário Camboriú will be informed by updated climate data,\nwhere they relate to flooding and landslides, which will safeguard the technical sustainability of the Project. The BRT\noperation control will be integrated with civil protection and other disaster-risk management agencies to ensure\nefficient response to disasters. Moreover, the TOD and LVC support to the Consortium will maximize the amount of\nresidential and business areas within walking distance of public transport, thus increasing the use of public transport,\ngenerating greater efficiency in transporting passengers to job areas, and reducing the overall expenditures on roads\nand the negative externalities of congestion and low air quality. Where applicable, and in coordination with land\nregulations, it may create hub areas for densification that create opportunities for private sector participation and\neconomic enhancement.\n\n59. **Sustainability during operations will include adaptations to service plans for the BRT and future expansion of the**\n**network.** The existing municipal buses will be reallocated to ensure a feeder–trunk system for the BRT, and the BRT\noperation concession will be launched to include the BRT lines and the other corridors, i.e., the Central, Circular,\nNorthern, Southern, and the two Western corridors, with potential inclusion of route extensions if agreed between\nthe concessionaire and the Consortium. In addition, the provision of the fleet will be launched separately, as\ndemonstrated by the best practices of e-mobility. The intermunicipal bus services that use the corridor, under\ncontracts issued by the State of SC, will need to avoid competition, subject to negotiation with the state. The\nimplementation of the BRT-AMFRI will improve system performance and road safety, which should reduce the\noperating costs for these", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["climate data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000182", "page": 30, "chunk": 0, "title": "Brazil - Integrated Sustainable Mobility Project in the Foz do Rio Itajaí Region", "pdf_url": "https://documents1.worldbank.org/curated/en/099032624162515430/pdf/BOSIB-60d57288-4e09-4519-ae6c-ffdc0037e0b1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "climate data", "label": "VAGUE_DATA", "score": 0.7636212110519409, "start": 320, "end": 332, "probe_score": 0.7961, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Consultants under IBRD Loans and IDA Credit and\nGrants by World Bank Borrowers,” dated January, 2011, and the provisions stipulated in the\nLegal Agreement. Contract awards will also be published in UNDB, in accordance with the\nBank’s Procurement Guidelines (paragraph 2.60) and Consultants Guidelines (paragraph 2.31).\nProject activities will also be implemented following “Guidelines on Preventing and Combating\nFraud and Corruption in Projects Financed by IBRD Loans and IDA Credits and Grants,” dated\nOctober 15, 2006 and revised in January 2011. As an emergency operation, this project is\nentitled to the specificity and the flexibility described in paragraph 11 of OP 10.00 on Investment\nProject Financing.\n\n68. **_Procurement Plan_** **.** A Simplified Procurement Plan was reviewed, discussed and agreed\nupon by the Borrower and the project team during negotiations. It will be available in the\nproject’s database, and a summary will be disclosed on the Bank’s external website once the\nproposed project is approved by the Board. The Procurement Plan will be updated in agreement\nwith the Project Team annually or as required to reflect the actual project implementation needs\nand improvements in institutional capacity.\n\n\n**E.** **Social and Environmental (including Safeguards)**\n\n69. From an environmental and social safeguards standpoint, the project is a **Category B** .\nThe environmental and social impacts will be local and limited, as the project’s activities will\nfocus on targeted refugees’ and returnees’ camps. Specific mitigation measures will be designed.\nThe proposed interventions will include: (i) supplying food; (ii) supplying seed, animal feed, and\n\n\n18", "output": {"entities": {"named_data": [], "descriptive_data": ["project’s database"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000007", "page": 27, "chunk": 1, "title": "Chad - Emergency Food and Livestock Crisis Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/179061468215115488/pdf/PAD11010PAD0P1010Box385329B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "project’s database", "label": "DESCRIPTIVE_DATA", "score": 0.8398158550262451, "start": 903, "end": 921, "probe_score": 0.3436, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**I.** **STRATEGIC CONTEXT**\n\n\n**A.** **Country Context**\n\n\n1. **Jordan is a small middle-income country facing severe challenges.** These challenges are brought\nby insecurity in neighboring Syria and Iraq. The total closure of land trade routes with Syria and Iraq and\nother security-related challenges within and around Jordan adversely affected trade, tourism, investment,\nand construction. <sup>1</sup> [^1: As an indication, and comparing 2015 results with 2014, the number of tourist arrivals regressed by 9.7 percent;\nsimilarly, the number of construction permits were 9.6 percent lower and exports to Iraq and Syria were cut by 40.5\npercent and 40.3 percent, respectively.] According to a census conducted in 2015, Jordan has a population of 9.5 million (of\nwhich about a third are non-Jordanian) and suffers from a high unemployment rate of 13 percent for\nJordanians (about 200,000 individuals). Real gross domestic product (GDP) growth is estimated to have\ncontracted to 2.4 percent in 2015 from 3.1 percent in 2014. <sup>2</sup> [^2: Economic growth averaged 6.5 percent from 2000 to 2009. The economy’s performance was more muted from 2010\nto 2014, averaging growth of 2.7 percent.] GDP growth is forecasted to rebound slightly\nover 3.0 percent on average from 2016 to 2018. This low growth rate is insufficient to provide enough jobs\nto the growing population in Jordan.\n\n\n2. **The crisis in Syria has led to a massive influx of Syrian refugees into Jordan over the past five**\n**years.** As of June 2016, Jordan hosts 655,217 Syrian refugees registered with United Nations High\nCommissioner for Refugees (UNHCR), <sup>3</sup> [^3: _Source:_ UNHCR June 2016.] 80", "output": {"entities": {"named_data": [], "descriptive_data": ["census conducted in 2015"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 9, "chunk": 0, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "census conducted in 2015", "label": "DESCRIPTIVE_DATA", "score": 0.8953019976615906, "start": 697, "end": 721, "probe_score": 0.9769, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "workforce and adequate infrastructure (Butollo 2021; Arunyanart et al. 2021).\n\n\nAs discussed in Kilic Celik, Kose, and Ohnsorge (2023), potential output growth is\nexpected to slow in many EMDEs in the coming decade amid unfavorable demographics\nand slowing investment and productivity growth. One way in which policymakers in\nEMDEs can boost long-term growth of output and productivity is by promoting trade\nintegration through measures to reduce trade costs.\n\n\nOur study examines the following questions. First, what is the link between trade\ngrowth and long-term output and productivity growth? Second, what are the prospects\nfor trade growth in the coming decade? Third, how large are trade costs? Fourth, what\nare the correlates of trade costs? And fifth, which policies can help to reduce trade\ncosts?\n\n\nOur study contributes to the literature in a number of ways. First, it expands on World\nBank (2021b) with a new, comprehensive review of the theoretical and empirical\nliterature on the links between trade and output growth. Second, it presents an event\nstudy of the evolution of trade in goods and services through global recessions, including\nthe pandemic-induced global recession of 2020.\n\n\nThird, our study revisits an earlier literature that reported estimates of trade costs and\ntheir correlates (Arvis et al. 2016; Novy 2013; World Bank 2021b). It uses estimates of\nthe costs of goods trade for up to 180 countries (29 advanced economies and 151\nEMDEs) from the World Bank/UNESCAP database for 1995-2019. The drivers of the\ncosts of goods trade, which accounts for about 75 percent of world and EMDE trade in\ngoods and services, are estimated econometrically. Our study also quantifies the\ncontribution of one type of services trade—logistics and shipping services—to the costs\nof goods trade. In addition, our study goes further than previously published research in\nassessing the", "output": {"entities": {"named_data": ["World Bank/UNESCAP database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001145", "page": 4, "chunk": 0, "title": "idu0f731bf7c0ba660447f089fe0353b4723e925", "pdf_url": "https://local/prwp/idu0f731bf7c0ba660447f089fe0353b4723e925.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Bank/UNESCAP database", "label": "NAMED_DATA", "score": 0.8495076894760132, "start": 1477, "end": 1504, "probe_score": 0.9961, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "$4,000,000); (ii) Valuation of 50 percent of**<br>**fixed assets is completed and uploaded in IFMIS (US$1,000,000 for every 10 percent increment up to**<br>**$5,000,000); and (iii) an inventory of outstanding fixed asset-related issues prepared (US$1,000,000)**<br>• <br>**DLR 3.1.4: All bank and cash balances are consolidated on a weekly basis (US$6,000,000)**<br>• <br>**DLR 3.1.5: Pronouncement issued by CS NT for the adoption of accrual accounting (US$6,000,000)**<br>|\n|Description <br>|**Completion of annual DLRs outlined in the DLI table.** <br>|\n|Data source/ Agency <br>|**PFMRS** <br>|\n|Verification Entity <br>|**IVA** <br>|\n|Procedure <br>|**Annual review by IVA** <br>|\n|**3.2 : Transparency of public procurement spending is improved (Text)**|**3.2 : Transparency of public procurement spending is improved (Text)**|\n|Formula <br>|• <br>**DLR 3.2.1: e-GP piloted in 9 MDAs (US$4,000,000)**<br>• <br>**DLR 3.2.2: e-GP rolled out in 30 percent of national MDAs (US$2,000,000 for every 10 percent increment up to**<br>**", "output": {"entities": {"named_data": ["IFMIS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005028", "page": 39, "chunk": 1, "title": "Kenya - Second Program for Strengthening Governance for Enabling Service Delivery and Public Investment in Kenya Project", "pdf_url": "https://documents.worldbank.org/curated/en/099110823124529438/pdf/BOSIB-9a20732b-0c8b-4e90-82ba-833643ce1578.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "IFMIS", "label": "NAMED_DATA", "score": 0.5077311396598816, "start": 94, "end": 99, "probe_score": 0.0423, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " net wage of\na Ukrainian refugee (estimated based on\nthe SEIS UNHCR survey in chapter 2) from\n80% to 98% of the median in the economy\nas a whole (or from 80% to 93% according\nto Ukrainian refugee’s median in the NBP’s\n2024 survey), almost closing the gap to the\neconomy as a whole in these terms. It is in\nfact higher than the PLN 500 median net\nwage premium of the pre-war Ukrainian\nmigrants over Ukrainian refugees in the\nNBP (2024) survey, even though 68% of the\nformer and only 28% of the latter said they\nhad a high level of fluency in Polish.\n\n\n31\n\n\n\nprofessions (physicians, dentists, nurses,\nand midwives) have opened to migrants\nand refugees to reduce shortages, and\nwhile the shares for all of them stand at\njust 0.9% compared to 1.9% for Polish\ncitizens, the gap is actually very narrow for\nphysicians and dentists, who constitute\n0.7% of Ukrainian refugees and 0.8% of\nPolish citizens. In legal professions (legal\ncounsels, barristers, notaries, and bailiffs),\nthe gap remains wide, although in addition\nto occupational licensing, the likely causes\nmay be the differences between the Polish\nand Ukrainian legal systems as well as\nnew entrants’ struggles with attracting\nclients due to advertising restrictions. In\neffect, just 0.02% of Ukrainian refugees\nwork in legal professions, compared to\n0.4% of Polish citizens. There are also\nhigh contrasts across the remaining\nregulated professions, which employ\n0.8% of Ukrainian refugees and 3.3% of\nPolish citizens. These are construction\nengineers (0.02% Ukrainian refugees),\npharmacists (0.01%), and psychologists\n(0.09%), compared to the following shares\nfor Polish citizens: 0.26%, 0.19%, and 0.18%,\nrespectively.\n\n\n\n**One of the", "output": {"entities": {"named_data": ["SEIS UNHCR survey", "NBP’s\n2024 survey", "NBP (2024) survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 15, "chunk": 3, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS UNHCR survey", "label": "NAMED_DATA", "score": 0.8780580759048462, "start": 57, "end": 74, "probe_score": 0.9287, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "NBP’s\n2024 survey", "label": "NAMED_DATA", "score": 0.8511481285095215, "start": 212, "end": 229, "probe_score": 0.533, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "NBP (2024) survey", "label": "NAMED_DATA", "score": 0.7000123858451843, "start": 424, "end": 441, "probe_score": 0.0598, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " be developed\nfor all major groups using the Central Mediterranean\nRoute.\n\n\nĐ As digital platforms are accessible across borders,\n\nUNHCR offices can create synergies by **using**\n**the same platforms along the entire Central**\n**Mediterranean Route** . Currently, mobile tools such\nas apps, infolines, SMS, and social media platforms\n\n\n8 **WE DIDN’T THINK IT WOULD HAPPEN TO US**\n\n\n\nare only used at the national level, if at all. UNHCR\nshould also collected more data on the target\naudiences, including their access to mobile phones\nand their literacy levels.\n\n\nĐ **Add new formats to the UNHCR / TRS family**\n\n**of products** by creating a regular professional\n**news show**, presented by personalities from the\ncommunities and using audio and video files\nfrom community members, interviews, news\ndevelopments, etc. Different shows should be\ntailored to the different communities and produced\nin different languages (e.g. Somali, Tigrinya, etc).\n\n\nĐ In addition to individual testimonials disseminated\n\nthrough TRS and Dangerous Crossings, it should\nproduce **talk shows with VIP presenters** to raise\nawareness on **underreported topics** related to\nirregular migration. Potential topics include (1)\nthe situation of families who have to pay excessive\nransom, (2) the long-term effects of torture that\nsurvivors are experiencing, and (3) the persuasive\ntechniques smuggling agents are using to recruit\ncustomers.\n\n\nĐ UNHCR does not use the full potential of social\n\nmedia, especially the possibility to reiterate and\nreinforce communications by **cross-channel**\n**messaging** . All info products should be disseminated\nvia the usual UNHCR and TRS channels (mainly\nFacebook and YouTube) with additional strategic\nboosts, i.e. paid dissemination to defined target\naudiences.\n\n\nĐ CwC not only requires interventions at a large\n\nscale, such as TRS, but also at the country and field\noffice level.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on the target\naudiences"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001467", "page": 7, "chunk": 1, "title": "'We didn’t think it would happen to us': Mapping of CwC Activities along the Central Mediterranean Route", "pdf_url": "https://reliefweb.int/attachments/e4848429-dddb-32d5-a9ef-099d41db0db9/CentMed_CwC_screen.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on the target\naudiences", "label": "VAGUE_DATA", "score": 0.520002543926239, "start": 464, "end": 492, "probe_score": 0.0053, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad Agribusiness and Rural Transformation Project (P179238)\n\n\nand 271,000 active users of mobile money. The country has made significant progress in the last decade, but still\nlags peers in the CEMAC and WAEMU regions. Challenges include poor network connections, especially in remote\nareas, and the population’s low literacy rate. Only 19 percent of the population had made or received digital\npayments in 2019, compared to 35 percent in SSA.\n\n\n**Figure A8.4 Chad. Account Ownership: Time Series (2011, 2014, 2017)**\n\n\n_Source: World Bank Global Findex Database (2014-2017)_\n\n\n**III.** **The Agribusiness and Rural Transformation Project (ProAgri)’s Contribution to Tackling Identified**\n**Constraints**\n\n11. **ProAGRI will contribute to addressing some of the demand-side and supply-side constraints to increasing**\n**financial services to agribusiness SMEs.** As discussed in preceding paragraphs, demand-side constraints include:\n(i) SMEs’ inadequate documentation to permit banks to adequately gauge the risks associated with proposed\nsub- projects; (ii) SMEs’ low management and financial reporting capacities; and (iii) inadequate suitable collateral,\namong others. Supply-side constraints include financial products and services that are limited and not adapted to\nthe needs of agribusiness SMEs. They are also reticent about the risk associated with agribusiness, which is likely\nto be exacerbated by Climate Change. The project will address some of these constraints through Business\nAdvisory Services and a Credit Guarantee Facility.\n\n\n**Business Advisory Services**\n\n\n12. The project will finance activities with the aims at accelerating the creation, promotion and growth of Agrienterprises in partnership with the Chadian Chamber of Commerce, Industry, Agriculture, Mines, and Craft\n(CCIAMA). CCIAMA will put in place a one-stop", "output": {"entities": {"named_data": ["World Bank Global Findex Database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000183", "page": 89, "chunk": 0, "title": "Chad - Agribusiness and Rural Transformation Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099040824103517122/pdf/BOSIB-e8e37b29-1d61-491d-8aad-23a07cf57740.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Bank Global Findex Database", "label": "NAMED_DATA", "score": 0.7627716064453125, "start": 549, "end": 582, "probe_score": 0.9996, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "- Os documentos de pedidos de ofertas/pedidos de propostas deverão exigir que os\nlicitadores/proponentes que apresentem ofertas/propostas apresentem uma aceitação assinada\nno momento da licitação para serem incorporados em quaisquer contratos resultantes,\nconfirmando a aplicação e cumprimento das Orientações Anticorrupção do Banco, incluindo sem\nlimitação o direito de sanção do Banco e os direitos de inspeção e auditoria do Banco;\n\n\n     - A aceitação dos Direitos do Banco para rever a documentação e as atividades de aquisição.\n\n\nQuando forem aplicados pelo Mutuário outras disposições de licitação nacional de contratos públicos que\nnão sejam nacionais abertos, essas disposições serão sujeitas ao ponto 5.5 do Regulamento de Aquisição.\n\n\n**_Ativos locados_** _, conforme especificado no ponto 5.10_ do Regulamento de Aquisição: O arrendamento pode\nser utilizado para os contratos identificados nas tabelas do Plano de Aquisição. _\"Não aplicável\"_\n\n\n**_Aquisição de bens em segunda_** **_mão_** _, conforme especificado no ponto 5.11_ do Regulamento de Aquisição\n\n- é permitido para os contratos identificados nas tabelas do Plano de Aquisição _\"Não Aplicável\"_\n\n\n**_Preferência doméstica_** _, tal como especificado nos termos do ponto", "output": {"entities": {"named_data": [], "descriptive_data": ["tabelas do Plano de Aquisição", "tabelas do Plano de Aquisição"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003335", "page": 25, "chunk": 0, "title": "Eastern and Southern Africa - EASTERN AND SOUTHERN AFRICA- P178047- Development Response to Displacement Impacts Project in the Horn of Africa Phase II - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099062923175035774/pdf/P1780470fa87150740ac760eef050568b1c.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "tabelas do Plano de Aquisição", "label": "DESCRIPTIVE_DATA", "score": 0.5992497801780701, "start": 906, "end": 935, "probe_score": 0.0034, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "tabelas do Plano de Aquisição", "label": "DESCRIPTIVE_DATA", "score": 0.5516929030418396, "start": 1121, "end": 1150, "probe_score": 0.0001, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " primarily on consumption as this is the measure of well-being that is most\nfrequently used in the world for assessing poverty status, but we also note that income is used as a measure of wellbeing in many cases. For example, the 2012 global poverty estimates reported in Ferreira _et al._ (2016) are based on\ndata from 131 countries, of which 99 use consumption as the measure of well-being and 32 use income. In an abuse\nof terminology, we refer to “consumption” and “income” interchangeably as the measure of household living standards\nin this paper. See also Ravallion (2016) for a comprehensive discussion on the history of thought on poverty and other\nmeasurement approaches.\n\n\n2", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data from 131 countries"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000235", "page": 3, "chunk": 1, "title": "data gaps data incomparability and data imputation a review of poverty measurement methods for data scarce environments", "pdf_url": "https://local/prwp/data-gaps-data-incomparability-and-data-imputation-a-review-of-poverty-measurement-methods-for-data-scarce-environments.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from 131 countries", "label": "VAGUE_DATA", "score": 0.6752076148986816, "start": 310, "end": 333, "probe_score": 0.9932, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["M&E data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000013", "page": 29, "chunk": 2, "title": "West Bank and Gaza - Education Action Project", "pdf_url": "http://documents1.worldbank.org/curated/en/137371468765334508/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "M&E data", "label": "VAGUE_DATA", "score": 0.5883201956748962, "start": 530, "end": 538, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "government did little to address this problem, the mayor and his regional secretary taking the\nview that redistribution was unnecessary since the city had too many teachers. <sup>46</sup> [^46: Interviews with former mayor of Municipality B and former head of the city education agency and currently\n(August 2015) Regional Secretary, Municipality B, August 2015.] The Education\nBoard made a recommendation to the education agency at the time that it carry out a mapping\nof teacher needs and allocate teachers to schools accordingly. But this was never taken up. <sup>47</sup> [^47: Interview with the head of the Education Board, Municipality B, August 2015.]\nOne branch head ( _kepala bagian_ ) in the education agency official explained that the issue of\nteacher redistribution had been discussed extensively within the education agency but that there\nhad so far been little willingness to tackle the problem in any systematic or serious way. Indeed,\nthey had floated the idea of kicking the problem downstairs to the UPTD. He stated that the\nkey obstacle was the political challenges involved in teacher redistribution. <sup>48</sup> [^48: Interview, Municipality B, August 2015.]\n\nSince 2013, it appears that the city education agency has, however, started to change direction\non the issue. 2013 saw two important developments. The first was the election of a new mayor\nalthough, because of a Constitutional Court challenge to the election result, he did not take up\nthe job until late 2014. His choice as head of the local education agency told us that teacher\nredistribution is one of his top priorities indicating that the agency may be more active in this\narea in future. <sup>49</sup> [^49: Interview, Municipality B, August 2015.] Having only been in the job for four months at the time of interview, however,\nhe had not yet had the chance to make much progress so far.\n\nThe second", "output": {"entities": {"named_data": [], "descriptive_data": ["mapping\nof teacher needs"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006915", "page": 41, "chunk": 0, "title": "wps7913", "pdf_url": "https://local/prwp/wps7913.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "mapping\nof teacher needs", "label": "DESCRIPTIVE_DATA", "score": 0.6839783191680908, "start": 462, "end": 486, "probe_score": 0.3816, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nStrengthening Institutions for Refugee Administration Project (P165542)\n\n\n\n|Col1|organizational level and are<br>intended to measure<br>achievement of individual<br>organizational goals agreed<br>by each entity. Targets<br>should be set at the<br>beginning of each Fiscal<br>Year (FY) and reviewed at<br>the end of the FY.|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|Registered Afghan refugee users of visa<br>facilitation centers report satisfaction<br>with service standards|Indicator measures the level<br>of satisfaction with the<br>services provided by the<br>CAR to Afghan refugees<br>applying for visas. It is<br>expected that in the first<br>few years, satisfaction will<br>be low, but is expected to<br>improve as systems become<br>better. Service standards<br>will be defined during<br>project implementation and<br>placed in prominent places<br>around visa facilitation<br>centers and CAR offices.|Semi Annual<br>|Provincial<br>Commissione<br>rates for<br>Afghan<br>Refugees<br>|Survey of users<br>|CCAR<br>|\n|Registered Afghan refugee users of<br>visa facilitation centers report<br>satisfaction with service standards<br>(Female)|Indicator measures level of<br>satisfaction of female users.|Semi-Annual<br>|Provincial<br>Commissione<br>rates MIS<br>databases<br>|Survey of female users<br>|CCAR", "output": {"entities": {"named_data": [], "descriptive_data": ["Survey of users"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000009", "page": 28, "chunk": 0, "title": "Pakistan - Strengthening Institutions for Refugee Administration Project", "pdf_url": "http://documents1.worldbank.org/curated/en/108361587348120175/pdf/Pakistan-Strengthening-Institutions-for-Refugee-Administration-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Survey of users", "label": "DESCRIPTIVE_DATA", "score": 0.5327380895614624, "start": 1013, "end": 1028, "probe_score": 0.3906, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Recipient has entered into an Inter-Agency<br>Memorandum of Understanding with Program<br>MDAs participating in year 1 of the Program,<br>respectively.|Effectiveness<br>Date|Effectiveness<br>Date|\n|Section I.B of Schedule 2 to the<br>Financing Agreement.|The Recipient shall appoint in each Fiscal Year, an<br>Independent Verification Agent, with qualifications,<br>experience and terms and conditions of employment<br>satisfactory to the Association, to be responsible for<br>carrying out the Annual Performance Assessment|Each Fiscal Year|Each Fiscal Year|\n|Section I.B of Schedule 2 to the<br>Financing Agreement.|The Recipient shall by not later than three (3) months<br>after the Effectiveness Date, update, and thereafter,<br>adopt the Program Operational Manual, in form and<br>substance satisfactory to the Association.|November 2018|November 2018|\n|Section I.B of Schedule 2 to the<br>Financing Agreement.|The Recipient, through MoLHUD, shall prepare and<br>adopt, not later than March 31 of each Fiscal Year<br>(“FY”) during the implementation of the Program, a<br>Performance Improvement Plan (“PIP”) specifying<br>activities to be carried out by said MoLHUD during<br>said FY, and implement said PIP.|Each Fiscal Year|Each Fiscal Year|\n|Section IV.B of Schedule 2 to the<br>Financing Agreement|The Recipient, through MoLHUD, shall make<br>withdrawal for DLRs under Categories (1), (2), (3)<br>and (4) achieved prior to the Signature Date, except<br>for withdrawals up to an aggregate amount not to<br>exceed SDR", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000062", "page": 6, "chunk": 3, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents.worldbank.org/curated/en/946901526654169395/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda: Roads and Bridges in the Refugee Hosting Districts Project (P171339)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Total Project Cost|150.80|\n|---|---|\n|**Total Financing**|150.80|\n|**of which IBRD/IDA**|130.80|\n|**Financing Gap**|0.00|\n\n\n\n\n\n|World Bank Group Financing|Col2|\n|---|---|\n|International Development Association (IDA)|130.80|\n|IDA Grant|130.80|\n\n\n|Non-World Bank Group Financing|Col2|\n|---|---|\n|Counterpart Funding|20.00|\n|Borrower/Recipient|20.00<br>|\n\n\nPage 2 of 80", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 6, "chunk": 0, "title": "Uganda - Roads and Bridges in the Refugee Hosting Districts/Koboko-Yumbe-Moyo Road Corridor Project", "pdf_url": "http://documents.worldbank.org/curated/en/834931600048847296/pdf/Uganda-Roads-and-Bridges-in-the-Refugee-Hosting-Districts-Koboko-Yumbe-Moyo-Road-Corridor-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Adhvaryu, 2014).\n\nHowever, the slow adoption of accurate diagnostic tools remains a pervasive challenge\nin health care (Baker, 2001; Fleming et al., 2021). Many efforts in low- and middle-income\ncountries have focused on education and training interventions for health care providers.\nWhile systematic reviews indicate that provider-targeted training can improve patient outcomes, the overall quality of evidence remains low, and there are still relatively few studies\nthat directly address adherence to test results (Rowe et al., 2018, 2021). Moreover, most such\nstudies do not consider patient responses. But health workers do not operate in a vacuum:\ncare outcomes are a product of interactions between providers and patients. If patients do\nnot value diagnostic testing, providers may have limited incentives to routinely verify their\ndiagnoses with medical tests. <sup>1</sup> The empirical evidence on this channel is limited, in part\nbecause identification requires downstream data on provider behavior, care outcomes, and\npatient satisfaction.\n\n\n1For a review documenting the inconsistent linkages between patient satisfaction and quality of care, see\nFarley et al. (2014).\n\n\n1", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["downstream data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001383", "page": 3, "chunk": 1, "title": "idu17547a127149861475c1895a10c7fac248530", "pdf_url": "https://local/prwp/idu17547a127149861475c1895a10c7fac248530.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "downstream data", "label": "VAGUE_DATA", "score": 0.8118748664855957, "start": 973, "end": 988, "probe_score": 0.8818, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "The World Bank\n\n|Number of people with access to a basic<br>package of nutrition services (CBN), % female|Col2|Number|Value|0.00|29750000.00|44125000.00|\n|---|---|---|---|---|---|---|\n|Number of people with access to a basic<br>package of nutrition services (CBN), % female||Number|Date|29-Apr-2008|10-Dec-2013|07-Jan-2014|\n|Number of people with access to a basic<br>package of nutrition services (CBN), % female||Number|Comments|Source: Routine CBN data,<br>FMOH<br>(revised indicator definition,<br>baseline value and data<br>source)|Source: Routine CBN data,<br>FMOH|Routine CBN data, FMOH|\n|Number and percentage of children 6-59<br>months receiving a dose of Vitamin A every 6<br>months||Number<br>Sub Type<br> Breakdown|Value|10200000.00|10700000.00|11300000.00|\n|Number and percentage of children 6-59<br>months receiving a dose of Vitamin A every 6<br>months||Number<br>Sub Type<br> Breakdown|Date|29-Apr-2008|10-Dec-2013|07-Jan-2014|\n|Number and percentage of children 6-59<br>months receiving a dose of Vitamin A every 6<br>months||Number<br>Sub Type<br> Breakdown|Comments|UNICEF EOS 2008 data<br>(revised indicator definition<br>and baseline value)|Source: FMOH 2010-", "output": {"entities": {"named_data": ["UNICEF EOS 2008 data"], "descriptive_data": ["Routine CBN data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019062", "page": 2, "chunk": 0, "title": "Ethiopia - Ethiopia Nutrition (FY08) : P106228 - Implementation Status Results Report : Sequence 12", "pdf_url": "https://documents.worldbank.org/curated/en/845591468031578918/pdf/ISR-Disclosable-P106228-01-04-2014-1388849008746.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Routine CBN data", "label": "DESCRIPTIVE_DATA", "score": 0.5653745532035828, "start": 439, "end": 455, "probe_score": 0.9691, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNICEF EOS 2008 data", "label": "NAMED_DATA", "score": 0.884733259677887, "start": 1085, "end": 1105, "probe_score": 0.9054, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 4) Storage Department – supervises the transport and storage of wheat and barley between\nstorage platforms/silos, mills and feed centers. There is a stock unit in all silos for supervision. There is also a truck control system that\nmonitors the transfer of grains to all silos/storage platforms and then to the mills and feed centers. All vehicle and cargo data is monitored.\nIn addition, there is a Directorate of Trade in MoITS that oversees the procurement arrangements for grain. The Contracts Department is\nin charge of the signifying and implementation of contracts with shipping and inspection until the cargo reaches the port of Aqaba in Jordan.\nThe Department of Insurance oversees any delays, insurance, unloading operations and investigations of received quantities.\n\n\nPage 24 of 54", "output": {"entities": {"named_data": [], "descriptive_data": ["vehicle and cargo data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 28, "chunk": 2, "title": "Jordan - Emergency Food Security Project", "pdf_url": "http://documents.worldbank.org/curated/en/486071652556836130/pdf/Jordan-Emergency-Food-Security-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "vehicle and cargo data", "label": "DESCRIPTIVE_DATA", "score": 0.8827463388442993, "start": 340, "end": 362, "probe_score": 0.0016, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The Entry of Randomized Assignment into the Social Sciences** <sup>*****</sup>\n\n\nJulian C. Jamison\n\n\n<u>JEL codes: B16, C91, C93, C18, D04</u>\n\n\n<u>Keywords: randomization, RCT, field experiment, lab experiment, selection bias, causality, history of</u>\neconomic thought\n\n\n- I thank Art Boylston, Jesse Bump, Austin Frakt, Don Green, Judy Gueron, Glenn Harrison, Dean Jamison, Dean\nKarlan, Chris Lysy, Jack Molyneaux, Andreas Ortmann, Lior Pachter, Charlie Plott, Tasmia Rahman, and Al Roth for\nhelpful discussions and input. My interest was first piqued when I read an article by Druin Burch in _Natural History_\n(June 2013) that mentioned van Helmont’s early contribution to the topic. Thanks also go the James Lind Library,\nwhich is a wonderful resource for the relevant medical history, including translations of some of the early documents\nreferenced below. The usual caveats apply, including the fact that these are not necessarily the views of the World\nBank Group or indeed anyone other than the author.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007050", "page": 2, "chunk": 0, "title": "wps8062", "pdf_url": "https://local/prwp/wps8062.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 19. Tertiary education and corresponding**\n**occupational groups shares**\n\n\n\n**Chart 20. Ukrainian refugees median net wages by**\n**educational attainment**\n\n\n4,300 4,275\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\ncountry-specific knowledge and business\nnetworks) are more difficult to address\nthan others (such as language skills and\noccupational licensing). However, if the gap\nwas narrowed by half, the average wage of\nrefugees would increase by approximately\n10%. Assuming that the productivity\nincrease is equivalent to the wage increase,\nthis would result in PLN 3.5 billion of added\n\n\n\n**Addressing occupational downgrading**\n**could bring macroeconomic benefits.**\nTo demonstrate the potential impact,\na simulation was conducted in which\nthe underrepresentation of refugees in\nhigher-paying occupations was reduced by\nhalf. It was not assumed that there would\nbe no differences between refugees and\nPolish citizens, as some barriers (such as\n\n\n\n40%\n\n\nTertiary education share\n\n25-64 age group\nsurveys\n\n\n\nManagers, professionals,\nand technicians ZUS-insured\n\nemployment share\n\n\n\n\n#### **4.2 Access to regulated professions**\n\n\n\nnatives and this gap was largest for men,\nworkers in the highest education level, and\nnonnaturalized immigrants. This has an\nimportant impact on wages, because, as\nshowed in a seminal work by Kleiner and\nKrueger (2013) and confirmed in several\nanalyses, working in a regulated profession\ncomes with a significant wage premium.\nBrücker et al. (2021), who analysed\nGerman data, found that occupational\nrecognition led to full convergence of\nimmigrants’ earnings to those of their\nnative counterparts. Tani (2020) found\nthat in Australia, licensing raised hourly\n\n\n\nvalue to the economy. This estimate may\nunderestimate the potential benefits,\nas the boost in productivity would most\nlikely rise not just employee wages, but\nemployer profits as well", "output": {"entities": {"named_data": [], "descriptive_data": ["25-64 age group\nsurveys"], "vague_data": ["German data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 14, "chunk": 0, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "25-64 age group\nsurveys", "label": "DESCRIPTIVE_DATA", "score": 0.7532224655151367, "start": 1104, "end": 1127, "probe_score": 0.5821, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "German data", "label": "VAGUE_DATA", "score": 0.7212883830070496, "start": 1617, "end": 1628, "probe_score": 0.9229, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "#### **4 Simulation experiments**\n\nA simulation study is conducted to compare the performance of our approach, ELL, and a purely survey\n\nbased estimator in predicting FGT poverty measures. We focus on the poverty headcount ratio and the\n\n\npoverty gap with three generic poverty lines that render 25%, 50%, and 75% of the population poor.\n\n\nThe simulation setting is based on Tarozzi and Deaton (2009). In particular, the target population in\n\n\nthe census is a village with _N_ = 15 _,_ 000 households, divided into 150 clusters _kc_ _∈{_ 1 _, . . .,_ 150 _}_, each of\n\n\nsize 100. In each simulation run, an artificial household survey is drawn from the census by selecting\n\n\nrandomly ten households from 100 randomly selected clusters. First, both data sets are generated by the\n\n\nfollowing process with homoscedastic errors:\n\n\n_ych_ = _β_ 0 + _β_ 1 _xch_ + _ηc_ + _ech_ = 20 + _xch_ + _ηc_ + _ech_\n\n\n_xch_ = 5 + 0 _._ 01 _kc_ + _wch −_ _tch,_ _wch_ _∼_ _N_ (0 _,_ 1) _,_ _tch_ _∼_ _U_ (0 _,_ 1) _,_\n\n\n_ηc_ _∼_ _N_ (0 _,_ 0 _._ 01) _,_ _ech_ _∼_ _N_ (0 _,_ 1) _._\n\n\nNote that the explanatory variable is generated so that it differs in expectation between clusters. Such a\n\n\nsituation with large and systematic differences in the averages of covariates across clusters (e.g., average\n\n\nlevels of education or dwelling characteristics) is frequently observed in practice. This setting is", "output": {"entities": {"named_data": [], "descriptive_data": ["artificial household survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007406", "page": 11, "chunk": 0, "title": "wps8472", "pdf_url": "https://local/prwp/wps8472.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "artificial household survey", "label": "DESCRIPTIVE_DATA", "score": 0.5152830481529236, "start": 607, "end": 634, "probe_score": 0.5663, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " diligence for Financial Intermediaries.  The\nsystem can adequately provide, with reasonable assurance, accurate and timely information on the status of the project.\nThe financial management arrangements for the project have a **Substantial** residual risk rating. However, with planned\nimplementation support to the project as well as the implementation of agreed action plans, the financial management\narrangements will be strengthened to provide, with reasonable assurance, accurate and timely information on the status\nof the project resources required by IDA.\n\n**_Risk assessment and Mitigation_**\n\n13. The table below identifies the key risks that the project management may face in achieving these objectives and\nprovides a basis for determining how management should address these risks.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Risk Description|Risk Mitigating Measures Incorporated into Project Design|Risk rating|\n|---|---|---|\n|<br>**_Inherent risks_**<br>|<br> <br>|<br> <br>|\n|<br>**Country Level**- Recent fraud cases<br>in central government and the 2016<br>PEFA report show weaknesses in<br>government PFM systems. <br>|Weaknesses such as weak accounting capacity, budget credibility, payroll<br>rules and procurement compliance are being mitigated under a government<br>PFM reform program. New legislation is being crafted to freeze and<br>confiscate property acquired fraudulently. <br>|<br>S <br>|\n|<br>**Entity Level**-Line ministry could<br>delay in submitting relevant reports<br>due to weak capacity. <br>|<br>**MGLSD management will be enhanced by recruiting contracted personnel**<br>**to boost capacity. New measures to improve governance have been**<br>**", "output": {"entities": {"named_data": ["PEFA report"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 61, "chunk": 1, "title": "Uganda - Generating Growth Opportunities and Productivity for Women Enterprises Uganda Project", "pdf_url": "http://documents.worldbank.org/curated/en/527091655323259747/pdf/Uganda-Generating-Growth-Opportunities-and-Productivity-for-Women-Enterprises-Uganda-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PEFA report", "label": "NAMED_DATA", "score": 0.594710648059845, "start": 1052, "end": 1063, "probe_score": 0.0006, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEmergency Food Security Project (P178936)\n\n\nHowever, the economic impacts can be significant when considering the direct effects high food prices have on\nnutrition and poverty. Poor households including refugees spend about one third of their income on food. During\nthe COVID-19 pandemic, it was found that more than 50 percent of households were vulnerable to food insecurity\nand 40 percent of Jordanian households were resorting to crisis strategies that compromise their future ability to\nhandle shocks and productivity <sup>38</sup> [^38: REACH 2020] . A significant increase in the price of bread would further exacerbate this already\nfragile situation and draw a significant share of households further into poverty.\n\n**60.** **In the event of a price shock to grains in Jordan, refugees and their vulnerable host communities are**\n**going to be the hardest hit** . This is because they count among the poorest and most vulnerable population groups\nin the country and are among the most reliant on bread in their diets and on small ruminants for their livelihoods.\nLack of access to bread, could quickly have catastrophic food insecurity implications for these groups. Given the\nsystemic implications of such a scenario and the particularly high negative impacts on vulnerable communities\nincluding refugees, the project will finance public grain purchases sufficient to ensure uninterrupted supply and\nto replenish reserves to minimum levels deemed safe, while at the same time paving the way towards a managed\nphase-out from the current price policies towards a more sustainable policy approach and a more resilient food\nsystem, overall, in the medium term.\n\n**61.** **A disruption in the availability or price shock to barley would result in very high economic losses for**\n**livestock herders, owners and their dependents** . If fodder were to become physically or economically scarce, a\nloss in animal weight would occur on average as a result of culling and fodder rationing. Assuming average weight\nloss of 33 percent for", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 30, "chunk": 0, "title": "Jordan - Emergency Food Security Project", "pdf_url": "http://documents.worldbank.org/curated/en/486071652556836130/pdf/Jordan-Emergency-Food-Security-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Operational Manual. To achieve DLI#1 prior result, 20,000 work permits are to be issued\nbetween April 8 and October 31, 2016 to Syrian refugees.\n\n**Table 5. DLI#1: The Number of Work Permits Issued to Syrian Refugees**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n34. **This PforR supports the implementation of the Jordan Compact, which includes**\n**commitments from the Government of Jordan and the international community.** Jordan's ability to\nimplement its Compact commitments remains tied to the continued support provided by the international\ncommunity and fulfillment of its London commitments.\n\n\n35. **Better Work** is a joint International Labor Organization (ILO) and IFC program that provides\nassessment, advisory, and training services to factories and to improve working conditions and increase\ncompliance with international labor protection standards (child labor, working conditions, and so on) and\nlocal labor law. **Labor compliance with Better Work will be fostered through DLI # 2:** **Annual public**\n**disclosure by Better Work Jordan of report on factory-level compliance with a list of at least 29 social**\n**and environmental-related items.** This Program will be expanded to include factories exporting using\nthe EU trade preference. A major concern of stakeholders has been the nondisclosure of the findings of\nthese inspections. The proposed DLI will require disclosure of inspection findings. This compliance is also\nan important part of the investment value proposition.\n\n\n**_Theme 2: Improving the Investment Climate_**\n\n\n11", "output": {"entities": {"named_data": [], "descriptive_data": ["report on factory-level compliance"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 19, "chunk": 1, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "report on factory-level compliance", "label": "DESCRIPTIVE_DATA", "score": 0.5076737403869629, "start": 1045, "end": 1079, "probe_score": 0.0098, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "The second major socio-economic determinant of child mortality, which we quickly\n\nassess here in a descriptive way, is mother’s education. As can be seen in Figure 6, the share\n\nof mothers who completed at least primary education seems to show little correlation with\n\n\nchild mortality rates. Except for Senegal, all West African countries tend to have very low\n\n\nrates of primary completion while mortality levels as well as performance vary greatly within\n\nthis group. No country in West Africa has significantly expanded mothers’ education in the\n\n\nrespective period covered by the surveys. Yet, we have seen above, this has not prevented\n\nNiger from achieving a considerable reduction in child mortality. This also holds for\n\nMozambique. In the remaining two fairly successful countries, Uganda and Madagascar, child\n\n\nmortality improvements have been accompanied by improvements in mothers’ educational\n\nendowments.\n\n\n**Figure 6: Mothers with at least primary education and U5M rates**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|260|2|Col3|Col4|Col5|\n|---|---|---|---|---|\n|40<br>~~60~~|~~2~~|~~2~~|~~2~~|Gui<br>~~Ni~~|\n|40<br>~~60~~|||||\n|1<br>~~00~~<br>20|~~0~~<br><br>Mal|~~0~~<br><br>Mal|~~0~~<br><br>Mal|1<br>2<br>3<br>4<br>5<br><br>~~Mal~~|\n|1<br>~~00~~<br>20|0|0|0|0|\n|K<br>80<br>|~~-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["surveys"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004255", "page": 24, "chunk": 0, "title": "wps5062", "pdf_url": "https://local/prwp/wps5062.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "surveys", "label": "VAGUE_DATA", "score": 0.5471892952919006, "start": 585, "end": 592, "probe_score": 0.999, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad COVID-19 Strategic Preparedness and Response Project (P173894)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Number of communication campaigns<br>about COVID-19 broadcast to<br>communities|Number of awareness<br>communications<br>campaigns conducted|weekly|COVID-19<br>report|routine data|MOPH|\n|---|---|---|---|---|---|\n|<br>National COVID-19 risk communication<br>and community engagement strategy<br>established|<br>Establishment of a risk<br>communication and<br>engagement strategy in<br>Chad <br>|once<br>|<br>COVID-19<br>report<br>|routine data<br>|MOPH<br>|\n|Number of technical crisis coordination<br>meetings issuing an official report on<br>epidemic surveillance and response|<br>Number of meetings<br>conducted/official reports<br>issued by the emergency<br>crisis committee|weekly<br>|COVID-19<br>report<br> <br>|routine data<br>|MOPH<br>|\n|Number of treatment, isolation &<br>quarantine centers preparing daily report <br>|<br>Number of centers<br>preparing daily reports|weekly<br>|COVID-19<br>report<br> <br>|routine data<br>|MOPH<br>|\n|Number of centers assessed monthly<br>(using check list) treatment, isolation &<br>quarantine|Number of centers<br>assessed monthly|monthly<br>|<br>COVID-19<br>report<br> <", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["routine data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000039", "page": 38, "chunk": 0, "title": "Chad - COVID-19 Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/717781588366403375/pdf/Chad-COVID-19-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "routine data", "label": "VAGUE_DATA", "score": 0.5518015623092651, "start": 277, "end": 289, "probe_score": 0.4384, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Potential inputs by IOM and UNHCR:**\n\n\n     - Promote and explore new venues for cooperation and dialogue between Maltese\nAuthorities and reference authorities in countries of transit and origin.\n\n#### **6. CAPACITY BUILDING, RESEARCH AND TRAINING**\n\n\nIt is likely that Malta will continue to be exposed to unpredictable and variable numbers of irregular\narrivals departing from Libya. This means that Malta also needs to continue to develop capacity\nand expertise to deal with its reception and solutions responsibilities, including for unaccompanied\nchildren.\n\n\nIn order to ensure consistency in the quality of services, Malta may consider to set up permanent\ntraining and monitoring mechanisms to ensure quality standards of care for migrant and refugee\nchildren by psycho-social workers and cultural mediators, and maintain standard of care in every\nfacility accommodating unaccompanied children in Malta (addressing migration, asylum status, integration, return and reintegration, relocation and resettlement).\n\n\n**Potential inputs by IOM and UNHCR:**\n\n\n     - Set up a partnership with academia in Malta for a) to design a training curricula\nfor students to specialize in different fields: migration and asylum, psychosocial,\nhealth, age assessment, assistance to VoTs etc b) build a system of data collection and monitoring migration flows with particular focus on migrant children c) to\nconduct research on relevant topics for policy making eg, perceptions of young migrants on concepts and models of protection, factors motivating migratory routes,\nlong term integration prospects in Malta etc.\n\n\n     - Enter into a partnership with the University of Malta and potentially other universities in order to develop modules for a formal academic qualification on migration\nmanagement with focus on child migration. Topics to be included are: reception\nand assessment of needs of migrants, psychosocial assistance to highly vulnerable cases with post-traumatic stress, victims of trafficking, victims of abuse and\nexploitation, cultural mediation, research methodologies addressing child migration and solutions support.\n\n\n     - Set up a system of data collection on migration flows with the university and other\nrelevant entities (eg based on", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data collection on migration flows"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001059", "page": 18, "chunk": 0, "title": "Unaccompanied Migrant and Refugee Children: Alternatives to Detention in Malta", "pdf_url": "https://reliefweb.int/attachments/a0fb8d10-92e9-34e3-99bf-fdeb7f2f9cf4/Unaccompanied-Migrant-and-Refugee-Children-Alternatives-to-Detention-in-Malta.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data collection on migration flows", "label": "VAGUE_DATA", "score": 0.5490440130233765, "start": 2156, "end": 2190, "probe_score": 0.3117, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nStrengthening Insitutions for Refugee Administration Project (P165542)\n\n\nEmployee-related expenses (salaries), operating expenses, and repairs and maintenance expenditures of\nSAFRON and MoI and of the Pakistan Bureau of Statistics are agreed as EEPs (Annex 1).\n\n\n**38.** **For disbursements under Component 2, CCAR will establish a Designated Account (DA) in US**\n**dollars at the National Bank of Pakistan for receipt of funds from the Bank** . These disbursements will be\nreport-based: cash advances equivalent to six months’ expenditure forecast will be provided to the CCAR\nin the DA. The CCAR office will maintain separate books of accounts on the cash basis of accounting to\nrecord receipts and payments under the Project, and transactions will be entered in real time in the\nnational Financial Management Information System (FMIS). The Project’s financial statements will be\nprepared in accordance with the Cash Basis International Public Sector Accounting Standards (IPSAS) and\naudited by the Auditor General of Pakistan (AGP). The audited financial statements will be submitted to\nthe Bank within six months after the close of the financial year.\n\n\n**(ii) Procurement**\n\n\n**39.** **The overall procurement risk is rated High because of limited procurement capacity in the**\n**implementing agency.** SAFRON will be implementing a Bank project for the first time. Procurement risk\nwill be managed by providing additional capacity for procurement and contract management and by\nproviding close oversight of procurement processes and contracts under implementation. Procurement\nunder the Project will be carried out following the World Bank Procurement Regulations for Borrowers.\nThe implementing agency will establish a dedicated Procurement Committee to serve as the review body\nfor procurement documents and bid evaluation recommendations developed by the Project procurement\nspecialist. The committee members will be drawn from the CCAR and other departments. The Bank will", "output": {"entities": {"named_data": ["national Financial Management Information System"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000009", "page": 20, "chunk": 0, "title": "Pakistan - Strengthening Institutions for Refugee Administration Project", "pdf_url": "http://documents1.worldbank.org/curated/en/108361587348120175/pdf/Pakistan-Strengthening-Institutions-for-Refugee-Administration-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "national Financial Management Information System", "label": "NAMED_DATA", "score": 0.6157475113868713, "start": 801, "end": 849, "probe_score": 0.005, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### 1.8 11\n\n\n\nCurrent account balance . **.2**\n\n\n\nFinancing items (net)\nChanges in net reserves .. .\n_Memo:_\nReserves including gold _(US$ millions)_\nConversion rate _(DEC, locaW/US$)_ 177.7 177.7 177.7\n\n\n**EXTERNAL DEBT and RESOURCE FLOWS**\n\n**1979** **1989** **1998** **1999**\n_(US$ millions)_ **Compositlon of total debt, 1998 (USS milIlona)**\nTotal debt outstanding and disbursed 26 **179** 288\nIBRD 0 0 0\nIDA 0 26 50 49 G 15 B\n\nTotal debt service 2 15 6\nIBRD 0 0 0 C: 9\nIDA 0 0 1 1\n\nComposition of net resource flows E: 119\nOfficial grants 5 32 48\nOfficial creditors -1 3 2\nPrivate creditors 0 -1 0\nForeign direct investment 0 0 6 D: **95**\nPortfolio equity 0 0 0\n\nWorld Bank program\n\nCommitments 0 9 3 A  - IBRD E - Bilateral\nDisbursements 0 2 2 1 B - IDA D - Other rrultilateral F **-** Private\nPrincipal repayments 0 0 0 0 C- IMF G - Short-term\nNet flows 0 2 2 1\nInterest payments 0 0 0 0\nNet transfers 0 2 1 1\n\n\nNote: This table was produced from the Development Economics central database. 9/13/00", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000022", "page": 63, "chunk": 1, "title": "Albania - Microcredit Project", "pdf_url": "http://documents1.worldbank.org/curated/en/192291468767658763/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9087857007980347, "start": 960, "end": 998, "probe_score": 0.6996, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "policy objectives and available performance indicators. However, in sum, policies to improve connectivity with global markets could address:\n\nTraditional barriers to trade (from the negotiation of preferential market access to the\nreduction of domestic tariffs);\n\n\n\npolicy objectives and available performance indicators. However, in sum, policies to improve connectivity with global markets could address:\n\n- Traditional barriers to trade (from the negotiation of preferential market access to the\nreduction of domestic tariffs);\n\nCustoms (efficiency and procedures, including rules of origin);\n\nLogistics; and\nTransportation and telecommunications (regulatory and infrastructure dimensions, with a\ngreater focus on telecommunications for the offshoring of services, and transportation for\n\n\n\n\n\n\n\n\n\n\n\n\n|Table 1. Increasing connect Policy objectives|tivity with global markets: Policy objectives and performance indicators Performance indicators Trade restrictiveness Indices – OTRI, TTRI (WTI 1.1)|\n|---|---|\n|**Policy objectives**<br>|<br>**Performance indicators**<br> <br>|\n|<br>**Suppressing/reducing obstacles to trade**<br>**at the border, including trade facilitation**<br> <br>• <br>Suppression of quotas and other<br>quantitative restrictions on imports<br>and exports<br>• <br>Reduction of tariffs, suppression of<br>tariff peaks, tariff escalation or<br>simplification of tariff schedules<br>• <br>Customs modernization and reform,<br>harmonization of procedures and<br>cooperation across borders<br>• <br>Simplification of customs procedures,<br>including SPS, TBT, and other<br>certifications, rules of origin,<br>valuation, etc. to conform with<br>relevant agreements or international<br>best practices<br>• <br>Implementation", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005558", "page": 21, "chunk": 0, "title": "wps6406", "pdf_url": "https://local/prwp/wps6406.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\ncredibility weighting is to cap large losses before the application of credibility theory. Capping burn\ncosts then adding back the probability mass may be actuarially sound as infrequent events lack\nstatistically credibility. A properly chosen cap may not only add stability, but may even make the\nmethodology more accurate by eliminating extremes.\n\n\nThe resulting Pure Premium Rate (PPR) calculation on a portfolio basis does not increase or decrease\nrates relative to the Historical Burn Rate (HBR) calculation; the total weighted average PPR is the\nsame as the total weighted average HBR. Rather, the portfolio approach involves a re-spreading of\nrates between products where any difference in rates is judged to be statistically insignificant.\n\n\n<u>The Pure Premium Rate</u>\n\n\nInsurance products would first be grouped into Risk Collectives (RCs) and Balance Back Collectives\n(BBCs). A RC should contain similar products that are based on different sources of weather data. A\nBBC should contain one or more RCs, for which extreme claim events are expected to be similar in\nnature. For example a RC could include all products for a given crop sold in the same state and a\nBBC could include all products sold in a collection of states in the same agronomic region. The\ngrouping of products into collectives requires both expert judgment and practical considerations.\n\n\nFirst, the HBR is calculated for all products in the same Balance Back Collective, as for the standalone\napproach.\n\n\n7A similar methodology, implemented for part of the mNAIS portfolio by the public insurer, is described in\n(Clarke et al. 2011).\n\n\n14", "output": {"entities": {"named_data": [], "descriptive_data": ["weather data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005160", "page": 15, "chunk": 1, "title": "wps5985", "pdf_url": "https://local/prwp/wps5985.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "weather data", "label": "DESCRIPTIVE_DATA", "score": 0.7108075618743896, "start": 965, "end": 977, "probe_score": 0.9261, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "WE|IDA / 64450|Institutional Strengthening a<br>nd Project Management|Prior|Individual Consult<br>ant Selection|Open - National||23,000.00|0.00|Canceled|2024-03-18||2024-05-06||2024-05-27||2024-07-01||2025-07-01||\n|ET-MOWE-415125-CS-INDV /<br>Selection & Employment of #<br>1 Sanitation and Hygiene indi<br>vidual consultants for Educati<br>on Sector WaSH PMU, by Mo<br>WE|IDA / 64450|Institutional Strengthening a<br>nd Project Management|Post|Individual Consult<br>ant Selection|Open - National||23,000.00|0.00|Canceled|2024-03-18||2024-05-06||2024-05-27||2024-07-01||2025-07-01||\n|ET-MOWE-415126-CS-INDV /<br>Selection & Employment of #<br>1 M & E individual consultant<br>s for Education Sector WaSH<br>PMU, by MoWE|IDA / 64450|Institutional Strengthening a<br>nd Project Management|Post|Individual Consult<br>ant Selection|Open - National||23,000.00|0.00|Canceled|2024-03-18||2024-05-06||2024-05-27||2024-07-01||2025-07-01||\n|ET-MOWE-459556-CS-INDV /<br>Selection and employment of<br>individual consultant (Team l<br>eader/", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:004429", "page": 10, "chunk": 6, "title": "Ethiopia - EASTERN AND SOUTHERN AFRICA- P167794- One WASH?Consolidated Water Supply, Sanitation, and Hygiene Account Project (One WASH?CWA) - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099092325065024865/pdf/P167794-77283df2-b8d7-4756-bddb-c91171dd8c38.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " previous\nemployment background, compared to 50% of men. One possible explanation for this discrepancy is the higher\nproportion of men employed in sectors like construction and IT prior to displacement. These fields often\ndemand fewer country-specific qualifications, such as proficiency in the local language, thereby facilitating\neasier integration into similar roles in the host country.\n\n\n\n**<u>DISTRIBUTION OF WORKING AGE POPULATION BY</u>**\n**HIGHEST EDUCATION LEVEL ATTAINED**\n\n\nTechnical or Vocational Bachelor Master's Doctoral\n\n\n\n**<u>WAGE PREMIUMS FOR EDUCATION LEVEL GAINS: HOSTS</u>**\n**VERSUS REFUGEES, %**\n\n\n\nRefugee eduction\nwage premium\n(mean, 2024)\n\n\nBachelor's or\n\nabove\n\n\n\nHosts (2023)\n\n\nRefugees (2024)\n\n\nSource: Survey data, ILO\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n1%\n\n\n\nHost education wage\npremium (median,\n2022)\n\n\nTechnical or\n\nvocational\n\n\n\nNote: Wage premiums computed with lower secondary education as\nthe baseline\n\n\nSource: Survey data, Eurostat, SAG estimates\n\n\n18. The difference in median wages by highest education level attained. Weighted equivalently to refugee weights for comparability\n19. The wage gap for refugees was computed based on the difference in weighted means (instead of the difference in medians)\n\n\n**13**", "output": {"entities": {"named_data": [], "descriptive_data": ["Survey data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 12, "chunk": 1, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Survey data", "label": "DESCRIPTIVE_DATA", "score": 0.567653477191925, "start": 734, "end": 745, "probe_score": 0.9987, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " ensure close oversight of project activities. A Project\nOperations Manual (MOP) will be prepared within two months after project effectiveness and will describe the\ndetailed project implementation arrangements.\n\n**B. Results Monitoring and Evaluation Arrangements**\n\n\n**53.** **MoITS has the primary responsibility for the monitoring and evaluation of the project.** Operational\noversight of wheat and barley value chains is carried out by MoITS <sup>37</sup> [^37: The Directorate of Inventory Management (in the MoITS) has 5 departments: 1) Department of Bakeries – supervises the registration\nand licensing of bakeries; 2) Mills Department – supervises milling operations; 3) Department for Feedstock – supervises feedstock centers\nand distribution of feed to livestock breeders; 4) Storage Department – supervises the transport and storage of wheat and barley between\nstorage platforms/silos, mills and feed centers. There is a stock unit in all silos for supervision. There is also a truck control system that\nmonitors the transfer of grains to all silos/storage platforms and then to the mills and feed centers. All vehicle and cargo data is monitored.\nIn addition, there is a Directorate of Trade in MoITS that oversees the procurement arrangements for grain. The Contracts Department is\nin charge of the signifying and implementation of contracts with shipping and inspection until the cargo reaches the port of Aqaba in Jordan.\nThe Department of Insurance oversees any delays, insurance, unloading operations and investigations of received quantities.] . All the data of bakeries operating in Jordan\nand the daily allocations are recorded according to their market share and are linked to the mills. Mills keep track\nof sales of flour to bakeries. The information is linked to MoITS and follow up is carried out through a national\noperating system. The project will monitor the number and term of contracts for procurement of grains, including\nvolumes and prices and through the established monitoring systems by MoITS ensure that purchased grains are\navailable for human consumption and animal feed. This will be done through", "output": {"entities": {"named_data": [], "descriptive_data": ["data of bakeries operating in Jordan"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 28, "chunk": 1, "title": "Jordan - Emergency Food Security Project", "pdf_url": "http://documents.worldbank.org/curated/en/486071652556836130/pdf/Jordan-Emergency-Food-Security-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data of bakeries operating in Jordan", "label": "DESCRIPTIVE_DATA", "score": 0.9181310534477234, "start": 1573, "end": 1609, "probe_score": 0.5133, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "technology-based poverty trap, and then we will show that these requirements do not appear to\n\nhold in cross-country and firm-level data.\n\n\n_Theoretical mechanisms_\n\n\nTo be consistent with perfect competition, theoretical models usually assume that\n\nincreasing returns are external to the firm. As surveyed by Caballero and Lyons (1990), standard\n\nexplanations for these economies of scale that are external to the firm but internal to the industry\n\nor country include advantages of within-industry specialization, agglomeration, indivisibilities\n\nand public intermediate inputs such as roads or other infrastructure. Some papers along these\n\nlines include Bryant (1983), Weil (1989) and Durlauf (1991) who introduce some form of\n\nexternality in the production process, and Diamond (1982), Howitt (1985), and Howitt and\n\nMcAfee (1988) who analyze models of search and matching with thick market externalities. Most\n\nof these models, however, are highly stylized and not amenable to calibration. Nevertheless, as\n\nmentioned above they share the common feature that the increasing returns are assumed to be\n\nexternal to the firm, so that, in a model of homogeneous firms, the technology of a representative\n\nfirm _j_ has the form:\n\n\n(8) _Yj_ = _A_ ( _E_ ) _F_ ( _K_ _j_, _L_ _j_ )\n\n\nwhere <sup>_Y_</sup> _j_ <sup>,</sup> _K_ _j_, and <sup>_L_</sup> _j_ <sup>are the total output, capital, and labor of firm</sup> <sup>_j,_</sup> <sup>and</sup> _A_ ( _E_ ), the scale\n\nfactor capturing total factor productivity, depends on", "output": {"entities": {"named_data": [], "descriptive_data": ["cross-country and firm-level data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002845", "page": 26, "chunk": 0, "title": "wps3631", "pdf_url": "https://local/prwp/wps3631.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "cross-country and firm-level data", "label": "DESCRIPTIVE_DATA", "score": 0.6448100805282593, "start": 103, "end": 136, "probe_score": 0.8328, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on social development issues"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011693", "page": 24, "chunk": 0, "title": "Uganda - Energy for Rural Transformation Project", "pdf_url": "https://documents.worldbank.org/curated/en/352661468779120712/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on social development issues", "label": "VAGUE_DATA", "score": 0.581004798412323, "start": 1670, "end": 1703, "probe_score": 0.333, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSPF: Improved Livelihoods for Internally Displaced Persons in Azerbaijan (P178125)\n\n\nmechanism, stakeholder engagement, labor terms and conditions and occupational health and\nsafety, among other applicable requirements.\n\n46. **Fiduciary risks are considered Moderate.** While SCRI did not directly manage funds from\nthe LSLP, FM and Procurement experts who worked in SDFI on the LSLP are now working in SCRI\nand would be engaged in the PIU. These experts have long-term experience with World Bank\nfiduciary requirements and will receive training on any new aspects of FM and Procurement\nintroduced since the closing of the LSLP. There are also no large-scale procurement activities\nincluded in the design, but rather smaller payments to finance training and small goods packages\nfor participants. Strong fiduciary mechanisms will be put in place for the procurement of\nequipment and assets under the project.\n\n47. **Stakeholder risks are Moderate.** There is only one implementing agency responsible for\nimplementation, so intragovernmental coordination should not be complicated. There are\ndifferent development partners and civil society organizations supporting IDPs, so coordination\nwith these partners would be important. Existing Government-convened coordination bodies\nwould be used to facilitate information sharing and collaboration with other organizations that\nare engaged in supporting IDPs. In addition, a Selection Committee will be formed to make\ndecisions regarding the selection of project beneficiaries and the provision of supplies and\nequipment under Component 2.\n\n\n**VI.** **APPRAISAL SUMMARY**\n\n\n**Technical, Economic and Financial Analysis**\n\n\n48. Most of the technical design of the project has been implemented under the Youth\nSupport Program (YSP) which was a subcomponent of the LSLP. These activities were\nimplemented between 2018 and 2020 and evaluated using baseline and endline data collected\nfrom 827 persons out of the total number of 833 individuals that had participated in the YSP. This\nsurvey", "output": {"entities": {"named_data": [], "descriptive_data": ["baseline and endline data collected\nfrom 827 persons"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000007", "page": 22, "chunk": 0, "title": "Azerbaijan - State and Peacebuilding Fund (SPF) : Improved Livelihoods for Internally Displaced Persons in Azerbaijan Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099730012222232813/pdf/P1781250bdd2b50b0b9720d5c17632331c.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "baseline and endline data collected\nfrom 827 persons", "label": "DESCRIPTIVE_DATA", "score": 0.5874149203300476, "start": 1907, "end": 1959, "probe_score": 0.7237, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Students of **Sudanese** origin were the fifth largest group (311 students) supported by the DAFI programme. The number\nof Sudanese refugee students increased by 74% to the previous year. Only 17% of South Sudanese DAFI students were\nyoung women, mainly because of low secondary enrolment and completion rates. Additionally, a lack of employment\nperspectives, family funds and roles and responsibilities associated with a young Sudanese women pose barriers to higher\neducation (see also chapter 4.1). 55% of the students studied in Ethiopia, followed by Chad (16%) and Uganda (11%). The\nremaining 19% studied in Kenya, Egypt, South Sudan and India.\n\n\nTable 2 above shows trends in the choice of field of studies among DAFI students who are requested and supported\nto enrol in programmes with good chances for gaining an income after graduation. Medical science and health related\nprogrammes remain to be popular, as well as engineering, commercial and business, and social and behavioural science.\nEducation and teacher training ranked sixth. Further details are provided in <u>chapter 4.3.</u>\n\n\n**3.2 REGIONAL DYNAMICS**\n\n\nThe following chapters provide an overview of all five regions in which the DAFI programme was implemented in 2016,\nsupplemented by detailed country factsheets at the end of the report. The highest number of DAFI-supported countries\n(20 out of 37) are placed in Sub-Saharan Africa. 41% of all DAFI students studied in Sub-Saharan Africa. In the MENA\nregion DAFI scholarships are available in seven countries where a quarter of all DAFI supported students studied. Four\ncountries in Europe offered DAFI scholarships, including Turkey with the largest number of DAFI scholarships. 18% of all\nDAFI students studied in Europe. In Asia and the Pacific the DAFI programme is implemented in five countries, hosting\n16% of all DAFI students. In the Americas", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000537", "page": 16, "chunk": 0, "title": "DAFI 2016 Annual report", "pdf_url": "https://reliefweb.int/attachments/4d569d8e-1ba4-3f2f-a0c1-80d766ed85ea/5aaba2597.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "1. **Project alternatives** **considered** **and reasons for rejection:**\nDesln Alternative 1: Discontinue IDA support for the Emergency Recovery Support Fund\n(ERSF) and its successor, the National Social Action Project (NSAP). This option was rejected because\navailable evidence suggests that the on-going Community Reintegration and Rehabilitation Project\n(CRRP Cr. 3312-SL) has been successful. Although definitive audit and evaluation data are not yet\navailable, CRRP financed over 250 sub-projects that benefited extremely poor and devastated\ncommunities, including some areas of the country where security was marginal at best. NaCSA has been\nthe Government entity that has delivered much needed support to the population\n\n\nDesign Alternative 2: Withhold IDA support for NaCSA's newly-instituted Public Works\nProgram. This option was rejected for three reasons. First, the need to restore infrastructure beyond the\ncommunity sub-projects is urgent, especially in the newly accessible areas. Proposed works (e.g.\nrehabilitation of feeder roads and drainage systems) would complement other projects currently being\nimplemented by NaCSA. Second, IDA support for this program would provide an opportunity for\nNaCSA to develop a capacity building program for local administrators. This initiative, in the context of\nthe Public Works Program, would support the Government's decentralization policy and introduce a\nresults-based model of governance at the local level that would facilitate the gradual delegation of\nadditional implementation responsibilities to local authorities. Finally, labor intensive techniques will be\nused to employ ex-combatants and unemployed youth, to reduce the risk that they would turn to\nnon-legitimate income generating activities if they remain unemployed.\n\n\nDesien Alternative 3: Provide support for NaCSA's micro-credit program. The AfDB will\ncontinue to support micro-finance activities through the Government's Social Action and Poverty\nAlleviation (SAPA) program. A mnicro-finance policy", "output": {"entities": {"named_data": [], "descriptive_data": ["audit and evaluation data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000151", "page": 15, "chunk": 0, "title": "Bosnia and Herzegovina - Third Electric Power Reconstruction Project", "pdf_url": "http://documents1.worldbank.org/curated/en/873371468767980151/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "audit and evaluation data", "label": "DESCRIPTIVE_DATA", "score": 0.6453143954277039, "start": 418, "end": 443, "probe_score": 0.8111, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "summarizes the data sources and variable de…nitions. To ensure adequate coverage for\n\n\neach country, we excluded information for nations that do not have at least three con\n\nsecutive years of tari¤ and rainfall data. Table A.2 lists the countries and corresponding\n\n\ntime periods covered in our sample, while Table A.3 details the product classi…cation we\n\n\nemploy. To identify agricultural products we use the UN statistics division of the SITC\n\n\nclassi…cation. For robustness, we also consider a broader de…nition that includes as well\n\nother agricultural products. <sup>16</sup> [^16: As shown in Table A.3, this latter de…nition includes as well SITC product categories \"08\", \"09\", \"11\",] Irrigation data are available for 32 of the 70 countries ini\n\ntially considered. These data generally refer to the 2001-2009 period, but the extent of\n\n\ntime coverage di¤ers across countries. We therefore use the average value of this variable\n\n\namong non-missing observations for each of the 32 countries as a (time-invariant) proxy\n\n\nfor access to irrigation at the country-level.\n\n\nFigure 1 provides illustrative evidence on the rainfall variable we employ for a subset of\n\n\ncountries. The dashed lines in these diagrams refer to major, widely-documented droughts\n\n\nobserved in each nation. Many of these extreme weather events were associated with the\n\n\nEl Niño or La Niña phenomena, including Argentina (1999), Bolivia (1998), Brazil (1998,\n\n\n2003), Colombia (1992, 1997), Chile (1998), Costa Rica (2001), Guatemala (1997, 2001)\n\n\nand Peru (2000).\n\n\n[Figure 1 about here]\n\n\nOur theory applies to countries that have discretion to set import tari¤s on agricultural\n\n\ngoods. A potential concern is that, in reality, tari¤ setting might be constrained by limits\n\n\nassociated with GATT/WTO membership. As shown in Figure 2, however, countries\n\n\ntypically set their tari¤s on agricultural goods well below", "output": {"entities": {"named_data": [], "descriptive_data": ["Irrigation data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005546", "page": 17, "chunk": 0, "title": "wps6394", "pdf_url": "https://local/prwp/wps6394.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Irrigation data", "label": "DESCRIPTIVE_DATA", "score": 0.7538541555404663, "start": 693, "end": 708, "probe_score": 0.9363, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".00\n0.5 1\n\n\n\n**Component I: Strengthening Health Services** **9.79** **6.41** **16.19**\n1, A. Am6liorer l a couverture et de la qualit6 des soins 4.25 5.48 9.73\n2. B. Mobiliser la participation communautaire 3.40 0.50 3.90\n3. C. Assurer l a qualit6 des soins 2.14 0.42 2.56\n**Component** **_11:_** **Institutional Strengthening** **5.72** **1.43** **7.14**\n1. A. Assurer l e suivi et Evaluation 1.91 0.21 2.12\n2. B. Bureau de Gestion du Projet 0.80 0.03 0.83\n3. C. Renforcer les capacitds en gestion programmatique 0.44 0.58 1.02\n4. D. Renforcer les CapacitCs de gestion financibres 0.96 0.00 0.96\n5. E. Renforcer les capacitks de contractualisation 0.92 0.10 1.02\n6. F. Assurer l a suivi des depenses de sante 0.00 0.00 0.05\n_7._ G. Renforcement d'un systeme national d'assurance maladie 0.69 0.5 1 1.20\n\n**Refinancement de I'Avance PPF** **0.43** **0.00** **0.43**\n**Total Baseline Cost** **15.93** **7.83** **23.77**\n\n\n\n**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000092", "page": 36, "chunk": 1, "title": "Guinea - Health Sector Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/551731468037482453/pdf/28046.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nETHIOPIA WOMEN ENTREPRENEURSHIP DEVELOPMENT PROJECT ADDITIONAL FINANCING (P174874)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Equivalent measure at<br>baseline|Col3|Col4|Col5|Col6|Col7|\n|---|---|---|---|---|---|---|\n|Direct project beneficiaries (Digital<br>Training)||Quarterly<br>|IFWE pilot and<br>impact<br>evaluation<br>data<br>|survey and M&E data<br>from IFWE pilots<br>|World Bank and FUJCFSA<br>|World Bank and FUJCFSA<br>|\n|Citizen Engagement Survey<br>|A citizen engagement<br>survey will be provided to a<br>sub-set of beneficiaries and<br>designed to assess overall<br>satisfaction of services<br>(including ease of access,<br>quality, process, disclosure,<br>responsiveness of needs,<br>etc). The results of the<br>survey will be analyzed and<br>assessed in a report, which<br>will also contain proposed<br>recommendations for<br>project adjustments<br>informed by citizen<br>feedback.|<br> <br> <br>Annual<br>||survey<br>|World Bank and FUJCFSA<br>|World Bank and FUJCFSA<br>|\n\n\n\n\n\nNovember 25, 2020 Page 48 of 62", "output": {"entities": {"named_data": ["Citizen Engagement Survey"], "descriptive_data": ["survey and M&E data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007950", "page": 51, "chunk": 0, "title": "Ethiopia - Women Entrepreneurship Development Project : Additional Financing", "pdf_url": "https://documents.worldbank.org/curated/en/103061607914878676/pdf/Ethiopia-Women-Entrepreneurship-Development-Project-Additional-Financing.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey and M&E data", "label": "DESCRIPTIVE_DATA", "score": 0.8266993165016174, "start": 332, "end": 351, "probe_score": 0.6203, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Citizen Engagement Survey", "label": "NAMED_DATA", "score": 0.8383843302726746, "start": 432, "end": 457, "probe_score": 0.6041, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "output": {"entities": {"named_data": [], "descriptive_data": ["household expenditure survey data", "data from the Household Survey"], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000029", "page": 38, "chunk": 1, "title": "West Bank and Gaza - Health System Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/221361468779450522/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household expenditure survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8699104189872742, "start": 565, "end": 598, "probe_score": 0.7323, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.5808603167533875, "start": 870, "end": 881, "probe_score": 0.1461, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from the Household Survey", "label": "DESCRIPTIVE_DATA", "score": 0.5346028804779053, "start": 1978, "end": 2008, "probe_score": 0.1121, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "the needs and demands of the participating municipalities, with an anticipated peak demand at\nthe outset of the Project.\n\n\n19. The Project will seek the services of UNDP to implement this component in year one\nthrough the contracting by MOMA of UNDP. UNDP is already providing technical assistance to\nmunicipalities through an existing MOU with MOMA and is already working at the municipal\nand governorate levels conducting focus groups for verifying community needs. Partnering with\nUNDP will ensure that the Project benefits from and builds on UNDP’s existing network and\nlocal knowledge. It will also help the Project mobilize support to municipalities rapidly and\nenhance on-the-ground cooperation and synergies among various donors and development\nprograms. UNDP will provide assistance in the areas of:\n\n\n  - _Technical capacity:_ It is expected that the initial subprojects identified through the\n\nmunicipal focus groups will cluster around the core competences of the municipalities,\nsuch as solid waste management, roads and transportation, street lighting and small scale\ncommunity infrastructure. While category A municipalities will have some existing\ncapacity to rapidly expand services in these areas, other categories of municipalities may\nneed additional resources for planning, engineering, procurement and subproject\nimplementation — which will be provided under the Project.\n\n\n  - _Participation and social accountability:_ Taking advantage of the elections to municipal\n\ncouncils that were held in late-August, support will be provided to municipalities to reach\nout to their citizens and communities (especially hard-to-reach or vulnerable groups),\norganize more comprehensive participatory needs identification and prioritization\nprocesses, and establish institutional modalities for grievance redress. In collaboration\nwith the PMU in charge of strategic communication at the Project level, support would\nalso be given to municipalities to enhance transparency in the utilization of grant funds\nby facilitating citizens’ ability to monitor municipal investments and performance.\n\n  - _Local economic development:_ Based on the participatory needs identification and\n\nprioritization, UNDP will facilitate and support governorates and municipalities in\nanalyzing and assessing the local opportunities and challenges for economic growth and", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000089", "page": 42, "chunk": 0, "title": "Jordan - Emergency Services and Social Resilience Project", "pdf_url": "http://documents1.worldbank.org/curated/en/532171468273353365/pdf/PAD7230P1476890AD0October0100final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n\n**<u>HOUSEHOLD INCOME DISTRIBUTION BY SOURCE AND POVERTY CATEGORY</u>**\n\n\n\nEmployment Family support Social\nprotection\n(host country)\n\n\n\nOld age\npension\n(Ukraine)\n\n\n12%\n\n\n67%\n\n\n\nSocial\nprotection\n(Ukraine)\n\n\n35%\n\n\n\nHumanitarian\ncash\n\n\n8%\n\n\n\n13%\n\n\n\n23%\n\n\n\n6%\n\n\n\nOther\n\n\n5%\n\n\n3%\n\n\n\n3%\n\n\n5%\n\n\n\nBelow the poverty line\n\n\nBelow the poverty line after housing\n\ncost correction\n\n\nAbove the poverty line after housing\n\ncost correction\n\n\nSource: Survey data, SAG estimates\n\n\n\n26%\n\n\n\n88%\n\n\n\n**Higher employment earnings were the main driver behind the drop in poverty rates from**\n**2023**\n\n\nThe mean monthly equivalized household income <sup>12</sup> [^12: Household disposable income adjusted for size, as per Eurostat’s methodology] of Ukrainian refugees across the seven countries surveyed\nin both rounds increased by 38% from last year, to an equivalent of EUR 763. This increase was much higher\nthan the 4% rise in the regional poverty threshold over the same time.\n\n\nApproximately 90% of the increase in refugee household income can be attributed to higher employment\nearnings, driven by a combination of rising employment rates and wage growth. A significantly smaller, though\nstill notable, contribution came from increased financial support from families in Ukraine, although this finding\nmay partially be an artifact of adjustments to the survey questionnaire <sup>13</sup> .\n\n\n**<u>WEIGHTED AVERAGE MONTHLY EQUIVALIZED INCOME EVOLUTION, EUR</u>**\n\n\n800\n\n\n600\n\n\n400\n\n\n200\n\n\n\n0\n\n\n\nFamily\nsupport\n\n\n\nHost country\n\nsocial\nprotection\n\n\n\nUkraine\n\nsocial\nprotection\n\n(inc.\npensions)\n\n\n\nHumanitarian\n\ncash\n\n\n\nEquivalized\n\n\n\nEmployment\n\nincome\n\n\n\nOther Equivalized\n\n\n\nincome\n\n\n\n2024\n\n\n\nincome\n\n\n\n2023\n\n\n\nNote: Only includes data from the 7 countries surveyed in both rounds (Bulgaria, Czech Republic, Hungary, Republic of Moldova, Poland, Romania, and\nSlovakia)\n\n\nSource", "output": {"entities": {"named_data": [], "descriptive_data": ["Survey data", "data from the 7 countries surveyed in both rounds"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 8, "chunk": 0, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Survey data", "label": "DESCRIPTIVE_DATA", "score": 0.6597267985343933, "start": 544, "end": 555, "probe_score": 0.9981, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from the 7 countries surveyed in both rounds", "label": "DESCRIPTIVE_DATA", "score": 0.5191153883934021, "start": 1824, "end": 1873, "probe_score": 0.9846, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Consumption items are partitioned into modules. Each household is administered only one randomly\n\nassigned module, creating significant time savings and making it possible to administer a full questionnaire\n\nincluding household and individual questions in less than 60 minutes. The full consumption estimate is\n\nobtained by imputing the deliberately absent consumption values for items that are not explicitly asked for\n\na specific household, but was administered to other households. The methodology makes it possible to\n\nderive poverty estimates without compromising the credibility of the resulting estimate, and it performs\n\nconsiderably better than alternative approaches based on reduced consumption aggregates and cross-survey\n\nimputations. The methodology has been widely applied especially in the context of FDPs in Ethiopia,\n\nKenya, Nigeria, Somalia, South Sudan and Sudan (Pape et al., 2019a; Pape et al., 2019b) to allow for shorter\n\ninterview time, creating space for in-depth displacement-specific questions while reducing enumerator and\n\nrespondent fatigue.\n\n\nAn alternative way to obtain accurate consumption estimates without limiting the time of the interview can\n\nbe borrowed from small-area estimation methods (Elbers, Lanjouw and Lanjouw, 2002; Molina and Rao,\n\n2010). This approach administers the full consumption module only to a small subset of households, while\n\nthe majority of households do not receive any consumption questions. Instead, within-survey imputations\n\nare used to impute consumption for this part of the full sample. This approach avoids the pitfalls of cross\nsurvey imputations while improving accuracy as compared to assigning subsets of consumption items\n\nacross all households. <sup>10</sup> [^10: Accuracy improves compared to Pape (2021) because distributing consumption modules across households ignores\ncorrelation between consumption modules in the imputation. The small-area estimation approach, in contrast,\nestimates full consumption for a subset of households automatically considering any within correlations.] However, the subset of households with full consumption modules might suffer\n\nfrom questionnaire fatigue increasing measurement error, which can ultimately exceed the model error in\n\napproaches like Pape (2021).\n\n\nAfter consumption data is obtained, questions arise on how to value consumption. FDPs often receive aid", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["consumption data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001130", "page": 17, "chunk": 0, "title": "idu0f21f2e9f0f7b704c420a5af038bbbbb4f592", "pdf_url": "https://local/prwp/idu0f21f2e9f0f7b704c420a5af038bbbbb4f592.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "consumption data", "label": "VAGUE_DATA", "score": 0.7445372939109802, "start": 2287, "end": 2303, "probe_score": 0.521, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Table 17** **Estimates of the tariff equivalents of ad valorem and specific tariffs**\n**and tariff rate quotas on Tunisian imports, 2001 (percent)**\n\n\n\n_Sector_ _Imports from EU_ _Imports from_\n\n_GAFTA_\n\n\n\n_Imports from Rest_\n\n_of World_\n\n\n\nLive animals, products 87.9 18.8 75.4\nDairy products 60.7 9.2 108.3\nCoffee, etc, sugar, cut flowers 78.6 20.9 21.2\nFruit and veg 74.0 67.0 85.1\nCereals 87.7 15.4 56.6\nOil seeds and fats 14.7 114.1 21.8\nBeverages and tobacco 32.5 17.2 34.8\nOther agricultural products 28.4 12.4 45.9\nFish and products 41.4 20.4 27.0\nMineral products 7.2 6.0 16.4\nMetals, products 9.3 16.7 27.0\nChemical etc 6.0 7.9 25.9\nLeather products 14.5 21.0 38.1\nWood products, pulp, paper 16.8 14.6 25.6\nTextiles and apparel 18.0 9.0 32.6\nTransport equipment 7.5 13.4 19.5\nOther machinery and equipment 7.9 7.4 18.2\nElectrical machinery 4.8 12.4 20.3\nOther manufacturing <u>21.7</u> <u>19.3</u> <u>34.0</u>\n\n\n_Source_ : GTAP version 6 database.\n\n\n47", "output": {"entities": {"named_data": ["GTAP version 6 database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004531", "page": 48, "chunk": 0, "title": "wps5341", "pdf_url": "https://local/prwp/wps5341.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "GTAP version 6 database", "label": "NAMED_DATA", "score": 0.9166687726974487, "start": 935, "end": 958, "probe_score": 0.9992, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 40</mark>\n<mark>percent of households report that there are areas in the community where women and girls are not</mark>\n<mark>allowed to go.</mark>\n\n<mark>The main barriers to movement reported for women and girls across all population groups are mahram</mark>\n<mark>requirements, followed by discrimination and the lack of civil documentation, the latter underlining how</mark>\n<mark>women and girls’ limited access to civil documentation disproportionately impacts on their daily lives.</mark>\n\n\n<mark>Education centres are most prominently among the places not fully accessible for women and girls</mark>\n<mark>followed by markets, health clinics and waterpoints. The significant number of women and girls that</mark>\n<mark>may not be able to access lifesaving health services at clinics within their community is of particular</mark>\n<mark>concern.</mark>\n\n\nUNHCR / August 2024 4", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000920", "page": 3, "chunk": 1, "title": "Afghanistan Protection Brief - August 2024", "pdf_url": "https://reliefweb.int/attachments/884b0a08-73d3-4bb7-b920-c9a4d77322b8/Protection%20Brief%20-%20Afghanistan%20-%2028%20August%202024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "##### **1 Introduction**\n\nMigration is one of the most politically polarizing issues in advanced countries. This is reflected\n\n\nin the way migration and its effects are described in the news. While some studies look at\n\nhow migration-related news influences public opinion and votes in destination countries, <sup>1</sup> little\n\n\nis known about the effect of changes in the sentiment of migration-related news in destination\n\n\ncountries on _en_ _route_ migrants and their migration choices. Investigating this matter is impor\n\ntant to better understand the impact of the increasing use of an aggressive tone by populist\n\nleaders trying to discourage migrants from seeking entry into Europe or the US. <sup>2</sup>\n\n\nThis paper studies how changes in the sentiment of migration-related news published in mi\n\ngrants’ preferred destination countries affect migrants’ movements within Libya and the timing\n\n\nof their journey to these countries. Libya is the country with the largest number of international\n\nmigrants in all of North Africa and the major gateway from Africa to Europe. <sup>3</sup> By showing to\n\n\nwhat extent changes in the news sentiment in destination countries impact the choices of mi\n\ngrants in Libya, we contribute to a better understanding of the determinants of the movements\n\n\nalong the most important irregular migration route to Europe.\n\n\nOur analysis combines two main data sources. First, we use data on migrants located in\n\n\nLibya during the period 2017-2020 collected by the International Organization for Migration\n\n\n(IOM). Even though some migrants plan to remain in the country, for most of them Libya\n\n\nis a transit country towards their final destination. While in Libya, migrants often stay for\n\n\nlong periods in the same location, live in rented houses, and have an (informal) job (IOM,\n\n\n2018a). During their stay in the country, migrants often move across locations several times,\n\n\nusing different internal routes according to their nationality (Di Maio", "output": {"entities": {"named_data": [], "descriptive_data": ["data on migrants located in\n\n\nLibya"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001310", "page": 3, "chunk": 0, "title": "idu15106e1d115d5e14819185f71a49e5ec89065", "pdf_url": "https://local/prwp/idu15106e1d115d5e14819185f71a49e5ec89065.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on migrants located in\n\n\nLibya", "label": "DESCRIPTIVE_DATA", "score": 0.9168266654014587, "start": 1423, "end": 1458, "probe_score": 0.9592, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "A. If score equal to target for FY, full allocation,<br>B. If score below target for FY, pro-rata reduction,<br>C. If score above target for FY, pro-rata increase.<br> <br>Disbursement will be made provided that previous disbursements from GoU<br>to LGs have all been made.<br> <br>Formula for disbursement from the Bank to GoU in the FY 2018/19,<br>2019/20, 2020/21, 2021/22:|\n\n\n41", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000014", "page": 48, "chunk": 2, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents1.worldbank.org/curated/en/143681526614252328/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nBeirut Housing Rehabilitation and Cultural and Creative Industries Recovery (P176577)\n\n\n\n\n\n|Col1|financial support through<br>the project in the<br>reconstruction of their<br>residential unit from the<br>PoB explosion.<br>Rationale: 100 rental<br>contracts x 3.5 people/HH|Col3|and<br>Evaluation<br>Reports. Esti<br>mates by<br>Project<br>Management<br>Team.|disaggregating the<br>beneficiary data of the<br>progress reports|Team/UN-Habitat|\n|---|---|---|---|---|---|\n|Direct beneficiaries of cultural production<br>work|Number of people including<br>cultural practitioners,<br>individuals in cultural<br>entities and additional<br>workers involved in the<br>implementation of the<br>cultural productions.|Quarterly<br>|Progress,<br>Monitoring<br>and<br>Evaluation<br>Reports.<br>Third-Party<br>Monitoring<br>Agent<br>reports.<br>Estimates by<br>Project<br>Management<br>Team.<br>|Number of<br>beneficiaries will be<br>tracked in the progress<br>reports through<br>reporting updates by<br>each grant recipient of<br>the total number of<br>people participating on<br>each cultural<br>production work<br>|Project Management<br>Team/UN-Habitat<br>|\n|Of which, are female|Number of females<br>including cultural<br>", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["beneficiary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 40, "chunk": 0, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "beneficiary data", "label": "VAGUE_DATA", "score": 0.6853852868080139, "start": 400, "end": 416, "probe_score": 0.0908, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["M&E data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010754", "page": 29, "chunk": 2, "title": "Ethiopia - Second Road Sector Development Support Project (RSDSP II)", "pdf_url": "https://documents.worldbank.org/curated/en/287381468771238509/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "M&E data", "label": "VAGUE_DATA", "score": 0.5883201956748962, "start": 530, "end": 538, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "/sup>\n\n1+( _ε_ <sup>_L_</sup> _w_ <sup>)</sup> <sup>_it_</sup> <sup>where</sup>\n\n\n\n( _ε_ <sup>_L_</sup> _w_\n\n\n\n\n<sup>_L_</sup> _w_ <sup>)</sup> <sup>_it_</sup> <sup>_∈ℜ_</sup> <sup>+</sup> <sup>is the wage elasticity of labor supply.</sup> <sup>Hence, if wages tend to be inelastic with</sup>\n\n\n\nrespect to labor supply, then firms are likely to compress wages when faced with increased\n\n\ncompetition.\n\n\n\n(a)\n\n\n\n\n\n(b)\n\n\n\n\n\n\n\n(c)\n\n\n\n(d)\n\n\n\nFigure 4: Trends in Employment Level and Real Wage\n\n\n**_Source:_** Author’s analysis based on data from the World Bank Regional Project on Enterprise Development (RPED) and Ghana Manufacturing Survey (GMES) from 1992 to 2003.The surveys were\nconducted by the Centre for the Study of African Economies (CSAE) at the University of Oxford,\nUniversity of Ghana, and Ghana Statistical Service.\n**_Note:_** Panels (a) & (b) present trend in average employment and real wages for small, medium, and\nlarge firms. Employment data is reported in levels while real wage data is indexed with 1991=100.\nPanels (c) & (d) repeats the analysis in Panel (a) & (b) respectively for only small and medium firms.\n\n\nFigure 4 shows the trend in average employment levels and real wages across the three\n\ncategories of firm sizes.", "output": {"entities": {"named_data": ["World Bank Regional Project on Enterprise Development", "Ghana Manufacturing Survey"], "descriptive_data": [], "vague_data": ["Employment data", "real wage data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001845", "page": 20, "chunk": 1, "title": "markups market imperfections and trade openness evidence from ghana", "pdf_url": "https://local/prwp/markups-market-imperfections-and-trade-openness-evidence-from-ghana.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Bank Regional Project on Enterprise Development", "label": "NAMED_DATA", "score": 0.9132811427116394, "start": 547, "end": 600, "probe_score": 0.9896, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Ghana Manufacturing Survey", "label": "NAMED_DATA", "score": 0.9232840538024902, "start": 612, "end": 638, "probe_score": 0.9756, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Employment data", "label": "VAGUE_DATA", "score": 0.7429737448692322, "start": 944, "end": 959, "probe_score": 0.8446, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "real wage data", "label": "VAGUE_DATA", "score": 0.6888981461524963, "start": 988, "end": 1002, "probe_score": 0.6214, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " This is a commission and <sup>is expected to recruit its key</sup>\n\nfinancial staff. accounting staff at competitive <sup>salaries. The staff to</sup> <sup>be</sup>\nrecruited would be required <sup>to have a mmnimum</sup>\n\n\n                                - 47", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000176", "page": 51, "chunk": 5, "title": "Sierra Leone - National Social Action Project", "pdf_url": "http://documents1.worldbank.org/curated/en/976421468759851028/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nGenerating Growth Opportunities and Productivity for Women Enterprises Uganda Project (P176747)\n\n\n**B. Results Monitoring and Evaluation Arrangements**\n\n\n**Monitoring and Regular Reporting**\n\n79. **Objectives and design** . The objective of the M&E system is to track the project’s implementation progress and\nachievement of expected outcomes to enable the government (national and sub-national) and World Bank to address\nissues as they arise. An integrated web-based data collection platform will be established at the MGLSD into which data\non implementation progress and outcomes will be entered will be entered to track implementation of project\ninterventions and their outcomes. The MGLSD will contract a consulting firm to design and develop the integrated data\nplatform, which will include an interface that allows the persons responsible for M&E at all implementing agencies to\nenter monitoring data that they collect.\n\n80. **The MGLSD will lead the overall M&E efforts.** The MGLSD already has an experienced Planning Unit which has\nbeen responsible for leading the efforts to track government programs. Staff with specialized skills in (a) survey design,\nimplementation, and analysis; (b) operations and maintenance of management information systems; and (c) data\nmanager; and (d) others as needed will comprise the M&E team at the MGLSD.\n\n81. **M&E teams will be established as members of the PITs at both the national.** They will be responsible for collecting\nand sharing information presented in the results framework in accordance with the procedures laid out in the M&E\nmonitoring plan, and entering the data into the integrated data platform. Data from each implementing agency will be\naggregated with the data of others and used as the basis of quarterly progress reports.\n\n82. **Data generation and reporting** . The data to track the key performance indicators come from (", "output": {"entities": {"named_data": [], "descriptive_data": ["Data from each implementing agency"], "vague_data": ["monitoring data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000088", "page": 36, "chunk": 0, "title": "Uganda - Generating Growth Opportunities and Productivity for Women Enterprises Uganda Project", "pdf_url": "http://documents1.worldbank.org/curated/en/527091655323259747/pdf/Uganda-Generating-Growth-Opportunities-and-Productivity-for-Women-Enterprises-Uganda-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "monitoring data", "label": "VAGUE_DATA", "score": 0.6173052191734314, "start": 910, "end": 925, "probe_score": 0.0303, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Data from each implementing agency", "label": "DESCRIPTIVE_DATA", "score": 0.7661868333816528, "start": 1678, "end": 1712, "probe_score": 0.1516, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Two Afghan asylum-seekers are on their way**\n**to meet smugglers,\u0003** who they hope will help\nthem cross into Hungary in the European Union.\nThey walk through the grounds of a Serbian brick\nfactory, uncertain about what the future holds.\n\n\n**14** UNHCR Asylum Trends 2014", "output": {"entities": {"named_data": ["UNHCR Asylum Trends 2014"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000195", "page": 13, "chunk": 0, "title": "UNHCR Asylum Trends 2014: Levels and Trends in Industrialized Countries", "pdf_url": "https://reliefweb.int/attachments/13c6c725-6f6b-390e-b8a1-95582c5f7d14/551128679.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR Asylum Trends 2014", "label": "NAMED_DATA", "score": 0.8631131649017334, "start": 248, "end": 272, "probe_score": 0.9994, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "SOCIO-ECONOMIC INCLUSION AND LIVELIHOOD\n\n\nAs we can see in figure 62, most respondents or\nfamily members are working in person at the\ncompany they are employed at (77%), while the\nother 21% either work remotely in Ukraine (11%),\nremotely in other countries outside of\n\n\nFigure 62 **| Work modality of employed respondents**\n\nN=651\n\n\nIn person employment, in Romania\n\n\nRemote employment, in Ukraine\n\n\nHybrid employment, in Romania\n\n\nRemote employment, other country\n\n\nRemote employment, in Romania\n\n\n\n\n\nUkraine (3%), through a flexible/hybrid\narrangement in Romania (4%), or remotely in\nRomania (3%). Two per cent prefer not to answer\nor do not know how to answer.\n\n\n77%\n\n\n\n\n\n\n\nDo not know\n\n\nPrefer not to answer\n\n\nThe question regarding the main difficulties in\nfinding work targeted both the respondents and\ntheir household members of working age\n(N=1618). According to the figure presented, the\n\n\nFigure 63 **| Main employment barriers**\n\nN=1618\n\n\nLack of knowledge of local language\n\nLack of decent pay\n\nLack of flexible schedule\n\nLack of skills\n\n\n\n\n\n\n\nmain barrier in finding work is the lack of\nknowledge of the local language (Romanian),\nreported by 36% of cases. Fourteen per cent\nmention the lack of decent pay, while another 11\n\n\n36%\n\n\n\n\n\nNeed to care for others\n\nLack of opportunities for my age\n\nLack of childcare facilities\n\nLack of formal work\n\nLack of education\n\nLack of other documentation\n\nLack of working permit\n\nPrefer not to answer\n\nLack of transportation\n\nDiscrimination\n\nNot planning to stay\n\nLack of information\n\nOther\n\nPrefer not to answer\n\n\n\n\n\n\n\n\n\n56\n\n\n\nSOCIO-ECONOMIC INSIGHTS SURVEY FINAL REPORT, ROMANIA 2024", "output": {"entities": {"named_data": ["SOCIO-ECONOMIC INSIGHTS SURVEY"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001333", "page": 56, "chunk": 0, "title": "Romania Socio-Economic Insights Survey (SEIS) 2024 - Final Report", "pdf_url": "https://reliefweb.int/attachments/cd5961a4-039a-582e-8b9a-1a66f308a256/Romania%20Socio-Economic%20Insights%20Survey%202024%20-%20Final%20Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SOCIO-ECONOMIC INSIGHTS SURVEY", "label": "NAMED_DATA", "score": 0.8907201290130615, "start": 1578, "end": 1608, "probe_score": 0.9929, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " The dependent variable is the annual remittances reported by the migrant. Additional controls consist o **f**\nyears of education and indicators for whether a wife is employed, unaware of her husband's expenses, having\ndisagreements over remittance uses, and if the migrant spends on temptation goods. All regression includes a **c**\nterm. Bootstrapped standard errors (with 500 replications) are displayed in parenthesis, clustered at the district\n\n\n\nonstant\n\n\n\nlevel.\n\n\n\n*** denotes statistical significance at the 1% level, ** at the 5% level and * at the 10% level.\n_Source:_ Authors’ analysis based on data from QSKF.\n\n\nTable 3 presents the OLS estimates of equation (12), where column 1 is the basic\n\n\nremittance regression that excludes the reported earnings ratio. Column 2 is the same regression,\n\n\nnow augmented with the reported earnings ratio that is statistically significant at the 1 percent\n\n\nlevel. The overall fit of the regression substantially improves with the addition of the earnings\n\n\nratio. Remittances sent home are about 6 percent higher when the reported earnings ratio is 10\n\n\npercent larger. In column 3, we also include the predictors of the earnings ratio explored in table\n\n\n2 and find that the correlates of the reported earnings ratio are not statistically different from zero\n\n\nat conventional levels, individually and collectively. <sup>20</sup> This suggests that the earnings ratio can\n\n\n20. An F-test of joint significance yields a p-value of 0.47.\n\n\n27", "output": {"entities": {"named_data": ["data from QSKF"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006424", "page": 28, "chunk": 1, "title": "wps7368", "pdf_url": "https://local/prwp/wps7368.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from QSKF", "label": "NAMED_DATA", "score": 0.8196657299995422, "start": 607, "end": 621, "probe_score": 0.9728, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "جال التعليم والصحة ومن القسائم الغذائية\n\nلكترونية .. وسيُصار إلى جمع كافة البيانات التي تفصل بين الذكور واإلناث للتمكّن من رصد مشاركة النساء والفتياتاإل\n\nإلى ذلك، سترصد المؤشرات الوسيطة الوعي وفعالية البرنامج من حيث التوقيت بين تقديم الطلب واإلشعار باألهلية طيلة\n\n.فترة المشروع\n\n\nا م المعلومات اإلدارية المُمَكنَن الذي تمّ وضعه في إطار المرحلة األولى من البرنامج الوطني الستهداف44.  يشكّل نظ\n\nأسماء األسر التي قدّمت طلبًا فياألسر األكثر فقرًا العنصر األساسي في نظام الرصد والتقييم ويتضمّن وحدة تقوم بتسجيل\n\n)قاعدة بيانات البرنامج وتسجيل نتائج تقييم أهليتها (بما في ذلك النتيجة في البرنامج الوطني الستهداف األسر األكثر فقرًا\n\nالتي يقدّمونها. وستتواصل بلورة هذه الو", "output": {"entities": {"named_data": [], "descriptive_data": ["قاعدة بيانات البرنامج"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000066", "page": 31, "chunk": 2, "title": "Lebanon - Emergency National Poverty Targeting Program Project : Lebanon - Emergency National Poverty Targeting Project", "pdf_url": "http://documents1.worldbank.org/curated/en/424991467998238335/pdf/PAD1030-ARABICBox394864B-PUBLIC-FINAL-LEB-ENPTP-Arabic-Final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "قاعدة بيانات البرنامج", "label": "DESCRIPTIVE_DATA", "score": 0.512493371963501, "start": 508, "end": 529, "probe_score": 0.0215, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Handcrafted - Only handcrafted products. Mass products were excluded since those are not\n\ndirect competition to this product portfolio.\n\n\nBased on the criteria set above, we summarized the research results in the following table. This data set\nwas used for the pricing strategy; we analyzed the market price of the competitors’ products and\ncalculated the average of those to determine the potential shelf price.\n\n\n**Table 1: Portfolio Market Price Analysis**\n\n\nFollowing this analysis, we identified the price range for each product type. Afterwards, we refined the\nprices within the same product type based on the materials used for the production. This was rather\nnecessary, since the costs of materials vary and can have severe impact on the profitability of the\nproducts.\n\n\n_<mark>Segmentation</mark>_\n\n\nAfter researching the market in terms of identifying the consumer needs, market demand for home decor\nproducts and price comparison to similar hand-made products available on the Swiss and global market,\nwe defined and divided the Swiss market into segments. This would help further clarify the “Place” within\nthe 4Ps of marketing.\n\n\nThe segmentation was based on several criteria; the size and type of stores available in the market, the\nquality of the products these stores offer, the price range of their products, their involvement in CSR\nactivities and indirectly the variety of their customers. The objective was to design a specific value\nproposition and portfolio for each segment that matches the business model and the profile of the shop\nas well as the expectation of their customers.\n\n\nWe identified that some stores would find it beneficial to be part of the sustainable business model in the\nlong run, potentially increasing their competitive advantage through access to new markets and serving\na good cause. There are retailers that are already involved in CSR activities or source via the Fair Trade", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data set"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000172", "page": 24, "chunk": 0, "title": "New issues in refugee research - Research paper no. 282 - From care and maintenance to self-reliance: Sustainable business model connecting Malian refugee artisans to Swiss markets using public-private partnerships", "pdf_url": "https://reliefweb.int/attachments/0e8553de-def8-3058-ad13-5158de6f63d9/5857ebef4.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data set", "label": "VAGUE_DATA", "score": 0.7261486053466797, "start": 237, "end": 245, "probe_score": 0.0374, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n\n**Living in a vulnerable household is associated with higher poverty risks**\n\n\nJust like last year, members of households with vulnerabilities were found to more likely be living in poverty\nthan the general refugee population. Almost half of individuals living with an older adult (age 65+) reported an\nequivalized disposable income below the poverty threshold. For individuals living with household members\nwith a disability or members with MHPSS needs <sup>11</sup> [^11: Defined as someone feeling so upset, anxious, worried, agitated, or depressed that it affects daily functioning] these rates stood at 41% and 27%, respectively. Gender of the\nhead of household, however, was not found to have a significant impact on the poverty rate. Mixed gender (at\nleast one male and one female head) was associated with higher income, though likely due to increased\nchances of multiple breadwinners being present in the household.\n\n\n**<u>REFUGEE POVERTY RATES BY VULNERABILITY CHARACTERISTIC AND GENDER OF HEAD OF HOUSEHOLD</u>**\n\n\n\nNo Yes\n\n\n\n\n\nFemale Male Mixed\n\n\nHead of\nhousehold\n\ngender\n\n\n\nOlder adult\n(65+) present\n\n\n\nHousehold\nmember with\n\n\n\na disability\n\n\n\nHousehold\nmember with\nMHPSS needs\n\npresent\n\n\n\npresent\n\n\n\nSource: Survey data, SAG estimates\n\n\n**Refugee housing expenses are on average much higher than for nationals, which implies an**\n**even greater disparity in financial wellbeing**\n\n\nAt the regional level, the weighted average share of the host population living in rented housing was calculated\nat 13% based on Eurostat data. This figure is dwarfed by 60% of refugee households fully paying rent for their\naccommodation and 21% partially paying, as per the SEIS survey. Likewise, accommodation expenses as a\nshare of disposable income were estimated at 17% for hosts, including mortgages, compared to 32% for\nrefugees. This essentially implies that refugees, on average", "output": {"entities": {"named_data": ["Eurostat data", "SEIS survey"], "descriptive_data": [], "vague_data": ["Survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 4, "chunk": 0, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Survey data", "label": "VAGUE_DATA", "score": 0.6225104331970215, "start": 1331, "end": 1342, "probe_score": 0.9992, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Eurostat data", "label": "NAMED_DATA", "score": 0.8027759194374084, "start": 1634, "end": 1647, "probe_score": 0.9853, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "SEIS survey", "label": "NAMED_DATA", "score": 0.8660741448402405, "start": 1780, "end": 1791, "probe_score": 0.9409, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n\nJust like last year, employment rates demonstrated disparity by age group, gender, education level, the\npresence of a disability, and being in need of MHPSS. Disability was found to be associated with the largest\ndrop in employment, with this factor halving the probability of working in 2024 when compared to the sample\noverall. Having MHPSS needs and being female were also associated with a lower employment likelihood,\nalthough to significantly smaller degrees.\n\n\nCompared to the host population, the refugee sample demonstrated higher employment rates at lower age\nbrackets (15-19 and 20-24), which, considering the findings on poverty, can be interpreted as a coping strategy\nassociated with low income. Higher age brackets (55-59 and 60-64) saw the highest gap in the employment\nrate compared to hosts, supporting the hypothesis that older age individuals have more difficulty integrating\ninto the local labor market.\n\n\n**<u>REGIONAL EMPLOYMENT RATE BY AGE AND POPULATION</u>**\n\n\nRefugees (2023) Refugees (2024) Hosts (2023)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n52%\n\n\n\n\n\n\n\n15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64\n\n\nSource: Survey data, ILO\n\n\n\n**<u>REGIONAL REFUGEE EMPLOYMENT RATE BY POPULATION</u>**\n\n**GROUP (2024)**\n\n\n\n**<u>EMPLOYMENT RATE BY EDUCATION LEVEL</u>**\n\n\nRefugees (2023) Refugees (2024) Hosts (2023)\n\n\n96%\n92%\n86%\n\n\n\nOverall\n\n\nMale\n\n\nFemale\n\n\nWith severe psychological\n\ndistress\n\n\nWith a disability\n\n\nSource: Survey data, SAG estimates\n\n\n\n64%\n\n\n67%\n\n\n63%\n\n\n57%\n\n\n\n72%\n\n\n\n\n\n49%\n\n\n\n\n\n\n\nTechnical or\n\nVocational\n\n\n\nBachelor's Master'", "output": {"entities": {"named_data": ["Survey data, ILO", "SAG estimates"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 10, "chunk": 0, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Survey data, ILO", "label": "NAMED_DATA", "score": 0.6002267003059387, "start": 1238, "end": 1254, "probe_score": 0.9987, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "SAG estimates", "label": "NAMED_DATA", "score": 0.5162914395332336, "start": 1552, "end": 1565, "probe_score": 0.9922, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "br>the market.<br>Component III: Supporting the development of the institutional framework for microfinance<br>and non-bank financial institutions (NBFIs) supervision (US$ 0.8 million)<br>22. This component aims at supporting policy, legal, and regulatory reforms to develop the NBFI<br>and micro finance sector. Recognizing the importance of its role as a financial regulator and<br>supervisor, for not only banks but also for NBFIs, CBJ took the decision to regulate and supervise the<br>microfinance sector. This would entail setting a legal and regulatory framework that is conducive to<br>micro finance and NBFIs, as well as, institutional reforms that would allow CBJ to undertake such<br>mandate. In addition, it would also cover IT, both software and hardware, strengthening the<br>institutional infrastructure.<br>23. The project will also support the CBJ in gathering all available data about all NBFIs in the<br>market that are engaged in financial services (e.g. consumer lending, unregulated investment funds,<br>factoring, and financial leasing) and operate without any specialized regulation or supervision, to<br>identify the risks, and issues that need to be covered and assist the CBJ in adopting a more<br>comprehensive approach of regulating and supervising NBFIs, and not only MFIs. This will include a<br>comprehensive market study, technical assistance in drafting any needed regulation and building the<br>capacity and training of the staff in charge of supervising these institutions.<br>24. The upcoming regulations that will be supported by the EU Programme would move all MFIs<br>under the regulatory and supervisory umbrella of the CBJ, and depending on further judgments based<br>on a NBFI market study, there are plans to also", "output": {"entities": {"named_data": [], "descriptive_data": ["NBFI market study"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000060", "page": 6, "chunk": 1, "title": "Jordan - Enhancing Governance and Strengthening the Regulatory and Institutional Framework for Micro, Small, and Medium Enterprise (MSME) Development Project", "pdf_url": "http://documents.worldbank.org/curated/en/926531468040487242/pdf/838160PID0Appr0Box382106B00PUBLIC0.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NBFI market study", "label": "DESCRIPTIVE_DATA", "score": 0.8037207126617432, "start": 1715, "end": 1732, "probe_score": 0.0892, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|KE-BUSIA COUNTY-151027-<br>GO-RFQ / Tilapia Brooder<br>4mm feed pellets 32% CP <<br>1.8 FCR|IDA / 59450|Component 1: Upscaling<br>Climate-Smart Agricultural<br>Practices (US$163.8 million<br>equivalent, of which IDA<br>US$150.0 million eq<br>uivalent)|Post|Request for<br>Quotations|Limited|Single Stage - One<br>Envelope|Col8|12,580.00|11,817.75|Completed|Col12|Col13|Col14|Col15|Col16|Col17|2019-12-23|2020-01-22|Col20|Col21|Col22|Col23|Col24|Col25|2020-02-17|2020-01-28|2020-08-15|2020-02-11|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n|KE-BUSIA COUNTY-151028-<br>GO-RFQ / Tilapia Brooders<br>male one thousand  pieces<br>|IDA / 59450|Component 1: Upscaling<br>Climate-Smart Agricultural<br>Practices (US$163", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016906", "page": 4, "chunk": 0, "title": "Kenya - AFRICA- P154784- Kenya Climate Smart Agriculture Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/700711585742668929/pdf/Kenya-AFRICA-P154784-Kenya-Climate-Smart-Agriculture-Project-Procurement-Plan.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " vulnerability and adaptation\nb) Patient charters, service standard displays at health facilities, etc.\nc) Initiatives on citizen engagement and empowerment to usher in a social\n\nmovement in health, including an annual Regional Health Forum of all relevant\nstakeholders which channel their findings upward to an Annual National Health\nForum\n(iv) Data systems to create feedback loops from health system users, including on climate\nvulnerability/sensitivity, using ongoing user-experience surveys; the integration of user\nexperience data into administrative systems’ facility self-evaluations to inform and\ninfluence decision makers\n(v) Grievance redress mechanism at different levels.\n\n`o` _Sub-component 2.3: Project management –_ This subcomponent will support project management, including\n\nproject M&E.\n\n**<mark>Component 3: Contingent Emergency Response Component - CERC (US$0 million).</mark>**\n\n49. This contingent emergency response component is included under the project in accordance with World\nBank’s Investment Project Financing Policy, paragraphs 12, for situations of urgent need of assistance. This will\nallow for rapid reallocation of project proceeds in the event of a natural or man-made disaster or health outbreak\nor crisis that has caused or is likely to imminently cause a major adverse economic and/or social impact.\n\n\nPage 30 of 64", "output": {"entities": {"named_data": [], "descriptive_data": ["user-experience surveys", "user\nexperience data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000131", "page": 34, "chunk": 1, "title": "Djibouti - Health System Strengthening Project", "pdf_url": "http://documents1.worldbank.org/curated/en/772381653594094662/pdf/Djibouti-Health-System-Strengthening-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "user-experience surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8641936779022217, "start": 472, "end": 495, "probe_score": 0.154, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "user\nexperience data", "label": "DESCRIPTIVE_DATA", "score": 0.6610193848609924, "start": 516, "end": 536, "probe_score": 0.0014, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|**100,000**|\n|**Financial audit**|**40,000**|**40,000**|**40,000**|**40,000**|**40,000**|**40,000**|**40,000**|*", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000142", "page": 56, "chunk": 86, "title": "Djibouti - Public Administration Modernization Project", "pdf_url": "http://documents1.worldbank.org/curated/en/826531523301322820/pdf/Djibouti-Public-Admin-PAD-PAD2604-04062018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "mark>\n<mark>Africa and slightly better to slightly lower than the aggregate scores for all lower-middle income countries</mark>\n<mark>ranked by the SPI. It is important to note that the rankings are based on 2019 data. Given continuing progress</mark>\n<mark>reported under the Kenya Statistics PforR, and the fact that the 2019 census has now undergone quality</mark>\n<mark>control and the results are publicly available, it is possible that some of Kenya’s scores will improve in the next</mark>\n<mark>iteration of the SPI.</mark>\n\n\n77. In general, counties have made very good progress on M&E since they came into existence in 2013. Under\nKDSP, from the first Annual Capacity and Performance Assessment (ACPA) in 2016 to the third ACPA (covering\n2017-2018), counties have doubled their score (achievement) on Key Results Area 2, which is Planning and\nM&E. In particular, it is worth noting that most counties now regularly collect performance information on\nthe implementation of the CIDP and publish this in their Annual Progress Report. Counties have also set up\ncounty M&E committees. Where counties they lack most, however, is on evaluations, with very few counties\nundertaking their own evaluations routinely.\n\n\n78. <mark>In sum, the TA concluded that Kenya’s overall statistical data capacity, supplemented by the County</mark>\n<mark>Readiness Assessment and other preparatory work undertaken for FLLoCA, is adequate for purposes of</mark>\n<mark>initiating implementation. Preparation of FLLoCA is helping to address the G-FLLoCA M&E challenges</mark>\n<mark>identified in para. 70 above for those parts of G-FLLoCA that FLLoCA will support. The learning achieved in this</mark>\n<mark", "output": {"entities": {"named_data": ["2019 census"], "descriptive_data": [], "vague_data": ["2019 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016143", "page": 24, "chunk": 1, "title": "Final Technical Assessment - Financing Locally-Led Climate Action Program - P173065", "pdf_url": "https://documents.worldbank.org/curated/en/650141633388861479/pdf/Final-Technical-Assessment-Financing-Locally-Led-Climate-Action-Program-P173065.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2019 data", "label": "VAGUE_DATA", "score": 0.742974579334259, "start": 208, "end": 217, "probe_score": 0.753, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "2019 census", "label": "NAMED_DATA", "score": 0.5935677289962769, "start": 323, "end": 334, "probe_score": 0.667, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "; yet, they employ only 20\npercent of the workforce. Firms with fewer than 50 employees represent 97 percent of all firms and\nemploy 44 percent of the workforce, while, overall, SMEs (fewer than 250 employees) account for almost\nall firms (99.5 percent) and employ 66 percent of all formal sector workers. However, 84 percent of all\nnew job creation between 2014 and 2016 was generated by large firms (more than 250 employees); firms\nwith between 50 and 250 employees accounted for 20 percent of job creation, while firms with fewer\nthan 50 employees experienced net employment loss (–4.5 percent). Meanwhile, SMEs are more highly\nexposed to rising mandatory labor costs, such as the increase in the national minimum wage, which grew\nby 33 percent in nominal terms between December 2015 and January 2016. Constrained by such costs,\nSMEs may resort to hiring workers informally or might exit completely from the registered formal sector\nand continue operations informally.\n\n\n17. **Another major challenge affecting the capacity of firms to create jobs and expand is the capacity**\n**to find skilled workers.** An inadequately educated labor force is perceived to be among the top five\nconstraints to doing business in Turkey. The analysis of data on more than 7 million job postings at the\npublic employment agency (İŞKUR) between 2016 and 2018 and from İŞKUR’s Labor Market Needs\nAssessment Survey and the top nine online job search portals shows that the most critical skills sought by\nemployers across provinces are behavioral, socioemotional, and software-related skills. <sup>14</sup> [^14: https://media.İŞKUR.gov.tr/33412/istihdamda-3i-30-sayi-ek1-2019-yili-isgucu-piyasasi-arastirmasi-sonuclari.pdf]\n\n\n13 Enterprise Surveys (database), International Finance Corporation and World Bank, Washington, DC,\nhttps://www.enterprisesurveys.org/.\n14 https://media.İŞKUR.gov.tr/33412/istihdamda-3i-30-sayi-ek", "output": {"entities": {"named_data": ["Labor Market Needs\nAssessment Survey"], "descriptive_data": ["data on more than 7 million job postings"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000025", "page": 16, "chunk": 1, "title": "Turkey - Formal Employment Creation Project", "pdf_url": "http://documents1.worldbank.org/curated/en/211181585965751622/pdf/Turkey-Formal-Employment-Creation-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on more than 7 million job postings", "label": "DESCRIPTIVE_DATA", "score": 0.8796371817588806, "start": 1241, "end": 1281, "probe_score": 0.8427, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Labor Market Needs\nAssessment Survey", "label": "NAMED_DATA", "score": 0.8391753435134888, "start": 1361, "end": 1397, "probe_score": 0.9911, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "the Government of Chad assists with their resettlement in four designated areas. WFP gives\npriority to women as the designated recipients of vouchers or direct food transfers. For direct\nfood transfers, a local food management committee is established; WFP requires 50 percent of its\nmembers to be women.\n\n9. Vouchers will be distributed monthly at designated distribution sites, where the\ncontracted NGO partners will check registration cards against the local beneficiary lists. Many\nrefugees and returnees have lost their national identification cards in their flight from CAR, so\nbeneficiaries of the food assistance component of the project will receive registration cards with\ntheir photos. To limit the possibility of unauthorized reproduction and redemption, each voucher\nwill also have a specific security code and a 3D printed hologram. Beneficiaries with vouchers\nand registration cards will enter shops or distribution areas set up by local traders, where they\ncan redeem the vouchers and collect commodities of their choosing, corresponding to the\nvoucher value. The voucher allows purchase of staple foods, legumes, oil, canned fish, tomatoes,\nand onions (14 items altogether). This approach gives individuals some flexibility in their food\nchoices, including the ability to obtain fresh foods. It also supports local markets and traders and\nstrengthens supply chains.\n\n10. Each partner NGO will reconcile its monthly distribution of vouchers against those\nredeemed by the traders and compensates the traders accordingly. The NGOs will receive\nadvanced funds, sufficient to cover one month’s distribution only, to pay the traders. Once those\nfunds are exhausted, an NGO must submit a verified, reconciled account of the use of those\nfunds to receive a further advance to handle the next month’s voucher distribution.\n\n11. Because agriculture is a highly seasonal occupation, and because everyone—the refugees,\nreturnees, and host population—depends highly on local markets to buy food, voucher provision\nin the lean season has the potential to trigger food price inflation, which would reduce the\npurchasing power of all of these groups. For that reason, direct food transfers will be", "output": {"entities": {"named_data": [], "descriptive_data": ["local beneficiary lists"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000007", "page": 35, "chunk": 0, "title": "Chad - Emergency Food and Livestock Crisis Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/179061468215115488/pdf/PAD11010PAD0P1010Box385329B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "local beneficiary lists", "label": "DESCRIPTIVE_DATA", "score": 0.8528916239738464, "start": 456, "end": 479, "probe_score": 0.3836, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 3 of data collection from July to August 2021. Dashboard available at:\n<u>[https://data.globalprotectioncluster.org/en/situations/globalprotectioncluster/location/16040?secret=unhcrrestricted.](https://data.globalprotectioncluster.org/en/situations/globalprotectioncluster/location/16040?secret=unhcrrestricted)</u>\n6 In two districts, the status of CADs is unknown. In this context, classifying a CAD as only partially functional means that its operational capacities\n(opening days and hours, level of staffing etc.) are limited and/or that it processes only certain types of identity and civil documents, but not all.\n7 The CADs in Fallujah and Qaim districts are reportedly closed; CADs in Ana and Ramadi districts are reportedly only partially functional. The\noperational status of CADs Heet and Rutba districts could not be ascertained.\n8 In Salah al-Din, CADs are reportedly closed or non-existent in the districts of Samarra, Daur, Balad and Hirqat.\n9 In Diyala, the CADs are reportedly only partially functional in the districts of Muqdadiya, Baquba and Khalis.\n10 The Health Clusters reports that just slightly over 30,000 IDPs and returnees have been vaccinated against COVID-19.\n\n6", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000342", "page": 5, "chunk": 3, "title": "Protection Analysis Report: Right to identity and civil documentation, October 2021", "pdf_url": "https://reliefweb.int/attachments/2a84c057-4091-37f9-8dda-00c9f8eb9bda/protection_cluster_analysis_-_right_to_identity_and_civil_documentation.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "the PTA as bilateral or plurilateral (more than two members), and determine whether it has been\n\n\nnotified to the WTO. Unlike the WTO data, which includes agreements on trade in services as well\n\n\nas goods, our database focuses on merchandise trade agreements only. The distinguishing feature\n\n\nof the new database is the inclusion of agreements that have not been notified to the WTO, which\n\n\noutnumber the notified PTAs by 130 to 99 (see Figure 1). <sup>22</sup>\n\n\n\n\n\n\n\n\n\n\n\n\n\nFigure 1: Growth in the number of PTAs\n\n_Source:_ WTO and author’s estimates.\n\n\nThe left axis of Figure 1 shows the number of PTAs signed in a given year, using stacked columns\n\n\n22As before, this estimate counts the EU-25 as a single agreement. If EU-15 is treated as a single agreement instead\n(implying that all PTAs between the EU and the new accession countries, as well as between the accession countries\nthemselves, are included in the estimate), the number of unnotified agreements remains the same, but the number of\nnotified PTAs rises to 155.\n\n\n13", "output": {"entities": {"named_data": ["WTO data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003251", "page": 15, "chunk": 0, "title": "wps4038", "pdf_url": "https://local/prwp/wps4038.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "WTO data", "label": "NAMED_DATA", "score": 0.6909595727920532, "start": 130, "end": 138, "probe_score": 0.9707, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**B.** **Overall Risk Rating Explanation**\n\n\n69. The overall preparation risk of this project is rated as substantial because of stakeholder\nand implementing agency risks. Delayed implementation of project components could affect the\npopulation’s expectations which need to be managed to avoid civil unrest, especially in a context\nof high tariff levels and political instability. It is expected that this risk will be mitigated through\nthe combination of several measures. At the sectorial level, the authorities are preparing a plan\nto help improve the financial situation of the sector. At the project level, the mitigation measures\ninclude: upstream project preparation actions; early finalization of the procurement plan and\nbidding documents, and advance procurement activities; as well as the preparation of an\nappropriate communication strategy.\n\n70. The institution’s capacity to carry out project management, monitoring and evaluation;\nincluding capacity to carry out activities pertaining to procurement, disbursement, financial\nmanagement and safeguards need to be strengthened. This risk is compounded by extremely\nlong national procurement procedures which affect the speed of project implementation. A\nsurvey conducted in 2010 showed that the procurement process could take anywhere between\nnine to fourteen months. This risk will however be partially mitigated by the new procedures\nwhich assign the review of procurement documents to decentralized structures.\n\n71. The risks relating to project management capacity are partially mitigated by the\nexperience of the implementing agencies in the ongoing and recently closed IDA projects. As\nthe Ministry of Energy is encouraging capacity building within national institutions, it is\nexpected that capacity building efforts to support project implementation will be done by\nenhancing capacity in DGE through the recruitment of fiduciary and safeguards staff (which\nwould be financed under this project).\n\n\n72. The implementation risk rating is considered moderate, as the project will benefit from\nlessons learned from the Power Sector Development and the Energy Access Projects; both of\nwhich are more complex and wider in scope. Procurement related issues indicated earlier are\nknown beforehand and the lengthy procurement process will be taken into consideration in\nestablishing", "output": {"entities": {"named_data": [], "descriptive_data": ["survey conducted in 2010"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000136", "page": 29, "chunk": 0, "title": "Burkina Faso - Electricity Sector Support Project (ESSP)", "pdf_url": "http://documents1.worldbank.org/curated/en/801561468229175933/pdf/779300PAD0P1280y0Box377377B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey conducted in 2010", "label": "DESCRIPTIVE_DATA", "score": 0.8928678035736084, "start": 1217, "end": 1241, "probe_score": 0.0002, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "ERA staff in the application of these systems, the principles, planning and monitoring of asset\nmanagement contracts, and the strengthening of data collection.\n\n\n**27.** This subcomponent will also cater for OPRC strategy and bidding document preparation\nfor priority OPRC contracts, which includes the assessment of priority roads to be maintained,\npreparation of an OPRC bidding document, conducting social assessment and preparation of\nenvironmental and social management plan **(ESMP)** to be included in the road asset management\ncontracts. The adoption of low cost pavement standards will involve analysis of alternative\npavement types and experience sharing arrangement for ERA staff.\n\n\n**Road** **Safety** **and Institutional Development**\n\n\n**_28._** _Road Safety:_ According to data provided **by** the Ministry of Transport (MOT) the Road\nSafety campaign that has been conducted over the last **10** years has resulted in the reduction of\nfatal accidents from 114 deaths per **10,000** vehicles to 74 deaths per **10,000** vehicles. The target\nunder the Growth and Transformation Plan (GTP), to be achieved **by** **2016,** is 27deaths per\n\n**10,000** vehicles, which is a bench mark some countries are aiming to meet.\n\n\n**29.** The support to Road Safety strategy development targets assessing the gaps in the existing\nRoad Safety related regulations and design standards for road infrastructure and enhancing the\nachievements in the reduction of road accidents. The activities that were initially requested under\nthis project, such as the road accident database establishment will be financed **by** **EU.** GoE is\nproviding equipment for the federal police for enforcement. The Road Fund also allocates funds\nfor Road Safety annually. This project will focus on strategy development. The green aspect\ndeals with protection of road", "output": {"entities": {"named_data": [], "descriptive_data": ["road accident database"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:021211", "page": 40, "chunk": 0, "title": "Ethiopia - Roads Sector Support Project", "pdf_url": "https://documents.worldbank.org/curated/en/991261468024613829/pdf/PAD7000P131118010Box382121B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "road accident database", "label": "DESCRIPTIVE_DATA", "score": 0.8313633799552917, "start": 1552, "end": 1574, "probe_score": 0.0185, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " advise on scientific matters related\nto design of activities supported by the projects and on publication of findings that emerge.\nManagement will recommend to the countries that the Panel of Scientists should play a key\nadvisory role if the pilot is repeated (see paragraph 16 below). Management will also suggest that\nthe Panel of Scientists serve as a review body to screen publications prepared from work of the\nprojects to assure that the work is of high quality.\n\n16. **_Possible repeat of the pilot:_** Management agrees that this is indeed the only way in which the\ndata for an adequate environmental impact assessment of the chopping methodology can be\ncollected. The countries may wish to have an additional method of water hyacinth removal to\nsupplement biological control, and may, after consultation with stakeholders, conclude that they\nwould like to proceed with such a repeat of the pilot, especially in a situation where rapid\nremoval of water hyacinth would have a direct benefit to the local communities. Forthcoming\nsupervision missions will discuss this possibility with the countries involved. If the pilot were to\nbe repeated, it could be financed from the IDA Credits and GEF Grants. If this were to be done\nin Kenya, it would be overseen by the Ministry of Environment and Natural Resources, and\nresources would be available under the present project. Management will remain open to\nconsideration of a repeat of the chopping pilot in the event of: (i) recurrence of weed infestation\nof sufficient area and density to warrant chopping; (ii) a request from one of the countries to\nundertake the pilot; (iii) adequate prior consultation with potentially affected communities; (iv)\ninvolvement of the international scientific advisory panel in the design and execution of the pilot;\nand (v) availability of good baseline data and evidence of commitment and capacity to monitor.\nIn the event of a repeat of the pilot, Management would ensure that all the requirements set forth\nin relevant policies and procedures are complied with. Funds are available within the existing\nproject", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017670", "page": 5, "chunk": 1, "title": "Kenya - Lake Victoria Environmental Management Project : management report and recommendation in response to the Inspection Panel Investigation report", "pdf_url": "https://documents.worldbank.org/curated/en/752361468773397263/pdf/217810Mgmt0Response0402001.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "baseline data", "label": "VAGUE_DATA", "score": 0.7463257908821106, "start": 1834, "end": 1847, "probe_score": 0.0082, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "people_with_disabilities_in_the_Gaza_Strip.pdf20240214_ACAPS_Palestine_Impact_of_the_conflict_on_people_with_disabilities_in_the_](https://www.acaps.org/fileadmin/Data_Product/Main_media/20240214_ACAPS_Palestine_Impact_of_the_conflict_on_people_with_disabilities_in_the_Gaza_Strip.pdf)\n[Gaza_Strip.pdf](https://www.acaps.org/fileadmin/Data_Product/Main_media/20240214_ACAPS_Palestine_Impact_of_the_conflict_on_people_with_disabilities_in_the_Gaza_Strip.pdf)\n\n67 Key observations shared through surveys with OPDs in Gaza by the Protection Cluster conducted in May and June 2025.\n\n68 [Palestinian Central Bureau of Statistics, the Palestinian children›s situation on the eve of the Palestinian Child Day, 5 April 2025. PCBS | H.E. Dr. Awad,](https://www.pcbs.gov.ps/post.aspx?lang=en&ItemID=5965)\n[highlights the Palestinian children›s situation on the eve of the Palestinian Child Day, 05/04/2025.](https://www.pcbs.gov.ps/post.aspx?lang=en&ItemID=5965)\n\n69 [OCHA, Gaza Humanitarian Impact Snapshot, 07 May 2025. Humanitarian Situation Update #286 | Gaza Strip | United Nations Office for the](https://www.ochaopt.org/content/humanitarian-situation-update-286-gaza-strip)\n[Coordination of Humanitarian Affairs -", "output": {"entities": {"named_data": [], "descriptive_data": ["surveys with OPDs in Gaza"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000539", "page": 16, "chunk": 1, "title": "Occupied Palestinian Territory (oPt): Gaza Protection Analysis Update, July 2025 - Risks and barriers faced by persons with disabilities and older persons [EN/AR]", "pdf_url": "https://reliefweb.int/attachments/4da1e6e2-27bd-4c77-96da-2ce94393f538/Occupied%20Palestinian%20Territory%20-%20Gaza%20-%20Protection%20Analysis%20Update%20July%202025_AR_Final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "surveys with OPDs in Gaza", "label": "DESCRIPTIVE_DATA", "score": 0.9246175289154053, "start": 494, "end": 519, "probe_score": 0.9559, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ");\nb.   have been served by a refugee resettlement entity; and,\nc.   fall between the ages of 18 and 64 at the time of intervention.\n\nIf, for any reason, the sample in the study does not fall completely within those parameters, we\nwill contact the author in order to obtain disaggregated data for the population that meets the\ncriteria of a, b, and c. If we are unable to obtain disaggregated data, we plan to use sensitivity\nanalyses based on studies with mixed populations.\n\n\n_Types of interventions_\n\n\nEligible interventions include any designed to broadly increase the economic self-sufficiency\nand well-being of resettled refugees compared to a control or comparison group receiving\n‘services as usual’ or an alternative intervention. Interventions typically last from three months\nto five years and may include services such as employment casework to discuss goals and\n\n\n61", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["disaggregated data", "disaggregated data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001008", "page": 63, "chunk": 1, "title": "The labour market integration of resettled refugees", "pdf_url": "https://reliefweb.int/attachments/97c91085-db0b-389e-8aa0-5cd80b1ee5a3/the%20labour%20market%20integration%20of%20resettled%20refugees.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "disaggregated data", "label": "VAGUE_DATA", "score": 0.611375629901886, "start": 274, "end": 292, "probe_score": 0.3316, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "disaggregated data", "label": "VAGUE_DATA", "score": 0.60146564245224, "start": 379, "end": 397, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ",000 houses were destroyed dunng the war and only 10,000 have been\nrebuilt so far. Government is particularly concerned with the shelter needs of returnees, IDPs <sup>and</sup>\n\n\n\ngovernment employees such as health workers and teachers. The state of shelter in many <sup>areas is one</sup> <sup>of</sup>\nthe factors constraining the return of government employees and the revitalization of district and local\neconomic activity. The agricultural sector is particularly important because it currently <sup>employs 75%</sup> <sup>of</sup>\nthe country's labor force. The 2000 Baseline Service Delivery Survey reported that between <sup>65%</sup> <sup>and</sup>\n85% of the population do not have access to safe drinking water and sanitation facilities. Recent\nestimates in the most neglected communities of the \"newly accessible areas\", such as Bombali, <sup>suggest</sup>\nthat access to potable water and adequate sanitation are as low as 5% and 3%, respectively.\n\n\n\nWidespread human rights abuses during the civil war included the forced recruitment of children\nas combatants, porters and sex slaves. In addition, tens of thousands of people continue to suffer <sup>from</sup>\nthe traumatic effects of amputation and other injuries, sexual violence, loss of parents, and the general\nstress of living through a civil war. This has greatly increased the need for a kind of <sup>social service</sup>\nsupport that was not as widely needed before the war, integrating traditional health services <sup>with</sup>\npsycho-social care, counselling, foster homes and disability programs. The challenges ahead <sup>will include</sup>\n\nthe provision of community-", "output": {"entities": {"named_data": ["2000 Baseline Service Delivery Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010646", "page": 9, "chunk": 1, "title": "Kenya - El Nino Emergency Project", "pdf_url": "https://documents.worldbank.org/curated/en/280541468046748610/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2000 Baseline Service Delivery Survey", "label": "NAMED_DATA", "score": 0.8882462978363037, "start": 568, "end": 605, "probe_score": 0.97, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "u> <u>-0.104***</u>\n<u><mark>(0.025)</mark></u> <u><mark>(0.031)</mark></u> <u><mark>(0.094)</mark></u> <u><mark>(0.025)</mark></u>\n**<u>R</u>** <sup>**2**</sup> **<u>(%)</u>** <u>21.2</u> <u>39.7</u> <u>14.7</u> <u>7.4</u> <u>27.6</u>\n**<u><mark>N</mark></u>** <u><mark>5391</mark></u> <u><mark>1868</mark></u> <u><mark>1868</mark></u> <u><mark>1868</mark></u> <u><mark>1868</mark></u>\n_Source: Kalobeyei SES (2018); Kakuma SES (2019)_\n_Note: Significance level: 1% (***), 5% (**), 10% (*)._\n\n\n20", "output": {"entities": {"named_data": ["Kalobeyei SES", "Kakuma SES"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000594", "page": 19, "chunk": 7, "title": "Understanding the Socioeconomic Differences of Urban and Camp-Based Refugees in Kenya", "pdf_url": "https://reliefweb.int/attachments/5771bd73-902d-38cb-b9cc-5663dee46116/Understanding-the-Socioeconomic-Differences-of-Urban-and-Camp-Based-Refugees-in-Kenya.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Kalobeyei SES", "label": "NAMED_DATA", "score": 0.8732540607452393, "start": 396, "end": 409, "probe_score": 0.9702, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Kakuma SES", "label": "NAMED_DATA", "score": 0.8488487005233765, "start": 418, "end": 428, "probe_score": 0.9775, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "somewhat effective and 23.08% say it was not\neffective at all. Only 23.08% said such efforts were\nvery effective indicating a need to further\nstrengthen access and inclusion for marginalized\ngroups in aid distribution.\n\n\nGiven these challenges, participants suggested\nincreasing funding and strengthening local\npartnerships to improve both the fairness and\n\n\n\nCOMMUNITY PERCEPTION SURVEY ANALYSIS 2024\n\n\neffectiveness of aid distribution. They called for\nmore inclusive aid programs that incorporate local\nvoices and a greater focus on transparency to\nprevent the diversion and mismanagement of\nresources. This was reinforced by survey data\nshowing that only 22.86% of respondents felt that\ntraining on protection, inclusivity, and equality was\n“very effective,” pointing to a need for enhanced\ncapacity-building initiatives.\n\n\n###### Community Engagement and Participation\n\n\n\nReports from the Community Engagement and\nAccountability (CEA) Taskforce indicate that while\ncommunities show a clear preference for in-person\nreporting and engagement, there are varied\nperceptions regarding the effectiveness of\nhumanitarian organizations’ engagement with\ncommunities. Although 31.18% of respondents\nbelieve such engagement is somewhat effective,\nonly 26.42% rate it as very effective, indicating that\ncurrent efforts are falling short of delivering\nsubstantial impact. More concerning is the 21.80%\nof respondents who perceive these engagement\nefforts as not effective at all, suggesting significant\nroom for improvement.\n\n\nWhen it comes to disseminating key messages on\nissues such as abuse and exploitation, the response\nis similarly divided. While 33.56% of community\nmembers view these messages as somewhat\neffective, only 21.20% consider them effective, and\n23.71% find them ineffective. While messages\nrelated to inclusion, fraud, aid diversion and\ncorruption were viewed at 33.99% “somewhat\neffective” to not effective at 22.51%, expressing a\nmoderate to little impact. This indicates that despite\nattempts to raise awareness, these messages are not\nachieving their intended outcomes and may require\na re-evaluation of communication strategies.\n\n\nCommunity involvement in program design appears\nto be", "output": {"entities": {"named_data": ["COMMUNITY PERCEPTION SURVEY ANALYSIS 2024"], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000151", "page": 9, "chunk": 0, "title": "UNHCR Somalia Community Perception Survey Analysis 2024", "pdf_url": "https://reliefweb.int/attachments/0b5a49de-8281-5f7b-88b0-010ae99e6bfe/UNHCR%20Somalia%20Community%20Perception%20Survey%20Analysis%202024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "COMMUNITY PERCEPTION SURVEY ANALYSIS 2024", "label": "NAMED_DATA", "score": 0.5375465750694275, "start": 360, "end": 401, "probe_score": 0.2677, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.7673431038856506, "start": 629, "end": 640, "probe_score": 0.9493, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".\nRegionally, the Ukraine refugee NEET rate tends to\nincrease with age, as it becomes more affected by\nunemployment, which is high for the 15 – 24 cohort\n(at 17%).\n\n\n\nOther\n\n\nNo longer\n\nemployed\n\n\nConstruction\n\n\nEducation\n\n\nAdministrative\n\nand\nsupport\n\nservice\nactivities\n\n\n\n16 Likely to be a bit overstated, as the survey did not inquire about activities of 15-year-olds outside of school enrollment. Also,\nsome respondents were not asked about distance learning in Moldova\n\n17 [Reference indicators were taken from the OECD dataset for 2022 with the exception of Moldova, where 2023](https://data.oecd.org/youthinac/youth-not-in-employment-education-or-training-neet.htm) <u>[data reported by](https://statistica.gov.md/en/youth-neet-in-the-republic-of-moldova-for-the-second-9430_60713.html)</u>\n<u>[the national statistics office](https://statistica.gov.md/en/youth-neet-in-the-republic-of-moldova-for-the-second-9430_60713.html)</u> was used\n\n\n**8**", "output": {"entities": {"named_data": ["OECD dataset"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 7, "chunk": 1, "title": "3", "pdf_url": "https://local/jad_paddy_docs/3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "OECD dataset", "label": "NAMED_DATA", "score": 0.88618004322052, "start": 521, "end": 533, "probe_score": 0.9945, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on social development issues"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000176", "page": 24, "chunk": 0, "title": "Sierra Leone - National Social Action Project", "pdf_url": "http://documents1.worldbank.org/curated/en/976421468759851028/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on social development issues", "label": "VAGUE_DATA", "score": 0.581004798412323, "start": 1670, "end": 1703, "probe_score": 0.333, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2018-07-06||2018-08-10||2019-02-06||\n|UG-MEMD-48036-GO-DIR /<br>Supply of six (6) porous pot<br>electrode for Magnetotelluric<br>equipment<br>|IDA / 56530|Institutional Strengthening<br>and Impacts Monitoring|Post|Direct Selection|Direct<br>|||15,000.00|0.00|Canceled|||||2018-02-21||2018-02-26||||||||2018-04-02||2018-09-29||\n|UG-MEMD-47591-GO-DIR /<br>Supply of geophysical data<br>processing software(Empower)<br>&Training<br>|IDA / 56530|Institutional Strengthening<br>and Impacts Monitoring|Post|Direct Selection|Direct<br>|||35,500.00|36,000.00|Signed|||||2018-08-15||2018-08-20||||||||2018-09-24||2019-03-23||\n|UG-MEMD-72497-GO-RFB /<br>Supply and installation of<br>two (2) fixed meter (Lot 1)<br>and six (6) portable<br>meter(Lot 2) testing<br>equipment.<br>|IDA / 56530|Institutional Strengthening<br>and Impacts Monitoring|Post|Request for Bids|Open -<br>International<br>|Single Stage - One<br>Envelope||1,040,000.00|1,014,390.50|Signed||||", "output": {"entities": {"named_data": [], "descriptive_data": ["geophysical data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018785", "page": 2, "chunk": 2, "title": "Uganda - AFRICA- P133312- Uganda Energy for Rural Transformation III - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/826991565272314937/pdf/Uganda-AFRICA-P133312-Uganda-Energy-for-Rural-Transformation-III-Procurement-Plan.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "geophysical data", "label": "DESCRIPTIVE_DATA", "score": 0.72954922914505, "start": 364, "end": 380, "probe_score": 0.0106, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". The\nGoJ has rolled out in the majority of line ministries and budget units the Government Financial\nManagement Information System (GFMIS) for budget preparation and execution however, since\nthis project is not included in the budget Law of 2013, GFMIS will not be used for this operation\nbut will be used during the year 2014 after Project is included in the budget Law of 2014. As\nGFMIS is not capable of generating the IFRs the Project will use Excel sheets to generate the\nquarterly IFRs. The reports will consist of Statement of Cash Receipts and Payments by category\nand accounting policies and explanatory notes, including a footnote disclosure on schedules: (i)\nwheat and LPG sales in tons, unit costs calculation, and subsidy value at the end of each period,\n(ii) “the list of Contracts above US$ 200,000 showing Contract amounts committed, paid, and\nunpaid under each contract”, (iii) Reconciliation Statement for the balance of the Designated\nAccount, and (iv) a list of vaccines and drugs generated from inventory system of “Directorate of\nPurchases and Supplies” (MOH). MOF will prepare the IFRs and submit to the Bank by no later\nthan 45 days after the end of each quarter.\n\n\n12. **<u>Training and Implementation Support.</u>** The World Bank team will intensively supervise\nthe Project, particularly early in implementation, and will provide adequate training to an\nAccountant to ensure full understanding and application of the World Bank financial\nmanagement and disbursement Policies and Procedures.\n\n\n45", "output": {"entities": {"named_data": [], "descriptive_data": ["inventory system"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000064", "page": 44, "chunk": 1, "title": "Jordan - Emergency Project to Assist Jordan Partially Mitigate Impact of Syrian Conflict", "pdf_url": "http://documents1.worldbank.org/curated/en/419981468271818589/pdf/781290PAD0JO0R0t0Box377365B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "inventory system", "label": "DESCRIPTIVE_DATA", "score": 0.5594133138656616, "start": 1017, "end": 1033, "probe_score": 0.9192, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "POST DISTRIBUTION MONITORING NOVEMBER – 2019\n\n\nBamboo treatment brings more sustainable housing to camps © UNHCR/Will Swanson\n\n\nUse of help desks and complaint mechanisms\n\n\nFew of the respondents reported challenges during and after distribution. Among the respondents who reported challenges in this survey during and after distribution, only 10 respondents (11%) filed complaints to\nthe different complaint mechanisms. 7 refugee respondents filed complaints to UN/NGO staff, while the 2\nothers filed complaints at help desks and information points. The last respondent did not elaborate to whom\nor where the complaint was filed.\n\n\nPreferred type of assistance\n\n\nAbout 43% of surveyed refugees stated that\ntheir preference was for cash voucher type assistance. This represent a 16% increase since the\nApril 2019 PDM when only 27% of the refugees\nreported a preference for cash voucher support.\n38% of the respondents stated that they would\nprefer a combination of voucher and in-kind, a\n9% increase compared to results reported April\n2019 PDM when 29% of the respondents reported their preference for a combination of voucher\n\n\n1 8 UNHCR / NOVEMBER, 2019", "output": {"entities": {"named_data": ["April 2019 PDM"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001023", "page": 17, "chunk": 0, "title": "Post-Distribution Monitoring: Shelter and Non-Food Items, Bangladesh Refugee Situation (November 2019)", "pdf_url": "https://reliefweb.int/attachments/9b478488-a23e-3e73-a8d6-1b06df8eccad/73887.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "April 2019 PDM", "label": "NAMED_DATA", "score": 0.6407701373100281, "start": 802, "end": 816, "probe_score": 0.7923, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " exclusions were 42 percent higher than their pre-SG level after two years. The\n\nmain foreign beneficiaries of the SG application were exporters of products that were excluded because of\n\nthe developing country exemption; the model estimates imply these exports ended up 123 percent higher\n\nthan their pre-SG levels after two years. The exclusions provided in the safeguard resulted in substantially\n\ndifferent trade effects for partners that export products for which other foreign competitors were subject\n\nto the new import restriction.\n\n\n**4.2** **Basic robustness checks to the model**\n\n\nColumn (5) begins our sensitivity analysis by reporting the OLS estimates of the model without the\n\ninstrument for the lagged growth rate of imports. While the size of some of the coefficients changes\n\nmarginally, the qualitative pattern of the results is unchanged.\n\n\nColumn (6) addresses the concern that the results may be sensitive to missing observations due to\n\ncountry-product level entry and exit in the annual data. Such a concern is also motivated by our important\n\n\n29 This figure is based on the estimates in column (4) of Table 5. They result from differential impacts on import\ngrowth for each set of products relative to the set of steel products that also faced the SG investigation but for which\nno countries faced an import restriction.\n\n\n20", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["annual data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005532", "page": 21, "chunk": 1, "title": "wps6378", "pdf_url": "https://local/prwp/wps6378.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "annual data", "label": "VAGUE_DATA", "score": 0.799967348575592, "start": 1005, "end": 1016, "probe_score": 0.1109, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "to 513 (Hurun Report, 2015). Finally, account holdings leaked from a number of tax havens show\nconsiderable wealth in developing countries (ICIJ, 2016).\n\n\nAccording to our analysis, global inequality as measured by the Gini index has declined very\nslightly between 1988 and 2008. As the solid line in Figure 1 shows, the global Gini index fell\nfrom 72.2% in 1988 to 70.5% in 2008, a fall of almost 2 percentage points which was particularly\nstrong since 2003. Not surprisingly, global inequality is much higher than what is found within\nindividual countries. For example, in 2008 the Gini index of South Africa, one of the most unequal\ncountries, was 63%. The results are robust to using the same countries throughout, as shown by\nthe dashed line in Figure 1. <sup>5</sup> But given the numerous margins of errors involved in these\ncalculations, both sampling and non-sampling (e.g. PPP exchange rates) (Anand and Segal, 2015),\nit would be premature to claim that global inequality declined robustly. Furthermore, once we\nattempt to impute top incomes (Figure 1, dotted line), global inequality has remained almost\nunchanged over these 20 years, although the decline in the last five years remains. <sup>6</sup>\n\n\nTaken together this suggests that at the very least, there is no evidence pointing toward _increasing_\ninequality at the global level. Newer data for 2011 finds that the downward trend is accelerating\n(Milanovic, 2016, p. 120). Although different methods and inequality measures disagree over the\ntiming and size of the decline, the fall since the mid-2000s is robust across a number of sources. <sup>7</sup>\nViewed over the long run, this is a remarkable development. Bourguignon and Morrisson (2002)\nfind that global inequality rose steadily between", "output": {"entities": {"named_data": [], "descriptive_data": ["account holdings leaked from a number of tax havens"], "vague_data": ["Newer data for 2011"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006790", "page": 6, "chunk": 0, "title": "wps7776", "pdf_url": "https://local/prwp/wps7776.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "account holdings leaked from a number of tax havens", "label": "DESCRIPTIVE_DATA", "score": 0.6758044362068176, "start": 38, "end": 89, "probe_score": 0.7189, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Newer data for 2011", "label": "VAGUE_DATA", "score": 0.6413838863372803, "start": 1349, "end": 1368, "probe_score": 0.6731, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " personas mayores\ny las personas con discapacidades o las personas\ncuyas identidades se intersecan. Las consideraciones\nespecíficas de protección, como la protección contra la\nviolencia de género, el abuso o la explotación de niños\ny niñas y las cuestiones de inclusión siguieron siendo\ncuestiones fundamentales debido a la demografía del\ndesplazamiento interno. En 16 de las 20 operaciones\npara las que se dispone de datos demográficos, las\nmujeres constituían más de la mitad de todos los\ndesplazados internos (52%) a finales de 2019. Los valores\nmás altos se registraron en Burundi (65%), Sudán (57%),\n\n\n\n34 ACNUR > **TENDENCIAS GLOBALES 2019**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["datos demográficos"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000179", "page": 33, "chunk": 1, "title": "Tendencias Globales Desplazamiento: Forzado Global en 2019", "pdf_url": "https://reliefweb.int/attachments/100d2641-38d0-3a30-8f7c-afa6f61615c9/UNHCR%20SP.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "datos demográficos", "label": "VAGUE_DATA", "score": 0.6852045059204102, "start": 418, "end": 436, "probe_score": 0.0612, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " critical.** Some Country Offices are investing\n\n\n\nsignificant advocacy efforts on policy, strategy,\nfunding and technical issues with governments\nand donors where refugee and asylum seekers\nare not eligible for government social protection\nprogrammes. For example, Kenya has supported\ngovernment social protection policy formulation,\nlegal framework and co-ordination processes and\ncollaboration with local government agencies at\nKakuma and with the emerging pension scheme\nrolling out in urban areas. Many Country Offices are\nalso regularly participating in government and/or\nUN-led social protection sectors/working groups\nto advocate for the extension of social protection\nprogrammes to refugee-hosting areas including\nscaled-up coverage of host populations.\n\n\n**10. Advancing refugees’ self-reliance is also a**\n**powerful advocacy tool** for inclusion in social\nprotection systems as an entry point to short- and\nlong-term labour and employment programmes\nin national social protection policies. This also\nprovides the government with positive business\ncase elements (refugees will contribute to\nnational systems, defining an exit strategy out\nof non-contributory social assistance benefits).\nFor example, increasing the capacity of refugees\nto pay into national health insurance schemes\nvia livelihoods and IGAs is carried out in urban\nhealth insurance projects in Kenya, Rwanda and\nGhana. Further, Rwanda has invested significant\nefforts to define a joint UNHCR-government\neconomic inclusion strategy for refugees backed\nby the government and international donors that\nis used to advocate for the inclusion of refugees in\nsocial and economic services (WBG IDA18 RSW\nSocio-Economic Inclusion of Refugees and Host\nCommunities in Rwanda Project, MINEMA-WFP\nMisizi Marshland Project funded by IKEA and\nDenmark, inclusion of refugees in the National\nHousing and Population Census in 2022).\n\n\n\nINCLUSION OF REFUGEES IN GOVERNMENT SOCIAL PROTECTION SYSTEMS IN AFRICA 17", "output": {"entities": {"named_data": ["National\nHousing and Population Census"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001334", "page": 18, "chunk": 1, "title": "Inclusion of Refugees in Government Social Protection Systems in Africa, January 2021", "pdf_url": "https://reliefweb.int/attachments/cd86536f-7a81-3d16-a7e5-f70e3c8de951/61bb42624.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "National\nHousing and Population Census", "label": "NAMED_DATA", "score": 0.8592730164527893, "start": 1844, "end": 1882, "probe_score": 0.3814, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\neconomy.\n\n\n**B. Sectoral and Institutional Context**\n\n\n4. **Kenya is rapidly urbanizing, with the urban population growing at about 4.3 percent a year. In 2019, about 27**\n**percent of Kenyans lived in urban areas** <sup>**3**</sup> . Kenya’s five largest urban areas (Nairobi, Mombasa, Kisumu, Nakuru, and\nEldoret) account for approximately 34 percent of the urban population. By 2050, about half of the population will be\nliving in cities. Urbanization if well managed presents a key opportunity to change the structure and location of economic\nactivity from a basis in rural agriculture to more diversified and larger urban industrial and service sectors. But growth\nwill be weaker if unprepared migrants are forced to leave rural areas for the cities because of rapidly growing rural\npopulation density and scarcity of agricultural land.\n\n\n1 GNI per capita, Atlas method (current US$), World Development Indicators, The World Bank.\n2 Kenya National Bureau of Statistics.\n3 World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.\n\n\nPage 11 of 69", "output": {"entities": {"named_data": ["World Urbanization Prospects"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010786", "page": 11, "chunk": 2, "title": "Kenya - Second Kenya Informal Settlements Improvement Project", "pdf_url": "https://documents.worldbank.org/curated/en/289711597111250042/pdf/Kenya-Second-Kenya-Informal-Settlements-Improvement-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Urbanization Prospects", "label": "NAMED_DATA", "score": 0.6381801962852478, "start": 1055, "end": 1083, "probe_score": 0.9989, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " platform\nthat integrates registration databases from the different sources to track and manage grievances. This\nwill provide the MoPH with timely access to grievance data to address grievances.\n\n\n51. **The WB will conduct regular implementation support missions** during which implementation\nprogress, outputs, and work plan updates will be assessed, and adjustments made as necessary. On the\nbasis of these missions, regular implementation status and results reports will be prepared.\n\n**D. Sustainability**\n\n\n52. **The project’s sustainability is reinforced through three elements.**\n\n\n(a) **Alignment with GoL priorities and the national health sector strategy.** This alignment will\n\nbe achieved as follows: (i) short-term stabilization by addressing the immediate health\nneeds of poor Lebanese and displaced Syrians through an expanded package of services and\nimproved staff and physical capacities at the PHC and hospital levels; (ii) medium-term\nresilience of the system to ensure sustainability by laying the ground for a more effective\nPHC model focusing on prevention and outpatient case management; and (iii) long-term\nsupport to the MoPH strategy for UHC.\n(b) **Ownership.** The project was conceived, planned, and designed by MoPH, and all levels of\n\nthe ministry have demonstrated steadfast commitment and ownership. MoPH will have an\noverall responsibility for project implementation and oversight.\n(c) **Strengthened MoPH management capacity.** The project supports MoPH management\n\ncapacity in critical areas such as contracting, financial management, M&E, procurement, and\ngrievance redress mechanisms.\n\n\nPage 26 of 54", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["grievance data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000032", "page": 28, "chunk": 1, "title": "Lebanon - Health Resilience Project", "pdf_url": "http://documents.worldbank.org/curated/en/616901498701694043/pdf/Lebanon-Health-PAD-PAD2358-06152017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "grievance data", "label": "VAGUE_DATA", "score": 0.6898921728134155, "start": 157, "end": 171, "probe_score": 0.0228, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<mark>.</mark>\n\n\n<mark>.</mark>\n\n\n\n**<u><mark>PAD DATA SHEET</mark></u>**\n\n_<u><mark>West Bank and Gaza</mark></u>_\n\n_<u><mark>Gaza Solid Waste Management Project (P121648)</mark></u>_\n\n**<u><mark>PROJECT APPRAISAL DOCUMENT</mark></u>**\n\n\n_<u><mark>MIDDLE EAST AND NORTH AFRICA</mark></u>_\n\n_<u><mark>Urban Social and Disaster Risk Management Unit</mark></u>_\n\n\n\n\n\n\n\n\n\n\n\n|Report No.: PAD84<br>.|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|Col10|\n|---|---|---|---|---|---|---|---|---|---|\n|<br>**Basic Information**|<br>**Basic Information**|<br>**Basic Information**|<br>**Basic Information**|<br>**Basic Information**|<br>**Basic Information**|<br>**Basic Information**|<br>**Basic Information**|<br>**Basic Information**|<br>**Basic Information**|\n|Project ID|Project ID|Project ID|Project ID|EA Category|EA Category|EA Category|EA Category|Team Leader|Team Leader|\n|P121648|P121648|P121648|P121648|", "output": {"entities": {"named_data": ["PAD DATA SHEET"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000035", "page": 5, "chunk": 0, "title": "West Bank and Gaza - Solid Waste Management Project", "pdf_url": "http://documents1.worldbank.org/curated/en/270781468141890599/pdf/PAD840P1216480010Box382166B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PAD DATA SHEET", "label": "NAMED_DATA", "score": 0.7252629399299622, "start": 46, "end": 60, "probe_score": 0.049, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "completed sub-projects local authorities provide\nconform to ministry standards, resources and staff to operate\ndesigns and norms. and maintain facilities (e.g.\nprovision of teachers and\n\ntextbooks in the case of\nprimary schools);\n\n\nl(b) Targeted communities are lb. 1 At <sup>least 90%</sup> <sup>of</sup> - Beneficiary/ impact - Sub-projects reflect\nempowered to carry out projects are assessed as assessments and other beneficiary needs and\npriority investments. successful by communities evaluation reports improved access to social and\n(achieve rmnimum expected economic services;\noutputs and\noutcomes/imnpacts).\n\n                                     - Supervision missions                                     - PPA methodology is\nlb.2 All supported                  - Beneficiary Assessments internalized by NaCSA and\ncommunities have conducted                - NSAP quarterly progress partners;\nparticipatory needs reports\nassessments and project                 - Participatory M&E results\nidentification using PPA\napproach.                 - Continuous social                 - Capacity building efforts\nI assessment process provided and/or coordinated\nlb.3 100% of communities                  - Participatory M&E results by NaCSA are appropriate and\nhave project management effective;\nstructures in place and trained\ncommunity members.\n\n**2.** Pilot and Special 2a.1 100 km. of feeder roads - Supervision <sup>missions;</sup> - NaCSA's commitment to\n\n**Programs in** Newly rehabilitated. - NSAP quarterly reports; pilot both programs remains\n**Accessible** **Areas** - Annual technical audits; strong\n2a.2 800,000 person days of                  - NaCSA M&E data\n**2(a)** **Rural Public Works** temporary employment\n**Program:** created.\n\nInfrastructure constructed 2a.3 250,000 \"woman days\" of\nand/or upgraded using labor temporary employment\nintensive techniques. created.\n\n\n2a.4 At mid-term review the\ncost per day", "output": {"entities": {"named_data": ["NaCSA M&E data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000096", "page": 30, "chunk": 0, "title": "Guinea - Multi-Sectoral AIDS Project (MAP)", "pdf_url": "http://documents1.worldbank.org/curated/en/570211468749964429/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NaCSA M&E data", "label": "NAMED_DATA", "score": 0.9113216400146484, "start": 1658, "end": 1672, "probe_score": 0.7359, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "countries** . Ninety-five percent of mortality occurs in poor countries with 50 percent taking place\nin sub-Saharan Africa alone. In addition, for every case of maternal death, 16 women suffer\ncomplications related to pregnancy and deliveries. Three-quarters of all maternal deaths are\ncaused by hemorrhage, obstructed labor, hypertensive disorders, puerperal sepsis and\ncomplications of abortion. By scaling up good quality ante natal care and skilled attendance at\nbirth, especially emergency obstetric care, the majority of the deaths can be averted. Many lowincome countries are however particularly challenged with achieving routine facility-based\ndeliveries for the majority of the population for various reasons ranging from poor quality\nservices, shortages of health workers and general underfunding of the health sector, to proximity\nbarriers, financial barriers, and low perception of the benefits by the general population.\n\n9. **The major causes for the high disease burden are preventable, if women can access**\n**obstetric services of good quality** . For most of the conditions, cost effective interventions exist\nand can be provided at the primary care level. Due to high poverty levels, a majority of women\nare unable to afford these basic and essential services. According to WHO, interventions that\navert one DALY for less than average per capita income for a given country are generally\nconsidered as very cost-effective. Based on this, the interventions supported under the project are\ncost-effective as Uganda has a GDP of US490 per capita. Estimates based on analysis conducted\nin Uganda in 1999 <sup>19</sup> [^19: Jamison, D.T., J.G. Breman, A.R. Measham, G. Alleyne, M. Claeson, D.B. Evans, P. Jha, A. Mills, and P. Musgrove. 2006.\nDisease Control Priorities in Developing Countries. Second edition. Washington, DC: World Bank and Oxford University Press] reveal that costs per DALY averted for antenatal care was US$2.26 per\npregnant woman per year in public facilities and", "output": {"entities": {"named_data": [], "descriptive_data": ["analysis conducted\nin Uganda in 1999"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012208", "page": 49, "chunk": 1, "title": "Uganda - The Uganda Reproductive Health Voucher Project", "pdf_url": "https://documents.worldbank.org/curated/en/387111468115145982/pdf/842950PAD0P1440ucherPADFinal0Oct03.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "analysis conducted\nin Uganda in 1999", "label": "DESCRIPTIVE_DATA", "score": 0.6971163153648376, "start": 1582, "end": 1618, "probe_score": 0.9228, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "18</sup>\nThese data reveal the likelihood of women making more multi-destination trips than men and relying more on walking\nand public transport. Public consultations held during Project preparation revealed that women in the Region use\nbicycles more than the average rate in Brazil; however, there is still a gender gap, and women might consider using\nbicycles more if the infrastructure were safer. Moreover, public transport analyses of Brazilian cities <sup>19,20</sup> reveal that\nwomen and minorities are more dependent on buses than other groups, and they also tend to make more timeconsuming, chained trips and multi-purpose journeys, such as for jobs, childcare, and shopping. Therefore, ensuring\nthat jobs, schools, childcare, and other services are accessible by public transport is critical for women and minorities.\n\n16. **The safety and security of public transport disproportionally affect women.** According to a survey from 2019\nconducted by the _Locomotiva_ and _Patrícia Galvão_ institutes across Brazil, 97 percent of interviewed Brazilian women\nsaid they had experienced sexual harassment in public transport or in taxis or ride-hailing vehicles. According to data\nobtained from stakeholder engagement activities and limited surveys made in the Region during Project preparation,\nat least 25 percent of respondents had suffered sexual harassment in public transport in the Region, and less than half\nof the respondents considered public transport safe for women. However, between 2020 and 2021, the Region\nrecorded on average only 114 cases, <sup>21</sup> which highlights the prevalence of underreporting. Forty-eight percent of\nBrazilian women perceive their city as unsafe, while only 11 percent feel that their surroundings are safe; the Southern\nstates are considered safer than the north. In addition, a lack of clarity regarding responsibilities and governance\nstructures for the design and implementation of protocols for responding to sexual harassment in public transport\nlimits the possibility of appropriately responding to survivors.", "output": {"entities": {"named_data": [], "descriptive_data": ["public transport analyses of Brazilian cities", "survey from 2019"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000182", "page": 15, "chunk": 1, "title": "Brazil - Integrated Sustainable Mobility Project in the Foz do Rio Itajaí Region", "pdf_url": "https://documents1.worldbank.org/curated/en/099032624162515430/pdf/BOSIB-60d57288-4e09-4519-ae6c-ffdc0037e0b1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "public transport analyses of Brazilian cities", "label": "DESCRIPTIVE_DATA", "score": 0.5792577266693115, "start": 411, "end": 456, "probe_score": 0.8845, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey from 2019", "label": "DESCRIPTIVE_DATA", "score": 0.8525171279907227, "start": 929, "end": 945, "probe_score": 0.9747, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "-2014|30-Sep-2015|\n|Sub-projects fully operational and sustainably<br>managed 2 years after initial investment (in<br>1000).||Number|Comments|Baseline is zero as this refers<br>to investments that will be<br>conducted under the project.|As of MTR|Note: the MTR discussed with<br>Govt to amend the end target,<br>as the sub-component design<br>was modified|\n|Sales value of key selected value chain<br>commodities supported at the end-of-the-value-<br>chain.||Percentage|Value|175000.00|216967.00|400000.00|\n|Sales value of key selected value chain<br>commodities supported at the end-of-the-value-<br>chain.||Percentage|Date|31-Mar-2010|31-Mar-2014|30-Sep-2015|\n|Sales value of key selected value chain<br>commodities supported at the end-of-the-value-<br>chain.||Percentage|Comments|Baseline vales refer to 6<br>difference commodities. An<br>index may be developed.<br>Figures here refer only to<br>wheat.|Wheat only and referring to<br>2013 data|Wheat only.|\n|Farmers benefiting from the investments of<br>sub-component 2.1 (in 1000).||Number|Value|0.00|30.60|72.00|\n|Farmers benefiting from the investments of<br>sub-component 2.1 (in 1000).||Number|Date|31-Mar-2010|31-Mar-2014|30-Sep-2015|\n|Farm", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["2013 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020037", "page": 5, "chunk": 1, "title": "Ethiopia - ET: Agricultural Growth Program : P113032 - Implementation Status Results Report : Sequence 07", "pdf_url": "https://documents.worldbank.org/curated/en/915191468030234812/pdf/ISR-Disclosable-P113032-10-12-2014-1413110409450.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2013 data", "label": "VAGUE_DATA", "score": 0.777445912361145, "start": 938, "end": 947, "probe_score": 0.5838, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<mark>TABLE 14</mark> **Asylum applications lodged in 44 industrialized countries by origin, fourth quarter \u0003** | 2013\n\n\nCovering all 44 asylum countries which provided monthly data to UNHCR. See notes in Annex Table 1.\nTop-20 ranking of countries based on applications lodged in all countries. An asterisk (*) denotes between 1 and 4 applications.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nUNHCR Asylum Trends 2013 **37**", "output": {"entities": {"named_data": ["UNHCR Asylum Trends 2013"], "descriptive_data": [], "vague_data": ["monthly data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001462", "page": 36, "chunk": 0, "title": "UNHCR Asylum Trends 2013: Levels and Trends in Industrialized Countries", "pdf_url": "https://reliefweb.int/attachments/e3c004e1-00b1-35e4-9688-91cf1e57dc5a/Asylum%20Trends%202013.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "monthly data", "label": "VAGUE_DATA", "score": 0.610742449760437, "start": 169, "end": 181, "probe_score": 0.8632, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHCR Asylum Trends 2013", "label": "NAMED_DATA", "score": 0.8195512890815735, "start": 366, "end": 390, "probe_score": 0.9981, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", and information about<br>the systems developed on its website, which is constantly being updated at https://id.gov.et/.<br>● The website contains frequently asked questions that address the risks related to some<br>misconceptions.<br>● NIDP organized a series of stakeholder consultations with civil society organizations, human and digital<br>rights groups, and legislative and executive wings of the Government among others during 2021–23.<br>The program will be able to further expand these activities once the project is operational, notably<br>further engaging with communities and local leaders.<br>● Based on the registrant’s request, all logs and audit trails of the user’s personal data and their<br>authentication history can be accessed and/or deleted. There are also facilities for the user to lock<br>their personal data so that it cannot be used for authentication.|\n\n\nPage 37 of 39", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["personal data", "personal data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000005", "page": 47, "chunk": 2, "title": "Ethiopia - Digital ID for Inclusion and Services Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099112223132535848/pdf/BOSIB0efb09b920d90858a0135df22da7d1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "personal data", "label": "VAGUE_DATA", "score": 0.5123068690299988, "start": 684, "end": 697, "probe_score": 0.3304, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "personal data", "label": "VAGUE_DATA", "score": 0.5458481907844543, "start": 822, "end": 835, "probe_score": 0.119, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000029", "page": 62, "chunk": 2, "title": "West Bank and Gaza - Health System Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/221361468779450522/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">basis<br>|SNSOP MIS<br>|This data will be<br>collected through<br>registration and<br>payments<br>|Implementing Partner<br>|\n|Number of beneficiaries receiving<br>economic opportunities who are youth|Number of beneficiaries<br>receiving economic<br>opportunities under<br>Component 2, in accordance<br>with the Project Operations<br>Manual, of which are youth,<br>defined as people between<br>the ages of 18 and 35 years,<br>and have receive at least 1|<br>This<br>indicator<br>will be<br>measured,<br>at a<br>minimum,<br>on a<br>quarterly<br>basis|SNSOP MIS<br>|Beneficiary data will be<br>gathered at registration<br>and will be updated<br>over the course of<br>project<br>implementation.<br>Payment data will be<br>regularly updated in the<br>SNSOP MIS|The Implementing<br>Partner in charge of<br>Component 2 will be<br>responsible for data<br>collection<br>|\n\n\nPage 58 of 74", "output": {"entities": {"named_data": ["SNSOP MIS"], "descriptive_data": ["Beneficiary data", "Payment data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 62, "chunk": 1, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SNSOP MIS", "label": "NAMED_DATA", "score": 0.5669784545898438, "start": 11, "end": 20, "probe_score": 0.2167, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Beneficiary data", "label": "DESCRIPTIVE_DATA", "score": 0.6072738766670227, "start": 564, "end": 580, "probe_score": 0.0781, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Payment data", "label": "DESCRIPTIVE_DATA", "score": 0.5558620095252991, "start": 695, "end": 707, "probe_score": 0.2095, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "du projet pour une évaluation complète du progrès et des résultats du projet. L’ADDS préparera\nun rapport de RMP, qui sera partagé avec la Banque avant la mission de RMP.\n\n59.En outre, des consultants indépendants seront chargés de concevoir et de réaliser une\névaluation de l'impact des interventions du projet sur les bénéficiaires, sur la base d'enquêtes\nreprésentatives utilisées pour référence. Les évaluations seront menées à mi-parcours et à\nl'achèvement du projet. Les évaluations porteront sur l'accès aux services, l'utilisation et la\nsatisfaction des services fournis par le projet, et l'évolution des revenus et du niveau de vie\nrésultant des opportunités génératrices de revenus appuyées par le projet.\n\n\n60. Les informations recueillies à partir des rapports de S&E seront utilisées pour évaluer les\nprogrès de la mise en œuvre des activités du projet et la probabilité que le projet atteigne son\nobjectif de développement. Les informations du rapport de S&E seront également utilisés pour\nidentifier les goulots d'étranglement dans la mise en œuvre qui nécessiteraient des efforts et des\nressources, ou des ajustements supplémentaires grâce à des changements ou à une\nrestructuration. L'information recueillie mettra également en exergue des exemples de réussite\nqui pourraient être diffusés et reproduits dans d'autres projets des bailleurs de", "output": {"entities": {"named_data": [], "descriptive_data": ["rapports de S&E"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000134", "page": 56, "chunk": 0, "title": "Djibouti - Second Urban Poverty Reduction Project : Djibouti - Second Projet de Reduction de Pauvrete Urbaine", "pdf_url": "http://documents1.worldbank.org/curated/en/786961467998828687/pdf/PAD791-FRENCH-P145848-PUBLIC-Box393238B.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "rapports de S&E", "label": "DESCRIPTIVE_DATA", "score": 0.7628433108329773, "start": 764, "end": 779, "probe_score": 0.8177, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**DLI 6**<br>Program LGs with<br>Town Clerks in place63|8|2.7%|14|18|18|18|18|18|\n|**Allocated amount**||||**1.6**|**1.6**|**1.6**|**1.6**|**1.6**|\n|**Total financing**<br>**Allocated**|**300**|**100%**||**51.10**|**69.10**|**90.10**|**79.10**|**10.60**|\n|**DLI Matrix for DLIs 7 and 8 Results on Physical Planning, Land Tenure Security and Urban Infrastructure Development in Refugee Host Areas.64 **|**DLI Matrix for DLIs 7 and 8 Results on Physical Planning, Land Tenure Security and Urban Infrastructure Development in Refugee Host Areas.64 **|**DLI Matrix for DLIs 7 and 8 Results on Physical Planning, Land Tenure Security and Urban Infrastructure Development in Refugee Host Areas.64 **|**DLI Matrix for DLIs 7 and 8 Results on Physical Planning, Land Tenure Security and Urban Infrastructure Development in Refugee Host Areas.64 **|**DLI Matrix for DLIs 7 and 8 Results on Physical Planning, Land Tenure Security and Urban Infrastructure Development in Refugee Host Areas.64 **|**DLI Matrix for DLIs 7 and 8 Results on Physical Planning, Land Tenure Security and Urban Infrastructure Development in Refugee Host Areas.64 **|**DLI Matrix for DLIs 7 and 8 Results on Physical Planning, Land Tenure Security and Urban Infrastructure Development in Refugee", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000168", "page": 41, "chunk": 2, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents1.worldbank.org/curated/en/946901526654169395/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:021030", "page": 62, "chunk": 2, "title": "Ethiopia - Forestry Project", "pdf_url": "https://documents.worldbank.org/curated/en/978451468256730240/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### 1.8 11\n\n\n\nCurrent account balance . **.2**\n\n\n\nFinancing items (net)\nChanges in net reserves .. .\n_Memo:_\nReserves including gold _(US$ millions)_\nConversion rate _(DEC, locaW/US$)_ 177.7 177.7 177.7\n\n\n**EXTERNAL DEBT and RESOURCE FLOWS**\n\n**1979** **1989** **1998** **1999**\n_(US$ millions)_ **Compositlon of total debt, 1998 (USS milIlona)**\nTotal debt outstanding and disbursed 26 **179** 288\nIBRD 0 0 0\nIDA 0 26 50 49 G 15 B\n\nTotal debt service 2 15 6\nIBRD 0 0 0 C: 9\nIDA 0 0 1 1\n\nComposition of net resource flows E: 119\nOfficial grants 5 32 48\nOfficial creditors -1 3 2\nPrivate creditors 0 -1 0\nForeign direct investment 0 0 6 D: **95**\nPortfolio equity 0 0 0\n\nWorld Bank program\n\nCommitments 0 9 3 A  - IBRD E - Bilateral\nDisbursements 0 2 2 1 B - IDA D - Other rrultilateral F **-** Private\nPrincipal repayments 0 0 0 0 C- IMF G - Short-term\nNet flows 0 2 2 1\nInterest payments 0 0 0 0\nNet transfers 0 2 1 1\n\n\nNote: This table was produced from the Development Economics central database. 9/13/00", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000038", "page": 63, "chunk": 1, "title": "Africa - Multi - Country HIV/AIDS Program for the Africa Region (Ethiopia and Kenya)", "pdf_url": "http://documents1.worldbank.org/curated/en/287591468768313907/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9087857007980347, "start": 960, "end": 998, "probe_score": 0.6996, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " not a good\n\nalternative to ask health center health workers to be trainers, there skill i s not\nsufficient for such a task and there are not enough midwifes to give them such a\nmission while priority should be on supporting clinical activities.\n\n\nHiring midwifes at local level (CRD): quality o f care for expectant women relies\non a first consultation given by a midwife (Who has better capacity than a health\nworker to identify maternal risks) who should be able to follow up all women\nunder risk. The shortage and the uneven dispatching o f midwifes in the country\nwould not make it possible to have a midwife in each health center. Nevertheless\nto improve dramatically quality o f care there i s a need to have more midwifes in\nmost populated rural areas. Hiring 50 extra midwifes at local level (CRD) should\nbe possible in regard to the potential market response.\n\n\n\n\n_o_ Sub-component B : Community mobilization: investments would be made mainly\nto: . Support the existing successful MURIGA system, which i s a health\n\n\n\nmutual system implemented during the previous World Bank financed\nproject, and which provides coverage mainly for women’s health related\nto birth. Health mutuals, which cover more risks than the MURIGAs,\nwould also be created.\nIn order to strengthen the Government’s policy for decentralization,\nsome health centers would be managed by communes and CRDs, starting\nwith a pilot activity in six prefectures the first year. The evaluation o f\nthis pilot would help decide how to extend it to the other 12 prefectures.\nAgreements would be signed with those urban and rural communes\nrather than with the health center’s management committee.\n\n\n\n.\n\n\n\n28", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000092", "page": 33, "chunk": 1, "title": "Guinea - Health Sector Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/551731468037482453/pdf/28046.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 1No. at Mtwapa Customs Beach\nEach ablution block would feature:\n\n    - Six toilets with an equal number for each gender\n\n    - Two shower rooms; one for each gender\n\n    - Toilet fitted with special amenities for use by disabled persons\n\n    - A shop, store and offices\n\n    - A septic tank\n\n    - A 5,000-litre water tank\nThe Ablution blocks would each sit on a piece of land measuring 23m x 17m. This land was\nselected on the basis that;\n\n  - There was sufficient space to set up the ablution block\n\n  - It was publicly owned\n\n  - There was high traffic in the area and therefore a high need for the lavatory facilities\nA faecal sludge handling facility would also be constructed in Maweni. This would receive the\nwastewater collected from toilets and septic tanks within Mtwapa Area and would treat the\nwater before it was released into the environment.\n\nThe Expert explained the purpose of the public engagement, explaining the reason for doing\nthe ESIA. Mitigation measure would be put in place following the site visits and questionnaire\nsurveys and would be incorporated into the ESIA report being presented to NEMA. Comments\nand questions from the public would be addressed in the meeting. Matters arising that may\nhave impacts on the project as currently designed would be included in the report as\nrecommendations, and will, where necessary advice on future improvements and alterations to\nthe design.\n\n\n**_Abbreviated Resettlement Action Plan for Mtwapa-Mariakani Sanitation Development Projects under_**\n**_KIMAWASCO in Kilifi County_** **_28_**", "output": {"entities": {"named_data": [], "descriptive_data": ["questionnaire\nsurveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000456", "page": 58, "chunk": 1, "title": "Kenya - Water and Sanitation Development Project : Resettlement Plan (Vol. 7 of 3) : Abbreviated Resettlement Action Plan Report for Mtwapa-Mariakani Sanitation Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/099020003242234748/pdf/P1566340c1ef3a0a3087a10e3c61a646fde.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "questionnaire\nsurveys", "label": "DESCRIPTIVE_DATA", "score": 0.8166770935058594, "start": 1031, "end": 1052, "probe_score": 0.0023, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " engagement in forced labor\n(including the worst forms of child labor) and children living on the street. Poverty, inflation, decreased access to income\ngenerating activities due to conflict and drought, high levels of youth unemployment, and the impact of climate change are\nmajor drivers. Limited recovery from previous shocks, including loss of livelihood activities, inflation, family separation,\ninsufficient and delayed food assistance, lack of access to education, poor value towards education as well as weak law\n[enforcement mechanisms drove up instances of exploitation and trafficking, including child labor (RDRMB](https://app.thedeep.io/permalink/leads-uuid/81c16dae-1623-4eb7-96f0-ec2b8fb90429) 31/08/2023).\nChildren face numerous challenges and risks during their journey and upon arrival in destination countries, as well as hardships\nupon deportation and return, making their reintegration into their communities challenging.\n\n\nThe **Eastern migration route**, which runs from the Horn of Africa through Yemen to the Kingdom of Saudi Arabia is one of the\nmost widely used corridors. With an average of 23,000 outward cross-border movements per month, Ethiopia is the main\ncountry of origin for migrants, most of whom have their origins in the currently conflict affected areas i.e. Amhara, Tigray and\nOromia, with data as of November 2023, reporting over 285,000 Eastern Route migrants having departed from Ethiopia in\n2023, mostly men (64%), followed by women (28%), boys (5%), and girls (3%). <u>[(IOM](https://reliefweb.int/report/yemen/regional-migrant-response-plan-mrp-horn-africa-yemen-and-southern-africa-2024)</u> 02/2024).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data as of November 2023"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001342", "page": 9, "chunk": 2, "title": "Ethiopia Protection Analysis Update, August 2024", "pdf_url": "https://reliefweb.int/attachments/cecab6f4-02c2-46b7-988d-c90a05e276a8/pau_ethiopia_august_final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data as of November 2023", "label": "VAGUE_DATA", "score": 0.7121137976646423, "start": 1331, "end": 1355, "probe_score": 0.1819, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|**Intermediate Results Area 1 (MDG Element):****_Improve urban service delivery through enhanced urban local development grant_ **|\n|**4.**Municipal** r**oads built<br>or rehabilitated with<br>related infrastructure<br>using urban LDG|√|3|Km<br>Targets|53.02|Measured<br>Annually|Measured<br>Annually|Measured<br>Annually|Measured<br>Annually|Measured<br>Annually|Annually|Municipal reports|Participating<", "output": {"entities": {"named_data": [], "descriptive_data": ["Municipal reports"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000014", "page": 36, "chunk": 4, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents1.worldbank.org/curated/en/143681526614252328/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Municipal reports", "label": "DESCRIPTIVE_DATA", "score": 0.8177699446678162, "start": 1379, "end": 1396, "probe_score": 0.2443, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2019\n\n\n0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%\n\n\nEast and Horn of Africa, and Great Lakes\n\n\nSouthern Africa\n\n\nWest and Central Africa\n\n\nAmericas\n\n\nAsia and the Pacific\n\n\nEurope\n\n\nMiddle East and North Africa\n\n\nCensus Estimate Government registration\n\n\nJoint or other registration UNHCR registration Various/Other\n\n\nUNHCR > **GLOBAL TRENDS 2019** 69", "output": {"entities": {"named_data": ["Middle East and North Africa\n\n\nCensus Estimate"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001657", "page": 68, "chunk": 1, "title": "Global Trends: Forced Displacement in 2019", "pdf_url": "https://reliefweb.int/attachments/ffb577d2-2185-3ba5-bdc7-8130fa9ba6e8/5ee200e37.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Middle East and North Africa\n\n\nCensus Estimate", "label": "NAMED_DATA", "score": 0.5229725241661072, "start": 183, "end": 229, "probe_score": 0.3735, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " by women, led to an increase of female Members of Parliament from 11 percent to 26 percent between 2002\nand 2018.\n\n7. **Food insecurity, exacerbated by the war in Ukraine, compounds Djibouti’s human development**\n**challenges.** In 2021, Djibouti ranked 99 <sup>th</sup> out of 116 countries with a Global Hunger Index <sup>6</sup> score of 27.4. Only\nabout 1,000 square kilometers or 0.04 percent of the country’s total land area is considered arable. According to\nthe World Food Program (WFP), 90 percent of food is imported. About 10 percent of the population are food\ninsecure and among them, 60 percent live in rural areas and depend on agriculture-based livelihoods. The war in\nUkraine has already had an impact on global wheat prices and is likely to have a significant impact on food access\n\n\n2 Due to insufficient country data, Djibouti has not been included in the Human Capital Index assessment by the World Bank.\n3 https://microdata.worldbank.org/index.php/catalog/3463/related-materials\n4 United Nations strives for full eradication of FGM by 2030.\n5 Djibouti prohibits the practice of FGM through Article 333 of the Penal Code, which criminalizes and punishes its performance;\nSubsequent amendments to the law have included criminalizing the failure to report FGM and aiding and abetting the practice.\n6 https://www.globalhungerindex.org/djibouti.html\n\n\nPage 8 of 64", "output": {"entities": {"named_data": ["Global Hunger Index", "Human Capital Index"], "descriptive_data": [], "vague_data": ["country data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000131", "page": 12, "chunk": 2, "title": "Djibouti - Health System Strengthening Project", "pdf_url": "http://documents1.worldbank.org/curated/en/772381653594094662/pdf/Djibouti-Health-System-Strengthening-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Global Hunger Index", "label": "NAMED_DATA", "score": 0.7431668043136597, "start": 300, "end": 319, "probe_score": 0.0847, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "country data", "label": "VAGUE_DATA", "score": 0.6336902976036072, "start": 824, "end": 836, "probe_score": 0.9615, "gold": "NON_MENTION", "gold_tier": "human-final"}, {"text": "Human Capital Index", "label": "NAMED_DATA", "score": 0.564024031162262, "start": 876, "end": 895, "probe_score": 0.1898, "gold": "NON_MENTION", "gold_tier": "human-final"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " entered into the MIS. This\ndatabase will help support operations through feedback loops as it can track who is accessing which services in real time.\nThe MIS will also be important in being able to establish a sample of study participants to draw on for an impact\nevaluation or other learning activities.\n\n61. The project will also support MGLSD’s capacity to lead and oversight social risk management. At the national level,\nthis will support capacity building of unit staff, public fora, SRM experts, etc. At the district level, GROW will provide\ntechnical assistance on specific areas (Stakeholder engagement, grievance management, management of workers) to\ngovernment officers based in the districts and relevant government entities (MGLSD, NEMA- Social unit, CDOs, Labour,\nGender, Occupational Health and Safety (OHS), and all other government departments that manage social risk in the\ncountry), and sub-county staff. Key focus will also be given to building capacity of MGLSD, PSFU and other relevant\ngovernment institutions, including academia on social risk mitigation.\n\n\n62. **Subcomponent 4B: Policy innovation and evidence generation.** This subcomponent will finance data collection\nefforts beyond the information gathered through the MIS and digital delivery platforms), analysis and publication of data\nfrom project and non-project datasets on female entrepreneurship, climate resilience and WEE, establishment of a data\nportal, and research workshops and policy forums on female entrepreneurship and WEE. In addition, the learning agenda\ncould also include the design and implementation of innovative pilot activities within the project to test what works to\naddress the key constraints faced by beneficiaries, including refugees and women living in RHDs. This work will be\ndesigned and conducted in collaboration with the World Bank’s Africa Gender Innovation Lab as well as other local\nresearch institutes and development partners. A research workshop will be held to explore the possibility of including a\nrigorous impact evaluation of a program component or", "output": {"entities": {"named_data": ["MIS"], "descriptive_data": ["project and non-project datasets"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 30, "chunk": 1, "title": "Uganda - Generating Growth Opportunities and Productivity for Women Enterprises Uganda Project", "pdf_url": "http://documents.worldbank.org/curated/en/527091655323259747/pdf/Uganda-Generating-Growth-Opportunities-and-Productivity-for-Women-Enterprises-Uganda-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "MIS", "label": "NAMED_DATA", "score": 0.5796350240707397, "start": 18, "end": 21, "probe_score": 0.0002, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "project and non-project datasets", "label": "DESCRIPTIVE_DATA", "score": 0.649100661277771, "start": 1324, "end": 1356, "probe_score": 0.1606, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad Rural Mobility and Connectivity Project (P164747)\n\n\nby close supervision and regular capacity strengthening of the PMCU and associated services, in\naccordance with the detailed actions for procurement and FM. <sup>26</sup> Residual FM risk is substantial. The PMCU\nhas also shown broadly satisfactory performance on procurement. Residual procurement risk is\nsubstantial.\n\n\n104. **Environmental and social: High.** The environmental risk associated with the project is moderate,\nas it involves only rehabilitation of existing unpaved roads and small crossing or drainage works and can\nbe adequately mitigated by the measures prescribed in the ESMF and associated ESMPs. Social risk due\nto resettlement consists mainly of economic displacement and can be adequately addressed through the\nmeasures prescribed in the RPF and associated RAPs. Social risk due to GBV, however, is high as GBV is\nwidespread in Chad, including in the refugee camps, although it is underreported. <sup>10</sup> [^10: According to the UNHCR SGBV Strategy for Chad 2012-2016. https://www.unhcr.org/protection/operations/56b1fd9f9/chadsgbv-strategy.html] Women are also at a\nheightened risk of GBV as a result of their displacement. Additionally, widespread poverty in the region\ncreates additional pressures on communities and households that lead to conditions that induce GBV. It\nis reported that 29 percent of women have experienced physical violence in their lifetime, 11.6 percent\nreported experiencing sexual violence in their lifetime, and 43.5 percent of women experiencing violence\nnever told anyone and never sought help after experiencing violence. The prevalence of GBV in Chad is\n57 percent; <sup>11</sup> [^11: Percentage of women who have experienced physical and/or sexual violence from an intimate partner at some time in their\nlives. _Source:_ OECD, Gender, Institutions and Development Database 2015 (GID-DB) (accessed September 2017).] however, the Chadian Government has taken positive steps ining", "output": {"entities": {"named_data": ["Gender, Institutions and Development Database 2015"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000048", "page": 36, "chunk": 0, "title": "Chad - Rural Mobility and Connectivity Project", "pdf_url": "http://documents.worldbank.org/curated/en/815491545534039786/pdf/Chad-PAD-11302018-636811128215032206.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Gender, Institutions and Development Database 2015", "label": "NAMED_DATA", "score": 0.6799352765083313, "start": 1864, "end": 1914, "probe_score": 0.7587, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nsafety, and traffic counts on select road sections), and the revision of design and maintenance\nstandards to reflect changing climate conditions, particularly related to drainage and slope\nstabilization. This subcomponent will also finance the preparation of routine maintenance manual for\nsmall contractors, and bidding documents and training on performance‐based contracts for road\nmaintenance. This subcomponent could benefit at later stages from additional support from disaster\nrisk management and climate adaptation funds.\n\n\n16. **Subcomponent 2.** Support the planning and implementation of road safety measures (US$2 million).\nThis subcomponent will benefit the Secretariat of the NRSC and will primarily finance the elaboration\nof a national strategy and action plan on road safety, as well as the implementation of select priority\nroad safety measures in collaboration with other interested parties. This subcomponent could benefit\nat later stages from grants from the GRSF and/or other interested donors.\n\n\n17. It is important to note that Lebanon has one of the worst road safety records globally, and that road\nsafety fatalities and injuries continue to rise. This has been affecting both Lebanese host communities\nand the Syrian refugees as evidenced in the road safety fatality and injury statistics prepared by the\nLebanese traffic police (see table 1.5 below), which remain underreported compared to WHO and\nWorld Bank estimates, given differing methodologies for accounting for road safety fatalities and\ninjuries.\n\n\n18. **Subcomponent 3.** Support planning and design studies (US$2 million). This subcomponent will finance\nCDR studies to prepare the required planning and design studies for critical transport projects\nidentified as priorities by the Lebanese governments.\n\n\nPage 54 of 90", "output": {"entities": {"named_data": [], "descriptive_data": ["road safety fatality and injury statistics"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 57, "chunk": 1, "title": "Lebanon - Roads and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/210611486651815142/pdf/Lebanon-Roads-Employment-PAD-P160223-01262017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "road safety fatality and injury statistics", "label": "DESCRIPTIVE_DATA", "score": 0.9074208736419678, "start": 1273, "end": 1315, "probe_score": 0.6355, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|**Component 3: Road Safety**|\n|Development<br>and<br>operationalization of the Road<br>Accident Database Management<br>System<br>Training<br>and<br>awareness<br>campaigns in the Project area|• <br>Road<br>safety<br>awareness<br>campaigns in the Project area,<br>and road safety data collection<br>and management as part of<br>contingency planning including<br>accident data attributed to<br>climate<br>change<br>such<br>as<br>increased runoff and higher<br>temperatures which increase<br>the pavement deterioration<br>hence the ride quality of the<br>road<br>and<br>necessitating<br>frequent<br>maintenance<br>routines.<br>• <br>Use<br>the<br>Road<br>Accident<br>Database Management System<br>to inform decision making<br>towards targeted interventions<br>that make the road safer to<br>users and more resilient to<br>climate change||\n\n\n\nPage 78 of 80", "output": {"entities": {"named_data": [], "descriptive_data": ["road safety data"], "vague_data": ["accident data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000146", "page": 82, "chunk": 1, "title": "Uganda - Roads and Bridges in the Refugee Hosting Districts/Koboko-Yumbe-Moyo Road Corridor Project", "pdf_url": "http://documents1.worldbank.org/curated/en/834931600048847296/pdf/Uganda-Roads-and-Bridges-in-the-Refugee-Hosting-Districts-Koboko-Yumbe-Moyo-Road-Corridor-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "road safety data", "label": "DESCRIPTIVE_DATA", "score": 0.5024296045303345, "start": 267, "end": 283, "probe_score": 0.0119, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "accident data", "label": "VAGUE_DATA", "score": 0.6551704406738281, "start": 361, "end": 374, "probe_score": 0.0483, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n\n\nproblems, and in each age group females reporting\nmore problems than males, except among children\nunder the age of 11, where boys reported slightly\nmore problems than girls.\n\n\nThese overall upward trends underscore that, even\nin the third year of the Ukraine response, mental\nhealth and psychosocial needs remain a significant\nand growing challenge requiring sustained support,\nattention, and increased financing to ensure\nadequate care and resources are available.\n\n\n**<u>% OF INDIVIDUALS WITH MENTAL HEALTH OR</u>**\n**PSYCHOSOCIAL PROBLEMS BY AGE GROUP AND GENDER**\n\n\nFemale Male\n\n\n\n**<u>% OF INDIVIDUALS WHO REPORT EXPERIENCING MENTAL</u>**\n**HEALTH AND PSYCHOSOCIAL PROBLEMS AND TRIED TO**\n**ACCESS SUPPORT BY COUNTRY**\n\n\n\n46%\n\n\n58%\n\n\n57%\n\n\n51%\n\n\n50%\n\n\n48%\n\n\n45%\n\n\n43%\n\n\n35%\n\n\n34%\n\n\n32%\n\n\n\n\n\nRegional\n\n\nHungary\n\n\nLatvia\n\n\nLithuania\n\n\nPoland\n\n\nCzechia\n\n\nEstonia\n\n\nBulgaria\n\n\nMoldova\n\n\nRomania\n\n\nSlovakia\n\n\n\n\n\n\n\n5-11 12-17 18-34 35-59 60+\nyears old\n\n(N=17,972)\n\n### **Access to Mental** **Health and** **Psychosocial** **Support**\n\nAmong the 23% of individuals reported to have\nmental health or psychosocial problems affecting\ndaily functioning (such as the ability to get out of\nbed, care for oneself or others, or carry out daily\nactivities such as cooking, going to school), 46%\n(47% of women and girls; 42% of men and boys)\nreported trying to access support. This means that\nmore than half (54%) of individuals experiencing\nsuch problems did not try to access support, which\nmay be due to multiple factors, including stigma,\nmental health awareness, or other access barriers.\n\n\n**20*", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000004", "page": 19, "chunk": 0, "title": "NAVIGATING HEALTH AND WELL BEING CHALLENGES FOR REFUGEES FROM UKRAINE   2nd Edition", "pdf_url": "https://local/jad_paddy_docs/navigating health and well-being challenges for refugees from ukraine - 2nd edition.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">Theory</mark> <mark>and</mark> <mark>Methods, 46:8, 3848</mark>\n<mark>[3863, DOI: 10.1080/03610926.2015.1073317](https://doi.org/10.1080/03610926.2015.1073317)</mark>\n\n\n<mark>Yi-Ting Chen (2018) A Unified Approach to Estimating and Testing Income Distributions With Grouped</mark>\n\n<mark>Data, Journal of Business & Economic Statistics, 36:3, 438-455</mark>", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000753", "page": 23, "chunk": 3, "title": "idu04f787105008b604f5108f1a061fe88def833", "pdf_url": "https://local/prwp/idu04f787105008b604f5108f1a061fe88def833.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " resistance.\nThe technique made use of readily available materials,\nand was relatively cheap and culturally adequate. The\nproject helped to restore confidence in adobe construction and created jobs for those to be relocated, including\nthe opening of an adobe factory.\n\n\nConstruction, however, was not completed as planned.\nNot all of the infrastructure and services were provided,\nand only 230 of the 498 homes were eventually built,\nwith the last houses completed in 2004. The new _barrio_\ndeveloped slowly and in a piecemeal way, with new units\nonly built when the municipality had the funds to do so.\n\n\nBeyond the initial post-disaster phase, when the municipality succeeded in mobilising its traditional develop\n\n\n102 This case study draws on research by Dr Esther Leemann for the 2005 project _Towards sustainable disaster preparedness: the role of local,_\n_national and global responses in enhancing societal resilience to natural hazards in India and Nicaragua,_ funded by the Swiss National\nScience Foundation (SNSF) and the Swiss Agency for Development Cooperation (SDC)\n\n103 Based on a review of data from the municipality and the National Information and Development Institute (INIDE), 2005\n\n104 Calculated using IDMC’s methodology for displacement caused by disasters, by multiplying the number of destroyed homes by average\nhousehold size. In the absence of data from 1999, household size was determined using UN fertility rate data for 2010 to 2015\n\n105 _Op. cit._ INIDE, 2005\n\n106 Leemann, E.“Communal leadership in post-Mitch housing reconstruction in Nicaragua”. In: Duyne Barenstein, Jennifer and Esther Leemann\n(eds.), _Post-Disaster Reconstruction and Change: Communities’ Perspectives._ Boca Raton: CRC Press, Taylor & Francis Group, 2013\n\n107 Leemann, E. “Housing Reconstruction in Post-Mitch Nicaragua: Two Case Studies from the Communities of San Dionisio and Ocotal”, In:\nMiller, DeMond", "output": {"entities": {"named_data": [], "descriptive_data": ["data from the municipality"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001319", "page": 31, "chunk": 2, "title": "Urban informal settlers displaced by disasters: challenges to housing responses", "pdf_url": "https://reliefweb.int/attachments/cb1a9a83-bd0e-3f4b-ab49-79a6c8cdc297/201506-global-urban-informal-settlers.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from the municipality", "label": "DESCRIPTIVE_DATA", "score": 0.8372566103935242, "start": 1106, "end": 1132, "probe_score": 0.8167, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "output": {"entities": {"named_data": [], "descriptive_data": ["random survey"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011960", "page": 16, "chunk": 0, "title": "Kenya - National Agricultural Research Project : Phase II", "pdf_url": "https://documents.worldbank.org/curated/en/371471468774952141/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7714613080024719, "start": 379, "end": 395, "probe_score": 0.582, "gold": "NON_MENTION", "gold_tier": "human-final"}, {"text": "random survey", "label": "DESCRIPTIVE_DATA", "score": 0.7173007130622864, "start": 1487, "end": 1500, "probe_score": 0.012, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "عتها\n\nب توفير بقية لحتياجات المالية إلعادة **ا** . س وف تقوم حكومة جيبوتيلجتماعي للبنك الدولي **ا** ووفقا إلجراءات الضمان لستراتيجية **ا**\n\n\n\n**ا** **ا** **ا**\n\nمن .خالل برامج اإلسكان األخرىوقد يكون ذلك ،)ماليين دوالر أمريكي اإلعمار (المقدرة بنحو5\n\n\n\nفي األحياء الحضرية المختارة للمكو ن الفرعيالمشروع يتبنى. **<u>المكو ن الفرعي2.2: المشاركة المجتمعية وتوظيف الشباب</u>** .32\n\nفي الدورة الكاملة لعملية تصميماألحياء العشوائية وذلك بهدف إشراك المجتمعات المستهدفة نهجا ًتشاركيا شامالً لتشجيع تطوير 2.1\n\nلستثمارات المختلفة . سيقوم المشروع بتبسيط وا ضفاء طابع رسمي على النهج التشاركي و طلبات إصالح المظالم من أجل **ا** وصيانة\n\nمحددة يمكن أن تستفيد من", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000018", "page": 23, "chunk": 4, "title": "Djibouti - Integrated Slum Upgrading Project", "pdf_url": "http://documents1.worldbank.org/curated/en/164091553234500653/pdf/PAD2774-PAD-ARABIC-P162901-PUBLIC.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on social development issues"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011661", "page": 24, "chunk": 0, "title": "Ethiopia - Fourth Telecommunications Project", "pdf_url": "https://documents.worldbank.org/curated/en/350571468914988674/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on social development issues", "label": "VAGUE_DATA", "score": 0.581004798412323, "start": 1670, "end": 1703, "probe_score": 0.333, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "activities, and has Government support through the development of a land management\npolicy.\n\n\n**Agricultural Rehabilitation and SLM Project, Burundi (IDA Grant H1170, ID:**\n**P064558):** SLM projects need to deal effectively with economic and social issues.\nBrazil’s experience shows that outcomes from SLM practices are unlikely to benefit\nevenly, and compensation mechanisms for “losers”, if any, should be identified.\nKAPSLM will support adoption of SLM practices and linking conservation objectives\nwith production and income objectives.\n\n\n**Land degradation-related projects supported by GEF.** A review of the “GEF Land\nDegradation Linkage Study” from 2001 recommended that projects should not only focus on\nredressing the effects of land degradation, such as soil erosion, vegetation destruction, and water\npollution, but also on the drivers of land degradation, and on M&E of land degradation projects.\nKAPSLM will support development and implementation of a viable M&E system that will\ninclude environmental and social indicators.\n\n\n**Lessons from UNDP Assessment.** Lessons learned from a UNDP assessment of eight land\ndegradation projects supported by GEF indicate that: (i) the development of viable alternative\nland use systems require a substantial investment in high-quality targeted research; and (ii) large\nand rapid impacts on land degradation may be obtained by addressing policy and economic\nstructures affecting land use. KAPSLM incorporates these lessons by including components\naimed at informing policy makers (through studies and project activities that are likely to put\npressure on policy areas) where reforms are needed to develop a positive policy environment.\n\n\n**Alternatives considered and reasons for rejection**\n\n\n**The project was initially designed as part of a larger IDA program (KAPP).** An APL was\nselected as the instrument for KAPP. While KAPP has been ongoing, the preparation of\nKAPSLM has lagged, due to the", "output": {"entities": {"named_data": ["GEF Land\nDegradation Linkage Study"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011379", "page": 22, "chunk": 0, "title": "Kenya - Agricultural Productivity and Sustainable Land Management Project", "pdf_url": "https://documents.worldbank.org/curated/en/331301468283550731/pdf/kAPSLM0PID010Appraisal0Stage.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "GEF Land\nDegradation Linkage Study", "label": "NAMED_DATA", "score": 0.8000674247741699, "start": 617, "end": 651, "probe_score": 0.8604, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<br>See Annex I for country codes used.<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|**Table 6. Annual asylum applications lodged in industrialized countries by origin, 2007**<br>Covering 29 major asylum countries which provided monthly data to UNHCR. Values between 1 and 4 have been replaced with an asterisk.<br>See Annex I for country codes used.<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|**Table 6. Annual asylum applications lodged in industrialized countries by origin, 2007**<br>Covering 29 major asylum countries which provided monthly data to UNHCR. Values between 1 and 4 have been replaced with an asterisk.<br>See Annex I for country codes used.<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|**Table 6. Annual asylum applications lodged in industrialized countries by origin, 2007**<br>Covering 29 major asylum countries which provided monthly data to UNHCR. Values between 1 and 4 have been replaced with an asterisk.<br>See Annex I for country codes used.<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|**Table 6. Annual", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["monthly data", "monthly data", "monthly data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001058", "page": 17, "chunk": 4, "title": "Asylum levels and trends in industrialized countries, 2007", "pdf_url": "https://reliefweb.int/attachments/a0f955c8-b460-3603-b1cc-8d2ccc064a5f/BF4CF8525B21A81049257410001BC61A-Full_Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "monthly data", "label": "VAGUE_DATA", "score": 0.678413987159729, "start": 248, "end": 260, "probe_score": 0.5506, "gold": "NON_MENTION", "gold_tier": "human-final"}, {"text": "monthly data", "label": "VAGUE_DATA", "score": 0.6197843551635742, "start": 578, "end": 590, "probe_score": 0.6221, "gold": "NON_MENTION", "gold_tier": "human-final"}, {"text": "monthly data", "label": "VAGUE_DATA", "score": 0.5452378988265991, "start": 908, "end": 920, "probe_score": 0.5255, "gold": "NON_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "rehabilitation (disaggregated by<br>infrastructure type, gender, displacement status)<br>(Number)||0.00|35,000.00|80,000.00|\n|Percentage of subprojects for which arrangements<br>for operations and maintenance are established<br>(disaggregated by infrastructure type).<br>(Percentage)||0.00|60.00|75.00|\n|**Component 2: Local Institution Strengthening**|**Component 2: Local Institution Strengthening**|**Component 2: Local Institution Strengthening**|**Component 2: Local Institution Strengthening**|**Component 2: Local Institution Strengthening**|\n|Percentage of BDC/PDC members trained<br>(disaggregated by gender, displacement status).<br>(Percentage)||0.00|60.00|80.00|\n|Percentage of leadership positions held by women<br>in BDCs/PDCs. (Percentage)||0.00|20.00|40.00|\n|Percentage of women in O&M groups.<br>(Percentage)||0.00|15.00|50.00|\n|Percentage of BDCs/PDCs engaged in DRM<br>activities to reduce the vulnerability to climate-<br>sensitive natural hazards, such as floods and<br>droughts. (Percentage)||0.00|15.00|30.00|\n\n\n\nPage 52 of 94", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 57, "chunk": 1, "title": "South Sudan - Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/824121596765983121/pdf/South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\naccordance with agreed financing percentages.\n\n54. The primary disbursement method will be advances. The Project will be also able to process reimbursements and\ndirect payments if required. Fund flow will rely on existing Consortium (i.e., Country) systems: the CIM-AMFRI will make\nall payments using the Bertha System once payment obligations have been committed and verified.\n\n\na. Funds will be transferred to a specific segregated bank account (designated account [DA]), which is to be\n\nopened specifically for the Project and administered by the CIM-AMFRI. This account will be opened at a\ncommercial bank acceptable to the World Bank (Banco do Brasil). The account will be denominated in Brazilian\nreais (BRL). Project payments to beneficiaries’ accounts will be transferred from the DA.\nb. The CIM-AMFRI will register payment processes in the Bertha System. The records will be reconciled at the\n\nend of each month.\n**c.** The CIM-AMFRI will prepare Statements of Expenditures (SOEs) using information available in the Bertha\n\nSystem. The SOEs will be supported by the accounting records. <sup>56</sup>\n\n55. The DA ceiling will be variable. The Minimum Application Size (MAS) for direct payment Withdrawal Applications\n(WAs) will be US$1,000,000 equivalent. The Eligible expenditures paid from the DA are to be presented at least once every\nsix months.\n\n56. The Project will report on the use of advances and process reimbursement requests through WAs supported by\nSOEs. Direct payments will be documented by records. The CIM-AMFRI will approve WAs documenting expenditures based\n\n\n56 The General Conditions require the Borrower to retain all records (contracts, orders, invoices, bills, receipts, and other documents) evidencing\neligible expenditures and to enable the Bank’s representatives to examine such records. They also require the records to be retained for at", "output": {"entities": {"named_data": ["Bertha System", "Bertha System", "Bertha\n\nSystem"], "descriptive_data": ["accounting records"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000182", "page": 56, "chunk": 1, "title": "Brazil - Integrated Sustainable Mobility Project in the Foz do Rio Itajaí Region", "pdf_url": "https://documents1.worldbank.org/curated/en/099032624162515430/pdf/BOSIB-60d57288-4e09-4519-ae6c-ffdc0037e0b1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Bertha System", "label": "NAMED_DATA", "score": 0.5084892511367798, "start": 306, "end": 319, "probe_score": 0.5826, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Bertha System", "label": "NAMED_DATA", "score": 0.5595808625221252, "start": 850, "end": 863, "probe_score": 0.3259, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Bertha\n\nSystem", "label": "NAMED_DATA", "score": 0.6045172810554504, "start": 1026, "end": 1040, "probe_score": 0.3015, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "accounting records", "label": "DESCRIPTIVE_DATA", "score": 0.5928223133087158, "start": 1076, "end": 1094, "probe_score": 0.3695, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " cases, the numbers went up significantly compared\nto 2012 (+365% and 142% respectively).\nFrance, the third largest recipient of\nRussian asylum claims in 2013 with\n4,600 applications, however, recorded\na decrease of 13 per cent compared to\n2012 (5,400 claims). Other important\ndestination countries were Austria\n(2,800 claims), Sweden (1,000 claims),\nand Denmark (980 claims). Overall,\nasylum claims from the Russian Federation accounted for 7 per cent of all\napplications recorded among the 44 industrialized countries.\n\n**Afghanistan** dropped from being\nthe main country of origin of asylumseekers in industrialized countries in\n2012 to third place a year later. Provisional data indicate that 38,700 Afghans requested refugee status in 2013,\na drop of 8,900 applications or 19 per\ncent. The share of asylum-seekers\nfrom Afghanistan in the total number of asylum claims dropped from\n10 to 6.5 per cent as a result of the\nlower number of applications in 2013.\nTurkey remained the prime destination for Afghan asylum-seekers with\n8,700 claims registered in 2013, despite\na 38 per cent drop compared to 2012\n\n\n\n\n\n\n\n\n\n\n\n**18** UNHCR Asylum Trends 2013", "output": {"entities": {"named_data": ["UNHCR Asylum Trends 2013"], "descriptive_data": [], "vague_data": ["Provisional data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001462", "page": 17, "chunk": 1, "title": "UNHCR Asylum Trends 2013: Levels and Trends in Industrialized Countries", "pdf_url": "https://reliefweb.int/attachments/e3c004e1-00b1-35e4-9688-91cf1e57dc5a/Asylum%20Trends%202013.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Provisional data", "label": "VAGUE_DATA", "score": 0.7613623142242432, "start": 666, "end": 682, "probe_score": 0.1149, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHCR Asylum Trends 2013", "label": "NAMED_DATA", "score": 0.6918479800224304, "start": 1126, "end": 1150, "probe_score": 0.9571, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " than that for male beneficiaries. Women will be targeted for inclusion in planning\ncommittees, where relevant, and they will be incentivized to participate in and use all projectfunded services and activities.\n\n116. **The project will also support women’s employment in the energy sector.** Employment\nopportunities will be created for female technicians and engineers in O&M activities. Limited sexdisaggregated data are available, but <mark>global data indicate that women are underrepresented in both</mark>\n<mark>technical and nontechnical roles and that the sector as a whole is male dominated. Field</mark> evidence further\nreports a near-complete lack of women in similar operations in Chad, which explains the baseline to be\nassessed as zero. The key barriers for accessing these jobs were assessed to stem primarily from lack of\nskills/education and social norms/lack of targeted recruitment. Therefore, private O&M companies will\nbe mandated to train and employ female professionals to boost women’s opportunities for joining the\nsector and help them overcome the key barrier of school-to-work transition and access to technical skills\nand men-dominated jobs. They will also be expected to accommodate women through a more equitable\nemployment policy, which is currently lacking in most operations and limits employment possibilities.\n\n117. **M&E.** Several indicators will monitor project progress with respect to gender, including\n(a) A percentage of female-headed households provided with electricity access under the project.\n\n\n\nThis indicator will track progress toward raising the share of electrified households that are female\nheaded to 15 percent. This percentage is based on the level of their prevalence recently measured\nby the survey on the ability and willingness of households to pay for electricity, provided in annex\n6, updating earlier data. This indicator will be applied to Component 1 and Subcomponent 2.3;\n(b) A percentage of women technicians employed in O&M under Component 1 and Subcomponents\n\n\n\n2", "output": {"entities": {"named_data": [], "descriptive_data": ["sexdisaggregated data"], "vague_data": ["global data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000193", "page": 48, "chunk": 1, "title": "Chad - Energy Access Scale Up Project", "pdf_url": "https://documents1.worldbank.org/curated/en/860701648216750651/pdf/IBArchive-bd2c789e-ee04-4df7-a219-9409a5f705d3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "sexdisaggregated data", "label": "DESCRIPTIVE_DATA", "score": 0.7131137251853943, "start": 397, "end": 418, "probe_score": 0.1156, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "global data", "label": "VAGUE_DATA", "score": 0.8299614787101746, "start": 444, "end": 455, "probe_score": 0.2257, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". As argued by Hausmann\n(2003), there is a major difference between Venezuela, on the one hand, where oil exports are, so\nto speak, the only game in town, and countries like Brazil and Colombia, which have\nexperienced substantial terms of trade gains and yet display a significantly greater degree of\nexport diversification. Beyond these latter countries lies Mexico, an oil exporter that also has one\nof the highest index of export product diversification in the region. Third, the rise in export\nconcentration during the recent commodity bonanza, however, has not led to a reduction of the\nnumber of exports. As shown in Table 1, the number of exports for most of the larger LAC\ncountries has not only not declined, but it has increased in some cases. Moreover, the LAC\ncountries reported in Table 1 export a surprisingly high number of goods, relative to the potential\nmaximum number of products as classified by the Standard International Trade Classification\nRevision 3 at the 6-digit level.\n\n\nBe that as it may, another worry about LAC’s trade comes from the fact that there is little\nevidence suggesting that intra-industry trade (IIT) has been playing a significant growthenhancing role for LAC. As suggested by many in the literature, the degree of IIT between two\ncountries can be used as a proxy for technology diffusion and knowledge spillovers. <sup>29</sup> [^29: See, for example, Bernstein and Nadiri (1988), Helpman and Krugman (1989), and Badinger and Egger (2010).] In Figure\n\n\n27 The measure of complexity in Hausmann et al (2011) takes into account, among other things, the number of\nproducts a country exports (“diversity”) and the number of countries that export those products (“ubiquity”). Japan\nand Germany, at the top of the complexity ranking, export many goods that are of low ubiquity and that are\nproduced by highly diversified countries.\n\n28 Data on trade volumes are not available in sufficient disaggregated detail", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Data on trade volumes"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005955", "page": 19, "chunk": 1, "title": "wps6837", "pdf_url": "https://local/prwp/wps6837.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data on trade volumes", "label": "VAGUE_DATA", "score": 0.6703423857688904, "start": 1874, "end": 1895, "probe_score": 0.6016, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Types of program Implementation, monitoring and evaluation data**\nDifferent types of data help humanitarian actors understand the situation of people living with\ndisabilities and the progress of the response.\n\n\n1. Data at the **individual level** that identifies disability, needs, and barriers individuals may face as well\nas the capacities they may have. Individual data allows the population to be differentiated, providing\nan insight into size of the population of persons with disabilities that allows meaningful planning\ntargets to be set and evaluations to occur. Individual data can be obtained in two ways:\n\n\n  - Data that **extrapolates for the whole population** such as a national census or large-scale sample\nsurvey helps determine prevalence, and is useful to shape programmatic interventions. This type\nof individual data is better gathered in advance of the crisis, and where it exists this type of data\nprovides an excellent baseline against which to assess the response during an evaluation.\n\n\n  - **Administrative processes** where data from individuals is collected during the course of a\nhumanitarian response can also be used effectively to understand how people with disabilities\nare being reached. Data such as collected by UNHCR when a refugee is registered that is entered\ninto the “ProGres” database can be used by the humanitarian community to understand the\nprevalence of persons with disabilities. Administrative data of this type has limitations if it was\nimproperly captured, if individuals were “unregistered”, or their disabilities were “unidentified”.\n\n\n2. **Service level data** on the availability of inclusive services (or barriers to be addressed) does not track\nindividuals, but the proportion of services, facilities or activities in terms of accessibility to persons\nwith disabilities. Data of this type can be used for program planning, setting targets, measuring\nprogress and evaluations. During a humanitarian action, this kind of data may be easier to obtain.\nThis kind of data looks at the proportion of WASH facilities are accessible, for example", "output": {"entities": {"named_data": ["ProGres"], "descriptive_data": ["national census", "large-scale sample\nsurvey", "Administrative data", "Service level data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001044", "page": 14, "chunk": 0, "title": "Collecting Data on Persons with Disabilities in Humanitarian Contexts", "pdf_url": "https://reliefweb.int/attachments/9e8bf575-fe63-3807-9e67-18fad3d0a5b1/workshop_report_270318_004.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "national census", "label": "DESCRIPTIVE_DATA", "score": 0.8277655839920044, "start": 686, "end": 701, "probe_score": 0.1314, "gold": "DATA_MENTION", "gold_tier": "flip"}, {"text": "large-scale sample\nsurvey", "label": "DESCRIPTIVE_DATA", "score": 0.8597522377967834, "start": 705, "end": 730, "probe_score": 0.0326, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "ProGres", "label": "NAMED_DATA", "score": 0.7978785037994385, "start": 1311, "end": 1318, "probe_score": 0.0, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Administrative data", "label": "DESCRIPTIVE_DATA", "score": 0.517009437084198, "start": 1430, "end": 1449, "probe_score": 0.0, "gold": "DATA_MENTION", "gold_tier": "flip"}, {"text": "Service level data", "label": "DESCRIPTIVE_DATA", "score": 0.7797842621803284, "start": 1596, "end": 1614, "probe_score": 0.2674, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the rural labor\nmarket in pilot areas. Furthermore, seeking to promote the demand for employment through enhanced\ncontract farming has the potential to build this approach into the agricultural sector more broadly.\n\n\n82. Finally, the project aims to enhance the capacity of the ACC to ensure that the interventions and\nactivities supported by the project are scalable, thereby moving toward formalization of agriculture\nworkers more generally. These tools and practices (that is, registry of skilled workers and database of\nvacancies and training materials) are designed to be easily extended in other rural areas even beyond\nthose with presence of refugees.\n\n\n**IV.** **PROJECT APPRAISAL SUMMARY**\n\n\n**A. Technical and Economic Analysis**\n\n\n83. **The project design draws on international best practice by integrating supply- and demand-side**\n**interventions targeted to vulnerable populations in rural areas, both refugees and natives, in the**\n**agriculture sector in Turkey.** As explained in the section on lessons learned, integrated interventions that\ncombine supply- and demand-side approaches fare better in improving employability. In the current\ncontext, both demand and supply factors affect the employment capacity for vulnerable populations in\nthe rural areas in Turkey (Table 2). On the supply side, agricultural workers lack job-relevant skills including\nlanguage, technical, and behavioral. They also lack information about the possibility of and benefits from\nformal employment, particularly for the refugee population. Finally, workers can have trouble signaling\n\n\nPage 31 of 85", "output": {"entities": {"named_data": [], "descriptive_data": ["registry of skilled workers", "database of\nvacancies and training materials"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000114", "page": 34, "chunk": 1, "title": "Turkey - Agricultural Employment Support for Refugees and Turkish Citizens through Enhanced Market Linkages Project", "pdf_url": "http://documents1.worldbank.org/curated/en/671481617301015363/pdf/Turkey-Agricultural-Employment-Support-for-Refugees-and-Turkish-Citizens-through-Enhanced-Market-Linkages-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "registry of skilled workers", "label": "DESCRIPTIVE_DATA", "score": 0.8867179155349731, "start": 481, "end": 508, "probe_score": 0.0005, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "database of\nvacancies and training materials", "label": "DESCRIPTIVE_DATA", "score": 0.8982347249984741, "start": 513, "end": 557, "probe_score": 0.0036, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Zero** **N** **%** **Missing** **N** **%**\n\n\nNot‐tagged 11,310 97.9 Not‐tagged 10,862 94\n\n\nTagged 243 2.1 Tagged 691 6\n\n\nTotal 11,553 100 Total 11,553 100\n\n\nThe medians are calculated following exactly the same process as in food cleaning. All medians are estimated at the\nEA level if a minimum of 5 observations are available. If the minimum number of observations is not met, weighted\nmedians are estimated at the strata‐level requiring a minimum number of 10 observations before proceeding to the\nitem level. Medians are calculated excluding zero values and tagged values so as not to replace reported values with\nzeroes or invalid values.\n\n\nFor durables, the cleaning process involved cleaning ownership statistics as well as the calculated depreciation rates.\nThe quantity of an item is replaced by the item‐specific survey median (due to paucity of data) if the reported\nquantity is unrealistically high assessed by manual inspection. The purchase value of durables is recorded in the year\nand currency of purchase. Outliers of purchase values in the reported currency are identified by hard constraints\nand replaced by the item‐specific survey median. Items with at least 3 observations purchased in the same year are\nreplaced by the respective item‐year specific median. Alternatively, the item‐state‐level median prices are used if at\nleast 5 observations are given. Hypothetical selling prices are replaced by the item‐state level median if at least 5\nobservations are available. Without the minimum number of observations available, the item‐specific median is\nused. All prices reported in foreign currencies are converted into SSP through conversion to USD.\n\n\n   - Rule 1 (quantity outliers): Quantities above 100 units of an asset are replaced with the item‐specific median.\n\n\n**N** **%**\n\n\nNot‐\n5,007 99.9\ntagged\n\nTagged", "output": {"entities": {"named_data": [], "descriptive_data": ["item‐specific survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007628", "page": 33, "chunk": 0, "title": "wps8722", "pdf_url": "https://local/prwp/wps8722.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "item‐specific survey", "label": "DESCRIPTIVE_DATA", "score": 0.5132114291191101, "start": 810, "end": 830, "probe_score": 0.3905, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " protection.\nThis takes into account, that:\n\n\n- The sector can provide both short term\njobs and sustainable income generating\nopportunities without large capital\ninvestments;\n\n\n- Syrians under temporary protection in\nTurkey have been living in areas with similar\necosystems (climates, soil composition, and\nbiological diversity) and that agriculture\nis concentrated in refugee-dense areas of\nTurkey; and,\n\n\n- Many Syrians under temporary protection\nhave been involved in agricultural\nproduction before the crisis, and their\nknowledge and experience in agriculture is\noften greater than it is in other sectors.\n\n\nGiven increased food prices, combined\nwith other risks surrounding the Turkish\neconomy, it is important to adopt a\nstrategy of supporting the most vulnerable\nsegments of the population of Syrians under\ntemporary protection and host communities\nwith tools and means to produce their own\nfood (fresh fruit and vegetable) in order to\nprotect households against rising prices and\nthe economic outlook.\n\n\n\n22\n23\n\n\n24\n25\n\n\n\nhttp://www.turkstat.gov.tr\nAgricultural Livelihoods and Labour Market Assessment, FAO and Ankara University Development Studies Research and\nApplication Centre, Forthcoming\nhttp://www.tuik.gov.tr/PreHaberBultenleri.do?id=24635\nWhile official data is not available on exact numbers, Syrian agricultural workers have been reported in 45 provinces\nacross the country. (Parliamentary Research Committee on the Problems of the Agricultural Workers, Commission\nReport prepared by the Parliament Speaker Cemil Cicek, 2015)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["official data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000196", "page": 31, "chunk": 2, "title": "Turkey: 3RP Country Chapter - 2019/2020 [EN/TR]", "pdf_url": "https://reliefweb.int/attachments/13e868fe-f867-3866-ad71-478dc409516b/68618.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "official data", "label": "VAGUE_DATA", "score": 0.7034755349159241, "start": 1263, "end": 1276, "probe_score": 0.0748, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|80|119|117|426|\n|South Lebanon|37|50|38|27|152|\n|Total|318|330|314|313|1275|\n|percent of total|24.52|25.44|24.21|24.13|98.30|\n\n\n\n6. Based upon the rehabilitation unit costs and existing surface areas presented in Table 3\nbelow, the cost of works was calculated for all 399 eligible schools. As a result, the total needed\nbudget to repair all these schools is US$121 million. With the proposed amount of\nsubcomponent financing, the project can finance the full rehabilitation of the first 10 schools of\nthe priority list.\n\n\n7. Project preparation included the preparation of a database which accounts for many of the\nschool facilities characteristics in order to prepare criteria and indicators for the selection of\npriorities. These show that out of the 1,275 schools during school year 2014-15:\n\n\n    - Some 708 schools do not belong to MEHE and rent is paid for 540 of them;\n\n    - 306 (20 percent) of school buildings were not originally designed as schools;\n\n    - Almost 95 percent of the public schools have Syrian students during the 1st shift;\n\n    - 89 schools have second shifts for Syrians;\n\n    - 652 schools are located in vulnerable areas as per the Education Working Group\n\nstandards.\n\n\n27", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["database"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000030", "page": 35, "chunk": 1, "title": "Lebanon - Emergency Education System Stabilization Project", "pdf_url": "http://documents.worldbank.org/curated/en/578481467991017996/pdf/PAD1190-PAD-P152848-PUBLIC-Box391435B-LB-EESSP-Final-PAD-for-printing.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "database", "label": "VAGUE_DATA", "score": 0.5580024719238281, "start": 577, "end": 585, "probe_score": 0.4667, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000102", "page": 19, "chunk": 1, "title": "Burundi - Second Social Action Project", "pdf_url": "http://documents1.worldbank.org/curated/en/590301468744270104/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7292463183403015, "start": 272, "end": 283, "probe_score": 0.8771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " stress on social life and\nlocal infrastructure caused by the population growth\nand density. <sup>177</sup>, <sup>178</sup> To address the negative impacts of\nthe Rohingya influx on the host community, the JRP\nmakes provision for 25% of donor funding for host\ncommunities. <sup>179</sup>\n\n\nQualitative results also show that the Rohingya refugees\nfeel that the local community perceives them as\n“culprits”. There has been a negative perception in the\nhost community that the religious beliefs and practices\nof the Rohingya are different and regressive. The strong\nnegative sentiments towards Rohingya refugees is also\nreflected in the Ground Truth Solutions Survey in January\n2019 <sup>180</sup> on social cohesion, where the majority (61%) of\nthe Rohingya refugees compared to only about one third\n(31%) of the Bangladeshi locals believe that there is intercommunity harmony between the Rohingya and the host\ncommunities.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n22 Camps 1, 1E, 2, 15.\n23 Camps 11, 12.", "output": {"entities": {"named_data": ["Ground Truth Solutions Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000732", "page": 60, "chunk": 1, "title": "An intersectional analysis of gender amongst Rohingya refugees and host communities in Cox’s Bazar, Bangladesh", "pdf_url": "https://reliefweb.int/attachments/6b69cc90-e03e-3419-8199-a82b4a40691f/Coxs-Bazar-Gender-and-Intersectionality-Analysis-report_2020.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Ground Truth Solutions Survey", "label": "NAMED_DATA", "score": 0.8993039131164551, "start": 635, "end": 664, "probe_score": 0.1849, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda COVID-19 Education Response Project (P174033)\n\n\nFinancing Facility Advisory Services and Analytics is providing catalytic resources to provide technical assistance\nin three main areas linked to strengthening continuity of health services during the context of COVID-19.\n\n\n**B. Sectoral and Institutional Context**\n\n\n11. **In Uganda, there are over 15 million students enrolled in the education system, including higher**\n**education.** The majority of Ugandan students are enrolled in day schools while others are in boarding schools\nwhere many facilities are shared and students are constantly in close contact with each other, their teachers and\nother visitors on a daily basis, presenting an environment for easy transmission of the COVID-19. <mark>The education</mark>\n<mark>[system in Uganda has a structure of seven years of primary education](https://en.wikipedia.org/wiki/Primary_education)</mark> _<mark>,</mark>_ <mark>[six years of secondary education](https://en.wikipedia.org/wiki/Secondary_education)</mark> <mark>(divided</mark>\n<mark>into four years of lower secondary and two years of upper secondary school). Based on the data in 2017, the gross</mark>\n<mark>enrollment</mark> <sup>8</sup> [^8: EMIS data 2017, Ministry of Education and Sports] <mark>for preprimary was 14.4 percent, primary 115.7 percent, and secondary 28 percent, respectively.</mark>\n\n12. **All schools are currently closed as part of the Government’s COVID-19 response.** In response to the\ndanger posed by the pandemic to Ugandan students, the Government announced the closure of all schools from\nMarch 20, 2020 for a period of 30 days in a bid to", "output": {"entities": {"named_data": ["EMIS data 2017"], "descriptive_data": [], "vague_data": ["data in 2017"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000034", "page": 12, "chunk": 0, "title": "Uganda - COVID-19 Emergency Education Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/645041598936002560/pdf/Uganda-COVID-19-Emergency-Education-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data in 2017", "label": "VAGUE_DATA", "score": 0.6442813873291016, "start": 1166, "end": 1178, "probe_score": 0.9998, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "EMIS data 2017", "label": "NAMED_DATA", "score": 0.8455054759979248, "start": 1239, "end": 1253, "probe_score": 0.9653, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "DJIBOUTI\nSchool Access and Improvement Program\n\n\n**Project Appraisal Document**\n\n\nMiddle East and North Africa Region\n\nMNSHD\n\n\n\nDate: November 17, 2000 Team Leader: Qaiser M. Khan\n\n\n\nCountry Director: Inder K. Sud Sector Director: Baudouy\nProject **ID:** P044585 Sector(s): EP - Primary Education, ES - Secondary\n\n\n\n. Education\nLending Instrument: Adaptable Program Loan <sup>(APL)</sup> Theme(s): Education; Gender and development\n\n\n\nPoverty Targeted Intervention: N\n\n\n\nProgram Fin ncing Data\n\n\n\nEstimated\nAPL Indicative Financing Plan Implementation Period (Bank FY) Borrower\n\n\n\n**IBRD** Others **Total** **COMMITMENT** **Closing**\n**US$** m % US$ m US$ m Date Date\nAPL 1 10.00 75.8 3.20 13.20 03/31/2001 06/30/2005 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\n________________ Education\n\n\n\nAPL 2 10.0 65.8 5.20 15.20 07/01/2005 06/30/2008 Republic of\n\n\n\nLoan/ Credit Djibouti\n\n\n\nCredit Ministry of\n\n\n\ni_________ ________________ Education\n\n\n\nAPL 3 10.00 41.0 14.40 24.40 07/01/2008 06/30/2011 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\nEducation\n\n\n\nTotal 30.00 22.80 52.80\nProject Financing Data Credit\nFor Loans/Credits/Others: Amount (US$m): 10.0\n\n\n\nProposed Terms: Standard Credit\n\n\n\nGrace period (years): 10 Years to maturity: 40\nCommitment fee: 0.50% (0% for FY01) Service charge: 0.75", "output": {"entities": {"named_data": ["Project Financing Data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010745", "page": 4, "chunk": 0, "title": "Kenya - Health Rehabilitation Project", "pdf_url": "https://documents.worldbank.org/curated/en/286731468277744556/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Project Financing Data", "label": "NAMED_DATA", "score": 0.5102046728134155, "start": 1106, "end": 1128, "probe_score": 0.1169, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda Secondary Education Expansion Project (P166570)\n\n\n\n|Col1|Col2|Col3|Col4|(about 590,000) and<br>50% of students<br>enrolled in private<br>schools (about 322,000)<br>and students enrolled<br>in new schools. The<br>training of the teachers<br>will be done gradually:<br>25% trained in Y2, 50%<br>by Y3, 75% by Y4 and<br>100% by Y5. Students<br>from the new schools<br>are included as well.|Col6|\n|---|---|---|---|---|---|\n|Students benefiting from direct<br>interventions to enhance learning -<br>Female||Same as for<br>the core<br>indicator<br> <br>|Same as for<br>the core<br>indicator<br>|<br>Same as for the core<br>indicator<br>|Same as for the core<br>indicator<br>|\n|Enrolment at public lower secondary<br>schools in targeted districts, girls|The indicator will measure<br>the number of female<br>students who will annually<br>enroll in public school in the<br>targeted districts (2017 is<br>the baseline year).<br>|<br>Measuremen<br>t will be<br>taken at<br>project<br>midterm and<br>end of<br>project.<br>|<br>EMIS<br>|Headcount<br>|MoES<br>|\n|Enrolment at", "output": {"entities": {"named_data": ["EMIS", "MoES"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000060", "page": 56, "chunk": 0, "title": "Uganda - Secondary Education Expansion Project", "pdf_url": "http://documents1.worldbank.org/curated/en/406361595815248191/pdf/Uganda-Secondary-Education-Expansion-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "EMIS", "label": "NAMED_DATA", "score": 0.6574360728263855, "start": 1042, "end": 1046, "probe_score": 0.7645, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "MoES", "label": "NAMED_DATA", "score": 0.5296992063522339, "start": 1065, "end": 1069, "probe_score": 0.7645, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nhealth, nutrition, and livelihoods. Access to sufficient fuel for cooking is a major challenge, and the\nconsumption of firewood is a driver of environmental degradation and a major source of protection risk,\nespecially for women and children who are mostly tasked with gathering firewood. Shortage of fuel for\ncooking causes competition for these resources and tensions between refugees and nearby host\ncommunities. Alleviating energy deprivation can provide significant benefits associated with better\nlighting, protection, gender equality, food security, water, sanitation and health, education, livelihoods,\nconnectivity, and environmental protection.\n\n6. The project aims to alleviate energy deprivation of about 400,000 refugees from 20 refugee camps\nand a city and 740,000 people from host communities located within 25 km from refugee camps, including\nboth rural areas and cities. In addition, it will provide electricity access for 150 medical centers and 200\nschools that are located in areas comprising refugee camps and host communities, as well as for 500 PUEs.\nThe eligibility criteria of 25 km for host communities was replicated from the ongoing PARCA that aims to\n(a) improve access of refugees and host communities to basic services, livelihoods, and safety nets in\nseven provinces and (b) strengthen country systems to support refugees. Synergies will be exploited\nbetween the project and PARCA. The activities of the project will align with preexisting and ongoing\ninitiatives from the UNHCR and implementing partners toward better energy access for refugees. In\nparticular, targeting of refugees will be coordinated with them through already available data, and\ncapacity building of refugees in implementation and maintenance could be provided by the UNHCR. The\nproject will adapt as needed to changing circumstances during implementation with respect to focus\nsites/areas, including the ability to serve new refugee camps and nearby host communities.\n\n\nPage 68 of 87", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["already available data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000193", "page": 73, "chunk": 1, "title": "Chad - Energy Access Scale Up Project", "pdf_url": "https://documents1.worldbank.org/curated/en/860701648216750651/pdf/IBArchive-bd2c789e-ee04-4df7-a219-9409a5f705d3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "already available data", "label": "VAGUE_DATA", "score": 0.7487351298332214, "start": 1655, "end": 1677, "probe_score": 0.8822, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " participating on<br>each cultural<br>production work<br>|Project Management<br>Team/UN-Habitat<br>|\n|Of which, are female|Number of females<br>including cultural<br>practitioners, individuals in<br>cultural entities and<br>additional workers involved<br>in the implementation of<br>the cultural productions.|Quarterly<br>|Progress,<br>Monitoring<br>and<br>Evaluation<br>Reports. Esti<br>mates by<br>Project<br>Management<br>Team.<br>|Number of women will<br>be determined by<br>disaggregating the<br>beneficiary data of the<br>progress reports<br> <br>|Project Management<br>Team/UN-Habitat<br>|\n\n\nPage 35 of 66", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["beneficiary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000034", "page": 40, "chunk": 1, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents1.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "beneficiary data", "label": "VAGUE_DATA", "score": 0.713057279586792, "start": 501, "end": 517, "probe_score": 0.0507, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "SNSOP<br>Management<br>Information<br>System (MIS)<br> <br>|Data on participation in<br>Component 2 will be<br>collected at registration<br>where based on the<br>targeting and<br>registration process<br>outlined in the Project<br>Operations Manual,<br>eligible beneficiaries<br>will be allocated to<br>Component 2. Data on<br>payment of the<br>livelihood grant will be<br>collected through the<br>SNSOP MIS that will be<br>linked with SNSOP<br>payment data<br>|The Implementing<br>Partner responsible for<br>Component 2 will be<br>responsible for data<br>collection<br>|\n|Eligible beneficiary households with<br>functional income-generating investments|<br>The total number of<br>households with functional|This indicator<br>will be|SNSOP<br>Management|Data will be collected<br>through routine M&E|Implementing Partner<br>|\n\n\nPage 53 of 74", "output": {"entities": {"named_data": ["SNSOP MIS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 57, "chunk": 1, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SNSOP MIS", "label": "NAMED_DATA", "score": 0.7557827234268188, "start": 397, "end": 406, "probe_score": 0.0361, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad COVID-19 Strategic Preparedness and Response Project (P173894)\n\n\n\n\n\n|Monitoring & Evaluation Plan: Intermediate Results Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **|**Definition/Description **<br>|**Frequency **|**Datasource **<br>|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|1.1. Update of National COVID-19<br>Response Action Plan|Updating of national action<br>plan to respond to COVID-<br>19 <br>|once<br>|COVID-19<br>report<br>|<br>routine data<br>|<br>MOPH<br>|\n|1.2 Percentage of healthcare workers<br>trained in surveillance and investigation <br>|<br>Number of trained<br>healthcare workers as a<br>percentage of all the health<br>care workers that could be<br>trained|<br>weekly<br>|<br>COVID-19<br>report<br> <br>|routine data<br>|MOPH<br>|\n|1.2 Number of health workers trained on<br>case definition, management, infection<br>prevention and control for COVID-19|<br>Number of trained<br>healthcare workers <br>|weekly<br>|COVID-19<br>report<br>|routine data<br>|MO", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["routine data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000124", "page": 37, "chunk": 0, "title": "Chad - COVID-19 Response Project", "pdf_url": "http://documents1.worldbank.org/curated/en/717781588366403375/pdf/Chad-COVID-19-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "routine data", "label": "VAGUE_DATA", "score": 0.5242028832435608, "start": 549, "end": 561, "probe_score": 0.6146, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "’s\nRegulated Professions Database. This can\nbe a problem, as occupational licensing is\ncited in the literature among the reasons\nfor occupational downgrading of migrants.\nCassidy and Dacass (2021) found that in the\nUnited States, immigrants were significantly\nless likely to have a license than similar\n\n\n\n**Chart 21. Share of regulated professions by citizenship and legal status, Q2 2024**\n\n\n\n**The educational premium seems**\n**to be lower for Ukrainian refugees**\n**compared to the general workforce**\n**in Poland.** According to the SEIS survey,\nUkrainian refugees with master’s and\nPhD degrees earn a 22% higher median\nnet wage than those with only secondary\neducation. This appears to be a small\ngain, even accounting for the fact that,\ngenerally, the differences between median\nwages are less pronounced than between\naverage wages (which are pulled higher\nby top incomes) and that our method of\nwage estimation based on SEIS household\nincomes <sup>26</sup> [^26: As described in chapter 2, SEIS measures incomes on the household level. Using it to estimate individual wages likely underrepresents lowest and highest incomes.\nDetails are available in the Online Technical Appendix.] flattens the distribution.\nAccording to the most recent estimate in\nOctober 2022, in the economy as a whole,\nthe average gross wage of master’s and\nPhD degree holders was 84% higher than\nthose with only secondary education. <sup>27</sup> [^27: Note that the GUS (2024) data for the host population is not exactly comparable, as it does not include microenterprises, it covers an earlier period and focuses on\ngross and average wages.]\n\n\n\n**Most Ukrainian refugees work in**\n**a different sector than previously**\n**in Ukraine, which also points to**\n**occupational downgrading.** The SEIS\nsurvey indicates that 34% of Ukrainian\nrefugees currently employed in Poland\nwork in the same sector", "output": {"entities": {"named_data": ["SEIS survey", "SEIS household\nincomes"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 14, "chunk": 2, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS survey", "label": "NAMED_DATA", "score": 0.8044195175170898, "start": 538, "end": 549, "probe_score": 0.9814, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "SEIS household\nincomes", "label": "NAMED_DATA", "score": 0.7057094573974609, "start": 928, "end": 950, "probe_score": 0.8237, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the longer-term recovery. Local and community-led approaches can ensure that\nactions respond to the priority needs of affected people. **Women’s networks need capacity-building to monitor and**\n**report protection violations in evacuation centres.**\n\n\n**•** **Monitor, collect and share gender information related to programming**\n\nClusters and agencies implementing humanitarian response activities should **include the different needs and**\n**priorities for women, men, boys and girls in their regular assessments, monitoring and data collection.** They should\nshare this information with other agencies to ensure a cohesive working approach.\n\n\n**EMERGENCY PREPAREDNESS MEASURES**\n\n\n**•** **Capacity-building to support gender-sensitive disaster response mechanisms and for the**\n**implementation of referral pathways**\n\nFor gender sensitivity to be systemic across disaster responses from the immediate onset of a disaster,\n**humanitarian staff need capacity-building on gender in emergencies in a regular and embedded manner**, rather\nthan as ad-hoc trainings, and gender sensitivity must be integrated into **anticipatory action framework processes** .\nTraining and support on the **implementation of referral pathways** must be provided. Measures and awareness for\nthe prevention of sexual exploitation and abuse need to be strengthened and inclusion measures, **in particular for**\n**people with disabilities**, need to be integrated across disaster preparedness measures.\n\n\n**•** **Rapid gender analysis and use of sex and age disaggregated data**\n\nRather than waiting until after months of the disaster/emergency response have passed, a **comprehensive joint**\n**rapid gender analysis** should be conducted as part of the needs assessment at the immediate onset of a disaster\nto inform emergency programming. It is important to collect sex and age disaggregated data throughout all\nphases of programming, but data collection must", "output": {"entities": {"named_data": [], "descriptive_data": ["sex and age disaggregated data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000705", "page": 4, "chunk": 1, "title": "Gender Alert: Philippines Super Typhoon Rai Response (May 2022)", "pdf_url": "https://reliefweb.int/attachments/66ec32b7-3dd8-3109-8f95-9eee0e27c3e5/GenderAlert-Philippines%20Typhoon%20Final%20version%2028April2022.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "sex and age disaggregated data", "label": "DESCRIPTIVE_DATA", "score": 0.5956521034240723, "start": 1524, "end": 1554, "probe_score": 0.8784, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " casualties were recorded in Sa’ada.\n\n\n###### **Countrywide Civilian Impact Snapshot** **(August - October 2018)**\n\n\n\nCivilian impact\nincidents\n\nTotal civilian\ncasualties\n\nFatalities\n\nChildren /\nWomen\n\nInjured\n\nChildren /\nWomen\n\n\n###### **670**\n\n\n###### **1,478**\n\n\n###### **622**\n\n\n###### **144/73**\n\n\n\n**Psychosocial trauma**\n**incidents**\n\n**Incidents with**\n**vulnerability**\n\n**Children & Women**\n\n**Children/Women/**\n**IDPs/Refugees**\n\n\n###### **43/14/** **13/2**\n\n\n###### **568** **472** **400**\n\n\n###### **856**\n\n\n###### **215/53**\n\n\n\nThe casualty totals were driven by two factors: the intensity of fighting and mass casualty incidents (incidents with more than 10\ncivilian casualties). The casualty totals peaked in early-August and early-September due to increased fighting in Al-Hudaydah, and in\nthe second week of August when airstrikes hit a bus carrying schoolchildren in Sa’ada, causing 130 civilian casualties, including 96\nchildren. This incident had the highest number of child casualties since CIMP began monitoring. But, there were another 263 children\nkilled or injured in the quarter, 24% of all civilian casualties. 400 incidents were recorded impacting women and children, with another\n43 impacting only children and 14 impacting women alone. In addition, 13 incidents impacted on existing IDPs, including women and\nchildren, and 2 on refugees. In total, 70% of the recorded incidents impacted on vulnerable", "output": {"entities": {"named_data": ["Countrywide Civilian Impact Snapshot"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000783", "page": 6, "chunk": 1, "title": "Civilian Impact Monitoring Report - August - October 2018", "pdf_url": "https://reliefweb.int/attachments/73509408-77aa-3e8c-85b4-eca825ef0a18/civilian_impact_monitoring_report_august_-_october_2018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Countrywide Civilian Impact Snapshot", "label": "NAMED_DATA", "score": 0.845470666885376, "start": 48, "end": 84, "probe_score": 0.8366, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " for the country and the climate, and how best to deal\nwith the operations and maintenance issues for school upkeep.\n\n\nThe list of sites for the Phase I schools follows. Note that the first year sites are fixed while there\nmay be some adjustments on the second year sites.", "output": {"entities": {"named_data": [], "descriptive_data": ["list of sites for the Phase I schools"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017628", "page": 32, "chunk": 2, "title": "Kenya - South Nyanza Sugar Project", "pdf_url": "https://documents.worldbank.org/curated/en/749631468915090487/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "list of sites for the Phase I schools", "label": "DESCRIPTIVE_DATA", "score": 0.5663033723831177, "start": 123, "end": 160, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Disbursement forecast\n\n\n\nContract number\n*Contract subject\nAwardee\n*Launching date\n-Expected delivery date\n-Non objection date\n*Expected date of final delivery\n*Bidder nationality\n*Contract allocation (general account, budget, loan\ncategory, geographic area)\n*List of contracts\nManagement of financial -Standard financial statements (balance sheet;\naccounts statement of sources and uses of funds/income\nstatement, ...)\n*LACI reports for the project duration\nFixed Assets management -Inventory of Fixed Assets (type, quantity, valuation,\ndate of service, etc.)\n\n\n\nSupplier\nAccounting category ; budgetary and accounting\nallocation of fixed assets\n\n\n\nLocation\nDepreciation\n-Disposal of Fixed assets\n\n\n\n**Module** Functions\nSorting parameters Project ID and currency used\n\n                  - Fiscal years\nCurrency\nDecentralized data entry locations\n\n\n\nChart of accounts, managerial reports, geographic\nareas of intervention, etc.\n\n\n\n\n                - Books of accounts\nDonors\n\n                 - Contracts\nCategories of disbursement\nUser Management Data storage ; restitution ; correction; cleaning; etc.\n\n                - Import/export of data to other Tempro modules\n\n\n\nIt is expected that the application would be modified to differentiate the operations from the\nprojects, as well as funding sources to allow for reporting in financial and accounting terms of the\nproject objectives and activities. The concept should allow for proper monitoring of the project\nduring the life of the credit, namely: (i) chart of accounts; (ii) by category, component, and subcomponent; (iii) by geography (type of establishment, site and district); (iv) by category of\nexpenses; and (v) in local and foreign currency. Reporting of multi-level data is planned, which\n**wiU** bring about a more dynamic approach to the management of the project, and which should", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["multi-level data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018211", "page": 51, "chunk": 0, "title": "Kenya - Olkaria Geothermal Power Project", "pdf_url": "https://documents.worldbank.org/curated/en/789321468089667053/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "multi-level data", "label": "VAGUE_DATA", "score": 0.6651609539985657, "start": 1720, "end": 1736, "probe_score": 0.4661, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda Skills Development in Refugee and Host Communities (P176263)\n\n\nimprove quality of TVET, promote sustainable TVET financing, and ensure effectiveness of TVET management and organization. The\nBTVET Strategic Plan (2011) also provides a shift in the approach to employment-led skills development by providing labour marketrelevant skills and competencies. The core tenets are to increase internal efficiency and resource available to TVET, as well as to\nprovide more equitable access to skills development which is in line with this project’s PDO.\n14 See Table 16 (page 48) of the Education Response Plan for Refugees and Host Communities in Uganda (2018) presents data from\nRMIS and multiple sources in September 2017.\n15 Only 8 percent of refugees have received some form of formal training. See\nhttp://documents.worldbank.org/curated/en/571081569598919068/Informing-the-Refugee-Policy-Response-in-Uganda-Resultsfrom-the-Uganda-Refugee-and-Host-Communities-2018-Household-Survey\n16 In 2016, over 50% of GDP and 80% of the labor force can be attributed to the informal sector in Uganda (UBOS, 2014). While there\nare no official statistics on informal labor market in Uganda’s RHC, the UNHCR reports the economy in RHC as a predominantly informal\nsector.\n17 Violence against children in schools is widespread and has negative lasting impacts on physical and mental health, leading to risk of\nlow levels of educational attainment. A Raising Voices (2017) study identified that 93% of boys and 94% of girls aged 11-14 have\nexperienced physical violence from teachers in school. Sexual violence is likely to be underreported due to associated stigma.\n[18 For more details on Prospects, see the Vision Note (https://www.ilo", "output": {"entities": {"named_data": ["RMIS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000016", "page": 13, "chunk": 0, "title": "Concept Project Information Document (PID) - Uganda Skills Development in Refugee and Host Communities - P176263", "pdf_url": "http://documents.worldbank.org/curated/en/336661632309532618/pdf/Concept-Project-Information-Document-PID-Uganda-Skills-Development-in-Refugee-and-Host-Communities-P176263.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "RMIS", "label": "NAMED_DATA", "score": 0.5782008767127991, "start": 698, "end": 702, "probe_score": 0.9689, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### 1.8 11\n\n\n\nCurrent account balance . **.2**\n\n\n\nFinancing items (net)\nChanges in net reserves .. .\n_Memo:_\nReserves including gold _(US$ millions)_\nConversion rate _(DEC, locaW/US$)_ 177.7 177.7 177.7\n\n\n**EXTERNAL DEBT and RESOURCE FLOWS**\n\n**1979** **1989** **1998** **1999**\n_(US$ millions)_ **Compositlon of total debt, 1998 (USS milIlona)**\nTotal debt outstanding and disbursed 26 **179** 288\nIBRD 0 0 0\nIDA 0 26 50 49 G 15 B\n\nTotal debt service 2 15 6\nIBRD 0 0 0 C: 9\nIDA 0 0 1 1\n\nComposition of net resource flows E: 119\nOfficial grants 5 32 48\nOfficial creditors -1 3 2\nPrivate creditors 0 -1 0\nForeign direct investment 0 0 6 D: **95**\nPortfolio equity 0 0 0\n\nWorld Bank program\n\nCommitments 0 9 3 A  - IBRD E - Bilateral\nDisbursements 0 2 2 1 B - IDA D - Other rrultilateral F **-** Private\nPrincipal repayments 0 0 0 0 C- IMF G - Short-term\nNet flows 0 2 2 1\nInterest payments 0 0 0 0\nNet transfers 0 2 1 1\n\n\nNote: This table was produced from the Development Economics central database. 9/13/00", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015703", "page": 63, "chunk": 1, "title": "Ethiopia - Seventh Education Project", "pdf_url": "https://documents.worldbank.org/curated/en/620811468036355245/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9087857007980347, "start": 960, "end": 998, "probe_score": 0.6996, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Disbursement forecast\n\n\n\nContract number\n*Contract subject\nAwardee\n*Launching date\n-Expected delivery date\n-Non objection date\n*Expected date of final delivery\n*Bidder nationality\n*Contract allocation (general account, budget, loan\ncategory, geographic area)\n*List of contracts\nManagement of financial -Standard financial statements (balance sheet;\naccounts statement of sources and uses of funds/income\nstatement, ...)\n*LACI reports for the project duration\nFixed Assets management -Inventory of Fixed Assets (type, quantity, valuation,\ndate of service, etc.)\n\n\n\nSupplier\nAccounting category ; budgetary and accounting\nallocation of fixed assets\n\n\n\nLocation\nDepreciation\n-Disposal of Fixed assets\n\n\n\n**Module** Functions\nSorting parameters Project ID and currency used\n\n                  - Fiscal years\nCurrency\nDecentralized data entry locations\n\n\n\nChart of accounts, managerial reports, geographic\nareas of intervention, etc.\n\n\n\n\n                - Books of accounts\nDonors\n\n                 - Contracts\nCategories of disbursement\nUser Management Data storage ; restitution ; correction; cleaning; etc.\n\n                - Import/export of data to other Tempro modules\n\n\n\nIt is expected that the application would be modified to differentiate the operations from the\nprojects, as well as funding sources to allow for reporting in financial and accounting terms of the\nproject objectives and activities. The concept should allow for proper monitoring of the project\nduring the life of the credit, namely: (i) chart of accounts; (ii) by category, component, and subcomponent; (iii) by geography (type of establishment, site and district); (iv) by category of\nexpenses; and (v) in local and foreign currency. Reporting of multi-level data is planned, which\n**wiU** bring about a more dynamic approach to the management of the project, and which should", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["multi-level data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007986", "page": 51, "chunk": 0, "title": "Kenya - National Extension Project", "pdf_url": "https://documents.worldbank.org/curated/en/105851468272402607/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "multi-level data", "label": "VAGUE_DATA", "score": 0.6651609539985657, "start": 1720, "end": 1736, "probe_score": 0.4661, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nLebanon Health Resilience Project (P163476)\n\n\nii. For the purposes of this Loan, the said Additional Budget Lines could be opened in the budget of\na specific year up until 31 January of the following year and those contracted or not contracted\nare carried forward per the request of the MoPH.\n\n69. **Accounting system and financial reporting.** The MoPH does not have an accounting information\nsystem to process accounting transactions. However, it has an information system for public health that\nconnects to the PHCCs. In the EPHRP, each health center has been using the financial module of the HIS\nto record daily transactions and submit requests for payments. The connection has been installed in all\ncenters, and training and follow-up are conducted by the PMU. For Component 1, which scales up\nactivities under the existing emergency project, the same financial module will be used by the expanded\nnumber of PHCCs to record daily transactions and account for the data on treated patients.\n\n70. **The system allows the MoPH to monitor and control expenditures made by the PHCCs in the**\n**context of the project.** The flow of activity and expenditure cycle is as follows:\n\n     - Any contract to be signed by the PHCCs with a third party is submitted in the system to the\nMoPH for clearance.\n\n     - Once the contract is cleared by the MoPH and then signed, any subsequent payment on this\ncontract will be through a “payment request” submitted by the PHCC in the system to the\nMoPH for review and clearance.\n\n     - Once the payment request is cleared by MoPH, the FO prepares the payment (check or bank\ntransfer) to be signed by the project coordinator and the Director General.\n\n     - The funds are then transferred from the Designated Account to the PHCC’s bank account\n(which is a segregated bank account opened exclusively for the project)", "output": {"entities": {"named_data": [], "descriptive_data": ["data on treated patients"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000032", "page": 35, "chunk": 0, "title": "Lebanon - Health Resilience Project", "pdf_url": "http://documents.worldbank.org/curated/en/616901498701694043/pdf/Lebanon-Health-PAD-PAD2358-06152017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on treated patients", "label": "DESCRIPTIVE_DATA", "score": 0.7688190340995789, "start": 988, "end": 1012, "probe_score": 0.072, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " incentivize technology adoption and crossover into higher value-added activities.** The\nsubcomponent will finance (i) technical assistance and (ii) competitive grants (technology kits and operational costs) of\neligible formal or informal MSMEs selected based on a transparent, merit-based competition that will consist of:\n\n(a) Gender-friendly campaigns to surface climate-change solutions in the targeted value chains.\n(b) Training and coaching on business plan development for up to 1,200 beneficiaries to create a strong pipeline\nof proposals that include climate change mitigation and adaptation measures.\n(c) Evaluation of business plans by an independent panel of experts based on: (i) potential for diversification,\nvalue added, and jobs creation; (ii) technology; (iii) adoption and use of climate-resilient technologies and/or\nimplementation of climate-friendly solutions; and (iv) social benefits, including for women and refugees.\n(d) Grants of US$10,000–US$20,000 (US$9 million total grant portfolio with an average of US$15,000 per\nbeneficiary MSME) for up to 600 MSMEs with at least 50 percent of funding allocated to climate adaptation.\n\n\n33 As part of this activity, the project will support providers of improved logistics services for market access in Great Lakes border regions in\n<u>conjunction with the Great Lakes Trade Facilitation and Integration Project (P174814).</u>\n\nPage 18 of 55", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000004", "page": 21, "chunk": 2, "title": "Burundi - Jobs and Economic Transformation Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099111023141528640/pdf/BOSIB1dda1d49e0221807413cf06ea9ae3f.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\n\n\n\n\n\n\nmuch of the heterogeneity inside of these\ngroups. Every two years, GUS publishes\ninformation about the average wages in\n128 occupational groups, with the latest\ndata for October 2022 (GUS, 2024a).\nWhen ZUS data is aggregated into these\noccupational groups with the assumption\nthat wage structure remains the same as in\nOctober 2022, the rate at which Ukrainian\n\n\n\n\n\n\n\n**The occupational progress of**\n**Ukrainian refugees as compared to the**\n**host population may be faster than**\n**the nine main occupational groups**\n**above suggest.** What is particularly\nstriking is the similar pace of progress of\nUkrainian refugees and pre-war Ukrainians\nin the nine main occupational groups\npresented above. However, it conceals\n\n\n\n**Chart 12. Ukrainian refugee wages relative to Polish citizens in the same employee-cells**\nEmployee cells are divided by poviat, sex, age group, and main occupational group\n\n\n20\n\n\n2022 Q2 2024 Q2\n\n\nNote: Data are based on average social security contributions bases in employee-cells, each cell for a specific poviat, sex, age group, and main\noccupational group. All data are for the 01XX ZUS insurance code (employees). Data for Q2 2022 encompass 6945 employee-cells of Ukrainian\nrefugees joined with likewise cells for Polish citizens, while for Q2 2024 13477 such cells. Ukrainian refugees have been identified by PESEL UKR and\nUkrainian citizenship, Poles by Polish citizenship.\n\nSource: Deloitte own elaboration based on ZUS data.\n\n\n\nrefugees move to better-paid occupations\nbecomes clearer. Between June 30, 2022,\nand June 30, 2024, Ukrainian refugees\ngained an estimated 7% in earnings having\nshifted towards better paid occupations,\npre-war Ukrainians 5%, non-Ukrainian\nforeigners 4%, and Polish citizens 1%.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n**Ukrainian refugees have been slowly**\n**", "output": {"entities": {"named_data": ["ZUS data", "ZUS data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 8, "chunk": 0, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "ZUS data", "label": "NAMED_DATA", "score": 0.7097043991088867, "start": 284, "end": 292, "probe_score": 0.9435, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "ZUS data", "label": "NAMED_DATA", "score": 0.5020396709442139, "start": 1534, "end": 1542, "probe_score": 0.9933, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "required for local government involvement, and arrangements for maintenance, monitoring and\nevaluation (M&E). Social capital enhancing activities would be a mandatory part of all sub-projects, and\nwould be tailored to support activities chosen by the communities.\n\nSupport to Decentralized Government Structures. Most local administrations are beginning\nto operate again with a limited number of staff and other inputs. District and chiefdom authorities are\nvery weak, however, and lack the financial and human resources needed to address their concerns and\npnorities effectively. NGOs have demonstrated their ability to implement successful community-based\nsocial and economic projects and have played a key role in shelter reconstruction activities. With the\ngradual strengthening of local government capacity, partnerships between community groups and local\nauthorities are expected to increase. Upon completion of initial training, district and chiefdom authorities\nwould be required to demonstrate that they have used the training by showing that there have been some\nimprovements in their community. For instance, at the end of each training session, district authorities\nwould be required to develop a simple action plan that specifies some activities that NSAP or other\npartners could support. District and chiefdom authorities would also gain experience in implementing,\nsupporting or overseeing community development activities.\n\nHealth. The unfavorable health indicators in Sierra Leone can be attributed to several factors.\nHigh fertility, female genital mutilation and the presence of HIV/AIDS increase morbidity and mortality\nrisks for women and children. Many risk factors that have contributed to HIV/AIDS epidemics in other\nAfrican countries have long been present in Sierra Leone, and the protracted conflict has created the\nconditions for explosive growth in HIV/AIDS infection rates. The Centers for Disease Control carried\nout a survey in 2002 which found the HIV prevalence among adults (aged 1549) to be 6.1 %; in\nFreetown, 4% in rural areas and 4.9% nationwide. In response to the crisis, Government has developed\na multi-sector HIV/AIDS Program, which is being supported by various", "output": {"entities": {"named_data": [], "descriptive_data": ["survey in 2002"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000017", "page": 10, "chunk": 0, "title": "West Bank and Gaza - Integrated Community Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/158081468762622780/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey in 2002", "label": "DESCRIPTIVE_DATA", "score": 0.6400850415229797, "start": 1950, "end": 1964, "probe_score": 0.9708, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Figure 9 GDP in Selected Regions, 1980–2010|Col2|Col3|\n|---|---|---|\n|<br>**a. Sub-Saharan Africa**|<br>**b. Asia**|<br> <br> <br> <br> <br> <br> <br> <br> <br> <br> <br>**____**|\n|<br>|||\n|**c. Latin America and the Caribbean**|**d. Europe and the Middle East and North**<br>**Africa**|**d. Europe and the Middle East and North**<br>**Africa**|\n|<br>|<br>|<br>|\n|_Source_: Fardoust and Dhareshwar 1990, World Development Indicators, and authors’ computations.|_Source_: Fardoust and Dhareshwar 1990, World Development Indicators, and authors’ computations.|_Source_: Fardoust and Dhareshwar 1990, World Development Indicators, and authors’ computations.|\n\n\n**5 Going Forward: By Way of a Conclusion**\n\n\n\n\n\nThis section presents a brief forecasters’ view of the key trends at work in the world economy\n\ntoday. It draws some lessons about how best to deploy scarce organizational resources to\n\nposition and use a forecasting team that works closely with a team of experts in research centers\n\naround the world.\n\n\nIn recent years, researchers and international organizations have built a number of long-term\n\nforecasting models that focus on productivity, convergence, technological progress and catch-up,\n\nand economic growth (see, for example, Bergheim 2008; Dadush and Shaw 2011; Hughs and\n\n\n56", "output": {"entities": {"named_data": ["World Development Indicators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005831", "page": 57, "chunk": 0, "title": "wps6705", "pdf_url": "https://local/prwp/wps6705.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Development Indicators", "label": "NAMED_DATA", "score": 0.6681943535804749, "start": 405, "end": 433, "probe_score": 0.9586, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "variable listed in column 1 (the 𝑍� of Section III) has no explanatory power for the estimated\nposterior class-membership probabilities, 𝜋���, 𝑐�1, . . .4.\n\n\nInterpreting these statistics involves a multiple comparisons problem: which criteria to apply\nwhen judging statistical significance? This depends upon the insights that the reader hopes to\ndraw—the hypothesis being tested. One natural null hypothesis is that our estimated class\nprobabilities are no better than random in terms of their relationship with the whole set of\nvariables listed in Table D.1. Then, the appropriate approach is to apply a family-wise error rate\n(FWER) method. We use the Holm-Bonferroni method (Holm 1979), reporting criteria for\nstatistical significance in the rightmost three columns of Tables 4a and 4b. A significant value\nfor even one _p_ -statistic in these columns is evidence of better-than-random for the LCA\nprocedure.\n\n\nThe null hypothesis that our estimated class probabilities are no better than random is\nrejected decisively. This is the case for both relations with suppliers and with customers. This\nrejection of the null hypothesis provides overall support for the validity of the method developed\nin this paper, including the formulation of the survey questions and LCA's interpretation of the\ndata.\n\n\nGiven the confidence that we have that our posterior-probability data are better-thanrandom, we can proceed to examine hypotheses on individual variables using a criterion that has\nmore power than the FWER. An alternative agenda examines hypotheses on individual\nvariables. However, using standard criteria applied to the highest values of a set of 𝑝-statistics\nviolates the conditionality assumptions of standard tests. Therefore, we use the false discovery\nrate (FDR). If the FDR is set at 5%, for example, significance levels are set so that 95% of the\nindividual-variable effects labeled as significant are inconsistent with the null hypothesis of no\neffect. We use the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["posterior-probability data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001841", "page": 20, "chunk": 0, "title": "mapping the landscape of transactions the governance of business relations in latin america", "pdf_url": "https://local/prwp/mapping-the-landscape-of-transactions-the-governance-of-business-relations-in-latin-america.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "posterior-probability data", "label": "VAGUE_DATA", "score": 0.6383354663848877, "start": 1348, "end": 1374, "probe_score": 0.9048, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " participating on<br>each cultural<br>production work<br>|Project Management<br>Team/UN-Habitat<br>|\n|Of which, are female|Number of females<br>including cultural<br>practitioners, individuals in<br>cultural entities and<br>additional workers involved<br>in the implementation of<br>the cultural productions.|Quarterly<br>|Progress,<br>Monitoring<br>and<br>Evaluation<br>Reports. Esti<br>mates by<br>Project<br>Management<br>Team.<br>|Number of women will<br>be determined by<br>disaggregating the<br>beneficiary data of the<br>progress reports<br> <br>|Project Management<br>Team/UN-Habitat<br>|\n\n\nPage 35 of 66", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["beneficiary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 40, "chunk": 1, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "beneficiary data", "label": "VAGUE_DATA", "score": 0.713057279586792, "start": 501, "end": 517, "probe_score": 0.0507, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nGreater Colombo areas are increasingly used for residency by people work within Colombo. Puttalam i s about 3\nhours drive from Colombo; therefore, with increased economic activities and i t s relative closeness to Colombo, the\naverage real estate price i s likely to increase by around 12-15 percent in the coming years. The Puttalam has\nalready witnessed recent increase in land transactions as a result o f this housing project.\n\n\n\n**35**\n\n\n\nExcluding value o f their land.\n\n\n\n36 Rs.250,000 for temporary houses (5,653) and Rs. 100,000 for partly completed houses (2,232).\n\n3 1 Based o n the NEHRP experience, the cost o f skilled labor i s close to Rs. 1,200 per day and that for unskilled i s\n\nabout Rs. 800. For this exercise, it i s assumed that beneficiaries use a combination o f skilled and unskilled labors o n\n50:50 bases which cost them Rs. 1,000 per day o n average.\n\n\n\n3 1\n\n\n\n56", "output": {"entities": {"named_data": ["NEHRP experience"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000023", "page": 61, "chunk": 2, "title": "Sri Lanka - Puttalam Housing Project", "pdf_url": "http://documents1.worldbank.org/curated/en/194731468104646411/pdf/38147core.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NEHRP experience", "label": "NAMED_DATA", "score": 0.6201304793357849, "start": 595, "end": 611, "probe_score": 0.9464, "gold": "DATA_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "is concerned that the continuation of the assistance would\nprovide a reason for people to remain and potentially put them\nat greater risk than if they moved to areas identified as safer\nsuch as the Bentiu POC or villages where ICRC and MSF is\naccessing. Vulnerable IDPs should be provided alternative\nlocations to move to where they can access assistance\nsupported by humanitarians in locations that can also provide\ncommunity support. <sup>21</sup>\n\n\nThe newly formed IO 2 moved to the north causing fear and\nsome displacement in Guit County. Many civilians (11,000\napprox) opted to settle around Nimni and Cadet reportedly\nbecause of access to food distributions by WFP. Tensions in\nMayom related to the splitting of the county triggered unrest\nalso leading to displacement of approximately 200 civilians.\n\n\nThe creation of new States in the Lakes region along the\nsouthern border with Unity resulted in conflict between three\ncommunities’ of Dinka, Beli and Bongo. Immediately after the\ndecree of a new state was made public, the conflict of Bhargel\nbetween Gok and Beli communities started. In August 2016\nfighting erupted and continues which led to displacement of\n1865 residents of Bhargel.\n\n\nDisplacement Trends Mar2014 - Dec2016 (in million)\n\n\n1.7m 1.5m\n\n\n\n1.85m\n\n\n\n\n\n\n\n\n|0.8m<br>0.4m 0.6m|0.77m|1.29m<br>0.85m|\n|---|---|---|\n|<br>Dec<br>Dec<br>Mar|<br>Dec<br>Dec<br>Mar|Dec<br>|\n\n\n\n\n\nFighting in Juba\nforced thousands\nto flee their homes", "output": {"entities": {"named_data": ["Displacement Trends"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001625", "page": 7, "chunk": 0, "title": "Protection Trends South Sudan No 9 | October - December 2016 - South Sudan Protection Cluster, February 2017", "pdf_url": "https://reliefweb.int/attachments/fb70ba51-eb89-301d-bf69-a5ed07a4c632/south_sudan_protection_trends_paper_october_-_december_2016_09022017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Displacement Trends", "label": "NAMED_DATA", "score": 0.6166033148765564, "start": 1199, "end": 1218, "probe_score": 0.9029, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "output": {"entities": {"named_data": [], "descriptive_data": ["household expenditure survey data", "data from the Household Survey"], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010771", "page": 38, "chunk": 1, "title": "Kenya - Second Integrated Agricultural Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/288771468046860938/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household expenditure survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8699104189872742, "start": 565, "end": 598, "probe_score": 0.7323, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.5808603167533875, "start": 870, "end": 881, "probe_score": 0.1461, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from the Household Survey", "label": "DESCRIPTIVE_DATA", "score": 0.5346028804779053, "start": 1978, "end": 2008, "probe_score": 0.1121, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nBeirut Housing Rehabilitation and Cultural and Creative Industries Recovery (P176577)\n\n\n\n|Col1|Col2|Col3|Team estimat<br>ions.|Col5|Col6|\n|---|---|---|---|---|---|\n|Of which, are members of female<br>headed households|Number of females who<br>receive technical and<br>financial support through<br>the project in the<br>reconstruction of their<br>residential unit from the<br>PoB explosion.|Annual<br>|Progress<br>Reports, Mon<br>itoring and<br>Evaluation<br>Reports.<br>Third-Party<br>Monitoring<br>Agent report<br>s. Project<br>Management<br>Team<br>estimations.<br>|Number of women will<br>be determined by<br>disaggregating the<br>beneficiary data of the<br>progress reports<br>|Project Management<br>Team/UN-Habitat<br>|\n|Owners benefiting from resilient,<br>rehabilitated residential units|Number of owners who<br>receive technical and<br>financial support through<br>the project in the<br>reconstruction of their<br>residential unit from the<br>PoB explosion.|Annual<br>|Progress<br>Reports, Mon<br>itoring and<br>Evaluation<br>Reports.<br>Third-Party<br>Monitoring<br>Agent<br>reports. Proj<br>ect<br>Management<br>Team<br>estimations.<br>|Number", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["beneficiary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 39, "chunk": 0, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "beneficiary data", "label": "VAGUE_DATA", "score": 0.6391081809997559, "start": 653, "end": 669, "probe_score": 0.2134, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "1. **Project alternatives** **considered** **and reasons for rejection:**\nDesln Alternative 1: Discontinue IDA support for the Emergency Recovery Support Fund\n(ERSF) and its successor, the National Social Action Project (NSAP). This option was rejected because\navailable evidence suggests that the on-going Community Reintegration and Rehabilitation Project\n(CRRP Cr. 3312-SL) has been successful. Although definitive audit and evaluation data are not yet\navailable, CRRP financed over 250 sub-projects that benefited extremely poor and devastated\ncommunities, including some areas of the country where security was marginal at best. NaCSA has been\nthe Government entity that has delivered much needed support to the population\n\n\nDesign Alternative 2: Withhold IDA support for NaCSA's newly-instituted Public Works\nProgram. This option was rejected for three reasons. First, the need to restore infrastructure beyond the\ncommunity sub-projects is urgent, especially in the newly accessible areas. Proposed works (e.g.\nrehabilitation of feeder roads and drainage systems) would complement other projects currently being\nimplemented by NaCSA. Second, IDA support for this program would provide an opportunity for\nNaCSA to develop a capacity building program for local administrators. This initiative, in the context of\nthe Public Works Program, would support the Government's decentralization policy and introduce a\nresults-based model of governance at the local level that would facilitate the gradual delegation of\nadditional implementation responsibilities to local authorities. Finally, labor intensive techniques will be\nused to employ ex-combatants and unemployed youth, to reduce the risk that they would turn to\nnon-legitimate income generating activities if they remain unemployed.\n\n\nDesien Alternative 3: Provide support for NaCSA's micro-credit program. The AfDB will\ncontinue to support micro-finance activities through the Government's Social Action and Poverty\nAlleviation (SAPA) program. A mnicro-finance policy", "output": {"entities": {"named_data": [], "descriptive_data": ["audit and evaluation data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010499", "page": 15, "chunk": 0, "title": "Kenya - Structural Adjustment Credit Project", "pdf_url": "https://documents.worldbank.org/curated/en/270431468285587652/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "audit and evaluation data", "label": "DESCRIPTIVE_DATA", "score": 0.6453143954277039, "start": 418, "end": 443, "probe_score": 0.8111, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_State protection against trafficking_\n\n\nTo examine claims for asylum by those who suffered or fear trafficking, courts often\nused available country reports to assess the availability of state protection against\ntrafficking. In Australia, the courts have consistently denied trafficking-related\nasylum applications from Albania on the basis that state protection is available.\nCanadian courts noted increased efforts to combat trafficking by governments in\nasylum cases of women fearing trafficking from Estonia, Lithuania and Albania and\ndenied asylum to these applicants on the grounds of availability of state protection. <sup>128</sup> [^128: _Naivelt v. Canada (Minister of Citizenship and Immigration)_, 2004 FC 1261.]\nWhat is of a concern is a seeming gap between the reports of mounting efforts by\nstates to tackle trafficking and the actual effectiveness of such efforts.\n\n\nThe U.K. courts have been unpredictable in determining sufficiency of state\nprotection. For one Albanian woman who was abducted by masked men, gang-raped\nand threatened with prostitution, but received no help from the police, the Court of\nAppeals agreed with the Immigration Appeal Tribunal that “[t]he abduction and rape\nwas regarded as criminal conduct against which the Albanian authorities were able\nand willing to provide effective protection,” <sup>129</sup> [^129: _Kacaj v Secretary of State for the Home Department_ [2002] EWCA Civ 314, 14 March 2002.] and commented that “actions are being\ntaken to stem such lawlessness and the police are _undoubtedly_ willing to provide\nprotection”(emphasis added). <sup>130</sup> [^130: Ibid.] However, for another Albanian woman who was\nsold by her family to a criminal thug in a form of a marriage, the Immigration Appeal\nTribunal concluded, more than a year after the above case, that the state protection\nwas insufficient. <sup>131</sup> [^131: SK Albania UKIAT [2003] 00023, 7 Jul 2003.]\n\n\nIn general, the U.K.", "output": {"entities": {"named_data": [], "descriptive_data": ["country reports"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000197", "page": 19, "chunk": 0, "title": "International Protection for Trafficked Persons and Those Who Fear Being Trafficked", "pdf_url": "https://reliefweb.int/attachments/14203aa6-1ec9-34b2-92f3-cdbc4f5d3465/B2DA64611A8A9E02C12573C600476367-unhcr-dec2007.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "country reports", "label": "DESCRIPTIVE_DATA", "score": 0.8096708655357361, "start": 141, "end": 156, "probe_score": 0.8283, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSPF: Improved Livelihoods for Internally Displaced Persons in Azerbaijan (P178125)\n\n\n11. **Findings from the IDP survey reveal limitations in IDP civic engagement and social**\n**cohesion.** There is a very low level of IDP participation in social activities in their communities\nsuch as youth and women’s groups, cultural activities, agricultural or entrepreneurship activities.\nOnly eight percent of respondents participate in such activities. Forty two percent of\nrespondents said that they either do not know where to, or would not want to, lodge a complaint\nor make a request regarding the delivery of services. In terms of social cohesion and community\nintegration, 61 percent of respondents said that they felt well integrated into their village/city\nand only 40 percent felt that if someone in their family was in an emergency, they could count\non support of their community. While the survey did not collect comparative data for non-IDPs,\nthese findings indicate that the unique living conditions of IDPs may limit their participation in\ncommunity-based activities and lead them to feel less well-supported by their communities. This\nmay be a significant challenge for people who are returning to their places of origin as these\nplaces are less likely to have established local governance arrangements. Given that these are\nessentially newly created villages and cities, they will take time to operate effectively, posing\nchallenges for the returnees. In order for these new settlements to succeed, there will need to\nbe active engagement of residents to identify and to help resolve challenges that arise. By\nparticipating in local decision-making processes and social organizations, IDPs can contribute to\nimproving living conditions in their places of origin upon return and facilitating a smoother\ntransition through more actively engaging.\n\n\n**C. Higher Level Objectives to which the Project Contributes**\n\n12. **The proposed project activities will contribute to the World Bank Group’s Azerbaijan**\n**Country Partnership Framework (", "output": {"entities": {"named_data": [], "descriptive_data": ["IDP survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000007", "page": 12, "chunk": 0, "title": "Azerbaijan - State and Peacebuilding Fund (SPF) : Improved Livelihoods for Internally Displaced Persons in Azerbaijan Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099730012222232813/pdf/P1781250bdd2b50b0b9720d5c17632331c.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "IDP survey", "label": "DESCRIPTIVE_DATA", "score": 0.8501316905021667, "start": 128, "end": 138, "probe_score": 0.9816, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "- **_The procurement is open to eligible firms from any country;_**\n\n\n  - **_The request for bids/Proposal documents shall require that_**\n\n\n**_bidders/proposers submitting Bids/Proposal present a signed_**\n\n\n**_acceptance at the time of bidding, to be incorporated in any_**\n\n\n**_resulting contracts, confirming application of and compliance_**\n\n\n**_with the Bank’s Anti-Corruption Guidelines, including without_**\n\n\n**_limitation the bank’s right to sanction and the Bank’s inspection_**\n\n\n**_and audit right;_**\n\n\n  - **_Contracts with an appropriate allocation of responsibilities, risks_**\n\n\n**_and liabilities;_**\n\n\n  - **_Application of Standstill period and Publication of contract award_**\n\n\n**_information;_**\n\n\n  - **_Maintenance of records of the procurement process; and_**\n\n\n  - **_The Bank has the right to review procurement documentation_**\n\n\n**_and activities._**\n\n\nWhen other national procurement arrangements other than national open\ncompetitive procurement arrangements are applied by the Borrower, such\narrangements shall be subject to paragraph 5.5 of the Procurement\nRegulations.\n\n\n**_Leased Assets as specified under paragraph 5.10_** of the Procurement\nRegulations: Leasing may be used for those contracts identified in the\nProcurement Plan tables. **“** **_Not Applicable”_**\n\n\n**_Procurement of Second-Hand Goods_** **_as specified under paragraph_**\n**_5.11_** of the Procurement Regulations – is allowed for those contracts identified\nin the Procurement Plan tables _“_ **_Not Applicable”_**\n\n\n**_Domestic preference as specified under paragraph 5", "output": {"entities": {"named_data": [], "descriptive_data": ["Procurement Plan tables"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002884", "page": 1, "chunk": 0, "title": "Ethiopia - EASTERN AND SOUTHERN AFRICA- P167794- One WASH?Consolidated Water Supply, Sanitation, and Hygiene Account Project (One WASH?CWA) - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099061024044527827/pdf/P16779417716f801d1bac217488428075ec.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Procurement Plan tables", "label": "DESCRIPTIVE_DATA", "score": 0.5457196831703186, "start": 1250, "end": 1273, "probe_score": 0.0003, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " meet the high barriers to entry but are most likely to work\nin these areas are given opportunities by creating pathways and ladders to gain entry and broaden the set of\nrequirements of access by supporting programs that can validate acquired experience or through recognition of\nprior learning programs. While there are really no apparent systemic barriers within the training sector that\nprevents women from participating in technical education and vocational training programs, the number of\nwomen in non-traditional programs and courses continues to be small. The USAID’s Workforce Development\nprogram’s Gender Assessment reveals that a combination of prevalent social norms, parental influence, and poor\ncommunications, impacts decisions by women to participate in these programs. The assessment also highlights\nfinancial barriers for women to access to TVET (to cover the cost of courses including equipment as well as the\ncost of transportation), supply-side barriers (discrimination and harassment during trainings, few female trainers\nplaying as role models, lack of targeted trainings to female needs/interests due to their limited participation in\ndecision-making, etc.). These issues will need to be addressed to help improve system equity in terms of gender.\nNotwithstanding these concerns, it does need to be acknowledged that the official statistics suggest that nearly\n41 percent of students in the TVET sector are women, suggesting that the sheer lack of opportunities and access\nin other programs (such as, higher education) does result in a significant number of women accessing these\nprograms. Nevertheless, it is important and critical to support not only the expansion of opportunities for more\nwomen, but also to increase the range of opportunities thereby incentivizing women and young girls to access\ntraining in non-traditional programs.\n\n32. **The government is committed to ensuring access to quality education for all students considered as**\n**vulnerable, which include girls from host communities, refugees, and children with special needs.** Girls’\nenrollment is lower at all education levels and makes up 49 percent of preschool, 46 percent", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["official statistics"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000195", "page": 23, "chunk": 1, "title": "Djibouti - Skills Development for Employment Project", "pdf_url": "https://documents1.worldbank.org/curated/en/927731664308482374/pdf/IBArchive-38b35d89-2c5c-4636-ab7e-0ba662b95a5f.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "official statistics", "label": "VAGUE_DATA", "score": 0.7136119604110718, "start": 1345, "end": 1364, "probe_score": 0.1952, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the\n\nlifecycle stage of energy efficiency projects. However, unlike Joskow and Marrow, net financial benefits for\n\nend-users were estimated using actual residential energy prices (electricity and natural gas) as benchmarks.\n\nTo populate these models, information and parameters come, for example, from statistical data, surveys,\n\ninterviews and secondary data. In the case of the Kyoto Protocol mechanisms, studies source figures\n\n\n                                         - 29", "output": {"entities": {"named_data": [], "descriptive_data": ["statistical data"], "vague_data": ["secondary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005703", "page": 30, "chunk": 2, "title": "wps6565", "pdf_url": "https://local/prwp/wps6565.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistical data", "label": "DESCRIPTIVE_DATA", "score": 0.6897892355918884, "start": 303, "end": 319, "probe_score": 0.8465, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "secondary data", "label": "VAGUE_DATA", "score": 0.6636874079704285, "start": 346, "end": 360, "probe_score": 0.9281, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " urban areas in 2013). <sup>6</sup> [^6: World Bank World Development Indicators (2013).]\n\n2. **Uganda faces several challenges including a recent economic slowdown** <sup>**7**</sup> [^7: Uganda’s economy slowed from an average of 7% annual GDP growth in the early 2000s to 4.5% in the 5 years leading up to 2017.] **, which could impede the country’s**\n**progress toward middle-income status by 2020 – a goal outlined in its second National Development Plan (NDPII)** .\nThis slowdown is attributed to various factors including adverse weather conditions and meagre harvests, private\nsector credit constraints, conflict and unrest in neighboring countries, and underperformance in public sector project\nimplementation. <sup>8</sup> [^8: Uganda: Driving inclusive socio-economic progress through mobile-enabled digital transformation, GSMA, 2019.] Uganda’s relatively low productivity in the agricultural sector, which employs the bulk of its\nworkforce, and in the private sector further impedes its growth potential: in the past years, growth in agricultural\nincomes has been largely driven by expanding cultivation areas and exogenous variables such as good weather and\nhigh commodity prices rather than a significant increase in the use of modern production technologies and other\nproductivity-enhancing factors. In addition to agriculture, the manufacturing sector led by micro, small and mediumsize enterprises (MSMEs) contributes a significant share of GDP at 20%. In parallel, the digital sector is growing at a\nfast pace (see Section B below), and newly found oil and gas reserves are driving recent investments in the energy\nsector. <sup>9</sup> [^9: Ibid.]\n\n\n1 World Bank World Development Indicators (2017).\n2 Ibid.\n3 Diagnostic study n°5.1 to 5.3 to support the mid-term review of Uganda’s 2nd National Development Plan (", "output": {"entities": {"named_data": ["World Bank World Development Indicators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000063", "page": 2, "chunk": 1, "title": "Concept Project Information Document (PID) - Uganda Digital Acceleration Program - P171305", "pdf_url": "http://documents.worldbank.org/curated/en/948351570727493669/pdf/Concept-Project-Information-Document-PID-Uganda-Digital-Acceleration-Program-P171305.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Bank World Development Indicators", "label": "NAMED_DATA", "score": 0.7771656513214111, "start": 41, "end": 80, "probe_score": 0.9997, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " of Jordan on the<br>enforcement of 2007 Access to Information law.<br>DLR 8.2: Public dashboard and semi-annual reports of the PMDU.<br> DLR 8.3 & 4: Annual report on the implementation of access to information from the Information<br>Commission.|\n|Verification Entity|KACE.|\n|Procedure|DLR 8.1: Verification of official notification documenting the submission by the GoJ to Parliament of<br>amendments to the 2007 Access to Information Law  that they include the following provisions: (1) opening<br>of the Information Council, which oversees the enforcement of the law to Civil Society Organizations<br>(CSOs), strengthening its oversight responsibility; (2) specifying that exceptions do not include information<br>related to human rights violations, war crimes, and crimes against humanity;  (3) mandating proactive<br>information disclosure and the appointment of information officers in all departments; and (4) shortening<br>delays to respond to requests for information.<br>DLR 8.2:  Verification of the availability of information on the PMDU dashboard every semester.<br>DLR 8.3 & 4: Verification of annual reports to be submitted by the Information Council regarding the<br>enforcement of the Access to Information Law based on spot checks by the IVA in government entities.|\n\n\n\n\n\n\n\n|DLI 9 on expanding access to user-friendly and interactive statistical data.|Col2|\n|---|---|\n|Formula|**Scalable.**The DLI disburses against the strengthening of the statistical legal framework; progress toward<br>the integration of data from various government entities; the public disclosure of key indicators, as well as<br>their underlying micro-data, subject to an established protocol for access. It", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000181", "page": 57, "chunk": 1, "title": "Jordan - People-Centric Digital Government Program for Results", "pdf_url": "https://documents1.worldbank.org/curated/en/099030724150040202/pdf/BOSIB-70f97ae8-b741-401c-82cc-e87615cc5487.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.567761242389679, "start": 1355, "end": 1371, "probe_score": 0.0217, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "embre 2021.\n\n4. L’étude a été réalisée dans 3 écoles dans la zone de Barsalogho,\nBurkina Faso.\n\n\n\nElèves qui ne se sentent\npas en sécurité à l'école\n\n\n\n\n\nElèves qui ont peu ou pas du\n\ntout d'espoir en l'avenir\n\n\n\nEnfants qui ne peuvent pas se\n\n\n\ndevoirs\n\n\n\nconcentrer pour faire leurs", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000768", "page": 2, "chunk": 3, "title": "Améliorer le bien-être et l’apprentissage des enfants dans le Sahel central : renforcement du soutien psychosocial dans les écoles", "pdf_url": "https://reliefweb.int/attachments/70d4db7f-0015-3c29-9a27-adfba6f6d0e4/wca_educationsomadvocacynotesfr_20220124.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "16\n\n\ntraditional gross or net enrollment ratios. Their most recent version of the data set also\ntakes into account changes in school duration over time within countries.\n\nThe second global data set for average years of schooling is that of Cohen and\nSoto (2001), which covers 95 countries and spans the period 1960 to 2000 on a decade\nbasis. This data set uses 3 main sources of data. They are the OECD database on\neducation, national censuses or surveys published by UNESCO’s Statistical Yearbook\nand censuses obtained directly from national statistical agencies’ web pages. Based on\nreports from its members and other non-member countries, the OECD has published\ndetailed information on educational attainment, beginning at the end of the 1980s. This\ninformation refers to the population aged 15 to 64 broken up in different age groups and\nthis is the cornerstone of the Cohen-Soto data set for high-income countries. The main\nadvantage of the OECD data set is that the information is presented in a standardized\nform across countries. Cohen and Soto extend the study performed by the OECD to\nmissing periods and countries.\n\n\nOne key difference between the Cohen-Soto dataset is in the methodology for\nextrapolating the missing data. Barro and Lee extrapolate missing data for the whole\npopulation either backwards or forwards to obtain educational attainment for missing\nyears. As opposed to using the whole population, Cohen and Soto utilize estimates for\nage-specific groups, which they argue tend to result in more reliable estimates. Cohen\nand Soto also claim that for some countries, they had more recent census information\nthan that used by Barro and Lee.\n\n\nIn order to obtain the broadest coverage of countries for data on educational\nattainment, we combined the information from the Barro-Lee and Cohen-Soto data sets to\nobtain the resultant data set that covers 144 countries for the period 1960 to 2000. If\neducational attainment data on a specific country is contained in both data sets, then we\nfollow Bosworth and Collins (2003) and take the", "output": {"entities": {"named_data": ["OECD database on\neducation", "Cohen-Soto data set", "OECD data set", "Cohen-Soto dataset", "Barro-Lee"], "descriptive_data": ["census information"], "vague_data": ["educational attainment data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002639", "page": 15, "chunk": 0, "title": "wps3366knowledge", "pdf_url": "https://local/prwp/wps3366knowledge.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "OECD database on\neducation", "label": "NAMED_DATA", "score": 0.8370257019996643, "start": 398, "end": 424, "probe_score": 0.8825, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Cohen-Soto data set", "label": "NAMED_DATA", "score": 0.7262440323829651, "start": 873, "end": 892, "probe_score": 0.9575, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "OECD data set", "label": "NAMED_DATA", "score": 0.5618789196014404, "start": 946, "end": 959, "probe_score": 0.9951, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Cohen-Soto dataset", "label": "NAMED_DATA", "score": 0.6636618971824646, "start": 1159, "end": 1177, "probe_score": 0.9341, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "census information", "label": "DESCRIPTIVE_DATA", "score": 0.608286440372467, "start": 1613, "end": 1631, "probe_score": 0.9869, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Barro-Lee", "label": "NAMED_DATA", "score": 0.7895325422286987, "start": 1794, "end": 1803, "probe_score": 0.9319, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "educational attainment data", "label": "VAGUE_DATA", "score": 0.7567206621170044, "start": 1920, "end": 1947, "probe_score": 0.5568, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " before the onset of the conflict has resulted\nin steep decline of the oil revenues and raised the budget deficit to 10 percent of GDP. The economy of Yemen has\nbeen in decline since the conflict erupted in 2015, and the real GDP has contracted by 35 percent since late 2014. In\naddition, the public revenues have declined by about 50 percent in 2015 and by additional 20 percent in 2016 due to\nthe fall in oil revenues (77 percent) and non-oil revenues (34 percent).\n\n\nPage 8", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000008", "page": 12, "chunk": 2, "title": "Yemen - Emergency COVID-19 Project", "pdf_url": "http://documents1.worldbank.org/curated/en/106571586194037855/pdf/Yemen-Emergency-COVID-19-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n\n# Executive summary\n\nThe war in Ukraine, now in its third year, continues\nto have devastating effects on the Ukrainian\npopulation, triggering one of the largest\ndisplacement crises in Europe since World War II. As\nof December 2024, over 6.2 million Ukrainian\nrefugees have been recorded across Europe, the\nmajority of whom are women, children, and older\npersons. The European Union extended the\nTemporary Protection Directive until March 2026,\ngranting Ukrainian refugees access to essential\nhealth services, education, and other critical\nsupport. The Republic of Moldova followed this\nmodel and also introduced Temporary Protection for\nUkrainian refugees.\n\n\nIn 2024, to assess the health and mental health\nsituation of Ukrainian refugees, their access to\nservices, and the barriers they face across\ncountries, Regional Refugee Response Plan (RRP)\nhealth and mental health and psychosocial support\n(MHPSS) partners conducted a regional analysis of\nthe Socio-Economic Insights Survey (SEIS) data from\n10 refugee-hosting countries: Bulgaria, Czechia,\nEstonia, Hungary, Latvia, Lithuania, Poland, Republic\nof Moldova, Romania, and Slovakia. The analysis\nincludes a comparison with key indicators collected\nin 2023.\n\n\nKey finding from the regional analysis include:\n\n\n\n\n\n\n\n\n\n\n\n\n\n**3**", "output": {"entities": {"named_data": ["Socio-Economic Insights Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000004", "page": 2, "chunk": 0, "title": "NAVIGATING HEALTH AND WELL BEING CHALLENGES FOR REFUGEES FROM UKRAINE   2nd Edition", "pdf_url": "https://local/jad_paddy_docs/navigating health and well-being challenges for refugees from ukraine - 2nd edition.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Socio-Economic Insights Survey", "label": "NAMED_DATA", "score": 0.9244328737258911, "start": 1024, "end": 1054, "probe_score": 0.9776, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "B, but effectively these areas are defined by two criteria. First, they are blobs with con\n\ntiguous pixels of the density of above 1,500 per sq. km. Then, for these blobs to be in our\n\n\nsample, they should have at least one UN listed metropolitan area and the populations of\n\n\nall the listed UN metropolitan areas in the blob should sum to at least 800,000. Once we\n\n\nhave defined these areas, we then give the agglomeration the Landscan population num\n\nber obtained by summing over all grid squares in the blob. The primary issue is that, with\n\n\nthe lower density criterion, vast swathes of seemingly rural areas in India and China are\n\n\ncombined into, and considered, gigantic urban areas regardless of whether the areas are\n\n\nreally urban in nature. Hence, we prefer the higher density thresholds as well as a cross\n\n\ncheck with the official UN data.For 6 African countries, we did our own checks, but doing\n\n\nthe world in detail for smaller places and densities was beyond our scope.\n\n\nGiven these criteria, we establish a set of 599 cities worldwide, with 451 in the devel\n\noping world. We ran regressions with dependent variables, in logs, as follows: personal\n\n\npopulation density [PPD], simple population density [PD], the coefficient of variation term\n\n\nin eq (2), the De La Roca-Puga agglomeration measure [RPA], the simple average of the\n\n\nlocal De La Roca-Puga measure [AD], and the covariance term in (3). For the RPA mea\n\nsure, we use a spatial discount rate of -0.5, as compared to De La Roca and Puga (2017)\n\n\nwho use no discounting. Later in the paper we will analyze the optimal rate of discount\n\n\nfor a particular and narrower context, where we find that -0.5 is close to the optimal rate\n\n\nfor Africa.\n\n\nFigure 5 shows the differences in PPD worldwide by country; where", "output": {"entities": {"named_data": [], "descriptive_data": ["UN data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007590", "page": 15, "chunk": 0, "title": "wps8678", "pdf_url": "https://local/prwp/wps8678.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UN data", "label": "DESCRIPTIVE_DATA", "score": 0.5934030413627625, "start": 845, "end": 852, "probe_score": 0.9771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\n\n\n\n\n\n\n\n|Monitoring & Evaluation Plan: PDO Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **|**Definition/Description **|**Frequency **|**Datasource **|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|Beneficiaries of social safety net programs||This indicator<br>will be<br>measured at<br>least on a<br>quarterly<br>basis during<br>missions and<br>ISRs<br>|SNSOP MIS<br>which hosts<br>beneficiary<br>registration<br>and payment<br>data<br>|The implementing<br>partner will collect<br>beneficiary data during<br>targeting and<br>registration. The<br>payment service<br>provider will document<br>payment data and<br>share with the<br>implementing partner<br>|Implementing Partner<br>|\n|Beneficiaries of social safety net<br>programs - Female||This indicator<br>will be<br>measured at<br>least on a<br>quarterly<br>basis during<br>missions and<br>ISRs<br>|SNSOP MIS<br>which hosts<br>beneficiary<br>registration<br>and payment<br>data<br>|The implementing<", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["beneficiary data", "payment data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 55, "chunk": 0, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "beneficiary data", "label": "VAGUE_DATA", "score": 0.5927293300628662, "start": 655, "end": 671, "probe_score": 0.0877, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "payment data", "label": "VAGUE_DATA", "score": 0.5629788041114807, "start": 765, "end": 777, "probe_score": 0.0486, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Methodology A:** Uses the Specific Needs Codes (SNC) in _proGres_ to estimate the number of people in need of\n\nresettlement. This methodology requires Offices to create a report from _proGres_ showing the number\nof persons who have specific needs that correspond to a likelihood of resettlement eligibility. The\nguidelines further provide breakdown of SNC into high/medium or variable/low resettlement likelihood.\n\n\n**Methodology B:** \u0007Uses community-based approaches, participatory assessments, and the HRIT to inform resettlement\n\nneeds of people of concern to UNHCR as well as to key partners. The HRIT links participatory\nassessments and individual assessment methodologies to identify refugees at risk.\n\n\n**Methodology C:** \u0007Uses “best estimates” based upon limited available data. This methodology requires Country Offices to\n\nprovide a “best estimate” of the projected resettlement needs by using relevant internal and external\ndata.\n\n\nThe most thorough and reliable approach combines all of the above methodologies with an emphasis on methodologies\nA and B. Methodology C alone is normally only used when Offices do not have access to _proGres_ data and are unable to\nconduct participatory assessments or a representative sample survey of the refugee population. For the 2020 planning\ncycle, the vast majority of Country Offices combined various methodologies to ensure a comprehensive and multi-year\napproach to this exercise.\n\n\n\n60", "output": {"entities": {"named_data": ["_proGres_ data"], "descriptive_data": ["representative sample survey of the refugee population"], "vague_data": ["internal and external\ndata"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000739", "page": 60, "chunk": 0, "title": "UNHCR Projected Global Resettlement Needs 2020", "pdf_url": "https://reliefweb.int/attachments/6ce5b0b3-c2b0-3a37-afa5-11faad94047c/5d1384047.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "internal and external\ndata", "label": "VAGUE_DATA", "score": 0.5667802691459656, "start": 915, "end": 941, "probe_score": 0.5908, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "_proGres_ data", "label": "NAMED_DATA", "score": 0.7145851850509644, "start": 1145, "end": 1159, "probe_score": 0.4676, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "representative sample survey of the refugee population", "label": "DESCRIPTIVE_DATA", "score": 0.6784731149673462, "start": 1217, "end": 1271, "probe_score": 0.0247, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " between households of female owners and households of male owners.\n\n\n(See columns 4 through 6 of Table 4). We do find significant differences in the rate at\n\n\nwhich household durable goods ownership increases, and in financial assets. Column 7 of\n\n\nTable 4 takes as the dependent variable the first principal component of a vector of 17\n\n\nhousehold assets, including landline and cellular telephones, television, autos, bicycles\n\n\nand gold jewelry. The weights in the index are derived from baseline data. Asset\n\n\nownership increases generally in the sample, but the regression results reported in column\n\n\n7 shows that the increase is significantly larger in households of male enterprise owners\n\n\n                               - - 17", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003950", "page": 18, "chunk": 1, "title": "wps4746", "pdf_url": "https://local/prwp/wps4746.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "baseline data", "label": "VAGUE_DATA", "score": 0.7459962368011475, "start": 492, "end": 505, "probe_score": 0.7136, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Figure 5-B. Explanation of Differences in Informality, LAC Countries and Chile**\n\nHeritage Foundation Informal Market index (range 1-5: higher, more informality)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|ARGENTINA<br>(%)<br>80<br>60<br>40<br>20<br>0|ARGENTINA|Col3|Col4|Col5|Col6|Col7|BOLIVIA<br>(%)<br>80<br>60<br>40<br>20<br>0|BOLIVIA|Col10|Col11|Col12|Col13|Col14|BRAZIL<br>(%)<br>80<br>60<br>40<br>20<br>0|BRAZIL|Col17|Col18|Col19|Col20|Col21|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n|0<br>20<br>40<br>60<br>80<br>(%)<br>ARGENTINA|(%)<br>|(%)<br>|(%)<br>|(%)<br>|(%)<br>|(%)<br>|(%)<br>|(%)<br>|(%)<br>|(%)<br>|(%)<br>|(%)<br>", "output": {"entities": {"named_data": ["Heritage Foundation Informal Market index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004083", "page": 29, "chunk": 0, "title": "wps4888", "pdf_url": "https://local/prwp/wps4888.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Heritage Foundation Informal Market index", "label": "NAMED_DATA", "score": 0.8375258445739746, "start": 84, "end": 125, "probe_score": 0.9928, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "3\n\n\n**2. Project development objective** (see Annex 1)\n\nThe objective of the project is to enhance the quality of education and to increase enrollment in\nprimary schools.\n\n\n**3. Key performance indicators:** (see Annex 1)\n\nThe key performance indicator is an increased number of students enrolled in grades 1-9, especially\namong girls.\n\n\nB. **STRATEGIC CONTEXT**\n\n\n**1. Sector-related Country Assistance Strategy (CAS) goal supported by the project** (see Annex 1)\n\n\n**Document number:** P 7403 DJI **Date of latest CAS discussion:** (scheduled for) 12/19/00\n\nThe CAS has been prepared in the context of the country's economic difficulties and deepening\npoverty. Despite Djibouti's relatively high nominal per capita income (US$790 versus an average of\nUS$510 for Sub-Saharan Africa, and US$100 for Ethiopia), Djibouti has one of the poorest social\nindicators in the world (poverty, illiteracy, maternal and infant mortality, and morbidity), according to\nthe UNDP Human Development Index, ranking 157th among 174 countries.\n\n\nThe Republic of Djibouti has very few natural resources and the economy is mainly dependent on the\nport, external financial assistance, the French military and associated services. However, with the\n\ndecreased amount of external assistance, and deepening structural problems, the country has suffered\neconomic stagnation over the past decade and a half. As a result, per capita Gross Domestic Product\n(GDP) declined by 50% in real terms since 1985. The switch of Ethiopia's transit traffic from Assab in\nEritrea to Djibouti in mid-1998 and the consequent four-fold increase in port traffic has opened new,\nas yet not fully exploited, opportunities for investment and growth. Djibouti's open economic policies\nand relative stability, characterized by a liberal trade policy and exchange system, which operates free\n\nof capital or", "output": {"entities": {"named_data": ["UNDP Human Development Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:021184", "page": 6, "chunk": 0, "title": "Ethiopia - Drought Area Rehabilitation Project", "pdf_url": "https://documents.worldbank.org/curated/en/989301468255255694/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNDP Human Development Index", "label": "NAMED_DATA", "score": 0.8519672155380249, "start": 959, "end": 987, "probe_score": 0.9988, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "br>El Salvador<br>3,102<br> <br>Somalia<br>1,124<br> <br>Zimbabwe<br>2,300<br> <br>Haiti<br>2,701<br> <br>Afghanistan<br>705<br> <br>China<br>2,185<br> <br>Mexico<br>2,472<br> <br>Occ. Palest. Terr.<br>157<br> <br>Iraq<br>2,075<br> <br>Guatemala<br>2,185<br> <br>DR of Congo<br>76<br> <br>Somalia<br>1,960<br> <br>Colombia<br>1,199<br> <br>Sudan<br>76<br> <br>Eritrea<br>1,905<br> <br>Ethiopia<br>1,140<br> <br>Ethiopia<br>54<br> <br>Pakistan<br>1,765<br> <br>Indonesia<br>1,018<br> <br>Sri Lanka<br>50<br> <br>Sri Lanka<br>1,250<br> <br>Honduras<br>933<br> <br>Eritrea<br>45<br> <br>Nigeria<br>905<br> <br>Iraq<br>734<br> <br>** Data for Serbia might include Montenegro in a few cases where no separate statistics are available for both countries.<br>**** Combination of cases (DHS) and persons (EOIR).<br>|Turkey<br", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Data for Serbia"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001058", "page": 35, "chunk": 9, "title": "Asylum levels and trends in industrialized countries, 2007", "pdf_url": "https://reliefweb.int/attachments/a0f955c8-b460-3603-b1cc-8d2ccc064a5f/BF4CF8525B21A81049257410001BC61A-Full_Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data for Serbia", "label": "VAGUE_DATA", "score": 0.6554558277130127, "start": 630, "end": 645, "probe_score": 0.6111, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "15|15|||\n|Total|Total|Total|Total|Total|Total|100|100|100|100|\n|I certify that there is no Adaptation and Mitigation Climate Change Co-benefits information applicable to this project.|I certify that there is no Adaptation and Mitigation Climate Change Co-benefits information applicable to this project.|I certify that there is no Adaptation and Mitigation Climate Change Co-benefits information applicable to this project.|I certify that there is no Adaptation and Mitigation Climate Change Co-benefits information applicable to this project.|I certify that there is no Adaptation and Mitigation Climate Change Co-benefits information applicable to this project.|I certify that there is no Adaptation and Mitigation Climate Change Co-benefits information applicable to this project.|I certify that there is no Adaptation and Mitigation Climate Change Co-benefits information applicable to this project.|I certify that there is no Adaptation and Mitigation Climate Change Co-benefits information applicable to this project.|I certify that there is no Adaptation and Mitigation Climate Change Co-benefits information applicable to this project.|I certify that there is no Adaptation and Mitigation Climate Change Co-benefits information applicable to this project.|\n|||||||||||\n|**Themes**|**Themes**|**Themes**|**Themes**|**Themes**|**Themes**|**Themes**|**Themes**|**Themes**|**Themes**|\n|Theme (Maximum 5 and total % must equal 100)|Theme (Maximum 5 and total % must equal 100)|Theme (Maximum 5 and total % must equal 100)|Theme (Maximum 5 and total % must equal 100)|Theme (Maximum 5 and total % must equal 100)|Theme (Maximum", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000026", "page": 6, "chunk": 5, "title": "Jordan - Emergency Services and Social Resilience Project", "pdf_url": "http://documents.worldbank.org/curated/en/532171468273353365/pdf/PAD7230P1476890AD0October0100final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "BWE’s accounts (including before merger) since 1994.\n\n\n**Financial performance (2008–2013 and 2014 estimate)**\n\n\n164. The past financial performance covers years 2008–2013 and 2014 (estimates). It is based on\nunaudited financial statements prepared on cash basis and consists of collection of bills and\ndisbursement of different operational expenses. No receivables, payables, fixed assets, and other\nassets or liabilities are recorded in the financial statements presented to the Government.\nConsequently, no provision for doubtful accounts or depreciation of fixed assets is included. This\ngives a limited picture of the BWE financial situation. Nevertheless, the project team undertook a\nfinancial analysis based on all available data and information.\n\n\n165. **BWE revenues** _._ Water collection rate has increased substantially over the years but remains\nbelow standards. As shown in the BWE records, the collection rate of water fees has increased from\n17.5 percent in 2009 to about **35 percent in 2013** . No increase was noticed in year 2014, however\ngiven the critical role that bill collection plays BWE is submitting a new proposal to its Board to\nreactivate the collection issue. New subscriptions and the outreach campaign during the previous\nBank-funded project with the assistance of other donors have contributed to improvement in the BWE\nrevenue collection by about 100 percent from 2009 to 2013. Efforts made during the last three years\nhave had positive impact on BWE finances. BWE is now able to pay regularly its staff and part of its\n\nelectricity bills. BWE cash on hand at August 2014 was equivalent to approximately 1.5 year ’ s worth\nof staff salaries and benefits, a significant progress under difficult circumstances. However, many\nissues remain with a large number of households connected to the water system, but not paying bills\nand those illegally connected (estimated between 30 to 50 percent). To compensate for cash shortfall,\nthe BWE also receives grants from the Mo", "output": {"entities": {"named_data": [], "descriptive_data": ["BWE records"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000036", "page": 51, "chunk": 0, "title": "Lebanon - Lake Qaraoun Pollution Prevention Project", "pdf_url": "http://documents1.worldbank.org/curated/en/279341468589482380/pdf/PAD860-PAD-P147854-R2016-0133-1-Box396255B-OUO-9.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "BWE records", "label": "DESCRIPTIVE_DATA", "score": 0.7515518069267273, "start": 893, "end": 904, "probe_score": 0.506, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|* The market share represents the average of the sample market but only in countries in which the firms of the sample have an activity. The<br>standard deviations are given for regional and country measures.|* The market share represents the average of the sample market but only in countries in which the firms of the sample have an activity. The<br>standard deviations are given for regional and country measures.|* The market share represents the average of the sample market but only in countries in which the firms of the sample have an activity. The<br>standard deviations are given for regional and country measures.|* The market share represents the average of the sample market but only in countries in which the firms of the sample have an activity. The<br>standard deviations are given for regional and country measures.|* The market share represents the average of the sample market but only in countries in which the firms of the sample have an activity. The<br>standard deviations are given for regional and country measures.|* The market share represents the average of the sample market but only in countries in which the firms of the sample have an activity. The<br>standard deviations are given for regional and country measures.|\n\n\nFirst it shows that we tried to report data on the sectors as unbundled as possible.\n\n\nSecond, for the electricity and telecommunications, we managed to get market data close\n\n\nenough to what a competition agency would consider appropriate. For water and sanitation,\n\n\nwe relied on two proxies: urban population and total population. The first probably gives a\n\n\nlower bound and the second an upper bound of the populations affected by the large operators\n\n\ncovered by the database. We should thus get respectively a further level of upper and lower\n\n\nbound for the concentration index from these two measures. Third, the country coverage is\n\n\nrelatively evenly distributed between OECD and non-OECD countries which ensures a\n\n\nreasonable sense of robustness when comparing the two country", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["market data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002739", "page": 9, "chunk": 2, "title": "wps3513", "pdf_url": "https://local/prwp/wps3513.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "market data", "label": "VAGUE_DATA", "score": 0.679681122303009, "start": 1409, "end": 1420, "probe_score": 0.5333, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " services|Description:Share of users satisfied by the received health care services|Description:Share of users satisfied by the received health care services|Description:Share of users satisfied by the received health care services|Description:Share of users satisfied by the received health care services|Description:Share of users satisfied by the received health care services|\n|||||||||\n|**Name:**Grievances registered<br>related to delivery of project<br>benefits addressed||Percentage|40.00|75.00|Bi-annual<br>|Grievance database<br>|PMU<br>|\n|Description:Percentage of grievances registered related to the delivery of project benefits that were addressed|Description:Percentage of grievances registered related to the delivery of project benefits that were addressed|Description:Percentage of grievances registered related to the delivery of project benefits that were addressed|Description:Percentage of grievances registered related to the delivery of project benefits that were addressed|Description:Percentage of grievances registered related to the delivery of project benefits that were addressed|Description:Percentage of grievances registered related to the delivery of project benefits that were addressed|Description:Percentage of grievances registered related to the delivery of project benefits that were addressed|Description:Percentage of grievances registered related to the delivery of project benefits that were addressed|\n|||||||||\n|**Name:**Hospital Assessment<br>carried out||Text|NA|Assessment<br>completed|Once<br>|MoPH<br>|MoPH/PMU<br>|\n|Description:Hospital Assessment carried out|Description:Hospital Assessment carried out|Description:Hospital Assessment carried out|Description:Hospital Assessment carried out|Description:Hospital Assessment carried out|Description:Hospital Assessment carried out|Description:Hospital Assessment carried out", "output": {"entities": {"named_data": ["Grievance database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000032", "page": 45, "chunk": 1, "title": "Lebanon - Health Resilience Project", "pdf_url": "http://documents.worldbank.org/curated/en/616901498701694043/pdf/Lebanon-Health-PAD-PAD2358-06152017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Grievance database", "label": "NAMED_DATA", "score": 0.6918053030967712, "start": 517, "end": 535, "probe_score": 0.0372, "gold": "NON_MENTION", "gold_tier": "human-final"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2014 censuses that would, without addressing them, make it impossible to estimate employment\ngrowth in Ghana over this period (Kerr and McDougall, 2019). The main issues we identified are\ndifferences in coverage of rural and urban areas, differences in the enumeration of associations and\ndifferences in coverage of the smallest firms.\n\n\nIn Kerr and McDougall (2019) we showed that the 2014 IBES enumerated a total number of own\naccount workers that was around 5% of own account workers enumerated in the 2010 population\ncensus. The number is “only” 5% because the smallest firms did not qualify for the firm census\n(which excluded household‐based firms unless there was a sign indicating the presence of a firm in\nthe household dwelling). But this same percentage was only 0.5% in the 2003 NIC. This means that\nthe 2014 IBES covered a dramatically higher fraction of own account workers than 2003. The fraction\nof small firms covered also increased (Kerr and McDougall, 2019). To ameliorate this issue, we limit\nour main analysis to firms with 5 or more persons engaged. Persons engaged includes working\nproprietors, employees, unpaid family workers and apprentices, as a large fraction of Ghanaians\nworking in manufacturing are not employees in the sense that the word is used in developed\ncountries.\n\n\nThe 2014 census covered rural areas much better than the 2003 census (Kerr and McDougall, 2019).\nThe 2003 NIC survey documentation notes that in rural areas only firms on the initial list of firms\nobtained prior to the census (likely obtained from tax records or the 1987 census) were enumerated,\nalthough enquiries were made of other firms in the vicinity. It is thus likely that rural areas would\nexperience higher “employment” growth between 2003 and 2014, simply because coverage of rural\nfirms was better in 2014. We ameliorate this issue in two ways. Firstly, we limit our analysis to firms\nwith 5 or more persons engaged, as discussed above, since we think that the enumeration of larger\nfirms", "output": {"entities": {"named_data": ["2014 IBES", "2010 population\ncensus", "2003 NIC", "2014 IBES", "2003 NIC survey", "1987 census"], "descriptive_data": ["2014 censuses", "firm census", "tax records"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000048", "page": 9, "chunk": 0, "title": "agglomeration urbanization and employment growth in ghana evidence from an industry district panel", "pdf_url": "https://local/prwp/agglomeration-urbanization-and-employment-growth-in-ghana-evidence-from-an-industry-district-panel.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2014 censuses", "label": "DESCRIPTIVE_DATA", "score": 0.5593956708908081, "start": 0, "end": 13, "probe_score": 0.875, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2014 IBES", "label": "NAMED_DATA", "score": 0.7447676062583923, "start": 386, "end": 395, "probe_score": 0.8871, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2010 population\ncensus", "label": "NAMED_DATA", "score": 0.7663804888725281, "start": 505, "end": 527, "probe_score": 0.8181, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "firm census", "label": "DESCRIPTIVE_DATA", "score": 0.5625469088554382, "start": 604, "end": 615, "probe_score": 0.9421, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2003 NIC", "label": "NAMED_DATA", "score": 0.8020446300506592, "start": 786, "end": 794, "probe_score": 0.9438, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2014 IBES", "label": "NAMED_DATA", "score": 0.5191802978515625, "start": 816, "end": 825, "probe_score": 0.9961, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2003 NIC survey", "label": "NAMED_DATA", "score": 0.7183222770690918, "start": 1406, "end": 1421, "probe_score": 0.941, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "tax records", "label": "DESCRIPTIVE_DATA", "score": 0.5754914283752441, "start": 1553, "end": 1564, "probe_score": 0.9789, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "1987 census", "label": "NAMED_DATA", "score": 0.6024100184440613, "start": 1572, "end": 1583, "probe_score": 0.5931, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".70 4.54 3.91 2.17 2.40 1.90\nPct. pavement in sec. road 0.44 0.47 0.51 0.26 0.42 0.44\n_<u>N.</u>_ _<u>of</u>_ _<u>Observations</u>_ <u>191</u> <u>64</u> <u>18</u> <u>36</u> <u>73</u>\n\n_<u>a</u>_ Computed excluding villages established after 1964.\nNote: Data come from the key informant survey of the Townsend-Thai dataset. Each observation\nis a village. P refers to Program villages.\n\n\n32", "output": {"entities": {"named_data": ["Townsend-Thai dataset"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002948", "page": 31, "chunk": 1, "title": "wps3734", "pdf_url": "https://local/prwp/wps3734.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Townsend-Thai dataset", "label": "NAMED_DATA", "score": 0.9037388563156128, "start": 300, "end": 321, "probe_score": 0.9969, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*\n\n\n\nThic Comitry\n\n\n\n**AV01.1d** **Bank**\n.P.0. Bo-, **3.0577** **-** **06100**\n\n\n\nNAIROB-I.\n\n\n\n**ISO** **9001:2008**\n\n**C** **e-** r t **11** **e** **d.**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009189", "page": 35, "chunk": 3, "title": "Audit Report", "pdf_url": "https://documents.worldbank.org/curated/en/183941516785085385/pdf/Audit-Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " sudden increased demand for services provided at the\nlocal level, whether run by central or municipal authorities, has put mayors and municipal\ncouncils under mounting pressure. The municipalities have been addressing the daily problems\nof keeping up with the provision of municipal services (for example, solid waste generation has\ndoubled in several areas with high concentration of refugees, contributing to ground water\ncontamination, pollution of water resources and spread of water-borne diseases), while they have\nalso been asked to find solutions to basic social demands such as education and health, among\nmany. This is not a new role for municipalities, which have traditionally been at the forefront of\naddressing the recurrent cycle of emergencies that have plagued Lebanon. In so doing, they have\nbeen working across confessional barriers and political differences in a way close to impossible\nfor the central government, providing practical solutions in the face of an ever growing crisis.\n\n\n**B.** **Situations of Urgent Need of Assistance**\n\n\n7. This Project is being prepared and implemented according to Paragraph 11 of the World\nBank Operational Policy 10.00, which allows for certain exceptions to the investment project\nfinancing policy requirements if the Bank deems the recipient to be in urgent need of assistance\nas a consequence of events such as man-made disasters or conflicts. The evolving situation in\nLebanon reflects both the impact of conflict (in neighboring Syria) and of a man-made disaster\n(resulting from the influx of refugees fleeing the conflict) – two specific situations that the\nprovisions were developed to address.\n\n\n2", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000003", "page": 12, "chunk": 1, "title": "Lebanon - Municipal Services Emergency Project", "pdf_url": "http://documents.worldbank.org/curated/en/119441469672145615/pdf/PAD10180PAD0P14972400PUBLIC00Box391431B.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".\n\n**Relevance of Implementation** is rated as **high both before and after the restructuring.**\n\nThe overall relevance of objectives, design and implementation is assessed as **high.**\n\n**3.2 Achievement of Project Development Objectives (Efficacy)**\n\nProgress of the results indicators was notable both before and after the results framework\nwas revised for the Additional Financing in 2011. The appraisal mission for PBS II\nAdditional Financing undertook a comprehensive review of the PBS program\nperformance and in terms of progress towards Development Objectives and\nImplementation Progress, PBS II was rated Satisfactory.\n\nMeasured in terms of meeting its results indicators before the Additional Financing, the\nPBS Program, while not exceptional, was progressing relatively well. This was evidenced\nby data in the project ISR before the AF, and the accompanying mission documentation.\nFor example, in education the Net Enrollment Rate for children in primary school\nincreased from 79 percent to 87.9 percent between FY07 and FY10, which represents an\nincrease of almost 1.5 million additional children attending school. The ratio of primary\nhealth workers to population at the time (beginning of 2011) reached 1:2,500 from\n1:4,369 three years earlier. Similarly, in agriculture, the number of development agents\nproviding technical advice to small-scale farmers has risen from about 50,000 in FY08 to\n63,000 in FY10, an increase of 26 percent. For water, 65.8 percent of the rural population\nhad access to potable water in FY10, which represented a substantial improvement over\nthe baseline in FY07, where 46 percent had access. Finally, there was improved\n\n\n15", "output": {"entities": {"named_data": [], "descriptive_data": ["data in the project ISR"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016413", "page": 30, "chunk": 1, "title": "Ethiopia - Second Phase of the Protection of Basic Services Program Project", "pdf_url": "https://documents.worldbank.org/curated/en/668611468029718524/pdf/ICR25740P103020IC0disclosed01080140.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data in the project ISR", "label": "DESCRIPTIVE_DATA", "score": 0.7375679016113281, "start": 809, "end": 832, "probe_score": 0.9403, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " stronger increase in\nlabour productivity than was assumed. As\na result, the positive impact of Ukrainian\nrefugees on the economy is greater than\npreviously expected.\n\n\n\n**As Ukrainian refugees entered the**\n**labour market, the economy adapted,**\n**resulting in more specialization and**\n**higher productivity.** In a simplistic\nsupply-demand framework, the influx\nof Ukrainian refugees should have\ncaused some Polish workers to become\nunemployed or leave the labour force, or\nreal wages to fall. This has not happened.\nFirst, among Polish citizens employment\nrates have grown, and unemployment\nrates have fallen. Second, poviats in which\nemployment share of Ukrainian refugees\nhas grown by 1 pp., saw 0.5 pp. higher\nemployment rates among Polish citizens,\nand 0.3 pp. lower unemployment rates.\n\n\n\nThird, there is no evidence of lowered\nwages, in fact the limited available data\nsuggests that Ukrainian refugees may have\ncaused higher wage growth in poviats\nwhich they have moved to. These are\ncommon findings well documented in\nacademic literature, that as immigrants\nenter the labour market, native workers\nspecialize in complementary, higher\nvalue tasks, which we see empirically in\nPolish workers moving to more attractive\noccupational groups. This can be seen in\nthe data, as Polish citizens are moving to\nbetter paid occupations. It constitutes a\npositive shock to productivity which is what\ncounterbalances labour market pressures. <sup>17</sup> [^17: For the literature review, underlying empirical evidence, and model calibration refer to the appendix on modelling strategy.]\n\n\n\nSource: Deloitte D.Climate estimates. For details see\nthe Online Technical Appendix.\n\n\n**The main impact of Ukrainian refugees**\n**is expanding the economy and putting**\n**it on a higher growth path.** According\nto the Deloitte D.Climate model, economic\nimpact of Ukrainian refugees amounted\nto a higher real GDP by 1.5% in 2022, as\nthey initially entered the labour market.\nWith more", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["limited available data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 11, "chunk": 2, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "limited available data", "label": "VAGUE_DATA", "score": 0.6761394739151001, "start": 857, "end": 879, "probe_score": 0.0747, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "consumption increased by more than fourfold between 2005 and 2015 (in China it\n\n\nsoared since 2005, from 482.0×10 <sup>8</sup> m <sup>3</sup> in 2005 to 1,973.0×10 <sup>8</sup> m <sup>3</sup> in 2015, with an\n\n\naverage annual growth rate of 15.1% [37]). Detailed contributions of various factors to\n\n\nthese four subpanels are also listed in Tables A5-A8.\n\n\n**Fig. 6.** Contributions of various driving forces to the emissions changes in countries with different income\n\nlevels between 1980 and 1990, and between 2005 and 2015. **_Note:_** (a) HI countries, (b) UMI countries,\n\n(c) LMI countries, and (d) LI countries.\n\n\n**4. Results from the Econometric Analysis**\n\n\n**4.1. The estimation results**\n\n\nThe results of the analysis using the GMM technique are presented in Table 1. In\n\n\nthe table, column 1 presents the empirical results for 110 countries, while columns 2-5\n\n\ndepict the empirical results for the HI, UMI, LMI, and LI groups of countries,\n\n\nrespectively. As shown in the bottom of Table 1, the null hypotheses of the Hansen and\n\n\nAR (2) tests cannot be rejected, indicating that the instruments remain valid and that\n\n\nthere is no evidence for second-order serial correlation.\n\n\nThe coefficient of the lag stock of CO2 (i.e., ln _CO_ 2 _it_  1 <sup>) is positive and strongly</sup>\n\n\nsignificant. If countries emitted large amounts of CO2 in the past, then they are likely\n\n\n15", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007411", "page": 16, "chunk": 0, "title": "wps8477", "pdf_url": "https://local/prwp/wps8477.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".7 15.7 15.3 14.9\nServices\n\nHousehold final consumption expenditure 79.5 73.2\nGeneral gov’t final consumption expenditure 10.2 11.5\nImports of goods and services 38.4 46.0 45.5 45.6\n\n\n**199545** growth **of exports** and imports (%)\n(average annual growth)\nAgriculture 1.8 1.2 0 . 7 2.5 2o\nIndustry 6.2 4.2 5.2 6.0 i Manufacturing 7.6 4.3 5.1 6.0\nServices 4.7 5.3 7.6 5.1\n\nHousehold final consumption expenditure 4.0 -10\nGeneral gov’t final consumption expenditure 3.7 .. **-20**\nGross capital formation 2.5 5.3 11.6 12.0 -Exports +Imports\nImports of goods and services 5.6 7.3 9.3 8.7\n\n\nNote: 2005 data are preliminary estimates.\nThis table was produced from the Development Economics LDB database.\n\n- The diamonds show four key indicators in the countly (in bold) compared with its income-group average. If data are missing, the diamond will\nbe incomplete.\n\n\n72", "output": {"entities": {"named_data": ["Development Economics LDB database"], "descriptive_data": [], "vague_data": ["2005 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000023", "page": 77, "chunk": 2, "title": "Sri Lanka - Puttalam Housing Project", "pdf_url": "http://documents1.worldbank.org/curated/en/194731468104646411/pdf/38147core.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2005 data", "label": "VAGUE_DATA", "score": 0.6627598404884338, "start": 594, "end": 603, "probe_score": 0.9905, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics LDB database", "label": "NAMED_DATA", "score": 0.8771077990531921, "start": 664, "end": 698, "probe_score": 0.999, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " cost benefit analysis of investments in lower secondary school completion is based on estimates of wage**\n**earnings and data for both investment and recurrent costs.** Earnings gains are based on results from Tables 5.2\nand 5.3. Cost data are available from the MoES for investment costs (school construction) and recurrent costs\n(cost of operating schools). In addition, the analysis incorporates out-of-pocket costs for parents to send their\nchildren to school as measured with the UNHS 2016/17. Based on the available data and assumptions (including\na time discount rate of two percent, which is on the low side), the estimated internal rate of return is 13.9 percent.\nThis rate of return is sensitive to assumptions, including on the unit cost of schools (a lower unit cost would\nincrease the rate of return) and the time discount rate (a higher discount rate would reduce the rate of return).\nThe baseline rate of return of 13.9 percent accounts only for gains in earnings for students completing lower\nsecondary school thanks to the construction of new schools. Some students may drop out (reducing the rate of\nreturn), but others may continue to the upper secondary level (increasing the rate of return). Alternatives are\ndiscussed in Wodon (2020a), with a summary of a few alternative scenarios provided in Table 5.4. When\nconstruction costs increase by 10 percent, this does not affect too much the internal rate of returns, in part\nbecause these costs are but part of the total cost for the state of public education (recurrent costs tend to be\nlarger per student over the lifetime of schools). By contrast, when the discount rate increases, this has a large\nimpact on the internal rate of return since the present value of the future gains in earnings are smaller. Other\nsimulations could be conducted, for example with different assumptions on the marginal earnings gains from\nmore years of schooling. Overall though", "output": {"entities": {"named_data": ["UNHS 2016/17"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 94, "chunk": 2, "title": "Uganda - Secondary Education Expansion Project", "pdf_url": "http://documents.worldbank.org/curated/en/406361595815248191/pdf/Uganda-Secondary-Education-Expansion-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHS 2016/17", "label": "NAMED_DATA", "score": 0.8773514628410339, "start": 486, "end": 498, "probe_score": 0.9716, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "br>water supply schemes**(DLI 11)**<br>• <br>Communities sustain<br>community-wide sanitation<br>status (ODF, public ECD and<br>primary schools and HCFs)**(DLI**<br>**12)** <br>• <br>Sustainable integrated water<br>utility services provided|\n\n\n\n26 Climate-vulnerable rural areas are areas that are prone to climate change-exacerbated floods and/or droughts. All rural areas under in this\nProgram are climate vulnerable.\n27 There is variance across WSPs for the type and number of leadership positions that will be accounted for in indicator data. Leadership positions\ninclude Board Members, managers, or chief Executive Officers.\n28 Refugee camp WASH facility designs will take into account the need for lighting and design to minimize the risk of gender-based violence.\n\n\nPage 14 of 57", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["indicator data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000190", "page": 18, "chunk": 8, "title": "Kenya - Water, Sanitation, and Hygiene Program", "pdf_url": "https://documents1.worldbank.org/curated/en/099120123140034670/pdf/BOSIB-9a6accb6-73d1-4bd1-8307-d41a339a51ab.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "indicator data", "label": "VAGUE_DATA", "score": 0.7203497290611267, "start": 531, "end": 545, "probe_score": 0.4917, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\n36. The second Result Area aims to achieve **_improved teaching and learning conditions._** The\nmechanism to achieve this goal is a focus on improving the school physical environment and the\ncapacity of teachers and school leaders, and fostering positive student and teacher behavior and civic\nawareness toward schools and their communities. The focus of this Result Area is both on the physical\nschool infrastructure and on the softer environmental factors that create a school climate that is\nconducive for learning, such as peer and teacher modes of communication and school values.\n\n\n37. The third Result Area is **_a reformed student assessment and certification system_** that will focus\non strengthening the MOE’s ability to measure and monitor student learning at all grade levels and to\nbridge the gap between learning and certification. This notably includes the reform of _Tawjihi_ and the\ninstitutionalization of an early grade diagnostic learning assessment.\n\n\n38. The fourth Result Area is **_strengthened education system_** **_management_** by focusing on\nsupporting MOE and strengthening its capacity to manage an increasing number of schools and\nstudents, notably due to the expansion of early childhood education and to the enrollment of a large\nnumber of refugee children in Jordanian schools. The focus of this Result Area is to provide and\nenhance the tools and resources available to the MOE for decision making and implementation. These\ntools include information systems such as the operationalization of the GIS, which will allow the MOE\nto map school construction, expansion, and rehabilitation needs, and the strengthening of the existing\nOpenEMIS to allow MOE to analyze and make use of disaggregated and gender‐sensitive data for\ndecision making. This Result Area will also support the MOE in securing budget additionality to the\nsector in an efficient and effective manner to ensure that resources are available for undertaking the\nnecessary reforms.\n\n\n19 In an effort to shed light on gender dynamics in the education sector in Jordan, the impact evaluation will assess\nheterogeneous effects", "output": {"entities": {"named_data": ["OpenEMIS"], "descriptive_data": [], "vague_data": ["disaggregated and gender‐sensitive data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000041", "page": 18, "chunk": 1, "title": "Jordan - Education Reform Support Program-for-Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/731311512702123714/pdf/Jordan-Educ-Reform-121282-JO-PAD-11142017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "OpenEMIS", "label": "NAMED_DATA", "score": 0.5259324312210083, "start": 1667, "end": 1675, "probe_score": 0.0023, "gold": "DATA_MENTION", "gold_tier": "flip"}, {"text": "disaggregated and gender‐sensitive data", "label": "VAGUE_DATA", "score": 0.6310058236122131, "start": 1716, "end": 1755, "probe_score": 0.303, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " (say insider\n\n\ntrading pursued by the stock exchange requires the backing of the sanctions of an SEC).\n\n\nAn important corporate governance mechanism is monitoring by banks, but the\n\n\ndevelopment of bank lending and monitoring obviously relies on the effectiveness of the\n\n\nregulatory framework and supervision, in addition to the other institutions for public\n\n\nenforcement allowing collateral to be collected.\n\n\n26", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002670", "page": 25, "chunk": 1, "title": "wps3409", "pdf_url": "https://local/prwp/wps3409.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ":** OBA will finance appointing an independent IVA to perform semi-annual\nverification confirming the scores achieved for each of the indicators, based on a review of technical\nscorecards and sample on-site verification of the service provided. The IVA will review the MIS records to\ncheck that scores have been calculated correctly. Acceptable verification will trigger the payment of the OBA\ngrant directly to the Designated OBA account. If output meets or exceeds the target set for each period, the\nfull subsidy allocated (100%) for that indicator is disbursed. If performance is above the minimum\nperformance level, but below the target level, prorated subsidies are disbursed.\n\n**Accounting system and Reporting:** Project accounts will be maintained on a cash basis of accounting. The\ncurrent accounting system (Bisan Enterprise) at the JSC-H&B will be used to account for the proposed\n\n\n52", "output": {"entities": {"named_data": [], "descriptive_data": ["MIS records"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000056", "page": 51, "chunk": 1, "title": "Middle East and North Africa - Output-Based Aid Pilot Solid Waste Management Project", "pdf_url": "http://documents1.worldbank.org/curated/en/388311468275943106/pdf/84657-PAD-P132268-Project-Commitment-Paper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "MIS records", "label": "DESCRIPTIVE_DATA", "score": 0.709824800491333, "start": 269, "end": 280, "probe_score": 0.1296, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "3\n\n\n**2. Project development objective** (see Annex 1)\n\nThe objective of the project is to enhance the quality of education and to increase enrollment in\nprimary schools.\n\n\n**3. Key performance indicators:** (see Annex 1)\n\nThe key performance indicator is an increased number of students enrolled in grades 1-9, especially\namong girls.\n\n\nB. **STRATEGIC CONTEXT**\n\n\n**1. Sector-related Country Assistance Strategy (CAS) goal supported by the project** (see Annex 1)\n\n\n**Document number:** P 7403 DJI **Date of latest CAS discussion:** (scheduled for) 12/19/00\n\nThe CAS has been prepared in the context of the country's economic difficulties and deepening\npoverty. Despite Djibouti's relatively high nominal per capita income (US$790 versus an average of\nUS$510 for Sub-Saharan Africa, and US$100 for Ethiopia), Djibouti has one of the poorest social\nindicators in the world (poverty, illiteracy, maternal and infant mortality, and morbidity), according to\nthe UNDP Human Development Index, ranking 157th among 174 countries.\n\n\nThe Republic of Djibouti has very few natural resources and the economy is mainly dependent on the\nport, external financial assistance, the French military and associated services. However, with the\n\ndecreased amount of external assistance, and deepening structural problems, the country has suffered\neconomic stagnation over the past decade and a half. As a result, per capita Gross Domestic Product\n(GDP) declined by 50% in real terms since 1985. The switch of Ethiopia's transit traffic from Assab in\nEritrea to Djibouti in mid-1998 and the consequent four-fold increase in port traffic has opened new,\nas yet not fully exploited, opportunities for investment and growth. Djibouti's open economic policies\nand relative stability, characterized by a liberal trade policy and exchange system, which operates free\n\nof capital or", "output": {"entities": {"named_data": ["UNDP Human Development Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011794", "page": 6, "chunk": 0, "title": "Uganda - Industrial Rehabilitation Project", "pdf_url": "https://documents.worldbank.org/curated/en/358481468110934129/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNDP Human Development Index", "label": "NAMED_DATA", "score": 0.8519672155380249, "start": 959, "end": 987, "probe_score": 0.9988, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "The World Bank\n\n\nPercent of OVC payments disbursed to\npayment service providers on time\n\n\n\n\n\nReport No: ISR13091\n\n\n\n<u>31-Dec-2016</u>\n\n\n\n\n|Col1|Col2|Comments|Col4|Revised during Additional<br>Financing. Will contribute to<br>overall NSNP indicators.|\n|---|---|---|---|---|\n||Percentage|Value|26.00|26.00|\n||Percentage|Date|30-Jun-2013|03-Sep-2013|\n||Percentage|Comments||Revised during Additional<br>Financing. Will contribute to<br>overall NSNP indicators.|\n\n\n\n**<u>Data on Financial Performance (as of 04-Nov-2013)</u>**\n\n\n**<u>Financial Agreement(s) Key Dates</u>**\n\n|Project|Ln/Cr/Tf|Status|Approval Date|Signing Date|Effectiveness Date|Original Closing Date|Revised Closing Date|\n|---|---|---|---|---|---|---|---|\n|P111545|IDA-45530|Effective|31-Mar-2009|08-May-2009|03-Jul-2009|31-Dec-2013|31-Dec-2013|\n|P111545|IDA-53120|Not Effective|31-Oct-2013|||31-Dec-2016|31-Dec-2016|\n|P111545|TF-97272|Effective|08-Jul-2010|20-Jul-2010|20-Jul-2010|31-Dec-2013|31-Dec-2013|\n\n\n\n**<u>Disburs", "output": {"entities": {"named_data": ["Data on Financial Performance"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019986", "page": 5, "chunk": 0, "title": "Kenya - Kenya Cash Transfer for Orphans and Vulnerable Children : P111545 - Implementation Status Results Report : Sequence 10", "pdf_url": "https://documents.worldbank.org/curated/en/912351468048291793/pdf/ISR-Disclosable-P111545-01-17-2014-1389974663623.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data on Financial Performance", "label": "NAMED_DATA", "score": 0.6545556783676147, "start": 468, "end": 497, "probe_score": 0.0074, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the GER for Nigerien children is 68 per cent in primary school\nand 20 per cent in secondary school. The drop-out rate from primary to secondary levels for refugees and\nhost communities continue to be attributed to population displacement, limited prioritization of access to\neducation by the head of household, absence of school feeding programs, early marriages among girls,\nfamily reliance on manual labor undertaken by children, and the shortage of nearby secondary schools. Out\nof 147,845 UNHCR registered refugee children aged 4 to 17, 105,326 were not in school and 51.79 per cent\nof them were girls. To address these challenges, the former President has advocated for and raised funds\nto establish new boarding schools for girls across the country.\n\n\n12 R E F U G E E P O L I C Y R E V I E W F R A M E W O R K > **N I G E R**", "output": {"entities": {"named_data": ["UNHCR registered refugee children"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001471", "page": 11, "chunk": 2, "title": "Niger: Refugee Policy Review Framework Country Summary as at 30 June 2023 (Update of Summary as at 30 June 2023)", "pdf_url": "https://reliefweb.int/attachments/e5194222-6740-4475-8065-5465cd3d0666/Niger%20RPRF%20Country%20Update%202020-23.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR registered refugee children", "label": "NAMED_DATA", "score": 0.5515211224555969, "start": 494, "end": 527, "probe_score": 0.9671, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "BuildUp was also developed to counter hostile and toxic narratives against refugees online and promote digital](https://howtobuildup.org/)</u>\npeacebuilding and acceptance by host communities.\n\n\nImportantly, in relation to the COVID-19 pandemic, **89 per cent of 140 countries** reporting indicated that areas\ninhabited by refugees, internally displaced persons (IDPs) and other forcibly displaced and stateless persons were\nreached by information campaigns about COVID-19 pandemic risks.\n\n\n**~~Feedback and Response~~**\n\n\nIn 2021, important efforts were made to maintain or expand opportunities for feedback from the people that\nUNHCR worked with and for, though with higher reliance on remote methods and technology than in the past. New\ninitiatives were also initiated to address gaps in operations’ capacity to manage large unstructured quantities of\nfeedback data and investments were made in multiple communication channels to maintain proximity with people\nof concern to UNHCR. This included further development of contact centres’ referral and response mechanisms,\nincluding at the inter-agency level.\n\n\nAs a result, **65 per cent of reporting operations** have multi-channel feedback and response systems designed\nbased on consultations with communities.\n\n\n**~~Organizational Learning and Adaptation~~**\n\n\nThis is an area that requires further investment. Reporting on this aspect remained quite limited in 2021, highlighting\nthe need for strengthened knowledge-sharing to support learning and adaptation and the scale-up of innovative\napproaches. Interim findings from the ongoing longitudinal evaluation of the AGD Policy also suggested limited use\nof feedback from participatory exercises to inform adaptations of programme activities. <sup>4</sup> Moreover, siloed ways of\nworking often prevent a more systematic inclusion of feedback and learning.\n\n\n4 UNHCR, “Longitudinal evaluation of the implementation of UNHCR’s Age, Gender and Diversity Policy – Year 1 report” (2022). Available from <u>[www.un", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["feedback data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000524", "page": 7, "chunk": 1, "title": "Advancing Participation and Inclusion - Age, Gender and Diversity Accountability Report 2021", "pdf_url": "https://reliefweb.int/attachments/4b743dae-ad6e-4f50-8918-dca72b5d1afd/62b5c4e24.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "feedback data", "label": "VAGUE_DATA", "score": 0.6940112709999084, "start": 855, "end": 868, "probe_score": 0.0077, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "completed sub-projects local authorities provide\nconform to ministry standards, resources and staff to operate\ndesigns and norms. and maintain facilities (e.g.\nprovision of teachers and\n\ntextbooks in the case of\nprimary schools);\n\n\nl(b) Targeted communities are lb. 1 At <sup>least 90%</sup> <sup>of</sup> - Beneficiary/ impact - Sub-projects reflect\nempowered to carry out projects are assessed as assessments and other beneficiary needs and\npriority investments. successful by communities evaluation reports improved access to social and\n(achieve rmnimum expected economic services;\noutputs and\noutcomes/imnpacts).\n\n                                     - Supervision missions                                     - PPA methodology is\nlb.2 All supported                  - Beneficiary Assessments internalized by NaCSA and\ncommunities have conducted                - NSAP quarterly progress partners;\nparticipatory needs reports\nassessments and project                 - Participatory M&E results\nidentification using PPA\napproach.                 - Continuous social                 - Capacity building efforts\nI assessment process provided and/or coordinated\nlb.3 100% of communities                  - Participatory M&E results by NaCSA are appropriate and\nhave project management effective;\nstructures in place and trained\ncommunity members.\n\n**2.** Pilot and Special 2a.1 100 km. of feeder roads - Supervision <sup>missions;</sup> - NaCSA's commitment to\n\n**Programs in** Newly rehabilitated. - NSAP quarterly reports; pilot both programs remains\n**Accessible** **Areas** - Annual technical audits; strong\n2a.2 800,000 person days of                  - NaCSA M&E data\n**2(a)** **Rural Public Works** temporary employment\n**Program:** created.\n\nInfrastructure constructed 2a.3 250,000 \"woman days\" of\nand/or upgraded using labor temporary employment\nintensive techniques. created.\n\n\n2a.4 At mid-term review the\ncost per day", "output": {"entities": {"named_data": ["NaCSA M&E data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010819", "page": 30, "chunk": 0, "title": "Uganda - Cotton Subsector Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/292691468765338093/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NaCSA M&E data", "label": "NAMED_DATA", "score": 0.9113216400146484, "start": 1658, "end": 1672, "probe_score": 0.7359, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "16\n\n\naddressed the Donors Roundtable and committed to increase Government resources to education to\nover 25% of the budget and noted that the government viewed education as the main source of future\ngrowth in Djibouti.\n\n\n**5. Value added of Bank support in this project**\n\nIDA has been supporting the national consensus building process through the National Education\nForum. The proposed project will help demonstrate that a consensus building approach that involves\n\nall elements of civil society is effective and produces results. In addition the use of an APL\ndemonstrates the long-term commitment by IDA to assist the Government in its strategic goal of\nreaching full enrollment in basic education. It is also hoped that the use of the IDA credit will further\ndecrease the construction unit cost (as IDA is supporting the use of local construction materials which\nshould be cheaper), help develop more cost-effective classroom designs, and provide the environment\nwith a more efficient procurement process.\n\n\n**E. SUMMARY PROJECT ANALYSIS** (Detailed assessments are in the project file, see Annex 8)\n\n\n**1. Economic (see Annex 4)**\n\n\nOther (specify) NPV=US$ million; ERR = ** % (see Annex 4)\n\n\n_** ERR = Over 11% based on system efficiency gains alone without allowing for development_\n_benefits, public goods nature of education and poverty reduction benefits._\n\n\nDjibouti's main resource base is its population and in order to achieve sustained development, the\ncountry needs to improve the quality of its human resource base. Quality starts with improved basic\neducation and school enrollments. In addition, the issue of equity arises. According to the household\nexpenditure survey data, in urban areas, the net enrollment rate (NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey", "output": {"entities": {"named_data": [], "descriptive_data": ["household\nexpenditure survey data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000093", "page": 19, "chunk": 0, "title": "Tajikistan - Education Reform Project (LIL)", "pdf_url": "http://documents1.worldbank.org/curated/en/555901468777299385/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household\nexpenditure survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8924797177314758, "start": 1661, "end": 1694, "probe_score": 0.9403, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " among\npersons of concern in urban accommodations (CRS,\n2017; CRS et al., 2016).\n\n\nAvailable PDMs do not capture food security\nindicators <sup>14</sup> [^14: The GCA PDM collects coping strategies, both general and food-related.] and findings presented in reports are\nnot disaggregated by food items. Furthermore, PDM\nreports include “unmet” or “unsatisfied” food and\n\n\n\nother needs, with food being the main, recurrent\n“unmet” need, together with clothing, transport,\nhealth and other needs (in no specific order) (Mercy\nCorps Greece, 2017; IRC Greece, 2017; CRS, 2017).\nHowever, since reports do not elaborate whether\n“unmet” refers to quantity, availability, or specific\nfood items, little can be concluded (on the basis of\nexisting evidence) on food security outcomes of\nmultipurpose cash transfers in this context, or the\nactual food and nutrition gap.\n\n\nIn line with PDM findings, male and female\ninterviewed unanimously stated that the majority\nof the multipurpose cash transfer is spent on food.\nIn addition, there were common complaints related\nto the inability to satisfy food needs for the whole\nmonth. Most indicated the ability to do so only for\napproximately 20 days a month. In turn, a range\nof negative strategies appeared to be deployed\nby FGD participants. These included reducing\nquality and quantity of food among adults to feed\nchildren, eating animal protein once a month or\nless, reducing purchases of milk and baby formulas\n(often accompanied by troubling feelings of\nbabies and toddlers growing up without necessary\nnutrients), borrowing from others, <sup>15</sup> [^15: PoCs who do not receive remittances borrow from those who do and pay back when cash is disbursed the following month.] and sacrificing\nneeds in other areas.\n\n\nThe above negative coping strategies were\nreported by all but appeared to be especially\npronounced among persons of concern living\nin suburban Peania. Male and female persons\nof concern spoke animatedly and at", "output": {"entities": {"named_data": ["GCA PDM"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000390", "page": 15, "chunk": 1, "title": "Greece Case Study: Multi-purpose Cash and Sectoral Outcomes", "pdf_url": "https://reliefweb.int/attachments/33b69c07-e2c4-31fe-bb36-4bf71fc2edba/5b2cfa1f7.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "GCA PDM", "label": "NAMED_DATA", "score": 0.5246396660804749, "start": 162, "end": 169, "probe_score": 0.7939, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Figure 11. Children in wealthier households have been more likely to be engaged in more interactive\neducational activities than poorer ones\n_Interactive distance learning by country and quintile_\n\n\nQ1 Q2 Q3 Q4 Q5\n\n\n100\n\n\n80\n\n\n60\n\n\n40\n\n\n20\n\n\n0\n\n\nNote: Modes of interactive distance learning include mobile apps, online or in-person meetings/sessions with a teacher or\ntutor, or other online learning platforms. 95% confidence intervals for difference from Q1 are shown (rather than from zero).\nThe pooled regression includes country and period fixed effects. Education data are only available for Round 4 in Myanmar\nand Round 2 and 4 in Indonesia. Source: HFPS\n\n###### 5. Prospects for inclusive recovery\n\n\nThis paper presents evidence from the High Frequency Phone Surveys (HFPS) indicative of the risk of rising\ninequality both in the short-and long-terms across a selected set of EAP countries.\n\nUnlike in developed countries, work stoppages and labor income have been relatively widespread at times\nof economic closure and downturn, although there is some evidence that the top 20 have been able shield\nthemselves more than workers at the bottom of the distribution when economic activity resumed. The data\non potentially harmful coping mechanisms, food insecurity, and distance learning suggest that the impacts\ncould be long lasting, suggesting that the recovery may be uneven.\n\nThese results from high-frequency survey data, should be taken as indicative of trends, in the absence of\nofficial household and labor force surveys. The HFPS, while timely and informative for looking at how\nhouseholds have weathered during the pandemic on a number of dimensions, is not without limitations.\nAs mentioned in the paper, limited numbers of survey rounds and a respondent sample can only provide a\npartial (and imperfect) picture of the impacts. In addition, the rapid nature of the phone surveys means\nthat the questionnaires may lack the level of detail necessary to look at precise mechanisms of the\npandemic’s economic impact on workers", "output": {"entities": {"named_data": ["High Frequency Phone Surveys", "HFPS"], "descriptive_data": ["high-frequency survey data", "household and labor force surveys"], "vague_data": ["Education data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001702", "page": 27, "chunk": 0, "title": "inequality under covid 19 taking stock of high frequency data for east asia and the pacific", "pdf_url": "https://local/prwp/inequality-under-covid-19-taking-stock-of-high-frequency-data-for-east-asia-and-the-pacific.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Education data", "label": "VAGUE_DATA", "score": 0.6250866651535034, "start": 558, "end": 572, "probe_score": 0.9877, "gold": "NON_MENTION", "gold_tier": "human-final"}, {"text": "High Frequency Phone Surveys", "label": "NAMED_DATA", "score": 0.8866679668426514, "start": 744, "end": 772, "probe_score": 0.9879, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "high-frequency survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8275673985481262, "start": 1403, "end": 1429, "probe_score": 0.8991, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "household and labor force surveys", "label": "DESCRIPTIVE_DATA", "score": 0.743798553943634, "start": 1499, "end": 1532, "probe_score": 0.7044, "gold": "DATA_MENTION", "gold_tier": "flip"}, {"text": "HFPS", "label": "NAMED_DATA", "score": 0.5285001993179321, "start": 1538, "end": 1542, "probe_score": 0.7655, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "In early July, I travelled to the Kutupalong refugee\nsettlement in Bangladesh, which has become\nhome to hundreds of thousands of Rohingya\nrefugees who have fled horrific violence in\nMyanmar. In a one-room learning centre, with the\nmonsoon rains hammering on the roof, I saw girls\nand boys learning the basics of reading, writing\nand maths for just two hours a day, before another\ngroup took their place, and then another.\n\n\nIt was heart-rending to watch this faint semblance\nof the proper schooling to which these young\nrefugees are entitled. But it also made it\nabundantly clear just how highly they value\neducation. Without it, their future, and eventually\nthe future of their communities, will be\nirrevocably damaged.\n\n\n\nHalf of the world’s refugees are children. Of the\nchildren who are of school age, more than half are\nnot getting an education – that equates to four\nmillion young minds not in school even though\nthey are bursting with potential.\n\n\nThe number of out-of-school refugee children\nhas increased by 500,000 in the last year alone.\nIf current trends continue, hundreds of thousands\nmore refugee children will be added to these\ndisturbing statistics unless urgent investment\nis made.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000854", "page": 2, "chunk": 0, "title": "Turn the Tide: Refugee Education in Crisis", "pdf_url": "https://reliefweb.int/attachments/7e39fa18-cfd3-3a7e-b2ab-968ddd206c6c/5b852f8e4.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "governments.|8|25|\n|<br>8. Number of County Value Maps prepared and submitted to Parliament.<br>|0|15|\n|<br>9. Number of people gaining access to improved water and sanitation<br>services.<br>10. Proportion of the Water Resources Authority (WRA)'s annual<br>operating costs financed through water abstraction revenues.|0 <br> <br>20 percent|<br>300,000<br> <br>70 percent|\n|<br>11. Number of poor and vulnerable households covered through<br>government-financed health insurance subsidies.|223,968<br>|1,000,000<br>|\n|<br>12. Capacity to respond to public health events and emergencies based on<br>IHR States Parties Annual Reporting Tool.|43 percent (2019)|<br>65 percent|\n|<br>13. Proportion of recurrent funding for universities that is performance-<br>based.<br>~~. ~~<br>|0 percent|30 percent|\n\n\n\nPage 4", "output": {"entities": {"named_data": ["IHR States Parties Annual Reporting Tool"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017975", "page": 6, "chunk": 1, "title": "Kenya - Accelerating Reforms for an Inclusive and Resilient Recovery Development Policy Financing", "pdf_url": "https://documents.worldbank.org/curated/en/773581623636025182/pdf/Kenya-Accelerating-Reforms-for-an-Inclusive-and-Resilient-Recovery-Development-Policy-Financing.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "IHR States Parties Annual Reporting Tool", "label": "NAMED_DATA", "score": 0.7315945625305176, "start": 598, "end": 638, "probe_score": 0.9155, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 12,692 fulfilled the eligibility criteria.\n\n\nAs explained above, and key to the integrity of the experimental design, baseline data\n\n\nwas collected prior to assigning localities to the three treatment and control groups. The\n\n\nbaseline questionnaire included simple variables on employment, assets, education, and\n\n\nhousehold characteristics.\n\n\nThe second public lottery took place in March 2016. The list of the 5,116 selected\n\n\nbeneficiaries was publicly released in each locality between July and September 2016. <sup>25</sup>\n\n\n24The baseline instrument was designed by the research team. NGO staff were trained as enumerators.\nAn independent team of experienced enumerators was hired to perform field supervision and data quality\nchecks. A double-blind data-entry process was set-up.\n\n25The lag between the second lottery and the release of the beneficiary lists was due to delays in the\n\n\n13", "output": {"entities": {"named_data": [], "descriptive_data": ["beneficiary lists"], "vague_data": ["baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000613", "page": 16, "chunk": 1, "title": "idu016356e4e01f4704759089a00b05060f249c1", "pdf_url": "https://local/prwp/idu016356e4e01f4704759089a00b05060f249c1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "baseline data", "label": "VAGUE_DATA", "score": 0.7376485466957092, "start": 119, "end": 132, "probe_score": 0.0022, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "beneficiary lists", "label": "DESCRIPTIVE_DATA", "score": 0.7350704669952393, "start": 851, "end": 868, "probe_score": 0.0042, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "br>12.48<br>5.25<br>7.00<br>**24.73**<br>5.00<br>**29.73**|\n\n\n\n**Financial Performance (2014–2022)**\n\n\n168. Projections to assess the BWE financial performance (2014–2022) are based on two main\nscenarios. The first scenario is based on a conservative revenue projection with an annual increase of\nonly 1 percent in fees and 1 percent in collection rate for the projected period. The second scenario\naims at a more aggressive collection rate of 2.5 percent a year for the same period. The result is total\nrevenue of LBP 26.5 billion for scenario 1 in year 2022 while scenario 2 reaches about LBP 35 billion\nfor the same period. In both scenarios, 2013 is considered as the baseline.\n\n\n169. Based on the above assumptions, financial projections have been prepared until 2022. <sup>55</sup> This\nanalysis is limited by the lack of audited financial statements prepared in the past. Given the fact that\nthere is no accrual accounting and no fixed assets register to calculate O&M and depreciation charges\nmore accurately, estimates used are based on available data provided by the MoEW and BWE as well\nas data provided through donor-funded technical assistance programs.\n\n\n170. In summary, for both scenarios, cost recovery of O&M would reach about 90 percent\n(excluding depreciation) in 2022 and collection rates for current year billing would reach 56 percent\nfor scenario 1 and 81 percent for scenario 2 by 2022. The different assumptions of financial scenarios\nhave been discussed with the BWE. Details on financial projections and assumptions are provided in\nthe project files.\n\n\n**Conclusion**\n\n171. The BWE revenues are currently covering about 50 percent of O&M (without depreciation).\nGiven the specific nature of the wastewater sector, this level of cost recovery", "output": {"entities": {"named_data": [], "descriptive_data": ["available data provided by the MoEW and BWE", "data provided through donor-funded technical assistance programs"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000036", "page": 52, "chunk": 4, "title": "Lebanon - Lake Qaraoun Pollution Prevention Project", "pdf_url": "http://documents1.worldbank.org/curated/en/279341468589482380/pdf/PAD860-PAD-P147854-R2016-0133-1-Box396255B-OUO-9.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "available data provided by the MoEW and BWE", "label": "DESCRIPTIVE_DATA", "score": 0.5989468693733215, "start": 1046, "end": 1089, "probe_score": 0.9831, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data provided through donor-funded technical assistance programs", "label": "DESCRIPTIVE_DATA", "score": 0.8122925758361816, "start": 1101, "end": 1165, "probe_score": 0.283, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**HASHEMITE KINGDOM OF JORDAN**\n**Education Reform Support Program‐for‐Results**\n\n\n**I.** **STRATEGIC CONTEXT**\n\n**A.** **Country Context**\n\n1. **Despite strong economic and social progress in previous decades, Jordan continues to face**\n**challenges that have been amplified by the Syrian refugee crisis.** Economic growth has slowed down\nin 2016 for the second year in a row—to an estimated 2 percent from 2.4 percent in 2015. Indicators\nof human development and living standards have stagnated since 2009, after strong improvements\nfrom 1990 to 2008. The Human Development Index (HDI), which measures long‐term progress in\nthree basic dimensions of human development (a long and healthy life, access to knowledge, and a\ndecent standard of living), has remained at 0.742 since 2008, placing Jordan in the 86 <sup>th</sup> position of 188\nin the HDI ranking. <sup>1</sup> [^1: Human Development Data (1990–2015); Human Development Report. 2016.] This situation is explained by various factors, including the effects of the Syrian\nrefugee crisis and the fallout from the 2007–2008 global financial crisis.\n\n2. **Jordan faces a significant demographic challenge with the influx of large numbers of Syrian**\n**refugees.** The Syrian refugee crisis adds to the fiscal stress and puts serious strains on the\ngovernment’s ability to provide public services, including health and education. As of August 2017,\nJordan hosts 660,582 <sup>2</sup> [^2: United Nations High Commissioner for Refugees (UNHCR). August 6, 2017.] registered Syrian refugees, of which 232,868 <sup>3</sup> [^3: Brussels Conference Paper. 2017.] are school‐aged children\nrequiring the provision of education", "output": {"entities": {"named_data": ["Human Development Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000127", "page": 8, "chunk": 0, "title": "Jordan - Education Reform Support Program-for-Results Project", "pdf_url": "http://documents1.worldbank.org/curated/en/731311512702123714/pdf/Jordan-Educ-Reform-121282-JO-PAD-11142017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Human Development Index", "label": "NAMED_DATA", "score": 0.6378366351127625, "start": 558, "end": 581, "probe_score": 0.9157, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Col1|Indicator 2.4: Teacher feedback on training and<br>certification system monitored, analyzed, and<br>included in the annual monitoring and progress<br>reports developed by ETC|Col3|No|Yes/No|No|Yes|Annually|MOE|Teacher surveys|\n|---|---|---|---|---|---|---|---|---|---|\n|Reformed<br>student<br>assessment and<br>certification<br>system<br>|Indicator 3.1: Grade 3 diagnostic test on early grade<br>reading and math implemented|7.2|No|Yes/No|No|Yes|Annually|MOE|Assessments records for a<br>sample of schools|\n|Reformed<br>student<br>assessment and<br>certification<br>system<br>|Indicator 3.2: Legal framework for the_Tawjihi_ exam<br>has been adopted so that its secondary graduation<br>and certification function is separated from its<br>function as a screening mechanism for university<br>entrance|7.4|No|Yes/No|No|Yes|Annually|MOE||\n|Reformed<br>student<br>assessment and<br>certification<br>system<br>|Indicator 3.3: Student and Teacher Feedback on first<br>phase_Tawjihi_ reform inform the", "output": {"entities": {"named_data": [], "descriptive_data": ["Teacher surveys", "Assessments records"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000041", "page": 39, "chunk": 0, "title": "Jordan - Education Reform Support Program-for-Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/731311512702123714/pdf/Jordan-Educ-Reform-121282-JO-PAD-11142017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Teacher surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8694089651107788, "start": 216, "end": 231, "probe_score": 0.7636, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Assessments records", "label": "DESCRIPTIVE_DATA", "score": 0.632613480091095, "start": 465, "end": 484, "probe_score": 0.98, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " TPM<br>report,<br>impact<br>evaluation<br>|Project monitoring,<br>TPM, impact<br>evaluation<br>|MoFP, LGB<br>|\n|Percentage of counties for which the<br>required information is uploaded to the<br>MIS in a timely manner to monitor results.|<br>Geo-referenced data on<br>subproject progress<br>uploaded in the MIS in a<br>timely manner for project<br>management to monitor<br>results.|Quarterly<br>|Project MIS,<br>quarterly<br>progress<br>report<br>|Project MIS, quarterly<br>progress monitoring<br>|MoFP, LGB, IOM<br>|\n\n\n\nPage 62 of 73", "output": {"entities": {"named_data": [], "descriptive_data": ["Geo-referenced data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000192", "page": 67, "chunk": 1, "title": "South Sudan - Second Phase of the Enhancing Community Resilience and Local Governance Project", "pdf_url": "https://documents1.worldbank.org/curated/en/543171647442225562/pdf/IBArchive-e8d67f4f-bc76-49af-9b6c-6099c748075b.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Geo-referenced data", "label": "DESCRIPTIVE_DATA", "score": 0.6720775961875916, "start": 243, "end": 262, "probe_score": 0.0038, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### The 2019 Update of the Health Equity and Financial Protection Indicators Database: An Overview\n\nAdam Wagstaff <sup>a</sup> *, Patrick Eozenou <sup>b</sup>, Sven Neelsen <sup>b</sup>, and Marc Smitz <sup>b</sup>\n\n\na Development Research Group, The World Bank, 1818 H Street, NW, Washington DC\n\n20433, USA\n\n\nb Health, Nutrition and Population Global Practice, The World Bank, 1818 H Street, NW,\n\nWashington DC 20433, USA\n\n\n**Keywords:** Health indicators; health equity; health and inequality; out-of-pocket health\nexpenditures; financial protection; health and poverty; millennium development goals; sustainable\ndevelopment goals; universal health coverage; non-communicable diseases\n\n\n**JEL codes:** I1, I3, J13", "output": {"entities": {"named_data": ["Health Equity and Financial Protection Indicators Database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002160", "page": 2, "chunk": 0, "title": "the 2019 update of the health equity and financial protection indicators database an overview", "pdf_url": "https://local/prwp/the-2019-update-of-the-health-equity-and-financial-protection-indicators-database-an-overview.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Health Equity and Financial Protection Indicators Database", "label": "NAMED_DATA", "score": 0.8881540894508362, "start": 27, "end": 85, "probe_score": 0.9942, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " in the same ways; beer and juice were luxury items with sunk costs,\nwhile the other items satisfied basic needs: _“Beer and juice is not something to be_\n_taken every day, you can just drink it when you want. Maybe every one or two_\n_weeks”_ (Interview 22, No053, July 29, 2014).\n\n|Table 1. Rank of Expenditure between Samples|Col2|\n|---|---|\n|**Rank of Item by Amount Spent (UGX), Refugee**<br>**Sample**|**Rank of Item by Amount Spent (UGX),**<br>**National Sample**|\n|1. Clothes, 5,600|1. Cloth, 4,333|\n|2. Rice, 4,200|2. Clothes, 3,833|\n|3. Cloth, 4,936|3. Rice, 3,800|\n|4. Shoes, 3,573|4. Shoes, 1,967|\n|5. Cooking Oil, 3,200|5. Cooking Oil, 1,433|\n\n\n\nThe rank of items shown in Table 1 is similar in both groups. Rice, clothes\nand cloth are the top three, while shoes and oil are at the bottom. Refugees spent\nmore on clothes and rice than education. Refugees also spent more on clothes, rice,\ncooking oil and shoes than nationals. Qualitative data will be used to uncover the\nsignificance of these differences in the next sub-section.\n\n\n12 It should be noted that schoolbooks were selected as a proxy for more general educational\ninvestments based on the free school fees and uniforms supplied by the UNHCR.\n\n\n16", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Qualitative data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001583", "page": 17, "chunk": 1, "title": "New issues in refugee research - research paper no. 280 - What difference does it make to be a refugee?: Evidence from field experiments and qualitative inquiry", "pdf_url": "https://reliefweb.int/attachments/f4fa8784-d980-3f78-bbbc-9b9a23888d0e/5857ea674.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Qualitative data", "label": "VAGUE_DATA", "score": 0.7522668242454529, "start": 939, "end": 955, "probe_score": 0.0083, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000038", "page": 62, "chunk": 2, "title": "Africa - Multi - Country HIV/AIDS Program for the Africa Region (Ethiopia and Kenya)", "pdf_url": "http://documents1.worldbank.org/curated/en/287591468768313907/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Nombre|%|\n|De 1 à 4 ans|337|9.20|353|9.63|690|18.83|\n|5 à 11 ans|469|12.80|526|14.36|995|27.16|\n|12 à 17 ans|238|6.50|202|5.51|440|12.01|\n|18 à 59 ans|767|20.93|445|12.15|1,212|33.08|\n|60 ans et Plus|212|5.79|115|3.14|327|8.92|\n|Grand Total|2,023|55.21|1,641|44.79|3664|100.00|\n\n\n\nSource: Enregistrement du 22 au 28 juillet 2010, UNHCR\n\n\n8 Voir carte en annexe\n\n3\nJAM TOGO SEPT 2010", "output": {"entities": {"named_data": ["Enregistrement du 22 au 28 juillet 2010"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001429", "page": 9, "chunk": 2, "title": "MISSION D'EVALUATION CONJOINTE-HCR-PAM: Des besoins des Nouveaux Réfugiés Ghanéens au TOGO", "pdf_url": "https://reliefweb.int/attachments/de3a446e-3437-3a7e-9f40-b36bea7eeee3/7C3DB8C9A3A25EA4492578160020FD2E-Rapport_Complet.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Enregistrement du 22 au 28 juillet 2010", "label": "NAMED_DATA", "score": 0.5753191709518433, "start": 289, "end": 328, "probe_score": 0.9994, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "output": {"entities": {"named_data": [], "descriptive_data": ["household expenditure survey data", "data from the Household Survey"], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000170", "page": 38, "chunk": 1, "title": "Albania - Water Supply Urgent Rehabilitation Project", "pdf_url": "http://documents1.worldbank.org/curated/en/949361468742522118/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household expenditure survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8699104189872742, "start": 565, "end": 598, "probe_score": 0.7323, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.5808603167533875, "start": 870, "end": 881, "probe_score": 0.1461, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from the Household Survey", "label": "DESCRIPTIVE_DATA", "score": 0.5346028804779053, "start": 1978, "end": 2008, "probe_score": 0.1121, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "all these countries appear to have been affected by the global financial crisis of 2008. FDI inflows\n\n\ninto other Middle Eastern countries are the most erratic over the period. A comparison of the\n\n\nleft and right side panels of Figure 1 suggests that countries with the largest increases in political\n\n\ninstability also suffered substantial reductions in greenfield FDI inflows.\n\n\n_2.3 Economic Variables_\n\n\nWhen examining the relationship between investment and political instability it is obviously\n\n\nimportant to account for economic factors. Unfortunately, high frequency data on economic\n\n\nvariables for MENA countries are scarce. We draw on two sources to compile quarterly data on\n\n\ninflation, industrial production, and exchange rates. Inflation, measured as the quarterly change in\n\n\nthe consumer price index, was derived from national statistical offices, and in some cases the\n\n\nEconomist Intelligence Unit database (EIU). The high-frequency database of the Middle East\n\n\nand North Africa Department of the International Monetary Fund (IMF) was the source for the\n\n\nindustrial production and nominal exchange rate data. In those cases when no industrial\n\n\nproduction data are available, we used quarterly export data from the IMF Direction of Trade\n\n\nStatistics database. Descriptive statistics of the variables included in the models are provided in\n\n\nTable A3 in the Appendix A3.\n\n\n**3. Estimation and Results**\n\n\n_3.1 Estimation Issues_\n\n\nOne challenge in isolating the effect of political instability on greenfield FDI is that political\n\n\ninstability and deteriorating macroeconomic performance often go hand in hand and may in fact\n\n\naggravate each other. Moreover, there is a possibility of reverse causality, with reductions in\n\n\ngreenfield FDI exacerbating political unrest. One solution to this problem would be to\n\n\n13", "output": {"entities": {"named_data": ["Economist Intelligence Unit database", "IMF Direction of Trade\n\n\nStatistics database"], "descriptive_data": ["industrial\n\n\nproduction data", "quarterly export data"], "vague_data": ["high frequency data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005841", "page": 14, "chunk": 0, "title": "wps6716", "pdf_url": "https://local/prwp/wps6716.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "high frequency data", "label": "VAGUE_DATA", "score": 0.73048996925354, "start": 562, "end": 581, "probe_score": 0.7531, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Economist Intelligence Unit database", "label": "NAMED_DATA", "score": 0.9172263145446777, "start": 891, "end": 927, "probe_score": 0.9956, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "industrial\n\n\nproduction data", "label": "DESCRIPTIVE_DATA", "score": 0.5359459519386292, "start": 1155, "end": 1183, "probe_score": 0.9876, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "quarterly export data", "label": "DESCRIPTIVE_DATA", "score": 0.5497117638587952, "start": 1207, "end": 1228, "probe_score": 0.9802, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "IMF Direction of Trade\n\n\nStatistics database", "label": "NAMED_DATA", "score": 0.9044915437698364, "start": 1238, "end": 1282, "probe_score": 0.9937, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "DJIBOUTI\nSchool Access and Improvement Program\n\n\n**Project Appraisal Document**\n\n\nMiddle East and North Africa Region\n\nMNSHD\n\n\n\nDate: November 17, 2000 Team Leader: Qaiser M. Khan\n\n\n\nCountry Director: Inder K. Sud Sector Director: Baudouy\nProject **ID:** P044585 Sector(s): EP - Primary Education, ES - Secondary\n\n\n\n. Education\nLending Instrument: Adaptable Program Loan <sup>(APL)</sup> Theme(s): Education; Gender and development\n\n\n\nPoverty Targeted Intervention: N\n\n\n\nProgram Fin ncing Data\n\n\n\nEstimated\nAPL Indicative Financing Plan Implementation Period (Bank FY) Borrower\n\n\n\n**IBRD** Others **Total** **COMMITMENT** **Closing**\n**US$** m % US$ m US$ m Date Date\nAPL 1 10.00 75.8 3.20 13.20 03/31/2001 06/30/2005 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\n________________ Education\n\n\n\nAPL 2 10.0 65.8 5.20 15.20 07/01/2005 06/30/2008 Republic of\n\n\n\nLoan/ Credit Djibouti\n\n\n\nCredit Ministry of\n\n\n\ni_________ ________________ Education\n\n\n\nAPL 3 10.00 41.0 14.40 24.40 07/01/2008 06/30/2011 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\nEducation\n\n\n\nTotal 30.00 22.80 52.80\nProject Financing Data Credit\nFor Loans/Credits/Others: Amount (US$m): 10.0\n\n\n\nProposed Terms: Standard Credit\n\n\n\nGrace period (years): 10 Years to maturity: 40\nCommitment fee: 0.50% (0% for FY01) Service charge: 0.75", "output": {"entities": {"named_data": ["Project Financing Data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000029", "page": 4, "chunk": 0, "title": "West Bank and Gaza - Health System Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/221361468779450522/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Project Financing Data", "label": "NAMED_DATA", "score": 0.5102046728134155, "start": 1106, "end": 1128, "probe_score": 0.1169, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda: Investment for Industrial Transformation and Employment (P171607)\n\n\nrefugee settlements located across 13 districts (including Kampala). About 57 percent of refugees are located in\nthe West Nile RHDs, 37 percent are located across six RHDs in the Southwest, and six percent are located in\nKampala. Refugees account for a significant share of the total population in some districts as shown in Table 1,\nand more than 45 percent in two West Nile districts. South Sudanese (61.7 percent) make up the largest refugee\npopulation followed by refugees from the Democratic Republic of Congo (29.3 percent); Burundi (3.4 percent);\nSomalia (2.9 percent); and others (1.7 percent) from Ethiopia, Eritrea, Rwanda, and Sudan. About 52 percent of\nrefugees are female, and 81 percent are women and children. Overall, one in two refugee households is female\nheaded, compared to less than one in three host households.\n\n\n**Table 1. Refugee and Host Population in Uganda** <sup>**10**</sup> [^10: Uganda Comprehensive Refugee Response Portal (https://data2.unhcr.org/en/country/uga), September 20, 2020.]\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Population|Col3|Refugee<br>% of Total|Number of Firms11|Col6|\n|---|---|---|---|---|---|\n||**Refugee**|**Ugandan Host**<br>**Community**|**Ugandan Host**<br>**Community**|**Refugee**|**Host**|\n|<br>**Northern West RHDs**<br>|<br>**Northern West RHDs**<br>|<br>**Northern West RHDs*", "output": {"entities": {"named_data": ["Uganda Comprehensive Refugee Response Portal"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000021", "page": 15, "chunk": 0, "title": "Uganda - Investment for Industrial Transformation and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/469061641926083502/pdf/Uganda-Investment-for-Industrial-Transformation-and-Employment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Uganda Comprehensive Refugee Response Portal", "label": "NAMED_DATA", "score": 0.7236497402191162, "start": 1006, "end": 1050, "probe_score": 0.9994, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "#### Figure 4. Demographics\n\nA. Impact of 1 percentage point higher\nworking- age population share on per\ncapita GDP growth\n\nPercent\n\n3\n\n\n2\n\n\n1\n\n\n\n70\n\n\n65\n\n\n60\n\n\n55\n\n\n\nB. Working-age population\n\n\nPercent of total population\n\n\n\n\n\n0\n\n\n\nAiyar and\n\nMody\n(2011)\n\n\n\nBloom and\nWilliamson\n\n(1998)\n\n\n\nBloom and\n\nCanning\n\n(2004)\n\n\n\nBloom et\nal. (2000)\n\n\n\nAhmed\nand Cruz\n\n(2016)\n\n\n\nC. Working-age population D. Potential growth\n\n\n\nPercent\n\n\n\n\n\nPercent\n\n\n\n2.8\n2.6\n2.4\n2.2\n2.0\n1.8\n\n\n\n75\n\n70\n\n65\n\n60\n\n55\n\n50\n\n\n\n\n\nBaseline Demographic trends Other factors\n\n5.6\n5.2\n4.8\n4.4\n4.0\n3.6\n\n\n\nSources: United Nations World Population Prospects: The 2022 Revision. World Bank.\nNote: AEs = advanced economies; EMDEs = emerging market and developing economies; EAP = East\nAsia and Pacific, ECA = Europe and Central Asia, LAC = Latin America and the Caribbean, MNA =\nMiddle East and North Africa, SAR = South Asia, and SSA = Sub-Saharan Africa.\nA. The sample of each study differs. Aiyar and Mody (2011): Indian states,1961-2001; Bloom and Williamson\n(1998): 78 countries, 1965-90; Bloom and Canning (2004): over 70 countries, 1965-95; Bloom et al. (2000):\n70 countries, 1965-90; Amer and Cruz (2016): 160 countries, 1960-2010.\nB.C. Population weighted averages. The working-age population is defined as people aged 15-64 years.\nD. GDP-weighted arithmetic averages. Derived using production function-based potential growth. “Other\nfactors” reflects declining population growth, convergence-related productivity growth, policy changes,\ncohort effects, and a slowdown in investment growth relative to output growth. “Factor” reflects the\npercentage-point changes between the averages of 2011-", "output": {"entities": {"named_data": ["United Nations World Population Prospects"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000635", "page": 28, "chunk": 0, "title": "idu01dc8e11c0d0ab047d80b7a60e220b64efa9d", "pdf_url": "https://local/prwp/idu01dc8e11c0d0ab047d80b7a60e220b64efa9d.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "United Nations World Population Prospects", "label": "NAMED_DATA", "score": 0.7755827307701111, "start": 577, "end": 618, "probe_score": 0.9999, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "000 inhabitants than the\n“EU-27” as a whole. The 42 **European** countries included in Table 1 received on average 1.8\nasylum-seekers per 1,000 inhabitants whereas the corresponding figure for **North America** and\n**Australia/New Zealand** was 1.2 and 0.8 respectively. **Japan** and **Republic of Korea** received\n0.03 asylum-seekers per 1,000 inhabitants given the high national population (more than 176\nmillion together) and comparatively low number of asylum-seekers.\n\n\n## **V. ORIGIN OF ASYLUM-SEEKERS**\n\nthe competent authorities of the host country. This\n\nasylum data to UNHCR.\n\nclaim in 2007. Half of all asylum applications were\n\nall claims), followed by **Europe** (15%), **Latin**\n**America and the Caribbean** (12%), and **North America** (1%). <sup>10</sup> [^10: The geographical regions used are those of the UN Statistics Division (http://unstats.un.org/unsd/methods/m49/m49.htm).] The country of origin of 4,700\nasylum-seekers, however, was unknown.\n\nOut of the 40 main asylum-seeker nationalities, 17 registered a rise during 2007. Among the\nmajor source countries of asylum-seekers, significant increases were registered by: **Iraq** (+98%),\n**Pakistan** (+87%), the **Syrian Arab Republic** (+47%), **Somalia** (+43%), and **Mexico** (+41%).\nConversely, out of the 23 nationalities which recorded a decrease in 2007 as compared to 2006,\nseven registered a drop of more than 20 per cent. This included asylum applicants originating\nfrom **Azerbaijan** (-41%), *", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["asylum data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001058", "page": 7, "chunk": 1, "title": "Asylum levels and trends in industrialized countries, 2007", "pdf_url": "https://reliefweb.int/attachments/a0f955c8-b460-3603-b1cc-8d2ccc064a5f/BF4CF8525B21A81049257410001BC61A-Full_Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "asylum data", "label": "VAGUE_DATA", "score": 0.6354289650917053, "start": 565, "end": 576, "probe_score": 0.9547, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "The field observations carried out in nine camps show\nthat latrines were away from the tube wells and just in\nfront of or beside the shelters. Due to the lack of nearby\nwater points, the toilets remained dirty all the time. Not\nevery camp or block had gender-segregated or disability\nand age friendly toilet facilities. Many toilets were broken\nand did not have a lock inside. While some of the toilets\nwere on the top of the hill with solar streetlights, others\nwere at the bottom of the hill and situated away from\nthe light. The toilets did not have adequate privacy and\nlacked facilities for menstrual hygiene. Only a few toilets\nwere designated for older people and people living with\ndisabilities. Most children under five years use open\ndefecation around the camps, which is a serious public\nhealth concern.\n\n\nThe 2020 JRP <sup>100</sup> shows that 32% of Rohingya refugee\nhouseholds experience problems accessing or using\nlatrines due to their low coverage, while 14% experience\nproblems due to the distance between the latrines and\ntheir shelters. Similarly, the 2019 UNICEF gender, GBV\nand inclusion audit of the WASH sector and capacity\ndevelopment assessment <sup>101</sup> shows that a lack of gender\nsegregation of latrines made women and girls have to\n\n\n\nqueue together with men to use them, thus affecting\nthe access of women and girls to WASH facilities. The\nSphere Handbook for Humanitarian Charter and Minimum\nStandards in Humanitarian Response <sup>102</sup> suggests that one\ntoilet for 20 persons (shared family) is the standard to be\npursued in medium to long-term situations. Currently, 100\nto 150 people use one toilet in the camps. As a result, the\ntoilets get flooded due to overuse and a lack of frequent\ndesludging.\n\n\nRohingya and host community women and girls use\nvarious strategies to cope with unsafe latrine facilities\n(Figures 17-18). The HH survey shows that", "output": {"entities": {"named_data": ["2020 JRP"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000732", "page": 41, "chunk": 0, "title": "An intersectional analysis of gender amongst Rohingya refugees and host communities in Cox’s Bazar, Bangladesh", "pdf_url": "https://reliefweb.int/attachments/6b69cc90-e03e-3419-8199-a82b4a40691f/Coxs-Bazar-Gender-and-Intersectionality-Analysis-report_2020.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2020 JRP", "label": "NAMED_DATA", "score": 0.8362260460853577, "start": 821, "end": 829, "probe_score": 0.999, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**</sup> decreased by\n36,300 persons compared to the start of the year,\nmainly as a result of a revision in the number in\nthe Bolivarian Republic of Venezuela. In contrast,\nfigures for both Pakistan and Ukraine increased\ndramatically. In Pakistan, some 283,500 individuals fled to Afghanistan as armed conflict in their\ncountry unfolded during the year; likewise, fighting in eastern Ukraine not only displaced more\nthan 800,000 people within the country but also\nled to 271,200 persons applying for refugee status\nor temporary asylum in the Russian Federation.\n\n\nDeveloping Countries\nAre Shouldering the Responsibility\n\n\nDeveloping regions <sup>**(19)**</sup> have continued to receive\nmillions of new refugees – and, during the past few\nyears, in increasing numbers. Two decades ago,\ndeveloping regions were hosting about 70 per cent\nof the world’s refugees. By the end of 2014, this\nproportion had risen to 86 per cent – at 12.4 million persons, the highest figure in more than two\ndecades. The Least Developed Countries <sup>**(20)**</sup> alone\nprovided asylum to 3.6 million refugees or 25 per\ncent of the global total.\n\nComparing the size of a refugee population to\nthe Gross Domestic Product (Purchasing Power\n\n\n\n**(20)** Ibid.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n**(16)** Figures for Iraqi refugees in the Syrian Arab Republic and the Islamic\n\nRepublic of Iran are Government estimates.\n\n\n\n**(17)** The Government of Jordan estimates the number of Iraqis in the country at\n\n400,000 individuals at the end of March 2015. This includes refugees and\nother categories of Iraqis.\n\n\n\n**(18)** This figure includes refugees as well persons in a refugee-like situation in\n\nEcuador, the Bolivarian Republic of Venezuela, Costa Rica, and Panama.\n\n\n\n**(19)** [See https://un", "output": {"entities": {"named_data": [], "descriptive_data": ["Figures for Iraqi refugees"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000809", "page": 14, "chunk": 1, "title": "UNHCR Global Trends: Forced Displacement in 2014", "pdf_url": "https://reliefweb.int/attachments/770fdfd8-d5c3-3438-a25c-1f02a52df5b9/556725e69.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Figures for Iraqi refugees", "label": "DESCRIPTIVE_DATA", "score": 0.5030471086502075, "start": 1274, "end": 1300, "probe_score": 0.8499, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nconsiderable degree of socio-economic integration, and are largely self-sufficient. In a\ncountry where half the population is under the age of 15, the vast majority of\nCongolese refugees have never seen their homeland. They speak Portuguese like the\nlocal population, while only the older refugees know the French they spoke in the\nDRC.\n\n\nIn 2005 the UNHCR reported that “positive signs came from the authorities for the\nprovision of legally secure local integration possibilities in the form of a permanent\nresidence permit under the Immigration Act or naturalization under the Nationality\nAct.” <sup>12</sup> On 15 February 2006, Angolan authorities made an announcement of their\ncommitment to finalize a local integration policy for the Congolese. They have\nindicated the possibility of residency rights as a prelude to full legal local integration\nfor the 90% of refugees who have indicated they would choose to remain indefinitely\nin Angola. <sup>13</sup>\n\n\n_Côte d’Ivoire_\n\n\nLiberians started fleeing to Côte d’Ivoire in 1989 when civil war in their home\ncountry. At the height of the war, over 400,000 Liberians had fled to Côte d’Ivoire\nand renewed violent conflict caused further population displacement in 1998 and\n\n\n11 UNHCR, (2007). _Protecting Refugees and the Role of UNHCR_ . (UNHCR, Geneva), p. 13.\n12 UNHCR, (2006). _Angola 2005 Annual Protection Report_ . (UNHCR: Geneva), p. 4.\n13 MINARS Survey, 2005. See UNHCR, (2006). _Angola 2005 Annual Protection Report_ . (UNHCR:\nGeneva).\n\n6", "output": {"entities": {"named_data": ["MINARS Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001236", "page": 7, "chunk": 1, "title": "Local Integration: An Under-Reported Solution to Protracted Refugee Situations", "pdf_url": "https://reliefweb.int/attachments/bdc56f6b-5df3-3f49-aa3c-1e3b3f0e0d58/ACE1406068C7302FC1257497004BBAC9-unhcr-jun2008.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "MINARS Survey", "label": "NAMED_DATA", "score": 0.8343148827552795, "start": 1401, "end": 1414, "probe_score": 0.8158, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ",” 2018.\n\n\nDelius, Antonia, and Olivier Sterck. “Cash Transfers and Micro-Enterprise Performance: Theory and Quasi\nExperimental Evidence from Kenya.” Department of International Development, 2020.\nhttp://dx.doi.org/10.2139/ssrn.3591146.\n\n\nGlobal Alliance for Clean Cookstoves. “Gender-Based Violence in Humanitarian Settings: Cookstoves and\n\nFuels.” Global Alliance for Clean Cookstoves, 2016. https://www.cleancookingalliance.org/binarydata/RESOURCE/file/000/000/478-1.pdf.\n\n\nHorrace, William, and Ronald Oaxaca. “Results on the Bias and Inconsistency of Ordinary Least Squares for\n\nthe Linear Probability Mode.” _Economics_ _-_ _Faculty_ _Scholarship_ 10 (2005).\nhttps://surface.syr.edu/cgi/viewcontent.cgi?article=1138&context=ecn.\n\n\nIFC, International Finance Corporation. “DHS Analytical Studies. Using Household Survey Data to Explore the\n\nEffects of Improved Housing Conditions on Malaria Infection in Children in Sub-Saharan Africa.” DHS\nAnalytical Studies No. 61. USA: IFC, 2016. https://dhsprogram.com/pubs/pdf/AS61/AS61.pdf.\n\n\n———. “Kakuma as a Marketplace. A Consumer and Market Study of a Refugee Camp and Town in Northwest\n\nKenya.” Washington DC: International Finance Corporation, 2018.\nhttps://www.ifc.org/wps/wcm/connect/0f3e93fb-35dc-4a80-a9556a7028d0f77f/20180427_Kakuma-as-a-Marketplace_v1.pdf?MOD=AJPERES&CVID", "output": {"entities": {"named_data": [], "descriptive_data": ["Household Survey Data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000594", "page": 13, "chunk": 1, "title": "Understanding the Socioeconomic Differences of Urban and Camp-Based Refugees in Kenya", "pdf_url": "https://reliefweb.int/attachments/5771bd73-902d-38cb-b9cc-5663dee46116/Understanding-the-Socioeconomic-Differences-of-Urban-and-Camp-Based-Refugees-in-Kenya.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Household Survey Data", "label": "DESCRIPTIVE_DATA", "score": 0.5896064639091492, "start": 808, "end": 829, "probe_score": 0.118, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "# **AFGHANISTAN PROTECTION ANALYSIS UPDATE – Q4**\n\n\n\n\n\n\n\n\n\n\n\nSource: IOM\n\n## **LIMITATIONS**\n\nIn quarter 4, many partners including those involved with protection\nmonitoring, continued to diversify the modalities of data collection\nas the context changed. For example, in remote locations instead of\nin-person interviews, case management with clients and\nmultisectoral programming, took place by phone. Protection\npartners revised their approaches, tools, and some terminology to\nadapt to the new context, to continue highlighting the on-going\nprotection-related concerns. From August 2021, many UNAMA\nnational staff members were relocated within the country due to the\ndeteriorating security situation. Consequently, UNAMA and OHCHR\nsupplemented their regular working methods with remote\n\n\n\nmonitoring and focused fact-finding and reporting mainly on credible\nallegations of violations and abuses committed during and following\nlarge-scale Taliban offensives.\n\n\nThe range of security challenges and operational constraints\nincluding movement restrictions imposed by the Taliban\nadministration while negotiations continued made it difficult for\npeople in need to reach services and impeded the capacity of\nprotection monitoring partners to collect high quality data and to\nprovide equitable protection.\n\n## **METHODOLOGY**\n\n\nThe report was prepared in collaboration with six partners\nundertaking protection monitoring: DRC, INTERSOS, IOM, IRC, NRC\nand UNHCR, using the data collected in Q4 from 12,722 Householdlevel interviews (HH), 589 Focus Group Discussions (FGDs) and 2,177\nKey Informants Interviews (KII). 38% of respondents were IDPs, 13%\nundocumented returnees, 42% members of the host community and\nIDP returnees 7%. 58% of the respondents were male while 42%\nwere female, which is an indication of limited access to women. This\nhowever has slightly improved compared to Q3 where female\nrespondents represented only 37% of those interviewed. The analysis\nis guided by the Global Protection Cluster <u>[Protection Analytical](https", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data collected in Q4"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001660", "page": 3, "chunk": 0, "title": "Afghanistan: Protection Analysis Update 2021 - Quarter 4", "pdf_url": "https://reliefweb.int/attachments/ffeb800e-1702-39ba-b790-dae700cb707b/Afghanistan%20-%20Protection%20Analysis%20Update%20-%20Quarter%204.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data collected in Q4", "label": "VAGUE_DATA", "score": 0.5661982893943787, "start": 1469, "end": 1489, "probe_score": 0.8305, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " variance analysis), we find that 75-85 percent of the total variation in wheat flour\n\n\nprices is explained by variation over the four quarters of the survey year; in contrast,\n\n\napproximately 5 percent of the total variation can be explained by variation across provinces.\n\n\n_Changes in food security over the survey year_\n\n\nThe potential impact of the commodity price increases can be seen in the raw data. Table 4\n\n\ndisplays population averages for some key indicators of food security by quarter of the\n\nsurvey. While the nominal values of total consumption and food consumption are relatively\n\n\n10 Prices are aggregated to the stratum level in order to mitigate potential measurement error in district-level\nprices. Strata are based on urban and rural designation within provinces.\n\n\n9", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["raw data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000447", "page": 10, "chunk": 1, "title": "food security and wheat prices in afghanistan a distribution sensitive analysis of household level impacts", "pdf_url": "https://local/prwp/food-security-and-wheat-prices-in-afghanistan-a-distribution-sensitive-analysis-of-household-level-impacts.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "raw data", "label": "VAGUE_DATA", "score": 0.7433642745018005, "start": 399, "end": 407, "probe_score": 0.5719, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*Findex 2014.</u>\n\n8. **Entrepreneurship.** The World Bank Enterprise Survey collects data from firms in the\nmanufacturing and service industries around the world. In Chad, only 13.1 percent of all firms have female\nparticipation in ownership and 9.0 percent have a majority of female participation in ownership. As a\nbenchmark, 29.6 percent have female participation in ownership and 12.3 percent have a majority of\nfemale participation in ownership in Sub-Saharan Africa. Moreover, only 1.9 percent of permanent fulltime production workers are female in Chad, compared to 19.0 percent in the region.\n\n\n\n\n\n\n\n\n\n\n\n|Indicator|Chad|Sub-<br>Saharan<br>Africa|All<br>Countries|\n|---|---|---|---|\n|Percent of firms with female participation in ownership<br>|13.1<br>|<br>29.6<br>|35.8<br>|\n|<br>Percent of firms with majority female ownership<br>|<br>9.0<br>|<br>12.3<br>|<br>14.4<br>|\n|<br>Percent of firms with a female top manager<br>|<br>12.0<br>|<br>15.4<br>|<br>18.0<br>|\n|<br>Proportion of permanent full-time workers that are female (%)<br>|<br>14.8<br>|<br>28.2<br>|<br>33.3<br>|\n|<br>Proportion of permanent full-time production workers that are female (%)a <br>|<br>1.9<br>|<br>", "output": {"entities": {"named_data": ["World Bank Enterprise Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000193", "page": 78, "chunk": 3, "title": "Chad - Energy Access Scale Up Project", "pdf_url": "https://documents1.worldbank.org/curated/en/860701648216750651/pdf/IBArchive-bd2c789e-ee04-4df7-a219-9409a5f705d3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Bank Enterprise Survey", "label": "NAMED_DATA", "score": 0.8971821069717407, "start": 48, "end": 76, "probe_score": 0.9984, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nProgram to Strengthen Governance for Enabling Service Delivery and Public Investment in Kenya (GESDeK)\n(P161387)\n\n\nexpected from a full-fledged Public Investment Management Information System (PIMIS). As a result, the National\nTreasury (NT) deemed it more appropriate to invest in developing a new PIMIS and prepared the functional and\ntechnical specifications for it in preparation for the procurement of a vendor to develop the system. This new\ntrajectory underpins the proposed way forward regarding this KRA.\n\n\n**8.** **The conceptualization and inception of automation initiatives underpinning the desired improvements in public**\n**procurement, and HR management have faced similar challenges.** The consultations, review, and approval process\nfor the E-procurement Plan and Roadmap took longer than anticipated during the planning stage, impacting the\nachievement of DLIs that depended on the completion of this action (i.e. DLR 3b and DLR 3c.) Progress toward the\nachievement of DLR 4b has also been limited due to the delays in the procurement process for both the development\nof the GHRIS and the hardware for the data warehouse to consolidate and host HR data, on which the achievement\nof this DLR depended. Lastly, DLI 5.3 was only partially achieved because of outstanding challenges regarding the\nreconciliation of the annual financial statements of MDAs with data in the IFMIS. The proposed amendments to the\nDLIs under these KRAs have been formulated in the context of the above-mentioned challenges.\n\n\n**9.** **Registering improvements in revenue collection has been a further challenge due to persistent institutional**\n**challenges regarding revenue forecasting, as well as the fiscal uncertainty the COVID-19 crisis precipitated.** DLR 2.2a\nhas not been achieved in three consecutive years due to significant differences between actual revenue collection and\nthe budgeted revenue. The growing and persistent divergence", "output": {"entities": {"named_data": ["IFMIS"], "descriptive_data": [], "vague_data": ["HR data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013185", "page": 8, "chunk": 0, "title": "Disclosable Restructuring Paper - Program to Strengthen Governance for Enabling Service Delivery and Public Investment in Kenya (GESDeK) - P161387", "pdf_url": "https://documents.worldbank.org/curated/en/447691635500209448/pdf/Disclosable-Restructuring-Paper-Program-to-Strengthen-Governance-for-Enabling-Service-Delivery-and-Public-Investment-in-Kenya-GESDeK-P161387.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "HR data", "label": "VAGUE_DATA", "score": 0.5639621615409851, "start": 1182, "end": 1189, "probe_score": 0.2771, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "IFMIS", "label": "NAMED_DATA", "score": 0.6289851069450378, "start": 1405, "end": 1410, "probe_score": 0.0168, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "21\n\n\nthey have to purchase water from trucks which costs four times as high than a household connection;\nand qat consumption poses a major social, income and productivity issue.\n\n\nIn order to capture as much of the school-age population presently out of school due to the lack of\nexisting places, the project will construct additional/rehabilitate classrooms. In addition, sanitation\n\nservices will be rehabilitated, and a study will be undertaken on which sanitation services best serve\nthe area, especially in a drought-prone area, and the most cost-effective methods of implementation\nand maintenance. The project will finance a study to analyze the factors that hinder girls' attendance\nand achievement, and of the feasibility of measures to overcome them, including the issues\n\nsurrounding access to education by the poor. The problems are cross-sectoral which the project, in\nPhase I, will not address (unemployed youth, health issues, non-Djiboutian school-age population,\netc.). See Section C above for program details.\n\n\nThe IDA's regional team will discuss with Government on updating the initial 1997 poverty\n\nassessment in order to produce a better picture of the issues as they exist now. In addition, it is\nenvisaged that IDA will discuss the rising health issues with the Government and the best ways for\naddressing these problems.\n\n\n_6.2 Participatory Approach: How are key stakeholders participating in the project?_\n\n\nKey stakeholders participated in the National Educational Forum _(Etats-Generaux de l'Education)_\nwhich was held in December 1999. This included officials, teachers, parents, students, members of\nparliament and the general public. The project is based on the outcome of the conference. The new\neducation law (approved in August 2000) sets in place the conditions for broadening participation in\nDjibouti's education system. It provides for setting up school management committees with parent\n\nand community involvement. The law also provides for the creation of conditions to increase private", "output": {"entities": {"named_data": [], "descriptive_data": ["1997 poverty\n\nassessment"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000147", "page": 24, "chunk": 0, "title": "Rwanda - Human Resources Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/837731468759911848/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1997 poverty\n\nassessment", "label": "DESCRIPTIVE_DATA", "score": 0.8141470551490784, "start": 1107, "end": 1131, "probe_score": 0.6186, "gold": "DATA_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Table A14: Summary of weights used with midline data\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Randomization weights w<br>k|Col2|Sub Sampling weights ωS<br>k|Col4|Tracking weights ωT<br>j|Col6|\n|---|---|---|---|---|---|\n|Treated|_wk_1<br>=<br>_Nk_<br>.<br>_Nk_1 _×_<br>_N_1<br>.<br>_NP_|Treated|_wS_<br>_k,_1<br>=<br>_Nk_1_/N Sk_1<br>_k_1 ,<br>_k_=locality|Respondents<br>main<br>phase<br>(_Ra_ = 1)|_ωT_ = 1|\n|Control|_wk_0_s_<br>=<br>_Nk_<br>.<br>_Nk_0_s ×_<br>_N_0<br>.<br>_NP_, _k_=locality x<br>gender|Control|_wS_<br>_k,_0 = 1|Non<br>Respondents<br>main phase<br>(_Ra_ = 0)|_ωT_<br>_j_ = _NES_<br>_b,j/NERS_<br>_s,b,j_ if re-<br>spondent in tracking phase<br>(_Eb_<br>=<br>1 et _Rb_<br", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["midline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000297", "page": 97, "chunk": 0, "title": "do workfare programs live up to their promises experimental evidence from côte d ivoire", "pdf_url": "https://local/prwp/do-workfare-programs-live-up-to-their-promises-experimental-evidence-from-côte-d-ivoire.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "midline data", "label": "VAGUE_DATA", "score": 0.6533288359642029, "start": 40, "end": 52, "probe_score": 0.9009, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "21\n\n\nthey have to purchase water from trucks which costs four times as high than a household connection;\nand qat consumption poses a major social, income and productivity issue.\n\n\nIn order to capture as much of the school-age population presently out of school due to the lack of\nexisting places, the project will construct additional/rehabilitate classrooms. In addition, sanitation\n\nservices will be rehabilitated, and a study will be undertaken on which sanitation services best serve\nthe area, especially in a drought-prone area, and the most cost-effective methods of implementation\nand maintenance. The project will finance a study to analyze the factors that hinder girls' attendance\nand achievement, and of the feasibility of measures to overcome them, including the issues\n\nsurrounding access to education by the poor. The problems are cross-sectoral which the project, in\nPhase I, will not address (unemployed youth, health issues, non-Djiboutian school-age population,\netc.). See Section C above for program details.\n\n\nThe IDA's regional team will discuss with Government on updating the initial 1997 poverty\n\nassessment in order to produce a better picture of the issues as they exist now. In addition, it is\nenvisaged that IDA will discuss the rising health issues with the Government and the best ways for\naddressing these problems.\n\n\n_6.2 Participatory Approach: How are key stakeholders participating in the project?_\n\n\nKey stakeholders participated in the National Educational Forum _(Etats-Generaux de l'Education)_\nwhich was held in December 1999. This included officials, teachers, parents, students, members of\nparliament and the general public. The project is based on the outcome of the conference. The new\neducation law (approved in August 2000) sets in place the conditions for broadening participation in\nDjibouti's education system. It provides for setting up school management committees with parent\n\nand community involvement. The law also provides for the creation of conditions to increase private", "output": {"entities": {"named_data": [], "descriptive_data": ["1997 poverty\n\nassessment"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014534", "page": 24, "chunk": 0, "title": "Ethiopia - Peasant Agricultural Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/542511468256148062/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1997 poverty\n\nassessment", "label": "DESCRIPTIVE_DATA", "score": 0.8141470551490784, "start": 1107, "end": 1131, "probe_score": 0.6186, "gold": "DATA_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**ANNEX 6: The INVITE Strategy in the Wider Context of Refugee and Host Livelihood Programming**\n\n\n**Context**\n\n\n1. **Uganda has a longstanding history of hosting refugees and is currently hosting the largest**\n**number of refugees in Africa and the third largest number in the world (1.5 million).** Most refugees\nreside in designated refugee settlements located across 13 districts (including Kampala). 57 percent\nof refugees are located in the West Nile Refugee Hosting Districts (RHDs), 37 percent are located\nacross six RHDs in the Southwest, and 6 percent are located in Kampala. Refugees account for a\nsignificant share of the total population in some districts as shown in Table 1, more than 45 percent\nin two West Nile districts. South Sudanese (61.7%) make up the largest refugee population followed\nby refugees from Democratic Republic of Congo (DRC) (29.3%), Burundi (3.4%), Somalia (2.9%) and\nothers (1.7%) from Ethiopia, Eritrea, Rwanda, and Sudan. 52 percent of refugees are female, and 81\npercent are women and children. Overall, 1 in 2 refugee households are female headed, compared to\nless than 1 in 3 host households.\n\n\n**Table 1: Refugee and Host Population in Uganda** <sup>**62**</sup> [^62: Uganda Comprehensive Refugee Response Portal ( _[https://data2.unhcr.org/en/country/uga](https://data2.unhcr.org/en/country/uga)_ ) 31 October 2021]\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Col2|Population|Col4|Refugee<br>% of<br>total|Col6|Number of<br>firms63|Col8|\n|---|---|---|---|---|---|-", "output": {"entities": {"named_data": ["Uganda Comprehensive Refugee Response Portal"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000021", "page": 76, "chunk": 0, "title": "Uganda - Investment for Industrial Transformation and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/469061641926083502/pdf/Uganda-Investment-for-Industrial-Transformation-and-Employment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Uganda Comprehensive Refugee Response Portal", "label": "NAMED_DATA", "score": 0.84051913022995, "start": 1214, "end": 1258, "probe_score": 0.9992, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "`o` Coughing or sneezing into a tissue or the bend of your arm, not your hand;\n\n`o` Disposing of any tissues used as soon as possible in a lined wastebasket and washing\n\nhands afterward;\n\n`o` Avoid sharing personal items or supplies such as phones, pens, notebooks, tools, PPE,\n\netc. when possible. Clean and disinfect them before and after use;\n\n`o` Use and remove PPE with care, being mindful of which surfaces may be contaminated.\n\nWorkers must clean their hands after handling any used PPE;\n\n`o` Avoiding common physical greetings, such as handshakes;\n\n`o` No sharing of food, drinks, cigarettes, personal hand tools. If hand tools are to be\n\nshared, clean and disinfect the contact points on the equipment; and\n\n`o` All common areas and surfaces should be cleaned at the end of each day.\n\n- At the project site, hand washing stations will be installed with sanitizer. Masks will be provided\nto the workers, and tools will be disinfected before and after use every day;\n\n- Workers will observe a minimum 1.5m social distance and the temperature for all the staff will\nbe checked daily and recorded before the work starts;\n\n- Working conditions will also accommodate the following:\n\n`o` Monitoring and controlling the entry and exiting of the worksite throughout from the\n\nstart and end of shifts;\n\n`o` All non-essential individuals are not permitted access to the site;\n\n`o` Detailed tracking of worker’s status on-site and off-site are kept at all times (e.g., fit to\n\nwork, sick, off-work for family caring duties, etc.)\n\n`o` Maintaining a list of workers that are currently working on sites and updating it daily.\n\n`o` Anyone with COVID-19 like symptoms such as sore throat, fever, high temperature\n\n(37.3 <sup>o</sup>", "output": {"entities": {"named_data": [], "descriptive_data": ["list of workers"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011132", "page": 28, "chunk": 0, "title": "Labor Management Procedures Improved Livelihood Opportunities and Accessibility for underserved urban communities in Meru Kenya (P163035)", "pdf_url": "https://documents.worldbank.org/curated/en/314241623993510344/pdf/Labor-Management-Procedures-Improved-Livelihood-Opportunities-and-Accessibility-for-underserved-urban-communities-in-Meru-Kenya-P163035.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "list of workers", "label": "DESCRIPTIVE_DATA", "score": 0.7391401529312134, "start": 1546, "end": 1561, "probe_score": 0.0429, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "* Popular Benchmarks\n**children.**\n\n\n**Project** **Development** **Outcome** **/** **Impact** **Project reports:** **(from** **Objective** **to Goal)**\n**Objective:** **Indicators:**\n**Assist** **war affected** - Improved social capital and - Initial Social Assessment - Communities in the NSAP\n**communities** **to restore** organizational development; (to establish indicators and target areas are assisted to\n**infrastructure,** **services** **and** - Increased access to and use methodologies for social ensure a reduced risk of\n**build** **local** **capacity for** of social and economic capital and organizational conflict\n**collective** **action.** Priority infrastructure and services development)\nwill be given to areas not - Proportion of NSAP - Annual social assessments; - NACSA complements and\npreviously serviced by investments targeted to newly - NaCSA M&E data; extends the work of other\ngovernment, newly accessible accessible areas, & areas - M&E data of relevant line agencies and rninistries\nand the most vulnerable previously not served, and mninistries; in support of the PRSP's\npopulation groups within those vulnerable people within these - Beneficiary Assessment poverty reduction and\nareas. areas; (BAs) biannually; decentralization objectives\n\n                  - Proportion of sub-projects                   - Participatory evaluation\nthat reflect priorities of reports for a random sample of                   - NACSA is fully integrated\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and", "output": {"entities": {"named_data": ["NaCSA M&E data"], "descriptive_data": ["M&E data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014032", "page": 29, "chunk": 1, "title": "Uganda - Structural Adjustment Credit Project", "pdf_url": "https://documents.worldbank.org/curated/en/506681468309344399/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NaCSA M&E data", "label": "NAMED_DATA", "score": 0.880613386631012, "start": 862, "end": 876, "probe_score": 0.7332, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "M&E data", "label": "DESCRIPTIVE_DATA", "score": 0.580130398273468, "start": 961, "end": 969, "probe_score": 0.5271, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a v\nManufacturIng 5 7 3.7 4 7 5 0 / s \\\\t oo  Services 475 272 190 201\n\nPrfvate consumpffon 90 7 81 9 938 95 1 20\nGeneral govemment consumption 7 0 9 6 146 17.2 =c ~GDFDl\nImpons of goods and servrcea 39 7 23 6 33 4 373 -3GW_G_____\n\n\n_(average_ _annual growth)_ 1981-9 1991401 2000 2001 Growth ot exports and Imports (%)\n\nAgrutumre -0 6 -2 6 2 2 3 8 oo\nIndustry 0.1 -41 51 5 6 s0\nManUnacturIng 6.9 . .\nServices -5 7 -5.4 4 0 51 \nPrivate oonsumpffon -2 0 -19 10 4 100 -50\nGeneral govemment consumption -5.1 -0 2 41.3 27 9 -100\nGross domestic Investment -06 3 0 50 - EOpois -tr-ports\nImports of goods and services -2 2 -151 85 0 61 3\n\n\nNote 2001 data are pretirrinary eastliates\n'The diamonds show four Key Indicators in the country (in bold) conipared with itS income-group average It data are missing, the diantond wiUt be rrconrrlte\n\n\n-56", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["2001 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010455", "page": 60, "chunk": 2, "title": "Ethiopia - Humera Agricultural Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/267681468243874141/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2001 data", "label": "VAGUE_DATA", "score": 0.7082152366638184, "start": 639, "end": 648, "probe_score": 0.0183, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and manufacturing sectors than in the services. Using data from the\ninternational input-output tables from TiVA, we further find that the negative association\nbetween trade and protectionism in government procurement concerns public and private\npurchases in qualitatively similar ways. This finding corroborates our initial hypothesis that\nprotectionism in government procurement can extend beyond the conduct of procurement\nauctions and affect the sourcing decisions of private firms as well (notably, the domestic ones\nwho are awarded procurement contracts).\n\nThe rest of the paper is organized as follows. Section II scopes out the existing literature on\ntrade policy and government procurement. Section III describes the construction of the\nindicators of protectionism based on national laws on government procurement, and the\ntrade data. We then present in Section IV the results from the cross-country regressions and\nfrom the estimations of the gravity model, both investigating the relationship between\nprotectionism in the law and trade openness. Section V concludes by summarizing the\nevidence and outlining limitations and policy implications.\n#### II. Literature review\n\n\nThis paper examines the importance of protectionist rules in government procurement across\ncountries and assesses their impact on cross-border flows, drawing on insights from different\n\n\n3", "output": {"entities": {"named_data": ["international input-output tables from TiVA"], "descriptive_data": [], "vague_data": ["trade data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001390", "page": 5, "chunk": 1, "title": "idu17835873d19f1e1402b184ca12dcc9be7c3a5", "pdf_url": "https://local/prwp/idu17835873d19f1e1402b184ca12dcc9be7c3a5.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "international input-output tables from TiVA", "label": "NAMED_DATA", "score": 0.6159076690673828, "start": 69, "end": 112, "probe_score": 0.8319, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "trade data", "label": "VAGUE_DATA", "score": 0.7568843364715576, "start": 832, "end": 842, "probe_score": 0.7863, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " adult\npopulation\n\n\n\nRelationship\nto HH Head\n\n\n\n**2.2.** **Household and individual sampling weights**\n\nThere are several sampling weights that are used in our analysis. To start with, there are the preCOVID-19 F2F household survey sampling weights ( **_wb_** ). These sampling weights serve as the\nstarting point for the computation of the HFPS household sampling weights in public use data sets\n( **_w1_** ), which are the calibrated versions of _wb_ to address coverage and non-response biases at the\nhousehold-level, leveraging the rich, pre-COVID-19 F2F survey data on (i) households that do not\nown a mobile phone and are excluded from the sampling frame; (ii) households that participate in\nthe HFPS, and (iii) households that are contacted but cannot not be reached. This latter scenario is\n\n\n9", "output": {"entities": {"named_data": [], "descriptive_data": ["preCOVID-19 F2F household survey", "F2F survey data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002035", "page": 10, "chunk": 6, "title": "representativeness of individual level data in covid 19 phone surveys findings from sub saharan africa", "pdf_url": "https://local/prwp/representativeness-of-individual-level-data-in-covid-19-phone-surveys-findings-from-sub-saharan-africa.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "preCOVID-19 F2F household survey", "label": "DESCRIPTIVE_DATA", "score": 0.5154947638511658, "start": 199, "end": 231, "probe_score": 0.8222, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "F2F survey data", "label": "DESCRIPTIVE_DATA", "score": 0.7640535831451416, "start": 555, "end": 570, "probe_score": 0.281, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " (26%) which is a sign of wealth in the area.\n\n\nFig o-6: Percentage distribution of households according to t~eir monthly earnings\n\n\n_Source:_ fielc:J data, t-.012\n\n4.3.8 Affected Crops/Trees, Buildings and stn.lctu~e.s1\n\n\nWithin the Ankole zone, a valuation of all the affected crops _I_ Trees (properties) is\nattached as Annex 2. The detailed assessment is provided in an excel spread sheet which\nis Volume B to this report -Valuer's report. From this list; crops, trees and in some cases\nfencing materials valued at Uganda Shillings 402,714,150/= have been valued. For\ncompensation purposes a 15% disturbance allowance of Uganda Shillings 60,407,122/= has\nbeen added bringing the total compensation package for the project area to Uganda\nshillings 463,121,272/=.", "output": {"entities": {"named_data": ["J data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019898", "page": 46, "chunk": 1, "title": "Uganda - Additional Financing for the Second Energy for Rural Transformation Adaptable Program Loan Project : resettlement plan (Vol. 1 of 4) : Resettlement action plan for the Masindi-Waki-Buliisa, and Nkonge-Kashozi 33kV power distribution line and associated low voltage networks", "pdf_url": "https://documents.worldbank.org/curated/en/905661468177546762/pdf/RP14200v10P1330osed0301901300Uganda.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "J data", "label": "NAMED_DATA", "score": 0.8353691101074219, "start": 149, "end": 155, "probe_score": 0.997, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "D.Climate** general equilibrium modelling\nstrategy compared to the previous Deloitte\n(2024) report, accounting for the impact\nof Ukrainian refugees on productivity.\nOver the past two decades, research by\nacademic economists has shown that\nviewing immigration solely through the lens\nof supply and demand severely constrains\nour understanding of the process\n(Peri, 2016). Such a model suggests that\nimmigration increases economic output\n\n\n36\n\n\n\nbut has negative labour market effects due\nto increased competition for jobs among\nworkers. However, little of these theoretical\nnegative labour market effects can be seen\nin empirical data. This is because immigrant\nworkers encourage further specialisation\namong native workers and firms, which\nincreases productivity and offsets the\nnegative effects. The same effects can\nbe expected in the case of refugees\nentering the Polish labour market – besides\nincreasing labour supply and competing\nwith Polish workers, they provide new skills,\nideas, and allow Polish workers to specialize\nin higher value-added tasks. These effects\nwere included in the estimates of the\nimpact of Ukrainian refugees on Polish\nGDP by Monitor Deloitte (2022) and Oxford\nEconomics (2022), but these estimates\nwere based on literature rather than Polish\nempirical data. In Deloitte’s 2024 study,\nthese effects were omitted due to a lack\nof empirical data with which to calibrate\nthem specifically. This study uses available\ndata, albeit limited, to create a conservative\nscenario that includes positive impacts on\nproductivity.", "output": {"entities": {"named_data": [], "descriptive_data": ["Polish\nempirical data"], "vague_data": ["empirical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 18, "chunk": 3, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "empirical data", "label": "VAGUE_DATA", "score": 0.5013534426689148, "start": 619, "end": 633, "probe_score": 0.9246, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Polish\nempirical data", "label": "DESCRIPTIVE_DATA", "score": 0.7275124788284302, "start": 1266, "end": 1287, "probe_score": 0.7406, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on social development issues"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000017", "page": 24, "chunk": 0, "title": "West Bank and Gaza - Integrated Community Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/158081468762622780/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on social development issues", "label": "VAGUE_DATA", "score": 0.581004798412323, "start": 1670, "end": 1703, "probe_score": 0.333, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "........................................................................................................22\n**3.15.** **OTHER RELEVANT ACTS** ........................................................................................................................................................................23\n**3.16.** **INSTITUTIONAL AND ADMINISTRATIVE FRAMEWORK** ......................................................................", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014544", "page": 1, "chunk": 19, "title": "Kenya - Kenya Tea Development Agency (KTDA) Small Hydro Programme Of Activities : Environmental Impact Assessment for Proposed Chania Mataara Small Hydropower Station", "pdf_url": "https://documents.worldbank.org/curated/en/543561539896512053/pdf/131043-EA-P160157-PUBLIC-Disclosed-10-17-2018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**_(Direction Générale des Douanes et des Droits Indirects –_** **إن تعزيز المديرية العامة للجمارك** .23\nللمديرية . فاألداء الجيد **هو بنفس القدر من األهمية والضرورة لزيادة تعبئة الموارد والقدرة التنافسية** **_DGDDI)_**\n\nلستهالك وا لضريبة على القيمة المضافة. في عام **ا** على لستيراد مثل الرسم الد اخلي **ا** أمر حاسم السترداد رسوم\n\nمن الضريبة على القيمة المضافة من قبل%المديرية . ومن هنا ضرورة تعزيز نظام ، تم جمع65.92015\nمعلومات اإلدارة (النظام اآللي للبيانات الجمركية العالمي) وضمان التفاعل من أجل المراجعة المزدوجة مع نظام\n\nتواجه تحديات كبيرة في ما يتعلق بتقييمالمديرية و عالوة على ذلك، ال تزالمعلومات الم .ديرية العامة للضرائب\n\nيجب معالج ة هذه التحديات لضمان القدرة التنافسية وزيادة لندماج في **ا** . وم البضائع وتحسين أوقات الت", "output": {"entities": {"named_data": [], "descriptive_data": ["معلومات اإلدارة"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000140", "page": 15, "chunk": 0, "title": "Djibouti - Public Administration Modernization Project", "pdf_url": "http://documents1.worldbank.org/curated/en/810531524548674826/pdf/PAD2604-ARABIC-PUBLIC-Project-Appraisal-Document-PAD-AR.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "معلومات اإلدارة", "label": "DESCRIPTIVE_DATA", "score": 0.5187833905220032, "start": 423, "end": 438, "probe_score": 0.2272, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "ant female|0.0093|0.3024|0.0265|0.3569|0.0156|0.3768|0.0444|0.4062|0.0348|0.3324|\n||[0.0022]|[0.0627]|[0.0037]|[0.0405]|[0.0032]|[0.0617]|[0.0070]|[0.0507]|[0.0046]|[0.0367]|\n|n.a.: not applicable. Sample means with standard errors in brackets._Source_: Demographic and Health Surveys<br>(Burkina Faso 2003, Cameroon 2004, Ghana 2003, Kenya 2003, Tanzania 2003-04). The data are weighted with<br>the sample weights given by the data provider.|n.a.: not applicable. Sample means with standard errors in brackets._Source_: Demographic and Health Surveys<br>(Burkina Faso 2003, Cameroon 2004, Ghana 2003, Kenya 2003, Tanzania 2003-04). The data are weighted with<br>the sample weights given by the data provider.|n.a.: not applicable. Sample means with standard errors in brackets._Source_: Demographic and Health Surveys<br>(Burkina Faso 2003, Cameroon 2004, Ghana 2003, Kenya 2003, Tanzania 2003-04). The data are weighted with<br>the sample weights given by the data provider.|n.a.: not applicable. Sample means with standard errors in brackets._Source_: Demographic and Health Surveys<br>(Burkina Faso 2003, Cameroon 2004, Ghana 2003, Kenya 2003, Tanzania 2003-04). The data are weighted with<br>the sample weights given", "output": {"entities": {"named_data": ["Demographic and Health Surveys"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003169", "page": 23, "chunk": 2, "title": "wps3956", "pdf_url": "https://local/prwp/wps3956.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Demographic and Health Surveys", "label": "NAMED_DATA", "score": 0.6364858150482178, "start": 254, "end": 284, "probe_score": 0.9863, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "## **Annex 4: Technical Assessment – Addendum**\n\n1. **A technical assessment was undertaken in October 2017** for USMID AF operation in accordance\nwith Bank Policy, Program for Results Financing. The following sections constitute a summary of the\nTechnical Assessment, which focused on up-date of the USMID TA conducted in 2012. The assessment\nwas based on a series of comprehensive studies, lessons learnt from implementation to date including the\ncompleted Mid-Term Review and a series of review missions. Moreover, as the Program will be up-scaling\nto eight additional municipalities, a detailed review of the capacity, preparedness and performance of the\nadditional municipalities as well as comparison on key dimensions with the original 14 municipalities was\nundertaken.\n\n**Detailed Program Description**\n\n\n2. **The design of USMID AF is an extension of the current program and will retain all its major**\n**components.** The current phase had a total Program Budget of US$ 160 million, of which IDA funding\nconstitutes US$ 150 million and GoU funding is US$ 10 million **.** USMID currently supports 14 municipal\nLGs as well as the Ministry of Lands, Housing and Urban Development (MLHUD). The largest part of the\nfunding goes to the LG level – the municipal development grant (now named DDEG under the IGFTR)\nUS$ 136 million, and the CB grants (CBG) US$ 15 million with the balance going to support results at the\nMLHUD level to support CB activities as well as Program implementation. The last grant cycle has just\nbeen released, based on the results from the annual performance assessments (APA).\n\n3. **USMID AF will provide support to part of the overall GoU Intergovernmental Fiscal**\n**Transfer Reform Program**, which is aiming at improving the overall grant system, including size,\nallocation, modalities and efficiency in the use of", "output": {"entities": {"named_data": [], "descriptive_data": ["annual performance assessments"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000006", "page": 53, "chunk": 0, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents.worldbank.org/curated/en/143681526614252328/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "annual performance assessments", "label": "DESCRIPTIVE_DATA", "score": 0.8784513473510742, "start": 1569, "end": 1599, "probe_score": 0.4967, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\n**Hogares encuestados, por corregimiento**\n\n0 50 100 150 200\n\n\n\nBetania\n\n\nJuan Díaz\n\n\nParque Lefevre\n\n\nBella Vista\n\n\nArraiján\n\n\n24 de Diciembre\n\n\nSan Francisco\n\n\nRío Abajo\n\n\nTocumen\n\n\nOtros\n\n_Fuente: HFS3_\n\n\n\n\n\n61%\n\n\n\nEl Corregimiento más representado en\n\nHFS3 fue Amelia Denis de Icaza,\n\nmientras que el HFS2 lo listaba en la\n\nséptima posición. Es también el único\n\ncorregimiento de San Miguelito entre\n\nlos principales diez en la encuesta del\n\nHFS3. Esta es la primera vez que se\n\nidentifica un corregimiento específico\n\ncon una distribución tan atípica en los\n\nmonitoreos de protección en Panamá.\n\nSe observó que varias personas\n\nencuestadas mantenían lazos familiares\n\nen el país antes de asentarse en este\n\nsector.\n\n\n\nEl 66% de las personas encuestadas se encontraba en corregimientos con menos de 10 familias\n\nencuestadas (59% en HFS2), y se agruparon como Otros, en la gráfica. El 34% de los corregimientos\n\nidentificados corresponden a un solo hogar encuestado (35% en HFS2). En un número importante\n\nde casos, no fue fácil para los participantes identificar con precisión el corregimiento donde residen,\n\npero esto se precisó con su dirección, durante la limpieza de datos.\n\n\nUNHCR / Febrero 2022 12", "output": {"entities": {"named_data": ["encuesta del\n\nHFS3"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001181", "page": 10, "chunk": 1, "title": "Monitoreo de protección: Panamá, Informe General - High Frequency Survey 3 Octubre 21 de 2021 a Diciembre 31 de 2021", "pdf_url": "https://reliefweb.int/attachments/b4aeeb01-2cd4-4f22-90c3-b234f09136e0/HFS%203%20General%20Report_Feb2022.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "encuesta del\n\nHFS3", "label": "NAMED_DATA", "score": 0.7825038433074951, "start": 433, "end": 451, "probe_score": 0.9078, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " do not use any cash\nfor health (and these are the majority, as cash is not\ntypically used for minor illnesses), or a lot of cash\nis used where there is a serious health problem\nthat requires expensive treatment. In turn, the 60\nUSD per household per month allocated for health\nexpenditures in the SMEB calculation (developed\nunder the CWG, as noted above), was described\nby the same respondent as largely artificial and not\n\n\n\nreflecting the huge variation of health expenditure\non the ground. This could be something useful to\nreflect upon as part of the development of the MEB\nor SMEB.\n\n\n**Complementarity with other programmes**\n\n\nAs a number of UNHCR staff explained, there\nare mechanisms in place to identify vulnerable\nreturnees, both at encashment centres (through\ninterviews) as well as through the ongoing\nprotection monitoring UNHCR carries out in\nthe country to identify violations of rights and\nprotection risks for people of concern. Persons with\nSpecific Needs identified at encashment centres\nare referred for follow up and potential assistance\nin the locations of (intended) return. As the example\nabove indicates however, some returnees may be\nfalling through the cracks. It was beyond the scope\nof this review to understand why, but the difficulties\nassociated with tracking returnees and the pattern\nof secondary displacement may be among the\nreasons.\n\n##### **Education**\n\n\n**Education sector outcomes and the**\n**contribution of cash**\n\n\nAs with WASH and health, returnee monitoring\nreports do not capture whether returnees have\nused any of the repatriation cash grant to cover\neducation-related costs. UNHCR Afghanistan (2015)\nonly captures returnee access to education and\nnotes that primary and secondary education is free\nfor all Afghan citizens. However, rates of enrolment\namong returnees are low and there are disparities\nbetween boys and girls. Research by UNHCR,\nOrange Door and VIAMO (2017) also finds low\nrates of enrolment and gender disparities among\nreturnee children: only", "output": {"entities": {"named_data": [], "descriptive_data": ["returnee monitoring\nreports"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000080", "page": 23, "chunk": 1, "title": "Afghanistan Case Study: Multi-purpose Cash and Sectoral Outcomes", "pdf_url": "https://reliefweb.int/attachments/020bd31a-6682-30a1-8823-7d27b21d2a9b/5b2cfab97.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "returnee monitoring\nreports", "label": "DESCRIPTIVE_DATA", "score": 0.8738459944725037, "start": 1485, "end": 1512, "probe_score": 0.0246, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Public Disclosure Copy\n\n\n**The World Bank** Implementation Status & Results Report\nEA Regional Transport, Trade and Development Facilitation Project (Second Phase of Program) (P148853)\n\n\nDate 12-Jun-2015 -- -- 30-Jun-2021\n\n\n**PHINDPDOTBL**\n\n\n Female beneficiaries (Percentage, Core Supplement)\n\n\nBaseline Actual (Previous) Actual (Current) End Target\n\n\nValue 0.00 -- -- 50.00\n\n\n**PHINDPDOTBL**\n\n\n Survey reports on citizen engagement available (Yes/No, Custom)\n\n\nBaseline Actual (Previous) Actual (Current) End Target\n\n\nValue N -- -- Y\n\n\nDate 12-Jun-2015 -- -- 30-Jun-2021\n\n\nOverall Comments\n\n\n**Intermediate Results Indicators**\n\n\nPHINDIRITBL\n\n\n Length of road rehabilitated - non rural (Kilometers, Custom)\n\n\nBaseline Actual (Previous) Actual (Current) End Target\n\n\nValue 0.00 -- -- 338.00\n\n\nDate 12-Jun-2015 -- -- 30-Jun-2021\n\n\n8/7/2015 Page 4 of 7\n\nPublic Disclosure Copy", "output": {"entities": {"named_data": [], "descriptive_data": ["Survey reports on citizen engagement"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009590", "page": 3, "chunk": 0, "title": "Africa - EA Regional Transport , Trade and Development Facilitation Project (Second Phase of Program) : P148853 - Implementation Status Results Report : Sequence 01", "pdf_url": "https://documents.worldbank.org/curated/en/211521468204569070/pdf/ISR-Disclosable-P148853-08-07-2015-1438985203717.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Survey reports on citizen engagement", "label": "DESCRIPTIVE_DATA", "score": 0.8457244634628296, "start": 399, "end": 435, "probe_score": 0.2055, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Disbursement forecast\n\n\n\nContract number\n*Contract subject\nAwardee\n*Launching date\n-Expected delivery date\n-Non objection date\n*Expected date of final delivery\n*Bidder nationality\n*Contract allocation (general account, budget, loan\ncategory, geographic area)\n*List of contracts\nManagement of financial -Standard financial statements (balance sheet;\naccounts statement of sources and uses of funds/income\nstatement, ...)\n*LACI reports for the project duration\nFixed Assets management -Inventory of Fixed Assets (type, quantity, valuation,\ndate of service, etc.)\n\n\n\nSupplier\nAccounting category ; budgetary and accounting\nallocation of fixed assets\n\n\n\nLocation\nDepreciation\n-Disposal of Fixed assets\n\n\n\n**Module** Functions\nSorting parameters Project ID and currency used\n\n                  - Fiscal years\nCurrency\nDecentralized data entry locations\n\n\n\nChart of accounts, managerial reports, geographic\nareas of intervention, etc.\n\n\n\n\n                - Books of accounts\nDonors\n\n                 - Contracts\nCategories of disbursement\nUser Management Data storage ; restitution ; correction; cleaning; etc.\n\n                - Import/export of data to other Tempro modules\n\n\n\nIt is expected that the application would be modified to differentiate the operations from the\nprojects, as well as funding sources to allow for reporting in financial and accounting terms of the\nproject objectives and activities. The concept should allow for proper monitoring of the project\nduring the life of the credit, namely: (i) chart of accounts; (ii) by category, component, and subcomponent; (iii) by geography (type of establishment, site and district); (iv) by category of\nexpenses; and (v) in local and foreign currency. Reporting of multi-level data is planned, which\n**wiU** bring about a more dynamic approach to the management of the project, and which should", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["multi-level data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009011", "page": 51, "chunk": 0, "title": "Uganda - Public Enterprise Project", "pdf_url": "https://documents.worldbank.org/curated/en/171971506445285879/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "multi-level data", "label": "VAGUE_DATA", "score": 0.6651609539985657, "start": 1720, "end": 1736, "probe_score": 0.4661, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**For more information please contact:**\nDivision of International Protection\nCommunity-based Protection Unit\n[hqts00@unhcr.org](mailto:hqts00@unhcr.org)\n\n\nRegional Bureau for Europe\n\n\nUNHCR Italy\n[vegaa@unhcr.org](mailto:vegaa@unhcr.org)\n[mittendo@unhcr.org](mailto:mittendo@unhcr.org)\n\n\n<mark>14</mark> PARTECIPAZIONE: EMPOWERING ORGANIZATIONS LED BY REFUGEES AND ASYLUM-SEEKERS AND COMMUNITY-BASED ORGANIZATIONS…", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000185", "page": 15, "chunk": 0, "title": "PartecipAzione: Empowering organizations led by refugees and asylum-seekers and community-based organizations to foster protection and meaningful participation in the host country - A promising practice on age, gender and diversity in Italy", "pdf_url": "https://reliefweb.int/attachments/11d87043-f0b0-4e17-9a7b-d851c8b3f53c/Empowering%20organizations%20led%20by%20refugees%20and%20asylum-seekers%20and%20community-based%20organizations%20to%20foster%20protection%20and%20meaningful%20participation%20in%20the%20host%20country.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Responsibilities and Functions o f the PPU: The PPU would: (i) identify beneficiaries; (ii) supervise civil\nworks and technical certification; (iii) be responsible for fund flow and financial management; and (iv)\nrecord and report project activities on a regular basis.\n\n\nManagement and Monitoring the Selection Process\n\n\nRank refugee camps using social and environment criteria;\nUndertake the Housing Assessment Survey in refugee camps to revalidate the number o f permanent,\npartly-completed and temporary thatched houses for purposes o f the cash grant allocation. This\nexercise would detail the extent o f additions needed for a party-completed house;\nOutsource the communications campaign for each phase o f the PHP. Ensure that the Puttalam IDPs\nare aware o f the project procedure and their rights;\nPublicize the eligibility criteria and beneficiary list;\nExplain beneficiary selection in public fora;\nEnsure compliance with national environmental regulations;\nTechnical monitoring; and\n\nSupport the grievance redressal process.\n\n\nPhysical Construction\n\n\n\n**_0_**\n\n\n**_0_**\n\n\n**_0_**\n\n\n**_0_**\n\n\n\nPrepare a material resource plan for each construction cycle to identify material requirement for a\nrefugee camp;\nFacilitate the procurement o f materials in bulk for beneficiaries when requested;\nMonitor civil works using technical officers; and\nProvide technical guidance and quality control to the homeowner.\n\n\n\nFund Flow and Financial Management\n\n\n\n**_0_**\n\n\n**_0_**\n\n\n**_0_**\n\n\n**_0_**\n\n\n**_0_**\n\n\n**_0_**\n\n\n\nDisburse cash grants to beneficiary bank accounts;\nMaintain project accounts and ensure utilization o f funds for project purposes;\nManage the flow o f funds;\nEnsure internal and external audits o f PHP accounts;\nPrepare Interim Financial Reports to comply with IDA reporting requirement; and\nDevelop computer-based forms and reports to measure and monitor physical progress and financial\nperformance.\n\n\n\nThe", "output": {"entities": {"named_data": ["Housing Assessment Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000023", "page": 46, "chunk": 0, "title": "Sri Lanka - Puttalam Housing Project", "pdf_url": "http://documents1.worldbank.org/curated/en/194731468104646411/pdf/38147core.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Housing Assessment Survey", "label": "NAMED_DATA", "score": 0.7440855503082275, "start": 394, "end": 419, "probe_score": 0.1502, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_Unaccompanied or separated children (UASC) seeking asylum_ <sup>*****</sup>\n\n\n\nProvisional data indicate that the\nnumber of unaccompanied or\nseparated children seeking asylum\non an individual basis is on the rise.\nMore than 25,300 individual asylum\napplications were lodged by UASC\nin 77 countries in 2013, far more than\nin previous years. At the same time,\n78 countries reported that they had\nnot registered a single asylum claim\nby an unaccompanied or separated\nchild during the year while a number\nof important recipients of asylumseekers were not able to report such\ninformation, including South Africa\nand the United States of America.\n\n\nThe number of UASC seeking\nasylum increased compared to 2012\n(21,300 claims in 72 countries), 2011\n(17,700 claims in 69 countries), and\n2010 (15,600 claims in 69 countries).\nThe 2013 level constituted about\n4 per cent of the total number of\nasylum claims lodged in these 77\ncountries. Despite fluctuations in\nthe global number of asylum claims\nregistered over the past years, this\nproportion has remained consistent\nwith the percentage observed in\n\n\n\nthe past six years (4% each). Much\nof the increase in 2013 came from\none country only: Kenya. Here, some\n4,600 UASC were registered by\nUNHCR, two-thirds (3,100) of them\nfrom boys and girls originating from\nSouth Sudan.\n\n\nEurope received 15,700 or more\nthan half of the 25,300 UASC claims.\nSweden and Germany registered the\ngreatest number of UASC new asylum\nclaims in Europe, with 3,900 and 2,500,\nrespectively. The United Kingdom\nand Norway were other important\nrecipients of UASC applications, with\n1,200 and 1,100 claims, respectively. In\nAsia, UNHCR offices in Malaysia and\nIndonesia reported having registered\nclose to 1,400 and 500 UASC claims,\nrespectively, while in the Americas,\nCanada registered 200 UASC claims.\nThe number", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Provisional data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001229", "page": 28, "chunk": 0, "title": "UNHCR Global Trends 2013: War's Human Cost", "pdf_url": "https://reliefweb.int/attachments/bccf108d-67b2-3a0c-9f57-b3c1e40ca740/Global_Trends_report_2013_V07_web_embargo_2014-06-20.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Provisional data", "label": "VAGUE_DATA", "score": 0.7602337598800659, "start": 80, "end": 96, "probe_score": 0.9792, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " repatriation, resettlement to a third country, local integration, naturalization\nand return to place of origin prior to displacement (for IDPs). However, a growing number of displaced populations\nhave limited opportunities for a durable solution. The COVID-19 pandemic has only exacerbated these challenges.\nThe partial or full closure of borders, along with more general restrictions on movement aimed at limiting the\npandemic’s spread, has dramatically impacted opportunities for displaced people to return to their home\ncountries or resettle to other countries.\n\n\n**Voluntary Repatriation (of Refugees)**\n\n\nFigure 11 **|** **Voluntary Repatriation Trends**\n\nThe region has experienced a constant decline in\nthe number of voluntary refugee repatriations since\n2016 with a sharp drop from 2016 to 2017 and gradual\nreductions with the lowest number in 2020 due\nmainly to travel restrictions as a result of the Covid19\npandemic with only 2,500 returns in the region.\nAfghanistan accounts for at least 90 per cent of all\nreturns in the region, with the largest refugee\nreturnee figures in the region over the last 5 years.\nIOM <sup>10</sup> report some 800,000 undocumented Afghans\nreturn from Pakistan in 2020.\n\n\n**8** \u0007The data for some countries may include a significant number of repeat claims, i.e. the applicant has submitted at least one previous application in\nthe same or another country.\n**9** \u0007The estimated percentage change in first instance asylum applications in 2020 does not include Government-registered refugee populations in\nIran, China, India and Nepal, as detailed information on this caseload is not available.\n**10** afghanistan-return_of_undocumented_afghans_situation_report_20-31_december_2020.pdf (reliefweb.int)\n\n\n14 Asia & the Pacific Regional Population Trends Analysis: Forced Displacement 2020", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data for some countries"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000881", "page": 13, "chunk": 1, "title": "Asia & The Pacific Regional Population Trends Analysis - Forced Displacement 2020", "pdf_url": "https://reliefweb.int/attachments/8258507f-f5b3-3fa1-a379-48a5fa38bee2/210716_Forced_Displacement_2020_V22.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data for some countries", "label": "VAGUE_DATA", "score": 0.6891665458679199, "start": 1224, "end": 1247, "probe_score": 0.0004, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Localised resilience in action: Responding to the Regional Syria crisis\n\n\nFigure 8 – Question 13 - Do your partnership agreements\nwith national and local actors include a dedicated budget\nfor capacity strengthening/organisational development?\n\n\nSource: Online survey conducted with 3RP partners between\n22 October and 10 November 2017.\n\n\nDespite evidence from the online survey of dedicated\nfunding for capacity building within partnership\nagreements, national and local organisations rarely\nreceive flexible overheads or programme support costs\nin the same way as UN agencies and international NGOs\n(with the exception of funding from CBPFs, see section\n8.1). This is particularly the case when receiving funds\nindirectly as implementing partners of international\norganisations. A lack of flexible financial support prevents\nnational and local actors from investing in their own\ninstitutional capacity development and building a solid\nfinancial base. At best, local and national organisations\nmay receive minimal funding for organisational overheads\nwhen receiving funding from donors directly. To take one\nexample of a Syrian organisation based in Turkey, the\norganisation received approximately US$6 million of\nfunding in 2017, only US$70,000 of which (equivalent to\njust over 1% of project budget) was for overheads and\nsupport costs.\n\n\n**27**\n\n\n\nResourcing projects in this way can prevent national and\nlocal organisations from keeping up basic operational\nstandards and competing with their international\ncounterparts e.g. paying decent salaries to attract and\nmaintain high quality staff, or ensuring that their financial\nsystems are up to standard. In some cases it may even\nincrease the likelihood of poor quality programming –\nleading to waste and even corruption – contributing to\na more risky funding environment overall. Undoubtedly\nthis reluctance to cover operational costs prevents longterm investments in staff development, and the ability to\nundertake meaningful research – a major impediment to\nactual capacity-building (USAID, 2016).\n\n\nCapacity building is an ongoing process; one that requires\ninvestment and commitment over long-term timeframes.\nThe short-term nature of humanitarian funding, therefore,\nis often at odds with capacity development", "output": {"entities": {"named_data": [], "descriptive_data": ["Online survey conducted with 3RP partners"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000316", "page": 26, "chunk": 0, "title": "Localised Resilience in Action: Responding to the Regional Syria Crisis (February 2019)", "pdf_url": "https://reliefweb.int/attachments/25871ceb-6a90-358d-958c-9059fd8deb3f/Localised%20resilience%20in%20action_final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Online survey conducted with 3RP partners", "label": "DESCRIPTIVE_DATA", "score": 0.7213510274887085, "start": 253, "end": 294, "probe_score": 0.9381, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Disbursement forecast\n\n\n\nContract number\n*Contract subject\nAwardee\n*Launching date\n-Expected delivery date\n-Non objection date\n*Expected date of final delivery\n*Bidder nationality\n*Contract allocation (general account, budget, loan\ncategory, geographic area)\n*List of contracts\nManagement of financial -Standard financial statements (balance sheet;\naccounts statement of sources and uses of funds/income\nstatement, ...)\n*LACI reports for the project duration\nFixed Assets management -Inventory of Fixed Assets (type, quantity, valuation,\ndate of service, etc.)\n\n\n\nSupplier\nAccounting category ; budgetary and accounting\nallocation of fixed assets\n\n\n\nLocation\nDepreciation\n-Disposal of Fixed assets\n\n\n\n**Module** Functions\nSorting parameters Project ID and currency used\n\n                  - Fiscal years\nCurrency\nDecentralized data entry locations\n\n\n\nChart of accounts, managerial reports, geographic\nareas of intervention, etc.\n\n\n\n\n                - Books of accounts\nDonors\n\n                 - Contracts\nCategories of disbursement\nUser Management Data storage ; restitution ; correction; cleaning; etc.\n\n                - Import/export of data to other Tempro modules\n\n\n\nIt is expected that the application would be modified to differentiate the operations from the\nprojects, as well as funding sources to allow for reporting in financial and accounting terms of the\nproject objectives and activities. The concept should allow for proper monitoring of the project\nduring the life of the credit, namely: (i) chart of accounts; (ii) by category, component, and subcomponent; (iii) by geography (type of establishment, site and district); (iv) by category of\nexpenses; and (v) in local and foreign currency. Reporting of multi-level data is planned, which\n**wiU** bring about a more dynamic approach to the management of the project, and which should", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["multi-level data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018094", "page": 51, "chunk": 0, "title": "Ethiopia - Sixth Telecommunications Project", "pdf_url": "https://documents.worldbank.org/curated/en/781361468243870721/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "multi-level data", "label": "VAGUE_DATA", "score": 0.6651609539985657, "start": 1720, "end": 1736, "probe_score": 0.4661, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPage 5 of 94", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 10, "chunk": 0, "title": "South Sudan - Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/824121596765983121/pdf/South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".............. 10**\n\n**E.** **Capacity Building and Institutional Strengthening.................................................................... 14**\n\n\n**III.** **PROGRAM IMPLEMENTATION ................................................................................................. 16**\n\n**A.** **Institutional and Implementation Arrangements ....................................................................... 16**\n\n**B.** **Results Monitoring and Evaluation ......................................................................", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 3, "chunk": 3, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|\n|[  ]<br>Loan|[X]<br>Grant|[X]<br>Grant|[X]<br>Grant|[ ]<br>Guarantee|[ ]<br>Guarantee|[ ]<br>Guarantee|[ ]<br>Guarantee|[ ]<br>Guarantee|[ ]<br>Guarantee|[ ]<br>Guarantee|[ ]<br>Guarantee|[ ]<br>Guarantee|\n|[  ]<br>Credit|[  ]<br>IDA Grant|[  ]<br>IDA Grant|[  ]<br>IDA Grant|[ ]<br>Other|[ ]<br>Other|[ ]<br>Other|[ ]<br>Other|[ ]<br>Other|[ ]<br>Other|[ ]<br>Other|[ ]<br>Other|[ ]<br>Other|\n|Total Project Cost:|Total Project Cost:|10.00|10.00|10.00|10.00|10.00|Total Bank Financing:|Total Bank Financing:|Total Bank Financing:|Total Bank Financing:|10.00|10.00|\n|Financing Gap:|Financing Gap:|0.00|0.00|0.00|0.00|0.00|||||||\n|**Financing Source** <br>**Amount**|**Financing Source** <br>**A", "output": {"entities": {"named_data": [], "descriptive_data": ["Project Financing Data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000003", "page": 6, "chunk": 2, "title": "Lebanon - Municipal Services Emergency Project", "pdf_url": "http://documents.worldbank.org/curated/en/119441469672145615/pdf/PAD10180PAD0P14972400PUBLIC00Box391431B.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Project Financing Data", "label": "DESCRIPTIVE_DATA", "score": 0.5564863085746765, "start": 4, "end": 26, "probe_score": 0.7898, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "br>Often<br>Attention is paid to<br>sub-group needs|**4 **<br>Seldom is attention<br>paid to sub-groups<br>needs|**5 **<br>No attention to<br>subgroups||Focus Group|\n|**Security/Law and order:** Does the population<br>always feel safe in the district?|**1 **<br>Always<br>(0 incidents per week)|**2 **<br>Very Often<br>(>1incidents/week)|**3 **<br>Often<br>(>2incidents/week)|**4 **<br>Seldom<br>(>3incidents/week)|**5 **<br>Never<br>(>4incidents/week)||Secondary Data or<br>Focus Group|\n|**Total**||||||||\n\n\n11", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Secondary Data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001568", "page": 10, "chunk": 1, "title": "A Vulnerability Analysis Framework for Syrian Refugees in Jordan", "pdf_url": "https://reliefweb.int/attachments/f36939c9-7234-371f-87cb-744133ba1925/ConceptualFrameworkforVulnerbailityAnalysisSyrianRefugeesJordanFinal.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Secondary Data", "label": "VAGUE_DATA", "score": 0.6475638151168823, "start": 454, "end": 468, "probe_score": 0.0103, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**References**\n\n\n\nAlexander, L., Jiang, S., Murga, M., & González, M. C. (2015). Origin–destination trips by purpose and time of day\n\n\n\ninferred from mobile phone data. Transportation Research Part C: Emerging Technologies, 58, 240-250.\nAnapolsky, S. (2013). Los flujos de movilidad territorial: Un análisis de la población y la movilidad en el área\n\n\n\nmetropolitana de Buenos Aires. Café ciudades.\n\n\n\nBachir, D., Khodabandelou, G., Gauthier, V., El Yacoubi, M., & Puchinger, J. (2019). Inferring dynamic origin\ndestination flows by transport mode using mobile phone data. Transportation Research Part C: Emerging\nTechnologies, 101, 254-275.\n\n\n\nBayir, M. A., Demirbas, M., & Eagle, N. (2010). Mobility profiler: A framework for discovering mobility profiles of\n\n\n\ncell phone users. Pervasive and Mobile Computing, 6(4), 435-454.\nBogotá, A. d. (2021). _Transmilenio requires additional resources due to pandemic effects_ . Retrieved from\n\n\n\nhttps://bogota.gov.co/mi-ciudad/movilidad/transmilenio-requiere-recursos-adicionales-por-efectosde-la-pandemia\n\n\n\nChapleau, R., Gaudette, P., Spurr, T., (2018). Strict and Deep Comparison of Revealed Transit Trip Structure\n\n\n\nbetween Computer-Assisted Telephone Interview Household Travel Survey and Smart Cards.\nTransportation Research Record: Journal of the Transportation Research Board. Volume 2672, Issue 42.\nCuhls, K., Rosa, A., Könnölä, T., Weber", "output": {"entities": {"named_data": ["Computer-Assisted Telephone Interview Household Travel Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000707", "page": 18, "chunk": 0, "title": "idu03cd59e8b0870c04785099900a77b56ab3732", "pdf_url": "https://local/prwp/idu03cd59e8b0870c04785099900a77b56ab3732.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Computer-Assisted Telephone Interview Household Travel Survey", "label": "NAMED_DATA", "score": 0.5485077500343323, "start": 1174, "end": 1235, "probe_score": 0.0243, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 5.5 \n 3.3 \n 3.0 \nPakistan\n 2,694 \n 2,803 \n 2,097 \n 2,051 \n 9,645 \n4%\n-25%\n-2%\n 4.3 \n 4.7 \n 3.4 \n 3.2 \nZimbabwe\n 3,945 \n 2,104 \n 810 \n 814 \n 7,673 \n-47%\n-62%\n0%\n 6.4 \n 3.6 \n 1.3 \n 1.3 \nIslamic Rep. of Iran\n 1,711 \n 1,392 \n 2,227 \n 2,301 \n 7,631 \n-19%\n60%\n3%\n 2.8 \n 2.4 \n 3.6 \n 3.6 \nSri Lanka\n 1,861 \n 1,536 \n 1,418 \n 1,566 \n 6,381 \n-17%\n-8%\n10%\n 3.0 \n 2.6 \n 2.3 \n 2.5 \nTurkey\n 1,580 \n 1,338 \n 1,438 \n 1,635 \n 5,991 \n-15%\n7%\n14%\n 2.5 \n 2.3 \n 2.3 \n 2.6 \nArmenia\n 1,399 \n 1,116 \n 1,333 \n 2,036 \n 5,884 \n-20%\n19%\n53%\n 2.3 \n 1.9 \n 2.2 \n 3.2 \nBangladesh\n 1,921 \n 1,678 \n 1,018 \n 1,019 \n 5,636 \n-13%\n-39%\n0%\n 3.1 \n 2.8 \n 1.7 \n 1.6 \nChina\n 1,160 \n 1,420 \n 1,463 \n 1,395 \n 5,438 \n22%\n3%\n-5%\n 1.9 \n 2.4 \n 2.4 \n 2.2 \nEritrea\n 1,064 \n 923 \n 1,359 \n 1,736 \n 5,082 \n-13%\n47%\n28%\n 1.7 \n 1.6 \n 2.2 \n 2.7 \nDem. Rep. of the Congo\n 1,168 \n 993 \n 1,155 \n 1,132 \n 4,448 \n-15%\n16%\n-2%\n 1.9 \n 1.7 \n 1.9 \n 1.8 \nSyrian Arab Rep.\n 1,003 \n 1,173 \n 989 \n 1,092 \n 4", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000381", "page": 26, "chunk": 1, "title": "Asylum figures fall in 2010 to almost half their 2001 levels", "pdf_url": "https://reliefweb.int/attachments/31bc4ca9-e978-3381-b95a-cfc86e39e16b/0C4784C3270B952CC125785E002F12B5-Full_Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " world. The population is unevenly distributed across the territory – 47%\nof the population is concentrated on only 10% of the total area of the country – and largely in rural\nareas, with only 21.7% of the population living in urban areas.\n\n\n**Sectoral and institutional Context**\nOverview of the system.\n\nThe education system in Chad is subdivided into early childhood education (almost inexistent, gross\nenrolment rate (GER) of 2%), six years of primary education, four years of lower secondary\neducation, three years of upper secondary education, and higher education. Teachers are trained at\nthe upper secondary level for service in primary schools and at the university level for service in\nsecondary schools. Recent (2013) ministerial restructuring shifted responsibilities for primary and\nlower secondary to the Ministry of Basic Education and Literacy (Ministère de l'Enseignement\nFondamental et de l'Alphabétisation, MEFA), for upper secondary (general and technical) to the\nMinistry of Secondary Education and Professional Training (Ministère des Enseignements et de la\nFormation Professionnelle Secondaires, MEFPS) and the responsibilities for higher education,\nresearch and post-secondary professional training to the Ministry of Research and Higher Education\n(Ministère de l'Enseignement, de la Recherche et de la Formation Professionnelle Supérieure,\nMERFPS). Primary and secondary education is delivered by three different types of schools, namely\ncommunity, public, and private schools.\n\nParents and communities play a crucial role in the country’s education system. In the context of the\ncivil war which followed independence, Parents’ Associations (Association des Parents d'Eleves APE) substituted themselves to the State which was unable to respond to their demand in setting up\nschools and continue to largely support the sector development today. APEs are nowadays\nespecially involved in: (i) the construction of new schools (called", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000020", "page": 1, "chunk": 1, "title": "Project Information Document (Appraisal Stage) - Chad Education Sector Reform Project Phase 2 - P132617", "pdf_url": "http://documents.worldbank.org/curated/en/444901468229746611/pdf/PID-Appraisal-Print-P132617-05-14-2013-1368525900048.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the situation that was agreed upon with\nthe Borrower.\n\nSigned by:\nFinancial Management v I _N_\n##### Specialist K {dO'.i1, O0\n\n(FMS-OPR) Rafika Chaouali, MNSHD Date\n\n\n**Part II:** **Procurement/Contract Management** System\n\nI have reviewed the procurement/contract management system relating to this project, including\nthe format and content of the section on Project Management Reports (PMRs) on procurement\n\nmonitoring. The objective of the review was to determine whether the procurement/contract\nmanagement system adopted by the project conforms to IDA's guidelines for procurement in\ninvestment projects. My review was based on the \"Assessment of Agency's Capacity to\nImplement Project Procurement, Setting of Prior Review Thresholds and Procurement\nSupervision Plan\" guidelines issued by IDA.\n\nI confirm that the project satisfies IDA's minimum procurement management requirements.\nHowever, in my opinion, the project does not have in place an adequate procurement/contract\nmanagement system that can provide the appropriate data on major procurement and contract\nmanagement (PMR - Section 3) as required by IDA.", "output": {"entities": {"named_data": [], "descriptive_data": ["data on major procurement and contract\nmanagement"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000161", "page": 54, "chunk": 1, "title": "Cambodia - Social Fund II Project", "pdf_url": "http://documents1.worldbank.org/curated/en/932001468769834027/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on major procurement and contract\nmanagement", "label": "DESCRIPTIVE_DATA", "score": 0.6258809566497803, "start": 1032, "end": 1081, "probe_score": 0.0015, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**x.** **Les mesures ci-dessous sont-elles appliquées pour le maintien des précautions universelles ?**\n\n\n\n**xi.** **Y-a-t-il eu une rupture du stock de gants, d’aiguilles ou de seringues de plus d’une semaine pendant ces douze**\n\n\n\n**derniers mois ?** **(Veuillez vérifier le compte des stocks).**\n\n\nSi la réponse est oui, détaillez :\n\n\n\nJ **oui** J **non**\n\n\n\n**xii.** **Y-a-t-il eu une rupture du stock de préservatifs de plus d'une semaine pendant ces douze derniers mois ?**\n\n\n\n**(Veuillez confirmer en vérifiant le compte des stocks).**\n\n\n**xiii.** **Existent-ils des protocoles de traitement des infections transmises sexuellement (ITS)**\n\n\n**tenant compte des syndromes ?**\n\n\nExistent-ils des médicaments adaptés au traitement des ITS ?\n\n\nY-a-t-il eu une rupture du stock de médicaments destinés au traitement des ITS de plus\n\n\nd'une semaine pendant ces douze derniers mois ? (Veuillez confirmer en vérifiant\n\n\nle compte des stocks).\n\n\nLes préservatifs sont-ils proposés dans le cadre de la gestion des ITS ?\n\n\nSi la réponse est oui, indiquez leur disponibilité dans l’établissement.\n\n\n37\n\n\n\nJ **oui** J **non**\n\n\n\nJ **oui** J **non**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001477", "page": 38, "chunk": 0, "title": "Besoins Relatifs au VIH Chez les Personnes Déplacées à l'Interieur de Leur Propre Pays et les Populations Affectées pas les Conflits: Outil d'Evaluation Rapide de la Situation", "pdf_url": "https://reliefweb.int/attachments/e5e599e2-c45c-3968-8168-f74321e0c5f4/9E7A791A8B8004D6C1257501003B8BF4-unhcr_2007.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "S)|Responsible Agency: Zambia National Climate Change Secretariat (NCCS)|Responsible Agency: Zambia National Climate Change Secretariat (NCCS)|\n|Contact: <br>David Kaluba <br> Title: <br>National Coordinator|Contact: <br>David Kaluba <br> Title: <br>National Coordinator|Contact: <br>David Kaluba <br> Title: <br>National Coordinator|Contact: <br>David Kaluba <br> Title: <br>National Coordinator|Contact: <br>David Kaluba <br> Title: <br>National Coordinator|Contact: <br>David Kaluba <br> Title: <br>National Coordinator|Contact: <br>David Kaluba <br> Title: <br>National Coordinator|\n|Telephone No.: 260-211-236480 <br> Email: davidkaluba@znccs.org.zm|Telephone No.: 260-211-236480 <br> Email: davidkaluba@znccs.org.zm|Telephone No.: 260-211-236480 <br> Email: davidkaluba@znccs.org.zm|Telephone No.: 260-211-236480 <br> Email: davidkaluba@znccs.org.zm|Telephone No.: 260-211-236480 <br> Email: davidkaluba@znccs.org.zm|Telephone No.: 260-211-236480 <br> Email: davidkaluba@znccs.org.zm|Telephone No.: 260-211-236480 <br> Email: davidkaluba@znccs.org.zm|\n|**Project Financing Data(in US$, millions)", "output": {"entities": {"named_data": ["Project Financing Data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000071", "page": 5, "chunk": 4, "title": "Africa - Displaced Persons and Border Communities Project", "pdf_url": "http://documents1.worldbank.org/curated/en/465201467989464233/pdf/PAD1510-PAD-P152821-IDA-R2016-0078-1-Box394886B-OUO-9.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Project Financing Data", "label": "NAMED_DATA", "score": 0.5128296613693237, "start": 1061, "end": 1083, "probe_score": 0.4315, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### IMPLICATIONS FOR POLICY\n\n\n\nThis program of research interrogated\nexisting data sets and did not involve\nprogram or policy evaluations. The\nresults nonetheless reveal important\ninsights about directions for policies\nand programs, given the robust evidence about the profile of deprivations\nand drivers of disparities, alongside the\nincreased risk of GBV and difficulty in\nshifting gender norms.\n\n\nThe gender dimensions of displacement\nhave implications for both humanitarian and development programming.\nThe protracted nature of displacement\nmeans that long-term perspectives\nneed to be adopted, even amidst\nemergencies. The average length of\nhumanitarian crises and responses has\nincreased over time, from 5.2 years to\n9.3 years between 2014 and 2018. <sup>62</sup>\nWhile funding for humanitarian responses has gradually increased over\nthe past decade, estimated needs have\noutpaced funding. In 2020, UN OCHA\nestimated a $22 billion gap between\nthe amount available for humanitarian\nresponse and the $39 billion required—\nthe largest deficit ever. <sup>63</sup>\n\n\nThe overarching general implication\nfor policy makers is that both humanitarian and development policies and\nprograms need to understand and\naddress the intersectionality of gender\n\n\n\nand displacement and respond appropriately to close gaps in status and\nopportunities in specific contexts. It is\nalso important to understand the needs\nof affected groups through direct consultations about their constraints and\npriorities and meaningful participation\nin program and policy design. <sup>64</sup>\n\n\nThe more direct implications for policy\nfall into several categories, beginning\nwith the value of better understanding\ncountry circumstances. We cover these\nin turn below.\n\n###### THE FEASIBILITY AND IMPORTANCE OF COUNTRY-SPECIFIC ANALYSIS\n\n\nThe research program reveals that\nmuch more can be done to inform\npolicy and program design even with\nexisting data. The analyses demonstrate\nhow diverse data sources—ranging from\nwell-known datasets such as the DHS\nto more recently fielded labor market\nand household income and expenditure\nsurveys designed to address questions\naround displacement—can", "output": {"entities": {"named_data": ["DHS"], "descriptive_data": ["labor market\nand household income and expenditure\nsurveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001238", "page": 26, "chunk": 0, "title": "The Gender Dimensions of Forced Displacement: A Synthesis of New Research", "pdf_url": "https://reliefweb.int/attachments/be0ec676-9a9a-3e88-8ef2-c61baa6c67d0/The-Gender-Dimensions-of-Forced-Displacement-A-Synthesis-of-New-Research.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "DHS", "label": "NAMED_DATA", "score": 0.9140810966491699, "start": 2020, "end": 2023, "probe_score": 0.8599, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "labor market\nand household income and expenditure\nsurveys", "label": "DESCRIPTIVE_DATA", "score": 0.841788649559021, "start": 2049, "end": 2106, "probe_score": 0.265, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " during<br>missions and<br>ISRs<br>|SNSOP MIS<br>which hosts<br>beneficiary<br>registration<br>and payment<br>data<br>|The implementing<br>partner will collect<br>beneficiary data during<br>targeting and<br>registration. The<br>payment service<br>provider and<br>implementing agency<br>will document payment<br>data<br>|Implementing Partner<br>|\n|Beneficiary households of social safety<br>net programs- Refugees|The number of total<br>beneficiaries HHs that are|This indicator<br>will be|SNSOP MIS<br>which hosts|The implementing<br>partner will collect|Implementing Partner<br>|\n\n\nPage 51 of 74", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["beneficiary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 55, "chunk": 1, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "beneficiary data", "label": "VAGUE_DATA", "score": 0.6620537638664246, "start": 163, "end": 179, "probe_score": 0.0147, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " monthly). Based on UNHCR data collected, cost of living per family is</mark> CHF 90 – 100 per\nhousehold per month (please see Annex 3). This includes non-food items, health needs, and half food\nbasket, with the other half-coming sister UN agency World Food Program. So even without the profits\nfrom these items, even if they were sold at cost, we perceived that the wages as described in production\ncost is enough to cover the full expenditures of the artisan’s family needs.\n\n\n<mark>However, market research indicates that similar items sell for much more than the production cost of the</mark>\n<mark>artisan goods produced by refugees. So their income can be even much higher, if profits are considered.</mark>\n<mark>In the table below, we summarized the profitability of the full portfolio that is currently in production at the</mark>\n<mark>refugee camp.</mark>\n\n\n26", "output": {"entities": {"named_data": ["UNHCR data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000172", "page": 27, "chunk": 1, "title": "New issues in refugee research - Research paper no. 282 - From care and maintenance to self-reliance: Sustainable business model connecting Malian refugee artisans to Swiss markets using public-private partnerships", "pdf_url": "https://reliefweb.int/attachments/0e8553de-def8-3058-ad13-5158de6f63d9/5857ebef4.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR data", "label": "NAMED_DATA", "score": 0.7359730005264282, "start": 20, "end": 30, "probe_score": 0.0634, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " HIE and appropriate oversight,\ngovernance, and management mechanisms. Building on the strong interoperability layer, the national EMR system will be\nexpanded to all MOH facilities at the primary, secondary, and tertiary levels. Currently, the Electronic Medical Records do\nnot track refugee status, making it difficult to determine whether a registered non-Jordanian – including Syrian refugee\npatient is eligible for subsidized healthcare services. This contributes to the low uptake of health-services by refugees.\nCollected data from the national EMR will then be used to strengthen institutional capacity in data use through\ninstitutionalized data quality audits.\n\n**7. Result Area 2 on government effectiveness supports a cross-cutting objective of enhancing the professionalization of**\n**the civil service, including its digital literacy, as well as two sector specific strategic objectives, namely: improving student**\n**assessments through digitalization and enhancing the quality of health data.**\n\n**- Enhancing the professionalization of the civil service in Jordan is one of the main strategic thrusts of the Public Sector**\n**Modernization Roadmap.** It seeks to uplift the overall quality and efficiency of the civil service, thereby addressing the\nweak partnership with the private sector and civil society. As part of this initiative, the Government has set an ambitious\ngoal to competitively recruit 100 percent of new civil service entrants by 2027 through competency-based promotions. This\nrepresents a significant shift, especially when considering that only 12 percent of recruitments currently are based on\ncompetency-based assessments. To further strengthen the reform, the Government has outlined pivotal milestones, such\nas the introduction of transparent career paths and the formation of a job competencies system by May 2024. A\ncompetency assessment center, expected to be operational by September 2024, will be instrumental in enhancing both\nrecruitment and promotions. This approach resonates with the identified need for effective public institutions and\nresponsible, competent civil employees who can translate national visions into actionable policies and plans. Moreover, in\nkeeping", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["health data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000181", "page": 63, "chunk": 1, "title": "Jordan - People-Centric Digital Government Program for Results", "pdf_url": "https://documents1.worldbank.org/curated/en/099030724150040202/pdf/BOSIB-70f97ae8-b741-401c-82cc-e87615cc5487.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "health data", "label": "VAGUE_DATA", "score": 0.5458675026893616, "start": 994, "end": 1005, "probe_score": 0.0228, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Figure 1** . Anchored AROPE rates (2022) and annual variation (2021-2022), EU27 (excluding\n\nGermany) and sub-regions\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nNote: Percentage of individuals (using survey weights). Regional averages are weighted by the country’s\npopulation. The poverty threshold of the AROP dimension is anchored to the 2019 survey year. The Harmonized\nConsumer Price Index (HCPI) is used to deflate income aggregates. Table A3.1 reports AROPE rates by sub-region.\nNorthern Europe (NE) consists of Denmark, Estonia, Finland, Latvia, Lithuania and Sweden. Southern Europe (SE)\nconsists of Cyprus, Spain, Italy, Portugal, Malta and Greece. Western Europe (WE) consists of Austria, Belgium,\nFrance, Ireland, Luxembourg, and the Netherlands. Central Eastern Europe (CEE) consists of Bulgaria, Czechia,\nHungary, Croatia, Poland, Romania, the Slovak Republic and Slovenia. EU-27 excludes Germany.\nSource: Own estimates based on 2021-2022 EU-SILC. We report the survey year and not the income year. AROPE\ndefinition based on EU2030 target. Eurostat does not report anchored AROPE rates.\n\n\n**Figure 2.** Anchored AROPE rates (2021 and 2022) by country\n\n\nNote: Percentage of individuals (using survey weights). The poverty threshold of the AROP dimension is anchored\nto the 2019 survey year. The Harmonized Consumer Price Index (HCPI) is used to deflate income aggregates. Table\nA3.2 reports AROPE rates by country and explains country acronyms. EU-27 excludes Germany. The 45-degree line\nreflects an equal AROPE rate between 2021 and 2022. A longer period is not presented due to the methodological\nchanges in the AROPE definition (2020 vs 2030 targets).\nSource: Own estimates based on 2021-2022 EU-SILC. We report the survey year and", "output": {"entities": {"named_data": ["2021-2022 EU-SILC"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001536", "page": 16, "chunk": 0, "title": "idu1c029d6f01b5dc140491b90a1924be575d65e", "pdf_url": "https://local/prwp/idu1c029d6f01b5dc140491b90a1924be575d65e.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2021-2022 EU-SILC", "label": "NAMED_DATA", "score": 0.7107667326927185, "start": 919, "end": 936, "probe_score": 0.9988, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Challenges in access to birth registration for refugees and asylum-seekers in Ethiopia | SEPTEMBER 2024\n\n\n### **II. Actions by the Government of**\n\n**Ethiopia to promote birth**\n**registration** **for** **refugee**\n**children.**\n\nAt the 2016 Leaders’ Summit on Refugees,\nEthiopia made nine very significant pledges\nto improve the lives of refugees and integrate\nthem more effectively in society. One of the\nkey pledges concerned documentation,\nspecifically to enhance the civil registration\nand vital statistics (CRVS) system to ensure\nthat all births, deaths, marriages, and other\nvital events for refugees would be registered\nand documented. This initiative was\nimportant for both refugees and for the\nnational authorities themselves, as it was also\nforeseen that it would improve the accuracy\nand reliability of population data, crucial for\nplanning and delivering public services, and\nfor informing development responses.\n\nA related legal proclamation was\nsubsequently passed. Ethiopia’s Vital Events\nRegistration and Nationality Identity Card\nProclamation (Amendment Proc. No. 1049\n/2017), entered into force in August 2017. The\nproclamation provides the legal foundations\nfor refugee access to vital events registration.\nAn implementing directive soon followed.\nThe launch of vital events registration for\nrefugees began in October 2017.\n\nThe revised Refugees Proclamation (Proc.\nNo.1110/2019) awards refugees the same\ntreatment as nationals regarding the\nregistration of vital events and issuance of\ncertificates.\n\nThe proclamation empowers the Refugees\nand Returnees Services (RRS) as the\nresponsible Government body that has the\nprimary responsibility for the security and\nmanagement of all refugee camps and\nsettlements in Ethiopia and in ensuring the\nprotection and physical security of refugees,\nin collaboration with federal and regional\ngovernments as well as with UNHCR and\nother partners.\n\n\n\nThe progress in the issuance of birth and\nother vital events registration to refugees has\nbeen constant, but at times slow. In 2019,\nthere were 8,080 vital events registered, with\nthe vast majority being", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["population data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000785", "page": 2, "chunk": 0, "title": "UNHCR Ethiopia: Challenges in Access to Birth Registration for Refugees and Asylum-Seekers in Ethiopia – Protection Brief | September 2024", "pdf_url": "https://reliefweb.int/attachments/73a29f6e-f2a7-4912-bb81-a3ff75393582/Protection%20Brief%20on%20CP-%20September%202024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "population data", "label": "VAGUE_DATA", "score": 0.7429518103599548, "start": 815, "end": 830, "probe_score": 0.2102, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on social development issues"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000016", "page": 24, "chunk": 0, "title": "Yugoslavia, Federal Republic of Serbia/Montenegro - Education Improvement Project", "pdf_url": "http://documents1.worldbank.org/curated/en/151961468759580842/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on social development issues", "label": "VAGUE_DATA", "score": 0.581004798412323, "start": 1670, "end": 1703, "probe_score": 0.333, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " erosion, storms and tidal surges due to severe cyclones and landslides. Its vulnerability is\nexacerbated by climate change induced increase in frequency and intensity of extreme weather events, sea level\nrise and uncertainty. Bangladesh is ranked the 6th most climate vulnerable country among 181 countries.\nDamages and losses associated with a single extreme event impose substantial costs on the national economy\nand repeated exposure to hydro-meteorological hazards such as cyclones and floods often pushes the poor,\nparticularly rural poor, into chronic poverty.\n\n**Situation in Urgent need of assistance**\n3. Since August 25, 2017, extreme violence in Rakhine State, Myanmar, has driven an estimated 730,000 <sup>1</sup>\npeople from the Rohingya community across the border into the Cox’s Bazar district of Bangladesh. This exodus\nbrings the total number of Displaced Rohingya Population (DRP) in the district to about 923,033 <sup>2</sup> in what is one of\n\n1 ISCG: Situation Report Rohingya Refugee Crisis, (September 27, 2018)\n2 IOM Needs and Population Monitoring round 12 as of October 10, 2018\n\n\nPage 11", "output": {"entities": {"named_data": ["IOM Needs and Population Monitoring round 12"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000111", "page": 12, "chunk": 2, "title": "Bangladesh - Emergency Multi-Sector Rohingya Crisis Response Project", "pdf_url": "http://documents1.worldbank.org/curated/en/655111552269808019/pdf/BANGLADESH-PAD-02212019-636878521930630901.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "IOM Needs and Population Monitoring round 12", "label": "NAMED_DATA", "score": 0.7602809071540833, "start": 1038, "end": 1082, "probe_score": 0.0273, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "from web<br>platform and<br>surveys<br> <br>|<br>Survey<br>|PSFU and UBOS<br>|\n|The percentage of jobs saved, that would<br>be lost due to COVID 19,|Percentage of firms<br>reporting an improvement<br>in employment|Annual<br>|<br>EPRC Panel<br>Data<br> <br>|Telephone survey<br>|PSFU/UBOS/EPRC<br>|\n|The number of new loans issued to firms<br>in the manufacturing sectors|<br>Loans issued after project<br>start date<br>|Annual<br>|<br>Reporting by<br>Participating<br>FIs and<br>Project portal<br>|Tracking transactions<br>on project web portal<br> <br>|BoU<br>|\n|Beneficiaries reached with financial<br>services|The indicator measures the<br>number of persons<br>benefited from financial<br>services in operations|Annual<br>|<br>|Web based reporting<br>by Participating<br>Financial Institutions to<br>BoU|BoU<br>|\n\n\nPage 53 of 92", "output": {"entities": {"named_data": ["EPRC Panel"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000021", "page": 58, "chunk": 1, "title": "Uganda - Investment for Industrial Transformation and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/469061641926083502/pdf/Uganda-Investment-for-Industrial-Transformation-and-Employment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "EPRC Panel", "label": "NAMED_DATA", "score": 0.8535920977592468, "start": 229, "end": 239, "probe_score": 0.8334, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "* . While\nfarmers depend on grazing during spring, they are reliant on subsidized feed through the rest of the year.\nCurrently, MoITS is the mandated importer of barley and operates storage across several silos and storage\nplatforms (bunkers). From there, barley is sold to sheep owners registered with the fodder sale centers of MoITS\nin the governorates – a network of outlets for distributing subsidized animal feed (barley and bran), according to\nthe number of livestock heads registered on the livestock vaccination card issued by the Ministry of Agriculture\n(MOA). Each head of sheep is allocated 20kg of barley per month at the subsidized price of JOD178 per ton. Over\nthe past 10 years, the price of barley has been subsidized and set constant at around JOD175 per ton, while wheat\nbran used for feed (byproduct of wheat milling) is being sold at JOD140 per ton. The private sector participates in\nthe animal feed value chains for other species such as cattle, importing barley, soybeans, maize and fortification\n\n\n26 There are eight mills in Amman including Juwaidah, two in Irbid, one in Ajloun, one in Zarqa and one in Mafraq.\n27 The mills are not allowed to sell the flour (Tahin Mouhad) at market rates, nor allowed to freely import wheat at market rates and sell\nthe flour (Tahin Mouhad) and bran locally at market rates. With special approvals, the mills are allowed to import wheat (soft) and reexport\nas flour at market rates, or sell as higher quality flour for pastries, or import wheat (durum) and sell as semolina for pasta production.\n_28_ [http://dosweb.dos.gov.jo/agriculture/livestock/](https://nam11.safelinks.protection.outlook.com/?url=http%3A%2", "output": {"entities": {"named_data": [], "descriptive_data": ["livestock vaccination card"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 21, "chunk": 2, "title": "Jordan - Emergency Food Security Project", "pdf_url": "http://documents.worldbank.org/curated/en/486071652556836130/pdf/Jordan-Emergency-Food-Security-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "livestock vaccination card", "label": "DESCRIPTIVE_DATA", "score": 0.8445203304290771, "start": 499, "end": 525, "probe_score": 0.5873, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " objective: To enhance the institutional performance of Program Local<br>Governments (LGs) to improve urban service delivery.<br> <br>Revised Program development objective: Same as above <br> <br>Program description: USMID is a Program for Results (PforR) operation supporting municipal local<br>governments in Uganda to improve their institutional performance for urban service delivery as well as<br>deliver infrastructure in line with locally identified priorities.|\n|**Exception to Policies**|**Exception to Policies**|**Exception to Policies**|**Exception to Policies**|\n|Is approval of any policy waiver sought from the Board (or MD if RETF operation is<br>RVP approved)?<br>Has this been endorsed by Bank Management? (_Only applies to Board approved_<br>_operations_) <br>Does the Program require any exception to Bank policy?<br>Has this been approved by Bank Management?|Is approval of any policy waiver sought from the Board (or MD if RETF operation is<br>RVP approved)?<br>Has this been endorsed by Bank Management? (_Only applies to Board approved_<br>_operations_) <br>Does the Program require any exception to Bank policy?<br>Has this been approved by Bank Management?|Is approval of any policy waiver sought from the Board (or MD if RETF operation is<br>RVP approved)?<br>Has this been endorsed by Bank Management? (_Only applies to Board approved_<br>_operations_) <br>Does the Program require any exception to Bank policy?<br>Has this been approved by Bank Management?|[  ]Yes  [X] No<br>[  ]Yes  [   ] No<br> <", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000062", "page": 6, "chunk": 1, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents.worldbank.org/curated/en/946901526654169395/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " were some improvements in efficiency, particularly when\nadditional students joined schools operating below capacity. However, other schools were\nalready relatively full at the onset of the crisis, and have since become overloaded with student\ndemand. Overall, there have been dramatic increases in the expenditure on public education,\nposing acute stress on the operations and the learning environment of public schools.\n\n\n57. Preliminary analysis of MEHE’s actual expenditures has revealed that total expenditure\nhas increased from US$431 million in academic year 2010-11 to US$573 million in 2013-14\n\n\n16", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000099", "page": 24, "chunk": 1, "title": "Lebanon - Emergency Education System Stabilization Project", "pdf_url": "http://documents1.worldbank.org/curated/en/578481467991017996/pdf/PAD1190-PAD-P152848-PUBLIC-Box391435B-LB-EESSP-Final-PAD-for-printing.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nPromoting Financial Inclusion Policies and Regulations in Jordan ( P163719 )\n\n\n2017; (iii) continuing to champion the financial education program into the existing Jordanian school\ncurriculum from class 7 to class 11 by 2020; (iv) enhancing interoperability among the payments systems in the\nkingdom by end 2018; (v) ensuring efficient and responsible growth of microfinance sector as part of the\nformal financial system; (vi) providing the refugees and non-nationals with access to digital financial services;\n(vii) ensuring the provision of an enabling legislative and regulatory environment for digital financial services;\n(viii) upgrading financial inclusion data collection and measurement to align with AFI's network to produce\ncomparable indicators by 2018; and (ix) increasing the financial inclusion access of Jordan’s youth (15-22 years)\nby 25 annually by 2020.\n\n   - **Moreover, CBJ has worked in the last four years on building an infrastructure for payment systems, including**\n\n**interoperable platforms for mobile money and bill payments.** The CBJ has also progressively modernized its\ninternal systems to support a greater shift of Government payments into electronic payments. An ongoing\nproject with GIZ called “Digi#ances” aims to target low income Jordanians and refugees through JoMoPay to\nprovide them with digital wallets to receive money and transact. This comes along with financial literacy\nprograms and outlook for digital cross-borders remittances routes.\n\n   - **The Government of Jordan has announced its commitment to digitizing money transfers.** This is of particular\n\nimportance as the World Bank Universal Financial Access (UFA) data portal estimates that 0.2 million adults can\nbe reached in Jordan by exploiting the country opportunity of digitizing G2P payments. Currently, 160 out of\n260 government services are paid electronically in the system where government transactions in the system\nare growing exponentially in terms of volume and number.\n\n   - **With the objective of attaining a", "output": {"entities": {"named_data": ["Universal Financial Access (UFA) data portal"], "descriptive_data": [], "vague_data": ["financial inclusion data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000013", "page": 4, "chunk": 0, "title": "Jordan - Promoting Financial Inclusion Policies and Regulations in Jordan Project : Project Information Document (Concept Stage) - Promoting Financial Inclusion Policies and Regulations in Jordan - P163719", "pdf_url": "http://documents.worldbank.org/curated/en/280421491408992654/pdf/IL-AISPID-CP-P163719-04-05-2017-1491408966691.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "financial inclusion data", "label": "VAGUE_DATA", "score": 0.6470186114311218, "start": 662, "end": 686, "probe_score": 0.0226, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Universal Financial Access (UFA) data portal", "label": "NAMED_DATA", "score": 0.5954482555389404, "start": 1651, "end": 1695, "probe_score": 0.3084, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on social development issues"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018079", "page": 24, "chunk": 0, "title": "Ethiopia - Women's Development Initiatives Project", "pdf_url": "https://documents.worldbank.org/curated/en/780341468746346948/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on social development issues", "label": "VAGUE_DATA", "score": 0.581004798412323, "start": 1670, "end": 1703, "probe_score": 0.333, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n\n### **Disability and** **MHPSS**\n\nMental health and psychosocial problems were\nsignificantly more often reported by individuals with\ndisabilities (51%, up from 42% in 2023) compared to\nthose without disabilities (21%, up from 17% in 2023).\nThis highlights the heightened vulnerability of\nindividuals with disabilities to mental health and\npsychosocial challenges, which are often\nexacerbated by social barriers such as limited\naccessibility, social exclusion, stigma, and a lack of\nsupport systems. There are clear variations across\ncountries, with Romania (61%) and Hungary (60%)\nreporting the highest percentage of problems\namong individuals with disabilities, while Moldova\n(29%) and Latvia (31%) reported the lowest\npercentage.\n\n\nThe overlap between certain mental health\nproblems, such as difficulties with memory,\nconcentration, or self-care, and the criteria used to\nassess disability further demonstrates the complex\ninterplay between these factors. The data also\nsuggests that structural and systemic differences\nbetween countries may influence outcomes, as\nreflected in the varying rates reported. These\nfindings highlight the critical need for inclusive\nMHPSS strategies that address the unique needs of\nindividuals with disabilities and provide targeted\ninterventions to reduce barriers and ensure\nequitable access to support. Additionally, further\nanalysis of country-specific contexts could help\nuncover underlying factors driving these disparities.\n\n\n\n**<u>% OF INDIVIDUALS WHO REPORTED EXPERIENCING</u>**\n**A MENTAL HEALTH OR PSYCHOSOCIAL PROBLEM BY**\n**DISABILITY STATUS AND COUNTRY**\n\n\nWith disability Without disability\n\n\n\nRegional\n\n\nRomania\n\n\nHungary\n\n\nPoland\n\n\nBulgaria\n\n\nEstonia\n\n\nLithuania\n\n\nSlovakia\n\n\nCzechia\n\n\nLatvia\n\n\nMoldova\n\n\n(N=17,934)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n**25**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000004", "page": 24, "chunk": 0, "title": "NAVIGATING HEALTH AND WELL BEING CHALLENGES FOR REFUGEES FROM UKRAINE   2nd Edition", "pdf_url": "https://local/jad_paddy_docs/navigating health and well-being challenges for refugees from ukraine - 2nd edition.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " challenge old assumptions”, American Journal of Public Health,\nvol. 104, No. 6 (2014), pp. e19-e26.\n35 cf. Monika Mitra and others, “Prevalence and characteristics of sexual violence against men with disabilities”, American Journal of Preventive Medicine,\nvol. 50, No. 3 (2016), pp. 311-317; Emily Lund and J. Vaughn-Jensen, “Victimisation of children with disabilities”, The Lancet, vol. 380, No. 9845 (2012), pp.\n867-869; Women’s Refugee Commission, ‘I See That It Is Possible’: Building Capacity for Disability Inclusion in Gender-based Violence Programming\nin Humanitarian Settings (May 2015).\n36 In the United States, for example, the lifetime prevalence of sexual violence other than rape is 40.2 per cent for gay males and 74.9 per cent for\nbisexual males, compared to 20.8 per cent for heterosexual males. Mikel Walters and others, The National Intimate Partner and Sexual Violence Survey\n(NISVS): 2010 Findings on Victimization by Sexual Orientation, (Atlanta, Georgia, Centers for Disease Control and Prevention, 2013). See also Emily\nRothman, Deinera Exner, and Allyson L. Baughman, “The prevalence of sexual assault against people who identify as gay, lesbian, or bisexual in the\nUnited States: a systematic review”, Trauma, Violence, & Abuse (2011); Ford Hickson and others, “Gay men as victims of nonconsensual sex”, Archives\nof Sexual Behavior, vol. 23, No. 3 (1994), pp. 281-294.\n37 United Nations Office for the Coordination of Humanitarian Affairs, “Discussion paper 2: the nature, scope and motivation for sexual violence against\nmen and boys in armed conflict”, (Paper presented at UNOCHA Research Meeting on the Use of Sexual Violence in Armed", "output": {"entities": {"named_data": ["National Intimate Partner and Sexual Violence Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001203", "page": 12, "chunk": 3, "title": "We Keep It in Our Hearts: Sexual Violence Against Men and Boys in the Syria Crisis", "pdf_url": "https://reliefweb.int/attachments/b8bb697e-67e5-3d05-8f95-a33c6944525f/StudyonSexualViolenceAgainstMenandBoysintheSyriaCrisis.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "National Intimate Partner and Sexual Violence Survey", "label": "NAMED_DATA", "score": 0.8407231569290161, "start": 845, "end": 897, "probe_score": 0.9938, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "3\n\n\n**2. Project development objective** (see Annex 1)\n\nThe objective of the project is to enhance the quality of education and to increase enrollment in\nprimary schools.\n\n\n**3. Key performance indicators:** (see Annex 1)\n\nThe key performance indicator is an increased number of students enrolled in grades 1-9, especially\namong girls.\n\n\nB. **STRATEGIC CONTEXT**\n\n\n**1. Sector-related Country Assistance Strategy (CAS) goal supported by the project** (see Annex 1)\n\n\n**Document number:** P 7403 DJI **Date of latest CAS discussion:** (scheduled for) 12/19/00\n\nThe CAS has been prepared in the context of the country's economic difficulties and deepening\npoverty. Despite Djibouti's relatively high nominal per capita income (US$790 versus an average of\nUS$510 for Sub-Saharan Africa, and US$100 for Ethiopia), Djibouti has one of the poorest social\nindicators in the world (poverty, illiteracy, maternal and infant mortality, and morbidity), according to\nthe UNDP Human Development Index, ranking 157th among 174 countries.\n\n\nThe Republic of Djibouti has very few natural resources and the economy is mainly dependent on the\nport, external financial assistance, the French military and associated services. However, with the\n\ndecreased amount of external assistance, and deepening structural problems, the country has suffered\neconomic stagnation over the past decade and a half. As a result, per capita Gross Domestic Product\n(GDP) declined by 50% in real terms since 1985. The switch of Ethiopia's transit traffic from Assab in\nEritrea to Djibouti in mid-1998 and the consequent four-fold increase in port traffic has opened new,\nas yet not fully exploited, opportunities for investment and growth. Djibouti's open economic policies\nand relative stability, characterized by a liberal trade policy and exchange system, which operates free\n\nof capital or", "output": {"entities": {"named_data": ["UNDP Human Development Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010759", "page": 6, "chunk": 0, "title": "Africa - Multi - Country HIV/AIDS Program for the Africa Region (Ethiopia and Kenya)", "pdf_url": "https://documents.worldbank.org/curated/en/287591468768313907/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNDP Human Development Index", "label": "NAMED_DATA", "score": 0.8519672155380249, "start": 959, "end": 987, "probe_score": 0.9988, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " NPTP|Component 1: Administration of the NPTP|Component 1: Administration of the NPTP|Component 1: Administration of the NPTP|Component 1: Administration of the NPTP|Component 1: Administration of the NPTP|3.89|3.89|3.89|3.89|3.89|\n|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|3.76|3.76|3.76|3.76|3.76|\n|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|0.55|0.55|0.55|0.55|0.55|\n|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|", "output": {"entities": {"named_data": [], "descriptive_data": ["Institutional Data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000047", "page": 6, "chunk": 13, "title": "Lebanon - Emergency National Poverty Targeting Program Project", "pdf_url": "http://documents.worldbank.org/curated/en/810511467987899324/pdf/PAD1030-ENGLISH-P149242-PUBLIC-FINAL-LEB-ENPTP-English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Institutional Data", "label": "DESCRIPTIVE_DATA", "score": 0.5252237915992737, "start": 1208, "end": 1226, "probe_score": 0.2474, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".029**|\n\n\nSource: Authors’ compilation from the DHS (2000, 2005, 2011 & 2014) data.\nNote: The p-values are for the F-test of the equality of rate ratios. The first part of the table is based on: _Is_\n\n_[(primary and none, in the latest survey) / (secondary and above, in the latest survey)] equal to [(primary and none_\n_in the Earlier Survey) / (secondary and above, in the Earlier Survey)]?_ Similarly, in the second part of the\ntable the quality of RR tests are: _Is [(rural, in the Latest Survey) / (urban, in the Latest Survey)] equal to [(rural,_\n_in the Earlier Survey) / (urban, in the Earlier Survey)]?_ Test is not applicable for NMR, IMR and U5MR\n\n\n\n\n\n\n\nTable 4b presents the education and spatial dimensions of relative gaps in health.\n\n\nThe results, in general, indicate that there has been narrowing relative gap by education\n\n\nand place of residence for all services and nutrition and mortality indicators. Nine out\n\n\nof ten indicators show a narrowing relative gap between rural and urban areas. The\n\n\n23", "output": {"entities": {"named_data": ["DHS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006554", "page": 24, "chunk": 2, "title": "wps7508", "pdf_url": "https://local/prwp/wps7508.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "DHS", "label": "NAMED_DATA", "score": 0.9298837780952454, "start": 48, "end": 51, "probe_score": 0.9975, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NGO programs for 4- and 5-year old children. The curriculum framework will be founded\n\non a child-centered, activity based pedagogical approach and the KG National Standards (to\nbe developed under subcomponent 3.1). Bank funds will be used for reproducing\neducational materials.\n\n32. **Subcomponent 2.2:** **Develop and deliver an effective teacher training program** **US$8.67 million (all GOE)**  - through the provision o f goods, training and consultant\nservices. This subcomponent will finance TA to support and assist CCIMD and CDIST in\nthe development o f an ECE teacher training program. Teacher training will be based on: (i)\nthe new KG curriculum; (ii) basic skills that are considered necessary in ECE; and (iii)\nresults from field work in model classrooms developed and delivered to five distinct groups\n\n  - f trainees (see Annex 4 for details). In addition, a “Train the Trainer” program will be\ndeveloped and delivered to 80 teacher trainers who will then be responsible for delivering the\nteacher training to all participants through face-to-face and video conferencing sessions.\n\n33. **Subcomponent 2.3:** **Link nutrition and health to ECE** - **US$18.34 million (GOE**\n**$2.0 million,** **WFP** **$16.34 million)**   - carrying out school nutrition and health programs\ntargeting KGs through the provision o f goods and consultants’ services. This subcomponent\naddresses the health and nutritional needs   - f young children and aims to improve their\nlearning potential. The subcomponent includes one major activity (with cost implications)\nand several other activities that are integrated into other components, which will be\nimplemented as per the Project Implementation Plan. The key activity o f the subcomponent\nis a school feeding program", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000040", "page": 13, "chunk": 0, "title": "Egypt - Early Childhood Education Enhancement Project", "pdf_url": "http://documents1.worldbank.org/curated/en/294331468744319926/pdf/311820EG.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2014|\n|Textbooks purchased||Number|Comments||||\n\n\n\n**<u>Data on Financial Performance (as of 26-Feb-2013)</u>**\n\n\n**<u>Financial Agreement(s) Key Dates</u>**\n\n|Project|Ln/Cr/Tf|Status|Approval Date|Signing Date|Effectiveness Date|Original Closing Date|Revised Closing Date|\n|---|---|---|---|---|---|---|---|\n|P110803|IDA-45700|Effective|31-Mar-2009|27-Aug-2009|04-Nov-2009|31-Jul-2012|31-Jul-2014|\n\n\n\n**<u>Disbursements (in Millions)</u>**\n\n|Project|Ln/Cr/Tf|Status|Currency|Original|Revised|Cancelled|Disbursed|Undisbursed|% Disbursed|\n|---|---|---|---|---|---|---|---|---|---|\n|P110803|IDA-45700|Effective|XDR|99.00|99.00|0.00|66.43|<br> 32.57|67.00|\n\n\n\n**<u>Disbursement Graph</u>**\n\n\nPage 5 of 6", "output": {"entities": {"named_data": ["Data on Financial Performance"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017963", "page": 4, "chunk": 1, "title": "Uganda - Post Primary Education and Training Program : P110803 - Implementation Status Results Report : Sequence 08", "pdf_url": "https://documents.worldbank.org/curated/en/772801468336057223/pdf/ISR-Disclosable-P110803-06-24-2013-1372078851834.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data on Financial Performance", "label": "NAMED_DATA", "score": 0.6740602850914001, "start": 56, "end": 85, "probe_score": 0.0591, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "02-02|||2023-12-01|2024-03-26|2024-02-13||2024-03-19||2024-11-14||\n|ET-MINT-381332-GO-RFP / T<br>he Supply & Installation of IT<br>Equipment for Integrating th<br>e National Databases|IDA / 68560|2. Digital government and c<br>onnectivity|Prior|Request for Propo<br>sals|Open - Internationa<br>l|Single Stage - Two E<br>nvelope||0.00|Under Imple<br>mentation|||||2023-10-15||2023-10-20||||2023-12-04||2024-02-16||2024-03-22||2025-03-22||\n|ET-MINT-381330-GO-RFP / S<br>upply, Delivery and Installati<br>on of IT Related Equipment f<br>or Federated System of Inter<br>net Exchange Points -Rebid|IDA / 68560|2. Digital government and c<br>onnectivity|Prior|Request for Propo<br>sals|Open - Internationa<br>l|Single Stage - Two E<br>nvelope||0.00|Under Imple<br>mentation|||||2023-10-05||2023-10-10||||2023-11-21||2024-02-03||2024-03-09||2024-11-04||\n|ET-MINT-387453-GO-RFP / D<br>evelopment, Supply and Conf<br>iguration of Online", "output": {"entities": {"named_data": [], "descriptive_data": ["e National Databases"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001663", "page": 4, "chunk": 2, "title": "Ethiopia - EASTERN AND SOUTHERN AFRICA- P171034- Ethiopia Digital Foundations Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099040524051081481/pdf/P17103416365140eb1b7831b9923b485c89.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "e National Databases", "label": "DESCRIPTIVE_DATA", "score": 0.5546319484710693, "start": 163, "end": 183, "probe_score": 0.0006, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_5.2._ _Prediction_\n\n\nIn order to compare the predictive performance associated with the various prior choices, we turn\nnow to the task of predicting the observable, growth, given the regressors. Of course, the predictive\ndistribution is also derived through model averaging, as explained in, _e.g._, FLS. As a measure of\nhow well each model predicts the retained observations, we use the log predictive score, which is\na strictly proper scoring rule, described in FLS. In the case of i.i.d. sampling, LPS can be given an\ninterpretation in terms of the Kullback-Leibler divergence between the actual sampling density and\nthe predictive density (see Fern´andez _et_ _al._ 2001a), and smaller values indicate better prediction\nperformance.\n\n\nWe compare the predictions based on: _(i)_ BMA, _(ii)_ the best model (the model with the highest\nposterior probability), _(iii)_ the full model (with all _k_ regressors), and _(iv)_ the null model (with only\nthe intercept).\n\n\nPanel A in Table 5 summarizes our findings for the FLS data: the entries indicating “best” or\n“worst” model or how often a model is beaten by the null are expressed in percentages of the 100\nsamples for that particular prior setting.\n\n\n_(i)_ BMA—The predictive performance of BMA is much superior to that of the other procedures—\n\nwhich corroborates evidence in _e.g._ Raftery _et_ _al._, 1997, Fern´andez _et_ _al._, 2001a and FLS. It\nis never the worst predictor and leads to the best predictions in more than half of the sampled\ncases (with the exception of the prior with fixed _θ_ = 0 _._ 5 and", "output": {"entities": {"named_data": ["FLS data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003445", "page": 20, "chunk": 0, "title": "wps4238", "pdf_url": "https://local/prwp/wps4238.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "FLS data", "label": "NAMED_DATA", "score": 0.8424618244171143, "start": 1018, "end": 1026, "probe_score": 0.969, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", financial management, procurement, and\nmonitoring and evaluation staff (from the MOHE and other government agencies). Additional personnel will be\nrecruited if needed to ensure sufficient capacity to implement the project.\n\n\n48. **A Project Operational Manual (POM), which will guide project implementation, will be developed no later**\n**than 30 days after loan effectiveness, in a manner satisfactory to the Bank** . The POM will describe detailed\narrangements and procedures for the implementation of the project, such as responsibilities of the PMU operational\nsystems and procedures, project organization structure, office operations and procedures, financial and accounting\nprocedures (including funds flow and disbursement arrangements), procurement procedures, and implementation\narrangements. The POM will include: (i) description of COVID-19 vaccine deployment activities to ensure inclusive,\nsafe, efficient and effective deployment following a ‘whole of Iraq’ approach; (ii) environmental and social\nrequirements; (iii) personal data protection measures; and (iv) fiduciary (procurement and financial management)\nrequirements. The project will be carried out in accordance with the arrangements and procedures set out in the\nPOM, which can be amended from time to time, provided all modifications are agreed upon with the World Bank in\nwriting prior to any changes taking effect. The POM will also include a Vaccine Delivery and Distribution Manual\n(VDDM) to define the operational aspects of vaccine deployment, including the details related to the distribution of\nvaccines eligible for retroactive financing that have already been deployed to enable third-party verification.\n\n49. Large volumes of personal data, personally identifiable information and sensitive data are likely to be collected\nand used in connection with the management of the COVID-19 outbreak under circumstances where measures to\nensure the legitimate, appropriate and proportionate use and processing of that data may not feature in national law\nor data governance regulations or be routinely collected and managed in health information systems. In order to guard\nagainst abuse, the project will", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["personal data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000058", "page": 29, "chunk": 1, "title": "Iraq - COVID-19 Vaccination Project", "pdf_url": "http://documents1.worldbank.org/curated/en/395791632832896615/pdf/Iraq-COVID-19-Vaccination-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "personal data", "label": "VAGUE_DATA", "score": 0.5810526013374329, "start": 1714, "end": 1727, "probe_score": 0.0279, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "KE-MEACLSS-145074-NCRFQ / The State Department\nfor Labour intends to procure\na consultant to design\ninfographics for the Kenya\nLabour Market Information\nSystem (KLMIS)\n\n\n\nIDA / 58120 Improving labor marketinformation Post\n\n\n\nIndividual\nConsultant\nSelection\n\n\n\nOpen\n\n\n\n4,000.00 0.00 UnderImplementation 2020-03-29 2020-06-22 2020-05-17 2020-06-07 2020-07-12 2021-01-08\n\n\nPage 4", "output": {"entities": {"named_data": ["Kenya\nLabour Market Information\nSystem"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009692", "page": 7, "chunk": 0, "title": "Kenya - AFRICA EAST- P151831- Kenya Youth Employment and Opportunities - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/217561607358085631/pdf/Kenya-AFRICA-EAST-P151831-Kenya-Youth-Employment-and-Opportunities-Procurement-Plan.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Kenya\nLabour Market Information\nSystem", "label": "NAMED_DATA", "score": 0.5861690044403076, "start": 121, "end": 159, "probe_score": 0.0182, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Table A1: Country Coverage and Sample Size of the Survey on Gender Equality at Home\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Region|Country|Female|Male|Region|Country|Female|Male|Region|Country|Female|Male|\n|---|---|---|---|---|---|---|---|---|---|---|---|\n|**Europe &**<br>**Central Asia**|Albania|841|1,065|**Middle East &**<br>**North Africa**|Algeria|1,787|1,793|**Latin America**<br>**& Caribbean**|Argentina|1,533|922|\n|**Europe &**<br>**Central Asia**|Armenia|1,157|808|808|Bahrain|800|795|795|Bolivia|1,270|1,154|\n|**Europe &**<br>**Central Asia**|Austria|1,223|1,050|1,050|Egypt|1,435|2,403|2,403|Brazil|2,917|1,960|\n|**Europe &**<br>**Central Asia**|Azerbaijan|1,097|1,019|1,019|Iraq|2,221|2,030|2,030|Chile|1,318|941|\n|**Europe &**<br>**Central Asia**|Belarus|1,503|939|939|Israel|1,113|964|964|Colombia|2,646|2,031|\n|**Europe &", "output": {"entities": {"named_data": ["Survey on Gender Equality at Home"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001534", "page": 50, "chunk": 0, "title": "idu1bf06cd191699f1462f18236168ed5e5295bf", "pdf_url": "https://local/prwp/idu1bf06cd191699f1462f18236168ed5e5295bf.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Survey on Gender Equality at Home", "label": "NAMED_DATA", "score": 0.7745264172554016, "start": 50, "end": 83, "probe_score": 0.8679, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " youth, defined as youth between the ages of 18 and 29, with no**\n**more than secondary education and who were unemployed or working in vulnerable jobs.** As discussed, employment\nrates among this group—especially youth under age 25—were more than twice those of older workers. In addition, youth\nheld a significantly higher incidence of low-productivity, low-paying jobs. To address potential difficulties in verifying the\neducation level of youth, chiefs and assistant chiefs were involved in the verification process, which helped limit inclusion\nerrors **.** <sup>**54**</sup> [^54: The Tracer Study for Cycle 1 youth showed that 16 percent of youth had more than high school education, while the BDSs/grants\nbaseline for Cycle 4 youth showed 7 percent had more than high school education.]\n\n\n47. **Special effort was made to benefit special-needs and hard-to-serve youth. Minimum quotas were established**\n**for people living with disabilities to ensure their participation. In addition,** the Project’s design included a line of action\nfocusing on the hard-to-serve youth. Specifically, the Innovation Challenge (Subcomponent 2.2) supported a\ncompetition—the “Future Bora Initiative”—among social enterprises for innovative programs aimed at benefiting\nparticularly vulnerable youth, such as single mothers, “street children”, children with disabilities, and youth living in\nconflict areas. A total of 1,931 vulnerable youths benefited from programs implemented by four social enterprises with a\nfocus on: (i) waste collection and recycling involving homeless youth—the so-called “street children,” and including\nprovision of health and daycare services; (ii) hydroponic farming; (iii) single mothers to engage in community work and\nbusiness creation; and (iv) farming involving children with disabilities.\n\n\n50 Building primarily upon existing labor market statistics and institutional agreements for the exchange of information with government\nand non-government actors, the KLMIS tracks key labor market indicators in three main", "output": {"entities": {"named_data": [], "descriptive_data": ["labor market statistics"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001454", "page": 26, "chunk": 1, "title": "Kenya - Youth Employment and Opportunities Project (KYEOP)", "pdf_url": "https://documents.worldbank.org/curated/en/099032224040028003/pdf/BOSIB-3a6f785a-0ee0-47ef-a953-93e14083da65.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "labor market statistics", "label": "DESCRIPTIVE_DATA", "score": 0.6817709803581238, "start": 1851, "end": 1874, "probe_score": 0.2893, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " emergency procedures while deferring exact projects/roads selection\nand associated safeguards to implementation;\n\n2. Agree on the first‐year road works program to speed up implementation;\n\n3. Include the purchase of necessary equipment which can be implemented quickly; and\n\n4. Introduce retroactive financing to support timely project implementation and initiate\nprocurement activities and required studies.\n\n  - **Deliver good quality infrastructure and asset management practices:**\n\n1. Prepare procurement strategy and packages to ensure a wider participation of local contractors\n(hence, broader benefits in different areas/communities) while maintaining well qualified\ncontractors to guarantee proper rehabilitation works in accordance with existing Lebanon’s high\nroad rehabilitation design standards;\n\n2. Introduce proper and objective road prioritization measures through the visual survey of the\nnetwork’s condition and safety, which will also later inform the creation of a new and integrated\nroad asset management system for Lebanon;\n\n3. Introduce road safety and climate resilient improvements to improve existing road design and\nconstruction standards and practices in Lebanon; and\n\n4. Introduce routine maintenance contracts as an important and efficient asset preservation\nmeasure (including possibly the piloting of performance‐based contracts).\n\n  - **Create significant number of short‐term jobs for Lebanese and Syrians:**\n\n      - Select road sections with required civil works such as drainage and slope stabilization structures\nto increase the labor content of contracts;\n\n\nPage 22 of 90", "output": {"entities": {"named_data": [], "descriptive_data": ["visual survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 25, "chunk": 1, "title": "Lebanon - Roads and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/210611486651815142/pdf/Lebanon-Roads-Employment-PAD-P160223-01262017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "visual survey", "label": "DESCRIPTIVE_DATA", "score": 0.5210471749305725, "start": 886, "end": 899, "probe_score": 0.0002, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "statelessness-statistics-iross)</u>\n<u>[on Statelessness Statistics (IROSS)](https://egrisstats.org/recommendations/international-recommendations-on-statelessness-statistics-iross)</u> by the UN\nStatistical Commission in March 2023. These\nrecommendations help guide the production of higherquality, harmonized statistics that are consistent and\ncomparable across countries.\n\n\n\n\n**•** **20 European countries** (Albania, Austria, Czech Republic, Croatia, Denmark, Estonia, Finland, Iceland,\nIreland, Lithuania, Malta, Norway, Poland, Portugal, Serbia, Slovakia, Sweden, Switzerland, Ukraine and\nthe United Kingdom) have conducted mapping studies or surveys to better understand the size and\nprofile of the stateless population in their territory.\n\n- The 2022 censuses in **Kyrgyzsta** n and **Tajikistan** included questions related to stateless people.\n\n**•** **Panama’s** 2023 census included questions about birth registration, and the results have allowed mapping\npopulations that might be at risk of statelessness or of undetermined nationality.\n\n- The 2019 Cartography of Persons at Risk of Statelessness in **Cote d’Ivoire** (CAPRA) provided a basis\nfor reporting updated and more accurate official figures for stateless persons and persons at risk of\nstatelessness.\n\n**•** **Mozambique** is the process of conducting a qualitative study on statelessness in line with the pledge\nmade in the 2019 High-level Segment on statelessness. The study is expected to be finalized by the end\nof 2024.\n\n- Qualitative studies on statelessness have been carried out in countries including Botswana, Burkina\nFaso, Democratic Republic of the Congo, Mali, and South Africa, helping inform identification and\ndocumentation efforts, as well as advocacy and resource mobilization activities.", "output": {"entities": {"named_data": ["2019 Cartography of Persons at Risk of Statelessness"], "descriptive_data": ["2022 censuses", "2023 census"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000303", "page": 40, "chunk": 1, "title": "The #IBelong Campaign: A Decade of Action to End Statelessness, 2014-2024", "pdf_url": "https://reliefweb.int/attachments/23f4420a-4cd3-4691-8d1c-038d8ed6ed50/web3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2022 censuses", "label": "DESCRIPTIVE_DATA", "score": 0.7170379757881165, "start": 753, "end": 766, "probe_score": 0.8916, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2023 census", "label": "DESCRIPTIVE_DATA", "score": 0.5721027851104736, "start": 873, "end": 884, "probe_score": 0.9063, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2019 Cartography of Persons at Risk of Statelessness", "label": "NAMED_DATA", "score": 0.7790239453315735, "start": 1057, "end": 1109, "probe_score": 0.8897, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "COMMUNITY ENGAGEMENT SURVEY REPORT\n\n## Methodology\n\n##### Who we spoke to?\n\nUNHCR interviewed over 3,000 displaced Yemenis, refugees, asylum seekers, and host community\n\nmembers across the country.\n\n\n\n\n###### 30%\n\n\n\nDisplaced Yemenis and host communities\n\n\n\n\n##### 27%\n\nof refugees and asylum\n\nseekers respondents\n\nwere men and boys\n\n\n##### 42%\n\nof IDPs respondents\n\nwere women and\n\ngirls\n\n\n##### 58%\n\nof IDPs respondents\n\nwere men and boys\n\n\n##### 73%\n\nof refugees and asylum\n\nseekers respondents\nwere women and girls\n\n\n\nUNHCR / September 2020 3", "output": {"entities": {"named_data": ["COMMUNITY ENGAGEMENT SURVEY REPORT"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000233", "page": 2, "chunk": 0, "title": "Understanding how UNHCR engages with communities in Yemen: Community engagement survey report (September 2020)", "pdf_url": "https://reliefweb.int/attachments/19080eda-831f-39b4-8c26-c68db9cf71b5/CWC%20survey%20report%20Final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "COMMUNITY ENGAGEMENT SURVEY REPORT", "label": "NAMED_DATA", "score": 0.7238330245018005, "start": 0, "end": 34, "probe_score": 0.9602, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a v\nManufacturIng 5 7 3.7 4 7 5 0 / s \\\\t oo  Services 475 272 190 201\n\nPrfvate consumpffon 90 7 81 9 938 95 1 20\nGeneral govemment consumption 7 0 9 6 146 17.2 =c ~GDFDl\nImpons of goods and servrcea 39 7 23 6 33 4 373 -3GW_G_____\n\n\n_(average_ _annual growth)_ 1981-9 1991401 2000 2001 Growth ot exports and Imports (%)\n\nAgrutumre -0 6 -2 6 2 2 3 8 oo\nIndustry 0.1 -41 51 5 6 s0\nManUnacturIng 6.9 . .\nServices -5 7 -5.4 4 0 51 \nPrivate oonsumpffon -2 0 -19 10 4 100 -50\nGeneral govemment consumption -5.1 -0 2 41.3 27 9 -100\nGross domestic Investment -06 3 0 50 - EOpois -tr-ports\nImports of goods and services -2 2 -151 85 0 61 3\n\n\nNote 2001 data are pretirrinary eastliates\n'The diamonds show four Key Indicators in the country (in bold) conipared with itS income-group average It data are missing, the diantond wiUt be rrconrrlte\n\n\n-56", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["2001 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013622", "page": 60, "chunk": 2, "title": "Ethiopia - Emergency Drought Recovery Project", "pdf_url": "https://documents.worldbank.org/curated/en/478481468771265056/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2001 data", "label": "VAGUE_DATA", "score": 0.7082152366638184, "start": 639, "end": 648, "probe_score": 0.0183, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nincrease in Polish citizens' employment\nrates by 0.5% and a decrease in the\nunemployment rate by 0.3%, in the\npreferred specification with dummy\nvariables for all quarters. All results are\nstatistically significant at a 0.01 level.\n\n\n\n**Chart 26. Polish citizens employment rate** **Chart 27. Polish citizens unemployment rate**\n\nEurostat survey data, 20-64 age group Eurostat survey data, 20-64 age group\n\n\n\n3.6%\n\n\n\n\n\n83.8%\n\n\n\n83.6%\n\n\n\n\n\n83.2%\n\n\n\n**Chart 28. Effect of a 1 pp. change in employment share of Ukrainian refugees on**\n\nPanel model of all 380 poviats quarterly data from Q1 2022 to Q2 2024. Results are statistically significant at a 0.01 level.\n\n\nPolish citizens employment rate Unemployment rate\n\n\n1.0 1.0\n\n\n0 0\n\n\n-1.0 -1.0\n\n\n-2.0 -2.0\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n2021-Q2 2022-Q2 2023-Q2 2024-Q2 2021-Q2 2022-Q2 2023-Q2 2024-Q2\n\n\n\nSeasonal Quarterly No time Seasonal\ndummies dummies dummies dummies\n\n\n\nQuarterly\ndummies\n\n\n\nNo time\ndummies\n\n\n\nSource: Deloitte own elaboration based\nof Eurostat data (Labour Force Survey).\n\n\n38\n\n\n\nMales Source: Deloitte own elaboration based Males\n\n\n\nSource: Deloitte own elaboration based\nof Eurostat data (Labour Force Survey).\n\n\n\nFemales of Eurostat data (Labour Force Survey). Females\n\n\n\nSource: Deloitte own elaboration based on GUS and ZUS data. All continuous variables have been regressed in first differences to account for non-stationarity Polish\ncitizens employment rates and registered unemployment rates. For details see the Online Technical Appendix.\n\n\n39", "output": {"entities": {"named_data": ["Eurostat survey data", "Eurostat data", "Labour Force Survey", "GUS", "ZUS data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 19, "chunk": 2, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Eurostat survey data", "label": "NAMED_DATA", "score": 0.6319754123687744, "start": 331, "end": 351, "probe_score": 0.9506, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Eurostat data", "label": "NAMED_DATA", "score": 0.5051237344741821, "start": 989, "end": 1002, "probe_score": 0.9995, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Labour Force Survey", "label": "NAMED_DATA", "score": 0.5443200469017029, "start": 1004, "end": 1023, "probe_score": 0.9886, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "GUS", "label": "NAMED_DATA", "score": 0.6635273098945618, "start": 1271, "end": 1274, "probe_score": 0.9985, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "ZUS data", "label": "NAMED_DATA", "score": 0.7076042294502258, "start": 1279, "end": 1287, "probe_score": 0.9836, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEnhancing Shared Prosperity through Equitable Services (P151432)\n\n\n\n\n\n\n\n\n\n\n\n\n\n|DLI IN01065473 ACTION<br>DLI 26|DLI 12.1 Improve nutrition services|Col3|Col4|Col5|\n|---|---|---|---|---|\n|**Type of DLI**|**Scalability**|**Unit of Measure**|**Total Allocated Amount (USD)**|**As % of Total Financing Amount**|\n|Intermediate Outcome|No|Text|50,000,000.00|0.01|\n|**Period**<br>Baseline|**Value**<br>The existing Woreda level nutrition coordination is<br>not functioning well; frontline service providers are<br>not adequately trained on nutrition BCC; 58%<br>mothers with children 0-23 months have had<br>contact with HEWs in the last 3 months as per the<br>IFPRI Impact Assessment from January 2016|**Value**<br>The existing Woreda level nutrition coordination is<br>not functioning well; frontline service providers are<br>not adequately trained on nutrition BCC; 58%<br>mothers with children 0-23 months have had<br>contact with HEWs in the last 3 months as per the<br>IFPRI Impact Assessment from January 2016|**Allocated Amount (USD)**|**Formula**|\n|2020|Woreda level coordination platform is in place,<br>consistent with agreed TOR, in PSNP Woredas|Woreda level coordination platform is in place,<br>consistent with agreed TOR, in PSNP Woredas|50,000,000", "output": {"entities": {"named_data": ["IFPRI Impact Assessment"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:006929", "page": 30, "chunk": 0, "title": "Disclosable Restructuring Paper - Enhancing Shared Prosperity through Equitable Services - P151432", "pdf_url": "https://documents.worldbank.org/curated/en/099525005132219434/pdf/P15143205eae130290a71d01be2f6f9ac10.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "IFPRI Impact Assessment", "label": "NAMED_DATA", "score": 0.6713664531707764, "start": 672, "end": 695, "probe_score": 0.9985, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "“normal” growth (the pattern of observed weight gain) are added. This adjustment uses the 2 kilocalories per gram of tissue synthesis suggested in\nFAO (2001) combined with the average annual weight gain for each age and\ngender in the National Nutrition Monitoring Bureau data. Adjustments for\nthe additional energy required by pregnant or nursing mothers are difficult\ndue to lack of data, but energy requirements of infants themselves can be\nincluded. REE for infants (children under age 1) is set such that male babies\nhave TEE of 650 calories and female babies have TEE of 600 calories, consistent with the (Indian Council of Medical Research 2009) report. Second,\nvalues outside of the 1% of the tails of the distribution are replaced with the\npercentile cutoff values prior to estimation.\n\n#### **B Estimation of Activity Levels (AL)**\n\n\nAppendix Table S.2 lists the time-use survey activity codes and headings, the\naverage share of time spent on the activity by rural and urban individuals,\nand the matched activity factors from FAO (2001). Estimates are not very\nsensitive to using alternative sources of activity factors, such as those developed for richer countries that tend to contain more detailed classifications\nof sports and exercise activities. Appendix Table S.2 includes the matched\nactivities and activity factors from (Ainsworth et al. 2000) (used by (Cutler\net al. 2003)) for comparison, and Appendix Table S.2 Panel C shows that\nthe difference in activity levels using the measure used in the text and this\nalternative set of activity factors is quite small.\n\nThe estimates reported in the text make two additional assumptions\nabout activity factors to derive activity levels. First, since the time-use data\nreports time spent on “related” or “other” activities within certain headings,\none must assign an activity factor in these cases. The activity factor used in\nthis case is equal to the average for the activities matched under the same\nheading.", "output": {"entities": {"named_data": ["National Nutrition Monitoring Bureau data"], "descriptive_data": ["time-use survey"], "vague_data": ["time-use data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000131", "page": 22, "chunk": 0, "title": "caloric intake and energy expenditures in india", "pdf_url": "https://local/prwp/caloric-intake-and-energy-expenditures-in-india.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "National Nutrition Monitoring Bureau data", "label": "NAMED_DATA", "score": 0.8387621641159058, "start": 234, "end": 275, "probe_score": 0.9887, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "time-use survey", "label": "DESCRIPTIVE_DATA", "score": 0.7703216075897217, "start": 872, "end": 887, "probe_score": 0.9298, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "time-use data", "label": "VAGUE_DATA", "score": 0.6698086261749268, "start": 1716, "end": 1729, "probe_score": 0.8088, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "---|---|---|\n|**1: Roads**<br>**Rehabilitation and**<br>**Maintenance**|Drainage structures and culverts; retaining<br>walls; routine maintenance.|184.6<br>|50<br>|0|\n|**2: Improving Road**<br>**Emergency**<br>**Response Capacity**|Increased MPWT’s capacity to deal with road<br>emergency works; purchase of necessary<br>equipment.|7.5<br>|7.5<br>|0|\n|**3.1: Strengthen**<br>**Road Asset**<br>**Management**|The creation of a road asset database for<br>Lebanon, and the revision of design and<br>maintenance standards to reflect changing<br>climate conditions.|2 <br>|2|0|\n|**3.2: Support the**<br>**planning and**<br>**implementation of**<br>**road safety**|n.a|2 <br>|0|0|\n|**3.3: Support**<br>**Planning and Design**<br>**Studies**|Finance necessary studies to produce<br>planning and design documents in the<br>transport sector, particularly public", "output": {"entities": {"named_data": [], "descriptive_data": ["road asset database"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 34, "chunk": 1, "title": "Lebanon - Roads and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/210611486651815142/pdf/Lebanon-Roads-Employment-PAD-P160223-01262017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "road asset database", "label": "DESCRIPTIVE_DATA", "score": 0.8678354620933533, "start": 426, "end": 445, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "up>17</sup> Youth-owned firms are more likely\nto receive a loan than older-owned firms. Interestingly, women are more likely to have had a bank loan than\nmen, though the difference in means is not statistically significant. However, younger women are almost twice\nas likely to have had a business loan than older women and older men (9 versus 5%). Having a line of credit or a\ncredit facility from suppliers is more than four times as likely a form of financing as getting a loan from a bank\nacross all firms. <sup>18</sup> Both younger men and younger women are more likely to receive supplier credit than older\nentrepreneurs (24 relative to 16% for women-owned firms, 40 relative to 23% for men-owned firms).\n\n\nIn terms of relationships with value chain partners, youth-owned firms are more likely to have relationships with\nall four types of value chain partners than older-age-owned firms. In particular, younger women-owned firms\nare about three times as likely to have relationships with large suppliers and large buyers than older womenowned firms. Interestingly, while men-owned firms are more likely to have relationships with large suppliers,\n\n\n17 Based on the underlying unweighted data, only 5.0% or 26 firms reported ever having received a bank loan.\n18 This is particularly surprising since the loan question refers to ever having had a loan while the supplier credit question is about current\nongoing financing.\n\n\n14", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["unweighted data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000272", "page": 15, "chunk": 3, "title": "digital technology uses among informal micro sized firms productivity and jobs outcomes in senegal", "pdf_url": "https://local/prwp/digital-technology-uses-among-informal-micro-sized-firms-productivity-and-jobs-outcomes-in-senegal.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "unweighted data", "label": "VAGUE_DATA", "score": 0.673588216304779, "start": 1182, "end": 1197, "probe_score": 0.9438, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " policies can im\nprove technology adoption by FTM and, in turn, reduce the productivity gap. Much at\ntention has been given to policies tackling the gender digital divide, mainly focusing on\n\nincreasing women’s participation in STEM and high technology sectors, fostering digital lit\n\n26", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001468", "page": 28, "chunk": 3, "title": "idu19d64fdd31725014bd11a04b1ee26fb7aba61", "pdf_url": "https://local/prwp/idu19d64fdd31725014bd11a04b1ee26fb7aba61.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " January 1, 2012.\n\n\nThe WTO commitments schedule became publicly available from the WTO\n\n\nafter the Russian Federation was formally invited to join the WTO on December 16,\n\n\n2011. The Russian Federation is scheduled to implement its commitments to the\n\n\nWTO in stages, beginning with the summer of 2012, with the longest transition period\n\n\neight years after accession, or 2020. We calculate the impact of the phased\n\n\nimplementation of the commitments, starting from the impact of the commitments in\n\n\n2012.\n\n\ncm3; and 870324 is for cylinder capacities exceeding 3 000 cm3. Within each six digit category, we\ntake a simple average of the lower and upper bounds as the expected value of the cylinder capacity, i.e.,\nfor 870321 we have 500 (0+1000)/2=500). Therefore, the following expected engine volumes apply:\n500 cm3 for 870321, 1250 cm3 for 870322, 2250 cm3 for 870323, and 3000 cm3 for 870324. Then we\nknow that all ten digit tariff lines with the same 6 digit code have this engine capacity and we can apply\nthe specific tariff to the numbers of cars in the import data based on the engine capacity that applies to\nthese ten digit tariff lines from the tariff schedule.\n\n[11 This document is available from the website of the Customs Union, http://www.tsouz.ru/.](http://www.tsouz.ru/)\n\n\n6", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["import data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005327", "page": 7, "chunk": 1, "title": "wps6161", "pdf_url": "https://local/prwp/wps6161.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "import data", "label": "VAGUE_DATA", "score": 0.7354282736778259, "start": 1064, "end": 1075, "probe_score": 0.0119, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "br>wellhead construction, suppl<br>y, and installation of casings|IDA / 64450|Rural Water Supply, Sanitati<br>on, and Hygiene (Rural WAS<br>H)|Post|Request for Bids|Open - National|Single Stage - One<br>Envelope||||112,860.00|106,323.15|Completed|||||2020-08-27|2021-01-05|2020-09-01|2021-01-13|||2020-10-01|2021-02-16|2020-10-31|2021-03-10|2020-11-24|2021-04-13|2021-03-2<br>4|2021-03-2<br>4|\n|ET-AMHARA WIEDB-181834-<br>CW-RFB / Drilling of 14 (Four<br>teen) Shallow Wells (SWs) to<br>a maximum of 70m in WaSH<br>CWA II program in Maekela<br>wi Gondar Zone CHILGA 2 &<br>LAY ARMACHICHO Woredas.<br>The work also includes wellh<br>ead construction, supply, an<br>d installation of casings and|IDA / 64450|Rural Water Supply, Sanitati<br>on, and Hygiene (Rural WAS<br>H)|Post|Request for Bids|Open - National|Single Stage - One<br>Envelope||||143,640.00|136,030.65|Completed|||||2020-08-27|2021-01-05|2020-09-01|2021-01-13|||2020-10-01|2021-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000692", "page": 2, "chunk": 8, "title": "Ethiopia - EASTERN AND SOUTHERN AFRICA- P167794- One WASH?Consolidated Water Supply, Sanitation, and Hygiene Account Project (One WASH?CWA) - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099021326023627503/pdf/P167794-5ee20add-e36b-4291-a9a4-74cd01a5d661.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " social safeguards compliance, including through technical assistance\nprovided by the mobile teams as well as pre-identified training sessions for LG staff.\n\n**F.** **Environment (including Safeguards)**\n\n\n79. The project will be implemented at the national level in 100 LGs selected according to a set\nof criteria established with the Government. The Government and the European Union are cofinancing the operation, however, the Bank’s safeguards policies will apply to the project as a\nwhole and to all sub-projects. The project is rated as a Category B project as it is expected that\nthe sub-projects’ proposed activities will have limited negative impacts on the environment.\nFurther, any such impacts are anticipated to be site-specific.\n\n80. OP 4.01 (Environmental Assessment) has been triggered. The overall environmental impact\nof the project is expected to be positive. Significant positive impact on the natural and\nsocioeconomic environments is likely to result from the implementation of activities on the part\nof participating LGs. By developing institutional capacity and environmental and social\nmanagement systems, the project will help improve the capacity of the LGs to deliver quality\nservices. While it can be expected that the majority of investments with environmental impacts\nwill include civil works, the precise nature, size, location, and characteristics of the sub-projects\nwill only be determined during project implementation. The Government has therefore prepared\nan Environmental and Social Management Framework (ESMF) which was consulted upon and\ndisclosed in-country and at the World Bank’s Infoshop on April 16, 2013. The ESMF provides a\nstep-by-step process for sub-project selection that will ensure that all investment are adequately\nscreened for their potential environmental and social impacts, and that correct procedures are\nfollowed to mitigate and minimize any potential negative impacts arising from these impacts.\nAny Environmental Assessment (EA) or Environmental Management Plan (EMP) that may be\n\n\n22", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000166", "page": 36, "chunk": 1, "title": "Mauritania - Local Government Development Program Project", "pdf_url": "http://documents1.worldbank.org/curated/en/943421468056371471/pdf/760530PAD0P127010Box377322B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**_Figure E.3. Comparison of average annual TFP growth rate weighted by real GDP using PWT 9.0 and WDI for_**\n**_developing countries by region_**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n**2)** **Statistical analysis**\n\n\n_<u>The relative contribution of the main determinants to total factor productivity</u>_\n\n\nWe conduct the variance decomposition of TFP growth rates using PWT 9.0 and WDI as primary sources and\n\n\ncompare the results. The list of developing countries with available TFP growth rates is different between PWT\n\n\n9.0 and WDI; therefore, we conduct the analysis for the full sample of countries for each source and for the\n\n\ncommon sample (60 developing and 21 OECD countries). Figure E.4 shows, for the OECD group, the largest\n\n\ncontributor is market efficiency using PWT 9.0 and innovation using WDI for the recent decade, and the smallest\n\n\ncontributor is infrastructure using the both data sources. For the developing countries, the largest contributor is\n\n\ninstitutions in the period 1985─94; however, in the period 2004─14, it varies among education, market efficiency,\n\n\nand institutions depending on a set of countries and data sources. The common feature among the four sets of\n\n\nresults for the developing countries is that innovation and infrastructure have a lower contribution compared to\n\n\nother determinants in the last decade.\n\n\n66", "output": {"entities": {"named_data": ["PWT 9.0", "PWT 9.0", "PWT 9.0"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001996", "page": 67, "chunk": 0, "title": "productivity growth patterns and determinants across the world", "pdf_url": "https://local/prwp/productivity-growth-patterns-and-determinants-across-the-world.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PWT 9.0", "label": "NAMED_DATA", "score": 0.5080751180648804, "start": 87, "end": 94, "probe_score": 0.9712, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PWT 9.0", "label": "NAMED_DATA", "score": 0.5321370363235474, "start": 387, "end": 394, "probe_score": 0.9093, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PWT 9.0", "label": "NAMED_DATA", "score": 0.5227113962173462, "start": 796, "end": 803, "probe_score": 0.9458, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 1\nPage 3 **of** 3\n\n\n**Key Performance**\n**Hierarchy of Objectives** **Indicators** **Monitoring &** **Critical Assumptions**\n**Evaluation**\n**Project Components / Sub-** **Inputs: (budget for each** **Project reports:** **(from Components to**\n**components:** **component)** **Outputs)**\n\n\nImprove Access: provision of US$5.8 million MOE monitoring Capacity within the\nclassrooms. Number of schools reports construction sector to handle\nconstructed per year; the volume of school\nimproved design and construction.\nefficiency.\nCreate Conditions for Quality US$1.1 million School surveys; student Good textbook distribution;\nImprovement: access to Number of textbooks per learning achievement management training\neducational materials; student; autonomous school reports (MOE effectiveness; Government\nimproved school management; salaries paid on monitoring reports). commitment to paying\nmanagement; teacher a timely basis teacher salaries.\nmotivation.\n\n\nImprove Government's US$4.1 million Project monitoring Purpose and integrity\nCapacity to Manage Sector: Project effectively reports; study reports. maintained within project\ncapacity building within the implemented and management; stakeholder\nMOE and its related services; management improved; participation in pilot studies.\npilot studies. reports with implementable\nresults.\n\n\n**Annexe 1 Attachment: Program and Project Monitorin** **Tar** **ets**\n**_Year_** _2001-02 2002-03_ **_2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10_**\nPrimary Enrollment Boys 19,125 21,506 24,300 26,627 29,867 31,696 34,457 37,217 40,129\nPrimary Enrollment Girls 14,875 17,994 20,", "output": {"entities": {"named_data": [], "descriptive_data": ["School surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000170", "page": 31, "chunk": 0, "title": "Albania - Water Supply Urgent Rehabilitation Project", "pdf_url": "http://documents1.worldbank.org/curated/en/949361468742522118/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "School surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8726161122322083, "start": 577, "end": 591, "probe_score": 0.0853, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " The sustainability of the sanitation measures will be carefully assessed from the point of view\nof good practices, cost effectiveness, affordability and the Djibouti water shortage environment.\n\n\n6. **Social**\n\n\n_6.1 Summarize key social issues relevant to the project objectives, and specify the project's social_\n_development outcomes._\n\n\nDjibouti is a small country and many key social issues were identified in the 1997 Poverty\n\nAssessment. The issues raised included the percentage of the population classified as poor in 1996\n(50-80% reaching the upper-bound when refugees, nomads and homeless are taken into account); large\nnumbers of refugees, nomads, and homeless populations; the majority of the poor live in urban areas\n(85%) even if the incidence of extreme poverty is overwhelmingly rural. Urban households can take\nadvantage of safety nets derived from the commodity market and services, and job opportunities are\nnot available in rural areas. The key problems faced by children include: (a) the high number of street\nchildren who have fled war ravaged Somalia and Ethiopia; (b) late entrance into school by poorer\nchildren (one out of four starts school at age 9 and leaves school at age 14); (c) health issues (diarrhea\n\nand malnutrition) are a leading cause of death for children under age 5. Other problems affecting the\nwhole population include respiratory infections on the increase (due to malnutrition); endemic health\nproblems (AIDS, tuberculosis, malaria, cholera); the widespread practice of Female Genital Mutilation\n(FGM); sanitation costs are high for poorer households not connected on the main water network as", "output": {"entities": {"named_data": ["1997 Poverty\n\nAssessment"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000041", "page": 23, "chunk": 1, "title": "Jordan - Community Infrastructure Project", "pdf_url": "http://documents1.worldbank.org/curated/en/294581468773394111/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1997 Poverty\n\nAssessment", "label": "NAMED_DATA", "score": 0.810173511505127, "start": 420, "end": 444, "probe_score": 0.0723, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nBeirut Housing Rehabilitation and Cultural and Creative Industries Recovery (P176577)\n\n\n\n|Col1|project will undertake<br>proactive efforts to<br>communicate the service<br>standard to address and<br>respond to feedback that<br>will be received.|Col3|Col4|mechanism|Col6|\n|---|---|---|---|---|---|\n|Beneficiaries reporting satisfaction with<br>project activities<br>|Percentage of beneficiaries<br>in component 1 satisfied<br>with project application,<br>grant disbursement,<br>implementation, and<br>technical support.<br>Beneficiaries in component<br>2 reporting improved<br>community cohesion,<br>enhanced social inclusion,<br>and neighborhood<br>revitalization.<br>The findings of these<br>surveys will be published<br>and/or that the survey<br>findings will be used by the<br>implementing entity to<br>generate an action plan to<br>address the feedback<br>acquired through the<br>surveys.|At mid-<br>point of<br>project and<br>project<br>closure<br>|The scope of<br>the GRM will<br>include<br>complaints<br>and other<br>types of<br>feedback<br>such as<br>suggestions,<br>queries (e.g.<br>Quality of<br>Life<br>Survey) and<br>compliments<br>|A survey will be carried<br>out with direct<br>beneficiaries of the<br", "output": {"entities": {"named_data": [], "descriptive_data": ["surveys", "surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 46, "chunk": 0, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "surveys", "label": "DESCRIPTIVE_DATA", "score": 0.5322814583778381, "start": 712, "end": 719, "probe_score": 0.0087, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "surveys", "label": "DESCRIPTIVE_DATA", "score": 0.5385900735855103, "start": 903, "end": 910, "probe_score": 0.0022, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### INTRODUCTION\n\n\n\nThe gender dimensions of forced displacement are critical to the Sustainable\nDevelopment Goals (SDGs), not\nleast because the numbers of forcibly displaced persons have reached\nunprecedented levels. Most recent\nestimates indicate there are 26.4 million\nrefugees and 48 million internally displaced persons (displaced within their\ncountries, IDPs) globally. <sup>1</sup>\n\n\nThe Gender Dimensions of Forced\nDisplacement (GDFD) research program\nhas sought to deepen the understanding of key gender disparities among\nforcibly displaced people, by examining\ngaps and the drivers, with a focus on\nGBV, and the discriminatory norms that\nprevent women from owning property, engaging in paid work and making\ndecisions about their own lives. The\nprogram generated nine country stud\nies—Colombia, Democratic Republic\nof Congo, Ethiopia, Jordan, Liberia,\nMali, Nigeria, Somalia, and Sudan—as\nwell as multi-country studies on child\nmarriage, multi-dimensional poverty,\nIPV covering 17 countries (see Annex\n1). These analyses cast new light on\nthe interaction of gender inequality\nand forced displacement, and fill two\nimportant gaps in the literature by\nproviding first, evidence on poverty\nand violence experienced by displaced\nwomen; and second, a focus on internal displacement. Earlier studies based\non microdata, with the exception of\nColombia, are almost entirely focused\non refugees.\n\n\n\nThe vast majority of forcibly displaced\npeople are located in low- and middle-income countries, with Turkey,\nColombia, Pakistan, and Uganda hosting the largest numbers of refugees\nglobally. <sup>2</sup> While it is difficult to quantify the average duration of refugee\ndisplacement, displacement is often a\nlong-term challenge. <sup>3</sup> Global evidence\nsuggests that displaced women have\nless access to employment opportunities than displaced men <sup>4</sup> and face a lack\nof access to crucial services including\nsexual and reproductive health services,\nmental health", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["microdata"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001238", "page": 8, "chunk": 0, "title": "The Gender Dimensions of Forced Displacement: A Synthesis of New Research", "pdf_url": "https://reliefweb.int/attachments/be0ec676-9a9a-3e88-8ef2-c61baa6c67d0/The-Gender-Dimensions-of-Forced-Displacement-A-Synthesis-of-New-Research.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "microdata", "label": "VAGUE_DATA", "score": 0.6375823020935059, "start": 1312, "end": 1321, "probe_score": 0.6591, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " open areas to\nprevent crowding and assembling. The meetings took place on June 18, 2021, at MGNP Headquarters.\n\n\nA total of 16 participants, mostly Batwa leaders, attended the Focus group meetings and the KIIs. A draft\nof the VMGP was created as a result. However, the evaluation of this draft report revealed some\nlimitations, mostly due to restrictions of the COVID-19 regulations that constrained the breadth and\nmethodology employed in consultations. For instance, given the cultural context of the Batwa, the\nutilisation of techniques like telephone interviews was not highly appropriate. Due to the small number of\nBatwa who owned telephones, these tactics not only restricted how the Batwa expressed themselves but\nwere also difficult. As a result, only a few chosen Batwa leaders had a chance to participate in the\nconsultations.\n\n\nThere was the need for more discussions to (a) involve more stakeholders and Batwa people in the project\narea, (b) reach more Batwa people, and (c) produce more baseline data that is site-specific.\n\n\n**2.3 Phase II of consultations (September 2022)**\n\n\nA second round of consultations was organized once most COVID-19 related restrictions were lifted in\nUganda. On September 24 <sup>th</sup>, 2022, a special consultation with the Batwa around MGNP was carried out, at\nthe MGNP Headquarters. The meeting was attended by 67 people in total (30 men and 37 women), with\nrepresentation from the frontline communities around MGNP. The goal of consulting the Batwa who\nreside around MGNP and depend on it for their livelihood was to learn about their concerns and\npreferences regarding the design and proposed implementation of the IFPA-CD project to give them\nequitable access to project benefits and minimize any unfavorable outcomes for the Batwa. Their opinions\nand the issues they presented have informed the finalization of this VMGP.\n\n\n16", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002060", "page": 15, "chunk": 1, "title": "Vulnerable and Marginalized Group Plan Uganda Investing in Forests and Protected Areas for Climate-Smart Development Project (P170466)", "pdf_url": "https://documents.worldbank.org/curated/en/099042723102025847/pdf/P1704660d83f50070a6000f4edb96a46d1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "baseline data", "label": "VAGUE_DATA", "score": 0.7301051020622253, "start": 1002, "end": 1015, "probe_score": 0.0035, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\n\n\n\n\n\n\n\n|Col1|Project Operations Manual,<br>and have received cash<br>transfers, at least for one<br>payment cycle.|minimum<br>on a<br>quarterly<br>basis|Information<br>System (MIS)|course of project<br>implementation.<br>Payment data will be<br>liked to and updated in<br>the MIS.|Col6|\n|---|---|---|---|---|---|\n|Number of beneficiaries receiving cash for<br>performing labor intensive public works<br>who are female|<br>Number of total<br>beneficiaries that directly<br>receive cash transfer for<br>working on LIPW under sub-<br>component 1.1 on behalf of<br>beneficiary HH, of which are<br>female|This<br>indicator<br>will be<br>measured<br>at a<br>minimum<br>on a<br>quarterly<br>basis<br>|Registration<br>and payment<br>data in the<br>SNSOP MIS<br>|Beneficiary data is<br>collected during<br>registration and<br>updated over the<br>course of the project.<br>Payment data will also<br>be periodically updated<br>in the MIS<br>|Selected Implementing<br>Partner<br>|\n|Number of beneficiary households<br>receiving cash transfer for participating in<br>the behavioral change communication<br>training|The number of beneficiary<br>households that participate<br>in behavioral change", "output": {"entities": {"named_data": ["SNSOP MIS"], "descriptive_data": [], "vague_data": ["Payment data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 60, "chunk": 0, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Payment data", "label": "VAGUE_DATA", "score": 0.5425735712051392, "start": 314, "end": 326, "probe_score": 0.2479, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "SNSOP MIS", "label": "NAMED_DATA", "score": 0.752434492111206, "start": 833, "end": 842, "probe_score": 0.0496, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Chapter 6\n\n\n**Recognizing the problem:**\n**Better statistics on**\n**statelessness**\n\n\nIn line with SDG 17 <sup>**72**</sup> and Target 17.18, <sup>**73**</sup> increasing\nthe availability of high-quality, reliable and\ndisaggregated data is critical in any effort to\nimpact development. Identifying stateless\npeople is the first step towards addressing\nthe difficulties they face, as well as enabling\ngovernments, UNHCR and others to prevent\n\n\n**72** SDG 17. Strengthen the means of implementation and revitalize the\nglobal partnership for sustainable development.\n**73** Target 17.18: By 2020, enhance capacity-building support to\ndeveloping countries, including for least developed countries\nand small island developing States, to increase significantly the\navailability of high-quality, timely and reliable data disaggregated\nby income, gender, age, race, ethnicity, migratory status,\ndisability, geographic location and other characteristics relevant\nin national contexts.\n\n\n\nand reduce statelessness. Recognition of\nstatelessness and gathering data about the\nproblem are key elements in UNHCR’s Global\nAction Plan to End Statelessness (Global Action\nPlan), which accompanies the #IBelong Campaign.\nTo improve quantitative and qualitative data\non stateless populations, UNHCR works with\nStates to undertake targeted surveys and studies\nand to incorporate questions allowing for the\nidentification of stateless persons in population\nand housing censuses. The Global Action Plan\nalso calls for the strengthening of civil registration\nand vital statistics systems and UNHCR works with\nothers to provide technical support to this end.\n\n\nMany countries have made strong commitments\nto address and end statelessness. Over 350\npledges were made to address statelessness\nat the High-Level Segment on Statelessness,\nheld in October 2019 to mark the midpoint of the\n\n\n\n\n\n\n\n\n\n\n\n\n\n62 UNHCR > **GLOBAL TRENDS 2019**", "output": {"entities": {"named_data": [], "descriptive_data": ["population\nand housing censuses"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001657", "page": 61, "chunk": 0, "title": "Global Trends: Forced Displacement in 2019", "pdf_url": "https://reliefweb.int/attachments/ffb577d2-2185-3ba5-bdc7-8130fa9ba6e8/5ee200e37.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "population\nand housing censuses", "label": "DESCRIPTIVE_DATA", "score": 0.8287676572799683, "start": 1424, "end": 1455, "probe_score": 0.2453, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**_Control Variables_**\n\nThe study has extracted the control variables from various sources, including the World Development\nIndicators (WDI) and other relevant sources. The set of control variables includes the political regime or\ndemocracy measure, including Polity2 of the Polity V dataset <sup>14</sup> [^14: The Polity V project codes the authority characteristics of states in the world system for purposes of comparative,\nquantitative analysis.] as political regime characteristics may lead\nto differentiated effects across countries. Following the literature (Hilger et al., 2020; Vicari et al., 2015),\nthe study also uses a set of control variables from WDI, including socio-economic and demographic\ncharacteristics (e.g., the share of the population aged between 15 and 44, the human capital index, and\nGDP per capita <sup>15</sup> [^15: This allows for the removal of the implicit income effects and reduces the gap between the values of the different variables.] ). The study also uses the power distributed by social group variable from V-Dem. In\naddition, the study uses the fixed internet broadband subscriptions per 100 inhabitants variable as a proxy\nfor internet penetration (Boulianne, 2009; Howard, 2006; Putman, 2000) from the International\nTelecommunication Union (ITU) dataset.\n\n\n**2.** **Overview of the Adoption of GovTech Platforms and the Level of Citizen Engagement**\n**Worldwide**\n\nIn the context of this study, a statistical analysis (including stylized facts) was conducted related to the\nadoption of GovTech platforms and the level of citizen engagement worldwide, focusing on the 198\ncountries covered by the GTMI. Table 1 summarizes information on the implementation of digital\nplatforms. In the sample of 198 countries, 82 (41.4%) have Implemented a digital platform allowing\ncitizens to participate in policy decision-making, and 75 countries (37.8%) have implemented a platform\nenabling citizens to provide feedback. However, 112", "output": {"entities": {"named_data": ["World Development\nIndicators", "Polity V dataset", "WDI", "V-Dem", "International\nTelecommunication Union (ITU) dataset", "GTMI"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001592", "page": 8, "chunk": 0, "title": "idu1e2fc782f13ddb14ac41ae801f190d313322f", "pdf_url": "https://local/prwp/idu1e2fc782f13ddb14ac41ae801f190d313322f.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Development\nIndicators", "label": "NAMED_DATA", "score": 0.8394247889518738, "start": 107, "end": 135, "probe_score": 0.9626, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Polity V dataset", "label": "NAMED_DATA", "score": 0.8176286220550537, "start": 276, "end": 292, "probe_score": 0.9696, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "WDI", "label": "NAMED_DATA", "score": 0.5356250405311584, "start": 663, "end": 666, "probe_score": 0.9825, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "V-Dem", "label": "NAMED_DATA", "score": 0.7213268876075745, "start": 1050, "end": 1055, "probe_score": 0.993, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "International\nTelecommunication Union (ITU) dataset", "label": "NAMED_DATA", "score": 0.8029798269271851, "start": 1248, "end": 1299, "probe_score": 0.9977, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "GTMI", "label": "NAMED_DATA", "score": 0.6201705932617188, "start": 1642, "end": 1646, "probe_score": 0.9763, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a v\nManufacturIng 5 7 3.7 4 7 5 0 / s \\\\t oo  Services 475 272 190 201\n\nPrfvate consumpffon 90 7 81 9 938 95 1 20\nGeneral govemment consumption 7 0 9 6 146 17.2 =c ~GDFDl\nImpons of goods and servrcea 39 7 23 6 33 4 373 -3GW_G_____\n\n\n_(average_ _annual growth)_ 1981-9 1991401 2000 2001 Growth ot exports and Imports (%)\n\nAgrutumre -0 6 -2 6 2 2 3 8 oo\nIndustry 0.1 -41 51 5 6 s0\nManUnacturIng 6.9 . .\nServices -5 7 -5.4 4 0 51 \nPrivate oonsumpffon -2 0 -19 10 4 100 -50\nGeneral govemment consumption -5.1 -0 2 41.3 27 9 -100\nGross domestic Investment -06 3 0 50 - EOpois -tr-ports\nImports of goods and services -2 2 -151 85 0 61 3\n\n\nNote 2001 data are pretirrinary eastliates\n'The diamonds show four Key Indicators in the country (in bold) conipared with itS income-group average It data are missing, the diantond wiUt be rrconrrlte\n\n\n-56", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["2001 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000013", "page": 60, "chunk": 2, "title": "West Bank and Gaza - Education Action Project", "pdf_url": "http://documents1.worldbank.org/curated/en/137371468765334508/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2001 data", "label": "VAGUE_DATA", "score": 0.7082152366638184, "start": 639, "end": 648, "probe_score": 0.0183, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Introduction and background**\n<u>Paving pathways for inclusion: A global overview of refugee education data</u>\n\n\nSchool safety – defined as the conditions that enable\nall users, including learners, teachers, and other\neducational personnel, to enjoy the right to education\nwithout fear of physical or psychosocial threat, danger,\ninjury, or loss posed by natural and climate-induced\nevents, conflict-related violence, instability, or violence\nby individuals (UNESCO, 2023a) – is also critical. Beyond\nprotection from external and internal risks, such as\nattacks on education and interpersonal violence, safety\nalso includes offering a secure, protective physical\nspace and adequate conditions for health and wellbeing, including safe facilities and infrastructure, a\npositive socio-emotional environment, and health\nand nutrition services. Despite the importance of safe\nconditions for learning, no comprehensive review of\nsafety indicators for refugee education was found.\nSimilarly, UIS and UNHCR (2021) found poor coverage\nof safety indicators, even in large-scale international\nsurveys that often aim to provide a comprehensive\nview of the national educational landscape. This is\ndespite the research showing the relevance of safe\nenvironments to promote a positive school and\ncommunity climate, which is critical for facilitating\nstudent learning and well-being (Kutsyuruba, Klinger,\n[and Hussain, 2015; Chavez and Aguilar, 2021).](https://www.unicef-irc.org/publications/1184-the-impact-of-community-violence-on-educational-outcomes.html)\n\n\nOne aspect of school safety that is particularly\nrelevantfor displaced student populations – and where\n\n\n**22**\n\n\n\ndata are almost completely absent – is discrimination\nand peer violence experienced by refugee learners.\nThe literature suggests that children who are\nperceived as different from their peers, in terms of\ntheir physical appearance, socio-economic status\n(Elgar et al., 2009), school performance (Thornberg,\n2011)", "output": {"entities": {"named_data": [], "descriptive_data": ["refugee education data", "large-scale international\nsurveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000382", "page": 21, "chunk": 0, "title": "Paving pathways for inclusion: a global overview of refugee education data", "pdf_url": "https://reliefweb.int/attachments/31f00be7-0481-4224-80ce-378c049a02d4/Paving%20pathways%20for%20inclusion%20--%20a%20global%20overview%20of%20refugee%20education%20data.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "refugee education data", "label": "DESCRIPTIVE_DATA", "score": 0.6328444480895996, "start": 87, "end": 109, "probe_score": 0.893, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "large-scale international\nsurveys", "label": "DESCRIPTIVE_DATA", "score": 0.8327977657318115, "start": 1059, "end": 1092, "probe_score": 0.7477, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nNational Uganda Social Action Fund (P179904)\n\n\n**(a)** Average increase of income for beneficiaries of livelihood support activities (percentage, gender\n\ndisaggregated)\n\n\n**(b)** Share of women beneficiaries reporting increased income (percentage)\n\n\n**(c)** Share of safety net beneficiaries who no longer use negative coping strategies11 (percentage,\n\ngender disaggregated)\n\n\n**(d)** Number of programs using dynamic social registry for delivery of pro-poor benefits and services\n\n(number).\n\n\n**D. Project Description**\n\n17. **The project will be implemented in geographic areas of high incidence of poverty and risks to climate-related**\n**shocks and will use an integrated approach to address the key drivers of poverty and vulnerability.** It will implement\nevidence-based interventions that aim to (a) systematically tackle monetary poverty and increase productivity of\nlivelihoods through interventions in Component 1 and safety net support in Component 2; (b) enhance investments in\nhuman capital through livelihoods interventions in Component 1 and gender, health, and nutrition safety net\ninterventions in Component 2; (c) increase the resilience of poor and vulnerable households to cope with shocks through\nlivelihoods interventions of Component 1 and safety net interventions of Component 2 that are expected to result in\nincrease in income and assets and protect the human capital investments of the households; and (d) strengthen delivery\nsystems and improve the efficiency of pro-poor public expenditures through investment in operationalization of\ntransformational delivery systems in Component 3. The implementation of the three project components will be\nsupported through project management and monitoring and evaluation (M&E) and by ensuring transparency,\naccountability, and anti-corruption (Component 4).\n\n\n18. **The project will ensure coordination and complementarity with key government and World Bank projects.** In\nparticular, it will complement existing World Bank-financed operations aiming to expand economic opportunities for", "output": {"entities": {"named_data": [], "descriptive_data": ["dynamic social registry"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002394", "page": 6, "chunk": 0, "title": "Project Information Document - National Uganda Social Action Fund - P179904", "pdf_url": "https://documents.worldbank.org/curated/en/099051223113532026/pdf/P179904085a07f070a16905df2462a4696.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "dynamic social registry", "label": "DESCRIPTIVE_DATA", "score": 0.7722408175468445, "start": 429, "end": 452, "probe_score": 0.0729, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**_Component 3:_** **Project Monitoring, Auditing and Verification (US$100,000)**\n\n\n27. This component will finance: (i) the costs of two special purpose audits (see below) as\nrequired for Component 1; and (ii) the cost of an external auditor, acceptable to the World Bank,\nwho will be appointed to audit the project financial statements covering the Project’s 12 months\nlifetime and for both Components 1 and 2.\n\n\n28. For Component 1, an audit firm will be contracted within three months of effectiveness to\nperform an audit of the funds disbursed under retroactive financing for vaccines and drugs. The\nauditor will issue a special opinion on supporting documents related to the Rational Drug List\nand the Designated Account (DA) to be established in the Central Bank of Jordan (CBJ) to\ndeposit the loan proceeds. Also, a consultancy firm will be contracted to perform a technical and\nfinancial verification of the list of medical bills of patients who will be referred to the non-MOH\nhospitals and health facilities before being further processed for payment by MOF.\n\n\n**B.** **Project Financing**\n\n\n**Financing Instrument**\n\n\n29. The financing instrument is an Investment Project Financing for the amount of US$150\nmillion, to be financed through an IBRD loan. The Borrower has requested a Variable Spread\nLoan (VSL), linked to commitment with a 25 year maturity including a 4.5-year grace period.\nThe Front-end Fee equal to one quarter of one percent (0.25%) of the Loan amount would be\nfinanced out of the loan proceeds.\n\n\n**Project Cost and Financing**\n\n\n30. The project costs and financing are detailed in the table below.\n\n\n**Table 1: Project Costs (US$)**\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Retroactive<br>(June 2012 - June 2013)<br>(US$", "output": {"entities": {"named_data": [], "descriptive_data": ["list of medical bills"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000064", "page": 18, "chunk": 0, "title": "Jordan - Emergency Project to Assist Jordan Partially Mitigate Impact of Syrian Conflict", "pdf_url": "http://documents1.worldbank.org/curated/en/419981468271818589/pdf/781290PAD0JO0R0t0Box377365B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "list of medical bills", "label": "DESCRIPTIVE_DATA", "score": 0.5593063831329346, "start": 917, "end": 938, "probe_score": 0.2119, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Evaluation Report<br><br>|Draft Bidding<br>Document /<br>Justification<br><br>|Draft Bidding<br>Document /<br>Justification<br><br>|Specific Procurement<br>Notice / Invitation<br><br>|Specific Procurement<br>Notice / Invitation<br><br>|Bidding Documents as<br>Issued<br><br>|Bidding Documents as<br>Issued<br><br>|Proposal Submission /<br>Opening / Minutes<br><br>|Proposal Submission /<br>Opening / Minutes<br><br>|Bid Evaluation Report<br>and Recommendation<br>for Award<br><br>|Bid Evaluation Report<br>and Recommendation<br>for Award<br><br>|Signed Contract<br><br>|Signed Contract<br><br>|Contract Completion<br><br>|Contract Completion<br><br>|\n|Activity Reference No. /<br>Description|Loan / Credit<br>No.|Component|Review Type|Method|Market Approach|Procurement<br>Process|Prequalification<br>(Y/N)|Estimated<br>Amount (US$)|Actual Amount<br>(US$)|Process<br>Status|Planned|Actual|Planned|Actual|Planned|Actual|Planned|Actual|Planned|Actual|Planned|Actual|Planned|Actual|Planned|Actual|Planned|Actual|\n|UG-OPM-20869-NC-DIR /<br>Non consulting services to<br>Develop a Bio-metric based<br>payment mechanism for the<br", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020736", "page": 3, "chunk": 1, "title": "Uganda - AFRICA EAST- P149965- Third Northern Uganda Social Action Fund (NUSAF 3) - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/959541624446298337/pdf/Uganda-AFRICA-EAST-P149965-Third-Northern-Uganda-Social-Action-Fund-NUSAF-3-Procurement-Plan.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<u>Abbreviated Resettlement Action Plan Report</u>\nProposed Infrastructures Improvement Works In Selected Informal Settlements In Kisumu County (6 No. Settlements)\n\n\n**5.3** **Demographic Details of PAPs**\n\n\n**5.3.1** **Household Heads and Gender**\n\nMost PAPs are males, at 83%, and females, at 17%. 4 of the PAPs were identified as vulnerable\ni.e., four were elderly people, with one being a widow and female head of household.\n\n\nThe gender representation of the PAPs is shown in Figure 5.1.\n\n\n**_Fig. 5. 1_** **: Gender of the PAPs**\n\n\n**5.3.2** **Household size**\n\nThe average household size of the PAPs is 11.8, with the highest household size reported being\n17 and the least being 2.\n\n\nFigure below shows the representation of household size.\n\n\n**_Fig. 5. 2_** **: Household sizes**\n\n**5.3.3** **Household heads and Marital status**\n\nFrom the survey, 87% of the PAPs reported being married, 9% being single, and 4% being\nwidowed.\n\n\n32", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001887", "page": 44, "chunk": 0, "title": "Kenya - Second Kenya Informal Settlements Improvement Project : Abbreviated Resettlement Action Plan Report for Manyatta A, Manyatta B, Nyawita and Kibuye Settlements", "pdf_url": "https://documents.worldbank.org/curated/en/099041724053516460/pdf/P1678141684bca0e31916c1482659966bd5.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey", "label": "VAGUE_DATA", "score": 0.6153147220611572, "start": 848, "end": 854, "probe_score": 0.9995, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "E)** survey\nmicrodata available on-line;\n\n**6.3** KIHBS **2015/16** microdata\navailable on-line;\n\n6.4 KCHS **2017** microdata\navailable on-line; and\n\n**_6.5_** KCHS **2018** microdata\navailable on-line.", "output": {"entities": {"named_data": ["KIHBS", "KCHS", "KCHS"], "descriptive_data": ["survey\nmicrodata"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012667", "page": 11, "chunk": 1, "title": "Official Documents- Financing Agreement, Credit 5717-KE (Closing Package)", "pdf_url": "https://documents.worldbank.org/curated/en/415181468047667798/pdf/RAD1015591673.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey\nmicrodata", "label": "DESCRIPTIVE_DATA", "score": 0.7377604246139526, "start": 5, "end": 21, "probe_score": 0.9483, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "KIHBS", "label": "NAMED_DATA", "score": 0.6276758909225464, "start": 50, "end": 55, "probe_score": 0.99, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "KCHS", "label": "NAMED_DATA", "score": 0.5519766807556152, "start": 102, "end": 106, "probe_score": 0.9919, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "KCHS", "label": "NAMED_DATA", "score": 0.5382615327835083, "start": 160, "end": 164, "probe_score": 0.9921, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " considera importante reflejar,**\n**de forma excepcional, la condición dual de refugiadas y de apátridas de las**\n**personas de este grupo dado que, de otra forma, podría tenerse la impresión**\n**de que el grupo de personas apátridas se ha reducido considerablemente.**\n**Este enfoque no se verá reflejado en la base de datos ni en el la versión de**\n**Excel de esta tabla. Por ello, las cifras pueden ser distintas.**\n\n**15 Cifras de refugiados relativas a final de 2016.**\n\n**16 Todas las cifras se refieren a final de 2016.**\n\n**17 Los 300.000 refugiados vietnamitas están bien integrados y en la práctica**\n**reciben protección del Gobierno de China.**\n\n**18 Las actividades de asistencia de ACNUR a desplazados internos en Chipre**\n**finalizaron en 1999. Para más información, véase la página del Observatorio**\n**de Desplazamiento Interno (IDMC).**\n\n**19 La cifra de apatridia se basa en una estimación del Gobierno en la que**\n**las personas o sus padres o abuelos migraron a Côte d’Ivoire antes o**\n**poco después de la independencia, y cuya nacionalidad no se estableció**\n**con la independencia ni antes de que en 1972 la ley sobre nacionalidad**\n**cambiara. La estimación proviene en parte de casos en", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["base de datos"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000519", "page": 34, "chunk": 17, "title": "Tendencias global desplazados forzosos en 2018", "pdf_url": "https://reliefweb.int/attachments/4a4b8fc2-fcc6-390b-b9e3-d1f08bbef1ad/5d09c37c4.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "base de datos", "label": "VAGUE_DATA", "score": 0.6224503517150879, "start": 312, "end": 325, "probe_score": 0.002, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda COVID-19 Education Response Project (P174033)\n\n\nalso increase with education level. For higher education the regional average is 21 percent, while the returns\nto primary and secondary education are 14.4 and 10.6 percent, respectively. As shown in the figure below,\nin Uganda, the average expected income also increases according to the highest education level attended.\n\n\n**Figure 1. Mean monthly wage, 14-64 years old, by highest education level attended, in UGX**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n_Source:_ UNHS 2016/17.\n_Notes:_ Monthly wage from main job, for those employed as paid employees, employers or self-employed.\n\n<mark>11.</mark> <mark>The direct project beneficiaries of the proposed project are 14 million</mark> <mark>students in preprimary, primary and</mark>\n<mark>lower-secondary students; and 520,000</mark> <mark>teachers and school administrators in Uganda. The main goal is to</mark>\n<mark>ensure learning continuity. The expected positive outcomes are therefore higher retention rates, as the</mark>\n<mark>pandemic might increase dropouts, affecting particularly harder children from poorer households and young</mark>\n<mark>girls.</mark>\n\n<mark>12.</mark> <mark>Costs are equivalent to the total cost of the project – which will disburse US$ 14.7M over a period of 18</mark>\n<mark>months – and additional costs due to the increased number of students enrolled in primary and lower</mark>\n<mark>secondary education as a result of the implementation of project’s activities. These additional students</mark>\n<mark>correspond to those who are currently enrolled in either primary or lower secondary education and would</mark>", "output": {"entities": {"named_data": ["UNHS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000034", "page": 46, "chunk": 0, "title": "Uganda - COVID-19 Emergency Education Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/645041598936002560/pdf/Uganda-COVID-19-Emergency-Education-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHS", "label": "NAMED_DATA", "score": 0.6628286838531494, "start": 517, "end": 521, "probe_score": 0.9989, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n\nthe survey data side, only households that did not have any missing information on income (respondents were\nasked to provide both sources and amounts) were included in the calculation. For households claiming no or\nvery little income an imputation was made based on expenses and the duration of stay in the host country.\n\n\nIt is important to note that while the poverty definition adopted in this assessment allows for comparisons\nacross the countries covered (limitations apply to the Republic of Moldova), it may not be directly comparable\nto other studies, as approaches tend to vary quite significantly. The setup of the questionnaire, the sampling\nmethodology, the processing of income data (including any imputations), the approach to equivalizing income,\nand finally the location of the poverty line itself in the income range all have a substantial impact on poverty\nindicators.\n\n\nIn order to compute refugee wages, household net employment income was divided by the total number of\nworking hours reported by all employed members. This figure was then weighted by the total number of\nworking hours and averaged overall all households within a given country (while also respecting poststratification weights). The result was then converted to a monthly wage assuming employment at 40 hours per\nweek and 4.33 weeks in a month. For comparability with host population data, net wages were converted to\ntheir gross equivalent utilizing local tax regulations.\n\n# **Limitations**\n\nThe statistical significance of the SEIS results is limited by the non-probabilistic selection of respondents.\nMoreover, the use of convenience sampling likely led to a larger share of data being collected from more\nvulnerable households.\n\n\nThere was also a notably high non-response rate regarding questions related to income and expenditure,\nwhich likely resulted in non-response bias. The income module of the SEIS was also materially different from", "output": {"entities": {"named_data": [], "descriptive_data": ["host population data"], "vague_data": ["survey data", "income data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 14, "chunk": 0, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.629576563835144, "start": 112, "end": 123, "probe_score": 0.7089, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "income data", "label": "VAGUE_DATA", "score": 0.7243103384971619, "start": 792, "end": 803, "probe_score": 0.6388, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "host population data", "label": "DESCRIPTIVE_DATA", "score": 0.6333092451095581, "start": 1464, "end": 1484, "probe_score": 0.9628, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", is largely comprised of\n\nwomen and children, and is highly vulnerable with high basic needs like food and\n\nwater, suggesting low capabilities to engage in onward movement.\n\n## **Data and profiles**\n\nThis snapshot draws upon 611 4Mi surveys conducted in July 2024 in Eastern Chad\n\nwith people who fled Sudan after the outbreak of conflict. Some 336 interviews were\n\nconducted in Adre (55% of respondents) and 275 in Tine (45%). Almost all respondents\n\n(99%) were Sudanese nationals, and most were women between the ages of 35-80 years\n\nold from Central Darfur (Figure 1). While MMC carries out non-probability sampling and,\n\nhence, the data are not representative, the key demographic characteristics of sampled\n\nrespondents aligns with estimates of the overall population of arrivals in Eastern Chad. <sup>5</sup>\n\nRespondents in Tine and Adre followed similar socio-demographic tendencies.\n\n**Figure 1. Overview of sample by age and sex**\n\n\n\n18-24\n\n\n25-34\n\n\n35+\n\n\n\n50%\n\n\n0% 10% 20% 30% 40% 50%\n\n\n\n\n\n\n\n\n\nTotal number of\nrespondents (n=611)\n\n\n\n5 UNHCR, _op. cit._\n\n\n\n1", "output": {"entities": {"named_data": ["611 4Mi surveys"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001554", "page": 0, "chunk": 2, "title": "Sudanese arrivals in Eastern Chad: Protection experiences, needs and onward movement intentions – November 2024", "pdf_url": "https://reliefweb.int/attachments/f12615d1-9c5c-48fb-9e0c-2d58ae918ffc/349_MMC-UNHCR-ESA-Sudanese-arrivals-in-Eastern-Chad.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "611 4Mi surveys", "label": "NAMED_DATA", "score": 0.6451261043548584, "start": 226, "end": 241, "probe_score": 0.9762, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\n\n\n\n\n\n|Col1|and have received cash<br>transfers, at least for one<br>payment cycle.|on a<br>quarterly<br>basis|Col4|Payment data will be<br>regularly updated in the<br>SNSOP MIS|Col6|\n|---|---|---|---|---|---|\n|Percentage of Labor Intensive Public<br>Works subprojects that mitigate climate-<br>induced shocks|Percentage of LIPW<br>subprojects that are<br>designed to mitigate the<br>impacts of climate-induced<br>shocks in beneficiary<br>communities, as identified<br>under the Project<br>Operations Manual.|This<br>indicator<br>will be<br>measured<br>at least on<br>a quarterly<br>basis<br>through<br>missions<br>and ISRs<br>|LIPW<br>monitoring<br>forms<br>|The implementing<br>partner will periodically<br>monitor LIPW as part of<br>quality control and<br>monitoring and<br>evaluation activities<br>carried out by<br>dedicated field staff<br>including field-based<br>engineers<br>|Implementing partner<br>|\n|Number of LIPW work days created|Number of total LIPW work<br>days generated by SNSOP|This<br>indicator<br>will be<br>measured<br>at<br>minimum<br>on a<br>quarterly<br>basis<br>including<br>", "output": {"entities": {"named_data": ["SNSOP MIS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 61, "chunk": 0, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SNSOP MIS", "label": "NAMED_DATA", "score": 0.8985754251480103, "start": 260, "end": 269, "probe_score": 0.0342, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n\n**Republic of Moldova: the case for housing costs corrections in income-based poverty metrics**\n\n\nData from the Republic of Moldova highlights the limitations of poverty metrics that rely solely on disposable\nincome, as they fail to account for vulnerability related to asset ownership. Based on income alone, the 2024\npoverty rate suggests that Ukrainian refugees are able to attain a higher standard of living than their hosts, with\nonly 10% living in poverty compared to 32% of Moldovans. This apparent disparity is largely driven by the\nsizeable financial support that Ukrainians received from humanitarian organizations in 2024, which amounted\nto 44% of their total household income. While the above comparison could suggest that the provided aid is\nexcessive, such an interpretation overlooks an important factor – namely that only 5% of Moldovans incur rental\nexpenses compare to 41% of refugees. In fact, including utilities, housing costs were estimated to consume 46%\nof refugees’ disposable income (inclusive of humanitarian aid), whereas they account for just 14% for Moldovan\nhouseholds. In essence, these findings indicate that refugees are using the entirety of their aid to cover\naccommodation needs. Adjusting disposable income at the household level to reflect these additional housing\nexpenses raises the poverty rate for refugees to 43%, surpassing that of Moldovans.\n\n\n**Poverty is associated with tangibly inferior living conditions, worse healthcare coverage,**\n**more frequently children being out of school, and having to skip meals**\n\n\nRefugee households with members living in poverty were found to more often not report feeling safe when\nwalking alone in their neighborhood after dark (18% vs 10% for those not at risk), to significantly more frequently\nlive in collective housing (27% vs 8%), and to feel under pressure to leave their accommodation (29% vs 11%", "output": {"entities": {"named_data": [], "descriptive_data": ["Data from the Republic of Moldova"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 6, "chunk": 0, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data from the Republic of Moldova", "label": "DESCRIPTIVE_DATA", "score": 0.7858414649963379, "start": 206, "end": 239, "probe_score": 0.943, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nDjibouti Skills Development for Employment Project (P175483)\n\n\nand 45.47 percent are women of the overall refugee population. A majority of these individuals (57.47 percent)\nare between the ages of 18-59 years or the working age group. Approximately 38 percent of the refugee\npopulation is less than 17 years of age. The current number of refugees and asylum seekers constitutes about\n3.4% of the total population living in Djibouti, making it one of the countries with a significant ratio of refugees\nand asylum seekers/population in the world. The share of refugees only is about 2.34 percent of the overall\npopulation of the country.  Educational attainment is very low across the population of refugees and asylum\nseekers with 53 percent of the population having no schooling at all. Figure 1 below illustrates attainment across\nthe population of refugees and asylum seekers.\n\n\nFIGURE 1\n\n\n\n\n\n\n\n4. **Djibouti is considered highly vulnerable to climate change** . While strategic location defines much of\nDjibouti's current economic growth strategy, location is also a concern for Djibouti when considering the impacts\nof climate change and the trends expected to be seen in the coming years. The Notre Dame Global Adaptation\nInitiative (ND-GAIN) Index places Djibouti at 117 out of 181 countries, implying that the country is vulnerable to\nclimate change impacts and is expected to experience adverse impacts from increased temperatures, aridity,\nreduced precipitation, and rising sea levels <sup>5</sup> [^5: World Bank (2021), Djibouti Climate Risk Country Profile, The World Bank.] . Mean annual temperatures are projected to increase by 1°C every\ntwenty years, with monthly average temperatures expected to rise by 1.9°C by the 2050s and a staggering 4.5°C\nby 2100. These temperature increases are likely to be associated with intense heat waves, with cold spells and\ncold nights expected to decrease which will have significant consequences for human, animal health, biodiversity,\nand water", "output": {"entities": {"named_data": ["Notre Dame Global Adaptation\nInitiative (ND-GAIN) Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000195", "page": 12, "chunk": 0, "title": "Djibouti - Skills Development for Employment Project", "pdf_url": "https://documents1.worldbank.org/curated/en/927731664308482374/pdf/IBArchive-38b35d89-2c5c-4636-ab7e-0ba662b95a5f.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Notre Dame Global Adaptation\nInitiative (ND-GAIN) Index", "label": "NAMED_DATA", "score": 0.5461861491203308, "start": 1218, "end": 1273, "probe_score": 0.8748, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Disbursement forecast\n\n\n\nContract number\n*Contract subject\nAwardee\n*Launching date\n-Expected delivery date\n-Non objection date\n*Expected date of final delivery\n*Bidder nationality\n*Contract allocation (general account, budget, loan\ncategory, geographic area)\n*List of contracts\nManagement of financial -Standard financial statements (balance sheet;\naccounts statement of sources and uses of funds/income\nstatement, ...)\n*LACI reports for the project duration\nFixed Assets management -Inventory of Fixed Assets (type, quantity, valuation,\ndate of service, etc.)\n\n\n\nSupplier\nAccounting category ; budgetary and accounting\nallocation of fixed assets\n\n\n\nLocation\nDepreciation\n-Disposal of Fixed assets\n\n\n\n**Module** Functions\nSorting parameters Project ID and currency used\n\n                  - Fiscal years\nCurrency\nDecentralized data entry locations\n\n\n\nChart of accounts, managerial reports, geographic\nareas of intervention, etc.\n\n\n\n\n                - Books of accounts\nDonors\n\n                 - Contracts\nCategories of disbursement\nUser Management Data storage ; restitution ; correction; cleaning; etc.\n\n                - Import/export of data to other Tempro modules\n\n\n\nIt is expected that the application would be modified to differentiate the operations from the\nprojects, as well as funding sources to allow for reporting in financial and accounting terms of the\nproject objectives and activities. The concept should allow for proper monitoring of the project\nduring the life of the credit, namely: (i) chart of accounts; (ii) by category, component, and subcomponent; (iii) by geography (type of establishment, site and district); (iv) by category of\nexpenses; and (v) in local and foreign currency. Reporting of multi-level data is planned, which\n**wiU** bring about a more dynamic approach to the management of the project, and which should", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["multi-level data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015130", "page": 51, "chunk": 0, "title": "Kenya - Fourth Education Project", "pdf_url": "https://documents.worldbank.org/curated/en/583101468089668773/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "multi-level data", "label": "VAGUE_DATA", "score": 0.6651609539985657, "start": 1720, "end": 1736, "probe_score": 0.4661, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|\n|Indicator Name|Baseline|Baseline|Actual (Previous)|Actual (Previous)|Actual (Current)|Actual (Current)|Closing Period|Closing Period|\n|Indicator Name|Value|Month/Year|Value|Date|Value|Date|Value|Month/Year|\n|Update and Implement<br>National Health Adaptation<br>Plan to Climate Change<br>(Yes/No)|No|Jun/2022|Yes|24-Jul-2025|Yes|09-Jan-2026|Yes|Jun/2026|\n|Update and Implement<br>National Health Adaptation<br>Plan to Climate Change<br>(Yes/No)|Comments on<br>achieving  targets|Comments on<br>achieving  targets|The DLI continues to show consistent progress and remains on track to meet the closing<br>period target.<br>Once the Bank receives the independent verification report from MOH, the team will update<br>the result/target accordingly.|The DLI continues to show consistent progress and remains on track to meet the closing<br>period target.<br>Once the Bank receives the independent verification report from MOH, the team will update<br>the result/target accordingly.|The DLI continues to show consistent progress and remains on track to meet the closing<br>period target.<br>Once the Bank receives the independent verification report from MOH, the team will update<br>the result/target accordingly.|The DLI continues to show consistent progress and remains on track to meet the closing<br>period target.<br>Once the Bank receives the independent verification report from MOH, the team will update<br>the result/target accordingly.|The DLI continues to show consistent progress and remains on track to meet the closing<br>period target.<", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002183", "page": 18, "chunk": 4, "title": "Disclosable Version of the ISR - Ethiopia Program for Results (Hybrid) for Strengthening Primary Health Care Services. - P175167 - Sequence No : 7", "pdf_url": "https://documents.worldbank.org/curated/en/099050126182033466/pdf/P175167-15c45375-7a63-4e0b-b87c-925842ce6169.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " بإجراء الضعف هذا أثر تخفيف وسيتم\n\n. والتلفزيـون واإلذاعـة الصـحف في اإلعالمية الحمالت خالل من الجمهور توعية في لستمرارو **ا** حكومية، غير منظمة\n\nهـذه فيـف تخ ويمكـن . الفنيـين الموظفين قدرات بناء عملية من النساء استبعاد في تتمثل أخرى اجتماعية مخاطر وهناك\n\nالفرعية القطاعات كل في الجنسين بين المساواة اعتبارات يراعي الذي القدرات لبناء خاص اهتمام إيالء خالل من المخاطر\n\nمـن لجتماعية **ا** التنمية على المشروع نواتج متابعة وسيجري. الزراعي اإلحصاء في النوع حسب البيانات وتحديد األربعة\n\n.للمشروع والنتائج الرصد إطار ووفق المشروع على اإلشراف خالل\n\n\n**المشاورات**\n\n\n4\nالجهـاز وهي –المنفذة الهيئات مع وثيق بشكل عمل المشروع فريق أن إذ تشاركي مشروع هو المقترح المشروع .\n\nوهيئة النقد وسلطة لإلحصاء الجهاز", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000059", "page": 86, "chunk": 3, "title": "West Bank and Gaza - Capacity-Building for Palestinian Economic and Regulatory Institutions Project", "pdf_url": "http://documents1.worldbank.org/curated/en/396821468329693397/pdf/532780PAD0ARAB1CUMENTS0SEPT02902010.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " from project investments and it provides the overarching framework by which\npotential resettlement issues will be addressed. Finally, the project will also provide resources to\nstrengthen the capacity of the CCEs in environmental and social management. The trainings are\ncurrently being organized for the CCEs and other key stakeholders in all the cities.\n\n\n80. **Safeguards capacity and institutional arrangements.** With regards to capacity, based on\nthe experience gained through the implementation of the PDUE, the PCU is considered to have\nacquired significant experience in implementing World Bank Safeguards Policies. The project\nemploys an Environment Specialist, and will recruit a social development specialist. To ensure\ncontinuity of safeguards supervision at the local municipal/city-level, the project will hire for the\nTLUs five social development specialists who will work in close collaboration with the safeguards\nspecialists at the central level.\n\n\n81. **Youth and gender.** As part of subcomponent 2.3 (Support to local initiatives), the project\nwill support implementation of a series of activities that target youth and women in certain poor\nneighborhoods of the targeted cities. A social assessment of targeted cities is underway and will\nprovide the relevant demographic, social, economic and cultural information regarding the\npopulations, including any baseline data that could be used for M&E. Additionally, the project is\n\n14 For the sludge treatment plant at the Ngombé site, an Abbreviated Resettlement Action Plan (ARAP) had already been prepared,\napproved and implemented under the Cameroon Sanitation Project (P117102). The ARAP was re-disclosed under the proposed\nProject in country and on InfoShop on April 28, 2017.\n15 Due to existing national regulatory and institutional framework for land expropriation and resettlement, World Bank projects\nexperience extensive delays due to compensations. The main constraint in consolidating the World Bank and national framework\nis with regard to the eligibility criteria and the lengthy procedures associated with land acquisition. Based on a request from the", "output": {"entities": {"named_data": [], "descriptive_data": ["social assessment of targeted cities"], "vague_data": ["baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000144", "page": 34, "chunk": 1, "title": "Cameroon - Inclusive and Resilient Cities Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/832091503626454254/pdf/CAMEROON-PAD-NEW-08032017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "social assessment of targeted cities", "label": "DESCRIPTIVE_DATA", "score": 0.8598402738571167, "start": 1205, "end": 1241, "probe_score": 0.0693, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "baseline data", "label": "VAGUE_DATA", "score": 0.6062896847724915, "start": 1380, "end": 1393, "probe_score": 0.0286, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " (US$)**|**Total**<br>**funding**<br>**(US$)**|**Amount**<br>**funded per**<br>**school**<br>**(US$)**|\n|Less than 50|968|27|28|27,000|1,000|\n|50 to 100|9,916|130|26|260,000|2,000|\n|101 to 150|22,147|176|20|440,000|2,500|\n|151 to 200|23,617|134|17|402,000|3,000|\n|201 to 250|22,347|100|16|350,000|3,500|\n|251 to 300|22,358|81|14|324,000|4,000|\n|301 +|123,334|256|8|1,024,000|4,000|\n|**Total**|**224,687**|**904**|**13**|**2,827,000**|**3,127**|\n\n\n\n31", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000030", "page": 39, "chunk": 2, "title": "Lebanon - Emergency Education System Stabilization Project", "pdf_url": "http://documents.worldbank.org/curated/en/578481467991017996/pdf/PAD1190-PAD-P152848-PUBLIC-Box391435B-LB-EESSP-Final-PAD-for-printing.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "br>|\n\n\n\n9. **Reduced compliance costs for taxpayers.** For the taxpayers, the major economic benefits include\na reduction in the time to comply with taxes and the time spent on dealing with tax inspections. The latter\nwill be achieved mainly through a strengthened compliance risk management mechanism and the fact\nthat tax inspectors would now need to spend less time on gathering and processing information, as well\nas doing surveillance during field audits. The 2015 Doing Business Report provides a baseline for the\naverage time needed to comply with taxes. The indicator is reported for a hypothetical medium-size\ncompany, which needs, on average, about 82 hours per year (or approximately 10 days) to comply with\nmajor types of taxes and contributions in Djibouti. The indicator can be subdivided further into the time\nneeded to comply with the corporate income tax (30 hours or 3.75 days per year), labor taxes (36 hours\nper 4.5 days), and consumption taxes (16 hours per 2 days).\n\n\n**Table 4.4. Compliance Costs**\n\n\n\n\n\n\n\n\n\n|Type of taxpayer|Number|Days|Days|Days|Days|Days|Days|Days|Days|\n|---|---|---|---|---|---|---|---|---|---|\n|||2018|2022|2023|2024|2025|2026|2027|2028|\n|Personal income taxpayers|3,224|4.5|4.25|4.2|4.15|4.1|4.05|4.025|4|\n|Corporate income taxpayers|470|3.75|3.5|3.4|3.3|3.2|3.1|3.2|3|\n|Value added taxpayers|320|2|1.9|1.", "output": {"entities": {"named_data": ["2015 Doing Business Report"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000142", "page": 67, "chunk": 2, "title": "Djibouti - Public Administration Modernization Project", "pdf_url": "http://documents1.worldbank.org/curated/en/826531523301322820/pdf/Djibouti-Public-Admin-PAD-PAD2604-04062018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2015 Doing Business Report", "label": "NAMED_DATA", "score": 0.8904022574424744, "start": 465, "end": 491, "probe_score": 0.989, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " as well as capital controls – an unprecedented situation for Lebanon’s historically\nfree capital account. A survey administered before COVID-19 found that 220,000 jobs had been temporarily or\npermanently lost between October 2019 and February 2020, one-third of companies reduced their workforce by 60%\non average and 12% ceased or suspended their operations. <sup>3</sup> [^3: Conducted by InfoPro: http://www.businessnews.com.lb/cms/Story/StoryDetails/7423/220,000-jobs-lost-estimated-by-InfoPro.] On March 7, 2020, the Government of Lebanon (GoL)\ndefaulted on US$1.2 billion Eurobond debt. Much of Lebanon’s current economic and social crisis is attributable to a\nsystem of corrupt elite capture that has failed to deliver adequate services to its people. The impact of the COVID-19\npandemic further exacerbated the precarious situation in the country. The pandemic overloaded a crippled public\nhealth infrastructure, exposing decades of underinvestment for public services. As of June 21, 2021, 543,505 cases\nhave been reported, with over 7,822 deaths due to the pandemic. <sup>4</sup> [^4: World Meter Coronavirus https://www.worldometers.info/coronavirus/country/lebanon/, dd June 21, 2021] The 12-month inflation rate rose steadily in 20192020 and sharply from 10% in January 2020, to 46.6% in April, 89.7% in June, and in August, 120 percent. Importantly,\ninflation is a highly regressive tax, affecting the poor and vulnerable disproportionately, as well as people on fixed\nincome, such as pensioners. <sup>5</sup> [^5: Lebanon Economic Monitor, Fall 2020.]\n\n\n1 World Bank Group; European Union; United Nations. 2020. Beirut Rapid Damage and Needs Assessment. World Bank, Washington, DC. © World Bank.\n<u>[https://openknowledge.worldbank.org", "output": {"entities": {"named_data": ["World Meter Coronavirus", "Lebanon Economic Monitor"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000054", "page": 2, "chunk": 1, "title": "Concept Project Information Document (PID) - Support for Social Recovery Needs of Vulnerable Groups in Beirut - P176622", "pdf_url": "http://documents.worldbank.org/curated/en/883871626924990781/pdf/Concept-Project-Information-Document-PID-Support-for-Social-Recovery-Needs-of-Vulnerable-Groups-in-Beirut-P176622.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Meter Coronavirus", "label": "NAMED_DATA", "score": 0.7609578371047974, "start": 1096, "end": 1119, "probe_score": 0.9794, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Lebanon Economic Monitor", "label": "NAMED_DATA", "score": 0.6041382551193237, "start": 1530, "end": 1554, "probe_score": 0.9736, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 6\nPage 5 of 6\n\n\n\n**Table B: Thresholds for Procurement Methods and Prior Review 1**\n\n\n\n**Expenditure Category** **Contract Value** **Contracts Subject to**\n**Threshold** **Procurement** **Prior Review**\n(US$ thousands) Method (US$ millions)\n1. **Works** - US$50,000 NCB All ICB if any.\n< US$50,000 Simplified NCB NCB contracts above US$150,000\nFirst 5 contracts regardless of\nvalue; first 3 contracts for each\n\n\n\nyear starting January 1.\n**2. Goods** - US$100,000 ICB All ICB.\n< US$100,000 NCB NCB contracts above US$70,000\n< US$50,000 IS or NS where there are at First 5 contracts regardless of\n\n\n\nleast 3 capable national value; first 3 contracts for each\nsuppliers. year starting January 1.\n<US$10,000 DC\n**3. Services** - US$50,000 QCBS Contracts above US$200,000\n(Firms) would be advertised in the UNDB.\n\n              - US$25,000 Contracts for firms above\n(Indiv.) CQ US$50,000, and for individuals\nSS above US$25,000.\n< US$25,000 First 5 contracts regardless of\n=< US$15,000 value; first 3 contracts for each\nyear starting January 1.\nAll TORs\n_____________________________________________________________IAll Sole Source\nThresholds generally differ by country and project.", "output": {"entities": {"named_data": ["UNDB"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000072", "page": 47, "chunk": 0, "title": "Jordan - Health Sector Reform Project", "pdf_url": "http://documents1.worldbank.org/curated/en/466121468773744158/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNDB", "label": "NAMED_DATA", "score": 0.7894626259803772, "start": 809, "end": 813, "probe_score": 0.3126, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_‘I live in a big house of 8 rooms, 1 bathroom and_**\n**_1 kitchen, we are 30 persons living here. We cook_**\n**_outside in the summer and inside in the winter. The_**\n**_roof is worn out and needs maintenance. Water_**\n**_enters when it rains.’_**\n\nGhanaian man, 28, Zwara\n\n\n\n**Risk of eviction**\n\n**One in five respondents reported having been recently**\n**evicted or threatened to be evicted (30/151),** **a much higher**\n**proportion than among the Libyan population assessed in**\n**the MSNA 2018, where only 3% reported being threatened**\n**with eviction and 7% having been evicted.** The locations in\nwhich these cases were reported were mainly Zwara (12/30)\nand Sebha (10/30). The top three reasons reported by refugees\nand migrants for (risk of) eviction were (1) because the\nowner increased the rent/asked for more money, (2) because\nrespondents could not afford the rent anymore, due to reduced\npersonal funds and (3) because the owner wanted them to leave.\n\nHousing represents one of the main expenses for refugees and\nmigrants. Findings from a recent study on refuges and migrants’\naccess and interaction with cash in Libya in June 2018 found\nthat interviewed refugees and migrants spent almost one third of\ntheir income on housing and food (32%) <sup>22</sup> and findings in a study\nby REACH in December 2017 highlighted that housing prices\nhad substantially increased compared to the previous year. <sup>23</sup> The\nabsence of written rental agreements and respondents’ reliance\non their employer for housing make refugees and migrants\nmore vulnerable to exploitation at the hands of landlords and", "output": {"entities": {"named_data": ["MSNA 2018"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000824", "page": 4, "chunk": 2, "title": "Mixed migration routes and dynamics in Libya: Refugees and migrants’ access to food, shelter & NFIs, WASH and assistance in Libya, November 2018", "pdf_url": "https://reliefweb.int/attachments/799c9a34-2a2f-360a-bc66-0ae961f9861c/impact_lby_so_refugees_and_migrants_access_to_food_wash_shelter_november_2018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "MSNA 2018", "label": "NAMED_DATA", "score": 0.8876728415489197, "start": 491, "end": 500, "probe_score": 0.982, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 1\nPage 2 of 3\n\n\n**Project Development** **Outcome / Impact** **Project reports:** **(from Objective to Purpose'**\n**Objective:** **Indicators:**\nExpand access to basic Increased number of school Project Reports. It is assumed that\neducation. places. Government's current fiscal\nsituation will be resolved\n\n(salary payment to civil\nservants and teachers).\nEnrollment increases in MOE reports. Expansion of facilities and\nprimary schools from 35,000 quality will contribute to\nto 80,000 increased enrollment\nincluding among girls.\nIncreased availability of It is assumed that the\ntextbooks. Government maintains\ndouble-shifting.\n\n\nTrained primary school head Headteachers have autonomy\nteachers. and authority in managing the\nschools.\nBetter trained contractual Contractual teachers are\nteachers recruited early enough before\nthe school year to allow time\nfor training.\n\n\n**Output from each** **Output Indicators:** **Project reports:** **(from Outputs to Objective)**\n**Component:**\nIncreased number of school 226 classrooms will be built Monthly disbursement Availability of school places\nplaces. increasing capacity by over summary. will increase enrollment.\n20,000 based on double\nshifting.\nProvide textbooks. Numbers of textbooks per Semi-annual Provision of textbooks will\npupil increases. supervision reports. improve learning.\nTrained primary school head- Primary school head-teachers Annual audit reports; Better trained head-teachers\nteachers. trained and Guidebook for site visits. will improve school\nschool management prepared efficiency.\nand distributed.", "output": {"entities": {"named_data": ["MOE reports"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008719", "page": 30, "chunk": 0, "title": "Kenya - Mombasa - Nairobi Oil Products Pipeline Project", "pdf_url": "https://documents.worldbank.org/curated/en/151901468273350732/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "MOE reports", "label": "NAMED_DATA", "score": 0.6933835744857788, "start": 385, "end": 396, "probe_score": 0.8075, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 2007-2008 where the biggest\nobstacles were socio cultural obstacles (27%) and lack of staffing (23%).\nMENA: Political situation (31%, up from 28% in 2007-2008) and lack of access to\ncommunity of concern (29%).\n\n<u>2.2.2 Comparison between 2007-2008 and 2008-2009 compliance rates</u>\nThe data from 2007-2008 and 2008-2009 is comparable as the response rates only differed\nby one. It is thus possible to explore emerging trends.\n\nComparison between compliance rates in 2007-2008 and 2008-2009 provides a mixed\npicture, as shown in Chart 5 below. Overall, there has been significant improvement in\ncompletion of accountability actions on SGBV. There has been an overall reduction in full\ncompliance with accountability actions for AGDM, with the exception of MFT leadership by\n\n\nPage 12 of 38", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data from 2007-2008 and 2008-2009"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001243", "page": 11, "chunk": 4, "title": "2008-2009 Global Analysis: UNHCR Accountability Framework for Age, Gender and Diversity Mainstreaming and Targeted Actions", "pdf_url": "https://reliefweb.int/attachments/bf74937f-0343-3231-b855-0518e9195067/2012533917143DEF8525761C00737C77-unhcr-accountability-framework-jun09.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from 2007-2008 and 2008-2009", "label": "VAGUE_DATA", "score": 0.6969093680381775, "start": 289, "end": 322, "probe_score": 0.8024, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "- Continue advocacy for close collaboration between the government\n\n(including local/municipal authorities) and civil society actors\n\n   - Provide support to livelihoods solutions for refugees and asylum\nseekers\n\n6. How are you planning to do it?\n3) Offer support (financially and through capacity-building) to\nUNHCR’s partner NGO pNan; promoting the positive, constructive\nwork by NGOs (not just pNan) in support of refugees and asylumseekers vis-à-vis the government to eliminate prejudice and the\nhostility or aversion by government officials towards NGOs and for\nthe government to realize that they can capitalize and utilize NGOs\ninformally and formally for a better implementation of the Refugee\nAct.\n4) Finalize pNan’s livelihoods research and survey; then lead technical\nmeetings and brainstorming sessions, interact with refugees and\nasylum-seekers to identify core areas of possible intervention,\ndiscuss with government, local and municipal authorities, potential\nemployers, and employment agencies to stimulate creation of small\nbusinesses.\n\n7. Who are you going to do it in partnership with?\n\n   - NGOs (many but especially UNHCR’s implementing partner since\n\n2014, pNan)\n\n    - Government: Ministry of Justice, Refugee Division\n\n    - Local and municipal authorities\n\n\n8. How will you monitor the activity and know if it had an impact?\n\n\nBoth 1 and 2 are at the core of UNHCR’s partnership agreement with pNAN\nand will be monitored on a regular basis to evaluate progress/shortcomings.\nIn addition, the two issues will figure prominently in the Representative’s dayto-day work with the Protection Unit to review progress, problems, etc., and to\nsee how the team can move forward.\n\n\n\nBuilding Communities of Practice for Urban Refugees – UNHCR’s Policy Development and Evaluation Service\n\n\n\n**68**", "output": {"entities": {"named_data": [], "descriptive_data": ["livelihoods research and survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000737", "page": 68, "chunk": 0, "title": "Building Communities of Practice for Urban Refugees - Americas Regional Workshop Report", "pdf_url": "https://reliefweb.int/attachments/6ca48499-833b-3b8b-8068-6e9a7c3772d8/americas_workshop_report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "livelihoods research and survey", "label": "DESCRIPTIVE_DATA", "score": 0.6676387190818787, "start": 726, "end": 757, "probe_score": 0.0314, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " enrolment, teacher training,<br>socio‐emotional learning program, school maintenance,<br>student assessment, etc.|MOE (OpenEMIS)|Third Party|The verification agency will check<br>the number of Syrian refugee<br>children enrolled in target schools<br>and will conduct site visits and spot<br>checks in a sample of randomly<br>selected schools to verify<br>enrollment numbers.|\n|**DLR#2**Number of additional<br>children enrolled in public and<br>private KG2|<br> <br> <br>Number of students enrolled in public or freely provided<br>private KG2. Data should be reported disaggregated by type of<br>school, directorate, gender, and nationality.|MOE (OpenEMIS)|Third Party|Enrollment data and disaggregation<br>is provided to the verification<br>agency. The verification agency will<br>conduct site visits and spot checks<br>in a sample of randomly selected<br>schools to verify enrollment<br>numbers. The sampling framework<br>should be acceptable to the WB.|\n|**DLR#3.1**Comprehensive and<br>harmonized quality assurance", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Enrollment data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000041", "page": 43, "chunk": 1, "title": "Jordan - Education Reform Support Program-for-Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/731311512702123714/pdf/Jordan-Educ-Reform-121282-JO-PAD-11142017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Enrollment data", "label": "VAGUE_DATA", "score": 0.662837028503418, "start": 670, "end": 685, "probe_score": 0.0021, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "#### **Services offered and taken up**\n\nRefugees primarily use their mobile wallets to\nobtain cash to pay monthly bills for rent and\nfood. Incentives are often given to withdraw\nall their money in a single transaction since\nthe initial cashing out each month is often\nexempt from fees. One report concluded:\n\n“ _Current humanitarian processes incentivise_\n_recipients to withdraw the full transfer_\n_amount. However, this undermines potential_\n_savings and trust in digital services by_\n_reinforcing the belief that only hard cash, as_\n_opposed to an electronic balance, has_\n_permanent value_ .” <sup>45</sup> [^45: _Humanitarian CT and FI lessons from Jordan, April 2020_]\n\nHowever, WFP has recently decided not to\ncover any withdrawal fees when transferring\nassistance to mobile wallets, with the\nobjective of incentivising digital transactions.\nThere are a range of other services\npotentially available through mobile wallets\nincluding:\n\n\n  - Person to person payments\n\n  - International payments and\nremittances\n\n  - Payment of bills (including phone topup)\n\n  - Savings and credit\n\n  - Insurance\n\n\n\nOne hypothesis is that refugees will become\nmore confident in the use of mobile wallets\nover time and expand the range of services\nthat they access. One potential area for\nexpansion is the payment of bills. The use of\nmobile services reduces the need and\ntransport costs for attending offices to pay\nbills. The Government significantly expanded\nthe use of eFAWATEERcom by government\ninstitutions from 21 in 2017 to 48 by the end\nof 2020. This is reflected by growth in this\nplatform but it still has very limited use by\nrefugees.\n\nAlthough non-Jordanians\nlag Jordanians in most\nmeasures of digital financial\nservices, this is not the\ncase with remittances.\n2017 data suggested that\n31.4% of non-Jordanians\nsent or received\nremittances through formal\nchannels in the previous\nyear, well above the rate of\n19.9% for Jordanians. <sup>46</sup> At\npresent mobile wallet\nproviders are", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["2017 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001027", "page": 26, "chunk": 0, "title": "Financial Inclusion of Refugees in Jordan - Knowledge Note (17 November 2022)", "pdf_url": "https://reliefweb.int/attachments/9c816ff0-5089-4521-bb38-d3262388dac7/171122%20Knowledge%20Note%20Final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2017 data", "label": "VAGUE_DATA", "score": 0.8002950549125671, "start": 1762, "end": 1771, "probe_score": 0.0001, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "diale\nde coopération et d’échange d’informations. En 2022, ce Réseau a fait des mises à jour sur\nles situations nationales en Éthiopie, au Pakistan et au Soudan afin d’éclairer l’engagement\ndes partenaires. Actuellement, il mobilise ses membres pour des engagements d’impact au\nForum mondial sur les réfugiés de 2023, afin d’accroître les possibilités de regroupement\nfamilial, conformément au Pacte mondial sur les réfugiés.\n\n\n54. L’élan ayant porté ces efforts, afin d’assurer les voies de la main-d’œuvre et de\nl’éducation, s’est poursuivi avec le lancement de programmes en Belgique, en France, en\nIrlande, en République de Corée et au Royaume-Uni de Grande-Bretagne et d’Irlande du\nNord. Des voies de l’enseignement postsecondaire se sont élargies en Italie et au Japon. Le\ntravail des équipes spéciales mondiales sur les voies de l’éducation et de la mobilité de la\nmain-d’œuvre a permis d’accroître l’accès aux voies complémentaires par l’engagement\nd’une vaste communauté de pratique, les efforts de renforcement des capacités et\nl’élaboration des outils et des orientations.\n\n### **IV. Respect des droits des déplacés internes**\n\n\n55. Les personnes déplacées à l’intérieur de leur propre pays par des conflits armés, des\nviolences généralisées et des", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001478", "page": 12, "chunk": 1, "title": "Note sur la protection internationale - Note du Haut-Commissaire (A/AC.96/74/3)", "pdf_url": "https://reliefweb.int/attachments/e6011b89-a248-4070-b444-382b10302abb/G2314714.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 1\nPage 2 of 3\n\n\n**Project Development** **Outcome / Impact** **Project reports:** **(from Objective to Purpose'**\n**Objective:** **Indicators:**\nExpand access to basic Increased number of school Project Reports. It is assumed that\neducation. places. Government's current fiscal\nsituation will be resolved\n\n(salary payment to civil\nservants and teachers).\nEnrollment increases in MOE reports. Expansion of facilities and\nprimary schools from 35,000 quality will contribute to\nto 80,000 increased enrollment\nincluding among girls.\nIncreased availability of It is assumed that the\ntextbooks. Government maintains\ndouble-shifting.\n\n\nTrained primary school head Headteachers have autonomy\nteachers. and authority in managing the\nschools.\nBetter trained contractual Contractual teachers are\nteachers recruited early enough before\nthe school year to allow time\nfor training.\n\n\n**Output from each** **Output Indicators:** **Project reports:** **(from Outputs to Objective)**\n**Component:**\nIncreased number of school 226 classrooms will be built Monthly disbursement Availability of school places\nplaces. increasing capacity by over summary. will increase enrollment.\n20,000 based on double\nshifting.\nProvide textbooks. Numbers of textbooks per Semi-annual Provision of textbooks will\npupil increases. supervision reports. improve learning.\nTrained primary school head- Primary school head-teachers Annual audit reports; Better trained head-teachers\nteachers. trained and Guidebook for site visits. will improve school\nschool management prepared efficiency.\nand distributed.", "output": {"entities": {"named_data": ["MOE reports"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014241", "page": 30, "chunk": 0, "title": "Kenya - Rural Water Supply Project", "pdf_url": "https://documents.worldbank.org/curated/en/522771468046142855/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "MOE reports", "label": "NAMED_DATA", "score": 0.6933835744857788, "start": 385, "end": 396, "probe_score": 0.8075, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "policies applicable to<br>Program‐for‐Results operations?<br>Yes [  ]<br>No [ X ]<br>Have these been approved by Bank management?<br>Yes [   ]<br>No [ X ]<br>Is approval for any policy waiver sought from the Board?<br>Yes [   ]<br>No [ X ]<br>** Overall Risk Rating: Substantial**|**Compliance** <br>**Policy** <br>Does the program depart from the CAS in content or in other<br>significant respects?<br>Yes [   ]<br>No [ X ]<br>. <br>Does the program require any waivers of Bank policies applicable to<br>Program‐for‐Results operations?<br>Yes [  ]<br>No [ X ]<br>Have these been approved by Bank management?<br>Yes [   ]<br>No [ X ]<br>Is approval for any policy waiver sought from the Board?<br>Yes [   ]<br>No [ X ]<br>** Overall Risk Rating: Substantial**|**Compliance** <br>**Policy** <br>Does the program depart from the CAS in content or in other<br>significant respects?<br", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000041", "page": 5, "chunk": 32, "title": "Jordan - Education Reform Support Program-for-Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/731311512702123714/pdf/Jordan-Educ-Reform-121282-JO-PAD-11142017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " access by income status and by geographical\nlocation. Rapid enrolment growth without requisite investment in qualified teaching staff, buildings,\nmachinery and equipment has led to slippages in quality and a lack of relevance in degree programs.\nCompounding access and quality concerns, Kenya’s higher education sector faces major financing\nchallenges, which have been exacerbated by the COVID-19 crisis, and must be urgently addressed to\nachieve financial sustainability, cut wasteful expenditures, and enable the sector to contribute to Kenya’s\neconomic recovery. The rapid growth in the number of universities and other public entities has\noverstretched public expenditures relative to allocated resources, with a negative impact on quality.\nCOVID-19 has also exposed the insufficient investment in virtual education delivery models; there is\ncurrently no policy in place for the evaluation and accreditation of online and blended learning despite\ntheir growing importance for tertiary education delivery. Addressing the performance and financial\nsustainability challenges facing higher education requires improving the model for supporting the sector\nwith public resources. At present, the allocation of resources to the numerous public universities is only\npartially based on objective criteria. As a result, universities receive differentiated per student subsidies\nnot linked to institutional performance, raising both equity and efficiency concerns regarding the\nallocation of this subsidy.\n\n**4.51.** **Substance of the reform:** The World Bank is supporting the Ministry of Education to secure the\nsustainable financing of the higher education sector. This includes working with the State Department of\nHigher Education to develop a policy for online and blended learning and facilitate student access to digital\nmodes of learning. To recognize how the suite of ongoing World Bank-supported reforms will culminate\nin a permanent change in the legal framework governing the public financing of tertiary education, the\nproposed series supports replacing the current University Act of 2012 with a new University Act. This will\nshift the financing model in the sector from input-based financing to an objective, performance-based\none, and streamline the overlapping mandates and activities of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017975", "page": 45, "chunk": 1, "title": "Kenya - Accelerating Reforms for an Inclusive and Resilient Recovery Development Policy Financing", "pdf_url": "https://documents.worldbank.org/curated/en/773581623636025182/pdf/Kenya-Accelerating-Reforms-for-an-Inclusive-and-Resilient-Recovery-Development-Policy-Financing.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda: Investment for Industrial Transformation and Employment (P171607)\n\n\nfirms per square kilometer), although business regulations, entry, and exit are the same across districts. Not\nsurprisingly, the market does not generate a large demand for labor, reflected in low hours per week and low\nwages. Wage labor is the main source of income for only 10 percent, and refugees earn wages that are 35 to 45\npercent lower compared to hosts.\n\n\n19. **The prevailing market conditions within RHDs, along with the limited resource endowments, create**\n**barriers to investment and limit the potential growth of firms.** The key factors influencing the types of firms and\nlevels of investment are the following: (a) time horizon, (b) capital, (c) capability, and (d) market demand.\nEconomic actors who eventually plan to return to their countries of origin, operating with limited time horizon,\nmay be reluctant to make long-lived investments. Limited access to finance in RHDs tends to constrain investment.\nFinance is especially difficult to access for lower-income segments among both refugee and host households and\nis often recognized as a binding constraint. Access to financial services for refugees is limited, particularly in the\nWest Nile region. Only one in five refugee households has a loan and less than one in ten of refugees receives any\nform of credit according to the World Bank’s Uganda Refugee and Host Communities 2018 Household Survey. <sup>27</sup>\nFurthermore, low firm capabilities (in this case, business acumen or technology access) limit the ability of supply\nchains to expand in RHDs. Lastly, relatively low disposable incomes result in limited market demand potential in\nRHDs, creating an environment where only business models based on low entry costs, scalability, and portability\nare profitable.\n\n\n20. **COVID-19 has had a profoundly negative impact on Uganda", "output": {"entities": {"named_data": ["Uganda Refugee and Host Communities 2018 Household Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000021", "page": 19, "chunk": 0, "title": "Uganda - Investment for Industrial Transformation and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/469061641926083502/pdf/Uganda-Investment-for-Industrial-Transformation-and-Employment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Uganda Refugee and Host Communities 2018 Household Survey", "label": "NAMED_DATA", "score": 0.9032341241836548, "start": 1411, "end": 1468, "probe_score": 0.9982, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**_Countries of asylum: an African perspective_**\n\n\nWithin the humanitarian community, discussions of the ‘politics of numbers’ almost invariably\nturn to the way in which countries of asylum in developing regions make exaggerated claims\nabout the number of refugees present on their territory. According to the conventional wisdom,\nthey do this for a number of reprehensible reasons: to embarrass the government of the\ncountry of asylum and to besmirch its human rights record; to attract large amounts of\nhumanitarian assistance into the country, which can then be siphoned off to members of the\npolitical, military and business elite; to provide employment to large numbers of bureaucrats\nand refugee camp workers, many of whom would otherwise be without work or an income; to\nensure a generous supply of food and other relief items to exiled groups which are engaged in\npolitical and military campaigns against their country of origin; to maximize the amount of\nforeign exchange brought into the country by humanitarian agencies, which can subsequently\nbe converted at rates favourable to the government; and to cast the most favourable light\npossible on the country’s commitment to humanitarian norms, thereby bolstering its\ninternational reputation and external support.\n\n\nWhile the truth of such allegations may be beyond dispute in certain cases, the notion that ‘host\ncountries always cheat with the figures’ is a crude and, given its prevalence in expatriate\ncircles, perhaps even a racist one. Rather than simply repeating the well-worn stories of\nexaggeration, corruption and statistical sleight of hand (the most lurid of which almost invariably\nrelate to Somalia and other countries in North-East Africa) this section of the paper considers\nthe role of the asylum country in a different, and to some extent more positive perspective.\n\n\nWhile much attention has been given to those countries in which refugee statistics appear to\nhave been inflated, far less attention has been devoted to those situations in which the ‘politics\nof numbers’ leads host country governments to report artificially low refugee statistics. As Yash\nTandon pointed out in", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["refugee statistics", "refugee statistics"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000558", "page": 9, "chunk": 0, "title": "\"Who has counted the Refugees?\" UNHCR and the Politics of Numbers", "pdf_url": "https://reliefweb.int/attachments/524235ad-ad20-3b57-8f5d-fb4ced1d78d8/ED9302CE174AB751C1256DAD0037FB44-hcr-count-jun99.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "refugee statistics", "label": "VAGUE_DATA", "score": 0.6941567659378052, "start": 1913, "end": 1931, "probe_score": 0.3907, "gold": "DATA_MENTION", "gold_tier": "flip"}, {"text": "refugee statistics", "label": "VAGUE_DATA", "score": 0.5134254097938538, "start": 2111, "end": 2129, "probe_score": 0.5685, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the effect of\nincreased transport costs due to internalizing external costs (like GHG emissions) on\nglobal trade volumes of ten commodities. The study found that, by 2040, there is a slight\nreduction (-0.2% to -4.2%) in the trade of all commodities, with the agricultural sector\npotentially experiencing the largest decrease. The study suggests that the decrease in\nagriculture trade is mainly caused by the substitution of foreign with domestic\nproduction.\n\nLee et al. (2013) studied the impact of a carbon tax on the global economy by focusing\ntheir economic model on containerized commodities. They considered six scenarios:\nthree different levels of potential maritime carbon tax (30, 60, 90 USD/ton CO2) across\ntwo geographical scopes (EU and Global). Particular attention was given to the GDPs of\nStates and the changes in volume of container flows in the year 2007. They found that the\nhighest loss in GDP for a country was estimated to be around -0.002% (estimated for\nChina at a carbon price of 90 USD/ton CO2). In contrast, another study estimated a GDP\nloss of up to -1% (estimated for Samoa at a carbon price of 30 USD/ton CO2, (Anger et al.,\n2013)), with some countries potentially even seeing a slightly positive change in their\ngross domestic products. <sup>5</sup>\n\nIn terms of the volume of containers transported globally, the study from Lee et al.\n(2013) found that a carbon tax of 90 USD/ton CO2 would result in the reduction of 915\nthousand TEU. The U.S. would be the most strongly affected State with a reduction of 325\nthousand TEU in imports. The results of the study also captured shifts in trade patterns.\nAn increase in the container trade volumes between Asian countries (China-Japan, ChinaRepublic of Korea) and European countries (Northern Europe-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002365", "page": 18, "chunk": 1, "title": "understanding the economic impacts of greenhouse gas mitigation policies on shipping what is the state of the art of current modeling approaches", "pdf_url": "https://local/prwp/understanding-the-economic-impacts-of-greenhouse-gas-mitigation-policies-on-shipping-what-is-the-state-of-the-art-of-current-modeling-approaches.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "output": {"entities": {"named_data": [], "descriptive_data": ["random survey"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000147", "page": 16, "chunk": 0, "title": "Rwanda - Human Resources Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/837731468759911848/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7714613080024719, "start": 379, "end": 395, "probe_score": 0.582, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "random survey", "label": "DESCRIPTIVE_DATA", "score": 0.7173007130622864, "start": 1487, "end": 1500, "probe_score": 0.012, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "competitiveness. The following regression is estimated to explain the determinants of inventory\nlevels:\n\n\n#### InventoryLevel I, C = ∑β i ⋅ Industry Dummy i + ∑λ x ⋅ Country Characteristic x +ε I,\n\n\n\n_i_ _i_ _x_\n\n_i_ _x_\n\n\n\n_x_ _x_ _I_, _C_\n\n_x_\n\n\n\nIt is difficult to obtain consistent time series data on inventory holdings for developing countries.\nThe aggregate data reported in the national accounts is the change in inventories rather than the\nstock of inventories; often this data is based not on an inventory survey but on the difference\nbetween production and sales which leads to highly inaccurate data <sup>9</sup> [^9: However, it is worth pointing out that the initials results of the research, using the aggregate inventory levels\ncomputed from the National Accounts data, were not inconsistent with the stylized observation that developing\ncountries hold more inventory than developed countries.] .Most national statistics\nagencies do have inventory stock data but they do not publish it. In order to report the size of the\ncountry's industrial production, the statistics agency typically carries out a firm survey or census,\nwhich asks about total inventory holdings at the beginning or end of the year. More detailed\nsurveys break down inventories into three or more categories: raw materials inventory, goods-in\nprocess inventory, and finished goods inventory.\n\nRegressions (1), (2), and (3) of Table 6 present the results of regressing raw materials inventory\non infrastructure and the presence of a free market, as well as some control variables. The\nanalysis uses two proxies for infrastructure, telephone mainlines per person and BERI's\ninfrastructure quality index, which, although more comprehensive, is available for fewer\ncountries. These proxies for infrastructure are significant at the 1 percent or 5 percent level; the\ncoefficients suggest that a one-standard deviation worsening in infrastructure increases\ninventories by 27 percent to 47 percent relative to U.S. levels. The proxy for the lack of a free\nmarket is transfers and subsidies to private and", "output": {"entities": {"named_data": ["BERI's\ninfrastructure quality index"], "descriptive_data": ["national accounts", "inventory survey", "inventory stock data", "firm survey or census"], "vague_data": ["time series data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003765", "page": 23, "chunk": 0, "title": "wps4558", "pdf_url": "https://local/prwp/wps4558.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "time series data", "label": "VAGUE_DATA", "score": 0.6929839849472046, "start": 286, "end": 302, "probe_score": 0.5283, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "national accounts", "label": "DESCRIPTIVE_DATA", "score": 0.508940577507019, "start": 386, "end": 403, "probe_score": 0.9642, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "inventory survey", "label": "DESCRIPTIVE_DATA", "score": 0.6951327919960022, "start": 506, "end": 522, "probe_score": 0.8102, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "inventory stock data", "label": "DESCRIPTIVE_DATA", "score": 0.7600281238555908, "start": 954, "end": 974, "probe_score": 0.9392, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "firm survey or census", "label": "DESCRIPTIVE_DATA", "score": 0.5834673643112183, "start": 1117, "end": 1138, "probe_score": 0.0554, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "BERI's\ninfrastructure quality index", "label": "NAMED_DATA", "score": 0.7526887059211731, "start": 1651, "end": 1686, "probe_score": 0.9636, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000149", "page": 62, "chunk": 2, "title": "Rwanda - Community Reintegration and Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/848391468777982563/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "................................... 31**\n\n\n**Annex II: Revealed Technological Advantage in Russia ........................................................................................ 32**\n\n\n**Annex III: Patent filings of Russian applicants by federal district, 2009 ............................................................. 33**\n\n\n**Annex IV: Start-ups related to the Federal Law 217, dated August 2009 ............................................................ 36**\n\n\n3", "output": {"entities": {"named_data": [], "descriptive_data": ["Patent filings of Russian applicants"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005424", "page": 4, "chunk": 5, "title": "wps6263", "pdf_url": "https://local/prwp/wps6263.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Patent filings of Russian applicants", "label": "DESCRIPTIVE_DATA", "score": 0.5683420896530151, "start": 207, "end": 243, "probe_score": 0.5964, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "** **Cultural and Creative Industries (CCI) are key drivers of the creative economy and represent important sources**\n**of employment, economic growth, and innovation that contribute to city competitiveness and sustainability.** A\nrecent World Bank report points out that through their contribution to urban regeneration and sustainable urban\n\n\n6 Income headcount poverty rates based on upper poverty line of $14 income per day and lower poverty line of $8.5 per day. For the lower\npoverty line, the corresponding increase is from 8.2 percent to 23.2 percent, bringing the total number of poor Lebanese to 1.1 million for the\nlower poverty line and 2.7 million for the upper one. Source: Fakih, Ali, Makdissi, Paul, Marrouch, Walid, Tabri, Rami V., Yazbeck, Myra,\n“Confidence in Public Institutions and the Run up to the October 2019 Uprising in Lebanon,” Working Paper, 2020.\n7 Marot, “Jadaliyya - The End of Rent Control in Lebanon: Another Boost to the ‘Growth Machine?’”\n8 UNDP, “Leave No One Behind for an Inclusive and Just Recovery Process in Post-Blast Beirut”; UN-Habitat, “Lebanon Urban Profile,” 2011.\n9 Since its independence in 1942, the Lebanese State has rarely engaged in the production of public housing or introduced measures to protect\nor secure affordable housing for low-income groups such as property regularization and neighborhood upgrading\n10 InfoPro, “Business Opportunities in Lebanon – Year XI. Real Estate in Greater Beirut [Database],” 2014.\n\n\nPage 7 of 66", "output": {"entities": {"named_data": ["Real Estate in Greater Beirut [Database]"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000034", "page": 12, "chunk": 2, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents1.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Real Estate in Greater Beirut [Database]", "label": "NAMED_DATA", "score": 0.627589762210846, "start": 1423, "end": 1463, "probe_score": 0.7441, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda Secondary Education Expansion Project (P166570)\n\n\nthat 40 percent of teachers in schools have been placed there based on factors other than the class time\nrequired by students. <sup>9</sup> [^9: UNESCO 2014, Teacher Issues in Uganda: A shared vision for an effective teachers’ policy.] Old curricula (replaced in 2020) used to further complicate teacher allocation\nacross schools by imposing too many subjects that required specialized teachers. This inefficiency was\nresolved by the new curricula.\n\n\n8. **In spite of increased access to schooling, the average level of education of the work force remains low**\n**and does not meet labor market requirements.** Uganda has been absorbing 600,000 new entrants to the labor\nmarket each year since 2014. In order to sustainably increase welfare, these entrants must find productive\nemployment. <sup>10</sup> [^10: Uganda job diagnostics/strategy, World Bank, 2018, draft.] Estimates from the Uganda National Household Survey (UNHS) (2016) show that only entrants\nwith post-secondary education can escape informal sector work. In order to increase the employability and\nproductivity of the expanding workforce, supply of quality education, especially for low-income, rural households\nand girls, is critical. According to the UNHS, only one in five people aged 15 and above completed full secondary\neducation. Thus, a large number of youth enter the job market without foundational skills of basic literacy and\nnumeracy, as well as generic skills essential for life and work.\n\n\n9. **Uganda is a pioneer in SSA in terms of setting the goal of achieving universal access to secondary**\n**education.** The secondary education sub-sector in Uganda is centrally managed and comprises six grades, Senior\n1 (S1) to Senior 6 (S6). S1-S4 is categorized as ordinary (‘O’) level, or lower secondary, while S5-S6 is Advanced\n(‘A’", "output": {"entities": {"named_data": ["Uganda National Household Survey", "UNHS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 14, "chunk": 0, "title": "Uganda - Secondary Education Expansion Project", "pdf_url": "http://documents.worldbank.org/curated/en/406361595815248191/pdf/Uganda-Secondary-Education-Expansion-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Uganda National Household Survey", "label": "NAMED_DATA", "score": 0.9097748398780823, "start": 964, "end": 996, "probe_score": 0.9795, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHS", "label": "NAMED_DATA", "score": 0.5107841491699219, "start": 1296, "end": 1300, "probe_score": 0.9429, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**HASHEMITE KINGDOM OF JORDAN**\n**Emergency Services and Social Resilience Project**\n\n\n**TABLE OF CONTENTS**\n\n**Page**\n\n\n**I.** **STRATEGIC CONTEXT .................................................................................................1**\n\nA. Country Context ............................................................................................................ 1\n\nB. Situations of Urgent Need of Assistance ...................................................................... 2\n\nC. Sectoral and Institutional Context .......................................", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000089", "page": 3, "chunk": 0, "title": "Jordan - Emergency Services and Social Resilience Project", "pdf_url": "http://documents1.worldbank.org/curated/en/532171468273353365/pdf/PAD7230P1476890AD0October0100final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " from hospitals, schools, and PHCs and\nauthorizing payments; (ix) managing the outreach campaign; (x) managing the ecard food voucher beneficiaries list, delivery of the e-cards to beneficiaries, and\nfollow up; and (xi) monitoring of the program (specifically inputs and outputs).\n\n     - The NPTP CMU in the PCM is responsible for the following: (i) managing the\n\ncentral database; (ii) validating data and cross-checking with national databases;\n(iii) processing household data, generating scores and ranks according to the\nproxy-means testing (PMT) formula, and providing the list of beneficiaries; (iv)\nmaintaining the PMT formula; (v) analyzing national data and reporting findings\nto the Social Inter-Ministerial Committee (Social-IMC); (vi) monitoring of\nprogram results including targeting performance; and (vii) auditing data\nprocessing.\n\n\n31", "output": {"entities": {"named_data": [], "descriptive_data": ["household data"], "vague_data": ["national data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000047", "page": 41, "chunk": 1, "title": "Lebanon - Emergency National Poverty Targeting Program Project", "pdf_url": "http://documents.worldbank.org/curated/en/810511467987899324/pdf/PAD1030-ENGLISH-P149242-PUBLIC-FINAL-LEB-ENPTP-English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household data", "label": "DESCRIPTIVE_DATA", "score": 0.6298694610595703, "start": 465, "end": 479, "probe_score": 0.0002, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "national data", "label": "VAGUE_DATA", "score": 0.6352871060371399, "start": 650, "end": 663, "probe_score": 0.0015, "gold": "NON_MENTION", "gold_tier": "human-final"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "* **𝑖**\n\nterm. The coefficient on _POL_ should be negative if political connections remained relevant. We also run\n\n**𝑖**\n\nregressions in which we augment the specification with an indicator of the return on the Jakarta Stock\n\nExchange Composite Index net of broader Southeast Asian Effects (referred to as _NR JCI_ ) and its\n\ninteraction with the indicator of political connectedness. _NR JCI_ serves as a measure of event severity. If\n\nthe severity of an adverse rumor affects politically dependent more than less dependent firms the\n\ninteraction term _NR JCI*POL_ should be positive. <sup>28</sup> [^28: Note that we anticipate _NR JCI_ to be negative such that a positive coefficient on the interaction _NR JCI*POL_ implies]\n\nTo set the scene for the analysis Figure B1a shows the response of share prices, as measured by\n\naverage daily returns, by level of political connectedness to rumors about Suharto’s health; connected\n\nfirms experienced greater reductions in their share prices than firms less dependent on Suharto. Such a\n\npattern is not present in Figure B1b, which examines share prices responses to six salient events leading\n\nup to Wahid’s impeachment.\n\nThe 51 surviving firms we use for our analysis of share prices responses to political news in the\n\npost-Suharto era do not seem to be systematically more or less connected than the original sample of 79\n\nfirms used by Fisman as is shown in Table B1 below. Since these 51 firms operate in different sectors, as\n\nis shown in column 2, the stock market data also allow us to examine sectoral heterogeneity in both the\n\nprevalence and valuation of political connections, which helps shed light on the external validity of our\n\n\n27 Specifically, we focus on six salient events. (i) On February 1 Wahid received his first parliamentary censure because of two\n\nfinancial scandals, “Bulogate” and “Bruneigate”. The “Bulogate” scandal involved the alleged theft of $2 million USD from\n\nstate food company Bulog in the name of Wah", "output": {"entities": {"named_data": [], "descriptive_data": ["stock market data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000305", "page": 44, "chunk": 1, "title": "does democratization promote competition evidence from indonesia", "pdf_url": "https://local/prwp/does-democratization-promote-competition-evidence-from-indonesia.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "stock market data", "label": "DESCRIPTIVE_DATA", "score": 0.7649094462394714, "start": 1508, "end": 1525, "probe_score": 0.9659, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Figure 11: Size of young firms over the years**\n\n\n\n\n\nSource: ASI Data pooled from the following census years: 1983/84, 1989/90, 1994/95, 2000/01, 2004/05\n\n**Figure 12: Firm Size and Age: Industry Heterogeneity**\n\n\n\n\n\n\n\nSource: ASI Data pooled from the following census years: 1983/84, 1989/90, 1994/95, 2000/01, 2004/05\n\n\n\n49", "output": {"entities": {"named_data": ["ASI Data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005843", "page": 50, "chunk": 0, "title": "wps6718", "pdf_url": "https://local/prwp/wps6718.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "ASI Data", "label": "NAMED_DATA", "score": 0.7145713567733765, "start": 63, "end": 71, "probe_score": 0.9966, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " The sub-component will\nsupport the implementation of the overall project by PSFU. The sub-component will support regular auditing,\nfinancial reporting, all safeguards assessments and monitoring and evaluation. Establishment of a web platform\nto enable the project to reach all beneficiaries (particularly refugees and host communities) and be accessible\nfrom all locations in Uganda. Monitoring and evaluation (M&E) activities undertaken as part of this component\nwill focus on data collection, survey implementation, and evaluating the economic impact of the program through\na structured impact evaluation at the conclusion of the project. The monitoring component of the M&E approach\nwill require data collection across different dimensions of the project: (a) performance tracking data (for example,\nsales, employment, wages, transactions); (b) activity tracking data reflecting the theory of change; (c) key results\ndata (for example, value of private investment in manufacturing firms, formal employment in manufacturing\nfirms); and (d) tracking of key risks (for example, project implementation performance, NPL ratio of banks, and\nportfolio at risk [PAR] of MFIs). The evaluation component will build on the data collected under the monitoring\ncomponent but additionally focus on implementing a structured impact evaluation process to measure the impact\nand attribution of the program.\n\n\n**C. Project Beneficiaries**\n\n\n52. The project targets direct beneficiaries, 140,000 MSMEs and 120,000 refugees, of these at least 40,000\nare expected to be women-led microenterprises. The project will seek to have a focus on the manufacturing\nand/or exporting supply chains. Other larger-size firms will also benefit from project interventions, for instance\nindirectly benefiting from the receivables financing under sub-component 1.3. The program will also focus on\neconomic opportunities <sup>42</sup> for RHDs by seeking to catalyze investments that enhance economic activity as well as\n\n\n40 This group of firms will typically include", "output": {"entities": {"named_data": [], "descriptive_data": ["performance tracking data", "activity tracking data", "key results\ndata"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000073", "page": 29, "chunk": 1, "title": "Uganda - Investment for Industrial Transformation and Employment Project", "pdf_url": "http://documents1.worldbank.org/curated/en/469061641926083502/pdf/Uganda-Investment-for-Industrial-Transformation-and-Employment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "performance tracking data", "label": "DESCRIPTIVE_DATA", "score": 0.8295468688011169, "start": 764, "end": 789, "probe_score": 0.0024, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "activity tracking data", "label": "DESCRIPTIVE_DATA", "score": 0.7876177430152893, "start": 849, "end": 871, "probe_score": 0.0126, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "key results\ndata", "label": "DESCRIPTIVE_DATA", "score": 0.7998610734939575, "start": 909, "end": 925, "probe_score": 0.0019, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "16\n\n\naddressed the Donors Roundtable and committed to increase Government resources to education to\nover 25% of the budget and noted that the government viewed education as the main source of future\ngrowth in Djibouti.\n\n\n**5. Value added of Bank support in this project**\n\nIDA has been supporting the national consensus building process through the National Education\nForum. The proposed project will help demonstrate that a consensus building approach that involves\n\nall elements of civil society is effective and produces results. In addition the use of an APL\ndemonstrates the long-term commitment by IDA to assist the Government in its strategic goal of\nreaching full enrollment in basic education. It is also hoped that the use of the IDA credit will further\ndecrease the construction unit cost (as IDA is supporting the use of local construction materials which\nshould be cheaper), help develop more cost-effective classroom designs, and provide the environment\nwith a more efficient procurement process.\n\n\n**E. SUMMARY PROJECT ANALYSIS** (Detailed assessments are in the project file, see Annex 8)\n\n\n**1. Economic (see Annex 4)**\n\n\nOther (specify) NPV=US$ million; ERR = ** % (see Annex 4)\n\n\n_** ERR = Over 11% based on system efficiency gains alone without allowing for development_\n_benefits, public goods nature of education and poverty reduction benefits._\n\n\nDjibouti's main resource base is its population and in order to achieve sustained development, the\ncountry needs to improve the quality of its human resource base. Quality starts with improved basic\neducation and school enrollments. In addition, the issue of equity arises. According to the household\nexpenditure survey data, in urban areas, the net enrollment rate (NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey", "output": {"entities": {"named_data": [], "descriptive_data": ["household\nexpenditure survey data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014929", "page": 19, "chunk": 0, "title": "Kenya - Second Highway Sector Project", "pdf_url": "https://documents.worldbank.org/curated/en/568721468045533586/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household\nexpenditure survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8924797177314758, "start": 1661, "end": 1694, "probe_score": 0.9403, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "38      Asylum Levels and Trends in Industrialized Countries - 2010\nMonthly asylum applications lodged in 44 industrialized countries | 2010\nCovering 44 countries which provided monthly data to UNHCR.\nAll data are provisional and subject to change.\nTable 24\nAsylum country\nJan.\nFeb.\nMar.\nApr.\nMay\nJun.\nJul.\nAug.\nSep.\nOct.\nNov.\nDec.\nChange\nNov-Dec\nAlbania\n - \n 3 \n - \n - \n - \n 2 \n 1 \n 2 \n 2 \n - \n - \n 2 \n..\nAustralia\n 644 \n 846 \n 947 \n 747 \n 583 \n 682 \n 683 \n 655 \n 642 \n 595 \n 652 \n 574 \n-12%\nAustria\n 798 \n 794 \n 875 \n 758 \n 910 \n 900 \n 907 \n 1,241 \n 962 \n 972 \n 999 \n 906 \n-9%\nBelgium\n 1,373 \n 1,968 \n 1,424 \n 1,160 \n 1,243 \n 1,375 \n 1,539 \n 1,773 \n 1,906 \n 2,076 \n 2,004 \n 2,100 \n5%\nBosnia and H.\n - \n 4 \n 1 \n 8 \n 3 \n - \n 5 \n 1 \n 4 \n 5 \n - \n 7 \n..\nBulgaria\n 98 \n 85 \n 100 \n 76 \n 54 \n 83 \n 93 \n 94 \n 77 \n 65 \n 93 \n 107 \n15%\nCanada\n 1,939 \n 1,935 \n 2,212 \n 1,751 \n 1,664 \n 1,633 \n 1,656 \n 2,319 \n 2,054 \n 1,918 \n 2,032 \n 2,044 \n1%\nCroatia\n 3 \n 1 \n 4 \n 8 \n 7 \n 26 \n 30 \n 44 \n 58 \n 32 \n 46 \n 31 \n-33%\nCyprus\n 207 \n 212 \n 192 \n 178 \n 211 \n 233 \n 213 \n 172 \n 189 \n 217 \n 350 \n 485 \n39%\nCzech Rep.\n 35 \n 41 \n 53 \n 38 \n 34 \n 36 \n 36 \n 58 \n 25 \n 29 \n 38 \n 39 \n3%\nDenmark\n 408 \n 412 \n 374 \n 354 \n 393 \n 311 \n 366 \n 527 \n 447 \n 531 \n 411 \n 431 \n5%\nEstonia\n 3 \n - \n 3 \n 6 \n 6 \n 2 \n 4 \n 4 \n - \n 1 \n 1 \n 3 \n200%\nFinland\n 419 \n 342 \n 430 \n 314 \n 362 \n 371 \n 316 \n 311 \n 338 \n 295 \n 242 \n 278 \n15%\nFrance\n 3,320 \n 4,348 \n 4,593 \n 3,836 \n 3,729 \n 3,803 \n 3,738 \n 3,604 \n 3,812 \n 4,609 \n 3,881 \n 4,518 \n16%\nGermany\n 2,716 \n 2,453 \n 2,716 \n 2,457 \n 2,417 \n 2", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["monthly data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000381", "page": 37, "chunk": 0, "title": "Asylum figures fall in 2010 to almost half their 2001 levels", "pdf_url": "https://reliefweb.int/attachments/31bc4ca9-e978-3381-b95a-cfc86e39e16b/0C4784C3270B952CC125785E002F12B5-Full_Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "monthly data", "label": "VAGUE_DATA", "score": 0.6252972483634949, "start": 178, "end": 190, "probe_score": 0.0004, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " to Information.\n\n\n_Disbursement Arrangements_\n\n\n7. **Funds flow and disbursement arrangements.** The project will follow the Government’s channel two fund flow\nmechanisms, where IDA funds will be made available directly to NIDP at the PMO. Funds will not flow to other beneficiary\ninstitutions. The PMO will open a DA denominated in US dollars at the NBE. This account shall be opened by the credit\nand grant effectiveness date. The authorized ceiling of the DA would be two quarters forecasted cash requirement based\non the approved AWPB. The PMO may also open an Ethiopian birr bank account for making payments in local currency to\nsuppliers of goods and services. NIDP at the PMO will manage the US dollar and local currency bank accounts. Details of\nthe DA once it is opened and the signatories appointed would be communicated to the World Bank. The fund flow\narrangement for the project is summarized in Figure 1.1.\n\n\n**Figure 1.1. Disbursement Arrangement**\n\n\n8. **Disbursement methods.** The project may follow one or a combination of these disbursement methods: Advance\nto Designated Account, Direct Payment, Reimbursement, and Special Commitment. For Advance to the Designated\nAccount and Reimbursement methods, the project will use IFRs as report-based disbursement method. Disbursement will\nbe made quarterly to the DA to cover cash requirements for the next six months based on a six-monthly expenditure and\ncash requirement forecast (prepared based on the approved AWPB) which is expected to be reported as part of the\n\n\nPage 33 of 39", "output": {"entities": {"named_data": [], "descriptive_data": ["six-monthly expenditure and\ncash requirement forecast"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000005", "page": 43, "chunk": 1, "title": "Ethiopia - Digital ID for Inclusion and Services Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099112223132535848/pdf/BOSIB0efb09b920d90858a0135df22da7d1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "six-monthly expenditure and\ncash requirement forecast", "label": "DESCRIPTIVE_DATA", "score": 0.7099660038948059, "start": 1393, "end": 1446, "probe_score": 0.0573, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and unemployed Lebanese and Syrians has a significant negative\nsocial, economic, and security impacts that could further destabilize the country. The Government of\nLebanon’s (GOL) strategy is to rapidly increase its public investments in key sectors, particularly the\ninfrastructure sectors, to stimulate the economy and create jobs while also meeting its longer‐term\ndevelopment needs therefore ensuring the sustainability of these investments. The GOL has therefore put\nin place a priority investment program of about US$2.5 billion primarily focused on the infrastructure\nsectors, especially energy and transport. The transport sector’s share of the program is about US$1 billion,\nof which about US$510 million for improving the main road network given its bad condition and its high\nimportance for the development of regions and local economies, and for the rapid creation of jobs.\n\n\n**B. Sectoral and Institutional Context**\n\n\n9. **The road network in Lebanon is generally in poor condition due to years of underinvestment**\n**and inefficient spending.** The Lebanese road network consists of a total of about 21,705 km of roads. The\nmain (or national) road network consists of about 6,380 km of mostly paved roads classified as: (a)\nInternational Roads (529 km), (b) Primary Roads (1,673 km), (c) Secondary Roads (1,367 km), and (d)\nInternal Roads (2,811 km). Municipal and other local roads are also mostly paved and represent the\nremaining 15,325 km of the Lebanese road network. While there is no accurate survey of road conditions\n(the last survey was done in 2000) the Ministry of Public Works and Transport (MPWT) estimates that\nabout 15 percent of the main network is in good condition, 50 percent in fair condition, and 35 percent in\npoor condition. The condition of the road network is hindering local economic development particularly\nin rural and lagging regions where", "output": {"entities": {"named_data": [], "descriptive_data": ["survey of road conditions"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 15, "chunk": 1, "title": "Lebanon - Roads and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/210611486651815142/pdf/Lebanon-Roads-Employment-PAD-P160223-01262017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey of road conditions", "label": "DESCRIPTIVE_DATA", "score": 0.7971493005752563, "start": 1516, "end": 1541, "probe_score": 0.7395, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Poles. Visible\n\n\n\ndifferences are identified in 15-19 and\n20-24 age groups, with much higher\nemployment rates for Ukrainian refugees\ndue perhaps to the fact that the Ukrainian\nschool system ends at 17 while the Polish\none at 19. <sup>13</sup> [^13: Children in Ukraine start school at 6 years of age, while in Poland at 7. School system lasts for 11 years in Ukraine and 12 years in Poland. After recent reform,\nUkrainian children who started school in or after 2018 will receive 12 years of schooling.] However, employment rates\ndrop for Ukrainian female refugees in the\n25-29, 30-34, and 35-39 age groups when\ncompared to younger and older groups, as\nwell as to Polish women, which may be due\nto insufficient access to childcare services.\nEmployment rates for Ukrainian female\nrefugees are also substantially lower in the\n55-59 age group, perhaps due to the fact\nthat female retirement age in Ukraine has\nonly recently (in 2021) become 60. <sup>14</sup> [^14: <u>https://www.social-protection.org/gimi/gess/Media.action;jsessionid=U1dm6XAPF38pPk5_pzhfaGoS_rOACMDDVv4w5uevMsKBeQEC5-_g!284293951?id=15680</u> 15 Percentage calculated based on GUS average for the economy as a whole in the months of the SEIS survey.]\n\n\n\n**With the current level of integration**\n**of Ukrainian refugees into the labour**\n**market and the jobs they perform,**\n**their median net earnings are about**\n**four-fifths of the national median**\n\n**– although likely lower in terms of**\n**average or gross earnings.** The median\nnet earnings of Ukrainian refugees in\nQ2 2024 were PLN 4,000 in SEIS, and\nPLN 3,767 in NBP (2024) surveys. This\nis 84% and 79% of the national median,\nrespectively. This estimate would be\nmost likely lower, if data allowed us to\nlook at", "output": {"entities": {"named_data": ["SEIS survey", "NBP (2024) surveys"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 9, "chunk": 1, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS survey", "label": "NAMED_DATA", "score": 0.8586939573287964, "start": 1204, "end": 1215, "probe_score": 0.9934, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "NBP (2024) surveys", "label": "NAMED_DATA", "score": 0.7926384210586548, "start": 1592, "end": 1610, "probe_score": 0.6828, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "output": {"entities": {"named_data": [], "descriptive_data": ["household expenditure survey data", "data from the Household Survey"], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000093", "page": 38, "chunk": 1, "title": "Tajikistan - Education Reform Project (LIL)", "pdf_url": "http://documents1.worldbank.org/curated/en/555901468777299385/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household expenditure survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8699104189872742, "start": 565, "end": 598, "probe_score": 0.7323, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.5808603167533875, "start": 870, "end": 881, "probe_score": 0.1461, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from the Household Survey", "label": "DESCRIPTIVE_DATA", "score": 0.5346028804779053, "start": 1978, "end": 2008, "probe_score": 0.1121, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014881", "page": 62, "chunk": 2, "title": "Kenya - Structural Adjustment Credit Project", "pdf_url": "https://documents.worldbank.org/curated/en/566061468272773431/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015374", "page": 19, "chunk": 1, "title": "Ethiopia - Revised Amibara Irrigation Project", "pdf_url": "https://documents.worldbank.org/curated/en/600751468256145013/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7292463183403015, "start": 272, "end": 283, "probe_score": 0.8771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<br>-<br> <br>-<br> <br>5<br> <br>636<br> <br>Hungary<br>-<br> <br>-<br> <br>-<br> <br>-<br> <br>-<br> <br>-<br> <br>-<br> <br>-<br> <br>-<br> <br>-<br> <br>-<br> <br>-<br> <br>-<br> <br>8<br> <br>Bangladesh<br>*<br>-<br> <br>11<br> <br>7<br> <br>-<br> <br>*<br>-<br> <br>*<br>35<br> <br>8<br> <br>-<br> <br>12<br> <br>150<br> <br>46<br> <br>** October and November 2009 only due to unavailability of data for December.<br>*** Figures may include citizens of Montenegro in the absence of separate statistics available for Serbia and for Montenegro.<br>**** UNHCR estimates.<br>***** Combination of number of cases (DHS) and persons (EOIR).|\n\n\nAsylum Levels and Trends in Industrialized Countries, 2009 31", "output": {"entities": {"named_data": ["Asylum Levels and Trends in Industrialized Countries"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000810", "page": 29, "chunk": 114, "title": "Asylum Levels and Trends in Industrialized Countries 2009 - Statistical Overview of Asylum Applications Lodged in Europe and selected Non-European Countries", "pdf_url": "https://reliefweb.int/attachments/771525db-5c40-325c-8321-aedadd127619/1EAB689A39141C4EC12576EF004A52BC-UNHCR_Mar2010.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Asylum Levels and Trends in Industrialized Countries", "label": "NAMED_DATA", "score": 0.5359285473823547, "start": 643, "end": 695, "probe_score": 0.2234, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Challenges in access to birth registration for refugees and asylum-seekers in Ethiopia | SEPTEMBER 2024\n\n\n\n**Alemwach** : the birth registration of refugee\nchildren relocated immediately after the\nconflict in Tigray did not take place mainly\ndue to the security concerns related to the\nconflict in Tigray and the suspension of\nregistration by the Government. As a result,\nabout 1,000 children were unable to get\nregistered. UNHCR took alternative\nmeasures to assist these children and\nregister them using KOBO software to ensure\nthat they could receive humanitarian\nassistance. As of 1 June 2024, about 700\nchildren included in the KOBO list were\ntransferred into UNHCR´s registration system\nproGres and issued the required documents.\nThe remaining children will be transferred in\nthe same way, despite the challenges in\ninternet connectivity in the region.\n\n**Assosa** : In Tsore refugee camp, there are\nabout 6300 children waiting for birth\nregistration. For other refugee camps in\nAssosa, a few cases have been handled on a\ncase-by-case basis through protection\nlitigation desk with teams composed of RRS,\nUNHCR, and child protection partners.\n\n**Bokh** : There is no functional vital events\nregistration. As a result, about 382 children\nwithout a birth registration have been\nidentified by UNHCR and partner OWSDevelopment Fund.\n\n**Borena and South-Omo settlements** : For\nthese locations, there is no dedicated\npresence of UNHCR and RRS staff. The\nnumber of refugee children registered in\nBorena and South-Omo stand at 1,754 and\n2,290 respectively. There is no available data\non their birth registration.\n\n**Gambella** : In 2019, RRS collaborated with\nImmigration and Citizenship Services to\nlaunch a mass registration campaign and\nissue birth certificates. The campaign\nresolved certain difficulties, but not to the\nintended level, and many children’s births are\nstill not registered. Exceptionally, cases of\nminors with", "output": {"entities": {"named_data": ["KOBO list"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000785", "page": 4, "chunk": 0, "title": "UNHCR Ethiopia: Challenges in Access to Birth Registration for Refugees and Asylum-Seekers in Ethiopia – Protection Brief | September 2024", "pdf_url": "https://reliefweb.int/attachments/73a29f6e-f2a7-4912-bb81-a3ff75393582/Protection%20Brief%20on%20CP-%20September%202024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "KOBO list", "label": "NAMED_DATA", "score": 0.5037383437156677, "start": 632, "end": 641, "probe_score": 0.2912, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nBurundi - Jobs and Economic Transformation Project- PRETE (P177688)\n\n\n<u><mark>Collection</mark></u>\n\n|Number of new NBFIs connected to Bi-Switch and are interoperable within the Burundi Financial System (Number)|Col2|\n|---|---|\n|Description <br>The indicator captures the number of new NBFIs that become interoperable within the Burundi Financial System by<br>connecting to Bi-Switch.|Description <br>The indicator captures the number of new NBFIs that become interoperable within the Burundi Financial System by<br>connecting to Bi-Switch.|\n|Frequency<br>Quarterly|Frequency<br>Quarterly|\n|Data Source<br>Project records|Data Source<br>Project records|\n|Methodology for Data<br>Collection<br>The data will be collected from the agency overseeing the Bi-Switch connection to determine the new connections to Bi-<br>Switch. A follow-up will also be conducted with NBFIs that received support from the project to connect to the Bi-Switch.|Methodology for Data<br>Collection<br>The data will be collected from the agency overseeing the Bi-Switch connection to determine the new connections to Bi-<br>Switch. A follow-up will also be conducted with NBFIs that received support from the project to connect to the Bi-Switch.|\n|Responsibility for Data<br>Collection <br> PIU|Responsibility for Data<br>Collection <br> PIU|\n|**Guaranteed loans disbursed to MSMEs with support of the PPCG fund (Amount [US$])PBC**|**Guaranteed loans disbursed to MSMEs with support of the PPCG fund (A", "output": {"entities": {"named_data": [], "descriptive_data": ["Project records", "Project records"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000004", "page": 43, "chunk": 0, "title": "Burundi - Jobs and Economic Transformation Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099111023141528640/pdf/BOSIB1dda1d49e0221807413cf06ea9ae3f.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Project records", "label": "DESCRIPTIVE_DATA", "score": 0.7926008701324463, "start": 626, "end": 641, "probe_score": 0.9271, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Project records", "label": "DESCRIPTIVE_DATA", "score": 0.6787747144699097, "start": 657, "end": 672, "probe_score": 0.6689, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013731", "page": 62, "chunk": 2, "title": "Ethiopia - Energy Project", "pdf_url": "https://documents.worldbank.org/curated/en/485831468275709540/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "27. Consultants for services meeting the requirements of Section V of the Consultant\nGuidelines will be selected under the provisions for the Selection of Individual Consultants,\nthrough comparison of qualifications among candidates expressing interest in the assignment or\napproached directly.\n\n\n**_Institutional Arrangements for Procurement and Capacity Assessment, Including Risk_**\n**_Mitigation Measures_**\n\n\n28. The EAPSP will prepare and manage contracts signed with two UN agencies, namely\nWFP and FAO, and the Government of Chad. In the implementation of Components A and B of\nthe proposed project, WFP and FAO procurement procedures will be applicable in place of the\nBank Procurement and Consultant Guidelines.\n\n\n**_Risks Identified and Proposed Mitigation Measures_**\n\n\n29. The procurement risk rating is deemed **moderate,** given that the rules and regulations of\nthe two qualified UN agencies that will manage activities under the two components of the\nproject, WFP and FAO, are acceptable to the Bank.\n\n\n**_Procurement Plan_**\n\n\n30. A first draft of a Simplified Procurement Plan for project implementation, providing the\nbasis for the procurement methods, has been developed. This Plan, covering the first 18 months\nof project implementation, was reviewed, discussed, and agreed upon by the Borrower and the\nproject team at negotiations. It will be available in the project’s database, and a summary will be\ndisclosed on the Bank’s external website once the project is approved by the Board. The\nProcurement Plan will be updated in agreement with the Project Team annually or as required to\nreflect the actual project implementation needs and improvement in institutional capacity.\n\n\n**_Publication of Results and Debriefing_**\n\n\n31. Publication of results of the bidding process is required for all ICBs, Limited\nInternational Biddings, and Direct Contracting. Publication should take place as soon as the noobjection is received, except for Direct Contracting, which may be done on quarterly basis and in", "output": {"entities": {"named_data": [], "descriptive_data": ["project’s database"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000007", "page": 50, "chunk": 0, "title": "Chad - Emergency Food and Livestock Crisis Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/179061468215115488/pdf/PAD11010PAD0P1010Box385329B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "project’s database", "label": "DESCRIPTIVE_DATA", "score": 0.8571559190750122, "start": 1383, "end": 1401, "probe_score": 0.007, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " et faciliter l'accès humanitaire, notamment la mise en place du Groupe de travail accès national (GTA-N) à Bamako,\nl'adoption de la stratégie d'accès de l'EHP (révisée en 2024), et la mise en place des Groupes de travail accès régionaux (GTAR) à Ménaka, Tombouctou, Gao, Ségou et Mopti. Le Cluster Protection participe activement à ces espaces de coordination en\nvue de contribuer à des actions et initiatives coordonnées et harmonisées pour améliorer l'accès et l'action humanitaire, en\nassurant l'assistance et la protection de toutes les personnes vulnérables, dans le respect des principes humanitaires. Le\nCluster Protection contribue notamment en termes d’analyse et de plaidoyer, utilisant les données du monitoring de\nprotection, et l’engagement communautaire pour approfondir l'analyse des tendances en matière de contraintes d'accès, et\nporter des messages conjoints auprès de l’EHP.\n\n**<u>LACUNES CRITIQUES DANS LE FINANCEMENT ET LA POPULATION TOUCHÉE</u>**\n\n\nEn décembre 2023, une partie importante des interventions humanitaires sur les engins explosifs au Mali ont pris fin avec le\ndépart de la MINUSMA. Malgré l’implication des ONG et des structures étatiques luttant contre les mines dans la région,\nl’action contre les mines est fortement réduite. Par ailleurs, le nombre de victimes de violations des droits humains a fortement\naugmenté, ce qui", "output": {"entities": {"named_data": [], "descriptive_data": ["données du monitoring de\nprotection"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001406", "page": 13, "chunk": 1, "title": "Mali : Analyse de Protection - Mise à jour des tendances en matière de conflits et de risques de protection au premier semestre 2024 (juillet 2024)", "pdf_url": "https://reliefweb.int/attachments/da21b072-22ff-470b-ba2d-813e8d08fa7c/analyse_pau_mali_semestre_1_2024_gpc.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "données du monitoring de\nprotection", "label": "DESCRIPTIVE_DATA", "score": 0.723824143409729, "start": 702, "end": 737, "probe_score": 0.0554, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Glass Barriers\n\n\nsampling frame is an exhaustive list of shipment crossings, the sample was meant to be\nrepresentative of small-scale cross-border trade crossings rather than crossers. <sup>6</sup> The IDIs\ncontain detailed information on both crossers (demographics, education, past\nexperiences as a trader/broker, perception of challenges, etc.) and crossings (goods\ntransported, purchase value, selling price, etc.).\n\n### 3. Overview of the Border Economy\n\n###### Definition of the population of interest\n\n\nSmall-scale cross-border trade (SSCBT) is an elusive concept. Different definitions have been\nused in the literature, <sup>7</sup> different rules apply depending on the country, <sup>8</sup> the value and quantity\nof goods traded per crossing may vary from one checkpoint to the next and SSCBT hides a\nvariety of actors. Subsequently, we need develop an alternative, unified definition of SSCBT.\n\nBased on field observations and stakeholder interviews, the population of interest shall be\ndefined along the following criteria in this study:\n\n\n   - **People who deal with authorities** . These comprise: (i) traders who do not hire brokers\nand thus pay taxes and fees and interact with border authorities in general themselves;\nand (ii) brokers who do that on behalf of traders. <sup>9</sup> Transporters who do not act as brokers\nand traders who do not interact with authorities are not included in the population of\ninterest. This criterion is meant to capture those who are the most knowledgeable about\nborder-crossing processes and most directly affected by border conditions. In what\nfollows, the population of interest shall be referred to as “traders and brokers” or\n“SSCBTers.”\n\n   - **People involved in “small-scale” trade** —as traders", "output": {"entities": {"named_data": ["Glass Barriers\n\n\nsampling frame", "IDIs"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007207", "page": 7, "chunk": 0, "title": "wps8249", "pdf_url": "https://local/prwp/wps8249.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Glass Barriers\n\n\nsampling frame", "label": "NAMED_DATA", "score": 0.7726231217384338, "start": 0, "end": 31, "probe_score": 0.8663, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "IDIs", "label": "NAMED_DATA", "score": 0.6735798120498657, "start": 202, "end": 206, "probe_score": 0.9706, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**9** Motor Cycle-Discover 125cc **1** **60,000**\n**10** Motor Cycle-Boxer 150cc **1** **63,000**\n\n**11** Managerial Chair **1** **18,000**\n\n12 Photo Copy Machine **1** **80,800**\n**13** Binding Machine **1** **3,700**\n\n14 Laptop Computer 2 44,500\n\n**15** Desk top computer **1** **27,900**\n\n**16** Colour Printer **1** **8,899**\n**17** Projecter **1** **21,850**\n**18** Laminating Machine **1** 3,480\n**19** HP Printer _2_ **19,600**\n20 Shelf 2 **18,000**\n\n21 Managerial Table 2 10,400\n22 Managerial Table _2_ **11,900**\n**23** Box **1** 2,200\n24 Contact free hand wash **5** **18,000**\n**25** Safe Box _2_ 17,400\n**26** Managerial Chair **5** 34,000\n**27** Refrigrator **1** 12,450\n**28** Hard disk 2 **7,798**\n**29** Managerial Table **3** **17,850**\n**30** Double Cabin Toyota Land Crueser **1** **3,926,606**\n\n**1** 4,624,533\nImplementing Entity: Shashemene\n\n\n\n**1*", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007248", "page": 19, "chunk": 0, "title": "Ethiopia - AFRICA EAST - P156433 - Second Ethiopia Urban Water Supply and Sanitation Project - Audited Financial Statement", "pdf_url": "https://documents.worldbank.org/curated/en/099655004082233836/pdf/P1564330ce8b4707b0b3fa046b161735c57.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Participation\nand Information Experiment and column (ii) uses 2006 baseline data for the Participation Experiment. Description\nof variables: Utilization from health facility records summarizes outpatients and deliveries. Utilization pattern of the\nusers summarizes seven measures including use of the project facility, an NGO facility, a private-for-profit facility,\nother government facility, another provider, a traditional healer and self-treatment, reversing sign of traditional\nhealer and self-treatment. Quality of services according to users summarizes the use of any equipment during the\nvisit and waiting time, reversing sign of waiting time. Catchment area statistics summarizes the number of\nhouseholds in the catchment area, the number of households per village, and the distance from the villages to the\nhealth facility. Health facility characteristics uses different data in columns (i) and (ii) because of differences in data\ncollected at the time of each baseline survey. For column (i) it summarize ten measures about the presence of piped\nwater, access to a radio, a newspaper, the existence of a separate maternity unit, the distance to the nearest Local\nCouncil I and to the nearest public health provider, number of staff with advanced A-level education and with less\nthan A-level education, drank safely today and days without electricity, reversing sign of days without electricity\nand distance to nearest local council. For column (ii) it summarizes six measures about the presence of piped water,\nworking water source, functioning electricity, yellow star certification of the health facility, number of staff with\nadvanced A-level education and with less than A-level education. Citizen perceptions of treatment summarize four\nmeasures about politeness, attention, freedom to express themselves and information about drug deliveries. Supply\nof drugs summarizes five measures about the availability of erythromycin, chloroquine, septrine, quinine and\nmebendazole. User charges summarize four measures about the existence of user charges for drugs, general\ntreatment, injections and deliveries, reversing all signs.", "output": {"entities": {"named_data": [], "descriptive_data": ["2006 baseline data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006117", "page": 33, "chunk": 1, "title": "wps7015", "pdf_url": "https://local/prwp/wps7015.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2006 baseline data", "label": "DESCRIPTIVE_DATA", "score": 0.754445493221283, "start": 63, "end": 81, "probe_score": 0.4914, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " intervention. This covers activities under<br>Component 2.|\n|Frequency|Quarterly|\n|Data source|Project MIS and Project Progress Reports.|\n|Methodology for<br>Data Collection|Monitoring project implementation. Hectarage mapped to include area of direct activity implementation (site<br>of works).|\n|Responsibility for<br>Data Collection|IA|\n\n\n\nPage 31", "output": {"entities": {"named_data": ["Project MIS and Project Progress Reports"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000186", "page": 46, "chunk": 2, "title": "Uganda - Second Phase of the Development Response to Displacement Impacts Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099051525164525007/pdf/BOSIB-ca473522-8ad0-4c80-9f0d-88bf887f2a2f.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Project MIS and Project Progress Reports", "label": "NAMED_DATA", "score": 0.6214077472686768, "start": 96, "end": 136, "probe_score": 0.0061, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "on</sup> <sup>the</sup> <sup>estimated</sup>\n\nfuture cash flows of <sup>the</sup> <sup>financial</sup> <sup>asset</sup> <sup>have</sup> <sup>occurred. Evidence</sup> <sup>that a</sup> <sup>financial</sup> <sup>asset</sup> <sup>is</sup> <sup>credit impaired</sup> <sup>include</sup>\n\n\n\nobservable data <sup>about the following</sup> <sup>events:</sup>\n\n\n\n\n**-** significant financial <sup>difficulty of the</sup> <sup>debtor;</sup>\n\n**-** a breach of contract;\n\n**-** it is probable that the debtor <sup>will enter bankruptcy;</sup> <sup>and</sup>\n\n**-** the disappearance of <sup>an</sup> <sup>active</sup> <sup>market</sup> <sup>for the financial asset because of financial difficulties.</sup>\n\n\n\nThe gross carrying <sup>amount</sup> <sup>of financial</sup> <sup>assets with</sup> <sup>exposure</sup> <sup>to</sup> <sup>credit</sup> <sup>risk</sup> <sup>at</", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["observable data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002660", "page": 34, "chunk": 6, "title": "Kenya - EASTERN AND SOUTHERN AFRICA - P165034 - Kenya Affordable Housing Finance Project - Audited Financial Statement", "pdf_url": "https://documents.worldbank.org/curated/en/099052725021539683/pdf/P165034-49f8d1fd-ba9d-4841-9363-4c3234062242.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "observable data", "label": "VAGUE_DATA", "score": 0.7308480143547058, "start": 285, "end": 300, "probe_score": 0.1209, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\n**The only reliable timeseries of the**\n**number of Ukrainians in Poland over**\n**the past decade is social insurance**\n**data on insured Ukrainian nationals,**\n**though it accounts only for workers.**\nThe focus on workers rather than on\nthe entire group does not change much\nin the data from before February 2022,\nas the previous influx consisted mainly\nof Ukrainians seeking employment in\nPoland. However, the actual number\nof employed Ukrainian nationals must\nhave been higher. First, certain types\nof legal work often undertaken by\ntemporary employees do not require\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 4. Age and gender structure of Ukrainian refugees**\n\n\n\n**Most of the refugees from Ukraine**\n**currently living in Poland are women**\n**and children, though over half of**\n**the total population is of working**\n**age.** The best population data available\nis the regularly updated active PESEL\ndatabase. <sup>4</sup> [^4: Available in the repository maintained by the government <u>https://dane.gov.pl/pl/dataset/2715</u> as well as UNHCR data portal <u>https://app.powerbi.com/</u>\n<u>view?r=eyJrIjoiODhkOGZiMzctZTliMi00NzA5LTgyM2QtZGZhM2IwZjBiZDk2IiwidCI6ImU1YzM3OTgxLTY2NjQtNDEzNC04YTBjLTY1NDNkMmFmODBiZSIsImMiOjh9</u>] According to the registry, 61.5%\nof the registered are women and 38.5%\nare men. The database also includes the\nage of PESEL UKR holders, which indicates\nthat over half (57.4%), i.e. more than\n560 thousand people, are of working age\n(18-65). While the male and female shares\nof people below 18 years of age (20% and\n19%, respectively) and 66+ (1%", "output": {"entities": {"named_data": ["PESEL\ndatabase"], "descriptive_data": ["data on insured Ukrainian nationals"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 4, "chunk": 0, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on insured Ukrainian nationals", "label": "DESCRIPTIVE_DATA", "score": 0.8426333665847778, "start": 198, "end": 233, "probe_score": 0.9623, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PESEL\ndatabase", "label": "NAMED_DATA", "score": 0.8646316528320312, "start": 1020, "end": 1034, "probe_score": 0.9643, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " was poor in 2021 as floods affected both agriculture and oil production and subnational\nconflict flareups constrained economic activities in parts of the country. Consequently, the economy is estimated to have\ncontracted by 5.1 percent in FY2020/21 and poverty to have increased by 2.3 percentage points to 79.3 percent <sup>2</sup> [^2: World Bank (2022). Towards a Jobs Agenda - South Sudan Economic Monitor (February 2022): Washington, DC] . The\nrecent shocks had detrimental effects on household welfare as income from farming was already reduced for 38 percent\nof households (HHs) and had stopped entirely for 11 percent of HHs during the COVID-19 pandemic in 2020 <sup>3</sup> [^3: World Bank (2020). Socioeconomic impacts of COVID-19 - South Sudan Economic Update (December 2020): Washington, DC] . Inflation\naveraged 43 percent in FY2020/2021 (compared to 33 percent in FY2019/2020) but was on a declining path in the first\nhalf of FY2021/2022. However, high frequency data indicate that food prices started increasing in February 2022.\nNevertheless, inflation is expected to decline gradually over the medium term and will benefit from improved fiscal and\nmonetary discipline, exchange rate market liberalization, and deepening public financial management reforms. South\nSudan’s fiscal position benefited from higher than projected oil revenue, improved domestic revenue mobilization, and\nfiscal consolidation efforts. The overall FY2020/21 budget deficit is estimated to have narrowed to about 6.9 percent of\nGross Domestic Product (GDP) from 9.8 percent in FY2019/20. Nevertheless, the government is accumulating arrears to\npublic service salaries, currently estimated at about two percent of GDP or five months of salaries, while South Sudan\nremains at high risk of debt distress, with total public debt estimated at 59.5 percent of GDP at end of FY2020/21. Given\ndeclining oil production and the lingering effects of climate shocks, the economy could", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["high frequency data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 11, "chunk": 1, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "high frequency data", "label": "VAGUE_DATA", "score": 0.7571456432342529, "start": 963, "end": 982, "probe_score": 0.4024, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "weight in the first year. Furthermore, regarding the CI, data on cleanliness will only be available after the\nfirst year of the project when the baseline study (routing optimization, bin evaluation, evaluation of\nstreets/areas) is conducted. CI performance targets proposed in the technical scorecard will thus be\ncalibrated after Year 1.\n\n**Table 3 Key Indicators and Proposed Weights**\n\n|#|Indicator|Weights: Year 1|Weights: Years 2-4|\n|---|---|---|---|\n|1 <br>|Strategy development/MIS implementation|50%|–|\n|2 <br>|Improvement in cleanliness of areas|15%|20%|\n|3 <br>|Increase in total waste managed|20%|30%|\n|4 <br>|Increase in percentage fee collection by M/VCs <br>|Increase in percentage fee collection by M/VCs <br>|Increase in percentage fee collection by M/VCs <br>|\n|4a <br>| <br>Increase in percentage fee collection in<br>Hebron governorate <br>|9%|15%|\n|4b <br>| <br>Increase in percentage fee collection in<br>Bethlehem governorate|6%|10%|\n|5|Increase in cost recovery|–|25%|\n||**Total **|**100% **|**100% **|\n\n\n\nThe actual subsidy payment for each indicator, in each audit period, will be calculated based on the\nindicator’s weight and on the year’s subsidy requirements, provided they are above the minimum\nperformance levels identified. If performance for any indicator falls below the minimum performance\nlevel, no subsidies are disbursed for that particular indicator. In cases where performance just meets the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on cleanliness"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000056", "page": 20, "chunk": 0, "title": "Middle East and North Africa - Output-Based Aid Pilot Solid Waste Management Project", "pdf_url": "http://documents1.worldbank.org/curated/en/388311468275943106/pdf/84657-PAD-P132268-Project-Commitment-Paper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on cleanliness", "label": "VAGUE_DATA", "score": 0.6822983026504517, "start": 57, "end": 76, "probe_score": 0.0497, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**2.2** **Descriptive statistics**\n\n\nAnnex A contains summary tables of the department‐ and sector‐level data. Tables A1‐A3 present the\nlevels and growth rates of labor productivity during 2002‐2012, by sector and department. Table A4 shows\nthe rates of poverty, by department. Tables A5‐A6 present information on the spatial concentration of\ndifferent sectors across departments. Table A7 presents some other relevant department‐level\ninformation, such as whether the department contains a port, a mine and a city with population of\n500,000 or more, and the percent population residing in urban areas.\n\n\nTable A1 shows that in both 2002 and 2012, the top one‐third of departments in terms of labor\nproductivity were: Moquegua, Lima‐Callao, Pasco, Tacna, Arequipa, Ancash, Ica and Madre de Dios. In\ngeneral, these departments have high labor productivity across the board. That is, they are also ranked\nhigh in terms of labor productivity within each main sector (Tables A1‐A3).\n\n\nThis correlation is the strongest for agriculture: for instance, the top ten most productive regions are also\nin the top ten in agricultural labor productivity, with one exception. This is not surprising given the large\nshare of agriculture in employment. While departments which rank high in overall labor productivity do\ntend to rank high on labor productivity in manufacturing, mining and services too, there are more\nexceptions compared to agriculture. Ayacucho, Cusco, Huancavelica, Piura, Junín and Amazonas are\nexamples of departments with above median productivity in the secondary or tertiary sectors, but not in\noverall productivity, in 2012.\n\n\nTables A1‐A3 also show that with the exception of mining, 2002‐2012 was a period of rising labor\nproductivity in Peru. Overall labor productivity grew annually at a rate of 3.7 percent. It grew by", "output": {"entities": {"named_data": [], "descriptive_data": ["department‐ and sector‐level data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006545", "page": 6, "chunk": 0, "title": "wps7499", "pdf_url": "https://local/prwp/wps7499.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "department‐ and sector‐level data", "label": "DESCRIPTIVE_DATA", "score": 0.8331872224807739, "start": 76, "end": 109, "probe_score": 0.8848, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "3.2.1 Macro stabilization variables\n\n\nWe include the log of _government consumption_ as a share of GDP, _lkg_, calculated\nas the log of csh_g from the PWT 10.0. This variable is supposed to capture growthreducing effects through distortionary taxation (Afonso and Furceri 2010) or public\ndebt issuance. The negative association with growth is motivated by the fact that\nwe include the positive effects that government consumption may have on growth\nseparately, for example, through spending on infrastructure. As our model describes\nlong-run growth, it is also important not to conflate the short-term positive stimulus\neffect that increased government consumption can have during economic\ndownturns. <sup>7</sup> [^7: For similar reasons, we also do not include fiscal deficit variables, which are highly cyclical and hence tend\nto smooth out over the five-year averages.]\n\n\n_Inflation_ is measured as the log change of _v_c/q_c_ (household consumption in\ncurrent national prices/household consumption in constant national 2017 prices)\nfrom the national accounts module of the PWT 10.0, which has greater availability\nthan inflation data from the World Bank’s World Development Indicators (WDI). <sup>8</sup> [^8: We add 1 to this variable to avoid negative numbers, which cannot be translated into logs.]\n\n\nThe _real exchange rate_, _lrer_, is calculated as the log of the GDP price level (in PPP)\nover the nominal exchange rate: _pl_gdpo/xr_, both taken from the PWT 10.0. Since\n_xr_ is measured as national currency/US$, an increase in _lrer_ reflects a real\nappreciation, which is expected to have a negative effect on output and growth\nthrough various channels (e.g., Rapetti 2019; Levy-Yeyati, Sturzenegger, and\nGluzmann 2013). <sup>9</sup>\n\n\n3.2.2 Financial variables\n\n\nTo measure countries’ _financial development_, we use the log of domestic credit to\nthe private sector", "output": {"entities": {"named_data": ["PWT 10.0", "PWT 10.0", "World Development Indicators", "PWT 10.0"], "descriptive_data": [], "vague_data": ["inflation data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000876", "page": 9, "chunk": 0, "title": "idu0864f5b27096720401c084f70585706522d9d", "pdf_url": "https://local/prwp/idu0864f5b27096720401c084f70585706522d9d.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PWT 10.0", "label": "NAMED_DATA", "score": 0.6211433410644531, "start": 151, "end": 159, "probe_score": 0.9579, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PWT 10.0", "label": "NAMED_DATA", "score": 0.5324646830558777, "start": 1078, "end": 1086, "probe_score": 0.9981, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "inflation data", "label": "VAGUE_DATA", "score": 0.698074460029602, "start": 1124, "end": 1138, "probe_score": 0.9634, "gold": "DATA_MENTION", "gold_tier": "flip"}, {"text": "World Development Indicators", "label": "NAMED_DATA", "score": 0.8583076596260071, "start": 1161, "end": 1189, "probe_score": 0.9877, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "PWT 10.0", "label": "NAMED_DATA", "score": 0.5155135989189148, "start": 1466, "end": 1474, "probe_score": 0.9981, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|||||||2018-12-13||||||||2019-01-10||2019-02-09||\n|KE-KAKAMEGA COUNTY-<br>84488-GO-RFQ / procure 50<br>delivery sets @ for level 3, 4 &<br>5 heath facilities<br>|IDA / 58360|Improving Primary Health<br>Care Results|Post|Request for<br>Quotations|Limited<br>|Single Stage - One<br>Envelope||3,500.00|0.00|Pending<br>Implementati<br>on|||||||2018-12-03||||||||2018-12-31||2019-01-30||\n|KE-KAKAMEGA COUNTY-<br>85290-GO-RFQ / procure<br>equipments for RH program<br>& county decentralised<br>training centre,  2 LCD<br>projector 2  projector screens<br>, 2  2 x2m white boards, 4<br>roll up kits|IDA / 58360|Improving Primary Health<br>Care Results|Post|Request for<br>Quotations|Limited<br>|Single Stage - One<br>Envelope||8,720.00|0.00|Pending<br>Implementati<br>on|||||||2018-12-04||||||||2019-01-01||2019-01-31||\n|KE-KAKAMEGA COUNTY-<br>84300-GO-RFQ /<br>procurement of 4300 colored<br>community spring weighing<br>", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000452", "page": 5, "chunk": 6, "title": "Kenya - AFRICA EAST- P152394- Transforming Health Systems for Universal Care - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099020001072218824/pdf/Kenya000AFRICA0Procurement0Plan0206.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Policy Research Working Paper 8123\n\n### **Abstract**\n\nThis paper proposes a methodology to approximate indi\nvidual income distribution dynamics using only time series\ndata on aggregate moments of the income distribution.\nUnder the assumption that individual incomes follow a\n\nlognormal autoregressive process, this paper shows that\nthe evolution over time of the mean and standard deviation of log income across individuals provides sufficient\ninformation to place upper and lower bounds on the\ndegree of mobility in the income distribution. The paper\ndemonstrates that these bounds are reasonably informative,\nusing the U.S. Panel Study of Income Dynamics where the\npanel structure of the data allows us to compare measures\n\n\n\nof mobility directly estimated from the micro data with\napproximations based only on aggregate data. Bounds on\nmobility are estimated for a large cross-section of countries, using data on aggregate moments of the income\ndistribution available in the World Wealth and Income\nDatabase and the World Bank’s PovcalNet database. The\nestimated bounds on mobility imply that conventional\nanonymous growth rates of the bottom 40 percent (top\n10 percent) that do not account for mobility substantially\nunderstate (overstate) the expected growth performance of\nthose initially in the bottom 40 percent (top 10 percent).\n\n\n\nThis paper is a product of the Macroeconomics and Growth Team, Development Research Group. It is part of a larger\neffort by the World Bank to provide open access to its research and make a contribution to development policy discussions\naround the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors\nmay be contacted at akraay@worldbank.org and rvanderweide@worldbank.org.\n\n\n_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development_\n_issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The", "output": {"entities": {"named_data": ["U.S. Panel Study of Income Dynamics", "World Wealth and Income\nDatabase", "PovcalNet database"], "descriptive_data": ["micro data", "data on aggregate moments of the income\ndistribution"], "vague_data": ["time series\ndata", "aggregate data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007100", "page": 1, "chunk": 0, "title": "wps8123", "pdf_url": "https://local/prwp/wps8123.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "time series\ndata", "label": "VAGUE_DATA", "score": 0.7869219779968262, "start": 155, "end": 171, "probe_score": 0.8674, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "U.S. Panel Study of Income Dynamics", "label": "NAMED_DATA", "score": 0.8532050251960754, "start": 621, "end": 656, "probe_score": 0.9998, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "micro data", "label": "DESCRIPTIVE_DATA", "score": 0.564091682434082, "start": 768, "end": 778, "probe_score": 0.9291, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "aggregate data", "label": "VAGUE_DATA", "score": 0.5948539972305298, "start": 813, "end": 827, "probe_score": 0.9722, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data on aggregate moments of the income\ndistribution", "label": "DESCRIPTIVE_DATA", "score": 0.8398128151893616, "start": 908, "end": 960, "probe_score": 0.9716, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "World Wealth and Income\nDatabase", "label": "NAMED_DATA", "score": 0.9388570785522461, "start": 978, "end": 1010, "probe_score": 0.9558, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PovcalNet database", "label": "NAMED_DATA", "score": 0.9342086315155029, "start": 1032, "end": 1050, "probe_score": 0.9853, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_(b) Ethno-Religious Features_\n\n\nThe density in Tigray Region in this time was 116 persons /square kilometers. Other ethnic groups in\nTigray consist of Amhara (1.63%), Irob (0.71%), Afar (0.29%), Agaw (0.19%), Oromo (0.17%) and\na Nilo-Saharan-speaking Kunama (0.07%). In the region, 95.6% of the population are Orthodox\nChristians, 4% Muslims, 0.4% Catholics and 0.10% Protestants.\n\n\n**<u>Amhara Regional State</u>**\n\n\n_(a) Demographic and Economic Features_\n\n\nThe Amhara Regional State covers a total land area of approximately 154,000 km <sup>2</sup> . The regional\naverage landholding is 0.3 ha/household. According to the CSA, 2013 national population projection\ndata from 2014-2017, the region has a total population of 20,018,988, out of which 84% live in rural\nareas. Even if more than 15 soil types are found in the region, leptosols, followed by Vertisols and\nCambisols exist predominantly. Under RLLP 48 watersheds in the region are targeted for the\nimplementation of RLLP activities (34 SLMP-1&2 and 14 newly added woredas).\n\n\n<u>Table 4. Amhara region existing and newly added RLLP targeted woredas</u>\n\n|No.|Existing woredas (WB- I & II)|Col3|Col4|Newly added woredas (WB- III)|Col6|\n|---|---|---|---|---|---|\n|1|Alefa|19|Gubalafto|", "output": {"entities": {"named_data": [], "descriptive_data": ["2013 national population projection\ndata"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010201", "page": 30, "chunk": 0, "title": "Ethiopia - Resilient Landscape and Livelihood Project : social assessment : Social assessment", "pdf_url": "https://documents.worldbank.org/curated/en/250681528364951447/pdf/Social-Assessment-RLLP-WB-MEC-SD-REV-May-21-2018-Clean-FOR-DISCLOSURE.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2013 national population projection\ndata", "label": "DESCRIPTIVE_DATA", "score": 0.5620561838150024, "start": 631, "end": 671, "probe_score": 0.9591, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "- **UNHCR Italy (Rome):** Some ad hoc initiatives\npromoted under the two partnerships, an online\nconsultation portal and focus groups discussions but\nnot with this specific focus on info/communication. <sup>6</sup>\n\n\n     - **UNHCR Sudan:** In the 2019 Multi-Functional Team\nParticipatory Assessment, CwC has been chosen as a\nthematic area. As part of this, a CwC survey is being\nadministered to capture refugee information needs\nand preferences.\n\n\n     - **UNHCR Sudan (Kassala):** Communication with\nrefugees was a mandatory question/area of attention\nin the recently concluded participatory assessment\n(November 2019).\n\n\n     - **UNHCR TRS:** Preparatory research was conducted\nwith the aim of developing a tailored communication\nstrategy for TRS. The survey fed into the various\ncomponents of the project such as: demographic,\ngeographical scope of the campaign, communication\ntools appropriate for each community,\ncommunication channels of the target audience, etc.\n\n\nAnother important source of information on media use\nby refugees is anecdotal evidence obtained through\nface-to-face contacts in various forms such as home\nvisits, visits to community and reception centres, and\nexchanges.\n\n\n6 [Communicating with Communities In Lebanon fact sheet, December 2018.](https://www.unhcr.org/lb/wp-content/uploads/sites/16/2019/01/Communication-with-Communities-Fact-Sheet-December-2018.pdf)\n\n\n16 **WE DIDN’T THINK IT WOULD HAPPEN TO US**\n\n\n\nAt least four operations deploy **outreach volunteers** as\npart of their CwC strategy.\n\n\n- **UNHCR Chad** uses 100 volunteers to collect and\nanalyse data on persons on the move but also to\ndisseminate information. They refer persons in need\nof protection to the relevant partners.\n\n\n- *", "output": {"entities": {"named_data": [], "descriptive_data": ["CwC survey"], "vague_data": ["data on persons on the move"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001467", "page": 15, "chunk": 0, "title": "'We didn’t think it would happen to us': Mapping of CwC Activities along the Central Mediterranean Route", "pdf_url": "https://reliefweb.int/attachments/e4848429-dddb-32d5-a9ef-099d41db0db9/CentMed_CwC_screen.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "CwC survey", "label": "DESCRIPTIVE_DATA", "score": 0.7177762985229492, "start": 360, "end": 370, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "data on persons on the move", "label": "VAGUE_DATA", "score": 0.7006366848945618, "start": 1591, "end": 1618, "probe_score": 0.0236, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "output": {"entities": {"named_data": [], "descriptive_data": ["random survey"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012940", "page": 16, "chunk": 0, "title": "Kenya - Geothermal Development and Energy Preinvestment Project", "pdf_url": "https://documents.worldbank.org/curated/en/431091468046750026/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7714613080024719, "start": 379, "end": 395, "probe_score": 0.582, "gold": "NON_MENTION", "gold_tier": "flip"}, {"text": "random survey", "label": "DESCRIPTIVE_DATA", "score": 0.7173007130622864, "start": 1487, "end": 1500, "probe_score": 0.012, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Union|Number of<br>Municipalities in<br>the union|Region|Registered<br>Lebanese<br>population|Number of Syrians<br>registered with<br>UNHCR*|\n|---|---|---|---|---|\n|Union of Al Buhaira<br>Municipalities|19|West Bekaa|99,100|15,801|\n|Union of Municipalities of Al<br>Sahel|12|West Bekaa|68,760|38,144|\n|Union of Kalaat el Estiklal|10|Rachaya|24,671|5,856|\n|Union of Jabal El Sheikh|14|Rachaya|41,460|3,917|\n|Union of Municipalities of<br>Central Bekaa|7|Central Bekaa|116,070|67,517|\n|Union of Municipalities of Zahle<br>Caza|7|Zahle|84,800|28,171|\n|Union of Municipalities of<br>Baalbeck and Surrounding<br>Communities|8|Baalbek|134,200|24, 977|\n|Union of Municipalities of Tyre|60|South Lebanon|282,768|28,062|\n|Union of Municipalities of<br>Aarqoub|7|Cheba’a area –<br>South Lebanon|70,000|3,803|\n|Union of Municipalities of<br>Central and Coastal Qayta’a|11|Bebnine/Abdeh<br>area – Akkar,<br>North Lebanon|89,100|20,315|\n|Union of Municipalities of Al<br>Shafat|11|Halba area –<br>Akkar, North", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000003", "page": 17, "chunk": 0, "title": "Lebanon - Municipal Services Emergency Project", "pdf_url": "http://documents.worldbank.org/curated/en/119441469672145615/pdf/PAD10180PAD0P14972400PUBLIC00Box391431B.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n\n\n**<u>TOP 5 REFUGEE EMPLOYMENT SECTORS SPLIT BY</u>**\n**EMPLOYEE BACKGROUND (2024)**\n\n\n\n**<u>TOP EMPLOYMENT BARRIERS FOR EMPLOYED REFUGEES</u>**\n**(2024)**\n\n\n\nEmployed in the same\nsector in Ukraine\n\n\nManufacturing\n\n\nHospitality\n\n\nConstruction\n\n\nWholesale\n\n\nIT\n\n\n\nLack of local language\n\nknowledge\n\nCannot find a job with\n\ndecent pay\n\nFew jobs for my skills or\n\nexperience\n\nLack of jobs with a suitable\n\nschedule\n\nDegree or skills recognition\n\nissues\n\n\nSource: Survey data\n\n\n\n17%\n\n\n15%\n\n\n\n35%\n\n\n\n5%\n\n\n2%\n\n\n4%\n\n\n\nEmployed in a different\nsector in Ukraine\n\n\n16%\n\n\n9%\n\n\n5%\n\n\n\n24%\n\n\n\n\n\n\n\n\n\n6%\n\n\n\n4%\n\n\n\n1%\n\n\n\nNote: Percentages are based on the distribution of relevant responses\nin the survey\n\n\nSource: Survey data\n\n\nMoreover, in the latest survey round, nearly 35% of employed refugees identified inadequate pay, a lack of\npositions that match their skill set, and challenges in having their qualifications recognized as barriers to\nemployment. All of these answers also suggest a mismatch between qualifications and job placement.\nConsistent with the findings on having to shift to jobs outside of previous employment backgrounds, working\nwomen reported the above employment barriers more frequently than men, supporting the hypothesis that\nthey may be facing underemployment more often.\n\n# **Methodology**\n\nThe approach to data collection in each of the countries included in the report differed depending on the\navailability of sampling frames and information on the distribution of the refugee population by geographic area\nand accommodation type. All interviews were conducted face to face. As a probabilistic selection of\nrespondents could not be ensured, the primary goal was to collect a diverse sample that would reflect the\npopulation’s composition as closely as possible.\n\n\nFor the regional analysis,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 13, "chunk": 0, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Survey data", "label": "VAGUE_DATA", "score": 0.5552560687065125, "start": 568, "end": 579, "probe_score": 0.9579, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "other county departments participating in the Program. Program-specific budget codes will be configured\nin IFMIS. FLLoCA will borrow from previous PforRs that have had an effective condition on the setting up\nof this system of tracking and the IFMIS codes but improve on it to ensure that subcode for various budget\nlines are added instead of one budget line that does not support financial reporting. The expenditure data\nand information will include:\n\n(a) Class of budget under development\n(b) The vote head\n(c) Administrative unit (vote head, cost center)\n(d) Source of funding (domestic or external (grants &loans), channel)\n(e) Program (sector, sub-program/project, activity)\n(f) Economic item (expense, investment on asset, liability)\n(g) Geographic location (county, sub-county, ward)\n(h) Analytical/tracking (climate change adaptation, mitigation, or cross cutting).\n\n**Funds Flow to Counties**\n\n\n**Figure 1. PforR Flow of Funds**\n\n\n\n\n\n6. **The funds to counties will flow directly from the exchequer in the TNT&P to the County Revenue**\n**Fund (CRF) and then to the Special Purpose Account (SPA)** opened by each county for these conditional\ngrants. The pre-appraisal mission discussed and endorsed the use of County Climate Change Fund (CCCF)\nso long as proper safeguards are provided. From previous experience, there is risk of delays in moving\nfunds from TNT&P to the counties; and in moving funds from the CRF to the SPA from where payments\nfor Program eligible expenditures will be paid. In order to address this, the PIU and participating counties\nwill commit to service standards, as part of the participation agreement to be signed, clearly specifying\nthe timelines within which funds have to be transferred. These standards will be measured during the\nentire", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["expenditure data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019277", "page": 2, "chunk": 0, "title": "Final Fiduciary Systems Assessment - Financing Locally-Led Climate Action Program - P173065", "pdf_url": "https://documents.worldbank.org/curated/en/862371633388886709/pdf/Final-Fiduciary-Systems-Assessment-Financing-Locally-Led-Climate-Action-Program-P173065.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "expenditure data", "label": "VAGUE_DATA", "score": 0.6093467473983765, "start": 406, "end": 422, "probe_score": 0.5942, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "10%)<br>|<br>Sector: Sub-national government administration (55%);Roads and highways (15%);Solid<br>waste management (10%);General industry and trade sector (10%);General water,<br>sanitation and flood protection sector (10%)<br>|\n|<br>Theme: Access to urban services and housing (29%);Municipal governance and<br>institution building (29%);Decentralization (28%);Municipal finance (14%)<br> <br>|<br>Theme: Access to urban services and housing (29%);Municipal governance and<br>institution building (29%);Decentralization (28%);Municipal finance (14%)<br> <br>|\n|<br>IBRD Amount (US$m.):<br>0.00<br>IDA Amount (US$m.):<br>150.00<br>GEF Amount (US$m.):<br>0.00<br>PCF Amount (US$m.):<br>0.00<br>Other financing amounts by source:<br> <br>BORROWER/RECIPIENT<br>58.00<br>58.00<br>|<br>IBRD Amount (US$m.):<br>0.00<br>IDA Amount (US$m.):<br>150.00<br>GEF Amount (US$m.):<br>0.00<br>PCF Amount (US$m.):<br>0.00<br>Other financing amounts by source:<br> <", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016462", "page": 0, "chunk": 1, "title": "Ethiopia-Irrigation and Drainage : Ethiopia - Irrigation and Drainage Project", "pdf_url": "https://documents.worldbank.org/curated/en/671811468038031627/pdf/AF0Integrated01et010Appraisal0Stage.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\n- The unit costs of centrally managed contracts under UTSEP are slightly higher in comparison to LG managed\ncontracts, and the price difference is due to the challenging locations of the centrally managed construction\nsites which are often located in hard to reach / northern territories (with expected higher cost of construction)\nand low LG capacity. Local communities and most of the LGs have limited capacity in procuring, managing and\nsupervising large construction contracts, thus the transaction costs to support contracts supervision are high.\nProcurement trough International Competitive Bidding (ICB) ends up with much higher costs than with\nNational Competitive Bidding (NCB) (AfDB-IV). The civil works will be managed centrally under the Project\nwith support from the LGs in supervising the contracts implementation.\n\n- Community-based procurement and contract management of school construction is highly cost-effective to\nbuild primary schools (2000-2004 SFG program; 2013-2014 Emergency program for primary schools) as well\nas secondary schools (2009-2014 UPPET). However, the quality of the supervision is challenging in these cases\nand could be associated with high centrally enforced supervision costs. Evidence from UPPET-APL1 shows that\nlarge contracts that exceed the school-communities’ management capacity lead to serious implementation\ndifficulties and delays.\n\n\n70. **Lessons related to promoting girls’ education incorporated into the Project design:**\n\n- Distance to lower secondary schools for young adolescents, especially girls from poor families, tends to raise\nopportunity costs and physical risks. Recent studies on child marriage and early pregnancy have shown that\nincreasing access to lower secondary schools, reducing costs of education for poor households, and providing\nincentives for girls to stay in school, are likely to have a positive effect on education access and attainment.\nThe project is addressing all three.\n\n- Current successful programs in Uganda show that it is critical to engage parents and communities in\nsupporting girls’ education. The Project will support such an approach under the Child Friendly School\nProgram", "output": {"entities": {"named_data": ["UPPET-APL1"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 32, "chunk": 1, "title": "Uganda - Secondary Education Expansion Project", "pdf_url": "http://documents.worldbank.org/curated/en/406361595815248191/pdf/Uganda-Secondary-Education-Expansion-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UPPET-APL1", "label": "NAMED_DATA", "score": 0.7730720043182373, "start": 1235, "end": 1245, "probe_score": 0.5887, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "53. Under the Uganda rainfall condition, the frequency of flooding in most municipalities is between\n10 to 15 times in a year lasting 3 to 4 hours per flooding. Private and commercial vehicles are disrupted\nleading to loss of time and income. Improved drainage also leads to improvements to the environment and\nhealth benefits from reduced incidence of water borne disease. The internal rate of return obtained in\nprevious studies in similar environments was used to estimate the stream of benefits generated by improved\ndrainage. The EIRR of drainage under USMID was calculated at 6%.\n\n**Increase in Property Values**\n\n54. Improvements in urban roads in all the municipalities sampled has led to increases in value of\nproperties (land, buildings) and rental prices of properties in the adjacent areas of the constructed roads\nranging from 20% to 100% as per the table below. In Hoima municipality, the sharp increase in both rent\nand land values can also be attributed to speculations about oil extraction impact on the local economy.\n\n**Table 9: Changes in Rent and Land values**\n\n\n**Employment Creation**\n\n55. Construction of urban roads created direct and indirect jobs during construction. However, most of\nthe urban road infrastructure projects visited had been completed or partially completed. It was only\nNyakana road in Fort Portal where construction was still ongoing and therefore data on employment was\nobtained. The construction of Nyakana road in Fort Portal with a length of 0.94km, was directly employing\n56 workers out of which, 10% were highly skilled, 10% were skilled and 80 % unskilled. The highly skilled\nworkers, skilled workers and unskilled workers were earning UGX35,000, UGX25,000 and UGX12,000\nper day respectively. The construction of the road was also indirectly employing approximately 70 workers.\nThe construction of the road was expected to last for one year and three months.\n\n56. It can therefore be estimated from this data that construction of one kilometer creates", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on employment"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000014", "page": 69, "chunk": 0, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents1.worldbank.org/curated/en/143681526614252328/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on employment", "label": "VAGUE_DATA", "score": 0.6891720294952393, "start": 1393, "end": 1411, "probe_score": 0.4287, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Adlung and Roy (2005) have assessed both the current coverage of specific\n\n\ncommitments of WTO members in the GATS and the offers that were on the table as of\n\n\n2006, when negotiations were suspended. For many countries the coverage of specific\n\n\ncommitments is well below 50 percent of all services and modes of supply. Adlung and\n\n\nRoy conclude that not only do the requests and offers made in the 6 years following the\n\n\nlaunch of negotiations on services in 2000 imply little if any liberalization of policies;\n\n\nmost countries were not even willing to use the GATS as a vehicle to “lock in” existing\n\nlevels of openness. <sup>5</sup> [^5: A number of studies have shown that there is often a major gap between the actual level of openness of\nsectors and the level of commitments in the GATS. For example, Barth et al. (2006) compare data on\nspecific GATS commitments for financial services with measures of actual policy in this sector for 123\ncountries. They conclude that in practice applied policy is much more liberal than what was committed to\nin the GATS.]\n\n\nThe lack of progress on services matters for several reasons. First, as mentioned\n\n\nin the Introduction, the extant research concludes that the potential direct gains from\n\n\nreform of services trade for most WTO members are likely to be large. Second, services\n\n\nreform is needed to enable developing countries to take advantage of the new\n\n\nopportunities that arise from goods trade liberalization. For example, Sub-Saharan\n\n\nAfrican exporters today pay transport costs that are at least five times greater than the\n\n\ntariffs they face in industrial country markets, but neither international maritime nor air\n\n\ntransport services figure seriously on the WTO agenda. Third, the WTO negotiating\n\n\nprocess requires countries that seek better market access to offer improved access to their\n\n\nown markets. In particular, attaining global liberalization of agriculture – a key objective\n\n\nof many developing countries – will require them to offer a quid pro quo. Greater\n\n\nopening in services, an area of export interest to many of the countries that", "output": {"entities": {"named_data": [], "descriptive_data": ["data on\nspecific GATS commitments"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003658", "page": 9, "chunk": 0, "title": "wps4451", "pdf_url": "https://local/prwp/wps4451.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on\nspecific GATS commitments", "label": "DESCRIPTIVE_DATA", "score": 0.759189248085022, "start": 838, "end": 871, "probe_score": 0.7061, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\n\n\nGreater Kampala Metropolitan Area Urban Development Program (P175660)\n\n\n\n\n\n\n\n\n|Revise Value for Money (VfM) audits in<br>the infrastructure investments<br>delivered (Percentage) DLI|Comments on achieving targets|Col3|Interim data as of March 31, 2026. The indicator is on track, projected to surpass the year-end June 30, 2026<br>target of 80% and will be verified under APA4 by IVA.|Col5|Col6|Col7|Col8|Col9|\n|---|---|---|---|---|---|---|---|---|\n|Revise Operation and Maintenance<br>(O&M) of Infrastructure Projects<br>(Percentage)   DLI|0|Jan/2022|80|31-Mar-2026|80|31-Mar-2026|90|Jun/2029|\n|Revise Operation and Maintenance<br>(O&M) of Infrastructure Projects<br>(Percentage)   DLI|Comments on achieving  targets|Comments on achieving  targets|Interim data as of March 31, 2026. The indicator has already met the year-end target of 80% and will be verified<br>under APA4 by IVA.|Interim data as of March 31, 2026. The indicator has already met the year-end target of 80% and will be verified<br>under APA4 by IVA.|Interim data as of March 31, 2026. The indicator has already met the year-end target of 80% and will be verified<br>under APA4 by IVA.|Interim data as of March 31, 2026. The indicator has already met the year-end target", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Interim data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003604", "page": 25, "chunk": 0, "title": "Disclosable Restructuring Paper - Greater Kampala Metropolitan Area Urban Development Program - P175660", "pdf_url": "https://documents.worldbank.org/curated/en/099071526102028268/pdf/P175660-6a3fbf62-9155-47c3-ad63-0584f88ac5c1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Interim data", "label": "VAGUE_DATA", "score": 0.5645259022712708, "start": 238, "end": 250, "probe_score": 0.5707, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\n2018.\n\n\n194. \u0007Tofail, F.B., C.; Corna, F., _Final Research Report:_\n_Evaluation of ACF’s Mental Health & Care_\n_Practices Community-based Prevention Program_\n_in Kutupalong and Nayapara Refugee Camps of_\n_Cox’s Bazar, Bangladesh_ 2013, ACF International;\nInternational Centre for Diarrhoeal Disease\nResearch, Bangladesh (icddr,b).\n\n\n\nReview 69", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001165", "page": 68, "chunk": 3, "title": "Culture, Context and Mental Health of Rohingya Refugees: A review for staff in mental health and psychosocial support programmes for Rohingya refugees", "pdf_url": "https://reliefweb.int/attachments/b0776d37-e679-3c93-a283-e62e622e2df8/5bbca9377.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nBalochistan Human Capital Investment Project (P166308)\n\n\nmeasles vaccination in Balochistan who are fully vaccinated. <sup>74</sup> [^74: Data on the relationship of measles and full vaccination come from PDHS 2017–18] Data on under‐five mortality comes from\nPDHS 2017–18. The impact of additional family planning visits on maternal mortality is based on the\nmaternal mortality effect of modern contraceptive use estimated by Ahmed et al. (2012). <sup>75</sup> [^75: <mark>Ahmed, S., Q. Li, L. Liu, and A. O. Tsui. 2012. “:Maternal Deaths Averted by Contraceptive Use: An Analysis of 172 Countries.”</mark> _<mark>The</mark>_\n_<mark>Lancet</mark>_ <mark>380 (9837): 111–125.</mark>] It is assumed\nthat 50 percent of family planning visits to the project facilities result in modern contraceptive use. An\nadjustment factor is applied throughout to account for crowding out of formal private health care services,\nassuming that 95 percent of the additional benefits in project facilities would have occurred in the absence\nof the project.\n\n\n**Table 1.3. Estimated Lives Saved over the Project Cycle**\n\n|Years|Neonatal|Under‐5|Maternal|Total|\n|---|---|---|---|---|\n|2020|0|0|0|0|\n|2021|7|17|5|29|\n|2022|8|22|7|36|\n|2023|9|28|9|45|\n|2024|10|37|11|58|\n|Total|33|103|32|168|\n\n\n\n11. **Lives saved by the project are converted into monetary terms using the concept of VSL", "output": {"entities": {"named_data": ["PDHS 2017–18", "PDHS 2017–18"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000085", "page": 44, "chunk": 0, "title": "Pakistan - Balochistan Human Capital Investment Project", "pdf_url": "http://documents1.worldbank.org/curated/en/519111593223468766/pdf/Pakistan-Balochistan-Human-Capital-Investment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PDHS 2017–18", "label": "NAMED_DATA", "score": 0.6523442268371582, "start": 224, "end": 236, "probe_score": 0.9853, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PDHS 2017–18", "label": "NAMED_DATA", "score": 0.5405505299568176, "start": 278, "end": 290, "probe_score": 0.9954, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", share of _vulnerable employment_, and the share of female workers in the total\nworkforce, _female intensity_ . In addition, we cover the number of ILO’s _basic_ _conventions_ (that is,\nfundamental and governance conventions) signed, complemented with different measures of wage\ninequality. We use the ILO’s _wage dispersion_ between the 9th and 5th wage decile, and the OECD’s\n_minimum wage_ relative to the median wage.\n\n\n_Social standards_ deal with a country’s basic welfare system. We use ILO data on the share of _health_\nexpenditure in total government spending, the share of workers contributing to a _pension_ scheme, and\nthe share of unemployed receiving regular _unemployment_ benefits. Additionally, we assess the role of\n_total conventions_ of the ILO signed.\n\n\n7 WEF’s foreign competition measure could equally be grouped under trade and investment policy.\n\n\n17", "output": {"entities": {"named_data": ["ILO data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007000", "page": 18, "chunk": 2, "title": "wps8007", "pdf_url": "https://local/prwp/wps8007.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "ILO data", "label": "NAMED_DATA", "score": 0.6455967426300049, "start": 495, "end": 503, "probe_score": 0.9762, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad Rural Mobility and Connectivity Project (P164747)\n\n\n**Table 3.2. Predicted Maintenance Cost Breakdown**\n\n\n9. Table 3.2 shows the estimated costs of maintenance based on historic data, additional required\nmaintenance based on the median predicted impacts of climate change, the total costs required to\nmaintain the roads in the face of climate change, and the percentage of each total comprised by regular\nmaintenance and by costs required to address climate change. These costs are all given in both current\nand future values, based on the number of years in the scope of the project, detailed in table 3.1. The\nanalysis suggests that the cost of additional maintenance incurred by the impacts of climate change is\nequal to 43 percent of the total required maintenance cost over the project time frame to ensure the road\nremains seasonally functional. Thus, planning for and securing these additional costs incurred due to\nclimate change will be crucial in ensuring the success of the project in the long term and for ensuring the\nimpacts of climate change are adequately addressed and considered. Sustainable mechanisms currently\nin place within the structure of the project include community maintenance plans and adequate\ninvestment in maintenance funding.\n\n\n10. Figure 3.2 shows the estimated difference in repair costs between the historically required\nmaintenance costs and the maintenance costs predicted to be needed as a result of climate change.\n\n\nPage 58 of 76", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["historic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000048", "page": 61, "chunk": 0, "title": "Chad - Rural Mobility and Connectivity Project", "pdf_url": "http://documents.worldbank.org/curated/en/815491545534039786/pdf/Chad-PAD-11302018-636811128215032206.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "historic data", "label": "VAGUE_DATA", "score": 0.7677522301673889, "start": 193, "end": 206, "probe_score": 0.9775, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "000 non-Arabs in Jordan. It is not clear how many of these are working informally.\n31 Economic migrants are subject to a minimum wage, which is lower than the minimum wage for Jordanian\nworkers. The separate minimum wage makes non-Jordanian workers more attractive to employers and therefore\nruns counter to the overall Government policy of promoting Jordanians workers over others.\n32 The remaining 26 percent are in trade (7 percent), construction (6 percent), and hotels (5 percent). See The\nNational Employment Strategy 2011-2020: An Update and Future Directions (ILO, 2015) based on data for\n2009-2014.\n33 See Tamkeen (undated) Breaking the Silence!! Irregular migrant workers in Jordan: between marginalization\nand integration. And Tamkeen (2014) Forgotten Rights: The Working and Living Conditions of Migrant\nWorkers in the Agricultural Sector in Jordan. Both available at www.tamkeen-jo.org.\n34 Better Work Jordan is part of the global Better Work partnership between ILO and the IFC in collaboration\nwith local and international stakeholders. See more at:\nhttp://betterwork.org/jordan/?page_id=7#sthash.Y2cqymct.dpuf\n35 The _kafala_ <mark>system requires all unskilled laborers to have an in-country sponsor, usually their employer, who</mark>\n<mark>is responsible for their visa and legal status. This practice has been criticized by human rights organizations for</mark>\n<mark>creating easy opportunities for the exploitation of workers, as many employers take away passports and abuse</mark>\n<mark>their workers with little chance of legal repercussions. Unlike in the Gulf countries, the</mark> _<mark>kafala</mark>_ <mark>system is not</mark>\n<mark>specified by Jordanian law (as it is in", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data for\n2009-2014"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 68, "chunk": 2, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data for\n2009-2014", "label": "VAGUE_DATA", "score": 0.8153204321861267, "start": 588, "end": 606, "probe_score": 0.9573, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Annex 6:** **Implementation Arrangements**\n\n\n**Annex 7:** **Financial Management Assessment Report**\n\n\n**Annex 8:** **Procurement Arrangements**\n\n\n**Annex** **_9:_** **Economic and Financial Analysis**\n\n\n**Annex** **10:** **Safeguard Policy Issues**\n\n\n**Annex** **11:** **Project Preparation and Supervision**\n\n\n**Annex 12:** **Documents in the Project File**\n\n\n**Annex 13:** **Statement of Loans and Credits**\n\n\n**Annex 14: Country at a Glance**\n\n\nMAW)\n**Country Map** - **IBRD 33485**\n**UNHCR Maps**\n\n\n\n40\n\n\n44\n\n\n50\n\n\n55\n\n\n61\n\n\n68\n\n\n_69_\n\n\n70\n\n\n72\n\n\n74\n75", "output": {"entities": {"named_data": ["UNHCR Maps"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000023", "page": 3, "chunk": 0, "title": "Sri Lanka - Puttalam Housing Project", "pdf_url": "http://documents1.worldbank.org/curated/en/194731468104646411/pdf/38147core.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR Maps", "label": "NAMED_DATA", "score": 0.8525792360305786, "start": 491, "end": 501, "probe_score": 0.1789, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Chapter 4 Chapter 4\n\n\n\nHonduras, Guatemala, Mexico, and Panama) have\nengaged in quantifying the resources required\nto implement comprehensive refugee responses\nat the national level. <sup>**47**</sup> Drawing on the process\non measuring the impact arising from hosting,\nprotecting, and assisting refugees, and with the\ntechnical assistance of UNHCR, a funding gap of\n63 per cent (USD 141 millions) was identified across\nall countries that are part of the Comprehensive\nRegional Protection and Solutions Framework for\nCentral America and Mexico (“MIRPS”). Within this\naverage, funding gaps varied considerably from\ncountry to country, ranging from 30 to 91 per cent\n(Belize 69%, Costa Rica 76%, El Salvador 65%,\nGuatemala 91%, Honduras 46%, Mexico 37%, and\nPanama 30%), depending upon the size of the\nconcerned population, local costs, the scope of\nsupport, and other context-specific parameters. <sup>**48**</sup>\n\n\nUNHCR’s budgetary situation also illustrates the\npersistence and evolution of funding gaps at global\nlevel. Between 2016 and 2020, the gap between\nbudgetary needs and available funds hovered around\n42 per cent, ranging from USD 3.1 to 3.8 billion.\nDespite a significant 22 per cent increase in funding\nreceived in the period following the adoption of the\nNew York Declaration and the GCR, the financial\nshortfall in meeting protection and livelihood needs\nin 2020 (USD 3.7 billion) was more than half a billion\nhigher than in 2016 (USD 3.1 billion). <sup>**49**</sup>\n\n\n**Preliminary data indicate that donors**\n**either maintained or increased ODA**\n**contributions to help countries with**\n**lower incomes respond to COVID-19 and**\n**refugee situations**\n\n\nDue to a lack of data for 2020", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Preliminary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000803", "page": 15, "chunk": 0, "title": "2021 Global Compact on Refugees Indicator Report", "pdf_url": "https://reliefweb.int/attachments/75fd0942-6cc3-3825-a32b-0013afceb78e/2021_GCR-Indicator-Report_spread_web.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Preliminary data", "label": "VAGUE_DATA", "score": 0.743516206741333, "start": 1488, "end": 1504, "probe_score": 0.9265, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 2\nPage 4 of 4\n\n**Project Component 3 -** US$ **4.10 million**\n\n**Improve the Government's Capacity to Manage Sector Reforms** will be addressed through:\n(i) supporting the activities of the CNOSEGE in its effort to coordinate the reforms and raise\nresources to support the reform; (ii) capacity building support to the Ministry of Education key\nunits such as the Planning Unit _(Service de la Planification),_ and the Education Projects Bureau\n(BEPE); and (iii) other technical assistance necessary to improve private public partnership in\neducation, development of an effective gender strategy, and possible reforms in textbook policy.\n\n\n_Detailed Description of Sub-components:_\n\n\n_(i) CNOSEGE:_ The Executive Secretariat of CNOSEGE is responsible for implementing the\nreform program. The project will finance the secretariat including its fund-raising activities.\n\n\n_(ii) Support to MOE Planning Unit:_ The project will finance capacity building of the Ministry of\nEducation's Planning Unit, through expert assistance in dealing with the collection of educational\nstatistics, the production of a _carte scolaire_ and analysis of census or household survey data, and\nkey staff in the BEPE including the purchase of project management tools (finance and\nprocurement). The planning unit will also carry out the monitoring and evaluation studies\nrequired under the project. In addition, the unit will implement and monitor the Environmental\nManagement Plan (EMP).\n\n\n_(iii) Additional Technical Assistance_ will also be provided to enable the ministry to develop more\ncost effective strategies including exploring the possibility of cost effective public/private\npartnerships. Technical Assistance will also be provided to develop strategies to reduce the\ngender gap in enrollments as well as the gap by income group. Pilot studies will also be financed\nunder the credit for optimal designs in school construction, demand financing, sanitation upkeep\nand maintenance, and", "output": {"entities": {"named_data": [], "descriptive_data": ["census or household survey data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000072", "page": 35, "chunk": 0, "title": "Jordan - Health Sector Reform Project", "pdf_url": "http://documents1.worldbank.org/curated/en/466121468773744158/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "census or household survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8749487400054932, "start": 1138, "end": 1169, "probe_score": 0.5876, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Syrian refugees living outside camps in Jordan - Home visit data findings - 2013**\n\n\n\n**1.4**\n\n\n\n**Expenditure on utilities**\n\n\n7.2% of household expenditure is on utilities\n(Figure 36). Figure 43 indicates that 30% of the\nhouseholds that report expenditures on utilities,\npay less than 10 JD a month, 52% pay between\n11 and 20 JD, and 17% pay between 21 and 40 JD.\nThe average is 17.6 JD with some variations between the governorates (Figure 44).\n\n\nAs shown in Figure 45, a higher proportion of\nexpenditures was consumed by utilities in 2013\nthan in the previous year. The proportion of expenditures consumed by utilities increased in\nmost governorate, with the notable exceptions of\nIrbid, Madaba and Tafilah.\n\n\n\nThis country-wide trend is not surprising in light\nof the fact that the Government of Jordan eliminated the fuel subsidy in November 2012 and replaced it with targeted cash transfers in some cases. Additionally, in mid-August 2013, the National\nElectric Power Company (NEPCO) raised electricity tariffs by 15%. The decrease in expenditures on\nutilities in three governorates, particularly Irbid,\nwarrants further study.\n\n\n\n\n\n\n\n\n\n_Source: UNHCR /IRD Home Visits 2013_\n\n\n\n66", "output": {"entities": {"named_data": [], "descriptive_data": ["Home visit data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000763", "page": 60, "chunk": 0, "title": "Syrian Refugees Living Outside Camps in Jordan", "pdf_url": "https://reliefweb.int/attachments/6fd6d58d-9706-32b7-8e61-3a834effba00/HVreport_09MarCS6_smallsize.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Home visit data", "label": "DESCRIPTIVE_DATA", "score": 0.7413307428359985, "start": 51, "end": 66, "probe_score": 0.9748, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " in selected countries neighbouring Europe, based on annual data. \n \nThe group of countries analysed in this report is collectively referred to as “the 44 industrialized \ncountries” and has been defined as such for the purpose of this report only. The 44 countries are: 27 \nMember States of the European Union3, Albania, Bosnia and Herzegovina, Croatia, Iceland, \nLiechtenstein, Montenegro, Norway, Serbia4, Switzerland, The former Yugoslav Republic of \nMacedonia, and Turkey, as well as Australia, Canada, Japan, New Zealand, the Republic of Korea and \nthe United States of America. The group of 44 countries received an estimated 377,200 asylum \napplications in 2009. \n \nAn asylum-seeker is an individual who has sought \ninternational protection and whose claim for \nrefugee status has not yet been determined. It is \nimportant to note, however, that a person is a \nrefugee if he/she fulfils the criteria set out in the \n1951 Convention Relating to the Status of \nRefugees. The formal recognition of someone \nthrough individual refugee status determination \ndoes not establish refugee status, but rather \nconfirms it. \n \nAs part of its obligation to protect refugees on its \nterritory, the country of asylum is normally \nresponsible for determining whether an asylum-\nseeker is a refugee or not. This responsibility is \noften incorporated in national legislation of the \ncountry and, for State Parties, is derived from the \n1951 Convention. \n \nThe numbers in this report reflect asylum claims \nmade at the first instance of asylum procedures; \napplications on appeal or review are not included. \nAlso, this report does not include information on \nthe outcome of asylum procedures or on the admission of refugees through resettlement programmes, as \nthis information is available in other UNHCR reports.5 \n                                                 \n1 This report has been prepared by the Field Information and Coordination Support Section (FICSS) at UNHCR Headquarters in Geneva. \nAny questions concerning this document should be addressed to FICSS at stats@unhcr.org. For other UNHCR statistics, visit UNHCR’s \nStatistical Online Population Database at http", "output": {"entities": {"named_data": ["Statistical Online Population Database"], "descriptive_data": [], "vague_data": ["annual data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000810", "page": 1, "chunk": 1, "title": "Asylum Levels and Trends in Industrialized Countries 2009 - Statistical Overview of Asylum Applications Lodged in Europe and selected Non-European Countries", "pdf_url": "https://reliefweb.int/attachments/771525db-5c40-325c-8321-aedadd127619/1EAB689A39141C4EC12576EF004A52BC-UNHCR_Mar2010.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "annual data", "label": "VAGUE_DATA", "score": 0.8411155939102173, "start": 53, "end": 64, "probe_score": 0.3425, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Statistical Online Population Database", "label": "NAMED_DATA", "score": 0.8467205762863159, "start": 2120, "end": 2158, "probe_score": 0.714, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "to more stable host countries with higher HIV prevalence. <sup>8</sup>\nMyths about overall high HIV prevalence levels among refugees compound the stigma that refugees already face, further\nconstraining their access to health services and highlighting\nthe need to address HIV- related stigma\nand discrimination as an integral part\nof eff ective responses.\n\n\n\nFactors that can limit the transmission of HIV among refugees\nare less well-studied, but may include: reduced mobility to\nhigh prevalence urban areas in search of work; the isolation\nand inaccessibility of some refugee populations; and in some\n\n\n\n_The many factors that contribute to_\n\n_the increased HIV risks to refugees_\n\n_in emergency and post-emergency_\n\n_phases are well-understood._ _They_\n\n_include loss of livelihoods and lack_\n\n_of access to basic services, often_\n\n_increasing the vulnerability of women_\n\n_and girls to sexual exploitation._\n\n\n\ncircumstances, especially in the postemergency phase, the availability of\nbetter protection and other HIV-related\nservices than in countries of origin or\namong surrounding populations. <sup>11</sup>\n\n\n\nThe many factors that contribute to\nthe increased HIV risks to refugees _phases are well-understood._\nin emergency and post-emergency\nphases are well-understood. <sup>9</sup> They\ninclude loss of livelihoods and lack\nof access to basic services, often increasing the vulnerability of women\nand girls to sexual exploitation. <sup>10</sup> Also, _and girls to sexual exploitation._\nconfl ict increases sexual violence\nagainst women and girls, including rape as a weapon of war,\nand breaks down social networks and institutions that usually\nprovide support and regulate behaviour. Exposure to mass\ntrauma such as confl ict can increase alcohol and other drug\nuse and, in general, infl uence people’s attitudes towards risk.\nThe additional disruption to health and education services\n\n\n\nThe", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000192", "page": 8, "chunk": 0, "title": "Educational Responses to HIV and AIDS for Refugees and Internally Displaced Persons: Discussion Paper for Decision-Makers", "pdf_url": "https://reliefweb.int/attachments/13ad659a-8126-35aa-8015-a366a96e2d1c/FF50D2DE5DD57DC7C1257282004A5BF6-unhcr-refugees-jan2007.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "UNHCR MID-YEAR POST DISTRIBUTION MONITORING REPORT - 2024\n\n\n**Figure 21: Channels actually used and channels preferred to receive information about cash**\n**assistance**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nWhen respondents were asked whether they felt they received adequate information about the cash assistance,\n**78 per cent reported feeling well-informed** while 22 per cent did not feel so as shown in figure (22). For those\nwho did not feel well-informed, they suggested that UNHCR could better inform them through sending clearer\nSMSs (14 per cent of all respondents) and providing more information on the documents required (4 per cent of\nall respondents) and increasing communication channels with refugees (3 per cent of all respondents). Other\nsuggestions mentioned by 1 per cent of all respondents respectively include; more information about the timing\nof distribution, clearer instructions on how to collect the assistance and more information on where to go or what\nto do in cases faced by a problem related to cash assistance.\n\n\n**Figure 22: Respondents feeling of having received adequate information about the assistance**\n\n\n\n\n\n\n\n\n\n24", "output": {"entities": {"named_data": ["UNHCR MID-YEAR POST DISTRIBUTION MONITORING REPORT"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000992", "page": 23, "chunk": 0, "title": "Mid-Year Post-Distribution Monitoring Report of UNHCR’s Multi-Purpose Cash Assistance to Refugees in Egypt, September 2024", "pdf_url": "https://reliefweb.int/attachments/9543af9b-5171-46cd-a644-232432ee2f4b/MPCA%20PDM-Mid%20Year%202024-Final%20Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR MID-YEAR POST DISTRIBUTION MONITORING REPORT", "label": "NAMED_DATA", "score": 0.727776825428009, "start": 0, "end": 50, "probe_score": 0.9956, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda Digital Acceleration Project – GovNet (P171305)\n\n\n**92.** Uganda has national laws and institutions for E&S risks management. There are, however, weaknesses in the\nnational environmental system performance related to institutional linkages, staffing level, and budget allocation,\nas well as human resource skills. The capacity of NITA-U to supervise, implement, monitor, and report on E&S risks\nwas assessed during project preparation and it was established that NITA-U does not have the required in-house\nE&S safeguards capacity. To strengthen the capacity for safeguards compliance, NITA-U will recruit one\nEnvironmental Specialist and one Social Specialist no later than 30 days after project effectiveness date, and\ncapacity building activities on applicable ESSs will be supported by the WB. The two specialists will work closely to\ndevelop specific plans based on the framework documents prepared. NITA-U will track and report on the\nperformance of E&S risks management as per the terms of the ESCP and financing agreement.\n\n\n**93.** Despite the main project implementation agencies’ experience in delivering similar operations, the E&S risk\nrating is Substantial due to the potentially complex implementation arrangement for the various sub-components\nand the wide geographical scope of the project that spreads across the country. Given the nature of the\nanticipated civil works, land acquisition, and involuntary displacement, the risks are expected to be minimal and\naddressed through the ESMF and RPF. Risks associated with influx of labor, particularly in RHDs and those that\nmight affect members of Vulnerable and Marginalized Groups will be addressed through the elaboration of an\nESMF and VMGF. Stakeholder engagement and effective grievance redress mechanisms will be crucial to ensure\nsmooth project implementation.\n\n\n**94.** **Citizen Engagement.** In addition to establishing a Grievance Redress Service (GRS), as discussed in Section V,\nthe", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000023", "page": 46, "chunk": 0, "title": "Uganda - Digital Acceleration Project", "pdf_url": "http://documents.worldbank.org/curated/en/473041622944887337/pdf/Uganda-Digital-Acceleration-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "relocation of landless and others i s alienated by the Government. This i s not planned in the initial period\n\n- f two to three years.\n\n\nThe term \"involuntary resettlement\" relates to the involuntary taking o f land resulting in: (i) relocation or\nloss o f shelter; (ii) loss o f assets or access to assets; (iii) loss of income sources or means of livelihood,\nwhether or not the affected persons must move to another location; or (iv) the involuntary restriction o f\naccess to legally designated parks and protected areas resulting in adverse impacts on the livelihoods of\nthe displaced persons.\n\n\nInvoluntary resettlement may cause severe long-term hardship, impoverishment, and environmental\ndamage unless appropriate measures are carefully planned and carried out. When a village social\nassessment determines that resettlement i s unavoidable, the NEHRP will provide a resettlement plan\nconsistent with these principles to the Bank for approval. _N E H R p ' s_ operations will follow the following\nprinciples:\n##### . Involuntary resettlement will be avoided where feasible, or minimized, exploring all viable\n\nalternative program designs.\nWhere it i s not feasible to avoid resettlement, resettlement activities will be conceived and\nexecuted as sustainable development programs, providing sufficient investment resources to\nenable the persons displaced by the program to share in _NEHRP_ benefits. Displaced persons will\nbe meaningfully consulted and will have opportunities to participate in planning and\nimplementing resettlement programs.\nDisplaced persons will be assisted in their efforts to improve their livelihood and standards of\nliving or at least to restore them, in real terms, to pre-displacement levels or to levels prevailing\nprior to the beginning o f program implementation, whichever i s higher.\n\n\nGuidelines based on OP 4.12 will be laid down to ensure that the different communities and caste groups\nrelocated within new housing schemes will have equal access to the community infrastructure and public\nutilities.\n\n\n_Concerns on Social Impacts and Mitigation Measures and Mitigation Measures_\nIn addition to", "output": {"entities": {"named_data": [], "descriptive_data": ["village social\nassessment"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000115", "page": 76, "chunk": 0, "title": "Sri Lanka - North East Housing Reconstruction Program", "pdf_url": "http://documents1.worldbank.org/curated/en/672131468763807868/pdf/304360LK.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "village social\nassessment", "label": "DESCRIPTIVE_DATA", "score": 0.5386075973510742, "start": 776, "end": 801, "probe_score": 0.0708, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". On the other hand, the most attractive\ncenters in terms of reception are those with greater economic development and available public\nservices. However, the arrival of IDPs increases the demand for services and the situation of the\nhistorically vulnerable population worsens (PIU of Antioquia, 2006). Despite being the Department\nwith the highest indices of forced displacement, the tendency seems to have changed in recent years\nas the number of people arriving in Medellín and in other municipalities of the department (Graph\n5) has decreased over the last two years.\n\n\nThe case of Santa Marta deserves similar attention. Santa Marta is one of the main IDP receiving\ncities in the country, with 70,000 displaced families registered in the RUPD through February 2007,\nequal to 19 percent of the total native population in Santa Marta (the pressure index, according to\nUNHCR figures for 2005 is around 15.5%). In addition, 74 percent of IDP households are below\nthe minimum living conditions and 65 percent of them live under the poverty line (ICRC and WFP,\n2007). The highest peak of IDP reception in Santa Marta was observed in 2002; since then, the\narrival of IDPs has generally declined although there was an increase in 2005 (Graph 6).\n\n\nAntioquia and Santa Marta are substantially affected by the fact that they are both regions which\nreceive IDPs and from which IDPs originate. In Antioquia every municipality has been affected by\nthis phenomenon. Displacement seems to be concentrated within the department (85% of the cases\nare intradepartmental displacements). Map 1 shows that, although Medellín receives the most IDPS\n\n\n18 Acción Social: January 31, 2008.", "output": {"entities": {"named_data": ["RUPD", "UNHCR figures for 2005"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000239", "page": 46, "chunk": 1, "title": "Protecting the displaced in Colombia: The role of municipal authorities", "pdf_url": "https://reliefweb.int/attachments/19bae1cd-32c9-3f6f-a0d1-1b5389b566ce/106B60B46FBB9662492575FB000FD01A-Full_Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "RUPD", "label": "NAMED_DATA", "score": 0.753337025642395, "start": 743, "end": 747, "probe_score": 0.9424, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHCR figures for 2005", "label": "NAMED_DATA", "score": 0.541107177734375, "start": 871, "end": 893, "probe_score": 0.0089, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on social development issues"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008801", "page": 24, "chunk": 0, "title": "Kenya - Education Project", "pdf_url": "https://documents.worldbank.org/curated/en/157361468047348649/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on social development issues", "label": "VAGUE_DATA", "score": 0.581004798412323, "start": 1670, "end": 1703, "probe_score": 0.333, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " process adopted under DLR 3.1.<br> <br>DLR 3.5. Regulatory burden on businesses has decreased by 30% following implementation of<br>business regulatory reform adopted under DLR 3.2.|2020|\n\n\n_Notes_ : The target dates are indicative.\n\n\n\n\n\n_Note_ : The baseline is 50 household enterprises in 2016. Syrian businesses will be allowed to operate only in sectors\nopen to foreigners.\n\n\nRegulations’ can include laws, bylaws, instructions, decrees, decisions, and so on, as will be defined by the proposed\npredictability framework.\n\n\n**3.1** **Predictability** :\n\n\n26. Identify and implement measures that will improve the predictability and transparency of\nregulatory changes that impose mandatory compliance on businesses through new or amended regulations,\nsuch as laws, bylaws, instructions, decrees, and so on. This would entail the following:\n\n\n    - Improved consultation with the private sector through a systemic and structured consultation\nprocess\n\n\n    - Adopting notice and comment mechanisms to allow for public comments on new/amended\nregulations\n\n\n    - Delayed entry into force to allow sufficient time for businesses to adjust to new compliance\nrequirements\n\n\n    - Requirement to publish all such regulations in the official gazette to be effective and binding\nfor the private sector\n\n\n30", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 38, "chunk": 1, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "-y(j,t-1) on y(j,t-1), which is of course mathematically identical to\n\n\nregressing y(j,t) on y(j,t-1): the coefficient on the initial value in the first regression will\n\n\njust be the coefficient in the second regression, minus one. But the coefficient in the\n\n\nsecond regression, which is just the autocorrelation coefficient of the governance rating,\n\n\nis for most of these data sources a positive number between 0 and 1. Suppose next that\n\n\nthe governance rating is a noisy proxy for true governance, i.e. that y(j,t) = g(j,t) + e(j,t)\n\n\nwhere g(j,t) is true governance and e(j,t) is the error made by a particular source. It\n\n\nseems quite plausible to us that governance on average changes rather slowly over\n\n\n8 These three sources are the Country Policy and Institutional Assessments produced by the\nWorld Bank, the African Development Bank, and the Asian Development Bank, which for the\nmost part are treated as confidential by these organizations. Only in the past few years has\nlimited, but growing disclosure of this data been made by these organizations, and full public\naccess to the detailed disaggregated and historical data on which we rely is still not permitted..\n\n\n9", "output": {"entities": {"named_data": [], "descriptive_data": ["Country Policy and Institutional Assessments", "disaggregated and historical data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003360", "page": 9, "chunk": 1, "title": "wps4149", "pdf_url": "https://local/prwp/wps4149.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Country Policy and Institutional Assessments", "label": "DESCRIPTIVE_DATA", "score": 0.6059528589248657, "start": 744, "end": 788, "probe_score": 0.9344, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "disaggregated and historical data", "label": "DESCRIPTIVE_DATA", "score": 0.7869182229042053, "start": 1104, "end": 1137, "probe_score": 0.6282, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "the actual area irrigated of 30 out of 44 systems was smaller than the designed command area while\n\nfive systems irrigated more area than originally planned. <sup>3</sup> [^3: These comparisons are based on operators’ recall since they do not maintain written records of the area irrigated or fees collected from the\nfarmers.]\n\n\nNearly 80 percent of the JCLISs in our sample draw water from dug wells. Seasonal or perennial\n\n\nstreams (with or without check dams) are the other important sources of water for irrigation\n\n\nsystems. Only 21 systems had reliable access to water throughout the year. Low availability of\n\n\nwater in April, May, and June is a constraint to growing summer crops in the command area. Every\n\n\nsecond operator mentioned water shortage during the critical periods as a constraint to expanding\n\n\nthe command area of their JCLIS. In one village in the Khunti district, farmers in the water user\n\n\ngroup were planning to invest in a buried pipeline to connect the dug well with a nearby stream to\n\n\nimprove water availability in the summer season. We do not know how user groups managed water\n\n\nscarcity. In our informal discussions, farmers reported bearing the yield loss due to soil moisture\n\n\nstress in the summer season after the source of the water dried up. On the other hand, the systems\n\n\nremain idle in the monsoon season (July, August, and September) because of a lack of demand for\n\n\nirrigation. The villages we visited had not experienced droughts or long dry spells during the\n\n\nmonsoon season in the last two years. In years of drought or during long dry spells, JCLISs may\n\n\nbecome useful even during the Kharif season by providing life-saving irrigation to the main paddy\n\n\ncrop if water is available in the source.\n\n\nOperators were also asked to recount the total hours of operation of pumps during the three\n\n\ncropping seasons of the 2020-21 crop year. Their recall data suggests low-capacity utilization of\n\n\nmost JCLISs. The median system worked for just 93.5 hours throughout 2020-21, while the\n\n\naverage operating time was 191.8", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["recall data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001011", "page": 11, "chunk": 0, "title": "idu0be619ce802229044310b97c088a139ef33c1", "pdf_url": "https://local/prwp/idu0be619ce802229044310b97c088a139ef33c1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "recall data", "label": "VAGUE_DATA", "score": 0.6987559199333191, "start": 1897, "end": 1908, "probe_score": 0.6286, "gold": "DATA_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEnhancing Community Resilience and Local Governance Project Phase II (P177093)\n\n\n88. The sustainability of institutions will be ensured by strengthening the capacity of county officials\nand BDCs/PDCs in inclusive development planning, local conflict mapping and mitigation, disaster risk\nmapping, preparedness, and emergency response. Through such training, the project aims to develop a\nlocal governance platform for community-government engagement, dialogue, collective decision-making,\nand collective action such as social audit. These mechanisms could also be adopted in whole or in part by\nother line ministries and development partners. The national government’s capacity will also be\nstrengthened so that it can adequately monitor the county governments’ performance. Regarding the\nsustainability of gender empowerment, capacity building of women under the project will contribute to\nimproved voice and agency of women and gender parity in community decision-making beyond the\nlifespan of the project. Participation of women in O&M committees that are envisioned to outlive ECRPII and sustain subproject infrastructure will also help sustain women’s empowerment.\n\n\n**IV.** **PROJECT APPRAISAL SUMMARY**\n\n\n**A. Technical, Economic and Financial Analysis**\n\n\n89. As part of preparation for this project, an economic and financial analysis (EFA) has been\nconducted to determine the value of the anticipated benefits relative to the costs associated with this\nproject. This EFA examines potential returns of the investments under Component 1, focusing on the\nbenefits associated with the different activities and investments. These benefits vary based on the type\nof investment being undertaken, such as a reduction in vehicle operating costs alongside increased traffic\nflows, benefits to commuters, and potential greater economic benefits expected to result from road and\ndrainage investments. The investment categories evaluated as part of the analysis include road and\ndrainage, boreholes, educational investments, latrines, public health, and flood risk reduction\ninvestments.\n\n\n90. This economic analysis accounts for the benefits in South", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000028", "page": 44, "chunk": 0, "title": "South Sudan - Second Phase of the Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/543171647442225562/pdf/South-Sudan-Second-Phase-of-the-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " take the data of 2017 as the achievement<br>within the project.<br>|<br>**Comments (achievements against targets):** <br>Baseline data was collected in December 2015. With the enhanced enforcement capacity of National Transport Safety Authority (NTSA), the<br>number of road cashes reduced by 30 percent and 22 percent, in 2016 and 2017 respectively, exceeding the original target.<br>Due to internal re-organizations occasioned by the Presidential Directive of January 2018 on Enforcement, the NTSA handed over the<br>responsibility and the enforcement gadgets to the National Police Service. Therefore, this ICR will take the data of 2017 as the achievement<br>within the project.<br>|<br>**Comments (achievements against targets):** <br>Baseline data was collected in December 2015. With the enhanced enforcement capacity of National Transport Safety Authority (NTSA), the<br>number of road cashes reduced by 30 percent and 22 percent, in 2016 and 2017 respectively, exceeding the original target.<br>Due to internal re-organizations occasioned by the Presidential Directive of January 2018 on Enforcement, the NTSA handed over the<br>responsibility and the enforcement gadgets to the National Police Service. Therefore, this ICR will take the data of 2017 as the achievement<br>within the project.<br>|<br>**Comments (achievements against targets):** <br>Baseline data was collected in December 2015. With the enhanced enforcement capacity of National Transport Safety Authority (NTSA), the<br>number of road cashes reduced by 30 percent and 22 percent, in 2016 and 2017 respectively, exceeding the original target.<br>Due to internal re-organizations occasioned by the Presidential Directive of January 2018 on Enforcement, the NTS", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data of 2017", "data of 2017", "data of 2017"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016932", "page": 31, "chunk": 6, "title": "Kenya - National Urban Transport Improvement Project", "pdf_url": "https://documents.worldbank.org/curated/en/702181563299068935/pdf/Kenya-National-Urban-Transport-Improvement-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data of 2017", "label": "VAGUE_DATA", "score": 0.6518411040306091, "start": 10, "end": 22, "probe_score": 0.9715, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "data of 2017", "label": "VAGUE_DATA", "score": 0.5903030037879944, "start": 629, "end": 641, "probe_score": 0.9746, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "data of 2017", "label": "VAGUE_DATA", "score": 0.5695998668670654, "start": 1248, "end": 1260, "probe_score": 0.9793, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n#### **2.2 Current occupational situation**\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nAdministrative ZUS data can be used as a\nproxy for both average and _gross_ earnings\npercentages. On June 30, 2024, average\nbases for social contributions of Ukrainian\nrefugees accounted for just 64% of those\nof Polish citizens. However, this is only\nrelative to Polish citizens not all workers in\nthe economy as a whole, and comes with\nother caveats of administrative instead\nof survey data sources – data given on a\nparticular day instead of period average,\nthe shadow economy unaccounted for,\ndifferent contributions based on the type\nof contract, no data for farmers who belong\nto a separate social insurance scheme.\nAlso, the ZUS data, that is available, is much\nmore limited that the SEIS survey data\nprimarily used in this report.\n\n\n\n**Ukrainian refugees in Poland have**\n**clearly improved their economic**\n**situation over the past year.** In\nthe 15-59/64 age group, employment\nrate of Polish citizens stood at 75% in\nQ2 2024 according to Eurostat, slightly\nmore than the 69% for Ukrainian refugees\nin the SEIS 2024 survey and 73% when\nadjusted for a different sex and age\nstructure. In the 15-64 age group, the\nemployment rate of Ukrainian male\nrefugees was 67% while that of Polish\ncitizens in Q2 2024 was 77%. For women,\nthe rates for Ukrainian refugees and Polish\ncitizens are closer in the 15-59 age group\n(female retirement age in Poland is 60) with\n70% for refugees and 72% for Poles. Visible\n\n\n\ndifferences are identified in 15-19 and\n20-24 age groups, with much higher\nemployment rates for Ukrainian refugees\ndue perhaps to the fact that the Ukrainian\nschool system ends at 17 while the Polish\none at 19. <sup>13", "output": {"entities": {"named_data": ["Administrative ZUS data", "ZUS data", "SEIS survey data", "SEIS 2024 survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 9, "chunk": 0, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Administrative ZUS data", "label": "NAMED_DATA", "score": 0.7478175163269043, "start": 197, "end": 220, "probe_score": 0.96, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "ZUS data", "label": "NAMED_DATA", "score": 0.6331503391265869, "start": 828, "end": 836, "probe_score": 0.9235, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "SEIS survey data", "label": "NAMED_DATA", "score": 0.8147104382514954, "start": 887, "end": 903, "probe_score": 0.9811, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "SEIS 2024 survey", "label": "NAMED_DATA", "score": 0.8446385264396667, "start": 1212, "end": 1228, "probe_score": 0.9774, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " single women, women-headed households, older persons (persons over\n60 years), persons with disabilities, and persons with a diverse sexual orientation or gender identity.\n56 As of December 2019, there are 147,282 refugees classified as PSNs by UNHCR/OPM, in 80,897 households. Population data\nis updated regularly by UNHCR and will be reflected in adjustments to firewood supply volumes and targeting.\n57 Grown on the planting area of approximately 10,000 ha.\n\n\nPage 27 of 83", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Population data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000043", "page": 30, "chunk": 2, "title": "Uganda - Investing in Forests and Protected Areas for Climate-Smart Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/304401587952865863/pdf/Uganda-Investing-in-Forests-and-Protected-Areas-for-Climate-Smart-Development-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Population data", "label": "VAGUE_DATA", "score": 0.7181878089904785, "start": 278, "end": 293, "probe_score": 0.0892, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "project and update the existing ESIA done in 2011 and (iv) Carry out two public\nconsultations as per the Category A, project requirements.\n\nThe specific objectives of the assignment are:\n\n  - To review and update the existing ESIA report to conform with World Bank\n\nEnvironmental and Social Safeguards Policies and Procedures for Environment\nAssessment (OP/BP 4.01), for project assigned **Category A, WBG General EHS**\n**Guidelines and applicable WBG Industry Sector Guidelines** and laws and\nregulations of the Government of Kenya,\n\n  - To review and identify gaps in the existing ESIA report prepared for this\n\nsubproject and address them by evaluating the established social and\nenvironmental context, reviewing the identified potential risks and impacts,\nbenefits and opportunities.\n\n  - To review and identify all the potential significant positive and adverse\n\nenvironmental and social impacts, including direct, indirect and cumulative\nimpacts associated with the proposed project\n\n  - To review proposed measures to avoid, reduce, mitigate, manage and/or\n\ncompensate for such impacts, including the institutional arrangements and\nrequired capacity building to implement all such measures and monitor their\neffectiveness\n\n  - To review and update the Environmental and Social Management Plan (ESMP)\n\n  - Ensure that the stakeholder analysis and consultation are conducted as part of the\n\nESIA review, and identify who among the affected population is particularly\nvulnerable to potential adverse impacts. The project should adopt differentiated\nmeasures so that potential adverse impacts do not fall disproportionately on the\ndisadvantaged or vulnerable\n\n  - To carry out site investigations to collect primary data and review available\n\nrelevant secondary data to establish a comprehensive environmental and social\nbaseline, indicators, and data collection methodology\n\n  - To conduct public consultations and meaningful stakeholder engagement with\n\nproject-affected persons, lead agencies and Non-Governmental Organizations\n(NGOs) about the project's environmental and social impacts, as well as offer\nopportunity to receive  their opinions and feedback so as to take their views into\naccount and reflect the issues raised into the final design for the project.\n\n  -", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["primary data", "secondary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018746", "page": 4, "chunk": 0, "title": "Kenya - National Urban Transport Improvement Project : Environmental Assessment : Consultancy Services for Reviewing and Updating of the Environmental and Social Impact Assessment for the Kisumu Northern Bypass", "pdf_url": "https://documents.worldbank.org/curated/en/824281539762683198/pdf/NUTRIP-ESIA-Review-TOR-Ksm-Northern-Bypass-Final-Disclosed.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "primary data", "label": "VAGUE_DATA", "score": 0.6305992007255554, "start": 1711, "end": 1723, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "secondary data", "label": "VAGUE_DATA", "score": 0.6825212240219116, "start": 1755, "end": 1769, "probe_score": 0.3815, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEthiopia Digital ID for Inclusion and Services Project (P179040)\n\n\n|Component Name|Cost (US$)|\n|---|---|\n|Building institutions and trust|21,000,000.00|\n|Establishing scalable and secure Fayda ICT infrastructure|68,000,000.00|\n|Inclusive ID issuance|214,000,000.00|\n|Improving service delivery|35,000,000.00|\n|Project management and coordination|12,000,000.00|\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Total Operation Cost|350.00|\n|---|---|\n|**Total Financing**|**350.00**|\n|**of which IBRD/IDA**|**350.00**|\n|**Financing Gap**|**0.00**|\n\n\n|World Bank Group Financing|Col2|\n|---|---|\n|International Development Association (IDA)|350.00|\n|IDA Credit|300.00|\n|IDA Grant|50.00|\n\n\n\n\n\n**II**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000005", "page": 6, "chunk": 0, "title": "Ethiopia - Digital ID for Inclusion and Services Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099112223132535848/pdf/BOSIB0efb09b920d90858a0135df22da7d1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " plusieurs facteurs aggravants, notamment, l’utilisation des espaces agricoles pour accueillir les réfugiés, la limitation de\nmise en œuvre des moyens d’existence, la vulnérabilité accrue des femmes et des enfants filles et garçons, la mendicité\ninfantile, la délinquance et les actes de banditisme, les mécanismes d’adaptation néfastes, les tensions et les conflits\nintercommunautaire etc.\n\n\n**<u>IMPACT SUR LES PROGRAMMES HUMANITAIRES REGULIER</u>**\n\n\nDepuis le début de l’urgence, il a été observé un chamboulement au niveau des programmes réguliers. Pour répondre à\nl’urgence et sauver des vies, la quasi-totalité des partenaires par solidarité déploient régulièrement le peu de ressources\nlogistiques, humaines et financières et les assistances pour faire face à cet afflux massif sans précédent à l’Est Tchad. Les trois\nprovinces de l’Est, Ouaddaï, Wadi Fira et le Sila faisaient déjà face à plusieurs défis opérationnels, avant cette nouvelle crise.\n\n\n**<u>IMPACT LIE A L’UTILISATION DE LA MODALITE DE TRANSFERT DES FONDS</u>**\n\n\nLe rapport de l’étude de PNUDiii cité ci-haut et complétée par l’analyse sur la fonctionnalité des marchés du PAMiv en juillet\n2023 et le monitoring des marchés réalisé par le HCRv en août 2023 déterminent les effets de conflits du", "output": {"entities": {"named_data": [], "descriptive_data": ["monitoring des marchés"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000417", "page": 3, "chunk": 3, "title": "Tchad : Analyse de Protection - L’Impact de la nouvelle crise soudanaise sur l’environnement de protection (octobre 2023)", "pdf_url": "https://reliefweb.int/attachments/3904dc01-f626-4723-bb3d-6b83182b98cf/pau_chad_november_2023.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "monitoring des marchés", "label": "DESCRIPTIVE_DATA", "score": 0.6820985674858093, "start": 1175, "end": 1197, "probe_score": 0.0031, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " timber or ecosystem services,\n\n\nwhereas indirect land use change e↵ects are relatively small in this stochastic application of\n\n\nthe FABLE model.\n\n##### **6 Conclusions**\n\n\nThis paper demonstrates how the uncertainties associated with nonstationary biophysi\n\ncal processes and technological change can be incorporated into an economic analysis of the\n\n\noptimal allocation of natural resources in the long run. In doing so, it introduces a novel com\n\nputational method, ENLCEQ, for solving nonstationary dynamic high-dimensional stochas\n\ntic problems and applies it to FABLE, a recently developed multi-sectoral dynamic model\n\n\nof global land use.\n\n\nFor illustrative purposes, the study focuses on uncertainty in future crop yields, one of\n\n\nthe core uncertainties a↵ecting the evolution of global land use in the long run. Combining\n\n\nscenarios from global climate models and high-resolution output from spatial crop simulation\n\n\nmodels for four major crops, it comes up with a plausible range of realizations of climate\n\n\nshocks and their e↵ect on future crop yields. These estimates are supplemented with an\n\n\nextensive survey of recent agro-economic and biophysical studies assessing the potential for\n\n\nclosing yield gaps as well as attaining further advances in potential yields through plant\n\n\nbreeding.\n\n\nThe paper’s key insight is to illustrate the magnitude of optimal land conversion deci\n\nsions in the context of di↵erent realizations of the stochastic crop productivity. Consistent\n\n\nwith the economic theory of natural resource management under uncertainty, the agricul\n\ntural productivity shocks, due either to adverse climate impacts or unexpected limits on\n\n\n24", "output": {"entities": {"named_data": [], "descriptive_data": ["high-resolution output from spatial crop simulation\n\n\nmodels"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001893", "page": 25, "chunk": 1, "title": "modeling uncertainty in large natural resource allocation problems", "pdf_url": "https://local/prwp/modeling-uncertainty-in-large-natural-resource-allocation-problems.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "high-resolution output from spatial crop simulation\n\n\nmodels", "label": "DESCRIPTIVE_DATA", "score": 0.5185970067977905, "start": 877, "end": 937, "probe_score": 0.5847, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nGenerating Growth Opportunities and Productivity for Women Enterprises Uganda (P176747)\n\n\n\n\n\n|Col1|(including women in RHDs<br>and refugees) who have<br>improved access to non-<br>financial entrepreneur<br>services supported by the<br>project under components 1<br>and 3.|Col3|specific to<br>each service.|service.|those specific to each<br>service.|\n|---|---|---|---|---|---|\n|Women in RHDs|<br>|||||\n|Refugee women|<br>|||||\n|Beneficiaries reached with financial<br>services|The indicator measures the<br>number of persons<br>benefited from financial<br>services in operations<br>supported by the Bank, and<br>the number of businesses<br>that benefited from<br>financial services.|Continuous<br>|PFI data<br>|The PFIs will maintain a<br>database of recipients<br>of grants linked to<br>loans.<br>|PSFU to collect the data<br>from the PFIs, and<br>compile and report it.<br>|\n|Women in RHDs|<br>|||||\n|Refugee women|<br>|||<br>||\n|Total project beneficiaries (Number)|Project beneficiaries are<br>women entrepreneurs who<br>derive benefits including the<br>(a) platforms and<br>communication campaign,<br>(b) enterprises support<br>services, (c) financial<br>services including improved<br>products for", "output": {"entities": {"named_data": ["PFI data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 49, "chunk": 0, "title": "Uganda - Generating Growth Opportunities and Productivity for Women Enterprises Uganda Project", "pdf_url": "http://documents.worldbank.org/curated/en/527091655323259747/pdf/Uganda-Generating-Growth-Opportunities-and-Productivity-for-Women-Enterprises-Uganda-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PFI data", "label": "NAMED_DATA", "score": 0.7302189469337463, "start": 717, "end": 725, "probe_score": 0.101, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "</sup>\n\n2. **Lower economic activity in the industry and services sectors will lead to job losses and, with the shift of**\n**labor back to agriculture, will result in increased vulnerabilities and increased poverty levels.** Growth in\nmanufacturing decelerated to 1.3 percent from June 2019 to June2020, from 6.5 percent from June 2018 to June\n2019, while growth in trade and tourism-related activities, such as hotel accommodation and restaurants, is\nexpected to shrink from an average annual growth of 3.5 percent to about 1 percent over the same period. <sup>2</sup> [^2: Uganda Economic Update, 15th Edition, July 2020.] Supply\nchain disruptions, increasing lead times for critical inputs and unanticipated delivery cancellations, are\nconstraining firm-level activity, which will affect industrial output. The number of people that could be pushed\ninto poverty is estimated at 780,000. <sup>3</sup> [^3: Statement on the Economic Impact of COVID-19 by the Ministry of Finance, Planning and Economic Development (MoFPED).] Overall, the poverty rate could increase between 1.8 and 7.3 percentage\npoints, from the current level of 25.3 percent. This would add between 0.5 and 2.07 million to the rural poor\n(which stood at 7.2 million in 2016/17).\n\n\n3. **Poverty has increased significantly in Uganda after the first COVID-19 lockdown in March–June 2020**\n**given the shift of workers to agriculture and the slow recovery of household incomes** <sup>**4**</sup> [^4: UBOS has recently announced poverty rates based on UNHS 2019/20.] . Despite an improvement\nbetween October 2020 and April 2021, income levels were still below pre-COVID levels for at least one third of\nhouseholds before the onset of the second COVID-19 wave in June 2021. This is concerning given the", "output": {"entities": {"named_data": ["UNHS 2019/20"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000073", "page": 13, "chunk": 1, "title": "Uganda - Investment for Industrial Transformation and Employment Project", "pdf_url": "http://documents1.worldbank.org/curated/en/469061641926083502/pdf/Uganda-Investment-for-Industrial-Transformation-and-Employment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHS 2019/20", "label": "NAMED_DATA", "score": 0.8801239132881165, "start": 1519, "end": 1531, "probe_score": 0.9904, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "6\n\n\nThere is strong support in the Government for increasing resources for education, and the Government\nmade a commitment to increase education's share of budget from 16% in 2001-02 to 25% in 2009-10.\n\n\nOne of the reasons for choosing an APL with a ten-year perspective is that the education budget\nshortages will continue to be a constraint in the next few years. Over this period, Government\n\nexpenditures in non-priority areas will be brought under control and Government expenditures on\neducation can be expected to increase significantly. Despite the manageability in the long-run, the\nshort-run prospects on the budget are more challenging and donors will need to finance some recurrent\ncosts. The proposed APL will be implemented in three phases with distinct triggers (see Section B. 4).\nAs a result, a 10-year projection of enrollments and education costs has been developed (which is the\noverall framework for the APL), and a detailed five year plan and project proposals have been\nprepared (which is the framework for the first phase of the APL).\n\n\n3. Sector issues **to be addressed by the project and strategic choices**\n\nThe project will directly address all the issues below except for higher education.\n\n\n_Issues/Sector Problems_ _Government strategy and project proposal_\n\n**School Places**\n\nThe immediate problem in Djibouti City and The Government's strategy includes a combination\nsurrounding suburbs and other towns is the lack of of building more schools and continuing with the\nschool places due to the strong demand for schooling. double-shifting policy. The project will finance new\nclassrooms, sanitation services, and school furniture.\n\n**Equity, Gender, Disparities**\n\nChildren from poorer families, rural children, and The Government will construct schools in underespecially girls do not always attend school. The served areas, particularly in poorer parts of Djiboutirecent Household Expenditure Survey states that Ville where almost 70% of the population lives.\nmajor reasons for the", "output": {"entities": {"named_data": [], "descriptive_data": ["Household Expenditure Survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011461", "page": 9, "chunk": 0, "title": "Uganda - Water Supply and Sanitation Rehabilitation Project", "pdf_url": "https://documents.worldbank.org/curated/en/336911468317942760/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Household Expenditure Survey", "label": "DESCRIPTIVE_DATA", "score": 0.6417368054389954, "start": 1906, "end": 1934, "probe_score": 0.9529, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " on external funding can be long-term. For example, Crisp (2003)\nnotes that the Kakuma camp in Kenya was still entirely dependent on external aid 10 years\nafter it came into existence. <sup>56</sup>\n\nAnother major issue influencing camp policies in Africa is security (Abuya, 2007; Schmidt, 2003;\nMilner 2009). These can range from attempting to reduce conflict between local populations\nand refugees, protecting refugee populations from attacks in neighbouring warring countries,\nto perceived increases in criminality if refugees are allowed to integrate locally (Schmidt,\n2003). <sup>57</sup> Recently however, all transnational movement by refugees and asylum seekers are\nbeing constructed as security threats and illegal. <sup>58</sup> Through a process of securitisation,\nrefugees and other forced migrants are seen as ‘others’ who are a security risk and a threat to\nthe identity of the nation (Haddad, 2008). <sup>59</sup> As Saunders (2014) notes, there has been a\nparadigm shift in asylum policy, from a focus on ‘humanitarian-driven refugee protection\nensconced in international law, to one prioritising the protection of national security interests’\n(p.72). <sup>60</sup> Meaning, while security concerns by host states do warrant serious attention, it is\nimportant to always differentiate between genuine security issues and the securitisation of\nrefugee movements by states for their own political gains.\n\nVarious case studies have suggested that many of the arguments set out above are based on\npotentially misinformed assertions. Furthermore, attempting to exercise control over a refugee\npopulation through encampment policies can create far more negative outcomes than\nintegration policies (Black, 1998). For example, Hovil (2007) found that in studies of local\nintegration in Uganda social tension and chaos did not occur. In contrast, camps in", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001370", "page": 12, "chunk": 1, "title": "New issues in refugee research - research paper no. 281 - Rights at risk: A thematic investigation into how states restrict the freedom of movement of refugees on the African continent", "pdf_url": "https://reliefweb.int/attachments/d3f8a290-99ed-38ad-8a55-f139a71cded2/5857eb794.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " accurate data than ground stations in most locations and do not extend as far\n\n\nback in time. Gridded data, on the other hand, aggregate data from ground stations via interpolation and\n\n\nacross a given space. This works well in developed countries, where there is wide and uniform coverage\n\n\nof weather stations across the entire territory, but not so much in developing contexts, where often\n\n\ngridded data aggregate weather information from a few old stations spread across the country. Sparse\n\n\ncoverage is a serious issue given the interpolation method adopted by gridded products. Finally, entry\n\n\nand exit of stations (quite common, especially in poorer countries) can be endogenous and represents an\n\nadditional source of measurement error of true weather conditions experienced by people. <sup>11</sup> Such\n\n\ndiversity in weather data products can affect econometric estimates of the relationship between climatic\n\n\nevents and a given socioeconomic outcome of interest. Second, the need for spatial anonymization for\n\n\nprivacy protection in household surveys, usually implemented through a random offset of true household\n\n\n11 See Auffhammer et al. (2013) and Dell, Jones and Olken (2014) for further discussion. For a comprehensive overview of\n\n\nthe availability and quality of climate data in the context of Africa see, instead, Dinku (2019).\n\n\n22", "output": {"entities": {"named_data": [], "descriptive_data": ["gridded data", "weather data products", "household surveys"], "vague_data": ["climate data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000662", "page": 23, "chunk": 1, "title": "idu02c48191c0d6dc044ee0bb92046827d430703", "pdf_url": "https://local/prwp/idu02c48191c0d6dc044ee0bb92046827d430703.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "gridded data", "label": "DESCRIPTIVE_DATA", "score": 0.5465752482414246, "start": 396, "end": 408, "probe_score": 0.2832, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "weather data products", "label": "DESCRIPTIVE_DATA", "score": 0.5618076324462891, "start": 832, "end": 853, "probe_score": 0.4642, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "household surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8191337585449219, "start": 1051, "end": 1068, "probe_score": 0.38, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "climate data", "label": "VAGUE_DATA", "score": 0.6923156380653381, "start": 1289, "end": 1301, "probe_score": 0.5026, "gold": "NON_MENTION", "gold_tier": "human-final"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " la\nregión de Oriente Medio y Norte de África, y en la República Democrática del Congo, donde\nse dieron a conocer herramientas prácticas y el módulo de capacitación de la Oficina sobre\nla inclusión de la discapacidad <sup>5</sup> [^5: Puede consultarse en https://www.unhcr.org/what-we-do/how-we-work/safeguarding-\n[individuals/persons-disabilities/strengthening-protection.](https://www.unhcr.org/what-we-do/how-we-work/safeguarding-individuals/persons-disabilities/strengthening-protection)] .\n\n\n37. El ACNUR empleó enfoques comunitarios de protección para garantizar una mayor\nparticipación de las personas desplazadas y apátridas mediante la cooperación con\norganizaciones de base dirigidas por refugiados, habida cuenta de que las estructuras\ncomunitarias suelen ser las primeras en responder ante una crisis humanitaria. También se\napoyó a las mujeres desplazadas y apátridas en las estructuras comunitarias de liderazgo y\ngestión. En Darfur (Sudán), la Oficina proporcionó a las estructuras comunitarias equipos y\n\n\n4 ACNUR, “Guidance: Identification of persons with disabilities at registration and other data\n[collection efforts”; puede consultarse en https://www.unhcr.org/media/65079.](https://www.unhcr.org/media/65079)\n[5 Puede consultarse en https://www.unhcr.org/what-we-do/how-we-work/safeguarding-](https://www.unhcr.org/what-we-do/how-we-work/safeguarding-individuals/persons-disabilities/strengthening-protection)\n[individuals/persons-disabilities/strengthening-protection.](https", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000379", "page": 8, "chunk": 3, "title": "Nota sobre protección internacional - Nota del Alto Comisionado (A/AC.96/74/3)", "pdf_url": "https://reliefweb.int/attachments/314f77fe-ae53-42b1-b2d0-38f7860fff71/G2314716.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nStrengthening Public Sector Efficiency and Statistical Capacity Project (P151155)\n\n\n**<mark>Subcomponent 4.2. Strengthening the national accounts production</mark>**\n\n\n45. **Objective** . The objective of this subcomponent is to improve the production of the national\naccounts.\n\n\n46. **Current status.** Building reliable national accounts requires an important amount of basic data\non enterprises including the informal sector, agricultural production, public finance (Central\nGovernment and communes), balance of payment and external trade, and so on. All those data are not\nalways available and if they are, the coverage might not be complete. A statistician has to develop\ndifferent strategies to get the work done, for example, by organizing light surveys to derive structural\nparameters that might help complete some estimations.\n\n\n47. Annual national accounts will be improved with better external trade statistics. External trade\nstatistics suffer from an incomplete coverage and the magnitude of the underestimation that results\nfrom this situation is unknown. External trade statistics are produced using information from the\ncustoms administration ( _Direction Générale des Douanes_ ). Clearly, merchandises that cross the borders\nwithout going through the customs are not captured by the external trade statistics. INS has identified\neight main sites of these activities all along the borders with Nigeria and other neighboring countries.\n\n\n48. In addition to classic national accounts, INS produces quarterly national accounts since 2015.\nThe methodology of building infra-annual accounts is different because basic annual data are not\navailable for each quarter. INS uses a series of indicators taken from quarterly enterprise surveys\n(financed from an ad hoc grant of MINFI) and some other sources to produce quarterly national\naccounts.\n\n\n49. **Proposed activities.** The project will finance data collection for a baseline year and the\ndevelopment of a methodology of collecting those data for the subsequent years. The idea is to develop\na light methodology making it", "output": {"entities": {"named_data": [], "descriptive_data": ["external trade statistics", "quarterly enterprise surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000044", "page": 59, "chunk": 0, "title": "Cameroon - Strengthening Public Sector Effectiveness and Statistical Capacity Project", "pdf_url": "http://documents1.worldbank.org/curated/en/305621511406035802/pdf/CAMEROON-PAD2-11012017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "external trade statistics", "label": "DESCRIPTIVE_DATA", "score": 0.657163679599762, "start": 915, "end": 940, "probe_score": 0.8107, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "quarterly enterprise surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8622771501541138, "start": 1739, "end": 1767, "probe_score": 0.6169, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the economy. It provides information\non the total impact of shocks on various\naspects of the economy, including the\nlabour market, government revenue, as\nwell as key economic aggregates. It is the\nmost appropriate tool for accounting for\nthe multi-layered impact of Ukrainian\nrefugees. A counterfactual analysis was\nperformed using the latest data on the\nPolish economy to account for the effects\nof other shocks in the economy. The model\nenabled a counterfactual analysis to be\nconducted by isolating the refugee influx\nfrom all other economic shocks, e.g. the\nother macroeconomic consequences of the\nwar in Ukraine. The results were calculated\nfor 2022, 2023 and 2024 with an additional\nlong-term analysis up to 2030 to assess the\neconomy’s long-term adaptation (assuming\nno new shocks, including no countershocks <sup>34</sup> [^34: E.g. refugees keep having lower productivity rather than adapt to level of natives.] ).\n\n\n32 <u>Economics of climate change | Deloitte Australia</u>\n\n\n\n**Chart 32. Average weekly hours in main job**\n\nWomen in 15-64 age group\n\n\n\n68.4%\n\n\n2023-Q2\n\n\n\n68.8%\n\n\n2024-Q2\n\n\n\n2021-Q2\n\n\n\n67.5%\n\n\n2022-Q2\n\n\n\n40.3\n\n\n\n40.3\n\n\n\n40.4\n\n\n\n40.4\n\n\n\n\n\n\n\n\n\n\n\nSource: Deloitte own elaboration based of Eurostat\ndata (Labour Force Survey).\n\n\n\nSource: Deloitte own elaboration based of Eurostat\ndata (Labour Force Survey).\n\n\n\nPart-time\n\nFull-time\n\n\n\n31 Deloitte has not received data that would be detailed as to citizenship, poviat, sex, age group, occupational group, and ZUS insurance code that would be suitable\nfor econometric approach.\n\n\n42\n\n\n\n33 <u>https://www2.deloitte.com/pl/pl/pages/risk/solutions/analiza-ryzyk-klimatycznych-badanie-scenariuszy-z-modelem-DClimate.html34</u>\n\n34 E.g. refugees keep having", "output": {"entities": {"named_data": ["Eurostat\ndata", "Labour Force Survey"], "descriptive_data": ["data on the\nPolish economy"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 21, "chunk": 2, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on the\nPolish economy", "label": "DESCRIPTIVE_DATA", "score": 0.7640239596366882, "start": 344, "end": 370, "probe_score": 0.4794, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Eurostat\ndata", "label": "NAMED_DATA", "score": 0.6647975444793701, "start": 1215, "end": 1228, "probe_score": 0.006, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Labour Force Survey", "label": "NAMED_DATA", "score": 0.6255925297737122, "start": 1230, "end": 1249, "probe_score": 0.9867, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "improve the fit of the regression, and so we stick with a linear income term for the remaining\n\ncolumns. <sup>14</sup> [^14: Total household labour income also led to a better fit than using either log(income/100+1) or per capita household\nlabour income. Adding one pa’anga to household labour income is done to allow taking logarithms of income for\nhouseholds which report zero labour income.]\n\n\nColumns 5 and 6 of Table 1 then estimate the correlates of mental health separately by sex. Most\n\n\nof the variables have similar relationships with mental health for males and females. In\n\n\nparticular, a 100 pa’anga increase in monthly household labour income is associated with a 0.11\n\n\nincrease in mental health for men and a 0.12 increase in mental health for women. In contrast,\n\n\nbeing employed is associated with a stronger effect on mental health for women than for men.\n\n\nSmoking is associated with lower mental health for men than for women. In Column 7, we\n\n\ntherefore re-estimate the regression by pooling sexes, but allowing for interactions between\n\n\ngender and employment status, and gender and smoking. This shows being employed to be\n\n\nsignificantly associated with better mental health status for females, but not for males.\n\n\n**5. The Effect of Migration on Mental Health**\n\n\n**5.1. Estimating treatment effects using experimental data**\n\n\nThe remainder of this paper focuses on estimating the impact of migration to New Zealand on\n\n\nthe mental health of Tongans. To determine the impact of migration on mental health, one must\n\n\ncompare the mental health of the migrant to what their mental health would have been like had\n\n\nthey not migrated. Typically, it is not possible to readily identify this unobserved counterfactual\n\n\noutcome. However, the PAC lottery system, by randomly denying eager migrants the right to\n\n\nmove to New Zealand, creates a control group of individuals that should have the same outcomes\n\n\nas what the migrants would have had if they had not moved. As can", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["experimental data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003350", "page": 10, "chunk": 0, "title": "wps4138", "pdf_url": "https://local/prwp/wps4138.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "experimental data", "label": "VAGUE_DATA", "score": 0.6279237866401672, "start": 1333, "end": 1350, "probe_score": 0.9455, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "PROTECTION BRIEF: SUDAN – APRIL 2024\n\n### Key Elements of UNHCR’s Protection Response\n\n\n**_Community based approach_**\nProtection monitoring reports reveal that a significant part of the displaced\npopulation has at least one specific need or vulnerability. The most common are\nhaving a chronic medical condition or physical disability, being an unaccompanied\nor separated child or elderly. These vulnerable people are disproportionately\naffected by the conflict and multiple displacements, exposing them to further\nrisks.\n\nWith constrained humanitarian access impacting protection programming,\nUNHCR in Sudan is strengthening the capacity of community-based protection\nnetworks (CBPNs) across the country, establishing community centres in areas of\nrecent displacement, enhancing its communication with communities (CwC)\nthrough various channels to reach out to the most vulnerable populations and\nsupporting community-led projects and organisations. To monitor, track and refer\npeople with specific needs, UNHCR developed a monitoring tool and standard\noperating procedures and pathways to identify and refer people for specific\nservices and assistance.\n\nUNHCR works with 345 community-based protection committees or associations\nrepresenting various groups of forcibly displaced people. UNHCR supports these\ncommunity-based protection networks with training on protection monitoring\nmethodologies and the identification of specific needs. The CBPN’s have been\ninstrumental in identifying, referring, and supporting vulnerable individuals,\nstrengthening communication with communities and building community\nresilience through monitoring and raising awareness on specific areas of\nprotection concern.\n\nUNHCR uses various communication channels to enhance its communication with\n[forcibly displaced populations especially in hard-to-reach areas. UNHCR’s Help](https://help.unhcr.org/)\n[Website provides essential information on protection queries, available services,](https://help.unhcr.org/)\nand contacts, and asylum procedures, rights and duties. UNHCR set up a\nWhatsApp channel for communication with forcibly displaced people which is\navailable in four languages and has proven indispensable to keep communication\nchannels open and understand the situation", "output": {"entities": {"named_data": [], "descriptive_data": ["Protection monitoring reports"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001397", "page": 14, "chunk": 0, "title": "Protection Brief Sudan, April 2024", "pdf_url": "https://reliefweb.int/attachments/d87b1be7-69c3-42fb-95cf-413e56b215c0/Protection%20Brief%20%20Sudan%20-%201%20year.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Protection monitoring reports", "label": "DESCRIPTIVE_DATA", "score": 0.8741475939750671, "start": 119, "end": 148, "probe_score": 0.2873, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " heard and a ruling was given in favour of the Bureau. **All** the\nmonographs have since been disseminated.\n\n\nII. **HCCC** **No 79** **OF** **2010** **BM** **Logistics VS** **KNBS (Godown** **case).**\n\nThis case involved the godown where the **2009** Population and Census\nmaterials were being stored. The claimant is claiming KShs.43 million for\nloss of business and rent. The Legal Unit is handling the case and is still\npending in court.\n\n\nIII. **Nakuru** **HCCC** **NO** **115 OF** **2008**\n**Attorney General** **(KNBS)** **VS** **The** **Standard Newspapers** **Limited**\n\nThis case concerned an accident that occurred near Gilgil involving the\nBureau's vehicle and another one owned **by** Standard Newspapers Limited.\nThe Bureau is claiming KShs.1.5 million, being the value of the vehicle that\n\nhad an accident. The hearing date is yet to be taken.\n\n\n**52**", "output": {"entities": {"named_data": [], "descriptive_data": ["Population and Census\nmaterials"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016623", "page": 57, "chunk": 1, "title": "Kenya National Bureau of Statistics audited financial statement FYE 30 June 2016", "pdf_url": "https://documents.worldbank.org/curated/en/682111493970304522/pdf/Kenya-National-Bureau-of-Statistics-audited-financial-statement-FYE-30-June-2016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Population and Census\nmaterials", "label": "DESCRIPTIVE_DATA", "score": 0.6019539833068848, "start": 251, "end": 282, "probe_score": 0.1364, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Employability and Skill Set of Newly Graduated Engineers in India** <sup>**1**</sup>\n\n\n**Andreas Blom and Hiroshi Saeki** <sup>**2**</sup>\n\n\n**JEL Classification** : I23, I25, J23, J24, J28, O15\n\n\n**Keywords** : Employability, Skills, Employer Survey, Satisfaction, Engineering, Higher Education,\nIndia\n\n\n1 The authors would like to thank the Federation of Indian Chambers of Commerce and Industry (FICCI) for\nits technical and implementation‘s support of the survey. The authors would like to express their gratitude to\nNational Project Implementation Unit under the Ministry of Human Resource Development for its\nadministrative support of the survey. The employer survey was made possible thanks to the FICCI‘s\nmember companies that kindly responded to the survey. We are also grateful for comments received at the\nFICCI Higher Education Summit 2009 and at World Bank presentations. We appreciate comments received\nfrom colleagues notably Patrick Terenzini and Amit Dar.\n2 [Andreas Blom (World Bank, ablom@worldbank.org), Hiroshi Saeki (World Bank, hsaeki@worldbank.org)](mailto:ablom@worldbank.org)", "output": {"entities": {"named_data": ["Employer Survey"], "descriptive_data": ["employer survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004822", "page": 2, "chunk": 0, "title": "wps5640", "pdf_url": "https://local/prwp/wps5640.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Employer Survey", "label": "NAMED_DATA", "score": 0.6958473920822144, "start": 237, "end": 252, "probe_score": 0.798, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "employer survey", "label": "DESCRIPTIVE_DATA", "score": 0.5394909977912903, "start": 659, "end": 674, "probe_score": 0.8653, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "squares of output, referred to as the weight. Thus, the R <sup>2</sup> of the joint-block equation (V.1),\n\n0.9566, is equal to the weighted average of the independent-block values for R <sup>2</sup> . The t\n\nscore in the joint-block regression is obtained from the estimation of equation (V.1). It is\n\n\nclear that the contribution of the within variables to the explanation of total output ( _y_ ) is\n\n\nrelatively small and that the t-score of the coefficients is lower than that obtained from the\n\n\nindependent-block estimation where the dependent variable is _W(it)y_ . On the other hand,\n\n\nthe difference between the two versions is smaller for the between-country estimates. This\n\n\nis a demonstration of the consequences of an implicit or explicit preference for using the\n\n\nbetween estimates, which in the case of panel data, would be the between-country\n\n\nestimates. The within estimates are avoided by working with country averages. However,\n\n\nthe within variables provide information for identifying the production function and are\n\n\nless contaminated by variables leading to inconsistency in the estimates.\n\n\nThe key question of this analysis is whether the coefficients of the variables\n\n\ncommon to the three canonical regressions are the same, aside from sampling error. A\n\n\ncasual inspection of the results indicates that they are quite different, confirming the basic\n\n\ninitial hypothesis that the regressions summarize the combined effect of changes in inputs\n\n\nand technology, and therefore the within and between regressions summarize different\n\n\nprocesses.\n\n\nTo introduce uniformity in the results of the various models we impose constant\n\n\nreturns to scale on the within estimates. This constraint is imposed only on the within\n\n\nestimates, because the between estimates are subject to the jointness effect and therefore do\n\n\nnot present pure input elasticities. The sum of the within elasticities without this constraint\n\n\nis 1.25, and the difference between the input elastic", "output": {"entities": {"named_data": [], "descriptive_data": ["panel data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003743", "page": 20, "chunk": 0, "title": "wps4536", "pdf_url": "https://local/prwp/wps4536.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "panel data", "label": "DESCRIPTIVE_DATA", "score": 0.6879571676254272, "start": 819, "end": 829, "probe_score": 0.9018, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". The change management and\ncapacity building features built into project design are intended to generate widespread buy-in and increased\ndemand from citizens and civil servants for the continuation of a culture of efficiency improvements in service\ndelivery through digital interventions. The project will facilitate increased coordination across the whole-ofgovernment to adopt and maintain a culture of an iterative, dynamic approach to selecting public services to be\nreengineered beyond the scope and duration of this project. In the future, the GoU will need to secure resources\nto cover operations and maintenance costs of the digital platforms and services deployed under the project.\n\n\n**IV.** **PROJECT APPRAISAL SUMMARY**\n\n\n**A.** **Technical, Economic and Financial Analysis (if applicable)**\n\n\n**Technical Analysis**\n\n**68.** **The UDAP-GovNet aims to expand access to high-speed Internet, improve efficiency of digital government**\n**services, and strengthen the digital inclusion of host communities and refugees.** The project components were\ndesigned as an integrated and interlinked program to maximize the development impact of the investments,\nwhich are being complemented by TA and regulatory reform. The project aims to: (a) expand access to high-speed\nInternet, (b) improve efficiency of digital government services development and delivery, and (c) strengthen\nthe digital inclusion of RHDs and refugees. The technical approach to address these outcomes aligns closely with\nlessons learned from recent implementation of RCIP-5 in Uganda, other projects with similar scope from around\nthe world, the findings of the World Development Report (WDR) 2016, which highlights the need for digital access,\nefficiency, and inclusion.\n\n**69.** **For component 1,** the technical design is based on a model of competitive, private-sector delivery wherever\npossible. The project will utilize a ‘cascade approach’ to leverage private", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000023", "page": 39, "chunk": 1, "title": "Uganda - Digital Acceleration Project", "pdf_url": "http://documents.worldbank.org/curated/en/473041622944887337/pdf/Uganda-Digital-Acceleration-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " recommandées pour les sous-composantes :\n\n<u>Composante</u> <u>Analyse des bénéfices</u> <u>Disponibilité des données</u>\n<u>Amélioration des Infrastructures</u>\nRéhabilitation des rues 2,3 Non\nAssainissement et drainage 2 Non\nCDC 2 Non\nJardin public et terrain de sport 2 Non\nDéveloppement communautaire 2 Non\n<u>Assistance technique</u> <u>3</u> <u>Non</u>\n_1 = préférences révélées, 2 = prix hédoniques, 3 = économies de ressources, 4 = évaluation contingente_\n\n\n**22.** Il a été convenu que parallèlement à la préparation des avants projets détaillés et des documents\nd’appel d’offre pour la première année de mise en œuvre du projet, l’ADDS collectera les données non\n\n\n62", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["données non\n\n\n62"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000163", "page": 61, "chunk": 2, "title": "Djibouti - Urban Poverty Reduction Program Project : Djibouti - Projet de Reduction de la Pauvrete Urbaine", "pdf_url": "http://documents1.worldbank.org/curated/en/934951468235146436/pdf/429990PAD0FREN1erni1re0version02008.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "données non\n\n\n62", "label": "VAGUE_DATA", "score": 0.5954980254173279, "start": 662, "end": 678, "probe_score": 0.5916, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Achieved by 106.8%. The project supported several interventions to strengthening the capacity of the Judiciary<br>and put in place mechanisms to resolve land disputes. The project supported the clearance of above 773 cases<br>under High Court Land, Commercial, and Family Divisions.|Achieved by 106.8%. The project supported several interventions to strengthening the capacity of the Judiciary<br>and put in place mechanisms to resolve land disputes. The project supported the clearance of above 773 cases<br>under High Court Land, Commercial, and Family Divisions.|Achieved by 106.8%. The project supported several interventions to strengthening the capacity of the Judiciary<br>and put in place mechanisms to resolve land disputes. The project supported the clearance of above 773 cases<br>under High Court Land, Commercial, and Family Divisions.|Achieved by 106.8%. The project supported several interventions to strengthening the capacity of the Judiciary<br>and put in place mechanisms to resolve land disputes. The project supported the clearance of above 773 cases<br>under High Court Land, Commercial, and Family Divisions.|Achieved by 106.8%. The project supported several interventions to strengthening the capacity of the Judiciary<br>and put in place mechanisms to resolve land disputes. The project supported the clearance of above 773 cases<br>under High Court Land, Commercial, and Family Divisions.|\n|Number of Parish Physical<br>Development Plans produced<br>(Number)|0.00|Sep/2020|||566.00|Nov/2024|653|Nov/2024|\n|Number of Parish Physical<br>Development Plans produced<br>(Number)|Comments on achieving targets|Comments on achieving targets|Achieved. Above 100% Achievement rate. The Physical Development plan subcomponent was successfully", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:004632", "page": 48, "chunk": 1, "title": "Uganda - Competitiveness and Enterprise Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/099100825112042288/pdf/BOSIB-477828a7-85a7-4919-989c-07717a00beec.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Figure 10. Contribution to Within-Group Inequality by Care Categories\n\n\n\n0.08\n\n\n0.07\n\n\n0.06\n\n\n0.05\n\n\n0.04\n\n\n0.03\n\n\n0.02\n\n\n0.01\n\n\n0.00\n\n\n\nMarket\nincome\n\n\n\nFinal\nincome\n\n\n\nDisposable\n\nincome\n\n\n\nConsumable\n\nincome\n\n\nSingle adults, dependents\n\nMarried couple, dependents\n\n\n\nNo dependents\n\nOther care categories\n\n\n_Source:_ Rodriguez, Wai-Poi, and Woodham (2022).\n\n\n\nAll told, in Jordan, the receipt of in-kind benefits, primarily education, determines which fiscal or care\n\ngroups receive positive net benefits from the fiscal system. When focusing only on cash benefits, the fiscal system\n\nis very close to neutral for groups. The Jordanian fiscal system does reduce within-group inequalities but has only a\n\nvery small impact on inequalities between groups which are very low at the outset. Most of the within-group\n\ninequality reduction happens when direct taxes and transfers are added to the fiscal system. <sup>39</sup>\n\n\nc. Incorporating Time-Use Data\n\n\nJordan has one of the lowest rates of female labor force participation in the world at around 15 percent, and during the\n\nCOVID-19 pandemic, unemployment rates among women rose dramatically. In Jordan, as elsewhere, women bear\n\nmore responsibility for childcare during school closures as well as care for other family members who have fallen sick.\n\nWomen ages 15 to 44 spend over thirteen times as much time on chores and nearly five times as much time on\n\nchildcare as men of the same age group (World Bank 2020).\n\n\n30", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Time-Use Data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001588", "page": 31, "chunk": 0, "title": "idu1e17bd9dd11435145f41a4cf146d8fcaf8bfe", "pdf_url": "https://local/prwp/idu1e17bd9dd11435145f41a4cf146d8fcaf8bfe.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Time-Use Data", "label": "VAGUE_DATA", "score": 0.6533215045928955, "start": 941, "end": 954, "probe_score": 0.8514, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">\n<u>(ICEET)</u> <u>Loans</u> <u>5.3</u>\n<u>La Sociedad de Fomento a la Educación Superior (SOFES)</u> <u>Loans</u> <u>60.4</u>\n\n<u>Instituto de Crédito Educativo del Estado de Sonora (ICEES)</u> <u>Loans</u> <u>30.7</u>\n<u>Scholarships</u> <u>16.7</u>\nPeru\n<u>Instituto Nacional de Becas y Créditos Educativos (INABEC)</u> <u>Loans</u> <u>31.7</u>\nNote: Amount in PPP US$ 2003 prices.\n\n**2.2.2. Accessibility**\n\nTo estimate the four accessibility indicators, we use data from the education and\ndemographic sections of the national household surveys. The education section provides\ndata on school participation, the highest level of education completed, father’s\neducational level, and current level of education. The demographic section of the surveys\ndescribes age, gender, relationship of interviewee to household head, and parent-children\nrelationships.\n\n**3. FINDINGS**\n\nThis section presents the findings of affordability and accessibility among the four LAC\ncountries and the high-income countries. We present each indicator of affordability and\naccessibility as a percentage of GDP per capita at PPP. The detailed results are in the\nannex (Table 8 – 21).\n\n**3.1. Affordability**\n\nFor our analysis, it is helpful to define five groups of countries:\n\n    - _Latin America_ : Brazil, Colombia, Mexico and Peru\n\n    - _Japan_\n\n    - _Anglo-Saxon countries_ : Australia, Canada", "output": {"entities": {"named_data": [], "descriptive_data": ["national household surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003724", "page": 13, "chunk": 1, "title": "wps4517", "pdf_url": "https://local/prwp/wps4517.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "national household surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8857257962226868, "start": 523, "end": 549, "probe_score": 0.9686, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### **Summary**\n\n**Objective**\n\n- This cross sectional survey was conducted among Syrian refugees living in Lebanon, to\nmonitor access to and utilization of key health services. Refugees in Lebanon are\npredominantly living in urban areas and informal settlements and there are no refugee\ncamps.\n\n\n**Methods**\n\n- 10 surveyors underwent two days of training.\n\n- The survey was carried out over a period of ten days from 15 <sup>th</sup> - 26 <sup>th</sup> August 2016.\n\n- Survey households were selected using stratified systematic sampling, from a list of refugee\nhouseholds who had a listed telephone number.\n\n- The head of household, or an adult (aged 18 or over) who could respond on his or her\nbehalf, was interviewed by telephone.\n\n- Data were entered using mobile tablets and analyzed using Microsoft Excel 2011.\n\n\n**Key findings**\n\n\n**Baseline characteristics of population and sample**\n\n- At the time of the survey the population of UNHCR registered Syrian refugees numbered\n1,033,513 individuals in 247,736 households.\n\n- 44% of the selected 685 households did not respond to the survey. Among these, 5%\nrefused to participate in the study and the rest could not be reached.\n\n- 386 households with 2,206 residents were surveyed.\n\n- On average, each household had 5.7 members.\n\n- 52% of household members were female and 17% were under 5 years of age.\n\n\n**Knowledge about health care access and childhood vaccination**\n\n- 57% of respondents knew that refugees should pay between 3,000 and 5,000 LBP for\nconsultation at a primary health care centre (PHC) compared to 75% in 2015 and 54% in\n2014. A lower proportion (49%) knew that medication for acute illnesses is free at PHCs.\n\n- 74% knew that UNHCR financially supports hospital care for life saving treatment", "output": {"entities": {"named_data": [], "descriptive_data": ["cross sectional survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001194", "page": 1, "chunk": 0, "title": "At a glance: Health access and utilization survey among Syrian refugees in Lebanon - September 2016", "pdf_url": "https://reliefweb.int/attachments/b74c4281-ade1-370a-9479-43d0606faf2d/LebanonHAUS2016Final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "cross sectional survey", "label": "DESCRIPTIVE_DATA", "score": 0.8354686498641968, "start": 39, "end": 61, "probe_score": 0.4644, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "UNHCR IDP Data Report – May 2012\n\n\n**6.  PROTECTION CONCERNS REPORTED BY CONFLICT-INDUCED**\n**DISPLACED**\n\nThe key cause of displacement for conflict-induced IDPs has been the severity of their\nprotection concerns. These have included targeted threats, intimidation, and extortions, aerial\nattacks, forced recruitment, illegal taxation, night searches, and armed conflict among others.\nIDPs have also reported protection concerns during flight and in their places of displacement.\n\nMany IDPs continue to face threats to their physical security and well-being, including\nintimidation and persecution, which may lead to secondary displacement. In particular, male\nIDPs could face the additional risk of forced recruitment or being accused of association with\nparties to the conflict.\n\nThe protection risks facing women and children in displacement vary based on regional\ncharacteristics in each area in Afghanistan. However, the most relevant ones are, child\nrecruitment in armed force (Government and Anti-Government Elements), denial of access to\nbasic social services to single female headed households or unaccompanied women, risk of\nchild labor, economic constraints of a displaced family preventing the children from attending\nschool, threat of underage marriage/forced marriage to local power brokers. The groups\nespecially at risks among this population of women and children, are unaccompanied women,\nsingle female headed households and separated children.\n\nDue to the intensity of the conflict and often entrenched positions of the warring parties,\ndisplacement is becoming increasingly prolonged. Deterioration of the protection situation in\nplaces of displacement due to severe winters, absence of critical services in places of\ndisplacement, and the lack of livelihoods have rendered IDPs more vulnerable.\n\nThe existence of mines and other explosive remnants of war (ERWs) constitute a major threat\nto IDPs trying to settle in unfamiliar places. In areas of return, these similarly may restrict\naccess to shelter, water and land for grazing and cultivation, and it hampers the restoration of\nessential infrastructure. The", "output": {"entities": {"named_data": ["UNHCR IDP Data Report"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000682", "page": 14, "chunk": 0, "title": "Conflict-Induced Internally Displaced Persons in Afghanistan - Interpretation of Data as of 31 May 2012", "pdf_url": "https://reliefweb.int/attachments/64f811a5-8219-303d-bda5-3c3861e14a28/UNHCR%20IDP%20Report%202012.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR IDP Data Report", "label": "NAMED_DATA", "score": 0.7620286345481873, "start": 0, "end": 21, "probe_score": 0.9809, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a v\nManufacturIng 5 7 3.7 4 7 5 0 / s \\\\t oo  Services 475 272 190 201\n\nPrfvate consumpffon 90 7 81 9 938 95 1 20\nGeneral govemment consumption 7 0 9 6 146 17.2 =c ~GDFDl\nImpons of goods and servrcea 39 7 23 6 33 4 373 -3GW_G_____\n\n\n_(average_ _annual growth)_ 1981-9 1991401 2000 2001 Growth ot exports and Imports (%)\n\nAgrutumre -0 6 -2 6 2 2 3 8 oo\nIndustry 0.1 -41 51 5 6 s0\nManUnacturIng 6.9 . .\nServices -5 7 -5.4 4 0 51 \nPrivate oonsumpffon -2 0 -19 10 4 100 -50\nGeneral govemment consumption -5.1 -0 2 41.3 27 9 -100\nGross domestic Investment -06 3 0 50 - EOpois -tr-ports\nImports of goods and services -2 2 -151 85 0 61 3\n\n\nNote 2001 data are pretirrinary eastliates\n'The diamonds show four Key Indicators in the country (in bold) conipared with itS income-group average It data are missing, the diantond wiUt be rrconrrlte\n\n\n-56", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["2001 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012307", "page": 60, "chunk": 2, "title": "Ethiopia - Public Service Delivery Capacity Building Program (PSCAP) Project", "pdf_url": "https://documents.worldbank.org/curated/en/393481468771265415/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2001 data", "label": "VAGUE_DATA", "score": 0.7082152366638184, "start": 639, "end": 648, "probe_score": 0.0183, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " has ratified the 1951 Refugee Convention\nand the 1967 Protocol Relating to the Status of Refugees and nine international and regional human rights\ninstruments relevant to refugee protection. These are domesticated into Uganda’s legal system through\n\n\n14 Based on the Uganda Refugee Protection Assessment Update August 4-22, 2022.\n\n\nPage 11 of 81", "output": {"entities": {"named_data": ["Uganda Refugee Protection Assessment Update"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000001", "page": 16, "chunk": 2, "title": "Uganda - Climate Smart Agricultural Transformation Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099050012052240654/pdf/BOSIB05e6fc47e0770aeec00ad5e11774f2.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Uganda Refugee Protection Assessment Update", "label": "NAMED_DATA", "score": 0.9019412398338318, "start": 268, "end": 311, "probe_score": 0.9477, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "output": {"entities": {"named_data": [], "descriptive_data": ["random survey"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019700", "page": 16, "chunk": 0, "title": "Ethiopia - Seventh Education Project", "pdf_url": "https://documents.worldbank.org/curated/en/891861468030352478/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7714613080024719, "start": 379, "end": 395, "probe_score": 0.582, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "random survey", "label": "DESCRIPTIVE_DATA", "score": 0.7173007130622864, "start": 1487, "end": 1500, "probe_score": 0.012, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "its Public Expenditure\nTracking Survey (PETS)\n\nscorecard inproves each\nsemester\n\n\n\n**Project Components /** **Inputs:** **(budget for** each Project reports: (from Components to\nSub-components: component) Outputs)\n\n\n\n1. Community Driven - US$ 28.0 million (IDA $25.0 <sup>- M&E data</sup> - Cormnunities emnpowered\n\n\n\n**Program** (CDP) million) - Quarterly progress reports; and responsible for\nimplementing sub-projects;\n\n                                                  - Implemnenting partners <sup>are</sup>\ncomnpetent to support\n**2.** Pilot and Special\n\n\n\n**Programs in** Newly cormmunities;\n\n                                                - Implementing partners\n**Accessible** **Areas**\n\n                - US$ 2.0 mnillion (ODA <sup>$1.75</sup> participate in capacity building\n\n\n\n**(a)** **Rural Public Works** million) activities;\n\n                - US$ 2.0 million (IDA <sup>$1.75</sup>                - Operations Manual and\n\n\n\n**(b)** **Shelter** Program **for** million) annexed Handbooks for Direct\n\nFinancing to Communities <sup>and</sup>\n**Vulnerable** **Groups**\n\n               - US$ 10.0 million (IDA <sup>$6.5</sup>                - NaCSA and IDA Public Works are thorough,\n\n\n\n3. **Project** **Manaeem2nt** <sup>**and**</sup> <sup>million)</sup> administrative data appropriate, and clear in\n\n\n\ndefining the and\n**In", "output": {"entities": {"named_data": ["Public Expenditure\nTracking Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011652", "page": 32, "chunk": 0, "title": "Uganda - Primary Education and Teacher Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/349991468110948689/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Public Expenditure\nTracking Survey", "label": "NAMED_DATA", "score": 0.8658173084259033, "start": 4, "end": 38, "probe_score": 0.357, "gold": "DATA_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEmergency Food Security Project (P178936)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPage 4 of 54", "output": {"entities": {"named_data": ["Emergency Food Security Project"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 8, "chunk": 0, "title": "Jordan - Emergency Food Security Project", "pdf_url": "http://documents.worldbank.org/curated/en/486071652556836130/pdf/Jordan-Emergency-Food-Security-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Emergency Food Security Project", "label": "NAMED_DATA", "score": 0.6013356447219849, "start": 19, "end": 50, "probe_score": 0.0147, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**2021/22 **<br>**By end FY**<br>**2022/23 **<br>**By end FY**<br>**2023/24 **<br>**Total **|<br>**Baseline **<br>**By end FY**<br>**2017/18 **<br>**By end FY**<br>**2018/19 **<br>**By end FY**<br>**2019/20 **<br>**By end FY**<br>**2020/21 **<br>**By end FY**<br>**2021/22 **<br>**By end FY**<br>**2022/23 **<br>**By end FY**<br>**2023/24 **<br>**Total **|<br>**Baseline **<br>**By end FY**<br>**2017/18 **<br>**By end FY**<br>**2018/19 **<br>**By end FY**<br>**2019/20 **<br>**By end FY**<br>**2020/21 **<br>**By end FY**<br>**2021/22 **<br>**By end FY**<br>**2022/23 **<br>**By end FY**<br>**2023/24 **<br>**Total **|\n|**Original values **|0.00|", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003649", "page": 50, "chunk": 4, "title": "Kenya - Program to Strengthen Governance for Enabling Service Delivery and Public Investment in Kenya (GESDeK)", "pdf_url": "https://documents.worldbank.org/curated/en/099071824152611352/pdf/BOSIB-263a3cc4-2216-417f-b962-c6972bf38da3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "post‐crisis period, possibly suggesting that young firms were forced to improve their\n\n\nlearning capabilities in order to operate in a more competitive environment. Yet this\n\nimprovement was not enough to compensate the worse sales growth performance of young\n\n\nenterprises after the crisis.\n\n\n**4 ­ Conclusions**\n\n\nIn this paper we examined the effects of the global downturn on innovative firms\n\n\nand on young firms in order to understand the growth prospects of Eastern European\n\n\ncountries using a unique panel data for 1,686 firms in six countries (Bulgaria, Hungary,\n\nLatvia, Lithuania, Romania, and Turkey) covering manufacturing, retail and other service\n\n\nsectors. Two empirical methods were used. First, we applied a panel‐data analysis in order\n\n\nto assess the difference of sales growth performance between innovative and non‐\n\ninnovative firms, and between young and older firms, over the pre and post‐crisis periods,\n\n\nwhen controlling for certain firm characteristics. Second, we used the Juhn ‐Murphy‐Pierce\n\n\ntechnique to decompose the difference in sales growth performance between innovative\n\n\n(young) non‐innovative (older) companies, over time, into three effects: characteristics\n\neffect; returns effect and unexplained effect.\n\n\nThe results show that innovative firms have suffered more than non‐innovative\n\n\ncompanies, regardless the estimator applied (population‐averaged estimator or FGLS), and\n\nthe criteria used to categorize innovation (introduction of a product or a process or\n\n\ndevelopment of R&D activities). We also showed that the decrease of sales growth rate of\n\n\nyounger firms was more severe than of older companies.\n\n\nWhen comparing innovative and non‐innovative companies, the decomposition\n\n\ntechnique showed three main outcomes. First, the positive difference in sales growth\n\n\nperformance in favor of innovative companies has been reversed after the crisis. Second,\n\n\nwhile before the crisis that positive gap in favor of innovative companies was due to their\n\nbetter characteristics, especially regarding size, and, mainly, to higher returns obtained by\n\n\ninnovative firms, after the crisis the gap reversion was due mostly", "output": {"entities": {"named_data": [], "descriptive_data": ["panel data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004469", "page": 20, "chunk": 0, "title": "wps5278", "pdf_url": "https://local/prwp/wps5278.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "panel data", "label": "DESCRIPTIVE_DATA", "score": 0.6246890425682068, "start": 509, "end": 519, "probe_score": 0.6948, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Policy Research Working Paper 9255\n\n##### **Abstract**\n\nAlthough household well-being is anchored in long-term\n\naverage rates of consumption, welfare comparisons typically rely on shorter-duration survey measurements. This\npaper develops a new strategy to identify the distribution\nof these long-term rates by leveraging a large-scale randomization that elicited repeated short-duration measurements\nfrom diaries and recall questions. Identification stems from\ndiary-recall differences in reports from the same household,\n\n\n\ndoes not require these reports to be error-free, and hinges\non a research design with broad replicability. This strategy delivers cost-effective suggestions for designing survey\nmodules to yield the most accurate measurements of\nconsumption well-being, and offers new insights for interpreting and reconciling diary-recall differences in household\nexpenditure surveys.\n\n\n\nThis paper is a product of the Poverty and Equity Global Practice. It is part of a larger effort by the World Bank to\n\nprovide open access to its research and make a contribution to development policy discussions around the world. Policy\nResearch Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted\nat nkrishnan@worldbank.org.\n\n\n_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development_\n_issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the_\n_names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those_\n_of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and_\n_its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._\n\n\nProduced by the Research Support Team", "output": {"entities": {"named_data": [], "descriptive_data": ["household\nexpenditure surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002239", "page": 1, "chunk": 0, "title": "the insights and illusions of consumption measurements", "pdf_url": "https://local/prwp/the-insights-and-illusions-of-consumption-measurements.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household\nexpenditure surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8772545456886292, "start": 863, "end": 892, "probe_score": 0.6222, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "UNHCR MID-YEAR POST DISTRIBUTION MONITORING REPORT - 2024\n\n#### **List of Acronyms**\n\n**CBI** Cash-based Interventions\n**CFM** Complaints and Feedback Mechanisms\n**EGP** Egyptian Pound\n**FSP** Financial Service Provider\n**MPCA** Multi-purpose Cash Assistance\n**PDM** Post-Distribution Monitoring\n**rCSI** Reduced Coping Strategy Index\n**SMS** Short Message Service\n**WFP** World Food Programme\n**UNHCR** United Nations High Commissioner for Refugees\n**USD** United States Dollar\n\n\n6", "output": {"entities": {"named_data": ["UNHCR MID-YEAR POST DISTRIBUTION MONITORING REPORT"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000992", "page": 5, "chunk": 0, "title": "Mid-Year Post-Distribution Monitoring Report of UNHCR’s Multi-Purpose Cash Assistance to Refugees in Egypt, September 2024", "pdf_url": "https://reliefweb.int/attachments/9543af9b-5171-46cd-a644-232432ee2f4b/MPCA%20PDM-Mid%20Year%202024-Final%20Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR MID-YEAR POST DISTRIBUTION MONITORING REPORT", "label": "NAMED_DATA", "score": 0.6705383658409119, "start": 0, "end": 50, "probe_score": 0.8842, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " argues that the\nrole of an endogenous growth framework is not to generate testable predictions, but\nrather to guide the process of data analysis.\n\n\n**_The Jones Critique_**\n\n\nA second criticism, especially relevant for the present study, is the seminal\ncontribution of Jones (1995). Testing endogenous growth models in the context of\ntime series implies establishing a relationship between a variable that is usually\nstationary? without drift? such as income growth, and a variable which is usually\nnon-stationary, such as years of schooling. In other words, his results fundamentally\ncall into question the implicit prediction of many endogenous growth models\nsuggesting output growth should exhibit large permanent increases. Time series data\nover a very long time period for the United States and other OECD countries reveal\nthat the growth rates of GDP per capita in these countries exhibit little persistent\nchanges, and can be characterized by more or less constant mean.\n\n\nThis observation imposes a testable prediction. According to endogenous growth\nmodels permanent changes in certain policy variables, such as schooling, or the\nnumber of scientists and engineers engaged in research and development, should have\n\n\n-10", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Time series data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002824", "page": 14, "chunk": 1, "title": "wps3610", "pdf_url": "https://local/prwp/wps3610.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Time series data", "label": "VAGUE_DATA", "score": 0.6985519528388977, "start": 729, "end": 745, "probe_score": 0.5611, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and earnings of refugee immigrants.\nEmpirical Economics, 52(1), 31-58.\n\n\nGradzewicz, M., Jabłonowski, J., Sasiela, M., Żółkiewski, Z. (2021). Structural model\nof the Polish economy – MOST_PL. Real Economy Analysis Team, Economic\nAnalysis Department, NBP.\n\n\nGromadzki, J., & Lewandowski, P. (2023). Refugees from Ukraine on the Polish\nlabour market. Social Insurance. Theory and Practice, 155(4), 29-40.\n\n\nKancs, D. A., & Lecca, P. (2018). Long‐term social, economic and fiscal effects of\nimmigration into the EU: The role of the integration policy. The World Economy,\n41(10), 2599-2630.\n\n\nKollman S. (2023) Ukrainian refugees: Nearly half intend to stay in Germany\nin the longer term, <u>[https://www.diw.de/en/diw_01.c.877322.en/ukrainian_](https://www.diw.de/en/diw_01.c.877322.en/ukrainian_refugees__nearly_half_intend_to_stay_in_germany_in_the_longer_term.html)</u>\n<u>[refugees__nearly_half_intend_to_stay_in_germany_in_the_longer_term.html,](https://www.diw.de/en/diw_01.c.877322.en/ukrainian_refugees__nearly_half_intend_to_stay_in_germany_in_the_longer_term.html)</", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 22, "chunk": 7, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["M&E data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008010", "page": 29, "chunk": 2, "title": "Ethiopia - National Fertilizer Sector Project - Supplemental Credit", "pdf_url": "https://documents.worldbank.org/curated/en/107581468751538047/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "M&E data", "label": "VAGUE_DATA", "score": 0.5883201956748962, "start": 530, "end": 538, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "11\n\n\nare not in the public domain. A further consideration is the county’s fiscal position. In China, it is\n\n\nthe central government that borrows from the World Bank. Beijing then on-lends to provinces,\n\n\ncharging a fee in the process, and the province then on-lends to the county, again charging a fee\n\n\nfor its services. Counties with very limited resources will not be able to repay the provincial\n\n\ngovernment, and are therefore less likely _ceteris paribus_ to end up with a World Bank project in\n\n\nhealth or any other sector. The final consideration is the county’s capacity to implement the\n\n\nproject, with counties with high capacity being preferred. This increases the likelihood of the\n\n\nproject achieving its objectives, but seems likely to tilt the scales against poorer counties.\n\n\nTable 5 reports the results of two county-level probit regressions (data refer to 2000). The\n\n\nsecond is included because the very high correlation among the covariates makes it hard to detect\n\n\ntheir independent effects—basically, per capita income is either a cause or consequence of most\n\n\nof the indicators. The results confirm that, within poverty counties, richer counties have a higher\n\n\nprobability of being a Health VIII county, and suggest strongly that counties with more health\n\n\nsector capacity, as proxied by the number of hospital beds, also have a higher probability of\n\n\nbeing selected for inclusion. Health VIII is clearly not reaching the poorest of the poor. From the\n\n\nprobit equation, a propensity score is computed for each county, using the full model rather than\n\n\nthe more parsimonious model.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data refer to 2000"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002957", "page": 11, "chunk": 0, "title": "wps3743", "pdf_url": "https://local/prwp/wps3743.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data refer to 2000", "label": "VAGUE_DATA", "score": 0.6178385615348816, "start": 863, "end": 881, "probe_score": 0.0153, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "output": {"entities": {"named_data": [], "descriptive_data": ["household expenditure survey data", "data from the Household Survey"], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000147", "page": 38, "chunk": 1, "title": "Rwanda - Human Resources Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/837731468759911848/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household expenditure survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8699104189872742, "start": 565, "end": 598, "probe_score": 0.7323, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.5808603167533875, "start": 870, "end": 881, "probe_score": 0.1461, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from the Household Survey", "label": "DESCRIPTIVE_DATA", "score": 0.5346028804779053, "start": 1978, "end": 2008, "probe_score": 0.1121, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Procurement Documents:** The World Bank’s Standard Procurement Documents (SPDs) shall be used for\nprocurement of goods, works, and non-consulting services under Open International Competitive Procedures. National\nBidding documents as set forth in the Public Procurement and Disposal Act, 2003 may be used under Open National\ncompetitive as well as for the Request for Quotation method subject to the inclusion of the universal eligibility and ES\nprovisions. Selection of consultant firms shall use the World Bank’s SPDs, in line with procedures described in the\nProcurement Regulations.\n\n\n37. In accordance with paragraph 5.3 of the Procurement Regulations, the request for bids/request for proposals\ndocument shall require that Bidders/Proposers submitting Bids/Proposals to present a signed acceptance at the time of\nbidding, to be incorporated in any resulting contracts, confirming application of, and compliance with, the World Bank’s\nAnti-Corruption Guidelines, including without limitation the World Bank’s right to sanction and the World Bank’s\ninspection and audit rights.\n\n\n38. **Record keeping and management.** All records pertaining to award of tenders, including bid notification, register\npertaining to sale and receipt of bids, bid opening minutes, bid evaluation reports and all correspondence pertaining to\nbid evaluation, communication sent to/with the World Bank in the process, bid securities, and approval of\ninvitation/evaluation of bids will be retained by the respective agencies in electronic or hard copy and uploaded in STEP.\n\n\n40 (a) open advertising of the procurement opportunity at the national level; (b) the procurement is open to eligible firms from any country; (c) the\nrequest for bids/request for proposals document shall require that Bidders/Proposers submitting Bids/Proposals present a signed acceptance at the\ntime of bidding, to be incorporated in any resulting contracts, confirming application of, and compliance with, the World Bank’s Anti-Corruption\nGuidelines,", "output": {"entities": {"named_data": [], "descriptive_data": ["register\npertaining to sale and receipt of bids"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 70, "chunk": 1, "title": "Uganda - Generating Growth Opportunities and Productivity for Women Enterprises Uganda Project", "pdf_url": "http://documents.worldbank.org/curated/en/527091655323259747/pdf/Uganda-Generating-Growth-Opportunities-and-Productivity-for-Women-Enterprises-Uganda-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "register\npertaining to sale and receipt of bids", "label": "DESCRIPTIVE_DATA", "score": 0.544321596622467, "start": 1196, "end": 1243, "probe_score": 0.023, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " survey by NITA-U referenced in the Diagnostic study n°5.1 to 5.3 to support the mid-term review of Uganda’s\n2nd National Development Plan (NDP-2) and evaluation of NDP-1 in Uganda, March 2019.\n45 NITA-U National ICT Survey Report, 2018.\n\n\nJul 22, 2019 Page 6 of 28", "output": {"entities": {"named_data": ["NITA-U National ICT Survey Report"], "descriptive_data": ["survey by NITA-U"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000063", "page": 5, "chunk": 3, "title": "Concept Project Information Document (PID) - Uganda Digital Acceleration Program - P171305", "pdf_url": "http://documents.worldbank.org/curated/en/948351570727493669/pdf/Concept-Project-Information-Document-PID-Uganda-Digital-Acceleration-Program-P171305.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey by NITA-U", "label": "DESCRIPTIVE_DATA", "score": 0.5884627103805542, "start": 1, "end": 17, "probe_score": 0.3429, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "NITA-U National ICT Survey Report", "label": "NAMED_DATA", "score": 0.6411902904510498, "start": 197, "end": 230, "probe_score": 1.0, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Venezuelans in Chile, Colombia, Ecuador and\nPeru – A Development Opportunity\n\n\n\n6 Labor Market Outcomes for Venezuelan\nMigrants and Hosts\n\n\n41\n\n\n\n**Figure 6.5 Monthly wages of hosts and Venezuelans in Colombia and Peru, by education**\n**level**\n\n\nMonthly wages (US dollars, 2017 PPP)\n\n\n\n0 200 400 600 800 1,000\n\n\n**Colombia**\n\n\nHosts\n\n\n\n1,200\n\n\nTertiary\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nVenezuelans\n\n\nHosts\n\n\nVenezuelans\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nTertiary\n\n\n**Peru**\n\n\nTertiary\n\n\n\nTertiary\n\n\n\n\n\n\n\n\n\nSources: Colombia: Pulso de la Migración (DANE 2022) and Gran Encuesta Integrada de Hogares (DANE 2021). Peru: Encuesta dirigida a la población venezolana\nque reside en el país (INEI 2022) and Encuesta Nacional de Hogares (INEI 2021).\n\n\nNote: Wages are measured in US dollars (PPP 2017) and censored at 2000 dollars.", "output": {"entities": {"named_data": ["Pulso de la Migración", "Gran Encuesta Integrada de Hogares", "Encuesta dirigida a la población venezolana\nque reside en el país", "Encuesta Nacional de Hogares"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001190", "page": 40, "chunk": 0, "title": "Venezuelans in Chile, Colombia, Ecuador and Peru: A Development Opportunity", "pdf_url": "https://reliefweb.int/attachments/b6b504c8-f3b2-4e0d-a2e0-3955b4beb78c/P17578013f69d804019f8516ffbb072fc34.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Pulso de la Migración", "label": "NAMED_DATA", "score": 0.9068702459335327, "start": 497, "end": 518, "probe_score": 0.9965, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Gran Encuesta Integrada de Hogares", "label": "NAMED_DATA", "score": 0.8930754661560059, "start": 535, "end": 569, "probe_score": 0.9994, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Encuesta dirigida a la población venezolana\nque reside en el país", "label": "NAMED_DATA", "score": 0.5771263837814331, "start": 589, "end": 654, "probe_score": 0.9999, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Encuesta Nacional de Hogares", "label": "NAMED_DATA", "score": 0.9008298516273499, "start": 671, "end": 699, "probe_score": 0.9983, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda Secondary Education Expansion Project (P166570)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Enrolment at lower secondary education<br>for refugees|The project will finance<br>construction of about<br>15,000 new places in lower<br>secondary schools in the<br>refugee hosting areas. The<br>target is set based on the<br>assumption that the current<br>proportion in enrollment<br>between refugees and hosts<br>is maintained (33% to 67%).<br>However, the overall<br>enrolment will depend on<br>the refuges influx and<br>internal migration during<br>the project life, which is<br>beyond the project control.<br>Enrolment in private and<br>public schools is counted as<br>reliable disagregated<br>baseline data is not<br>available.<br>AEP enrolment is not<br>included and measured<br>under a dedicated indicator.|Midterm and<br>end of<br>project|EMIS|Enrollment data by<br>refugee settlement and<br>hosting communities.|MOES|\n|---|---|---|---|---|---|\n|Enrolment at lower secondary education<br>for host communities|<br>The project will finance<br>construction of about<br>15,000 new places in lower<br>secondary schools in the<br>refugee hosting areas. The<br>target is set based on the<br>assumption that the current<br>proportion in enrollment|Data will be<br>reported at<br>midterm and<br>end of<br>project.<br>|Baseline", "output": {"entities": {"named_data": [], "descriptive_data": ["Enrollment data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000060", "page": 57, "chunk": 0, "title": "Uganda - Secondary Education Expansion Project", "pdf_url": "http://documents1.worldbank.org/curated/en/406361595815248191/pdf/Uganda-Secondary-Education-Expansion-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Enrollment data", "label": "DESCRIPTIVE_DATA", "score": 0.6920242309570312, "start": 842, "end": 857, "probe_score": 0.2298, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "# **ANALYSE CONJOINTE** **LOGONE-BIRNI**\n\n#### Juillet 2022 Analyse mise à jour en décembre 2022\n\n1", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000568", "page": 0, "chunk": 0, "title": "Analyse conjointe Logone-Birn, juillet 2022 (Analyse mise à jour en décembre 2022)", "pdf_url": "https://reliefweb.int/attachments/54321629-d14b-474b-88a4-ff4d8a35233b/analyse_conjointe_logone-birni_-_hdp_nexus.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_Sierra Leone_\n\n\nPRICES and GOVERNMENT FINANCE\n\n1981 1991 2000 2001 Inflation (%)\n_Domest)c_ _pHces_\n_(% change)_ c 1\nConsumer prices 16 7 102 7 -0.9 3 0 30 _< _\nImplicit GDP deflator 8 7 128 8 6 2 6 1 20\n\n_Govemment finance_ _10_\n_(% of GDP,_ _includes curent_ grants) 0\nCurrentrevenue .. 112 182 178 .10. 98 97 93 99 00 01\nCurrent budget balance .. -5 8 -4.5 -7 1 - GDP deflator _ CPI\nOverall surplus/deficit -10 4 -10.6 -12 3\n\n\nTRADE\n\n1981 1991 2000 2001 Export and Import levels (USS mnIll.)\n_(US$ millions)_\nTotal exports (fob) 147 176 75 78 400\nRutile . 72\nDiamonds (recorded) 32 10 21 300\nManufactures\nTotal imports (cHf) 317 158 161 303 20\nFood . 53 66 72 100\nFuel and energy 26 29 3d _ _8_\nCaptal goods .. 38 18 22  - __\n96 D6 97 9o 99 00 01\nExport price index _(1995=100)_ 90 86 87\nImport price Index (1995=100) 93 93 92 mExports ***Mrrports**\nTerms of trade (1995-100) 97 93 94\n\n\n\nBALANCE of PAYMENTS\n\n\n\n1981 1991 2000 2001 Curmnt account balance to GDP _(%)_\n_(US$_ _millions)_\nExports of goods and services 163 244 110 116 0\nImports of goods and services 349 226 212 252\nResource balance -186 18 -102 -137 .a*\n\n\n\nExports of goods and services 163 244 110 116 0\nImports of goods and services 349 226 212 252\nResource balance -186 18 -102 -137 .a*\n\nNet income -28 -60 -18 -20\nNet current", "output": {"entities": {"named_data": [], "descriptive_data": ["Export price index", "Import price Index"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010464", "page": 61, "chunk": 0, "title": "Ethiopia - Ethiopian Social Rehabilitation and Development Fund Project", "pdf_url": "https://documents.worldbank.org/curated/en/268241468023106890/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Export price index", "label": "DESCRIPTIVE_DATA", "score": 0.6043785214424133, "start": 751, "end": 769, "probe_score": 0.209, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Import price Index", "label": "DESCRIPTIVE_DATA", "score": 0.5586132407188416, "start": 792, "end": 810, "probe_score": 0.8072, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Uganda** **Electricity Transmission** **Company** **Limited** **ES-45**\n\nBujagali Interconnection Project\nSocial and Environmental Assessment   - Executive Summary\nDecember, 2006\n\n\n**Project** **Issue** **Summary** **of** **Mitigation and** **Net** **Effects**\n\nEffects on Managed The permanent loss of about 60 ha of forested land will reduce the available\nand Protected Areas habitat for vegetation and wildlife. To reduce effects of the wayleave within\n\nForest Reserves this has been limited to 35 m, versus 40 m in non-forest\nreserve areas. UETCL has estimated the Total Economic Value of lost forest\nresource, and will allocate at least equivalent monies to support initiatives by\nNFA, e.g. enhancement planting, which will compensate for loss of forest\nresource and associated benefit stream.\n\n\nAfter construction, ecological surveys will be undertaken by UETCL to\nmonitor post construction effects.\n\n\n\nThe resulting cleared corridor may pose a barrier to movement of \"forest\n\n\n\ninterior\" wildlife species between the forested areas north and south of the\nroute. The 220 kV line through the Mabira Forest Reserve has been routed\n\n\n\nimmediately adjacent to the existing 132 kV line to minimise fragmentation\neffects. Cross line vegetative corridors between the north and south forested\nareas will be established by minimising clearing and selective planting of\n\n\n\nsuitable vegetation at select valley locations.\n\n\n\nImprovements to access required for construction may have potential to\nincrease grazing, bushmeat hunting and illegal felling of timber. However,\naccess has been improved in recent years, by UETCL upgrading the existing\nright-of-way through Mabira Forest, including associated bridges and\nculverts. This has not resulted in significant encroachment. As no significant\n\nfurther upgrades are foreseen, no specific mitigations are necessary.\nTourism and Presence of the line reduces aesthetic values for ecotourism and recreation in\nAesthetics managed and protected areas.", "output": {"entities": {"named_data": [], "descriptive_data": ["ecological surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009890", "page": 53, "chunk": 0, "title": "Uganda - Private Power Generation Project : resettlement action plan (Vol. 1 of 9) : Resettlement action plan for UETCL Bujagali Interconnector : executive summary", "pdf_url": "https://documents.worldbank.org/curated/en/229961468318584035/pdf/RP492010vol-01.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "ecological surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8884432911872864, "start": 823, "end": 841, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**6. Results**\n\n\nSince 2014, the work of the SGFPN has resulted in greatly improved gender mainstreaming in the work of\nUN agencies and civil society organizations providing humanitarian assistance in Jordan. This was achieved\nin part by building awareness of the different needs, levels of access and participation of diverse women,\nmen, girls, and boys within Jordanian refugee programming.\n\n\nConcrete results include:\n\n\n- Gender focal points have benefited from increased authority in the sector meetings, especially if they are\nskilful in leading and coordinating gender mainstreaming and programming targeting women and girls\nwithin their sector.\n\n\n- All sectors are currently conducting gender analyses, with the education and health sectors having\ncompleted the process ( _see_ More information below).\n\n\n- Greater knowledge and skills on gender equality among humanitarian staff due to training initiatives.\n\n\n- Piloting of various IASC gender equality tools, contributing to the finalization of the _IASC Gender and Age_\n_Marker_ and a monitoring tool for the _Gender Empowerment Measures_ .\n\n\n- Improved gender equality mainstreaming in refugee response programme design, through support for\nthe correct usage of the _<u>[IASC Gender Marker](https://www.humanitarianresponse.info/en/topics/gender/page/iasc-gender-marker)</u>_ in Jordan Humanitarian Funds proposals.\n\n\n- Development and implementation of impact indicators related to participation and gender equality\nwithin the protection and education sectors.\n\n\n- Increased documentation and analysis of sex and age-disaggregated data (SADD) in assessment,\nmonitoring and evaluation, which has led to practical changes in programming.\n\n\nFor instance, as a result of monitoring and evaluation of SADD, the reasons behind the low participation of\ngirls in camp child- and youth-friendly spaces, youth committees and volunteering committees have been\nre-examined. Protection actors have drawn on the findings to improve programming and take measures to\naddress the barriers that prevent girls from", "output": {"entities": {"named_data": [], "descriptive_data": ["sex and age-disaggregated data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000401", "page": 18, "chunk": 0, "title": "Gender Equality Promising Practices: Syrian Refugees in the Middle East and North Africa", "pdf_url": "https://reliefweb.int/attachments/358b2f21-b525-3836-bbf7-0ca59d4614c1/UNHCR_Gender%20Equality%20Promising%20Practices_Syrian%20Refugees%20in%20MENA_2017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "sex and age-disaggregated data", "label": "DESCRIPTIVE_DATA", "score": 0.8204202055931091, "start": 1567, "end": 1597, "probe_score": 0.926, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "................................................................................................. 4\n\n**RESUME EXECUTIF** ............................................................................................ **Erreur ! Signet non défini.**\n\n**I.** **INTRODUCTION ET CONTEXTE** ............................................................................................................... 8\n\n**II.** **OBJECTIF DE L’ETUDE** ........................", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000003", "page": 1, "chunk": 1, "title": "Evaluation approfondie du programme d’assistance aux refugies Tchadiens de Langui (Nord) et Centrafricains dans les regions de l’Est et de l’Adamaoua du Cameroun, Rapport final - mai 2012", "pdf_url": "http://documents.wfp.org/stellent/groups/public/documents/ena/wfp251553.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**B.** **Sectoral and Institutional Context**\n\n\n4. **The pre‐tertiary education system in Jordan is organized in three levels** : (1) early childhood\neducation (ECE) or preprimary—kindergarten (KG) 1 and 2; (2) compulsory basic education,\ncomprising primary and lower secondary levels (grades 1–10); and (3) upper secondary education\ncomprising both academic and vocational streams (grades 11 and 12). The pre‐tertiary education\nsystem is managed by the Ministry of Education (MOE), while the Ministry of Higher Education and\nScientific Research (MOHESR) manages tertiary institutions (universities and vocational colleges).\n\n\n5. **Over the last two decades, Jordan has made efforts to improve access to education for boys**\n**and girls**, and to increase the efficiency of its education system. The country has spent many years\npursuing reforms toward a knowledge economy. Through multi‐donor development programs such\nas the Education Reform for Knowledge Economy (ERfKE), Jordan made impressive strides in terms of\nschool access and attainment and enrollment rates. Under the first phase of ERfKE, the primary gross\nenrollment ratio increased from 71 percent in 1994 to 99 percent in 2010 (98 percent for girls and 99\npercent for boys), and the transition rate to secondary school increased from 63 percent to 98 percent\nover the same period (98 percent for both girls and boys). <sup>6</sup> [^6: World Bank EdStats data base—illiteracy rates, primary gross enrollment ratio, and transition rate to secondary\nschool.] The transition rate between grades is\nrelatively stable above 96 percent from grades 1–8; however, in grade 9, there is a marked drop down\nto 90 percent and a corresponding surge in dropout up to 7 percent. Repetition peaks at 3 percent in\ngrade 10, but it is comparatively lower than in many other Middle East and North Africa (MENA", "output": {"entities": {"named_data": ["World Bank EdStats data base"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000041", "page": 9, "chunk": 0, "title": "Jordan - Education Reform Support Program-for-Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/731311512702123714/pdf/Jordan-Educ-Reform-121282-JO-PAD-11142017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Bank EdStats data base", "label": "NAMED_DATA", "score": 0.9011772274971008, "start": 1401, "end": 1429, "probe_score": 0.9965, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "persistence of macroeconomic aggregates, measured by the first order autocorrelation. To\ncompute statistics, all variables, except GDP ratios, are expressed in per capita terms and\nlogged and then, all are filtered using the Hodrick-Prescott filter with the smoothing\nparameter set at 100, the value commonly used for annual data. Statistics for the\nsimulated economies are the means of statistics computed for each of 200 replications.\nEach simulation is 228 periods long and the first 200 observations are dropped so that the\nresults do not depend on initial conditions. Second moments are computed using the\nremaining 28 observations - equal to the average sample size of 28 yearly periods of the\ndatabase used to compute Latin America’s business cycle facts.\n\nIn general, the benchmark model economy matches the core of business cycle frequency\nproperties for the typical LAC economy. The ability of the benchmark model economy to\nmimic key qualitative aspects related to persistence and comovements in actual cyclical\nbehavior is remarkable. The model correctly predicts that disposable income,\nconsumption and investment are strongly procyclical while the trade balance to output\nratio as well as the government debt to output ratio behave countercyclically. Even from\na quantitative point of view, the model is quite successful in replicating some of these\ncyclical correlations. The model also accounts for the strong persistence observed in most\nmacroeconomic aggregates.\n\nThe model matches the relative volatility of disposable income but does not quite succeed\nin reproducing the volatility of consumption and tax revenue. <sup>10</sup> [^10: The capital adjustment cost parameter ψ kx is calibrated so as to match the volatility of investment\ngenerated by the model to that of aggregate investment in the data.] However, the inability to\nmimic these features cannot be considered a major failure of the model. The volatility of\nconsumption is overestimated in the data because it includes durable goods consumption\nwhich tends to behave more like investment and, therefore, to exhibit much higher\nvolatility. Tax revenue volatility is understated because the model does not allow for tax\ndisturbances. WoldeMariam and Stotsky (2002) report", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["annual data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003451", "page": 22, "chunk": 0, "title": "wps4244", "pdf_url": "https://local/prwp/wps4244.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "annual data", "label": "VAGUE_DATA", "score": 0.6821959018707275, "start": 318, "end": 329, "probe_score": 0.8834, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad Energy Access Scale Up Project (P174495)\n\n\n\n|New electricity connections<br>(predominantly energized by solar PV and<br>battery storage) in 12 secondary cities|Col2|Quarterly|Reports of<br>SNE, progres<br>s reports of<br>PIU|Data provided by SNE<br>operational units and<br>Owner's Engineer|PIU of SNE|\n|---|---|---|---|---|---|\n|Electricity connections (predominantly<br>energized by solar PV and battery storage)<br>in new cities and towns, out of which|<br>|Quarterly<br>|<br>Progress<br>reports of<br>the PIU of<br>the Ministry<br>of Petroleum<br>and Energy<br> <br>|Data will be collected<br>by M&E specialists of<br>the PIU of Ministry of<br>Petroleum and Energy<br>from progress reports<br>made by private<br>operators and checked<br>through site visits.<br>|PIU of the Ministry of<br>Petroleum and Energy<br>|\n|In cities housing host communities||Quarterly<br>|Reports of<br>SNE, progres<br>s reports of<br>PIU<br> <br>|<br>Data provided by SNE<br>operational units and<br>Owner's Engineer<br>|PIU of SNE<br>|\n|Female-headed households electrified<br>under subcomponents 1.1 - 1.3||Quarterly<br>|<", "output": {"entities": {"named_data": [], "descriptive_data": ["Data provided by SNE", "Data provided by SNE"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000193", "page": 59, "chunk": 0, "title": "Chad - Energy Access Scale Up Project", "pdf_url": "https://documents1.worldbank.org/curated/en/860701648216750651/pdf/IBArchive-bd2c789e-ee04-4df7-a219-9409a5f705d3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data provided by SNE", "label": "DESCRIPTIVE_DATA", "score": 0.5984500050544739, "start": 249, "end": 269, "probe_score": 0.276, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Data provided by SNE", "label": "DESCRIPTIVE_DATA", "score": 0.5929863452911377, "start": 956, "end": 976, "probe_score": 0.0037, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Figure 4.4: Responses to 1 pp identified inflation shocks (short vs long maturity)**\n\n\n**A.** **Residuals from Philips curve (Identification1, annual data)**\n\n\n**B.** **Residuals from Philips curve (Identification1, quarterly data)**\n\n\n18", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["annual data", "quarterly data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001703", "page": 19, "chunk": 0, "title": "inflation and public debt reversals in advanced economies", "pdf_url": "https://local/prwp/inflation-and-public-debt-reversals-in-advanced-economies.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "annual data", "label": "VAGUE_DATA", "score": 0.6575381755828857, "start": 145, "end": 156, "probe_score": 0.4246, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "quarterly data", "label": "VAGUE_DATA", "score": 0.5560264587402344, "start": 218, "end": 232, "probe_score": 0.4035, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "a, herbal hibiscus, Jatropha carcus\nand these could be inventoried and sustainably exploited for purposes of alternative livelihoods\nand diversification.\n\n\nProposed BMP and BMTs for NMR issues:\n- A rapid appraisal of environmental status and monitoring of trends in land resource\nmanagement;\n- Development of a checklist of key biodiversity loss, medicinal plants and other flora and\nfauna;\n- Appropriate grazing and livestock production systems (e.g. reseeding of grazing lands and destocking) to reduce the negative effects of livestock on soil erosion and compaction and the\ndisruption of hydrological flows;\n- Alternative livelihoods such as apiculture, Jojopa, herbal hibiscus, honey, hides and skins etc.\nto reduce pressures on pasture land;\n- Land resources inventory;\n- Introduction herbaceous vegetation to cover the soil during the dry seasons in order to reduce\nsoil erosion and the siltation of waterways.\n\n\nc) Taita Hills Catchment: Taita hills are situated in Taita Taveta District, Coast Province. The\nTaita hills are important rain catchment areas, feeding rivers that flow down to the dry lowlands.\nThe catchment areas are threatened as agricultural land expands through encroachment of the\nnew areas and clearing the natural vegetation. Though there is a highland-lowland\ninterrelationship, less water is flowing to the lowlands because of the negative impacts of these", "output": {"entities": {"named_data": [], "descriptive_data": ["Land resources inventory"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018577", "page": 5, "chunk": 1, "title": "Uganda - Second Energy for Rural Transformation Adaptable Program Loan Project", "pdf_url": "https://documents.worldbank.org/curated/en/813681468121509840/pdf/Integrated0Saf10Concept0Stage01GEF1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Land resources inventory", "label": "DESCRIPTIVE_DATA", "score": 0.8654937148094177, "start": 750, "end": 774, "probe_score": 0.0684, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " was prepared and\ndiscussed during the ISM, and a detailed assessment and budget forecast is being prepared for each new city.\n\n2. Component 2 has continued to progress, and has reached a total of 10,724 clients by November, 2017. The training provision pace is expected to\nincrease with the recapitalization of the line of credit, the expansion to new cities, and through extensive local level promotion and engagement of\nprivate training providers. The target for the next 6 months is to provide training for 2000 clients and start a new business development services product\nthat will reach 125 clients. Quality assurance of WEDP training is a key focus of activities under Component 2. The training taskforce has monthly\n\n\n11/30/2017 Page 2 of 10\n\nPublic Disclosure Copy", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015102", "page": 1, "chunk": 3, "title": "Disclosable Version of the ISR - Ethiopia Women Entrepreneurship Development Project - P122764 - Sequence No : 11", "pdf_url": "https://documents.worldbank.org/curated/en/581081512056699883/pdf/Disclosable-Version-of-the-ISR-Ethiopia-Women-Entrepreneurship-Development-Project-P122764-Sequence-No-11.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "up> Although labor inspectors have an important role to play in enforcing\nworker rights.\n\n\n28 The unemployment rate was 13 percent in 2015, 13 percent in 2010, 15 percent in 2005 and 14 percent in\n2000. There are approximately 210,000 unemployed Jordanians in 2015. See Employment Unemployment\nSurvey for 2015. Available online at: http://www.dos.gov.jo/dos_home_e/main/linked-html/Emp&Un.htm\n29 In 2015, unemployment rates were 23 percent among women versus 11 percent among men; 19 percent\namong those with a bachelor degree or higher versus 11 percent among those with less than secondary\neducation; and 15 percent among 20–24 year olds, 26 percent among 25–29 years, and 14 percent among 40–54\nyear olds. Employment Unemployment Survey for 2015. Available online at:\n<u>http://www.dos.gov.jo/dos_home_e/main/linked-html/Emp&Un.htm. The largest share of unemployed</u>\nJordanians live in Amman (32 percent of the total), followed by Irbid (22 percent), Zarqa (14 percent), Mafraq\n(6 percent), and Balqa (6 percent). The remaining seven governorates are home to the remaining 21 percent of\nunemployed Jordanians.\n30 In 2015, the MOL issued 324,000 annual work permits, the majority of which were issued to Egyptians (65.3\npercent), with 3 percent to other Arabs and 26 percent to others. According to the new census, there are about\n636,000 Egyptians and 200,000 non-Arabs in Jordan. It is not clear how many of these are working informally.\n31 Economic migrants are subject to a minimum wage, which is lower than the minimum wage for Jordanian\nworkers. The separate minimum wage makes non-Jordanian", "output": {"entities": {"named_data": ["Employment Unemployment\nSurvey"], "descriptive_data": ["new census"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 68, "chunk": 1, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Employment Unemployment\nSurvey", "label": "NAMED_DATA", "score": 0.6160057783126831, "start": 270, "end": 300, "probe_score": 0.9882, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "new census", "label": "DESCRIPTIVE_DATA", "score": 0.7892296314239502, "start": 1307, "end": 1317, "probe_score": 0.9572, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_Project costs_** **.** Costs include investment costs and maintenance costs:\n\n\n(i) Investment costs data were provided by the engineering design studies, referring to actual\n\ncosts based on cost estimations of similar projects.\n\n(ii) The annual maintenance costs are estimated at 1% of the total investment based on other\n\nsimilar projects.\n\n\n**Table 5.8: Investment and Maintenance Costs**\n\n|Municipality/Cost|Investment Cost (CFAF)|Annual Maintenance cost<br>(CFAF)|\n|---|---|---|\n|**Douala 3**|8,432,150,615|62,935,385|\n|**Douala 5**|4,270,794,839|71,802,500|\n|**Total**|12,702,945,454|134,737,885|\n\n\n\n30. **_Results (Benchmark scenario)._** The Net Present Value (NPV) and Economic Internal Rate of\nReturn (EIRR) ex-ante (using a 5% discount rate) are presented in the table 5.9.\n\n\n33 Etablissement camerounais des Techniciens Associés en Bâtiments et Travaux publics - _e_ ngineering report\n34 National Statistics Institute of Cameroon\n35 Hutton, G. and L. Haller, “Evaluation of the Costs and Benefits of Water and Sanitation Improvements at the\nGlobal Level”, WHO, 2004.\n\n\n77", "output": {"entities": {"named_data": [], "descriptive_data": ["Investment costs data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000144", "page": 90, "chunk": 1, "title": "Cameroon - Inclusive and Resilient Cities Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/832091503626454254/pdf/CAMEROON-PAD-NEW-08032017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Investment costs data", "label": "DESCRIPTIVE_DATA", "score": 0.7093368768692017, "start": 84, "end": 105, "probe_score": 0.6567, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Only five woredas had a\nprocurement specialist at the beginning of PBS 3; 500 woredas had such staff by project completion. Federal\nProcurement and Property Administration systems were strengthened, and a Procurement Professionalization\nand Accreditation Program established, the first of its kind in Ethiopia.\n\n\n**Sub-Program B.3: Managing for Results**\n\n\nManaging for Results activities strengthened data, systems, and analytical capacity for accurately and timely\nreporting on service delivery results. The scope was ambitious, encompassing activities across many agencies.\nPBS 3 supported development of sectoral management information systems in education, agriculture, water\nand sanitation and roads. This was largely achieved, with some delays in roll-out of the WASH system and delays\nwith the Ethiopian Road Authority MIS that resulted in its postponement to the successor project. Data quality\nassessments by the Central Statistics Agency were carried out at least once in all basic service sectors. A\ncurriculum was developed and implemented for the Ministry of Education on indicators definitions and\ncollection methods, with training delivered to all woredas. The Ministry of Agriculture developed software on\nproductivity and impact of development agents. Four sectors had their indicators classified as official data\nthrough implementation of EDQAF, surpassing the intermediate results target of 2.\n\n\nNational level data on service delivery aspects were collected by the Central Statistics Agency, including:\ndevelopment of geo-referenced service facility maps for all regions, a mini-Demographic Household Survey\n(DHS), completion and publication of national household income and expenditure survey (with welfare\nmonitoring component), and support to disaggregation of data by gender at decentralized level (in all 11\nregions) and publication of country report on Gender Disaggregated Development Data, among others.\n\n\n**Sub-Program B.4: Risks and Safeguard Management Capacity**\n\n\nAdded in response to the Management action plan following an Inspection Panel case, this component <mark>focused</mark>\n<mark>on boosting woreda level capacity to manage environmental and social risks.", "output": {"entities": {"named_data": ["mini-Demographic Household Survey", "Gender Disaggregated Development Data"], "descriptive_data": ["geo-referenced service facility maps", "national household income and expenditure survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:021213", "page": 22, "chunk": 1, "title": "Ethiopia - Third Phase of Promoting Basic Services Project", "pdf_url": "https://documents.worldbank.org/curated/en/991331561645897187/pdf/Ethiopia-Third-Phase-of-Promoting-Basic-Services-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "geo-referenced service facility maps", "label": "DESCRIPTIVE_DATA", "score": 0.5041109919548035, "start": 1540, "end": 1576, "probe_score": 0.0865, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "mini-Demographic Household Survey", "label": "NAMED_DATA", "score": 0.7226738333702087, "start": 1596, "end": 1629, "probe_score": 0.0543, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "national household income and expenditure survey", "label": "DESCRIPTIVE_DATA", "score": 0.8610531687736511, "start": 1667, "end": 1715, "probe_score": 0.096, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Gender Disaggregated Development Data", "label": "NAMED_DATA", "score": 0.5980983972549438, "start": 1881, "end": 1918, "probe_score": 0.0415, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n\n\nFor the regional analysis, population weights were\napplied based on the most up-to-date refugee\npopulation figures for each country, ensuring the\nfindings accurately represented the broader\nregional refugee population. To maintain\ncomparability, the figures for 2023 presented in this\nreport were also re-estimated using survey weights.\n\n\nThis report utilises the criteria of the Washington\nGroup on Disability Statistics Short Set on\nFunctioning (WG-SS) <sup>7</sup> . The assessment included a\ncomprehensive set of questions covering mobility,\nvision, hearing, cognition, self-care, and\ncommunication. For the purpose of this report,\ndisability is defined as level 3 and above, indicating\nsignificant limitations in functioning (‘a lot of\ndifficulty’ or ‘cannot do at all’). For indicators related\nto chronic illness and vaccination, respondents\nself-reported whether they or any household\nmembers had a chronic illness and whether children\nin the household had received measles vaccine.\n\n\nTo facilitate trend monitoring, the questionnaires\nwere standardized across all countries, ensuring\nconsistency in the majority of indicators between\n2023 and 2024. Since the 2023 regional survey did\nnot include data from Latvia, Lithuania, and Estonia,\nvalues for these countries were excluded from the\n2023–2024 comparison. To maintain accuracy, only\nvalid responses were included in the calculations,\nwith responses such as ‘prefer not to answer’ or ‘do\nnot know’ excluded. To facilitate interpretation,\ncertain response options were consolidated into\nbroader categorical variables.\n\n\nTo protect data privacy and maintain confidentiality,\ninformed consent was obtained and documented\nfrom all participants, with clear explanations\nprovided regarding the purpose and use of the\ndata. The complete questionnaires, along with the\nconsolidated anonymized dataset, are available in\nthe <u>[UNHCR Microdata Library.](https://microdata.unhcr.org/index.php/catalog/?page", "output": {"entities": {"named_data": [], "descriptive_data": ["refugee\npopulation figures", "2023 regional survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000004", "page": 6, "chunk": 0, "title": "NAVIGATING HEALTH AND WELL BEING CHALLENGES FOR REFUGEES FROM UKRAINE   2nd Edition", "pdf_url": "https://local/jad_paddy_docs/navigating health and well-being challenges for refugees from ukraine - 2nd edition.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "refugee\npopulation figures", "label": "DESCRIPTIVE_DATA", "score": 0.6874606609344482, "start": 161, "end": 187, "probe_score": 0.7247, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2023 regional survey", "label": "DESCRIPTIVE_DATA", "score": 0.7757344841957092, "start": 1240, "end": 1260, "probe_score": 0.8437, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " of collateral, banks have\nbegun developing alternative credit ratings based on\nother data, such as M-Pesa transactions or savings\naccount history. With the rise of digital finance,\nbanks are able to reach customers in extremely\nremote locations without costly investments in\nbrick and mortar shops.\n\n\nEquity Bank already has considerable operations in\nKakuma camp and town (see box 3.2).\n\n\nAccess to credit\nThe low access to credit and use of informal\nlending mechanisms presents opportunities for\nformal financial institutions to expand to Kakuma.\nRespondents in the town (29 percent) are more\nlikely than those in the camp (24 percent) to receive\na loan. Kenyans are more likely to use the loan for\neducation or a business investment, while those in\nthe camp mostly borrow money from local shops\nto buy food on credit. Entrepreneurs in both areas\nconsider access to capital to be the main constraint\nto business growth. Equity Bank does lend directly to\nrefugees but through risk-partnerships with NGOs,\nwhich select beneficiaries and provide the funds,\nwhile Equity Bank holds the account and disburses\nthe loans. The Bank also supports traders and uses\ninventory as collateral.\n\n\n\n100%\n\n\n\n\n\n**Loan access by national group**\n\n\n_“Have you obtained a loan/borrowed money from this source over the past 12_\n\n_months?”_\n\n_- K-town 311 interviews -_\n\n_- K-camp 1,106 interviews -_\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|100|Col3|100|Col5|Col6|100|Col8|100|Col10|100|Col12|100|Col14|100|Col16|100|Col18|100|Col20|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|-", "output": {"entities": {"named_data": [], "descriptive_data": ["M-Pesa transactions"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001460", "page": 56, "chunk": 1, "title": "Kakuma as a Marketplace: A consumer and market study of a refugee camp and town in northwest Kenya (Special conference edition)", "pdf_url": "https://reliefweb.int/attachments/e369993f-b58b-3321-a902-2b776492e30f/20180427_Kakuma-as-a-Marketplace_v1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "M-Pesa transactions", "label": "DESCRIPTIVE_DATA", "score": 0.7913684844970703, "start": 100, "end": 119, "probe_score": 0.4346, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " [UNHCR Global Focus](https://reporting.unhcr.org/operational/regions/europe)\nEurope webpage\n\n- [UNHCR Ukraine Emergency](https://www.unhcr.org/emergencies/ukraine-emergency)\nwebpage\n\n\n\n**Operational data portals:**\n\n\n- [Ukraine Refugee Situation](https://data.unhcr.org/en/situations/ukraine)\n\n- [Europe Sea Arrivals](https://data.unhcr.org/en/situations/europe-sea-arrivals)\n\n\n\nwebpage **Contact:**\n\nUNHCR Regional Bureau for\nEurope\n[rbeext@unhcr.org](mailto:rbeext%40unhcr.org?subject=)\n**[Join our mailing list](https://manage.kmail-lists.com/subscriptions/subscribe?a=VYAYG5&g=QZGRtb)**\nwww.unhcr.org/europe\n\n\n\nPage 7 **U N H C R R E G I O N A L B U R E A U F O R E U R O P E,** O C T O B E R 2 0 2 4", "output": {"entities": {"named_data": ["UNHCR Ukraine Emergency", "Ukraine Refugee Situation", "Europe Sea Arrivals"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000406", "page": 6, "chunk": 2, "title": "UNHCR: Critical Funding Needs in Europe, October 2024", "pdf_url": "https://reliefweb.int/attachments/374e9362-93fe-47ef-8f0f-6555c9efb172/2024%20Critical%20Funding%20Needs%20-%20Europe.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR Ukraine Emergency", "label": "NAMED_DATA", "score": 0.5020880699157715, "start": 97, "end": 120, "probe_score": 0.0803, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Ukraine Refugee Situation", "label": "NAMED_DATA", "score": 0.7623345851898193, "start": 221, "end": 246, "probe_score": 0.0634, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Europe Sea Arrivals", "label": "NAMED_DATA", "score": 0.7627092599868774, "start": 298, "end": 317, "probe_score": 0.1368, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*|**Result Area 3 on Transparency and Accountability through Digitalization**|**Result Area 3 on Transparency and Accountability through Digitalization**|**Result Area 3 on Transparency and Accountability through Digitalization**|\n|DLI8 on enhancing e-<br>information|30.00|-|30.00|a. <br>Weak enforcement of the 2007 Access to Information Law on proactive<br>disclosure of information and response to requests for information.<br>b. <br>Opportunity to enhance government reporting to the public online about<br>progress achieved towards economic and public sector modernization.|\n|DLI9 on interactive<br>statistical<br>information|30.00|-|30.00|Important gaps in open data coverage and openness to be mitigated by<br>establishing a national data repository with an interactive interface and<br>protocols to allow access to the data for policy analysis and research purposes.|\n|DLI10 on<br>institutionalizing<br>effective health data<br>use|8|18.00|26.00|a. <br>Weak health data management.<br>b. <br>Need to institutionalize the data quality assurance mechanism in place,<br>establishing data quality standards and conducting routine assessments.<br>c. <br>Opportunity to better utilize quality data for more effective and timely<br>decision-making.|\n|Front-end Fees|0.8025|TBD||d. <br>|\n|**Total**|**350**|**54.34**|**404.34**||\n\n\n\nPage | 13", "output": {"entities": {"named_data": [], "descriptive_data": ["national data repository"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000181", "page": 22, "chunk": 3, "title": "Jordan - People-Centric Digital Government Program for Results", "pdf_url": "https://documents1.worldbank.org/curated/en/099030724150040202/pdf/BOSIB-70f97ae8-b741-401c-82cc-e87615cc5487.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "national data repository", "label": "DESCRIPTIVE_DATA", "score": 0.5823565125465393, "start": 733, "end": 757, "probe_score": 0.0057, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Col1|complaints data.<br>20. Furthermore, this component will finance the development of financial literacy programs<br>through public awareness campaign and media programs, on issues, such as the legal rights of clients,<br>understanding different financial products offered in the market and compliant resolution. This<br>component could also include advising CBJ on the Treating Customers Fairly Instructions and related<br>laws, including on any changes which may be considered necessary to fulfill the objectives outlined<br>above; and (iii) conducting two study tours for senior officers of the new Consumer Protection Unit<br>(once it is established) to countries which have well developed systems for financial consumer<br>protection regulation and supervision.<br>21. Strengthening the capacity of the Consumer Protection Unit will enable it to enforce the<br>following disclosure and accountability requirements reflected in the Treating Customers Fairly<br>Instructions, which include (in summary): (i) mandatory plain-language disclosures of all key prices,<br>terms, and conditions; (ii) requirement that all key information be stated in the contract; (iii) the<br>required disclosure of an effective annual percentage rate (which analytical work has shown to be<br>more comprehensible for many consumers including those with lower levels of education and<br>financial sophistication); (iv) the specific requirements that no additional fees can be charged beyond<br>those that are disclosed; and (v) the requirement that the difference between fixed and variable<br>interest rates is explained clearly to the customer up-front and is based on observable benchmarks in<br>the market.<br>Component III: Supporting the development of the institutional framework for microfinance<br>and non-bank financial institutions (NBFIs) supervision (US$ 0.8 million)<br>22. This component", "output": {"entities": {"named_data": [], "descriptive_data": ["complaints data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000060", "page": 6, "chunk": 0, "title": "Jordan - Enhancing Governance and Strengthening the Regulatory and Institutional Framework for Micro, Small, and Medium Enterprise (MSME) Development Project", "pdf_url": "http://documents.worldbank.org/curated/en/926531468040487242/pdf/838160PID0Appr0Box382106B00PUBLIC0.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "complaints data", "label": "DESCRIPTIVE_DATA", "score": 0.7680585384368896, "start": 6, "end": 21, "probe_score": 0.3933, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "3. **Lessons** **learned** <sup>**and reflected**</sup> <sup>**in the project design:**</sup>\n\n\n\nThe project design reflects <sup>lessons learned from intemational experience</sup> <sup>with</sup> <sup>social</sup> <sup>funds (SFs),</sup>\n\n\n\nas well as from IDA's <sup>experience</sup> <sup>with</sup> <sup>the on-going</sup> <sup>Community</sup> <sup>Reintegration</sup> <sup>and</sup> <sup>Rehabilitation</sup> <sup>Project</sup>\n\n\n\n(CRRP) (Cr. 3312-SL). <sup>The NaCSA</sup> <sup>and</sup> <sup>Bank teams drew</sup> <sup>on experiences,</sup> <sup>lessons learned</sup> <sup>and</sup>\n\n\n\nevaluations of several <sup>Bank</sup> <sup>and other donor projects</sup> <sup>in designing</sup> <sup>this project. Project documentation</sup>\n\nfrom Angola, Eritrea, <sup>Ethiopia,</sup> <sup>Rwanda,</sup> <sup>Burundi, Malawi,</sup> <sup>Zambia,</sup> <sup", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000151", "page": 17, "chunk": 0, "title": "Bosnia and Herzegovina - Third Electric Power Reconstruction Project", "pdf_url": "http://documents1.worldbank.org/curated/en/873371468767980151/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<br>signed documents at<br>MOE|Third Party|The verification agency will check<br>that the national assessment<br>strategy has been adopted, signed,<br>and published on MOE's website.|\n|**DLR#7.2**Grade 3 diagnostic<br>test on early grade reading and<br>math implemented in all target<br>schools|Schools are conducting rapid, no‐stakes formative assessments<br>given by Grade 3 teachers at the beginning of the year to<br>evaluate student learning needs, particularly in math and<br>reading.|School records of<br>assessments|Third Party|Check assessments records for a<br>sample of schools|\n|**DLR#7.3**First phase of _Tawjihi_<br>exam reform completed and<br>action plan for reform rollout is<br>produced|The first phase of the_Tawjihi_reform will consist of conducting<br>consultations on the reform with the various stakeholders, the<br>design of the new examination instruments and the piloting of<br>those instruments. After the first phase, MOE will analyze the<br>examination data, in addition to perception ", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["examination data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000041", "page": 47, "chunk": 1, "title": "Jordan - Education Reform Support Program-for-Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/731311512702123714/pdf/Jordan-Educ-Reform-121282-JO-PAD-11142017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "examination data", "label": "VAGUE_DATA", "score": 0.6958522796630859, "start": 970, "end": 986, "probe_score": 0.9862, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Note: The reference period for looking at changes in income are since the previous round. The exception is the first round, for\nwhich the reference period is pre-pandemic. Results from an OLS regression are shown. The pooled sample excludes PNG, for\nwhich income data is not available.\n\n\n34", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["income data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001702", "page": 35, "chunk": 0, "title": "inequality under covid 19 taking stock of high frequency data for east asia and the pacific", "pdf_url": "https://local/prwp/inequality-under-covid-19-taking-stock-of-high-frequency-data-for-east-asia-and-the-pacific.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "income data", "label": "VAGUE_DATA", "score": 0.7629333138465881, "start": 256, "end": 267, "probe_score": 0.872, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " as having gone ‘somewhat well’\n\n\n(26.4%) or ‘very well’ (71.7%).\n\n\nIn conjunction with the survey, we also collected data on the performance of public officials as assessed\n\n\nin their annual appraisal. Each year, public officials are evaluated by their direct manager on the tasks\n\n\nthat they were expected to contribute to. For example, tasks might include ‘Monitor and provide support\n\n\nto the [work] team preparing the budget’ and ‘Support the team to prepare soft and hard copy documents\n\n\nof the budget’. Managers evaluate the quality of contributions bureaucrats make to the tasks they were\n\n\ninvolved in and produce an overall ‘performance’ score. In addition to this performance-related score,\n\n\npublic officials are evaluated on their ‘attitude’ to work, which intends to measure their office behavior\n\n\nand alignment to the organization (Abagisa, 2014; Tereda, 2014). For the year 2016, we collected the\n\n\nperformance, attitude, and total scores (which are a weighted average of performance and attitude scores)\n\n\nfor each official from a subset of the organizations we visited for which they were available.\n\n\n9", "output": {"entities": {"named_data": [], "descriptive_data": ["data on the performance of public officials"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007560", "page": 10, "chunk": 1, "title": "wps8644", "pdf_url": "https://local/prwp/wps8644.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on the performance of public officials", "label": "DESCRIPTIVE_DATA", "score": 0.7477409243583679, "start": 118, "end": 161, "probe_score": 0.0194, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "activities include: agro-forestry; climate smart agriculture; rehabilitation of degraded rangelands; local\nlandscape management; improving access to water and promotion and conservation of efficient water use;\nnatural resource management and environmental conservation/community forestry; rehabilitation of\ndegraded lands and promotion of renewable energy sources and rural Infrastructure and Disaster Risk\nManagement. These activities support Government of Kenya under the third medium term plan of Kenya\nVision 2020, whose objective is to promote strategies for adaptation and mitigation of climate change effects\non agricultural systems.\n\n95. **Potential benefits of soil water conservation measures.** The environmental benefits associated with soil\nand water conservation, i.e. terracing and grass strips include carbon sequestration, nutrient recycling, and\nprevention of siltation of dams and other water bodies through reduction of soil erosion. Terraces were found\nto have higher soil carbon of up to (up to 6MgC/ha) compared to sites where farmers practiced conventional\nagriculture. Furthermore, terraces and grass strips have the benefit of increasing crop yields due to increased\nretention of soil moisture, nutrients, and prevention of seed loss. Increased crop yields associated with these\npractices have the impact of increasing household food security levels. UNDP and FAO (2020) <sup>29</sup> [^29: FAO & UNDP, (2020). Assessing agroforestry practices and soil and water conservation for climate change adaptation in\nKenya: A cost-benefit analysis. Rome, FAO.] conducted a\nsurvey from a survey of 642 households spread across five counties <sup>30</sup> [^30: Kilifi (low potential costal area), Homabay (low potential Nyanza), Kakamega (Western medium potential), Nyeri (Central\nmedium potential) and Nakuru (High potential central rift).] in Kenya, in order to establish the cost\nbenefit analysis of adapting soil and water conservation measures using terracing, which was adopted by 15%\nof farmers and grass strips (25% of farmers).\n\n\n96. Table 6 provides a summary of the netRR", "output": {"entities": {"named_data": [], "descriptive_data": ["survey of 642 households"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016143", "page": 38, "chunk": 0, "title": "Final Technical Assessment - Financing Locally-Led Climate Action Program - P173065", "pdf_url": "https://documents.worldbank.org/curated/en/650141633388861479/pdf/Final-Technical-Assessment-Financing-Locally-Led-Climate-Action-Program-P173065.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey of 642 households", "label": "DESCRIPTIVE_DATA", "score": 0.9223644137382507, "start": 1605, "end": 1629, "probe_score": 0.8152, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "43. **_DLIs 1 - 4 on the institutional performance of and service delivery by the 22 MLGs have evolved_**\n**_to incentivize further institutional improvements_** **.** Given the high attainment of performance measures in\nthe current phase by all participating municipal LGs, the same thematic areas have been retained under the\nAF but the indicators have been revised and strengthened to incentivize further improvement <sup>41</sup> [^41: The AF will retain the same seven thematic areas: i) linkages between municipal physical plan, five-year development plan and\nannual budget, ii) own source revenue generation, iii) procurement, iv) financial management, v) program execution and\nimplementation (budget execution), vi) monitoring, enhanced accountability, transparency and communication and vii)\nenvironmental and social sustainability. Service delivery will be measured through i) quantitative outputs against plans, and ii) value\nfor the money audits as well as iii) review of operational and maintenance performance, which an added parameter.] . For example,\nAnnual Program Assessments results showed that most MLGs scored above 90 percent in the last years\nassessment of environmental and procurement indicators. The bar for such indicators has therefore been\nraised throughout. Several new indicators have also been introduced, to ensure that municipalities play their\nroles in promoting LED, including: (i) addition of Municipal Commercial Officer as a minimum condition\nin year 2 and incentives for LGs that prioritize investments through a participatory process that includes\nprivate sector representatives; (ii) organization of regular forums to hear concerns of the private sector and\ntake action on them; (iii) creation of a One Stop Center providing registration, tax education, investor\naftercare and grievance desk services; and implementation of enterprise support activities through their\ncommercial office.\n\n44. **_DLIs 5 - 6 on the support to MoLHUD to develop the necessary systems for urban development_**\n**_and management have also been strengthened and improved to focus on key results_** **", "output": {"entities": {"named_data": ["Annual Program Assessments results"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000014", "page": 24, "chunk": 0, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents1.worldbank.org/curated/en/143681526614252328/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Annual Program Assessments results", "label": "NAMED_DATA", "score": 0.5053667426109314, "start": 1067, "end": 1101, "probe_score": 0.0596, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad Rural Mobility and Connectivity Project (P164747)\n\n\n**Table 3.1. Assumptions and Parameters Used to Run IPSS**\n\n|Assumption and Parameters|Value|Reference Source|\n|---|---|---|\n|Discount rate|6%|Discounting Costs and Benefits in Economic Analysis<br>of World Bank Projects|\n|Number of lanes in the road|2|On average, from time in the field, the road has two<br>lanes|\n|Cost of rehabilitating or constructing a<br>tertiary, unpaved road (US$/km)|US$52,195|Implementation Completion and Results Report for<br>Zambia Road Rehabilitation and Maintenance Report<br>(P071985)|\n|Cost of annual maintenance (US$/km)|US$300|Implementation Completion and Results Report for<br>Zambia Road Rehabilitation and Maintenance Report<br>(P071985|\n|Design life|20 years|Estimated life span for this given project|\n|Climate models used|CMIP5|World Climate’s Research Program (WCRP) Working<br>Group on Coupled Modeling (WGCM)|\n|Time period of consideration|2018–2050|Period of interest in planning this project|\n\n\n\n**5.** Further details about the process used by IPSS to estimate the risks and costs to road\ninfrastructure can be found at the Resilient Analytics website (https://resilient-analytics.com/pages/rahome_en.html). For additional application of the IPSS methodology, the large-scale study assessing road\nnetworks throughout Sub-Saharan Africa conducted by the World Bank should be referenced. <sup>13</sup>\n\n\n**Results**\n\n\n6", "output": {"entities": {"named_data": [], "descriptive_data": ["large-scale study assessing road\nnetworks throughout Sub-Saharan Africa"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000048", "page": 59, "chunk": 0, "title": "Chad - Rural Mobility and Connectivity Project", "pdf_url": "http://documents.worldbank.org/curated/en/815491545534039786/pdf/Chad-PAD-11302018-636811128215032206.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "large-scale study assessing road\nnetworks throughout Sub-Saharan Africa", "label": "DESCRIPTIVE_DATA", "score": 0.6740753054618835, "start": 1289, "end": 1360, "probe_score": 0.8063, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*ـ**\nرّت **ـ** ي ي� <sup>ت</sup> **ـ** ة، وال **ـ** مناحات ال <sup>آ</sup> **ـ** ي المسام � <sup>ف</sup> **ـ** ي تق� <sup>ت</sup> **ـ** طة ال **ـ** نشور ال <sup>أ</sup> **ـ** ة، أو لحض **ـ** المدرس\n\nن. **ـ** و آم **ـ** ي جاح � <sup>ف</sup> **ـ** د الإفص **ـ** بالتأكي\nن **ـ** ة م **ـ** خاص ذوي الإعاق **ـ** شن أن ال <sup>أ</sup> **ـ** اب ع **ـ** ة النق **ـ** وث العلمي **ـ** فت البح **ـ** د كش **ـ** وق\nي **ـ** ف العاطف **ـ** �ي ، والعن **ـ** ف الجن **ـ** دي، والعن **ـ** ف الجس **ـ** وا للعن **ـ** ح أن يتعرض **ـ** المرج\nا **ـ** أم <sup>9</sup> .بمة *", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001345", "page": 5, "chunk": 4, "title": "Jordan GBV IMS Task Force Annual Report 2021 [EN/AR]", "pdf_url": "https://reliefweb.int/attachments/cf37dda3-317e-40f3-88df-e4bb3bc6d56d/Final%20GBVIMS%202021%20Report_%20Arabic.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nBeirut Housing Rehabilitation and Cultural and Creative Industries Recovery (P176577)\n\n\n\n\n\n|Col1|financial support through<br>the project in the<br>reconstruction of their<br>residential unit from the<br>PoB explosion.<br>Rationale: 100 rental<br>contracts x 3.5 people/HH|Col3|and<br>Evaluation<br>Reports. Esti<br>mates by<br>Project<br>Management<br>Team.|disaggregating the<br>beneficiary data of the<br>progress reports|Team/UN-Habitat|\n|---|---|---|---|---|---|\n|Direct beneficiaries of cultural production<br>work|Number of people including<br>cultural practitioners,<br>individuals in cultural<br>entities and additional<br>workers involved in the<br>implementation of the<br>cultural productions.|Quarterly<br>|Progress,<br>Monitoring<br>and<br>Evaluation<br>Reports.<br>Third-Party<br>Monitoring<br>Agent<br>reports.<br>Estimates by<br>Project<br>Management<br>Team.<br>|Number of<br>beneficiaries will be<br>tracked in the progress<br>reports through<br>reporting updates by<br>each grant recipient of<br>the total number of<br>people participating on<br>each cultural<br>production work<br>|Project Management<br>Team/UN-Habitat<br>|\n|Of which, are female|Number of females<br>including cultural<br>", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["beneficiary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000034", "page": 40, "chunk": 0, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents1.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "beneficiary data", "label": "VAGUE_DATA", "score": 0.6853852868080139, "start": 400, "end": 416, "probe_score": 0.0908, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\nprotective support to HHs and investment in resilience building community assets will help sustain livelihoods, strengthen\nresilience, and prevent the most vulnerable from falling into destitution or being forcibly displaced. It will also directly\nsupport the Government’s Community Empowerment and Socioeconomic Development Strategy for Refugee Hosting\nAreas in South Sudan, with cash transfers promoting section 4.6 of the strategy on creation of livelihood and income\ngenerating opportunities given the lack of employment prospects in refugee-hosting environments.\n\n37. **In the absence of an enabling environment for widescale mobile payment systems, beneficiaries will receive**\n**physical cash at the time of payment, except for Juba where mobile money payment will be piloted.** A financial service\nprovider (i.e., paying agent), which will be competitively selected by the MAFS, will deliver cash to beneficiaries. The\nMAFS will provide the recipient list and amount of money to the financial service provider, and the list of beneficiaries\nwill be generated from the MIS. The MIS will capture beneficiaries' biometric data, which will be used to ensure that only\nthe eligible individuals will receive the cash transfer. The financial service provider pays beneficiaries verifying them\nbiometrically. In addition, implementing partners (i.e., UNOPS and NGOs contracted by MAFS to implement the project)\nand community leaders will be present and monitor the transfer process to ensure transparency and accountability.\nBased on the findings of a recently concluded analytical work, the project will pilot the use of mobile money payments\nin Juba. Mobile money payments would help strengthen transparency and safety and were assessed to be feasible in\nlarge urban center like Juba under the SSSNP. This pilot would inform potential future scale up of mobile money payments\nin urban areas.\n\n**Sub-component 1.1: Cash for Labor-Intensive Public Works and Complementary Social Measures** *", "output": {"entities": {"named_data": ["MIS", "MIS"], "descriptive_data": ["biometric data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 23, "chunk": 0, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "MIS", "label": "NAMED_DATA", "score": 0.802470862865448, "start": 1169, "end": 1172, "probe_score": 0.1458, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "MIS", "label": "NAMED_DATA", "score": 0.6210047602653503, "start": 1178, "end": 1181, "probe_score": 0.0462, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "biometric data", "label": "DESCRIPTIVE_DATA", "score": 0.6377971768379211, "start": 1210, "end": 1224, "probe_score": 0.2475, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda Secondary Education Expansion Project (P166570)\n\n\n11. **There are disparities in access to secondary education by region, location, wealth, and gender.** The\nNorthern region lags behind in terms of access to secondary education (Figure 6), with GER for nearly all districts\nin the region below the national average of 28 percent and many of them below 10 percent. The enrollment rates\nin urban areas of the Central region are dramatically higher than those in rural and underserved areas in the North.\nFor instance, in 2015, GER in the capital city of Kampala was over 50 percent, while in rural Kaabong (Karamoja\ndistrict), it was only 5 percent. Variations by welfare quintiles reveal that secondary school enrollment drops with\ndecreasing welfare. It is the lowest for persons in the lowest quintile (7 percent) and highest in the fifth quintile\n(41 percent). <sup>15</sup> Disparities in completion <sup>16</sup> rates are evident between rural areas, at 6.5 percent, and urban, at just\nover 14 percent. Variations in secondary completion rates persist across the country with Kampala (Central) having\n\n\n15 National Household Survey 2012/13. [Data on wealth and enrolment disparities not included in the 2016 National Household Survey]\n16 Completion rate here is defined as children completing primary seven as a proportion of children entering primary one.\n\n\nPage 10 of 96", "output": {"entities": {"named_data": ["National Household Survey", "2016 National Household Survey"], "descriptive_data": ["Data on wealth and enrolment disparities"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 15, "chunk": 0, "title": "Uganda - Secondary Education Expansion Project", "pdf_url": "http://documents.worldbank.org/curated/en/406361595815248191/pdf/Uganda-Secondary-Education-Expansion-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "National Household Survey", "label": "NAMED_DATA", "score": 0.6167446970939636, "start": 1137, "end": 1162, "probe_score": 0.9793, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Data on wealth and enrolment disparities", "label": "DESCRIPTIVE_DATA", "score": 0.592409610748291, "start": 1173, "end": 1213, "probe_score": 0.3042, "gold": "NON_MENTION", "gold_tier": "human-final"}, {"text": "2016 National Household Survey", "label": "NAMED_DATA", "score": 0.7427452802658081, "start": 1234, "end": 1264, "probe_score": 0.9563, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2023 Standardized Expanded Nutrition\nSurvey (SENS)\n\n#### Indicators for Women of Reproductive Age (15-49 years)\n\nAmong women of reproductive age, acute malnutrition was low (1.8%) and anemia was of medium public\nhealth significance (24.1%). Program coverage (antenatal care, iron folic acid supplementation and blanket\nsupplementary feeding) was high for pregnant and lactating women, a continuation of the trend for the past\nrounds of SENS although BSFP coverage was slightly below the 90% target in Mega Camps at 85.5% (Fig.8).\n\n###### Table 6: Health and Nutrition Indicators among Women of Reproductive Age in Cox’s\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Bazar Rohingya Camps (2023)|Col2|Col3|Col4|\n|---|---|---|---|\n|**Indicator**|**Mega Camps**<br>**(95% CI)**|**Registered Camps**<br>**(95% CI)**|**Overall**<br>**(Weighted)**|\n|Low MUAC (<210mm) among<br>women of reproductive age|**1.8%**<br>(0.9 - 3.3)|**1.3%**<br>(0.7 - 2.4)|**1.8%**|\n|Low MUAC (<210mm) among PLW<br>with child<6 months|**1.8%**<br>(0.4 - 7.0)8|**0.0%**<br>(0.0 - 0.0)|**1.8%**|\n|Mean women’s MUA", "output": {"entities": {"named_data": ["2023 Standardized Expanded Nutrition\nSurvey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000281", "page": 11, "chunk": 0, "title": "UNHCR Bangladesh 2023 Standardized Expanded Nutrition Survey (SENS) - Final Executive Summary", "pdf_url": "https://reliefweb.int/attachments/20299a92-34a5-48b9-8247-c3caee793a44/2023_BAN_CXB%20SENS%20FINAL%20EXEC%20SUMMARY_4%20JAN%202024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2023 Standardized Expanded Nutrition\nSurvey", "label": "NAMED_DATA", "score": 0.887717604637146, "start": 0, "end": 43, "probe_score": 0.8881, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "9\nRetired 9.0 8.8\nStudent 7.8 7.6\n<u>Other labor force status</u> <u>37.6</u> <u>38.8</u>\n<u>Source: Microdata provided by regional focal points, members of the Global Poverty Working Group. Authors’ calculations.</u>\n\n\nTheoretically, spatial price adjustments have an impact on the welfare ranking of households and on\ngrowth rates of household income and expenditure. However, according to our empirical analysis, unless\nspatial adjustments were conducted inconsistently over time, the impact of spatial price adjustments on\ngrowth rates including those of the bottom 40 percent is minimal. However, carrying out spatial price\n\n\n14", "output": {"entities": {"named_data": [], "descriptive_data": ["Microdata"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006643", "page": 15, "chunk": 1, "title": "wps7611", "pdf_url": "https://local/prwp/wps7611.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Microdata", "label": "DESCRIPTIVE_DATA", "score": 0.734312117099762, "start": 101, "end": 110, "probe_score": 0.9995, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nLebanon Energy Sector Reforms Program (P170506)\n\n# Program Information Document (PID)\n\n\n<mark>Concept Stage | Date Prepared/Updated: 04-Apr-2019 | Report No: PIDC185505</mark>\n\n\nMar 05, 2019 Page 1 of 10", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000011", "page": 0, "chunk": 0, "title": "Concept Stage Program Information Document (PID) - Lebanon Energy Sector Reforms Program - P170506", "pdf_url": "http://documents.worldbank.org/curated/en/260831554415577082/pdf/Concept-Stage-Program-Information-Document-PID-Lebanon-Energy-Sector-Reforms-Program-P170506.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 1\nPage 3 **of** 3\n\n\n**Key Performance**\n**Hierarchy of Objectives** **Indicators** **Monitoring &** **Critical Assumptions**\n**Evaluation**\n**Project Components / Sub-** **Inputs: (budget for each** **Project reports:** **(from Components to**\n**components:** **component)** **Outputs)**\n\n\nImprove Access: provision of US$5.8 million MOE monitoring Capacity within the\nclassrooms. Number of schools reports construction sector to handle\nconstructed per year; the volume of school\nimproved design and construction.\nefficiency.\nCreate Conditions for Quality US$1.1 million School surveys; student Good textbook distribution;\nImprovement: access to Number of textbooks per learning achievement management training\neducational materials; student; autonomous school reports (MOE effectiveness; Government\nimproved school management; salaries paid on monitoring reports). commitment to paying\nmanagement; teacher a timely basis teacher salaries.\nmotivation.\n\n\nImprove Government's US$4.1 million Project monitoring Purpose and integrity\nCapacity to Manage Sector: Project effectively reports; study reports. maintained within project\ncapacity building within the implemented and management; stakeholder\nMOE and its related services; management improved; participation in pilot studies.\npilot studies. reports with implementable\nresults.\n\n\n**Annexe 1 Attachment: Program and Project Monitorin** **Tar** **ets**\n**_Year_** _2001-02 2002-03_ **_2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10_**\nPrimary Enrollment Boys 19,125 21,506 24,300 26,627 29,867 31,696 34,457 37,217 40,129\nPrimary Enrollment Girls 14,875 17,994 20,", "output": {"entities": {"named_data": [], "descriptive_data": ["School surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020882", "page": 31, "chunk": 0, "title": "Ethiopia - Fourth Livestock Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/968941468250502683/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "School surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8726161122322083, "start": 577, "end": 591, "probe_score": 0.0853, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**2023 POST-EARTHQUAKE POPULATION DYNAMICS ANALYSIS**\n\n#### **Background**\n\n\nThe devastating 7.8 magnitude earthquake, and 7.7 magnitude aftershock, in\n\n\nsoutheast Türkiye on 22 February 2023 resulted in multiple waves of population\n\n\ndisplacement, and secondary displacement, both within and outside of the impacted\n\n\nareas. Significant numbers of Turkish nationals and refugee survivors moved on to\n\n\nother provinces, in many cases facilitated by the Government of Türkiye (GoTR). In\n\n\nthe immediate aftermath, several thousands of Syrian refugees benefitted from the\n\n\nGoTR’s offering temporary home visits for refugees from affected provinces. Voluntary\n\n\nreturns to Syria continued throughout the year as well, though returns were\n\n\nsignificantly fewer when compared to the same period in 2022. These movements\n\n\nchanged shape and frequency over the months, with many refugees eventually\n\n\nreturning to their original provinces of registration and residence within the impact\n\n\nzone.\n\n\nAlthough heading in different directions, population movement flows were influenced\n\n\nby the similar push and pull factors, illustrating the importance of socio-economic\n\n\nconsiderations behind intentions and decisions. To better understand the profiles of\n\n\nrefugees involved in these population flows, UNHCR carried out surveys and\n\n\nmonitoring activities throughout 2023. The findings of which are analysed in the\n\n\npresent end-of-year population movement report.\n\n##### **Purpose, scope and methodology**\n\n\nThis report provides a comparative overview of the various movement types of Syrian,\n\n\nand where applicable other, refugees in Türkiye. The report focuses on refugees\n\n\nsearch for temporary, or more sustainable, solutions inside or outside of the country,\n\n\ntheir demographic profiles, choices, needs and perceptions. This analysis of refugee\n\n\nmovements and their dynamics, post-earthquake (and post-2023 elections) seeks to\n\n\nassist future planning, including where appropriate, the adaptation of the response.\n\n\nThis report analyses data from 1 January - 31 December 2023, and uses both\n\n\nqualitative and quantitative data to enable cross-verification. This enables", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data from 1 January - 31 December 2023"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000759", "page": 3, "chunk": 0, "title": "2023 Post-Earthquake Population Dynamics Analysis - Türkiye", "pdf_url": "https://reliefweb.int/attachments/6ee003d6-58b7-4899-9a77-e1772778be15/UNHCR%20-%202023%20Population%20Dynamics%20post%20EQ.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from 1 January - 31 December 2023", "label": "VAGUE_DATA", "score": 0.6913726925849915, "start": 2038, "end": 2076, "probe_score": 0.8749, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "discussion revolves around students who face a language barrier. Incorporating statistics\n\nfor 2020 and 2021 could also shed light on the interaction of this educational integration\n\nprocess with the effect of the COVID-19 pandemic, which had catastrophic effects on\n\neducational systems around the world (UNICEF, 2022)\n\n\nMigrant students face obstacles at every step of the way, and well-formulated,\n\nevidence-based policies could help close the widening gap in access to educational opportunities vis-A -vis their native peers. <sup>˜</sup> This study is the first to analyze the differential\n\neffect of student aid on migrants and natives. Future studies should continue providing\n\nmore and better evidence to improve financial aid policies and increase access to higher\n\neducation.\n\n\n26", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["statistics\n\nfor 2020 and 2021"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000931", "page": 27, "chunk": 0, "title": "idu098e3e45807dbf0416d0b96c006008f32a01a", "pdf_url": "https://local/prwp/idu098e3e45807dbf0416d0b96c006008f32a01a.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistics\n\nfor 2020 and 2021", "label": "VAGUE_DATA", "score": 0.7048173546791077, "start": 79, "end": 108, "probe_score": 0.9532, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Irregular Maritime Movements – UNHCR Regional Office for South-East Asia\n\n\n# DEPARTURE\n\n\n\n\n\n\n- In the 12 months ending June 2014, UNHCR estimates that some\n53,000 people departed irregularly by sea from the BangladeshMyanmar border area in the Bay of Bengal, a 61 per cent increase\nfrom the previous 12 months.\n\n- As in previous years, departures from the Bangladesh-Myanmar\nborder peaked during the traditional sailing season from October to\nJanuary. Since June 2012, over half of all estimated departures took\nplace between the months of October and January.\n\nborder set out most frequently from Teknaf, Bangladesh, and from\nMaungdaw, Myanmar. Away from the border area, an estimated\n7,500 additional departures have originated from the Sittwe area in\nMyanmar since June 2012.\n\n- In the first half of 2014, Bangladeshi authorities reportedly arrested over 700 people (including smugglers and crew)\nattempting to depart irregularly by sea from Bangladesh.\n\n- UNHCR interviewed recent maritime arrivals in Thailand and Malaysia who travelled on boats that accounted for as\nmany as 10,000 departures since October 2013; 40 per cent of individuals interviewed by UNHCR were\nunaccompanied minors under the age of 18.\n\n- Virtually all maritime arrivals in Thailand had intended to travel to Malaysia, where many had family members. Most\nwere either referred to smugglers by family and friends or recruited from their villages by smugglers.\n\n- Individuals departing from the Bangladesh-Myanmar border paid between USD 50-300 to board departure vessels.\nSmall boats ferried groups of 5-30 passengers to larger fishing or cargo vessels with capacities typically ranging from\n100-700 passengers.\n\n\n\n\n\n\n\n10000\n\n\n8000\n\n\n6000\n\n\n4000\n\n\n2000\n\n\n0\n\n\n\nEstimated Irregular Maritime Departures from the Bangladesh-Myanmar Border\n\nJuly 2012 – June 2014\n\n\nJul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun\n\n\nUnited Nations High Commissioner for Refugees (UNHCR) – www.unhcr.org\n\n2", "output": {"entities": {"named_data": ["Estimated Irregular Maritime Departures from the Bangladesh-Myanmar Border"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001613", "page": 1, "chunk": 0, "title": "South-East Asia Irregular Maritime Movements", "pdf_url": "https://reliefweb.int/attachments/f9af21aa-85ae-302c-a109-09a3a22e4018/UNHCR%20-%20Irregular%20maritime%20movements.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Estimated Irregular Maritime Departures from the Bangladesh-Myanmar Border", "label": "NAMED_DATA", "score": 0.5836639404296875, "start": 1736, "end": 1810, "probe_score": 0.9534, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", more bank-based financial systems. It is also\nconsistent with the presence of financial frictions that vary by country and institutional\nenvironment. <sup>24</sup> [^24: Barrell and Davis (2005) analyse 13 European Union countries and the United States, and find a\nstronger association between equity prices and output in market-based than in bank-based financial\nsystems. Using data for 16 OECD countries, Ludwig and Slok (2004) show that the long-run\nresponsiveness of consumption to permanent changes in stock prices is higher for market-based than\nfor bank-based systems.]\n\n\nThe reaction of investment and consumption to changes in asset prices also appears to\ndepend in part on legal regimes and traditions. Empirical analysis by Claessens et al (2014b)\nsuggests that the responses of investment to changes in q are faster in countries with better\ncorporate governance and information systems. They interpret this as evidence of fewer\nfinancial frictions in such countries. The effects of house price changes on household\nconsumption can also depend on a country’s financial system and institutional environment\nin ways that suggest the presence of certain financial frictions.\n\n\nLimits to the predictive power of asset prices\n\n\nThere are limits to the predictive value of asset prices. Such limits appear to vary by type of\nasset and financial system. The standard theory implies that asset prices should be good\nproxies for expected growth (at both microeconomic and macroeconomic levels) because they\nare forward-looking. Equity prices, however, with their low signal-to-noise ratio and their\n(excess) volatility, do not have a good record of forecasting general economic developments.\nWhile equity prices have some predictive ability for investment, they do not generally increase\nthe out-of-sample forecasting ability of GDP when compared with other economic variables\n(see Aylward and Glen (2000)). This observation is succinctly described by the well-known\n\n\n23 For reviews of these issues, see Davis and Van Nieuwerburgh (2015), Iacoviello (2004) and Piazzesi\nand Schneider (2016).\n24 Barrell and Davis (2005) analyse 13 European Union countries and the United States,", "output": {"entities": {"named_data": [], "descriptive_data": ["data for 16 OECD countries"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007217", "page": 21, "chunk": 1, "title": "wps8259", "pdf_url": "https://local/prwp/wps8259.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data for 16 OECD countries", "label": "DESCRIPTIVE_DATA", "score": 0.8480111956596375, "start": 381, "end": 407, "probe_score": 0.9943, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on social development issues"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000129", "page": 24, "chunk": 0, "title": "Cambodia - Demobilization and Reintegration Project", "pdf_url": "http://documents1.worldbank.org/curated/en/753121468769494084/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on social development issues", "label": "VAGUE_DATA", "score": 0.581004798412323, "start": 1670, "end": 1703, "probe_score": 0.333, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". (2012). Index of Global Philanthropy and Remittances.\n\nAvailable at: http://www.hudson.org/files/publications/2012IndexofGlobalPhilanthropyandRemittances.pdf\n\n\nCERF Secretariat. (2010). Central Emergency Response Fund Life-Saving Criteria.\n\nAvailable at: https://docs.unocha.org/sites/dms/CERF/FINAL_Life-Saving_Criteria_26_Jan_2010__EFS.pdf\n\n\nCERF Secretariat. (2011). CERF Funding Specific Sector Protection.\n\nAvailable at: https://ochanet.unocha.org/p/Documents/Funding%20of%20Protection%20FINAL%2023%20\nSeptember%202011.pdf\n\n\nChannel Research. (2011). 5-year evaluation of the Central Emergency Response Fund – Final Synthesis Report.\n\nAvailable at:\nhttps://ochanet.unocha.org/p/Documents/110811%20CERF%20Evaluation%20Report%20v5.4%20Final.pdf\n\n\nCICR. (2013). Standards professionnels pour les activités de protection menées par les organisations humanitaires\n\net de défense des droits de l’homme lors de conflits armés et d’autres situations de violence\nAvailable at: http://www.icrc.org/fre/assets/files/other/icrc-001-0999.pdf\n\n\nCollinson, Sarah; Buchanan-Smith, Margie & Elhawary, Samir. (2009) Good Humanitarian Donorship Principles in\n\nPractice: Assessing humanitarian assistance to internally displaced persons in Sudan and Sri Lanka. HPG/ODI.\nAvailable at: http://www.odi.org.uk/sites/odi.org.uk/files/odi-assets", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001007", "page": 65, "chunk": 1, "title": "Placer la protection au cœur de l’action humanitaire: Etude sur le financement de la protection dans les situations d’urgence humanitaire complexes", "pdf_url": "https://reliefweb.int/attachments/97ac79d1-3da2-30e3-a535-139a5c135b12/GPC_funding_study_print_FR.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "000 jobs per year to keep up with the growing working-age population** <sup>**2**</sup> **.** Uganda\ncurrently relies heavily on low productivity agriculture, which amounts to about 25% of the economy, 50% of exports\nand 70% of employment. To keep up with growth in the labor force, the economy needs to create 700,000 jobs per\nyear, which far exceeds the 75,000 jobs that are currently created each year. Raising incomes further will require\nimproving productivity in agriculture and exploring opportunities for absorbing excess labor into more productive\nemployment in industry and services.\n\n\n6. **Uganda’s labor market is characterized by scarce employment opportunities that are concentrated in the informal**\n**sector** . Only half of working-age Ugandans are active in the labor force, and 48 percent are employed. Labor force\n\n\nJun 14, 2021 Page 3 of 14", "output": {"entities": {"named_data": [], "descriptive_data": ["Labor force"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000016", "page": 2, "chunk": 2, "title": "Concept Project Information Document (PID) - Uganda Skills Development in Refugee and Host Communities - P176263", "pdf_url": "http://documents.worldbank.org/curated/en/336661632309532618/pdf/Concept-Project-Information-Document-PID-Uganda-Skills-Development-in-Refugee-and-Host-Communities-P176263.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Labor force", "label": "DESCRIPTIVE_DATA", "score": 0.5557088255882263, "start": 822, "end": 833, "probe_score": 0.5221, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSupport for Social Recovery Needs of Vulnerable Groups in Beirut (P176622)\n\n\nand structural vulnerabilities prior to the Beirut port explosion exacerbated the vulnerabilities of People with\nDisabilities and Older Persons. In fact, at the end of 2019, the Ministry of Social Affairs – which had previously delivered\nservices to people with disabilities – rescinded its support services due to budgetary shortages. In turn, civil society\npartners providing services to People with Disabilities and Older Persons recorded a significant increase in their\nLebanese caseload over the course of 2020. <sup>45</sup> In late May 2020, a Rapid Needs Assessment conducted by HelpAge\nInternational in Beirut identified that 68% of people aged 50 and above had at least one disability or impairment. <sup>46</sup>\nElderly women who live alone are particularly vulnerable, given their greater likelihood of not having access to savings,\npensions and other social protection instruments. <sup>47</sup>\n\n**21.** **The heightened needs of People with Disabilities and Older Persons** **during and after crises has been well-**\n**documented with strong evidence showing that these needs are often overlooked.** <sup>**48**</sup> In the immediate aftermath of\nthe blast, cash assistance and shelter support were identified as key areas for emergency support, while access to\nmedical supplies and services were identified as top priorities for People with Disabilities and Older Persons in the\nmedium to longer term. In a survey of a sample of residents of the POB area from all age groups, 34% reported that\ntheir family had difficulties accessing health services and 45% reported difficulties accessing medicines. <sup>49</sup> This was a\nparticular concern for 65% of older person-headed households who have a chronic disease that require medicine and\nare at a heightened risk of contracting CO", "output": {"entities": {"named_data": ["Rapid Needs Assessment"], "descriptive_data": ["survey of a sample of residents"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000054", "page": 8, "chunk": 0, "title": "Concept Project Information Document (PID) - Support for Social Recovery Needs of Vulnerable Groups in Beirut - P176622", "pdf_url": "http://documents.worldbank.org/curated/en/883871626924990781/pdf/Concept-Project-Information-Document-PID-Support-for-Social-Recovery-Needs-of-Vulnerable-Groups-in-Beirut-P176622.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Rapid Needs Assessment", "label": "NAMED_DATA", "score": 0.6377810835838318, "start": 647, "end": 669, "probe_score": 0.7994, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey of a sample of residents", "label": "DESCRIPTIVE_DATA", "score": 0.6627276539802551, "start": 1521, "end": 1552, "probe_score": 0.9074, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " stated above, in the midst of contradictions between these policies, the 2017 Foreigners\nLaw is followed in practice. At the request of the Government, UNHCR generates refugee identity cards\nbased on information from the refugee database. These are subsequently handed over to CNAR, which in\nturn formally issues them.\n\n\n6 R E F U G E E P O L I C Y R E V I E W F R A M E W O R K - C O U N T R Y S U M M A R Y > **R E P U B L I C O F T H E C O N G O**", "output": {"entities": {"named_data": [], "descriptive_data": ["refugee database"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001408", "page": 5, "chunk": 3, "title": "Republic of the Congo: Refugee Policy Review Framework Country Summary as at 30 June 2020 (March 2022)", "pdf_url": "https://reliefweb.int/attachments/da25229b-2e72-3ef1-aa3a-cda946f837ae/ROC%20-%20Refugee%20Policy%20Review.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "refugee database", "label": "DESCRIPTIVE_DATA", "score": 0.7797843813896179, "start": 222, "end": 238, "probe_score": 0.0149, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " circular migration, with Ukrainians\ncoming to Poland for half of the year,\nthen returning to Ukraine for another six\nmonths, and coming back to Poland. The\ndata on employers’ declarations do not\nreveal the actual number of Ukrainian\ncitizens who followed this system – a single\nperson could hold several declarations,\nbecause with every change of employer\nor promotion at the same employer they\nhad to ask for a new declaration. What is\nmore, with stays shorter than one year,\n\n\n\nthose people fell outside the definitions\nof population used by Statistics Poland\n(Główny Urząd Statystyczny, GUS,\nPoland’s statistical office). The National\nBank of Poland estimated that between\n2014 and 2018, there were approximately\none to two million Ukrainian workers\nin Poland at a time (Strzelecki, Growiec\nand Wyszyński, 2022). According to the\n2021 Polish National Census, one year\nbefore the outbreak of the full-scale war\nin Ukraine there were about one million\nUkrainian citizens residing in Poland,\nalmost all of them on a temporary basis.\n\n\n\nAfter the full-scale Russian invasion of\nUkraine, Poland experienced a massive\ninflux of refugees – with more than\n27 million border crossings from Ukraine\nand more than 1.9 million applications for\nprotection submitted by April 7, 2025 <sup>1</sup> . Not\nall of those people stayed in Poland. Many\n\n\n\nof them later returned to Ukraine or moved\nto other countries. By February 14, 2025,\nPESEL UKR <sup>2</sup> [^2: PESEL UKR is a version of Polish national ID number for Ukrainian citizens in connection with the armed conflict in the territory of that country.] holders who remained\nin Poland stood at less than 1 million,\nwhile the border movement balance\nbetween Poland and Ukraine was slightly\nbelow 2 million.\n\n\n\n1 UNHCR data, <u>https://data2.unhcr.org/en/situations/ukraine</u>\n\n2 PESEL UKR is a version of Polish national ID number for Ukrainian citizens in connection with the armed conflict in", "output": {"entities": {"named_data": ["2021 Polish National Census", "UNHCR data"], "descriptive_data": ["data on employers’ declarations"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 3, "chunk": 1, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on employers’ declarations", "label": "DESCRIPTIVE_DATA", "score": 0.9036956429481506, "start": 157, "end": 188, "probe_score": 0.2361, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2021 Polish National Census", "label": "NAMED_DATA", "score": 0.8957979083061218, "start": 834, "end": 861, "probe_score": 0.6833, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHCR data", "label": "NAMED_DATA", "score": 0.7753179669380188, "start": 1757, "end": 1767, "probe_score": 0.9905, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " expanded and support was\nprovided to run an information\ncampaign on refugee employment\nrights.\n\n\nA training program was completed\nfor ISKUR personnel nationwide\nTurkey in order to ensure inclusion\nof refugees in ISKUR services\nand uniform service provision in\nall provinces of Turkey for refugee\nlivelihoods.\n\n\n\nThe training was completed in\nDecember, a total of 272 staff\nhave been trained on International\nand Temporary Protection Turkey.\nSignificant support has also been\nprovided to the Directorate General\nof Migration Management (DGMM)\non verification activities.\n\n\n\n\n\n<u>36</u>", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001030", "page": 34, "chunk": 1, "title": "(3RP) Regional Refugee and Resilience Plan 2017 - 2018 in response to the Syria Crisis | 2017 Annual Report [EN/AR]", "pdf_url": "https://reliefweb.int/attachments/9d0a64cf-a831-30be-8e02-dcfa7bd8a7f5/63530.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "without regard for the opportunity cost of public spending on health. A clear majority of\n\n\ncitizens respond that any additional public spending for their area be allocated to health and\n\n\nnutrition services for their children rather than to cash transfers, job creation programs, or\n\nroads (Table 2). <sup>14</sup> On a simple question about price subsidies that we tried out–whether gov\n\nernments should provide electricity for free– as many as 25 percent of respondents answered\n\n\nno, without any qualification, while 34 percent qualified that subsidies could be targeted to\n\n\npoor people. These responses from the average citizen respondent stand in contrast to the\n\n\nresponses from those who were identified in the data as leaders of the village SHG–only 17\n\n\npercent of SHG leaders answered no, and 52 percent answered with an unqualified yes, com\npared to only 40 percent of citizens saying yes (Table 3). <sup>15</sup> This pattern of citizen responses is\n\n\neven more striking when compared with how the higher income and educated respondents,\n\n\nsuch as doctors, in our sample answered this question. Among doctors, for example, 57 per\n\ncent answered with an unqualified yes, that governments should provide free electricity, with\n\n\nonly 6 percent saying no.\n\n\nCitizen responses to another set of questions– on whether they would vote for a candidate\n\n\nfor village Mukhiya who offers inducements at the time of elections, such as a gift or cash in\n\n\nexchange for votes–suggest a more sophisticated political way of thinking than one of gullible\n\n\nor cynical voters who are easy prey to vote-buying strategies. Only 10 percent of citizens\n\n\nanswer that they would vote for the gift-giving or bribing candidate, with 89 percent saying\n\n\nthey would not. It is not easy to dismiss these responses as arising only from social desirability\n\n\nbias because other respondents– those that are identified in the data as leaders of the village\n\n\nSHG, and the village ANMs–who may be equally subject to the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002119", "page": 28, "chunk": 0, "title": "strengthening public health systems policy ideas from a governance perspective", "pdf_url": "https://local/prwp/strengthening-public-health-systems-policy-ideas-from-a-governance-perspective.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a v\nManufacturIng 5 7 3.7 4 7 5 0 / s \\\\t oo  Services 475 272 190 201\n\nPrfvate consumpffon 90 7 81 9 938 95 1 20\nGeneral govemment consumption 7 0 9 6 146 17.2 =c ~GDFDl\nImpons of goods and servrcea 39 7 23 6 33 4 373 -3GW_G_____\n\n\n_(average_ _annual growth)_ 1981-9 1991401 2000 2001 Growth ot exports and Imports (%)\n\nAgrutumre -0 6 -2 6 2 2 3 8 oo\nIndustry 0.1 -41 51 5 6 s0\nManUnacturIng 6.9 . .\nServices -5 7 -5.4 4 0 51 \nPrivate oonsumpffon -2 0 -19 10 4 100 -50\nGeneral govemment consumption -5.1 -0 2 41.3 27 9 -100\nGross domestic Investment -06 3 0 50 - EOpois -tr-ports\nImports of goods and services -2 2 -151 85 0 61 3\n\n\nNote 2001 data are pretirrinary eastliates\n'The diamonds show four Key Indicators in the country (in bold) conipared with itS income-group average It data are missing, the diantond wiUt be rrconrrlte\n\n\n-56", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["2001 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000151", "page": 60, "chunk": 2, "title": "Bosnia and Herzegovina - Third Electric Power Reconstruction Project", "pdf_url": "http://documents1.worldbank.org/curated/en/873371468767980151/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2001 data", "label": "VAGUE_DATA", "score": 0.7082152366638184, "start": 639, "end": 648, "probe_score": 0.0183, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "* Following the crisis in 1991, the initial post-crisis years witnessed a strong positive\nresponse from investment and growth. In the first half of the nineties, deregulation of industry\nand foreign trade, strong export performance and the overall reform momentum drove investment\nhigher. The fixed investment surge was particularly strong in the manufacturing sector. As\nshown in Figure 3 below, investment intentions filed in industry more than doubled from 3038 in\n1991 to 6502 in 1995 and the proposed total investment also increased rapidly (from\napproximately Rs. 76310 crores in 1991 to Rs. 125509 crores in 1995).\n\n\n11", "output": {"entities": {"named_data": [], "descriptive_data": ["investment intentions filed in industry"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003448", "page": 10, "chunk": 2, "title": "wps4241", "pdf_url": "https://local/prwp/wps4241.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "investment intentions filed in industry", "label": "DESCRIPTIVE_DATA", "score": 0.5456949472427368, "start": 397, "end": 436, "probe_score": 0.9561, "gold": "DATA_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**PRESENTACIÓN**\n# **Dr.**\n\n\n\n**ROBERTO**\n**HERRERA CÁCERES**\n\n\n###### **L**\n\n\n\na Institución del Comisionado Nacional de los Derechos Humanos de Honduras (CONADEH) mediante la Unidad\nde Desplazamiento Forzado Interno (UDFI), adscrita a la Defensoría Nacional de las Personas Migrantes, Pueblos\nIndígenas y Afro-hondureños y Adulto Mayor, presenta el Segundo Informe Especial sobre el Desplazamiento For###### L zado Interno en Honduras: El informe está basado en la identificación de casos en los Registros de Quejas de las Oficinas\n\nRegionales y Departamentales, a nivel nacional, en el período comprendido entre el 1 de enero al 31 de diciembre de\n2017. Esta publicación ha sido posible gracias al apoyo del Alto Comisionado de las Naciones Unidas para los Refugiados\n(ACNUR).\n\n\n\nEl objetivo del informe especial es analizar los perfiles de riesgo, patrones, tendencias y zonas de mayor afectación por\nel desplazamiento forzado interno, con particular énfasis en la población con mayores necesidades de protección, con\nla finalidad de emitir recomendaciones para la protección local y nacional de las personas desplazadas internas que son\nvíctimas de múltiples violaciones de sus derechos humanos.\n\n\nEl CONADEH, mediante este informe, lanza un enérgico y urgente llamado de atención sobre la necesidad de establecer\nsiner", "output": {"entities": {"named_data": ["Registros de Quejas"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000291", "page": 6, "chunk": 0, "title": "Informe Especial: El Desplazamiento Forzado Interno en Honduras", "pdf_url": "https://reliefweb.int/attachments/21e1ba6a-7c7c-34a1-8247-aa2285b055b1/INFORME-DESPLAZAMIENTO-BOCETO-ACNUR.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Registros de Quejas", "label": "NAMED_DATA", "score": 0.746177613735199, "start": 498, "end": 517, "probe_score": 0.5756, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "........................................................................................ 21\n\n\n5. CONCLUSION ...................................................................................................................... 23\n\n\n**Figures & Tables**\n\n\nFigure 1. Displacement as of 8 July 2015……………………………………………………………………………………………..5\n\n\nFigure 2. Displacement as of 30 September 2015………………………………………………………………………………..5\n\n\nFigure 3. Family tracing and reunification data, per quarter, 2015……………………………………………………….6\n\n\nFigure 4. Types of GBV reported in the South Sudan GBV IMS, per quarter, 2015…………………………………8\n\n\nFigure 5. Incidents of grave violations reported to", "output": {"entities": {"named_data": ["GBV IMS"], "descriptive_data": ["Family tracing and reunification data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000601", "page": 1, "chunk": 6, "title": "Protection Trends South Sudan No 6 | July-September 2015 - South Sudan Protection Cluster, November 2015", "pdf_url": "https://reliefweb.int/attachments/589205c5-62ff-3033-8221-c68e4b07017a/protection_trends_paper_no_6_jul-sep_2015_final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Family tracing and reunification data", "label": "DESCRIPTIVE_DATA", "score": 0.7888814806938171, "start": 428, "end": 465, "probe_score": 0.9802, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "GBV IMS", "label": "NAMED_DATA", "score": 0.5122778415679932, "start": 561, "end": 568, "probe_score": 0.9576, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". <sup>84</sup> Inability to pay rent was the most common reason for eviction. <sup>85</sup> [^85: UNHCR, UNICEF and WFP, “VASyR 2020.”]\nIn the first half of 2020, 2,236 Syrians were evicted in the two governorates, constituting a 62 percent increase\ncompared to the first half of 2019. <sup>86</sup> [^86: Inter-Agency Coordination Lebanon, “In Focus - Rise in Evictions due to Increased Economic Vulnerability (July 2020).”]\n\n**5.** **With an oversupply of high-income housing and an underserved low-income housing market, a large**\n**and increasing share of Beirut City’s residents are suffering from a lack of affordable and adequate housing.**\nTypically, homeowners are middle-income families with access to low-interest housing mortgages who have found\nthe housing that they seek outside the boundaries of Beirut Municipality, within the greater city area. <sup>87</sup> [^87: CAS (2007)] On the\nother hand, the pressing housing needs have led many refugees, migrants and urban poor to settle in informal\nareas at the outskirts of the city or in overcrowded inner-city housing units, often with insecure tenure,\ndeteriorating living conditions, and inflating prices. These markets that were estimated to accommodate 30\npercent of the Greater Beirut population before the current Syrian crisis, typically combine several forms of\ninformality, such as violations of building and construction codes, urban regulations, and property rights, and\nsingle apartments with multiple sales. <sup>88</sup> [^88: UN-Habitat and UNHCR. (2014). Housing, land & property issues in Lebanon: Implications of the Syrian refugee crisis. New York: United Nations.]\n\n\n80 UN-Habitat, “Guide for Mainstreaming Housing in Lebanon’s National Urban Policy.”\n81 UN-Habitat, “Guide for Mainstreaming Housing in Lebanon’s National Urban Policyco", "output": {"entities": {"named_data": ["VASyR 2020"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000034", "page": 56, "chunk": 1, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents1.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "VASyR 2020", "label": "NAMED_DATA", "score": 0.6494830250740051, "start": 123, "end": 133, "probe_score": 0.9411, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\n<u>[examined by the Commission for Monitoring and Analysis of Domestic](https://cdf.md/category/publicatii/)</u>\n<u>[Violence Cases Resulting in Death or Serious Bodily Harm, 2023](https://cdf.md/category/publicatii/)</u>\n\n\n\nfindings from the 2022 <sup>8</sup> and 2024 <sup>9</sup> [^9: <u>[Ukraine Situation - Moldova. GBV Sub-Working Group GBV Safety Audit](https://data.unhcr.org/en/documents/details/108377)</u>\n<u>[Report, 2024](https://data.unhcr.org/en/documents/details/108377)</u>] GBV Safety Audits, conducted\nby the GBV Sub-Working Group, refugee women and girls in\nMoldova remain at risk of GBV and SEA, including at Refugee\nAccommodation Centres (RACs) and private accommodations.\nFurthermore, Intimate Partner Violence (IPV) remains a serious\nissue and deeply rooted in rigid gender roles, and manifests\nthrough physical and sexual abuse, as well as psychological\nviolence and denial of resources. Some groups, such as Roma\nwomen, women with disabilities, and adolescent girls, are at\nhigher risk of GBV and human trafficking due to discrimination\nand multiple barriers they face. Reduced ability to meet basic\nneeds, separation from protective networks, and limited access\nto protection support and to services are among the factors\nthat further increase GBV risks for refugee women.\n\n\n8 <u>[Ukraine Situation - Moldova. GBV Sub-Working Group GBV Safety Audit](https://data.unhcr.org/en/documents/details/95741)</u>\n<u>[Report, 2022](https://data.unhcr.org/en/documents/details/95741)</u>\n9 <u>[Ukraine", "output": {"entities": {"named_data": ["GBV Safety Audits"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000122", "page": 14, "chunk": 2, "title": "Barriers to the disclosure of Gender-Based Violence (GBV) including Violence Against Women and Sexual Exploitation and Abuse (SEA) in Moldova", "pdf_url": "https://reliefweb.int/attachments/07b53dcf-4e1f-43c1-b4a2-22bc9d3d8007/Barriers%20to%20the%20Disclosure%20of%20GBV%20UNHCR%20National%20Coalition%20Moldova.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "GBV Safety Audits", "label": "NAMED_DATA", "score": 0.569658100605011, "start": 493, "end": 510, "probe_score": 0.5238, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " foundation for democratic and sustainable local\n\n\n\ndevelopment. The Community Development Program will finance social and economic\ninfrastructure and support social capital building activities to facilitate the restoration of basic\nsocial services such as health and education and provide an incentive for teachers, health workers\nand displaced persons to return to their communities. The Rural Public Works and Shelter\nprograms will provide employment for demobilized soldiers and unemployed youth, housing for\ndisplaced persons and feeder roads to stimulate local economic activities. The innovative\nactivities including training and technical support will strengthen local government capacity to\nplan, contract, manage and sustain investments in local development and engage a wide array of\n\n\n\nstakeholders in participatory processes that contribute to sustainable local development.\n\n\n\nTargeting will be consistent with the Government's 2002-2003 National Recovery\nStrategy and the March 3, 2002 Transitional Support Strategy. Resources will be directed to (a)\nnewly accessible areas that have not received any support in more than a decade; and (b) remote\nareas that have received little, if any support from the ongoing IDA-financed CRRP or other\nsimilar projects. The results of the living standards measurement survey currently underway will\nbe available at the end of 2003 and will be used to review the validity of existing targeting\nmodalities.\n\n\nTarget Populations: Target groups include demobilized soldiers and unemployed youth,\nrefugees, IDPs, female-headed households, child laborers, orphans, primary school dropouts,\n\n\n_- 8 -_", "output": {"entities": {"named_data": [], "descriptive_data": ["living standards measurement survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000117", "page": 12, "chunk": 1, "title": "Sierra Leone - Rehabilitation of Basic Education Project", "pdf_url": "http://documents1.worldbank.org/curated/en/680761468763817221/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "living standards measurement survey", "label": "DESCRIPTIVE_DATA", "score": 0.8663687705993652, "start": 1291, "end": 1326, "probe_score": 0.7112, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Egyptian bid-ask spread information is unfortunately not readily available to analyze patterns\nover time. It is however possible to estimate transaction costs based on the incidence of zeroreturn trading days, days on which no price movement was recorded. The assumption underlying\nthis statistical model is that the marginal investor will not execute a trade unless the profit net of\nall transaction costs is positive. The model’s estimates in Exhibit 3.9 suggest that transaction\ncosts have come down in the whole benchmark group compared to 2005. In particular, Egypt’s\ntransaction costs have come down from over 130 basis points in 2005 to around 50 basis points\nfor 2008 and could be the lowest in the region.\n\n**Exhibit 3.9 – Transaction costs**\n_Transaction cost decomposition in 2007:Q2 for selected countries, basis points (left graph)_\n_Round-trip transaction cost estimates for the 25 largest stocks in Egypt and Qatar, 2005-08 (right_\n_Exhibit)_\n\n\n\n\n\n\n\n**<u>Country</u>** **<u>2005</u>** **<u>2006</u>** **<u>2007</u>** **<u>2008</u>**\n**<u>Abu Dabhi</u>** <u>8.79%</u> <u>6.82%</u> <u>4.22%</u> <u>4.83%</u>\n**Amman** 1.95% 1.30% 1.23% 1.24%\n**Cairo** 1.32% 0.74% 0.44% 0.52%\n**Casablanca** 2.48% 1.98% 1.73% 1.23%\n**Kuwait** 3.18", "output": {"entities": {"named_data": [], "descriptive_data": ["Egyptian bid-ask spread information"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004405", "page": 31, "chunk": 0, "title": "wps5213", "pdf_url": "https://local/prwp/wps5213.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Egyptian bid-ask spread information", "label": "DESCRIPTIVE_DATA", "score": 0.8369497060775757, "start": 0, "end": 35, "probe_score": 0.9717, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", has six\ninterconnected strategic themes: (i) implementation of the statistics law, which mainly pertains to\nthe coordination of the NSS and establishment of appropriate organizational units and standards;\n(ii) development of data quality procedures, which corresponds to the development of data quality\nassessment framework (DQAF), coordinated by the CSA for the NSS; (iii) enhancement of\nadvocacy and use of statistics through promotion of a common website for the NSS, and training of\nstakeholders; (iv) methodological improvements and statistical modernization, which relates to\nidentification and filling of data gaps and reduction of duplication of surveys; (v) Capacity\ndevelopment in the NSS to meet the increased demand for statistics, which involves investments\nthat improve organizational arrangements, enhance training and availability of skilled staff,\nencourage staff retention and reduce turnover, leverage ICT for quick data capture and\ndissemination, provide additional space, furniture and appropriate facilities for a conducive work\nenvironment and efficient operations; and (vi) relating the NSDS to the Monitoring and Evaluation\nof PASDEP and other interventions such as MDGs.\n\nThe CSA has two objectives: (i) to plan, collect, process, and disseminate statistical data and (ii) to\nlead national coordination and provide technical guidance and assistance to government agencies\nand institutions in building administrative systems and registers (See Figure 1). It is the principal\ncollector, aggregator and disseminator of official statistics and the coordinator of the National\nStatistical System (NSS) . The CSA has a staff of almost 2500, of which approximately 50 are\nmanagers, 380 are statisticians, 400 are technical and administrative professionals, 1400 are support\nstaff, and 250 logistical staff. Its annual budget (both capital and recurrent) is about US$10 million,\nof which about 30 percent is for staff salaries and the rest for surveys and operations (2012). This\nfunding model of the CSA differs favorably from many other statistical offices in Africa that\nusually fund staff salaries but do not provide budget for conducting surveys. In", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014954", "page": 2, "chunk": 1, "title": "Project Information Document (Appraisal Stage) - Ethiopia Statistics for Results Facility - P147356", "pdf_url": "https://documents.worldbank.org/curated/en/570201468031730420/pdf/PID-Appraisal-Print-P147356-03-31-2014-1396246763598.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.6010182499885559, "start": 1275, "end": 1291, "probe_score": 0.1342, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "#### **Mixed movements**\n\n\n\nMixed movements of refugees and migrants present\nsignificant, multifaceted challenges for Southern\nAfrican countries, the individuals involved and\ncommunities in countries of origin, asylum, transit\n\nand destination. These movements occur along two\nmajor routes:\n\n\n- The Southern Africa route from East Africa,\nthe Horn of Africa and the Great Lakes region\ntowards South Africa.\n\n- The Western Indian Ocean route towards\nComoros and Mayotte.\n\n\n\nWhile refugees have distinct needs for international\nprotection, as recognized in international refugee\n\nlaw, they often use the same routes as migrants and\nface similar vulnerabilities and risks, such as falling\nprey to traffickers and smugglers.\n\n\nEffectively and predictably responding to the\nchallenges of mixed movements requires a routebased approach. This involves engaging States,\n\nRECs and other key players to ensure more humane\n\nand effective protection and solutions for refugees,\n\nwhile upholding rights and creating opportunities for\nmigrants, along key routes.\n\n\n\nLand Air Sea Unknown Not available\n\n\n**81%**\n\n\n**62%**\n\n\nZambia Malawi\n\n\nFIGURE 5: Type of route used by refugees and asylum-seekers to enter host countries\n\n\n\n\n\nRegional analysis of cross-border movements shows\n\nthat forcibly displaced persons use various routes (for\nexample by land, air and sea). The primary reasons\nfor leaving their home countries include insecurity,\nconflict, wars, instability, persecution and rebel\n\nactivities. Zambia and Malawi are particularly effective\n\n\n\nin reporting on routes used by registered refugees and\n\nasylum-seekers in the region. Consequently, refugees\n\nand asylum-seekers are disaggregated by their routes\n\nof arrival in Zambia and Malawi as shown in Figure 5.\n\n\nWith the standardization of the regional registration\ndataset, systems have been revamped to prioritize\n\n\n\n24 **Population Data Analysis** Mid-Year Review Regional Bureau for Southern Africa | June 2024", "output": {"entities": {"named_data": [], "descriptive_data": ["regional registration\ndataset"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001265", "page": 23, "chunk": 0, "title": "Population Data Analysis Mid-Year Review - Regional Bureau for Southern Africa, June 2024", "pdf_url": "https://reliefweb.int/attachments/c1b0b5a1-a214-4d2c-88a3-12ef55655e27/2024_Population%20Data%20Analysis%20mid%20year%20review.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "regional registration\ndataset", "label": "DESCRIPTIVE_DATA", "score": 0.8871619701385498, "start": 1789, "end": 1818, "probe_score": 0.1951, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and providing TA on service delivery (including for the drafting of policy documents such as a Service\nDelivery Manual by the PMO) and supports the strengthening of statistical information under the Jordan Growth MDTF.\n\n**43.** **Background analysis and international benchmarks inform the scope and design of the Program** **across its RAs,**\n**including its focus on health and education.**\n\n\n  - World Bank diagnostics and international benchmarks warrant the leveraging of government digitalization under\nthe Program, including for service delivery. Although Jordan ranks among the best performers across the world\n(in group A under both the 2022 World Bank GovTech Maturity Index and the UN E-Government Development\nIndex) in terms of its scoring and ranking on government digitalization, there is room for improvement on\nmodernization and interoperability of core systems, monitoring of the use and performance of digital platforms,\nand digital citizen engagement. Under the UN’s E-Government Development Index, Jordan’s score on e-services\nshows a significant improvement, rising from a score of 0.36 in 2020 to 0.66 in 2022, while still lagging the best\nregional performer.\n\n\nPage | 17", "output": {"entities": {"named_data": ["2022 World Bank GovTech Maturity Index", "UN E-Government Development\nIndex", "E-Government Development Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000181", "page": 26, "chunk": 2, "title": "Jordan - People-Centric Digital Government Program for Results", "pdf_url": "https://documents1.worldbank.org/curated/en/099030724150040202/pdf/BOSIB-70f97ae8-b741-401c-82cc-e87615cc5487.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2022 World Bank GovTech Maturity Index", "label": "NAMED_DATA", "score": 0.8260245323181152, "start": 647, "end": 685, "probe_score": 0.3197, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UN E-Government Development\nIndex", "label": "NAMED_DATA", "score": 0.7866147756576538, "start": 694, "end": 727, "probe_score": 0.9977, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "E-Government Development Index", "label": "NAMED_DATA", "score": 0.595703661441803, "start": 987, "end": 1017, "probe_score": 0.9383, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["M&E data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014070", "page": 29, "chunk": 2, "title": "Ethiopia - Water Supply and Sanitation Project", "pdf_url": "https://documents.worldbank.org/curated/en/510011468749368345/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "M&E data", "label": "VAGUE_DATA", "score": 0.5883201956748962, "start": 530, "end": 538, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "measures, and specific arrangements for the proposed project; and procurement arrangements\nand procedures.\n\n\n\n\n\n\n\n**B. The Public Financial Management Environment in Chad**\n\n\n6. The recent Country Financial Accountability Assessment, considered as an essential tool\nby the Government of Chad, identified the following weaknesses in the public financial\nmanagement environment in Chad: (i) the lack of a computerized accounting and budget\nexecution system; (ii) the absence of unified tracking of public expenditures, (iii) weak capacity\nof the control bodies; and (iv) insufficiencies in the management of petroleum resources. The\n\n\n32", "output": {"entities": {"named_data": ["Country Financial Accountability Assessment"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000007", "page": 41, "chunk": 0, "title": "Chad - Emergency Food and Livestock Crisis Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/179061468215115488/pdf/PAD11010PAD0P1010Box385329B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Country Financial Accountability Assessment", "label": "NAMED_DATA", "score": 0.6846345663070679, "start": 189, "end": 232, "probe_score": 0.7803, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " frequent. <sup>22</sup> The successive years of severe flooding demonstrate\nhow the seasonality, duration, and intensity of the rainy season is shifting affected by climate variability\nfactors such as El Niño Southern Oscillation and under the influence of climate change.\n\n\n14 For example, while women comprise 80 percent of the labor force in agriculture, they have little control over how the fruits of their labor are\nused or sold or access to income.\n15 https://www.rescue.org/sites/default/files/document/2294/southsudanlgsummaryreportonline.pdf.\n16 UNOCHA Global Humanitarian Overview 2021.\n17 Dubbury, N., et al. 2019. _Economic and Social Costs of Violence Against Women and Girls: South Sudan_ .\n18 What Works to Prevent Violence against Women and Girls in Conflict and Humanitarian Settings (2017), “No Safe Place: A Lifetime of Violence\nfor Conflict-Affected Women and Girls in South Sudan.”\n19 South Sudan faced severe droughts in 2011 and 2015 and severe flooding in 2014, 2017, 2019, 2020, and 2021.\n20 Global Rapid Post-Disaster Damage Estimation (GRADE) Note on May–October 2021 South Sudan Floods, November 5, 2021.\n21 FAO (Food and Agriculture Organization). 2015. _Gathering Weather Data to Provide Early Warning on Climate_ ; NUPI (Norwegian Institute of\nInternational Affairs)/ Stockholm International Peace Research Institute (SIPRI). 2021. Climate, Peace, and Security Fact Sheet South Sudan.\n22 USAID (United States Agency for International Development). 2019. _South Sudan Climate Vulnerability Profile_ .\n\n\nPage 10 of 73", "output": {"entities": {"named_data": ["Global Rapid Post-Disaster Damage Estimation"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000028", "page": 15, "chunk": 2, "title": "South Sudan - Second Phase of the Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/543171647442225562/pdf/South-Sudan-Second-Phase-of-the-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Global Rapid Post-Disaster Damage Estimation", "label": "NAMED_DATA", "score": 0.7143271565437317, "start": 1019, "end": 1063, "probe_score": 0.659, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".**\nUkrainian refugees earn the highest\nwages in manufacturing, health, and\naccommodation and food service activities,\nwhile the lowest in education, other\nservices, and construction. A comparison\nto median earnings in these sectors in the\neconomy as a whole (after recalculation\nfrom gross to net earnings) changes that\norder, with Ukrainian refugees employed in\naccommodation and food service activities,\nand construction earning more than\n100% of all workers median, and education,\nhealth services, and transportation and\nstorage on the lowest ranks. Earnings\n\n\n\nrelative to the total economy would be\nlower, if gross wages were compared,\nbecause Ukrainian refugees are less\nlikely to have employment contracts and\npay social contributions on their entire\nearnings. <sup>16</sup> Ukrainian refugees employed\nin education have the lowest median\nnet wages when compared to other\nsectors. This is likely due to occupational\nregulations that prevent persons with nonEU citizenship from working as teachers in\npublic schools, which is further discussed\nin chapter 4.\n\n\n\n4,198 4,216\n\n\nSource: Deloitte own elaboration based on SEIS UNHCR survey and GUS data.\n\n\n© UNHCR / Anna Liminowicz\n\n\n\n16 As refugees more often than average in the Polish economy work based on civil law contracts or self-employment, they may not be covered by employee\nprotections denoted in the labour code. Furthermore, if they pay lower pension contributions, they will receive lower pensions in the future, as Poland has a defined\ncontribution system. It also lowers their sick leave benefits.\n\n\n20\n\n\n\n21", "output": {"entities": {"named_data": ["SEIS UNHCR survey", "GUS data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 10, "chunk": 1, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS UNHCR survey", "label": "NAMED_DATA", "score": 0.90616375207901, "start": 1124, "end": 1141, "probe_score": 0.9874, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "GUS data", "label": "NAMED_DATA", "score": 0.8479775190353394, "start": 1146, "end": 1154, "probe_score": 0.8815, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_ .\n“CR5” denotes the concentration ratio of the top 5 investing firms. Country-industries averaging fewer than 5 foreign investors are excluded from these calculations. “HHI” refers to\nthe Herfindahl-Hirschman concentration index, calculated using the “CR5” sample. “log(#\nMNEs)” represents the natural logarithm of the number of foreign investors, and “log(K)”\ndenotes the natural logarithm of the average capital expenditure. “Uncertainty” is based\non the “T3” variable from the World [Uncertainty](https://worlduncertaintyindex.com/) database (Ahir et al. 2022), which counts\nthe occurrence of the word “uncertainty” from Economist Intelligence Unit (EIU) reports\nfor 143 countries since the 1950s. A higher value indicates greater uncertainty. Uncertainty\nin year _t_ is approximated as the logarithm of the average number of uncertainty-related\nwords in EIU reports over the three years preceding the investment (standardized to have\na mean of zero and a standard deviation of 1). The analysis includes country fixed effects\nand (world) region by year fixed effects. Countries are classified into 7 regions based on\nWorld Bank classifications. Destination-specific control variables include the logarithms of\npopulation and GDP (source: Conte et al. (2022)) and the average exchange rate over the\nthree years preceding the investment (national currency/USD, Penn World Tables, mark\n10.1, Feenstra et al. (2015)). Standard errors are clustered at the destination country level.\nSignificance levels: *** _p <_ 0 _._ 01, ** _p <_ 0 _._ 05,   - _p <_ 0 _._ 1.\n\n\n37", "output": {"entities": {"named_data": ["Penn World Tables"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001598", "page": 38, "chunk": 1, "title": "idu1e54dc5941f94514f8e1ad111ba1e6ee0513d", "pdf_url": "https://local/prwp/idu1e54dc5941f94514f8e1ad111ba1e6ee0513d.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Penn World Tables", "label": "NAMED_DATA", "score": 0.9007754325866699, "start": 1364, "end": 1381, "probe_score": 0.9971, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "/sup> And in an agropastoralist community\nin Uganda, children and elderly persons were among\nthe demographic groups most likely to stay in areas\nimpacted by climate variability and environmental\nstressors, while young men and women younger\nthan 25 were most likely to move. <sup>129</sup>\n\n\nMMC has also carried out **in-depth climate**\n**mobility case studies** in Africa to uncover\ncommunity perceptions, attitudes and decision\nmaking around mobility and immobility related to\nclimate change. <sup>130</sup> Survey interviews and focus\ngroups conducted in some contexts, such as in\nEgypt, revealed that mobility was not commonly\ncited as a response to climate-related hazards;\nrather, many people interviewed did not have the\nresources or capacity to migrate, nor the aspiration\nto do so, despite reports of numerous climate\nhazards in the area. <sup>131</sup>\n\n\n**IOM: Working with local pastoralist**\n**groups to mitigate conflict over**\n**resources**\n\n\n- Real-time availability of strong and reliable\nstatistical data that tracks movement\ninfluenced or shifted by climate change\ncan help policymakers and stakeholders\nunderstand changing patterns of mobility\nand avert, mitigate and manage conflict.\n\n\nTranshumance, or the seasonal movement of people\n\n\n\nand livestock across regions, is a long-standing\ntraditional practice and an important economic\nactivity and source of food security around the\nworld. In West and Central Africa, where roughly\n13 per cent of inhabitants are nomadic or seminomadic, <sup>132</sup> unpredictable periods of rainfall related\nto climate change have introduced challenges for\ntranshumant communities looking for pastures to\nfeed their animals, fertile farmland and sufficient\nwater points. This has shifted migratory routes\nand resulted in growing competition over scarcer\nresources, leading to tensions between farming and\nherding communities.\n\n\nIn order to prevent and reduce these conflicts,\nIOM developed the Transhumance Tracking", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001147", "page": 15, "chunk": 3, "title": "Climate mobility and childhood: Examining the risks, closing the data and evidence gaps for children on the move (September 12, 2024)", "pdf_url": "https://reliefweb.int/attachments/adc59d7d-0a63-473e-a78c-72cfb4f1f972/Climate-mobility-and-childhood_report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7365182042121887, "start": 1006, "end": 1022, "probe_score": 0.8055, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\nan interface between community and the county government that other development partners can\nutilize. <sup>86</sup> [^86: Types of capacity-building activities include familiarity with conflict/disaster risks and needs identification, resource mapping, local\ndevelopment planning, project identification, budgeting, project implementation, oversight/monitoring, and social audit methods.]\n\n\n11. BDCs are expected to meet frequently after members are selected and as technical assistance is\nprovided to help establish and strengthen their role. Weekly meetings are anticipated to select a\nchairperson, develop recourse mechanisms, conduct needs assessments, review planning and subproject\nselection processes, and develop lists of potential subprojects. BDCs are expected to meet less frequently\nand on an as-needed basis at later stages in the project cycle. Members will serve for terms of six months,\nrenewable, but can be removed by a vote of three-quarters of the membership in the event of\nnonparticipation or concerns over elite capture. Project lists are developed on a consensus basis.\nDependent on the status of COVID-19 precautions at the time of community engagement, additional\nprecautions will be taken to provide extra space for discussions, community planning, and training. BDC\nmobilization will also include COVID-19 sensitization as part of community engagement protocols to\nprotect both BDC and community members during community organizing efforts.\n\n\n12. **Communities’ priorities will be validated with local service mapping** so as to (a) avoid any\nduplications; (b) pool resources with neighbouring communities for common priorities; (c) link with other\nprograms to improve service delivery using the infrastructure built under the project where feasible; and\n(d) determine the technical feasibility of proposed investments. To move from mere infrastructure\nbuilding to service provision, the ECRP mobilization process builds in donor and local service mapping to\nensure that priority subprojects can synergize with other ongoing activities. <sup>87</sup>\n\n\n13. **Gender considerations** will", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 78, "chunk": 0, "title": "South Sudan - Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/824121596765983121/pdf/South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 2022, the registered Afghan refugee population\nwas 1,282,963.\n\n\nAccording to the government of Pakistan, as of June 2022 some 250,000 new Afghans have arrived since\nAugust 2021 <sup>6</sup> .\n\n\n**4** Fourth largest globally behind Türkiye, Colombia and Uganda.\n**5** As of 31 December 2021\n**6** [Data source: https://www.unhcr.org/news/press/2022/6/62aca7074/unhcr-deputy-chief-concludes-visit-afghanistan-pakistan-urges-support-](https://www.unhcr.org/news/press/2022/6/62aca7074/unhcr-deputy-chief-concludes-visit-afghanistan-pakistan-urges-support-address.html)\n[address.html](https://www.unhcr.org/news/press/2022/6/62aca7074/unhcr-deputy-chief-concludes-visit-afghanistan-pakistan-urges-support-address.html)\n\n\n8 Asia & the Pacific Regional Trends on Forced Displacement 2021", "output": {"entities": {"named_data": ["Asia & the Pacific Regional Trends on Forced Displacement"], "descriptive_data": ["registered Afghan refugee population"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000836", "page": 6, "chunk": 1, "title": "Asia & The Pacific Regional Trends - Forced Displacement 2021", "pdf_url": "https://reliefweb.int/attachments/7bf80633-63c0-4ae4-93ab-3cdec5c8f5c0/20220722_FINAL%20DRAFT_Regional%20Report%202021_reduced.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "registered Afghan refugee population", "label": "DESCRIPTIVE_DATA", "score": 0.5758842825889587, "start": 11, "end": 47, "probe_score": 0.975, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Asia & the Pacific Regional Trends on Forced Displacement", "label": "NAMED_DATA", "score": 0.530528724193573, "start": 720, "end": 777, "probe_score": 0.997, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " The sustainability of the sanitation measures will be carefully assessed from the point of view\nof good practices, cost effectiveness, affordability and the Djibouti water shortage environment.\n\n\n6. **Social**\n\n\n_6.1 Summarize key social issues relevant to the project objectives, and specify the project's social_\n_development outcomes._\n\n\nDjibouti is a small country and many key social issues were identified in the 1997 Poverty\n\nAssessment. The issues raised included the percentage of the population classified as poor in 1996\n(50-80% reaching the upper-bound when refugees, nomads and homeless are taken into account); large\nnumbers of refugees, nomads, and homeless populations; the majority of the poor live in urban areas\n(85%) even if the incidence of extreme poverty is overwhelmingly rural. Urban households can take\nadvantage of safety nets derived from the commodity market and services, and job opportunities are\nnot available in rural areas. The key problems faced by children include: (a) the high number of street\nchildren who have fled war ravaged Somalia and Ethiopia; (b) late entrance into school by poorer\nchildren (one out of four starts school at age 9 and leaves school at age 14); (c) health issues (diarrhea\n\nand malnutrition) are a leading cause of death for children under age 5. Other problems affecting the\nwhole population include respiratory infections on the increase (due to malnutrition); endemic health\nproblems (AIDS, tuberculosis, malaria, cholera); the widespread practice of Female Genital Mutilation\n(FGM); sanitation costs are high for poorer households not connected on the main water network as", "output": {"entities": {"named_data": ["1997 Poverty\n\nAssessment"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012903", "page": 23, "chunk": 1, "title": "Kenya - Second Coffee Improvement Project", "pdf_url": "https://documents.worldbank.org/curated/en/429231468283489544/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1997 Poverty\n\nAssessment", "label": "NAMED_DATA", "score": 0.810173511505127, "start": 420, "end": 444, "probe_score": 0.0723, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**VI.** **APPRAISAL SUMMARY**\n\n\n**A.** **Economic and Technical Analysis**\n\n\n56. The Project has several potential benefits which justify the investments in service\ndelivery and local economic development. Tangible benefits are the investments by\nmunicipalities in local infrastructure and services. Intangible benefits include the enhanced\nconsultative and participatory processes underlying service delivery, livelihood and local\neconomic development at the local level. At a broader level, the Project contributes to GOJ’s\ninstitutional reforms through capacitating municipalities, and enhancing emergency preparedness\nat the central, governorate and local government levels, and among vulnerable communities.\n\n57. Central government fiscal transfers to municipalities in 2013 were about US$105 million,\nwith little change expected in 2014. Additionally, own source revenues of municipalities are\naround 30 percent of total revenues while several municipalities receive project-based financing.\nThe per capita total municipal revenues in the selected nine municipalities range from US$42 to\nUS$127 annually. On the expenditure side, the bulk of resources goes into wages and operating\ncosts. Municipal Grants in year one will amount to approximately US$67 per refugee capita.\nThis will help participating municipalities ramp up services in a significant manner, as well as\npotentially provide a short term stimulus to the local economy.\n\n\n58. The types of public infrastructure that may be created under Component 1 are likely to\nyield a higher rate of return (production efficiencies) than those under alternative arrangements\n(through central agencies or NGOs). The decisions taken by local governments are also likely to\nbetter reflect the local preferences identified through a local planning process (allocative\nefficiencies). Based on experience elsewhere, it is supposed that the resulting choices of local\npublic investments financed through the discretionary Municipal Grants provided by the Project\nare likely to yield higher rates of return over time. For example, evaluations of similar projects in\ncountries like India, Bangladesh and Uganda have yielded robust positive rates of return.\n\n59. Since the spending", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000026", "page": 27, "chunk": 0, "title": "Jordan - Emergency Services and Social Resilience Project", "pdf_url": "http://documents.worldbank.org/curated/en/532171468273353365/pdf/PAD7230P1476890AD0October0100final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ",446.643\nChange in Exports Exposure (billion USD)\n(1,127.362)\n\n\n\n-1,446.643 -2,750.395* -2,501.416\nChange in Exports Exposure (billion USD)\n(1,127.362) (1,549.210) (1,429.758)\n\n<u>Panel</u> <u>E.</u> <u>First-Stage.</u> <u>Response</u> <u>Variable:</u> <u>Change</u> <u>in</u> <u>Exports</u> <u>Exposure</u> <u>(billion</u> <u>USD)</u>\n\n\n\n-2,750.395*\n\n(1,549.210)\n\n\n\n(1) (2) (3)\n\n\n\n.0058*** .0046*** .0045***\nChange in Foreign Demand Exposure (billion USD)\n(.0006) (.0008) (.0004)\n\n<u>F-statistic</u> <u>77.82</u> <u>30.25</u> <u>139.95</u>\nTime Fixed-Effects ✓ ✓\nDistrict Fixed-Effects ✓ ✓\nSocio-Demographic Controls ✓\n<u>N</u> <u>120</u> <u>120</u> <u>120</u>\nDistrict cluster robust standard errors in parenthesis.\n\n\n\n.0058***\nChange in Foreign Demand Exposure (billion USD)\n(.0006)\n\n\n\n.0046***\n\n(.0008)\n\n\n\n\n- _p <_ 0 _._ 1; ** _p <_ 0 _._ 05; **", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001073", "page": 15, "chunk": 2, "title": "idu0d9e1ef010558b04cb10b110052e55e8b97cd", "pdf_url": "https://local/prwp/idu0d9e1ef010558b04cb10b110052e55e8b97cd.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["M&E data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000017", "page": 29, "chunk": 2, "title": "West Bank and Gaza - Integrated Community Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/158081468762622780/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "M&E data", "label": "VAGUE_DATA", "score": 0.5883201956748962, "start": 530, "end": 538, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nLebanon Health Resilience Project (P163476)\n\n\ndegree of autonomy. Around 47 percent of the Lebanese population have health insurance coverage;\nand 53 percent who lack any formal coverage are covered by the MoPH, which serves as an “insurer of\nlast resort.” This means a strong role for the ministry, not only in preventive care, public health\nleadership, and regulation, but also in curative care. To provide hospital coverage to about 250,000\ncases per year, the MoPH contracts 26 public and 105 private hospitals. Individual patient copayment to\nthe hospital constitutes 5 percent (public hospital) or 15 percent (private hospital) of the hospitalization\ncosts, and the MoPH directly reimburses the hospital for the 85–95 percent difference.\n\n10. **Despite the considerable resilience of Lebanon’s health system, the health sector indicators**\n**are regressing since the start of the Syrian crisis** . The gains that Lebanon made in meeting the\nMillennium Development Goals (MDGs) before the Syrian crisis are rapidly declining. The latest MoPH\nhospital data show significant setbacks in neonatal and maternal mortality indicators (this excludes\ndeliveries outside the hospitals). As of 2017, the data indicate that the neonatal mortality rate has\nincreased from 3.4 per 10,000 in 2012 to 4.9 per 10,000, with the rate among displaced Syrians (7 per\n10,000) almost double that among Lebanese (3.7 per 10,000). Similarly, the maternal mortality ratio\nincreased from 12.7 per 100,000 in 2012 to 21.3 per 100,000, with the rate among displaced Syrians\n(30.4 per 100,000) double that among Lebanese (15.8 per 100,000). <sup>5</sup>\n\n11. **Lebanon also faces epidemiological risks, the reemergence of some diseases that had been*", "output": {"entities": {"named_data": [], "descriptive_data": ["MoPH\nhospital data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000032", "page": 14, "chunk": 0, "title": "Lebanon - Health Resilience Project", "pdf_url": "http://documents.worldbank.org/curated/en/616901498701694043/pdf/Lebanon-Health-PAD-PAD2358-06152017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "MoPH\nhospital data", "label": "DESCRIPTIVE_DATA", "score": 0.7085379362106323, "start": 1061, "end": 1079, "probe_score": 0.8515, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "** **Jordan has been actively working on the digitalization of public services; however, user adoption remains limited.**\nThe Sanad application implemented by MODEE includes digital ID, electronic signature, and a personal document store,\nin addition to functioning as a unified online portal for accessing digitalized public services. Approximately 800,000 users\n(that is, about 7 percent of the population) have activated their Sanad accounts as of January 2024, which is far below the\nGOJ’s goal of 3.5 million active digital IDs by 2025. The limited adoption of Sanad is due to low perceived relevance for\nmany individuals and service providers, as well as to eligibility restricted so far to citizens, thus leaving various\ndemographic groups (such as non-Jordanians, amongst whom refugees, and military personnel) ineligible for a digital ID.\nMODEE plans to increase the uptake of Sanad by (1) expanding eligibility and outreach to enroll additional users (for\nexample, through the operationalization of new GSCs and targeted visits to refugee communities); (2) introducing new\nfeatures to enhance trust, interoperability, security, and people centricity, such as adding a mechanism to collect user\nconsent for data sharing; and (3) implementing a DPI ecosystem approach that is aligned with international good practice,\nto achieve effective, end-to-end, digitalized service delivery workflows. Taking a trusted, people-centric DPI ecosystem\napproach offers the opportunity to embrace international standards and open internet technologies by using trusted data\n\n\n4 See the _<u>State of the Country</u>_ _<u>Reports</u>_ <u>on the ESCJ website at https://www.esc.jo/Reportsen.aspx.</u>\n5 DPI refers to digital ID, payment, and data exchange capabilities that are fundamental to enabling service delivery at scale and\nsupporting innovation in the digital economy.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["trusted data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000181", "page": 12, "chunk": 2, "title": "Jordan - People-Centric Digital Government Program for Results", "pdf_url": "https://documents1.worldbank.org/curated/en/099030724150040202/pdf/BOSIB-70f97ae8-b741-401c-82cc-e87615cc5487.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "trusted data", "label": "VAGUE_DATA", "score": 0.6618227958679199, "start": 1554, "end": 1566, "probe_score": 0.3906, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "28. Investment climate accounts for up to 30 percent of firm productivity. According to Escribano\nand Guasch, <sup>12</sup> [^12: Escribano, A., and J. L. Guasch. 2005. “Assessing the Impact of the Investment Climate on Productivity using\nFirm-Level Data: Methodology and Cases of Guatemala, Honduras, and Nicaragua.” World Bank Research\nPaper 3621..] the contribution to the average productivity of the average number of days spent in\ninspections and regulation related work ranges between 2 percent to 8 percent, as estimated in a set of\nLatin American countries. Moreover, public-private dialogue or effective state-business relationship\nfacilitated by an organized private sector promotes the economic performance of firms as shown by\nQureshib and Veldeb. <sup>13</sup> [^13: Qureshi and Valde. 2007. “State-Business Relations, Investment Climate Reform, and Firm Productivity in\nSub-Saharan Africa.”]\n\n\n29. It is assumed that the investment climate reforms will lead to an increase of 1 percent in firms’\nproductivity in Jordan each year for the next 10 years.\n\n\n**_Investment Promotion_**\n\n\n30. Investment promotion efforts led by the reorganized and modernized the JIC in a context of a\npreferential market access granted by the EU through the relaxation of the rules of origins will lead to\nan increase of domestic and foreign investments in Jordan. Existing investments will expand to reap the\nbenefits of the European market. This will be a case in the garment sector, ready to address this market\nthanks to more than 10 years exporting to the U.S. This sector employs 60,000 employees and exports\nworth US$1.6 billion per year to the U.S. This sector is growing at 10 percent per year. In other sectors,\ninvestments may expand and be retained in Jordan thanks to improved aftercare services dispensed by\nthe JIC. Moreover, foreign investments will increase led by the Syrian diaspora, regional investors, and\ninvestors’ goodwill (corporate social responsibility)", "output": {"entities": {"named_data": [], "descriptive_data": ["Firm-Level Data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 65, "chunk": 0, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Firm-Level Data", "label": "DESCRIPTIVE_DATA", "score": 0.596569299697876, "start": 239, "end": 254, "probe_score": 0.9004, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**3.4. Estatus Legal.**\n\n\n\nMONITOREO DE PROTECCIÓN\n\n\n88% de los encuestados pudo realizar su\n\ningreso a Panamá de forma regular (HFS2:\n\n85%). 13% mencionó que ingresó\n\nirregularmente (HFS2: 13%).\n\n\n\n**¿Pudo realizar su ingreso de forma regular al país?**\nSí No\n\n\n\n\n\nNicaragua Venezuela Otra Cuba Colombia El Salvador\n\n_Fuente: HFS3_\n\n\n\nLos cambios en los patrones de ingreso\n\nregular e irregular podrían deberse, a su\n\nvez, a cambios en las proporciones de las\n\nnacionalidades encuestadas y sus\n\ndiferencias en patrones de entrada,\n\noportunidades y costos de ingreso regular\n\nal país, etc. Las situaciones de Venezuela y\n\nde Nicaragua, así como los cierres de\n\nfrontera y las limitaciones de viaje durante\n\nperíodos del Estado de Emergencia\n\nNacional son factores para considerar al\n\nanalizar estas fluctuaciones.\n\n\n\n**Ingreso irregular reportado**\n\n\nIngreso Regular Ingreso irregular (o no responde)\n\n\n<mark>8%</mark>\n19% 15% 13%\n\n\n92%\n81% 85% 87%\n\n\nPMT HFS1 HFS2 HFS3\n\n\n_Fuente: PMT, HFS1, HFS2, HFS3_\n\n\n\nUNHCR / Febrero 2022 18", "output": {"entities": {"named_data": ["HFS2", "HFS3_"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001181", "page": 16, "chunk": 0, "title": "Monitoreo de protección: Panamá, Informe General - High Frequency Survey 3 Octubre 21 de 2021 a Diciembre 31 de 2021", "pdf_url": "https://reliefweb.int/attachments/b4aeeb01-2cd4-4f22-90c3-b234f09136e0/HFS%203%20General%20Report_Feb2022.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "HFS2", "label": "NAMED_DATA", "score": 0.5181660652160645, "start": 129, "end": 133, "probe_score": 0.0, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "HFS3_", "label": "NAMED_DATA", "score": 0.5454821586608887, "start": 327, "end": 332, "probe_score": 0.9991, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nKenya Primary Education Equity in Learning Program (P176867)\n\n\n**Sectoral and Institutional Context**\n\n7. **Kenya has achieved remarkable progress in improving access to primary education.** Kenya\nintroduced the Free Primary Education (FPE) and the Free Day Secondary Education (FDSE) policies, in\n2003 and 2008 respectively, as part of its commitment to provide education for all. Continued\nimplementation of these policies resulted in increased enrollment across the education system. The\nsystem currently enrolls about 16 million learners in approximately 90,000 basic education institutions.\nThe Gross Enrollment Rate (GER) over the last decade has been above 100 percent in primary education\nand the Net Enrollment Rate (NER) increased from 56 percent in 2002 to 92 percent in 2018. Secondary\nGER increased from 67 percent in 2016 to 71 percent in 2019. Low enrollment rates at the secondary level\nare linked to low transition rates into upper education levels and for those students who transition,\ninefficiencies related to repetition and overage enrollment. Therefore, the Kenyan government\nannounced an objective of attaining 100 percent transition from primary to secondary education to\naddress this gap. Under the 100 Percent Transition Policy, the transition rate from primary to secondary\nlevels increased to 83 percent in 2019.\n\n\n8. **Access related outcomes for refugee learners are considerably below the national averages** .\nWhile there have been gains in primary school education over the last decade, primary school attendance\nin refugee camp-based schools is not as high as the national level. <sup>5</sup> [^5: In the refugee camp-based schools, the primary GER is 81 percent while the NER stands at 45 percent. UNHCR, (2021), Kenya\nEducation Data-October 2021.] Transition from primary to secondary\neducation among learners in refugee camp-based schools has also been challenging, with secondary\neducation GER at 46 percent and the NER standing at 18 percent in 2021. Increasing access to quality\nprimary education and supporting the transition to secondary school can help develop", "output": {"entities": {"named_data": ["Kenya\nEducation Data-October"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007386", "page": 5, "chunk": 0, "title": "Appraisal Stage Program Information Document (PID) - Kenya Primary Education Equity in Learning Program - P176867", "pdf_url": "https://documents.worldbank.org/curated/en/099725103042231883/pdf/Appraisal0Stag0g0Program000P176867.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Kenya\nEducation Data-October", "label": "NAMED_DATA", "score": 0.5481776595115662, "start": 1768, "end": 1796, "probe_score": 0.9989, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".\n\nWithin any given context, seemingly contradictory views may exist. For example, in urban\n\nareas, tolerance levels are generally lower and refugees are more likely to be perceived as an\n\neconomic burden, and yet hosts are more likely to hold progressive (cosmopolitan) attitudes\n\nto refugee rights. The Turkana hosts around Kakuma see refugees as a security threat while\n\ngenerally regarding them as friendly and valuing their economic contribution. Ugandan\n\nlandowners in Nakivale view refugees as both competitors and contributors. These ‘mixed’\n\nsentiments – positive and negative – are not mutually exclusive, but rather co-existent in host\n\nsociety. However, we also observe some clear patterns across contexts. For example, the role\n\nof ethno-linguistic proximity (notably revealed through the so-called ‘Somali bond’) plays\n\na role in shaping attitudes, the importance of neighbourhood and household-level attitude\n\nformation, and the role of a household’s own socio-economic position in relation to refugees\n\n(landlord or tenant, employer or employee, landowner or non-landowner) are important\n\nthemes across context. Furthermore, a clear theme is the distinction between urban and\n\nrural contexts: through our Uganda data there is evidence that direct interactions may play\n\na causal role in shaping attitudes in cities, but not in camp-like settings. Further, we find\n\nevidence across the countries that attitudes in camp-like settings are more positive than in\n\n\n21These two statements were asked to hosts in all sites except the Kakuma Camps in Kenya.\n\n\n28", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Uganda data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002099", "page": 30, "chunk": 1, "title": "social cohesion and refugee host interactions evidence from east africa", "pdf_url": "https://local/prwp/social-cohesion-and-refugee-host-interactions-evidence-from-east-africa.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Uganda data", "label": "VAGUE_DATA", "score": 0.6815807223320007, "start": 1221, "end": 1232, "probe_score": 0.9637, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Week35**<br>**Week36**<br>**Week37**<br>**Week38**<br>**Week39**<br>|**Week27**<br>**Week28**<br>**Week29**<br>**Week30**<br>**Week31**<br>**Week32**<br>**Week33**<br>**Week34**<br>**Week35**<br>**Week36**<br>**Week37**<br>**Week38**<br>**Week39**<br>|**Week40**<br>**Week41**<br>**Week42**<br>**Week43**<br>**Week44**<br>**Week45**<br>**Week46**<br>**Week47**<br>**Week48**<br>**Week49**<br>**Week50**<br>**Week51**<br>|**Week40**<br>**Week41**<br>**Week42**<br>**Week43**<br>**Week44**<br>**Week45**<br>**Week46**<br>**Week47**<br>**Week48**<br>**Week49**<br>**Week50**<br>**Week51**<br>|**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000142", "page": 56, "chunk": 6, "title": "Djibouti - Public Administration Modernization Project", "pdf_url": "http://documents1.worldbank.org/curated/en/826531523301322820/pdf/Djibouti-Public-Admin-PAD-PAD2604-04062018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "24\n\n\n**During negotiations the following assurances were received:**\n\n\n1. Agreement on triggers for subsequent phases\n2. Agreement on monitoring and impact assessment studies\n3. Agreement on project monitoring indicators\n4. Agreement on finalized bidding documents for the first batch of schools\n\n\n**Actions to be included in Development Credit Agreement:**\n\n\n_Financial_\n\n\n1. Audits and Project Management Reports.\n2. Dated covenant on the selection of the auditor before March 31, 2001.\n\n\n_Management_\n\n\n1. Daied covenant on a baseline survey to establish gender and social class distribution of students\nbefore December 31, 2001.\n2. Provide regular reports on monitoring indicators and prepare a draft midterm report for review\nwith IDA before September 15, 2002.\n\n\n**In addition the following Management conditions are included in supplemental letters attached**\n**to the Developinent Credit Agreement:**\n\n\n1. Triggers from Phase I to Phase II in APL\n2. Triggers from Phase II to Phase III in APL\n\n\nH. READINESS **FOR IMPLEMENTATION**\n\n\nL. a) The engineering design documents for the first year's activities are complete and ready for the\n\nstart of project implementation.\nD b) Not applicable.\n\n3 2. The procurement documents for the first year's activities are complete and ready for the start of\nproject implementation.\n\n\nK/ 3. The Project Implementation Plan has been appraised and found to be realistic and of satisfactory\n\nquality.\n##### D 4. \"he following 7tems are lacking and are discussed under loan conditions (Section G):", "output": {"entities": {"named_data": [], "descriptive_data": ["baseline survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000041", "page": 27, "chunk": 0, "title": "Jordan - Community Infrastructure Project", "pdf_url": "http://documents1.worldbank.org/curated/en/294581468773394111/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "baseline survey", "label": "DESCRIPTIVE_DATA", "score": 0.810932993888855, "start": 529, "end": 544, "probe_score": 0.1317, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a v\nManufacturIng 5 7 3.7 4 7 5 0 / s \\\\t oo  Services 475 272 190 201\n\nPrfvate consumpffon 90 7 81 9 938 95 1 20\nGeneral govemment consumption 7 0 9 6 146 17.2 =c ~GDFDl\nImpons of goods and servrcea 39 7 23 6 33 4 373 -3GW_G_____\n\n\n_(average_ _annual growth)_ 1981-9 1991401 2000 2001 Growth ot exports and Imports (%)\n\nAgrutumre -0 6 -2 6 2 2 3 8 oo\nIndustry 0.1 -41 51 5 6 s0\nManUnacturIng 6.9 . .\nServices -5 7 -5.4 4 0 51 \nPrivate oonsumpffon -2 0 -19 10 4 100 -50\nGeneral govemment consumption -5.1 -0 2 41.3 27 9 -100\nGross domestic Investment -06 3 0 50 - EOpois -tr-ports\nImports of goods and services -2 2 -151 85 0 61 3\n\n\nNote 2001 data are pretirrinary eastliates\n'The diamonds show four Key Indicators in the country (in bold) conipared with itS income-group average It data are missing, the diantond wiUt be rrconrrlte\n\n\n-56", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["2001 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019286", "page": 60, "chunk": 2, "title": "Kenya - Program Loan Project", "pdf_url": "https://documents.worldbank.org/curated/en/862591468046803369/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2001 data", "label": "VAGUE_DATA", "score": 0.7082152366638184, "start": 639, "end": 648, "probe_score": 0.0183, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEmergency Food Security Project (P178936)\n\n\n\n\n\n**11.** **Existing food insecurity levels are particularly high among Jordan’s refugee population.** According to the\nmost recent mobile Vulnerability Assessment and Mapping (mVAM) <sup>16</sup> completed by the World Food Program\n(WFP) in Jordan, 7 percent of Jordanian households (representing 535,559 individuals) were found to be food\ninsecure as of February 2021 and another 51 percent of households (representing 3,843,701 individuals) were\nvulnerable to food insecurity, meaning that they were very likely to experience an acute decline in food access or\nconsumption levels below minimum survival needs. WFP’s mVAM also found that food insecurity levels among\nJordan’s refugee community (which are not covered by Jordan’s social security net system) are significantly higher\nthan those registered at the level of Jordanian households. Of the more than 750,000 refugees <sup>17</sup> registered in\nJordan (89 percent of whom came from Syria), an estimated 17 percent live in the Za’atari and Azraq refugee\ncamps, while the remaining 83 percent are mostly in Jordan’s urban areas. Throughout the COVID-19 pandemic,\nfood security has been a key concern for refugees in both camps and in host communities mainly due to the loss\nof income from temporary and informal labor activities. More than 80 percent of labor activities performed by\nnon-Jordanians are estimated to take place in the informal economy versus 40 percent for Jordanian citizens\n(MOSD, 2019). February 2021 mVAM data showed that 23.3 percent of refugee households in host communities\nare food insecure (over 154,777 individuals), while another 63.7 percent of refugee households (equivalent to\napproximately 423,344 individuals) are vulnerable to food insecurity.\n\n**12.** **Ens", "output": {"entities": {"named_data": ["mobile Vulnerability Assessment and Mapping", "mVAM", "mVAM data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 14, "chunk": 0, "title": "Jordan - Emergency Food Security Project", "pdf_url": "http://documents.worldbank.org/curated/en/486071652556836130/pdf/Jordan-Emergency-Food-Security-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "mobile Vulnerability Assessment and Mapping", "label": "NAMED_DATA", "score": 0.8087602257728577, "start": 196, "end": 239, "probe_score": 0.9769, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "mVAM", "label": "NAMED_DATA", "score": 0.5027022361755371, "start": 683, "end": 687, "probe_score": 0.9957, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "mVAM data", "label": "NAMED_DATA", "score": 0.7920305728912354, "start": 1543, "end": 1552, "probe_score": 0.9942, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nBurundi Integrated Community Development Project (P169315)\n\n\n**Key Financial Results**\n\n28. These are gross margin, internal rate of return (IRR) before financing, IRR after project financing, IRR with\nproject, net present value (NPV), return on investment.\n\n<u>Gross margin</u>\n\n29. The gross margin in 'situation without project' and 'situation with project' is summarized in the table below:\n\n\n**Table 5.2: Gross margin (situation \"without project\" and situation \"with project\")**\n\n|Financial Models|Gross margin (US$)|Col3|\n|---|---|---|\n|**Financial Models**|**without project**|**with project**|\n|Poultry breeding|-217|784|\n|Orange-fleshed sweet potato production|1 144|2 684|\n|Beekeeping|359|616|\n|Local rural transport|1 443|2 092|\n|Bakery|9 989|11 930|\n|Cheese production|12 781|17 677|\n\n\n\nSource: drawn up by the project evaluation mission of November - December 2019.\n\n\n30. Analysis of the data in the above table shows that, compared to the situation without the project, the\n\"TURIKUMWE\" project will help to significantly improve the income of the associations and microenterprises\nbenefiting from its support by at least 19 percent. These results can be explained by a mastery of techniques for\nconducting the promoted activities, improved access to quality inputs and equipment and to markets at\nremunerative prices, a reduction in post-production losses, etc.\n\n<u>Internal rate of return (IRR)</u>\n\n31. IRR before financing is the intrinsic internal rate of return. The analysis shows that the targeted activities are", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data in the above table"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000110", "page": 79, "chunk": 0, "title": "Burundi - Integrated Community Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/644221583204472551/pdf/Burundi-Integrated-Community-Development-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data in the above table", "label": "VAGUE_DATA", "score": 0.6375959515571594, "start": 920, "end": 943, "probe_score": 0.9967, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". New seed varieties suitable for varying climatic zones,\nanimal health research, technologies aimed at managing the fragile natural resources and\npromoting soil fertilities, and research in biotechnology for crops an livestock were also\ndeveloped. The ARF which was established in 1991 to promote competitive research grants\nwas also financed under the project. A cross cutting instrument—socio-economic research—\nto test the viability of research programs and assess the impact of adopted technologies was\nalso an integral part of NARP-Phase II albeit with minimal follow-up. KARI’s technology\ndissemination strategy was dependent on the then prevailing Training and Visit System\n(T&V) supported under an IDA-assisted Agricultural Extension Project. In 1998, the T&V\nSystem collapsed in Kenya and the project ended prematurely with unsatisfactory outcomes. <sup>5</sup>\nTo overcome the absence of an extension service provider, KARI, in 2000, had to introduce a\nnew approach known as the Agricultural Technology and Information Response System\n(ATIRI).\n\n\n3.8 In 2005, KARI prepared an inventory of all its completed basic and adaptive research\nprograms including their adoption status. <sup>6</sup> KARI and its predecessor Institutes, dating back\nto the 1960s have developed over 750 technologies. Over 80 percent of the technologies\nwere released since the early 1990s covering the period of NARP Phase I and NARP Phase\n\n\n5. For a detailed review, see Madhur Gautam’s “Agricultural Extension The Kenya Experience: An Impact\nEvaluation”, OED, World Bank, 2000.\n6. Kenya Agricultural Research Institute, 2005, “Inventory of Technologies Developed by KARI up to 2005”.", "output": {"entities": {"named_data": ["Inventory of Technologies Developed by KARI up to 2005"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009006", "page": 16, "chunk": 1, "title": "Kenya - Second National Agricultural Research Project", "pdf_url": "https://documents.worldbank.org/curated/en/171831468272707569/pdf/421430PPAR0P001Disclosed0May0102008.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Inventory of Technologies Developed by KARI up to 2005", "label": "NAMED_DATA", "score": 0.6728058457374573, "start": 1613, "end": 1667, "probe_score": 0.6933, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "recent post-conflict period.\n\n\nTable 4: Unit Cost of a 6-Classroom Primary School\nComponents NaCSA (Provincial prices in MOEST (Freetown prices in\nLeones) Leones)\nCost of main building 120,865,000 106,078,530\nCost of hand pump well 7,000,000 9,500,000\nCost of 6-pit latrine 7,500,000 6,500,000\nTotal 135,365,000 122,078,530\n\n\nTo ensure that NaCSA investments are cost-effective, during implementation, a database of unit\ncosts by type of sub-project and by region will be established and updated at least twice a year. In\naddition, international experience suggests that moving to community management of resources leads to\na 25-40% reduction in unit costs of small-scale infrastructure. NaCSA will initiate direct financing of\ncommunities, and the effect on unit costs will be analyzed during implementation. Moreover, in the\nprevious project (ERSF), the actual beneficiaries were difficult to estimate as populations were just\nresettling. Available figures are therefore not reliable during appraisal and implementation. During\nimplementation, NaCSA will maintain more reliable information on cost per beneficiary for each\ncategory of sub-project.\n\n\nAdministrative Efficiency\n\n\nCompared to other govemment's agencies, NaCSA has the reputation of executing projects with\nrelative speed and efficiency in difficult communities. For example, the time lag between request\nsubmission by communities and payment of first tranche can be about 60 days. Also, the staff are\ncapable of delivering training and other services to communities with little international expertise. They\ncan work under pressure and can produce results on time. The series of training activities planned for\n\nstaff under the project will further build their capacities for such activities.\n\n\nHowever, it should be noted that the previous ERSF project had high overhead costs. This was\nbasically due to the fact that a new institution (NCRRR now NaCSA) was", "output": {"entities": {"named_data": [], "descriptive_data": ["database of unit\ncosts"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000176", "page": 40, "chunk": 0, "title": "Sierra Leone - National Social Action Project", "pdf_url": "http://documents1.worldbank.org/curated/en/976421468759851028/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "database of unit\ncosts", "label": "DESCRIPTIVE_DATA", "score": 0.916168749332428, "start": 404, "end": 426, "probe_score": 0.1083, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**List of Tables**\n\n\nTable 1.1: Typology of Concepts Used in the Informal Non-farm Sector ...................................... 2\nTable 2.1: Selected Economic Indicators (percent*) ...................................................................... 5\nTable 2.2: Poverty Incidence (percent) ........................................................................................... 5\nTable 2.3: Percent of Households Engaged in HE, by Area, 2006 ................................................. 9\nTable 2.4: Percent of Households Engaged in HE, by Asset Quintile, 2006 .................................. 9\nTable 2.5: Main Reason for Having an HE, by Economic Activity", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005058", "page": 5, "chunk": 0, "title": "wps5882", "pdf_url": "https://local/prwp/wps5882.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### Moving Teachers to Malawi’s Remote Communities: A Data-Driven Approach to Teacher Deployment\n\nSalman Asim* <sup>[1]</sup> Joseph Chimombo <sup>¥</sup> Dmitry Chugunov*     Ravinder Gera*\n\n\nJEL codes: I21, I28, D73; D78\n\n\nKeywords: Malawi, Schools, Teachers, Deployments, Political Economy, Data-Driven Model\n\n\n[1]Corresponding author: Salman Asim, Economist, Education GP for Africa Region email: sasim@worldbank.org.\nWe thank Fabiano Gwalidi, former Minister of Education, for his leadership of the project; the Ministry of Education\nScience and Technology, in particular Honorable Minister Bright Msaka, Deputy Director Ellen Simango, and Noel\nMwango, for support in collection of data and in holding focus group discussions; Director Joyce Somanje for access\nto payroll database; Ken Ndala, former Principal Secretary for Education, for strategic support; all District Education\nManagers and District EMIS officers for supporting updates and revisions to data; the MPs, District Commissioners,\nand others who attended focus groups; Laura Kullenberg, Gayle Martin, Innocent Mulindwa, and other World Bank\ncolleagues in Malawi for encouragement, support and advice; Cameron Friday, Michael Mambo, Zunaira Mughal\nand Xu Wang for invaluable research assistance; Education GP Management, Practice Managers Sajitha Bashir, Halil\nDundar and Safaa Al Tayab El Kogali, Lead Education Specialist Toby Linden, Lead Economist Andreas Blom, and\nSenior Economist Samer Al-Samarrai, for useful discussions, suggestions and comments; the LSE Capstone project\nfor valuable background work and insights; and participants in the World Bank Human Development Week Lightning\nTalks for comments and feedback. The findings, interpretations, and conclusions expressed herein are our own and\ndo not necessarily represent the views of the World Bank", "output": {"entities": {"named_data": [], "descriptive_data": ["payroll database"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007211", "page": 2, "chunk": 0, "title": "wps8253", "pdf_url": "https://local/prwp/wps8253.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "payroll database", "label": "DESCRIPTIVE_DATA", "score": 0.8699028491973877, "start": 769, "end": 785, "probe_score": 0.8115, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Independent Evaluation Group (IEG)** Implementation Completion Report (ICR) Review\nET-Local Govt Dev Project II (P133592)\n\n\nbusiness opportunities. However, performance of the infrastructure services delivered was not\nsupported by data collected as part of the results framework. The assessment of ULG performance in\nthis results area focused mostly on apex institutions and not on the users.\n\n  - **Enhanced Infrastructure Operations and Maintenance**\n\n    - Operations and Maintenance (O&M) expenditures increased in more cities, from 36 cities in FY 2015\nto 38 cities in FY 2019 with annual increase in O&M expenditures. O&M expenditure increase during\nthe five-year program by 35 percent, from 195 million ETB in FY 2015 to 753 million ETB in FY 2019.\nFive cities in FY 2015 increased to 39 cities in FY 2019 budgeted at least 10 percent of their Capital\nInvestment Plan toward O&M. However, not all completed infrastructure investments such as\nslaughterhouses and markets were put into operation because of absent business plans and\nassociated O&M arrangements (ICR, paragraph 111) (see Section 11, Lessons below).\n\n  - **Citizen Engagement in Infrastructure Planning**\n\n    - As part of minimum conditions, community members were involved in identifying, prioritizing, and\nselecting infrastructure projects. According to the Borrower's ICR, 16 cities of the 44 ULGs who\nparticipated in the beneficiary assessment noted that community members witnessed the handover\nof completed infrastructure projects (ICR, paragraph 36). In addition, participants indicated that as a\nresult of increased business opportunities and jobs, their households were food secure, they were able\nto pay for their utilities, had accumulated household assets, and had saved and invested in business.\nThe assessment also reported that 75.6 percent of respondents invested their income generated from\nthe project, 76.2 percent acquired household assets and 71.4 percent said they were better positioned\nto pay their children's", "output": {"entities": {"named_data": [], "descriptive_data": ["beneficiary assessment"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013887", "page": 7, "chunk": 0, "title": "Ethiopia - ET-Local Govt Dev Project II", "pdf_url": "https://documents.worldbank.org/curated/en/498001615841290441/pdf/Ethiopia-ET-Local-Govt-Dev-Project-II.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "beneficiary assessment", "label": "DESCRIPTIVE_DATA", "score": 0.584388256072998, "start": 1398, "end": 1420, "probe_score": 0.0005, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "-Poverty-in-Contexts-of-Forced-Displacement](http://documents.worldbank.org/curated/en/492181635479693932/A-Multi-Country-Analysis-of-Multidimensional-Poverty-in-Contexts-of-Forced-Displacement)</u>_\n\nThis paper **develops a Multidimensional Poverty Index (MPI) to examine patterns**\n\n**of multidimensional poverty among IDPs and refugees, with comparisons to**\n\n**host populations, in five African countries** . The MPI is disaggregated to analyze\n\nvariations in deprivation by displacement status of the household and gender of the\n\nhousehold head. The analysis draws on household survey data from Ethiopia, Nigeria,\n\nSomalia, South Sudan, and Sudan <sup>11</sup> [^11: In Ethiopia, the Skills Profile Survey (2017) sampled refugees in and around camps in the Tigray, Afar, Gambella,\nBenishangul Gumuz, and Somali regions. In Nigeria, the IDP Survey (2018) sampled IDPs and host communities in six\nnortheastern states (Adamawa, Bauchi, Borno, Gombe, Taraba, and Yobe). In Somalia, the High Frequency Survey (2017)\nsampled IDPs and host communities in secure parts of the country. In Sudan, the IDP Profiling Survey (2018) sampled IDPs\nand neighboring host communities in the Abu Shouk and El Salam camps, in Al-Fashir. And in South Sudan, the High\nFrequency Survey Wave 4 (2017) sampled IDPs and host communities in urban areas of seven of the ten pre-war states\n(Western Equatoria, Central Equatoria, Eastern Equatoria, Northern Bahr-El-Ghazl, Western Bahr-El-Ghazal, Warrap, Lakes\nstate).] .\n\n\n[10 This work is part of the program “Building the Evidence on Forced Displacement: A Multi-Stakeholder Partnership”. The](https://www.worldbank.org/en/programs/building-the-evidence-on-forced-displacement)\nprogram is funded by UK aid from the United Kingdom's Foreign, Commonwealth, and Development Office (FCDO). It is\nmanaged by the World Bank Group (WBG) and was established in partnership with the United Nations High Commissioner for\nRefugees (UNHCR). This", "output": {"entities": {"named_data": ["Skills Profile Survey", "IDP Survey", "High Frequency Survey", "IDP Profiling Survey", "High\nFrequency Survey Wave 4"], "descriptive_data": ["household survey data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000595", "page": 24, "chunk": 1, "title": "The Gender Dimensions of Forced Displacement: Findings from New Empirical Analysis", "pdf_url": "https://reliefweb.int/attachments/5780e76e-ec0d-3e63-a917-0e49930600b6/JDC%20Quarterly-Digest_-December-2021.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8323574066162109, "start": 573, "end": 594, "probe_score": 0.9796, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Skills Profile Survey", "label": "NAMED_DATA", "score": 0.8586145043373108, "start": 689, "end": 710, "probe_score": 0.9859, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "IDP Survey", "label": "NAMED_DATA", "score": 0.8088060021400452, "start": 841, "end": 851, "probe_score": 0.9857, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "High Frequency Survey", "label": "NAMED_DATA", "score": 0.8095586895942688, "start": 987, "end": 1008, "probe_score": 0.9886, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "IDP Profiling Survey", "label": "NAMED_DATA", "score": 0.8080330491065979, "start": 1096, "end": 1116, "probe_score": 0.9974, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "High\nFrequency Survey Wave 4", "label": "NAMED_DATA", "score": 0.838762104511261, "start": 1245, "end": 1273, "probe_score": 0.9867, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " markets and opportunities for value addition and non-farm employment|\n|---|---|\n|SDG 2 <br>SDG Goal 2: End hunger, achieve food<br>security and improved nutrition and<br>promote sustainable agriculture|2.a Increase investment, including through enhanced international cooperation, in rural<br>infrastructure, agricultural research and extension services, technology development and plant<br>and livestock gene banks in order to enhance agricultural productive capacity in developing<br>countries, in particular least developed countries|", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000157", "page": 48, "chunk": 3, "title": "Türkiye 3RP - Regional Refugee and Resilience Plan in Response to the Syria Crisis 2025 Update", "pdf_url": "https://reliefweb.int/attachments/0c321f49-717c-573b-8b08-cf248c7cf5ed/EN%20-%203RP%202025%20-%20Appeal%20Overview.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".6.2 Monitoring Changes to Vulnerability**\nKISIP will assess the vulnerability of individual and groups who may be potential candidates for\nvulnerability status. Particular attention shall be afforded to the most vulnerable, least visible and\nvoiceless for whom special consultation measures may be required.\n\n\nThe CLO will maintain and update existing records of vulnerable stakeholder groups and will screen\npotential individual and group candidates using the criteria developed in the Vulnerability Screening\nChecklist (see format in Appendix 4). This process requires an update to relevant data and an\nevaluation of vulnerability status, which will be undertaken either when the CLO identify a specific\nneed or at a minimum frequency of annually during construction and the first two years of\noperations.\n\n\n**3.6.3 Differentiated Engagement Measures**\n\n\nPage | 29", "output": {"entities": {"named_data": [], "descriptive_data": ["records of vulnerable stakeholder groups"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000732", "page": 28, "chunk": 1, "title": "Kenya - Second Informal Settlements Improvement Project : Stakeholder Engagement Framework", "pdf_url": "https://documents.worldbank.org/curated/en/099021524043525262/pdf/P1678141a5fd6905f1b7c412bf6dd2a6243.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "records of vulnerable stakeholder groups", "label": "DESCRIPTIVE_DATA", "score": 0.7593094706535339, "start": 353, "end": 393, "probe_score": 0.2243, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**WATER AND SANITATION DEVELOPMENT PROJECT (WSDP)**\n\n\n**SUMMARY PROCUREMENT PLAN** ( **first eighteen months)**\n\n\n**I.** **<u>General</u>**\n\n\nThe following procurement plan has been developed for project implementation during the\nfirst eighteen months and provides the basis for the procurement methods and bank\nprior/post review thresholds. It covers the three categories, namely, Works; Consultancies;\nand Goods. The plan will be updated when need arises to reflect the actual project\nimplementation needs.\n\n\n**1.** **Project information** :\n\n\n**Country / Borrower** : Republic of Kenya\n\n\n**Project** : Water and Sanitation Development Project (WSDP)\n\n\n**IDA Credit No.** 6029 & 6030\n\n\n**Project Implementing Agencies:** (a) Ministry of Water and Irrigation, (b)\nWaSREB, (c) Water Service Providers: Kilifi-Mariakani Water and Sewerage\nCompany (Kimawasco),; Taita-Voi Water and Sewerage Company (Tavevo);\nMombasa Water Supply and Sanitation Company (Mowassco); Kwale Water and\nSewerage Company (Kwawasco); Garissa Water and Sewerage Company\n(Gawasco); Wajir Water and Sewerage Company (Wajwasco); and Malindi\nWater and Sewerage Company; and (d) Counties: Kilifi; Taita Taveta;\nMombasa; Kwale; Garissa; and Wajir\n\n\n**2.** **Bank’s approval** **Date of the First Eighteen Months’ Procurement Plan:**\nJune 15, 2017\n\n\n**3.** **Date of General Procurement Notice** : June 14, 2017\n\n\n**4.** **Period covered by this procurement plan", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001020", "page": 0, "chunk": 0, "title": "Kenya - EASTERN AND SOUTHERN AFRICA- P156634- Water and Sanitation Development Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099022825143517918/pdf/P156634-bc81aa18-6bc7-41f9-bd6f-b91d468a7530.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " credibility. When available, video material, lists of victims and supplementary\ninformation from protection cluster partners is incorporated.\n\nCIMP monitors civilian impact that occurs after an incident of armed violence have taken place, thus CIMP numbers on\n\ndisplacement, loss of livelihood and restriction of movements/obstruction to flight only covers households that have experienced a\ndirect impact from armed violence, e.g. a house destroyed or a vehicle hit. Therefore, CIMP data does not include full numbers of\npeople being displaced, loosing livelihood or experiencing restricted freedom of movement/obstruction to flight, where numbers are\nnaturally much higher than what is captured by CIMP.\n\nCivilian impact incidents recorded by CIMP are divided into direct and indirect impact, with associated direct and indirect protection\nimplications. Direct impact includes incidents in which individuals or households are directly affected by the incident, e.g. damage to\nhouses and farms, damage to markets and local businesses, impact on vehicles or as well as exposure to UXOs and armed conflict\ngenerating casualties. Indirect impact can broadly be defined as incidents of armed violence impacting on infrastructure and basic\nservices and in turn restricting access of civilians to various vital services, infrastructure and goods, e.g. healthcare, education, food\nand water and transport infrastructure. Due to the nature of the indirect impact, the number of households impacted is often much\nhigher than during direct impact.\n\nAs CIMP aims to collect and disseminate data on civilian impact that occurs as a result of armed conflict, some incidents are\nexcluded. This includes incidents related to crime, domestic violence and small arms fire incidents that occurs away from areas of\nactive conflict and have less than two casualties. Small arms fire incidents are always included when they occur in areas of active\nconflict.\n\n\n###### **3**", "output": {"entities": {"named_data": ["CIMP data"], "descriptive_data": [], "vague_data": ["data on civilian impact"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000783", "page": 4, "chunk": 1, "title": "Civilian Impact Monitoring Report - August - October 2018", "pdf_url": "https://reliefweb.int/attachments/73509408-77aa-3e8c-85b4-eca825ef0a18/civilian_impact_monitoring_report_august_-_october_2018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "CIMP data", "label": "NAMED_DATA", "score": 0.7168613076210022, "start": 480, "end": 489, "probe_score": 0.3748, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data on civilian impact", "label": "VAGUE_DATA", "score": 0.5528236031532288, "start": 1581, "end": 1604, "probe_score": 0.0067, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "ABBREVIATIONS AND ACRONYMS\n\n\n|BoU|Bank of Uganda|\n|---|---|\n|COVID-19|Coronavirus Disease 2019|\n|CPF|Country Partnership Framework|\n|DA|Designated Account|\n|DLG|District Local Government|\n|DRC|Democratic Republic of Congo|\n|EMIS|Education Management Information System|\n|ESCP|Environmental and Social Commitment Plan|\n|ESMP|Environmental and Social Management Plan|\n|FM|Finance Management|\n|GBV|Gender Based Violence|\n|GDP|Gross Domestic Product|\n|GoU|Government of Uganda|\n|GPE|Global Partnership for Education|\n|GRS|Grievance Redress Service|\n|HCI|Human Capital Index|\n|ICWMP|Infectious Control and Waste Management Plan|\n|IDA|International Development Association|\n|IFR|Interim Financial Report|\n|IPC&WMP|Infection Prevention and Control and Waste Management Plan|\n|IRR|Internal Rates of Return|\n|LMP|Labor Management Plan|\n|M&E|Monitoring and Evaluation|\n|MOES|Ministry of Education and Sports|\n|NCDC|National Curriculum Development Center|\n|NPV|Net Present Values|\n|OHS|Occupational, Health and Safety|\n|PCU|Project Coordination Unit|\n|RDCs|Resident District Commissioners|\n|RFQ|Requests for Quotations|\n|SEA|Sexual Exploitation and Abuse|\n|SEP|Stakeholder Engagement Plan|\n|SH|Sexual Harassment|\n|SMCs|School Management Committees|\n|SSA|Sub-Saharan Africa|\n|TA|Technical Assistance|\n|TFR|Total Fertility Rate|\n|UNHS|Uganda National Household Survey|\n|UNICEF|The United Nations Children's Fund|\n|UPE|Universal Primary Education|\n|UPPET|Universal Primary Education and Training Project|", "output": {"entities": {"named_data": ["Uganda National Household Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000034", "page": 2, "chunk": 0, "title": "Uganda - COVID-19 Emergency Education Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/645041598936002560/pdf/Uganda-COVID-19-Emergency-Education-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Uganda National Household Survey", "label": "NAMED_DATA", "score": 0.761337399482727, "start": 1322, "end": 1354, "probe_score": 0.3001, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".899</u> <u>0.899</u>\n\n\n_Notes_ : Dependent variable is the log of cost per km; all models control for work activity fixed effects, year\nfixed effects, an interaction between work type and five-year period fixed effects and region fixed effects; base\ncategories are actual costs; robust standard errors in parentheses, clustered at the country; <sup>_∗_</sup>, <sup>_∗∗_</sup>, <sup>_∗∗∗_</sup> denote\nsignificance at 10%, 5% and 1% levels.\n_Source_ : Authors’ analysis based on data described in the text.\n\n\n14", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data described in the text"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006462", "page": 52, "chunk": 2, "title": "wps7408", "pdf_url": "https://local/prwp/wps7408.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data described in the text", "label": "VAGUE_DATA", "score": 0.8238163590431213, "start": 479, "end": 505, "probe_score": 0.9952, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Nevis and St. Kitts), and St. Vincent & the Grenadines. These were routes with short distances and very\nlow volumes with destinations that are now served by ferries or general aviation type charter flights.\n\n\n\n<u>Caribbean Hub Countries</u>\n\n\n\nThe Bahamas and Trinidad & Tobago stand out in the region because of their high volumes of domestic\ntravel (Figures 11a and 11b). The Bahamas features 18 islands with a total of 64 airports and heliports, of\nwhich 12 have regularly scheduled services. There were three airlines in 2013 serving the domestic\nmarket, with the bulk of the market served by Southern Air Charters (57%), followed by Bahamas Air\n(26%, also the state owned flag carrier), and SkyBahamas (17%). Growth has been significant: between\n2001 and 2013, capacity grew by 5.0% annually, and the recent five year annual growth rate, between\n2008 and 2013 (following the economic slowdown), stood at 9.6%. The number of direct-flight airport\npairs being served, however, has declined: the number of airports being served declined from a peak of 43\nto 23 in 2013 (Figure 11a).\n\n\n\n**Figure 11: Domestic travel in Hub Countries**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n_Note: Trinidad and Tobago only has one airport pair, between the two islands._\n\n\nThe volume of traffic between Trinidad and Tobago is also quite high (Figure 11b). There is a single\nairport pair, served solely by Caribbean Airlines, Trinidad’s flag carrier. Long-term growth has been 6.0%\n\n\n35", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006246", "page": 36, "chunk": 0, "title": "wps7169", "pdf_url": "https://local/prwp/wps7169.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Ruweng Administrative Area|Pariang|ECRP-I county, refugee-hosting county|\n|10|Jonglei|Pibor|ECRP-I county, possible flood risk reduction county|\n|11|Jonglei|Fangak|Possible flood risk reduction county|\n|12|Jonglei|Twic East|Possible flood risk reduction county|\n\n\n\n35. **<mark>Support for refugees and host communities.</mark>** <mark>Using the WHR resources, ECRP-II will scale up</mark>\n<mark>activities in t</mark> he two refugee-hosting counties of <mark>Pariang</mark> and Maban to include larger numbers <mark>of refugees</mark>\n<mark>in prioritization of,</mark> and benefits from <mark>, infrastructure. Coupled with institutional strengthening activities,</mark>\nECRP-II <mark>will help</mark> promote a transition from humanitarian dependence to a more development-focused\napproach to displacement challenges in both areas. In the two refugee-hosting counties, UNHCR will\nprovide guidance on refugee issues. In accordance with data-sharing arrangements, UNHCR will share\nrefugee data to facilitate inclusion of refugee and host communities and help bring their voices into\nproject activities and oversight.\n\n\n36. **Subproject budget allocations** will be made in two rounds in each _payam_ to promote\ncommunities’ learning by doing. They will be calculated on a per capita basis, supplemented by a\nperformance element in the second round. The first tranche will be calculated based on population using\nthe most recent data from humanitarian organizations. <sup>51</sup> The second tranche will comprise a base\nallocation equal for all _payams_ (80 percent of the total subproject budget), supplemented by a\n\n\n51 County allocation", "output": {"entities": {"named_data": [], "descriptive_data": ["data from humanitarian organizations"], "vague_data": ["refugee data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000028", "page": 26, "chunk": 1, "title": "South Sudan - Second Phase of the Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/543171647442225562/pdf/South-Sudan-Second-Phase-of-the-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "refugee data", "label": "VAGUE_DATA", "score": 0.6528199315071106, "start": 981, "end": 993, "probe_score": 0.0231, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from humanitarian organizations", "label": "DESCRIPTIVE_DATA", "score": 0.8373076915740967, "start": 1428, "end": 1464, "probe_score": 0.4164, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a thorough analysis was\nnot available. Thus while there are some opportunities to study factors affecting demand, one can\nnot look for a normal, market-driven supply curve.\n\nTo explain the variation in _the number of land parcel sales (i.e., completed transactions) in_\n_Russian regions in 2004,_ we tested several variables. Since only land privatization procedures are\nrelevant for the substantiation of this hypothesis, only observations related to those procedures\nwere selected (Procedure 3А, see Page 10 for the list of procedures). Consequently, any\nobservations related to procedures for leasing a land plot were not included in the regression\nmodel. <sup>24</sup> [^24: Also, while pricing policies for land privatization are Federally regulated and relevant data are available, rental rates for land\nowned by sub-national authorities is subject to less regulation and comparable data are not available.]\n\n\nInitially, we tried to fit models with the data from the 15 regions where the surveys were\nconducted (see, for example, Table 2 above for the list of surveyed regions). Due to a limited\nnumber of observations, we had to restrict ourselves to the following three simple models that\n## each tested for the dependent variable γ, where:\n\n\n22 Due to limited availability of regional data, this number was even less, mostly 14 or 13 observations depending on\na model.\n23 Federal policy allows sub-national authorities to set the price of land for privatization between specified minima and maxima.\nAccording to the Article 2 of the Federal Law on Enactment of the Land Code, \"the RF Subject shall adopt the following land\nprices in the settlements with the following population numbers:\n(i) More than 3 million inhabitants ─ in the amount from five to thirty times the land tax for one square unit of a land plot;\n(ii) From 500 thousand to 3 million inhabitants ─ in the amount from five to seventeen times the land tax for one square unit of\na land plot;\n(iii) Up to 500 thousand", "output": {"entities": {"named_data": [], "descriptive_data": ["data from the 15 regions"], "vague_data": ["regional data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003328", "page": 13, "chunk": 1, "title": "wps4115", "pdf_url": "https://local/prwp/wps4115.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from the 15 regions", "label": "DESCRIPTIVE_DATA", "score": 0.758514404296875, "start": 960, "end": 984, "probe_score": 0.2556, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "regional data", "label": "VAGUE_DATA", "score": 0.6729714274406433, "start": 1286, "end": 1299, "probe_score": 0.206, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " themselves.\nUkrainian refugees make up the largest\nshares of the population in the city of\nWroclaw (7.4%), Przemysl, a city on the\nUkrainian border (6.5%), and in Pruszkowski\npoviat, a suburban area of Warsaw (6.3%).\nThe city of Warsaw comes seventh with\nUkrainian refugees comprising 5.6% of the\nlocal population.\n\n\n\n**Ukrainian refugees in Poland continue**\n**to get their incomes primarily from**\n**work.** In the SEIS survey conducted in\nMay and June 2024, 80% of the refugee\nhouseholds’ incomes came from work,\nwhich included full-time and part-time\nwork, self-employment, remote work, and\nother forms of employment in Poland, as\nwell as remote employment in Ukraine.\nThis is the same as in the previous\nMSNA survey, conducted in July and\nAugust 2023 (see Deloitte, 2024), despite\n\n\n\nthe fact that the child benefit received\nby 42% of Ukrainian refugee households\nincreased in that time from PLN 500 to\nPLN 800 a month. For a vast majority of\nUkrainian household the „Family 800+”\nchild benefit was the only social benefit that\nthey received from the Polish government.\nOnly 5% of Ukrainian refugee households\nclaimed an accommodation allowance,\n4% – a disability grant and an even smaller\npercentage – other benefits.", "output": {"entities": {"named_data": ["SEIS survey", "MSNA survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 5, "chunk": 2, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS survey", "label": "NAMED_DATA", "score": 0.8371747136116028, "start": 418, "end": 429, "probe_score": 0.9975, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "MSNA survey", "label": "NAMED_DATA", "score": 0.8403642773628235, "start": 710, "end": 721, "probe_score": 0.9784, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">which are lodged, processed<br>and resolved through the<br>SNSOP GRM divided by all<br>complaints which are<br>lodged, processed and/or<br>resolved, expressed as a<br>percentage<br>|<br>This<br>indicator<br>will be<br>reviewed<br>on a<br>monthly<br>basis<br>|Monthly<br>GRM Reports<br>|GRM data will be<br>reviewed and analyzed<br>on a monthly basis<br>through the MIS GRM<br>module<br>|Selected Implementing<br>Partner<br>|\n|Percentage of cash transfers to<br>beneficiary households made on time|The total number of cash<br>transfers which were<br>completed on time for both<br>LIPW and DIS, per the<br>Project Operations Manual,<br>divided by the total number<br>of cash transfers, expressed|This<br>indicator<br>will be<br>measured,<br>at a<br>minimum,<br>on a|SNSOP MIS<br>and payment<br>schedules<br>|Payment data stored in<br>the MIS will be<br>compared with<br>approved payment<br>schedules.<br>|Selected Implementing<br>Partner<br>|\n\n\nPage 59 of 74", "output": {"entities": {"named_data": [], "descriptive_data": ["GRM data", "Payment data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 63, "chunk": 1, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "GRM data", "label": "DESCRIPTIVE_DATA", "score": 0.6408376097679138, "start": 287, "end": 295, "probe_score": 0.1581, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Payment data", "label": "DESCRIPTIVE_DATA", "score": 0.6770451068878174, "start": 807, "end": 819, "probe_score": 0.6285, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Consulting and Non-Consulting Services of the project. All payments and\nwithdrawal of eligible expenditures under the DA will be made based on Statement of Expenses (SOEs) submission.\nProcedural details will be noted in the Disbursement and Financial Information Letter and all disbursements would\nbe subject to the terms of the Financing Agreement. MENFOP will be responsible for timely and periodic\nsubmissions of Withdrawal Applications (WAs) to claim the funds. However, it must be noted that the use of a\nDesignated Account will be subject to the resolution of pending lapsed loans under the country’s portfolio.\n\n**Accounting Standards**\n\n100. Previous projects implemented by MENFOP have adopted a set of general accounting principles which\nincludes inter alia: (a) accrual accounting is the approach that will be used, (b) project transactions and activities\nwill be separated from other MENFOP activities, and (c) all sources and uses of project funds, including payments\nmade and expenses incurred, will be part of project accounting. The Project financial reporting will include\nunaudited IFRs and annual Project Financial Statements (PFS). The PSU will be responsible for preparing periodic\nreports and bookkeeping for project activities and generate annual PFS and quarterly unaudited IFRs.\n\n**Audit Arrangements**\n\n101. Annual audits will cover all aspects of the Project, including but not limited to - uses of funds, committed\nexpenditures, financial operations, internal control and financial management systems and a comprehensive\nreview of statement of expenditures.  Audit reports need to be submitted to the World Bank by June 30 every\n\n\nPage 44 of 68", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000195", "page": 48, "chunk": 1, "title": "Djibouti - Skills Development for Employment Project", "pdf_url": "https://documents1.worldbank.org/curated/en/927731664308482374/pdf/IBArchive-38b35d89-2c5c-4636-ab7e-0ba662b95a5f.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "sup>recently</sup> <sup>come</sup> <sup>under Government control.</sup>\n\n\n\n**2.** **Main sector** issues **and** <sup>**Government strategy:**</sup>\n\n\n\n_Sector Issues._\n_Poverty in Sierra Leone._ Sierra <sup>Leone has</sup> <sup>the lowest</sup> <sup>Human Development Index</sup> <sup>**in**</sup> <sup>the world</sup>\n\n\n\nand has a GNP per capita <sup>of only US$130</sup> <sup>compared</sup> <sup>to the average</sup> <sup>for Sub-Saharan</sup> <sup>Africa</sup> <sup>of $470.</sup>\n\n\n\nOver 82% of the population <sup>currently</sup> <sup>lives below</sup> <sup>the poverty line and life expectancy is only</sup> <sup>38 years.</sup>\n\n\n\nFertility, infant and child <sup>mortality are</sup> <sup>high</sup> <sup>and over</sup> <sup>a third</sup> <sup>of children and</sup> <sup>a fourth</sup> <sup>of adults</sup> <sup>are</sup>\n\n\n\nmalnourished. The pnmary <sup>school enrollment</s", "output": {"entities": {"named_data": ["Human Development Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011760", "page": 7, "chunk": 1, "title": "Kenya - Land Settlement and Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/356681468273331257/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Human Development Index", "label": "NAMED_DATA", "score": 0.6837996244430542, "start": 251, "end": 274, "probe_score": 0.0779, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Annex 9:** **Statement** **of Loans** **and** **Credits**\n\nSIERRA LEONE: NATIONAL SOCIAL <sup>ACTION</sup> <sup>PROJECT</sup>\n\n**I** 1-Mar-2003\n\n\n\nDifference between expected\n\n\n\n**and** actual\nOriginal Amount in US$ Mllions disbursements\n\n\n\nProject ID FY Purpose IBRD IDA Cancel Undisb Ong Fmm ReVd\n\nP074320 2003 Basic Educ Rehab 0 00 0 00 0 00 20 66 000 0 00\n\nP074128 2003 HEALTH SECTORRECONSTR/DEVELOP PROJ 000 000 000 2066 023 000\n\nP073883 2002 HIV/A1DS RESPONSE PROJECT 000 15 00 000 1581 090 0 00\n\nP070201 2001 Second Public Sector MNnasgent <sup>Support</sup> 000 3 50 0 00 1 98 1 09 0 00\n\nP040649 2000 COMMUNITY REINTEGRATION & <sup>REHABIUTA</sup> 0 00 25 00 000 34 89 1 79 0 00\n\nP002422 1996 HEALTHSECTOR 000 2000 000 024 234 -688\n\nP002420 196e TRANSPORT SECTOR PRO 000 3500 000 338 652 241\n\nP002428 1995 URBAN WATER SUPPLY 000 3600 000 0 15 329 000\n\n\nTotal. 000 13450 000 9758 1616 -447\n\n\nSIERRA LEONE\nSTATEMENT OF EFC's\nHeld and Disbursed Portfolio\n\nJun 30 - 2002\nIn Millions US.Dollars\n\n\nConmitted Disbursed\n\nIFC IFC\n\n\n\nFY Approval Company Loan Equity Quasi Partic Loan Equity Quasi Partic\n\n2001 MSICIH 11 Sierra 4.00 0.00 0.00 0.00 0.00 0.00 0 00 0.00\n\nTotal Portfolio: 4.00 0.00 0.00 0.00 0.00", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000017", "page": 59, "chunk": 0, "title": "West Bank and Gaza - Integrated Community Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/158081468762622780/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " social risks** described earlier, the PforR includes a DLI requiring annual public\ndisclosure by Better Work Jordan of reports on factory-level compliance with a list of at least 29 social and\nenvironmental-related items. This DLI will help mitigate social risks, as well as environmental risks specific\nto occupational health and safety standards. This public disclosure DLI is expected to incentivize an\nincrease in compliance, improve MOL monitoring, and serve as a pilot for expansion to other laborintensive sectors.\n\n\n66. **The environmental risks are expected to be Moderate, with risks including worker health and**\n**safety, air pollution, industrial water effluent, and industrial waste management.** No PforR funds will\nsupport infrastructure financing.\n\n\n67. **The applicable federal and governorate environmental and social management systems in**\n**Jordan, from a legal, regulatory, and institutional perspective, are considered to be generally**\n**appropriate and comprehensive.** Therefore, no significant changes to the overall structure of these\nmanagement systems are required or proposed. However, the institutions, processes, and procedures at the\ngovernorate level are not supported by adequate human and/or financial capacity to operate as designed.\nEnforcement of the legal framework governing compliance on labor and environmental standards is weak.\n\n\n68. **Jordan’s environmental and social management systems will be strengthened by** (a) managing\nperception issues about who the winners and losers are in the program; (b) providing the human resources,\ntechnologies, and financial means for the MOL and Ministry of Environment to conduct compliance\nmonitoring of selected SEZ estates; (c) supporting the replication of the Worker’s Centers pilot at a zone\nlevel through other development partners (EU, ILO) to improve labor practices and occupational safety and\nhealth within SEZs; and (d) public reporting of factory-level compliance information on selected issues.\nFor further details, refer to Annex 6.\n\n\n20", "output": {"entities": {"named_data": [], "descriptive_data": ["factory-level compliance information"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 28, "chunk": 1, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "factory-level compliance information", "label": "DESCRIPTIVE_DATA", "score": 0.7461093664169312, "start": 1939, "end": 1975, "probe_score": 0.0089, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " earned by Ukrainian refugees than\n\n\n\nthe general population. UNHCR (2025b),\nusing a different method than the one in\nthis report, estimated average instead\nof median net wages based on the SEIS\ndata. The average net wage of a Ukrainian\nrefugee they arrived at was PLN 4,214, only\nslightly higher than calculated above. This\nwould yield 72% of the national average net\nwage. <sup>15</sup> Average is not used here, because\nmedian is more relevant for discussing\neconomic impact, as it is not disrupted\nby bottom or top earnings. Furthermore,\nthere are no outside estimates to compare\nit to. Second, as discussed previously, there\nare much fewer Ukrainian refugees with\nemployment contracts than Poles, and\nthis lowers their social contributions and\nthus gross earnings. Unfortunately, there\nis no such data available, as both SEIS and\nNBP (2024) measure only net earnings.\n\n\n\n**Chart 13. Polish citizens and Ukrainian refugees’ employment rates by age group**\n\n\nMale Female\n\n\n\n**Chart 14. Ukrainian refugee median net wage estimates in Q2 2024**\n\n\nMonthly net wage (PLN) Percengate of all workers total economy average\n\n\n84%\n\n\nUNHCR NBP UNHCR NBP\n15 May - 24 June 2024 6 May - 5 July 2024 15 May - 24 June 2024 6 May - 5 July 2024\n\n\nSource: Deloitte own elaboration based on SEIS survey, NBP (2024) survey. Monthly GUS median wage in the general economy has been recalculated to reflect the\nspecific time periods of SEIS UNHCR and NBP (2024) surveys.\n\n\n\nSource: Deloitte own elaboration based on Eurostat Labour Force Survey data SEIS UNHCR survey\nconducted in May and June 2024. For Polish citizens reference period is Q2 2024.\n\n\n\nPolish citizens Ukrainian refugees\n\n\n\n**The wages of Ukrainian refugees are**\n**higher for men than women, but the**\n**gap is not wider than in the economy**\n*", "output": {"entities": {"named_data": ["SEIS\ndata", "SEIS", "SEIS survey", "NBP (2024) survey", "Eurostat Labour Force Survey data", "SEIS UNHCR survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 9, "chunk": 2, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS\ndata", "label": "NAMED_DATA", "score": 0.7670316696166992, "start": 190, "end": 199, "probe_score": 0.0002, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "SEIS", "label": "NAMED_DATA", "score": 0.50426185131073, "start": 826, "end": 830, "probe_score": 0.001, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "SEIS survey", "label": "NAMED_DATA", "score": 0.6063446998596191, "start": 1275, "end": 1286, "probe_score": 0.999, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "NBP (2024) survey", "label": "NAMED_DATA", "score": 0.6544063091278076, "start": 1288, "end": 1305, "probe_score": 0.8582, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Eurostat Labour Force Survey data", "label": "NAMED_DATA", "score": 0.6656429171562195, "start": 1496, "end": 1529, "probe_score": 0.9804, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "SEIS UNHCR survey", "label": "NAMED_DATA", "score": 0.7098275423049927, "start": 1530, "end": 1547, "probe_score": 0.9549, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " ou l’inexistence d’école sur place et dans les environs du site de déplacement,\nconstituaient les principales raisons évoquées au niveau des différents sites évalués où les\nenfants déplacés ne fréquentent pas l’école. Les sites les plus touchés par cette problématique\nliée à l’éducation des enfants déplacés sont principalement localisés dans les cercles de Gao,\nNiono, Bourem, Dire, Ségou, Ansongo, Douentza, Gourma-Rharous, et Koro.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000716", "page": 29, "chunk": 2, "title": "Mali : Rapport Matrice de Suivi des Déplacements (DTM) décembre 2020", "pdf_url": "https://reliefweb.int/attachments/68ec8b51-5cb5-33e1-841e-3935cff669d3/DTM_DECEMBRE_2020.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014416", "page": 62, "chunk": 2, "title": "Kenya - Smallholder Coffee Improvement Project", "pdf_url": "https://documents.worldbank.org/curated/en/534211468914087372/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", from the\npublic land patrimony in order to avoid displacement and land acquisition.\n\n58. During project implementation, each project financed by the CPG will be subject to a\nscreening and control process undertaken by the LG itself, supported by regional mobile teams\nand representatives from the Ministry of Environment and Sustainable Development’s (MEDD)\ndeconcentrated services. On the basis of this screening, it will be determined if there will be\nacquisition of land and/or population displacement and if a Resettlement Action Plan is required.\n\n59. The Bank team completed a consultation workshop with key government stakeholders in\nJanuary 2013 as part of project preparation. During the workshop, two core areas of capacity\nsupport for strengthening social safeguards compliance were agreed: (i) strengthen the role of the\nDepartment of Environmental Control (DCE) in overseeing compliance with safeguards\nstandards, including social aspects (support to the Department to fully carry out this mandate will\nbe provided under project Component 2), and (ii) strengthen the capacity of LGs to manage and\nsupervise social safeguards compliance, including through technical assistance provided under\nthe mobile teams as well as pre-identified training sessions for LG staff. It is expected that this\nsupport will help LGs comply with the national legal and regulatory framework as well as with\n\n\n                           - 63", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000166", "page": 77, "chunk": 1, "title": "Mauritania - Local Government Development Program Project", "pdf_url": "http://documents1.worldbank.org/curated/en/943421468056371471/pdf/760530PAD0P127010Box377322B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "project evaluation\n\n\nResults o f the analysis by\nDLC on an annual basis\nwill be used to improve\nmarketing design and\nclient strategy with DPM\nassistance and feedback\nfrom the Board and\nconsultative meetings.\nResults of the analysis and\nthe change process should\nbe documented in\nprogress reportshusiness\nplans and Minutes o f the\nBoard and the\nconsultative meetings.\nInformation required for\nthe supervision mission,\nmid-term review and\nend-project evaluation\n\n\n\n_To what extent is_\n_the program or_\n_courses offered_\n_meeting the needs_\n_of_ _the Government_\n_and other_\n_benejkiaries_ ?\n\n\ni _the training in_\n_emand, particularly_\n_y_ _thoseplanning_\n_nd implementing_\n_x i a l and economic_\n_evelopmentpolicies_\n_nd programs?_\n\n\n\n\n- No. and type of\ncourses developed or\nsupplied that\ncorrespond to the\ntraining needs\nidentified for (a) civil\nservants (b) others\n\n- Reactions from\ntrained (a) civil\nservants and (b) others\n\n- Assessment - f the\nDLC’s responsiveness\nto and linkages\n(institutional and\noperational) with the\nGovt. public service\ntraining strategy\n\n- Ability of the DLC to\nprovide the training\nrequired by\ndevelopment projects\n\n\n- Number o f (a) civil\nservant and (b) private\n(c) NGO that are\nenrolling (numbers\nshown by course and in\ntotal as well as client\nlocation)\n\n- Extent to which\nnonparticipants inquire\nabout the DLC and its\nservices\n\n- Comparison of actual\nparticipants vs the\nnumber o f potential\nclients in the civil\nservice marketlproject\ntarget group\n\n- Explanation o f why\nnon participants do not\ntake advantage of the\nlearning opportunities,\nor what are the barriers\n\n\n\nMarket\nStudy/Training Needs\nAssessment conducted\nat the start of the\nproject by a consultant\nhired by DPM.\n\n\nThe training needs o f\nprojects collected by\nDPM annually with\nDPM’s response as\npart of the Business\nPlan\n\n\nStrategy paper by\nDPM on integrating\nand linking the DLC\nwith the Govt", "output": {"entities": {"named_data": [], "descriptive_data": ["training needs o f\nprojects"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008476", "page": 52, "chunk": 1, "title": "Kenya - Development Learning Centre Project", "pdf_url": "https://documents.worldbank.org/curated/en/136581468774917583/pdf/245130KE.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "training needs o f\nprojects", "label": "DESCRIPTIVE_DATA", "score": 0.5315611362457275, "start": 1715, "end": 1742, "probe_score": 0.8099, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\n7,000\n\n\n6,000\n\n\n5,000\n\n\n4,000\n\n\n3,000\n\n\n2,000\n\n\n1,000\n\n\n\n0\n\n\n\nTripoli Sabha Bani Walid Tunis Tamarasset Zawiya Zuwara Sabratha Algiers Qatrun Tarzibu Ajdabiya Kufra Benghazi Al Jawf\n\n\nPhysical violence Robbery Detention Bribery/extortion Death Kidnapping SGBV\n\n\n\n_Source:_ Based on 4Mi interviews collected by MMC from 2020 to first quarter 2023 (MMC).\n_Note:_ Subject to sample bias; please see Methodology section.\n\n\n       - The locations perceived most dangerous by those interviewed by MMC include Tripoli, Sabha,\nBani Walid, Tunis and Tamanrasset (Figures 22 and 23).\n\n       - According to the Libyan Anti-Torture Network, in 2020, 88 persons on the move were reported\ntortured to death in Libya. Lower figures were recorded in 2021 and the first trimester of 2022\nwith a total of 40 deaths reported. Challenges faced in documenting each case of torture during\nthis report’s time frame (2021–2022) indicate the possibility that the actual deaths resulting from\ntorture of people on the move may be higher than the figures reported (Libyan Anti-Torture\nNetwork, 2022:9).\n\n\nMapping abuses: Result by section\n### 38", "output": {"entities": {"named_data": [], "descriptive_data": ["4Mi interviews"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001558", "page": 51, "chunk": 1, "title": "On This Journey, No One Cares if You Live or Die: Abuse, Protection and Justice along Routes between East and West Africa and Africa’s Mediterranean Coast – Volume 2", "pdf_url": "https://reliefweb.int/attachments/f1ab39c7-f280-4900-b552-2fd4f3fe6058/pub2023-093-el-on-this-journey-vol-2.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "4Mi interviews", "label": "DESCRIPTIVE_DATA", "score": 0.7038624882698059, "start": 283, "end": 297, "probe_score": 0.9558, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda Health Services Transformation Program (P518373)\n\n\nThe World Bank\n1818 H Street, NW\nWashington, D.C. 20433\nTelephone: (202) 473-1000\n[Web: http://www.worldbank.org/projects](https://projects.worldbank.org/en/projects-operations/projects-home)\n\n\n**V. APPROVAL**\n\n\nTask Team Leader(s): Rogers Ayiko\n\n\nADM Environmental Specialist:\n\n\nADM Social Specialist: Margarita Puerto Gomez\n\n\nJul 06, 2026 Page 7 of 7", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003473", "page": 6, "chunk": 0, "title": "Initial Environmental and Social Review Summary (ESRS) - Uganda Health Services Transformation Program - P518373", "pdf_url": "https://documents.worldbank.org/curated/en/099070626103077115/pdf/P518373-1520afff-e77e-46e3-8a74-2ad025a18333.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "#### **Support to Energy and Water Institutions**\n\n\n\n**Support to the Ministry of Energy and Water**\n**(MoEW), Water Establishments and Electricite**\n**du Liban**\n\n\nThe delivery of basic energy, water and sanitation services\nalready faced serious pre-crisis challenges due to structural\ndeficiencies. With the rapid and sharp increase in demand,\nthe water supply, energy and solid waste systems have been\nplaced under extreme pressure to address needs.\nAs a result, Lebanon currently suffers from a water supply\ndeficit of around 40%. Almost two thirds of people across\nLebanon are drinking unsafely managed water from their\nprimary household source. Over a million people are not\nconnected to a water network, and the majority of families\nlack access to safe water because of contamination and\nlack of adequate treatment facilities. In parallel, wastewater\nmanagement continues to be poor, with 92 percent of\nsewage being discharged directly into watercourses without\ntreatment.\n\n\n**_More sustainable management of water resources_**\nIn this critical context, partners provided essential financial\nand technical support to the Ministry of Energy and Water\n(MoEW) to enhance the delivery of basic services (electricity,\nwater, sanitation and hygiene) and mitigate the impact of the\nSyrian crisis on the environment. Overall in 2016, $38m was\nchanneled to Energy and Water institutions and 7 additional\nstaff were provided at the national level to improve energy\nproduction and the sustainable management of water\nresources. In addition to several research studies, a feasibility\nanalysis was conducted in four sites to pilot aquifer\nrecharge interventions aimed at addressing water scarcity.\nBuilding on these efforts, hydrogeological assessments\nwere undertaken in 12 districts to assess the possibility of\nalternative water sources. At the policy level, the first national\nhousehold water quality survey was recently implemented\nto establish a baseline for the sustainable development goal\n(SDG). In addition, a wastewater treatment plant audit is\nbeing conducted to ameliorate wastewater management\ncapacities", "output": {"entities": {"named_data": [], "descriptive_data": ["national\nhousehold water quality survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000922", "page": 21, "chunk": 0, "title": "Support To Public Institutions Under The LCRP 2016 [EN/AR]", "pdf_url": "https://reliefweb.int/attachments/88c8fd1b-eaea-3f60-a4b8-2fea30bd1ba3/PIST_2017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "national\nhousehold water quality survey", "label": "DESCRIPTIVE_DATA", "score": 0.9013141989707947, "start": 1866, "end": 1905, "probe_score": 0.1683, "gold": "NON_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " be very well used at the local level\nas it is too generalised. This is particularly true of environmental data. The Government is\ntrying to make social economic data more available at local level.\n\nFunding constraints: donors are becoming more interested in the environment, but still often\nthink that integration of cross cutting issues can be done at no/low cost. However, funds are\nneeded for mitigation activities. It is necessary to insist with donors that environmental issues\nare important - it is a joint responsibility. It is important to highlight the needs and the\nresources we need - can use the NEAT+ for asking for funds.\n\n\n56", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["environmental data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000102", "page": 55, "chunk": 2, "title": "Colombia: CAI Maicao Reception Centre - Environmental Scoping Report and Recommendations (November 2019)", "pdf_url": "https://reliefweb.int/attachments/05f9e898-eb30-553a-9324-f3cfea1828cc/UNHCR-CAI-Maicao-Environmental-Scoping-Report_FINAL.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "environmental data", "label": "VAGUE_DATA", "score": 0.6172004342079163, "start": 93, "end": 111, "probe_score": 0.0345, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda Development Response to Displacement Impacts Project Phase II\n(P510476)\n\n\n\nPROJECT APPRAISAL\n\nDOCUMENT\n\n\n\n|Workdays created through labor-intensive public works activities (Number)|Col2|\n|---|---|\n|Description|Quantitative indicator counting number of workdays from LIPW under component 2.The data is then<br>disaggregated by gender, by youth (<30 years), refugee/host community status.|\n|Frequency|Quarterly|\n|Data source|Project MIS and Project Progress Reports.|\n|Methodology for<br>Data Collection|Monitoring project implementation.|\n|Responsibility for<br>Data Collection|IA|\n|**People engaged in land restoration or protection activities (Number)**|**People engaged in land restoration or protection activities (Number)**|\n|Description|Quantitative indicator counting number of people involved in activities for land restoration or protection<br>under component 2, covering both sub-components.|\n|Frequency|Semi-annual.|\n|Data source|Project MIS and Project Progress Reports.|\n|Methodology for<br>Data Collection|Monitoring project implementation.|\n|Responsibility for<br>Data Collection|IA|\n|**Eonomic Opportunity**|**Eonomic Opportunity**|\n|**Project beneficiaries accessing credit at least once from project-supported groups (Number)**|**Project beneficiaries accessing credit at least once from project-supported groups (Number)**|\n|Description|Quantitative indicator counting number of beneficiaries accessing credit at least once from project-supported<br>groups. The data is disaggregated by gender, youth (18-30 years) and refugee/host community status.|\n|Frequency|Quarterly|\n|Data source|Project MIS.|\n|Methodology", "output": {"entities": {"named_data": ["Project MIS and Project Progress Reports"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000186", "page": 47, "chunk": 0, "title": "Uganda - Second Phase of the Development Response to Displacement Impacts Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099051525164525007/pdf/BOSIB-ca473522-8ad0-4c80-9f0d-88bf887f2a2f.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Project MIS and Project Progress Reports", "label": "NAMED_DATA", "score": 0.7176023721694946, "start": 449, "end": 489, "probe_score": 0.4367, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NCHRD and MOE—which started under ERfKE II and contributed to producing key pieces of analytical\nwork that have played a significant role in policy development—will continue under the proposed\nProgram. <sup>21</sup> [^21: These include “School Rationalization Evaluation “(2011); “Program for International Student Assessment (PISA)\nNational Report” (2015); “Trends in International Mathematics and Science Study (TIMSS)”; “Classroom\nObservation” (to assess teachers’ application of “Student‐Centered Active Learning and Teaching”); “Gender Gap in\nStudent Achievement in Jordan Study Report” (2015); and “Mapping of Student Assessments in Jordan” (2014).] One example of an evaluation study can be to look at how gender issues are addressed\nacross different policy proposals and program interventions. The annual plan for the M&E activities\nwill be endorsed by the GPSC and shared with all concerned donors and education sector partners.\n\n52. **The MOE has strengthened its data systems and will continue to do so to meet the M&E**\n**requirements of the Program** . Under ERfKE II <sup>22</sup> [^22: With the technical assistance of UNESCO, financed through the World Bank then the EU.], the MOE completed the redesign of its OpenEMIS,\nwhich was successfully deployed in all public schools in Jordan. OpenEMIS is a comprehensive and\nintegrated information and data collection system, which covers all education levels. The system\ncaptures disaggregated school level data on students, teachers, grades, subjects, and teaching periods\nfor all MOE operated schools and institutions in the country. A dashboard linked to the OpenEMIS is\ncurrently being developed and will be accessible to individual units at the MOE to enable them to\nmonitor their respective indicators. The Queen Rania Center (QRC) manages the EMIS and its\ndashboard. In addition to software and hardware management, QRC is also responsible for data\nverification and will coordinate", "output": {"entities": {"named_data": [], "descriptive_data": ["disaggregated school level data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000127", "page": 23, "chunk": 0, "title": "Jordan - Education Reform Support Program-for-Results Project", "pdf_url": "http://documents1.worldbank.org/curated/en/731311512702123714/pdf/Jordan-Educ-Reform-121282-JO-PAD-11142017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "disaggregated school level data", "label": "DESCRIPTIVE_DATA", "score": 0.8651008009910583, "start": 1440, "end": 1471, "probe_score": 0.1471, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "## **Sana'a hub**\n###### **4.3.2 Geographical spread Sana'a**\n\nNihm continued to be an active frontline in the conflict, which was reflected in the district witnessing the highest number of\nrecorded civilian impact incidents in Sana’a governorate. 10 incidents (60%) were recorded in Nihm, 2 in Bani Matar (11%), 2 in\nHamdan (11%), 1 in Bilad Ar Rus (6%) and 1 in Al-Hayma Al-Dakhiliya (6%). The last two districts were recorded for the first time\nsince the start of the civilian impact monitoring project. At the same time neither Sanhan, Bani Hushaysh or Arhab witnessed any\nincidents during February-March, in contrast to the previous reporting period where the three districts witnessed 11 incidents.\n\nWith the highest number of incidents, Nihm also saw the highest number of casualties, with 14 casualties reported. Hamdan saw a\ncomparable casualty count, with 11 casualties, although seeing only 2 civilian impact incidents. The majority of houses and farms\ndamaged were also in Nihm as well as vehicles impacted, meanwhile the other districts saw a lower proportion of houses and farm,\nthough a broader distribution of other types of incidents, including infrastructure, exposure to armed conflict and local business.\n\nThe impact on women and children was relatively high compared to the other governorates in the Sana’a hub, with 14 out of 20\nwomen and child casualties being recorded in Sana’a governorate.\n\n###### **Civilian impact per district** **37**\n\n\n|Nihm|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|Col10|Col11|Col12|\n|---|---|---|---|", "output": {"entities": {"named_data": [], "descriptive_data": ["civilian impact monitoring project"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000158", "page": 36, "chunk": 0, "title": "Civilian Impact Monitoring Report - April 2018", "pdf_url": "https://reliefweb.int/attachments/0c736139-4f39-310c-9a02-88f72ed3b907/cimp_bi-monthly_report_feb-march_2018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "civilian impact monitoring project", "label": "DESCRIPTIVE_DATA", "score": 0.7061001062393188, "start": 471, "end": 505, "probe_score": 0.755, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ") the procedures for calling for bids, selecting\nconsultants and awarding contracts; (b) procedures and sample contracts for community-based\nprocurement; (c) internal organization for supervision and control, including operational\nguidelines defining the role of the executing agency and reporting requirements; and (d)\ndisbursement procedures.\n\n\n48. **Project Procurement Strategy for Development.** A PPSD was prepared to ensure that\nprocurement activities are packaged and prepared in such a way as to minimize risk to the project.\nThe PPSD concludes that the environment is favorable for procurement of the activities envisaged\nunder the proposed project. These comprise primarily (a) small works: construction and\nrehabilitation; (b) goods and non-consulting services: vehicles and motorcycles; computers and IT\nequipment and laboratory equipment; and (c) consulting services: individual consultants and firms\nof consultants for specific activities. Among the latter, the PPSD makes a distinction between\nspecialized consultants and others.\n\n49. The national market for small works, vehicles and motorcycle, computers and IT\nequipment, communication equipment, and consulting services is sufficient to meet the project’s\nneeds. Many local firms have the capability and competencies to participate in open competitive\nbidding but there are few firms with capability to offer vehicles and motorcycles.\n\n\nPage 69", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000035", "page": 73, "chunk": 1, "title": "Chad - Refugees and Host Communities Support Project", "pdf_url": "http://documents.worldbank.org/curated/en/658761536982256019/pdf/PAD2809-PAD-PUBLIC-disclosed-9-12-2018-IDA-R2018-0286-1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n\n**<u>REGIONAL REFUGEE EMPLOYMENT RATE BY LEVEL OF</u>**\n\n**LOCAL LANGUAGE KNOWLEDGE (2024)**\n\n\nEmployment rate Share of the refugee population (rhs)\n\n\n\n80%\n\n\n60%\n\n\n40%\n\n\n20%\n\n\n0%\n\n\n\n<u>35%</u>\n\n\n\nDoes not\nunderstand\n\n\n\nBeginner Intermediate Advanced Fluent\n\n\n\nSource: Survey data\n\n\nThe 2024 survey introduced a new question on local language proficiency, reinforcing previous findings of a\nstrong correlation between language skills and employment. Respondents with at least an intermediate level of\nlocal language proficiency reported nearly twice the employment rate compared to those with no knowledge\n(9% of respondents). Even Ukrainians with only a basic understanding—limited to a few words or phrases (28%\nof the sample)—experienced a notable increase in employment compared to those with no local language\nskills <sup>16</sup> [^16: The data also demonstrates that the employment rate of refugees fluent in the local language is lower than for those with\nan intermediate or advanced knowledge. The reason for this is that the former group is heavily concentrated in lower age\nbrackets, with almost 30% being 15-19 years old] .\n\n\nFinally, unlike for the host population, refugee employment rates were found to be practically the same for all\neducation levels above technical or vocational <sup>17</sup>, implying that local employment markets may not be valuing\nadvanced degrees. Possible explanations include impediments to foreign qualifications recognition and other\nbarriers that are preventing placement into high-skilled jobs (such as language, a mismatch between\nqualifications and local demand, etc.).\n\n\n**Wages also improved but remain significantly below host levels**\n\n\nDespite a 28% increase in the regional weighted average wage of refugees in 2024, this figure still stands 30%\nlower than that of the local population. This means that, on average, Ukrainians earned roughly two-thirds of\nwhat their hosts did", "output": {"entities": {"named_data": [], "descriptive_data": ["2024 survey"], "vague_data": ["Survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 11, "chunk": 0, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Survey data", "label": "VAGUE_DATA", "score": 0.6700465083122253, "start": 376, "end": 387, "probe_score": 0.999, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2024 survey", "label": "DESCRIPTIVE_DATA", "score": 0.7158918380737305, "start": 394, "end": 405, "probe_score": 0.9953, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda: Investment for Industrial Transformation and Employment (P171607)\n\n\nindicated that they struggled to make ends meet. <sup>12</sup> [^12: Federation of Small and Medium Sized Enterprises in Uganda (August 2021).] Of those MSMEs in Kampala, 45 percent reported closing their\nbusiness as a direct consequence of the pandemic. They were facing both demand (willingness to spend) and\nsupply (labor force disruptions) constraints. Socioeconomically depressed districts, such as those hosting refugees,\nare expected to be even further negatively impacted. The poorest quintiles and vulnerable communities, including\nrefugees, are already showing significant income reductions and increased food insecurity.\n\n\n**B. Sectoral and Institutional Context**\n\n\n10. **COVID-19 remains a significant threat to emerging economic transformation in Uganda and**\n**puts prospects of new jobs in danger.** Data from the June 2020 <sup>13</sup> [^13: Uganda Bureau of Statistics June 2020 conducted with the support of the World Bank.] Uganda Bureau of Statistics (UBOS) high\nfrequency phone survey on the impact of the COVID-19 pandemic show that the following sectors lost the highest\nnumber of workers: services 43 percent, commerce 43 percent, and transport 39 percent. It is expected that the\nhardest-hit firms will be exporters to international markets, manufacturing companies, and start-ups. The\nfloriculture industry, for example, which employs over 10,000 people, is still facing severe disruptions in its supply\nchains and cancellation of orders. Restarting or continuing economic transformation will require the provision of\nnew loans and products in the market, leaner and more efficient firms and rapid adaptation to new market\nconditions, and the capacity to identify new markets and sources of demand, particularly for new and exporting\nfirms. This is consistent with the World Bank Group’s economic response including the <mark>Green, Resilient, and</mark>\n<mark>Inclusive Development (</mark>", "output": {"entities": {"named_data": [], "descriptive_data": ["Data from the June 2020", "high\nfrequency phone survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000021", "page": 16, "chunk": 0, "title": "Uganda - Investment for Industrial Transformation and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/469061641926083502/pdf/Uganda-Investment-for-Industrial-Transformation-and-Employment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data from the June 2020", "label": "DESCRIPTIVE_DATA", "score": 0.7066556215286255, "start": 911, "end": 934, "probe_score": 0.9993, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "high\nfrequency phone survey", "label": "DESCRIPTIVE_DATA", "score": 0.8159856796264648, "start": 1075, "end": 1102, "probe_score": 0.9305, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">follows the protocols<br>developed by WHO <br>Every 6<br>months<br> <br>WHO and<br>GHOs<br> <br>WHO to aggregate<br>reports from GHOs<br> <br>WHO and GHOs<br>|Number of health staff trained in infection<br>prevention and control per WHO<br>protocols <br>Health staff receiving<br>infection prevention and<br>control training which<br>follows the protocols<br>developed by WHO <br>Every 6<br>months<br> <br>WHO and<br>GHOs<br> <br>WHO to aggregate<br>reports from GHOs<br> <br>WHO and GHOs<br>|Number of health staff trained in infection<br>prevention and control per WHO<br>protocols <br>Health staff receiving<br>infection prevention and<br>control training which<br>follows the protocols<br>developed by WHO <br>Every 6<br>months<br> <br>WHO and<br>GHOs<br> <br>WHO to aggregate<br>reports from GHOs<br> <br>WHO and GHOs<br>|Number of health staff trained in infection<br>prevention and control per WHO<br>protocols <br>Health staff receiving<br>infection prevention and<br>control training which<br>follows the protocols<br>developed by WHO <br>Every 6<br>months<br> <br>WHO and<br>GHOs<br> <br>WHO to aggregate<br>reports from GHOs<br> <br>WHO and GHOs<br>|", "output": {"entities": {"named_data": [], "descriptive_data": ["reports from GHOs", "reports from GHOs"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000008", "page": 30, "chunk": 2, "title": "Yemen - Emergency COVID-19 Project", "pdf_url": "http://documents1.worldbank.org/curated/en/106571586194037855/pdf/Yemen-Emergency-COVID-19-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "reports from GHOs", "label": "DESCRIPTIVE_DATA", "score": 0.5983767509460449, "start": 117, "end": 134, "probe_score": 0.2224, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "reports from GHOs", "label": "DESCRIPTIVE_DATA", "score": 0.5702651143074036, "start": 451, "end": 468, "probe_score": 0.3856, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " project design are summarized below:\n\n\n     - _Strategic storage_ : Strategic reserves provide countries with critical lead time to secure alternative grain\nsupplies or supply routes during times of crisis. Reserves also offer psychological benefits that may prevent\nhoarding and pilferage. Moreover, historical data suggest a strong negative correlation between changes in\ngrain stocks and changes in grain prices. Not only could increasing strategic reserves reduce domestic price\nvolatility and the frequency of domestic price shocks, but it could also impact the global grain market and in\nturn mitigate international price risks. Importantly, the benefits of strategic reserves must be measured\nagainst the cost of maintaining them.\n\n\nPage 22 of 54", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["historical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 26, "chunk": 2, "title": "Jordan - Emergency Food Security Project", "pdf_url": "http://documents.worldbank.org/curated/en/486071652556836130/pdf/Jordan-Emergency-Food-Security-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "historical data", "label": "VAGUE_DATA", "score": 0.7840671539306641, "start": 302, "end": 317, "probe_score": 0.0002, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " ensure the protection of stateless persons, the\nnaturalization of the Makonde community, and an agreement to naturalize qualifying members of the\nShona community. However, scarce socioeconomic information of stateless populations that is comparable to nationals prevents a deeper understanding of their living conditions, hence hindering efforts\nto design targeted policy aimed at solving statelessness.\n\n\n**The Shona SES provides comparable socioeconomic profiles for the Shona community and nation-**\n**als, while contributing toward informing a targeted response to address the socioeconomic impacts**\n**of the COVID-19 pandemic.** Together with the Department of Immigration Services (DIS) and the\nKenya National Bureau of Statistics (KNBS) of the GoK, UNHCR Kenya, with technical support from the\nWorld Bank, conducted a preregistration exercise and socioeconomic survey for the Shona commu\nnity. The Shona SES marks one of the first quantitative studies of a stateless population that is based\non a national socioeconomic assessment tool. The SES compares the living conditions of the Shona\ncommunity residing in Nairobi and urban Kiambu counties to the conditions of Kenyan nationals in\nsuch counties, as well as to the national urban average. <sup>3</sup> [^3: Results from the Shona survey are compared to those from the Kenya National Bureau of Statistics and its Kenya Integrated\nHousehold Budget Survey 2015/16.] This approach does not attempt to establish\na causal connection between their legal status and living conditions. It does, however, provide evidence that shows strong correlations between statelessness, access to rights, and key indicators of\nwell-being. In addition, the SES links its findings to the results of the first wave of the Kenya COVID-19\nRapid Response Phone Surveys (RRPS) designed to assess the socioeconomic impacts of the COVID19 pandemic on nationals, refugees, and stateless persons.\n\n\n1 Based on the information available from 76 countries.\n2 [https://www.unhcr.org/protection/statelessness/54621bf49/global-action-plan-end-statelessness-2014-2024.html](https", "output": {"entities": {"named_data": ["Shona SES", "Kenya COVID-19\nRapid Response Phone Surveys"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001424", "page": 10, "chunk": 1, "title": "Understanding the Socioeconomic Conditions of the Stateless Shona Community in Kenya", "pdf_url": "https://reliefweb.int/attachments/dd3b5471-e866-3ca9-a23f-a4edfb270c6b/5fe319694.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Shona SES", "label": "NAMED_DATA", "score": 0.5540415048599243, "start": 413, "end": 422, "probe_score": 0.96, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Kenya COVID-19\nRapid Response Phone Surveys", "label": "NAMED_DATA", "score": 0.8716718554496765, "start": 1761, "end": 1804, "probe_score": 0.9836, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " by\n1.4 pp. (PLN 6,000-8,000), 0.6 pp.\n(PLN 8,000-10,000), and 0.3 pp. (above\nPLN 10,000) (see Chart 30).\n\n\n\nThird, cross-section regression analysis\nshows that poviats with a higher number of\nUkrainian refugees saw a greater increase\nin wages, which was caused by larger\nshare of refugees in local employment.\nDue to limitations in the wage dataset,\nour calculations incorporated yearly data.\nCross-section models were estimated using\na data sample for all 380 poviats in 2023.\nThe share of Ukrainian refugees among\nall employed, temporarily employed, and\nself-employed persons insured at ZUS in a\ngiven poviat was averaged across quarters\nto construct a yearly variable. The wage\nvariable is the GUS data series on gross\nmonthly wages and salaries <sup>30</sup> [^30: Unfortunately, GUS data for these time periods and poviat level include the enterprise sector (firms that employ 10 or more persons) and public sector, which is\nmost of the labour market, but not the total economy.], and taken\nas nominal change in 2023 from 2022.\nThe ordinary least squares cross-section\nmodel shows that in 2023, a 1 percentage\npoint increase in the employment share of\nUkrainian refugees was associated with an\nincrease in wages of PLN 66. Given that in a\nmean poviat gross wage growth amounted\nto PLN 757 and the gross wage in the\nprevious year was PLN 5,803, wages have\ngrown by 13.1% in nominal terms (including\ninflation), of which 0.7 percentage points\nwere associated with Ukrainian refugees\n(considering the fact that the employment\nshare of the Ukrainian refugees in a mean\npoviat was 0.61%).\n\n\nInstrumental variables regressions were\nperformed with the Two Stage Least\nSquares technique. In the first stage, it\nadjusts for the non-random distribution\nof Ukrainian refugees across poviats,\nand in the second stage, it calculates\nthe models. These results can be\ninterpreted causally. The", "output": {"entities": {"named_data": ["GUS data series", "GUS data"], "descriptive_data": ["wage dataset"], "vague_data": ["yearly data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 20, "chunk": 2, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "wage dataset", "label": "DESCRIPTIVE_DATA", "score": 0.8019264936447144, "start": 337, "end": 349, "probe_score": 0.9753, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "yearly data", "label": "VAGUE_DATA", "score": 0.6990386247634888, "start": 381, "end": 392, "probe_score": 0.9971, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "GUS data series", "label": "NAMED_DATA", "score": 0.8672032356262207, "start": 698, "end": 713, "probe_score": 0.8794, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "GUS data", "label": "NAMED_DATA", "score": 0.6090720295906067, "start": 785, "end": 793, "probe_score": 0.9712, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ",\nthe figures were prepared on a desk-by-desk basis, and did not conform to a standard format.\nThe Public Information Service published an annual refugee map and statistical table, but this\nsimply contained a single figure for each host country in the world, without any explanatory\nnotes or any indication as to the national origins of those refugees.\n\n\nWhen UNHCR’s evaluation unit undertook a detailed review of the statistical function in 1985,\nthe severity of the situation was revealed. Because the data at its disposal was so poor, the\nreview concluded, UNHCR was losing control of its programmes and losing credibility in the\neyes of donors. “As confidence in the statistics provided starts to decline,” the review stated,\n“numerous ad hoc and costly re-enumerations have been embarked upon, but with little\nconsideration of lessons learned in other countries and with little understanding of the\nlimitations of the techniques.”\n\n\nLooking further into the function, the review identified a range of other problems. First, the\norganization was in some situations “totally dependent on host governments for the numbers\non which assistance programmes are based.” Second, its efforts lacked consistency and\ncontinuity. At headquarters, several different UNHCR units were producing their own statistics,\nbut without making any real attempt to coordinate their activities. In the field, enumeration\nsystems were being “reinvented again and again by different staff of different levels of\ncompetence.” “In a few countries,” the report observed, “there is no way whatever to be certain\nabout _any_ figure.” Third, the report concluded, there was a general lack of seriousness in the\nway that statistics were handled. “Refugee enumeration is generally recognized as the\nfoundation of effective relief and assistance programmes, but it is almost inevitably given the\nlowest ranking in an emergency… In some situations, staff and officials may not merely neglect\nregistration, but oppose it.” <sup>34</sup>\n\n\nSeven years later,", "output": {"entities": {"named_data": [], "descriptive_data": ["refugee map and statistical table"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000558", "page": 14, "chunk": 1, "title": "\"Who has counted the Refugees?\" UNHCR and the Politics of Numbers", "pdf_url": "https://reliefweb.int/attachments/524235ad-ad20-3b57-8f5d-fb4ced1d78d8/ED9302CE174AB751C1256DAD0037FB44-hcr-count-jun99.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "refugee map and statistical table", "label": "DESCRIPTIVE_DATA", "score": 0.7959514260292053, "start": 146, "end": 179, "probe_score": 0.4398, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " de sus socios\ny donantes, ha apoyado al Gobierno del Ecuador en el\ndesarrollo de capacidades institucionales, la formación\nde personal, la modernización de procedimientos y el\nacompañamiento en la evaluación de casos complejos. Estos\nesfuerzos han contribuido a mejorar la eficiencia, calidad y\nsensibilidad del sistema nacional de asilo, permitiendo no\nsolo mayores volúmenes de reconocimiento, sino también\ndecisiones más oportunas y centradas en la protección. En\nun contexto regional desafiante y con recursos cada vez\nmás limitados, estos logros son un testimonio del impacto\npositivo que puede tener la cooperación internacional para\ngarantizar los derechos de las personas forzadas a huir.\n\n\n4000\n\n\n\n20000\n\n\n15000\n\n\n10000\n\n\n5000\n\n\n0\n\n\n\n\n\n2019 2020 2021 2022 2023 2024\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n3500\n\n3000\n\n2500\n\n2000\n\n1500\n\n1000\n\n500\n\n0\n\n\n\n\n\nFuente: Gobierno de Ecuador\nDepartamento de Protección Internacional a abril 2025\n\n\n\n2025*\n\n\n\nFuente: Gobierno de Ecuador\nDepartamento de Protección Internacional a abril 2025\n\n\n\n<u>[Fuente: Infografía solicitudes de asilo DPIN.](https://www.cancilleria.gob.ec/wp-content/uploads/2022/11/Infograf%C2%B0a-de-hist%C2%A2rico-de-solicitantes-de-refugio-colombianos-venezolanos-y-otros-pa%C2%B0ses-Oct-2022.pdf)</u> <u>[Fuente: Infografía reconocimientos DPIN.](https://www.cancilleria.gob.ec/wp-content/uploads", "output": {"entities": {"named_data": ["Infografía solicitudes de asilo DPIN", "Infografía reconocimientos DPIN"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000717", "page": 14, "chunk": 2, "title": "Ecuador: Informe Tendencias Nacionales - El desplazamiento forzado en Ecuador 2025", "pdf_url": "https://reliefweb.int/attachments/68fb243f-0f79-5d3a-a683-58c79916862e/250620_ACNUR%20Ecuador%20-%20TENDENCIAS%20NACIONALES%202025%20-%20VF.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Infografía solicitudes de asilo DPIN", "label": "NAMED_DATA", "score": 0.576774001121521, "start": 1032, "end": 1068, "probe_score": 0.9398, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Infografía reconocimientos DPIN", "label": "NAMED_DATA", "score": 0.5172399282455444, "start": 1264, "end": 1295, "probe_score": 0.7702, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "month, three months, and one year depending on the type of expense. Given the similarities\n\nbetween the change in food expenditure and the total household expenditure, it does not seem\n\nlikely that the longer reference period of some consumption items is affecting the timing of the\n\nexpenditure declines being uncovered in the baseline pattern.\n\n\nLastly, table 2 investigates potential heterogeneity in the drop in expenditure. Specifically,\n\ncolumn (8) re-estimates the baseline specification, but restricts the sample to households where\n\nthe head finished primary school; and column (9) re-estimates the baseline specification, but\n\nrestricts the sample to households where the head did not finish primary school. The estimates\n\nin columns (8) and (9) demonstrate that the timing of expenditure drops varies between the\n\ntwo types of households. Less-educated households observe an immediate drop in expenditure\n\nin October, while one cannot reject the hypothesis at conventional significance levels that more\neducated households did not reduce their expenditure in October. <sup>22</sup>\n\n\nThus, although there is an average drop in expenditure for all households by December,\n\nthere is significant heterogeneity in when this decline in expenditure occurred. The results are\n\nconsistent with better-off households being better able to cope with the occupation initially\n\nthan less better-off households. Although the survey did not capture savings, one potential\n\nexplanation for this pattern was that better-off households might have been able to rely more\n\non savings than other households.\n\n\n**5b.** **Brief** **Discussion** **of** **Interpreting** **the** **Expenditure** **Changes**\n\n\nThe above expenditure patterns are consistent with the declines being caused by the capture\n\nof Sana’a. It is important to note that these results are robust to two important concerns.\n\nFirst, one might be worried about the possibility that the poor economic conditions might\n\nhave led to the capture", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007392", "page": 14, "chunk": 0, "title": "wps8458", "pdf_url": "https://local/prwp/wps8458.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey", "label": "VAGUE_DATA", "score": 0.5954472422599792, "start": 1422, "end": 1428, "probe_score": 0.9281, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " CGAP.\n10 Uganda remittances were US$1.3 billion in 2019, US$1.425 billion in 2018 and US$1.2 billion in 2017, World Bank 20172019 data.\n11 The Economic Policy Research Centre conducted a rapid survey of businesses which indicated that three-quarters of businesses\nhave laid off employees due to the risks and subsequent containment measures presented by COVID-19, and estimated that 3.8\nmillion workers would lose their jobs permanently while 625,957 workers risk losing their jobs permanently, if the threat of\nCOVID and associated containment measures persist for the next six months.\n\n\nJun 09, 2020 Page 5 of 9", "output": {"entities": {"named_data": ["World Bank 20172019 data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000043", "page": 4, "chunk": 2, "title": "Project Information Document - Uganda: Investment for Industrial Transformation and Employment - P171607", "pdf_url": "http://documents.worldbank.org/curated/en/790161604416004965/pdf/Project-Information-Document-Uganda-Investment-for-Industrial-Transformation-and-Employment-P171607.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Bank 20172019 data", "label": "NAMED_DATA", "score": 0.6167967915534973, "start": 111, "end": 135, "probe_score": 0.0269, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "achieve the minimum service delivery requirements in terms of infrastructure, equipment, staffing\nas well as other arrangements to deliver RMNCAH activities. In accordance with the results focus\nof the project, these complementary central level activities will be financed using the Disbursement\nLinked Indicator (DLI) approach which links payments/disbursements to the attainment of selected\nresults/targets.\n\nComponent Three: Strengthen Capacity for Civil Registration and Vital Statistics (US$10 million).\n\nThe objective of this component is to support the GoU to improve the civil registration and vital\nstatistics system. The activities supported by this component will be aligned to the Global Civil\nRegistration and Vital Statistics Scaling Up Investment Plan 2015-2024. The areas of focus will\ninclude: (i) strengthening the CRVS institutions (such as the Uganda Bureau of Births and Deaths\nRegistration and the National Identification and Registration Authority); (ii) institutionalization of\nCRVS at local councils and community level; (iii) Removing the barriers to birth registration; (iv)\nimproving reporting and analysis of deaths and cause of death data; and (v) improving the\ndissemination and use of vital statistics.\n\n|Safeguard Policies that might apply Safeguard Policies Triggered by the Project|Yes|No|TBD|\n|---|---|---|---|\n|**Safeguard Policies Triggered by the Project**|**Yes**|**No**|**TBD**|\n|Environmental Assessment OP/BP 4.01|✖|||\n|Natural Habitats OP/BP 4.04||✖||\n|Forests OP/BP 4.36||✖||\n|Pest Management OP 4.09||✖||\n|Physical Cultural Resources OP/BP 4.11|✖|||\n|Indigenous Peoples OP/BP 4.10||✖||", "output": {"entities": {"named_data": [], "descriptive_data": ["deaths and cause of death data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009884", "page": 3, "chunk": 0, "title": "Project Information Document (Concept Stage) - Uganda Reproductive, Maternal and Child Health Services Improvement Project - P155186", "pdf_url": "https://documents.worldbank.org/curated/en/229551468008119268/pdf/PID-Print-P155186-02-11-2016-1455187049536.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "deaths and cause of death data", "label": "DESCRIPTIVE_DATA", "score": 0.5237131714820862, "start": 1138, "end": 1168, "probe_score": 0.4638, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Pharmaceutical Patents and Prices:\nA Preliminary Empirical Assessment Using Data from India\n\n\nMark Duggan and Aparajita Goyal <sup></sup>\n\n\n_JEL:_ O31, 034, L24, L43, I18\n\n_Keywords:_ Intellectual Property Rights, Technological Innovation, Patents,\nPharmaceutical Industry\n\n\n We are extremely grateful to Pete Lanjouw for bequeathing Jenny Lanjouw’s background material on\nIndia’s pharmaceutical industry to us, and to Daniel Lederman for help in obtaining the proprietary data\nfrom IMS Health. Thanks to a number of Intellectual property rights lawyers and industry experts, in\nparticular Tahir Amin, Ramesh Adige, Usha Rao, Manoj Kamra, Sudip Chaudhuri, Jayashree Watal for\nexplaining the institutional details of the pharmaceutical market and legal implications of TRIPs reform\nin India. Funding from the World Bank Research Support Budget, and the World Bank executed Trust\nFund on Trade is gratefully acknowledged. The views expressed in this paper are those of the authors and\ndo not necessarily reflect those of the World Bank, its Board of Directors, or the countries they represent.\nContact: Aparajita Goyal at World Bank, 1818 H Street, NW, Washington, DC 20433, Email:\nagoyal3@worldbank.org; Mark Duggan at the Wharton School of the University of Pennsylvania, 3620\nLocust Walk, Philadelphia, PA 19104, Email: mduggan@wharton.upenn.edu", "output": {"entities": {"named_data": ["proprietary data\nfrom IMS Health"], "descriptive_data": [], "vague_data": ["Data from India"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005234", "page": 2, "chunk": 0, "title": "wps6063", "pdf_url": "https://local/prwp/wps6063.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data from India", "label": "VAGUE_DATA", "score": 0.609444260597229, "start": 76, "end": 91, "probe_score": 0.993, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "proprietary data\nfrom IMS Health", "label": "NAMED_DATA", "score": 0.6666466593742371, "start": 463, "end": 495, "probe_score": 0.8596, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " relevant and significant volumes of resources will be needed\nto help Jordan and the countries in the region recover from the regional crisis.\n\n\n6. **This World Bank intervention will support Syrian refugees and the Jordanian host**\n**communities.** The severity of the external shock the Syrian and Iraqi crisis imposed on Jordan requires an\nexceptional and targeted response. Moreover, the proposed operation will be provided on concessional\nterms through use of an IDA Credit and support from a new Concessional Financing Facility (CFF), set up\n\n1 As an indication, and comparing 2015 results with 2014, the number of tourist arrivals regressed by 9.7 percent;\nsimilarly, the number of construction permits were 9.6 percent lower and exports to Iraq and Syria were cut by 40.5\npercent and 40.3 percent, respectively.\n2 Economic growth averaged 6.5 percent from 2000 to 2009. The economy’s performance was more muted from 2010\nto 2014, averaging growth of 2.7 percent.\n3 _Source:_ UNHCR June 2016.\n\n\n1", "output": {"entities": {"named_data": [], "descriptive_data": ["tourist arrivals"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 9, "chunk": 2, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "tourist arrivals", "label": "DESCRIPTIVE_DATA", "score": 0.5064043402671814, "start": 621, "end": 637, "probe_score": 0.0005, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "probability distribution of shocks for each household. For each location, we can obtain the\n\n\ndistribution of shocks from historical data on drought incidence. In our case we have monthly\n\n\nrainfall and temperature data for well-defined spatial grids from 1998 to 2012. Therefore we can\n\n\nobtain the historical distribution of shocks that a household is likely to encounter at a location.\n\n\nWe exploit this knowledge in combination with our knowledge on the average effect of a shock\n\n\nto calculate for each location the “expected loss” occurring from exposure to weather shocks for\n\n\neach time period in our historical distribution of the drought measure. In some periods the\n\n\ndrought measure is positive, and the expected loss will be zero. Based on this, it is possible to\n\n\nevaluate how many (if any) observations will fall below a specified outcome measure threshold\n\n\nin a hypothetical future period, thus indicating vulnerability rates at different risk-levels.\n\n\nWe apply this empirical strategy to measuring vulnerability to malnutrition for young\n\n\nchildren in West Africa. We use DHS data from five West African countries in order to capture\n\n\nthe incidence and prevalence of underweight and stunting that can be attributed to droughts. In\n\n\nthe next section we take up a discussion of the results.\n\n\n**5.** **RESULTS AND DISCUSSION**\n\n\nTable 3 shows the first stage results – the impact of shocks. The dependent variables are\n\n\nthe two most common measures of child malnutrition. Both variables are standardized relative to\n\n\nthe global reference median for children of the same age. The shock variable is also normalized\n\n\nusing the distribution over time and across space in our sample. The dependent variable is scaled\n\n\nby 100. Therefore, the results suggest that for a standard deviation change in shocks, stunting\n\n\nchanges by around an eighth of a standard deviation. The impact on underweight is just slightly\n\n\n18", "output": {"entities": {"named_data": ["DHS data"], "descriptive_data": ["historical data on drought incidence", "monthly\n\n\nrainfall and temperature data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006248", "page": 19, "chunk": 0, "title": "wps7171", "pdf_url": "https://local/prwp/wps7171.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "historical data on drought incidence", "label": "DESCRIPTIVE_DATA", "score": 0.6818484663963318, "start": 122, "end": 158, "probe_score": 0.4316, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "monthly\n\n\nrainfall and temperature data", "label": "DESCRIPTIVE_DATA", "score": 0.8852656483650208, "start": 180, "end": 219, "probe_score": 0.7524, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "DHS data", "label": "NAMED_DATA", "score": 0.8432738184928894, "start": 1092, "end": 1100, "probe_score": 0.6375, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on social development issues"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000096", "page": 24, "chunk": 0, "title": "Guinea - Multi-Sectoral AIDS Project (MAP)", "pdf_url": "http://documents1.worldbank.org/curated/en/570211468749964429/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on social development issues", "label": "VAGUE_DATA", "score": 0.581004798412323, "start": 1670, "end": 1703, "probe_score": 0.333, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "To explore the potential of an India–Bangladesh bilateral FTA, the World Bank (2006) provided a\ncomparative assessment between Bangladesh and India with respect to cement, light bulbs, sugar, and\nreadymade garments (RMGs). The partial equilibrium simulation suggested that for cement, lights bulbs,\nand sugar the likely effects of an FTA between Bangladesh and India were an expansion of Indian exports\nto Bangladesh, but no exports from Bangladesh to India. This is mainly because Indian export prices for\nthese products are substantially lower than ex-factory, before-tax prices of the same or similar products in\nBangladesh. The simulations for RMGs predicted increased Bangladeshi exports to India and also\nincreased RMG exports from India to Bangladesh. The study found that an FTA would bring large\nwelfare gains for consumers in Bangladesh provided there is adequate expansion of infrastructure and\nadministrative capacity at custom borders. It, however, cautioned that the benefits of such an FTA for\nBangladesh could be wiped out if it had the effect of keeping out cheaper, third-country imports (mainly\nfrom East Asia), and such trade diversion costs could be large. The study suggested that the only way to\nminimize trade diversion costs would be through further unilateral liberalization.\n\nStudies based on CGE models <sup>12</sup> [^12: Major studies that applied the CGE model to regional integration in South Asia are Pigato _et al._ (1997),\nBandara and Yu (2003), and Raihan and Razzaque (2007).] predict the effects of the trading arrangement on all variables including\nproduction, consumption, and trade flows in all sectors of the economy as well as on welfare. These\nstudies employed the Global Trade Analysis Project (GTAP) database and model, though they differ in\ntechnicalities and assumptions because of the evolution of the GTAP itself. Pigato _et al._ found that\nregional integration in South Asia would produce benefits for member nations, though unilateral trade\nliberalization would yield larger gains. Bandara and Yu argued that, in terms of real income, such\nintegration", "output": {"entities": {"named_data": ["Global Trade Analysis Project (GTAP) database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005321", "page": 7, "chunk": 0, "title": "wps6155", "pdf_url": "https://local/prwp/wps6155.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Global Trade Analysis Project (GTAP) database", "label": "NAMED_DATA", "score": 0.8535966277122498, "start": 1709, "end": 1754, "probe_score": 0.9491, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " new\neducation law (approved in August 2000) sets in place the conditions for broadening participation in\nDjibouti's education system. It provides for setting up school management committees with parent\n\nand community involvement. The law also provides for the creation of conditions to increase private\nsector participation in education.\n\n\n_6.3 How does the project involve consultations or collaboration with NGOs or other civil society_\n_organizations?_\n\n\nThe National Educational Forum consulted all stakeholders including NGOs and civil society during\nthe initial preparation. In addition, the project foresees the increased involvement of parent\nassociations or community-based associations in the management of project activities on the ground\n(i.e., operations & maintenance).\n\n\n_6.4 What institutional arrangements have been provided to ensure the project achieves its social_\n_development outcomes?_\n\n\nThe DGEN will be responsible for monitoring the gender gap in enrollment issues, and the gap\nbetween the poorest and the richest quintiles, and related education services available to them. The\ndata collection on enrollment will be strengthened by the capacity building support provided to the\nMinistry of Education's planning unit - thus over time these issues can be effectively monitored.\nTriggers are included in the APL phasing to ensure that various social development goals are met e.g.\ndecreasing the enrollment gap between the rich and the poor, decreasing the gender gap and increasing\ncommunity participation in school management.\n\n\n_6.5 How will the project monitor performance in terms of social development outcomes?_\n\n\nThe MOE planning unit will monitor enrollment paying attention to gender gaps, socioeconomic gaps\n\nand performance of students by socioeconomic class through use of surveys of students.", "output": {"entities": {"named_data": [], "descriptive_data": ["surveys of students"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000097", "page": 24, "chunk": 1, "title": "West Bank and Gaza - Second Community Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/573471468763473544/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "surveys of students", "label": "DESCRIPTIVE_DATA", "score": 0.8922238349914551, "start": 1811, "end": 1830, "probe_score": 0.3477, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " prevalence, whereas for the latter, the\nlower prevalence of unaffordability will not impact national prevalence.\n\nThe subnational correlation between the prevalence of unaffordability and the absolute number of\nhouseholds experiencing unaffordability varies by country. Looking at the two more densely\n\n\n21 Sub-national CoRD results for Nepal are presented by administrative zones as it provides more geographical data points (14\nentries) than provinces (7 entries). However, we caution that administrative zones no longer exist after Nepal’s transition to\nfederalism in 2015.\n\n\n18", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["geographical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002171", "page": 19, "chunk": 2, "title": "the cost of a nutritious diet in bangladesh bhutan india and nepal", "pdf_url": "https://local/prwp/the-cost-of-a-nutritious-diet-in-bangladesh-bhutan-india-and-nepal.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "geographical data", "label": "VAGUE_DATA", "score": 0.51275235414505, "start": 402, "end": 419, "probe_score": 0.0075, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", D. and A.B. Krueger (1992), “School quality and black-white relative earnings: a\ndirect assessment”, _Quarterly Journal of Economics_, 107, 151-200.\n\n\nCastelló-Climent, A. and A. Mukhopadhyay (2013), \"Mass education or a minority well\neducated elite in the process of growth: The case of India\", _Journal of Development_\n_Economics_, 105, 303-320.\n\n\nChecchi, D. and V. Peragine (2010), “Inequality of opportunity in Italy”, _Journal of_\n_Economic Inequality_, 8, 429-450.\n\n\n<mark>Chetty, R., Hendren, N., Jones, M. R. and S.R. Porter (2020), “Race and economic</mark>\n<mark>opportunity in the United States: An intergenerational perspective”,</mark> _<mark>Quarterly Journal of</mark>_\n_<mark>Economics</mark>_ <mark>, 135, 711-783.</mark>\n\n\nCoibion, O., Gorodnichenko, Y., Kudlyak, M. and J. Mondragon (2020), “Greater\ninequality and household borrowing: New evidence from household data”, _Journal of the_\n_European Economic Association_, 18, 2922-2971.\n\n\nConley, D. (2009), _Being black, living in the red. Race, wealth_, and social policy in\nAmerica. University of California Press: Berkeley and Los Angeles, California.\n\n\nCowell, F. and E. Flachaire (2018), “Inequality Measurement and the Rich: Why\nInequality Increased More than We Thought”, _Suntory and Toyota International Centres_\n_for Economics and Related Disciplines, LSE", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["household data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000315", "page": 28, "chunk": 1, "title": "does race and gender inequality impact income growth", "pdf_url": "https://local/prwp/does-race-and-gender-inequality-impact-income-growth.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household data", "label": "VAGUE_DATA", "score": 0.5410327315330505, "start": 876, "end": 890, "probe_score": 0.114, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "UNDP Regular Perceptions Survey Wave IV 11/28/18, 5(29 PM\n\n\n\n**Status**\n\n\n\n\n\n\n\n\n\n\n\n\n\nhttps://enketo.ona.io/x/#eqB7wB2W Page 4 of 32", "output": {"entities": {"named_data": ["UNDP Regular Perceptions Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000696", "page": 47, "chunk": 0, "title": "Social Stability - Regular Surveys on Social Tensions throughout Lebanon - Wave IV, September 2018", "pdf_url": "https://reliefweb.int/attachments/661ebcaf-9c3c-36ed-b917-ef8a3906a3ea/67048.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNDP Regular Perceptions Survey", "label": "NAMED_DATA", "score": 0.7759348154067993, "start": 0, "end": 31, "probe_score": 0.9988, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on social development issues"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017933", "page": 24, "chunk": 0, "title": "Transitional Government of Ethiopia - National Fertilizer Sector Project", "pdf_url": "https://documents.worldbank.org/curated/en/770851468032334430/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on social development issues", "label": "VAGUE_DATA", "score": 0.581004798412323, "start": 1670, "end": 1703, "probe_score": 0.333, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "von Braun, J., H. de Haen, and J. Blanken (1991). Commercialization of agriculture under population pressure: Effects\n\non production, consumption, and nutrition in Rwanda. Research report no. 85, International Food Policy Research\nInstitute. 5\n\n\nvon Braun, J., D. Hotchkiss, and M. Immink (1989). Nontraditional export cropsin Guatemala: Effects on production,\n\nincome, and nutrition. Technical Report Research Report No. 73, International Food Policy Research Institute. 4\n\n\nvon Braun, J., E. Kennedy, and H. Bouis (1990, February). Commercialization of smallholder agriculture: Policy\n\nrequirements for the malnourished poor. _Food Policy 15_ (1), 82–85. 19\n\n\nvon Braun, J., D. Puetz, and P. Webb (1989). Irrigation technology and commercialization of rice in The Gambia:\n\nEffects on income and nutrition. Technical Report Research Report No. 75, International Food Policy Research\nInstitute. 4\n\n\nWaterlow, J. C., R. Buzina, W. Keller, J. M. Land, M. Z. Nichaman, and J. M. Tanner (1977). The presentation and\n\nuse of height and weight data for comparing the nutritional status of groups of children under the age of 10 years.\n_Bulletin of the World Health Organization 55_ (4), 489–498. 9\n\n\nWorld Bank (1989). _Sub-Saharan Africa from crisis to sustainable growth:_ _A long-term perspective study_ . World Bank.\n\n6\n\n\nWorld Bank (2007, December). Malawi poverty and vulnerability assessment: Investing in our future. Full Report\n\n36546-MW, World Bank. 3, 8, 15, 17\n\n\nWorld Bank (2009, July). Gross national income per capita 2008, Atlas method and PPP. Technical report, World Bank.\n\n6\n\n\nZeller, M.", "output": {"entities": {"named_data": [], "descriptive_data": ["height and weight data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002371", "page": 26, "chunk": 0, "title": "up in smoke agricultural commercialization rising food prices and stunting in malawi", "pdf_url": "https://local/prwp/up-in-smoke-agricultural-commercialization-rising-food-prices-and-stunting-in-malawi.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "height and weight data", "label": "DESCRIPTIVE_DATA", "score": 0.6902621984481812, "start": 1020, "end": 1042, "probe_score": 0.193, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Figure 5: Poverty Incidence by Education Level of Household Head**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nSource: World Bank\n\n\nMost importantly for the aim of this research, very few Mauritanian households have access to\ncredit, and bank presence is almost exclusively restricted to urban areas. The EPCV includes\nquestions designed to gauge household demand for credit during the 5 years prior to the survey.\nFigure 6 shows the share of households that have applied for credit from a formal financial\ninstitution, as well as the share that had their requests approved. Households applying for credit\nrepresent a tiny fraction of the population at just 5.6 percent, down from 8.8 percent in 2008.\nHowever, the likelihood of a successful credit application increased between the two surveys, rising\nfrom 3.23 percent in 2008 to 4.45 percent in 2014. Credit applications are far more common, and\ncredit approval is far more likely, among urban households as opposed to their rural counterparts\n(Figure 6). Physical access to banks is even more heavily skewed in favor of urban households,\nabout a quarter of which have access to a bank, compared to just over 1 percent of rural households\n(Figure 7).\n\n\n10", "output": {"entities": {"named_data": ["EPCV"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006578", "page": 11, "chunk": 0, "title": "wps7533", "pdf_url": "https://local/prwp/wps7533.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "EPCV", "label": "NAMED_DATA", "score": 0.7521324157714844, "start": 278, "end": 282, "probe_score": 0.959, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "8. Ability to Achieve Self-Reliance\nIDP returnees fishing on the beach\nin Port Pedro, near Jaffna, Sri Lanka.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000126", "page": 34, "chunk": 0, "title": "Protecting Gaps: Framework for Analysis - Enhancing Protection of Refugees", "pdf_url": "https://reliefweb.int/attachments/086de220-6e6c-3a19-9737-23c557e070cd/9CABB71B7F805BE5C125721E0049252D-UNHCR-Oct2006.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Public Disclosure Copy\n\n\n**The World Bank** Implementation Status & Results Report\nSecond Agricultural Growth Project (P148591)\n\n\n\nPHINDIRITBL\n\n\n\n\n\nOverall Comments\nAll indicators other than the submission of annual reports, remain unchanged. Since the project launch in November 2016, activities have focused\non participatory planning and no field level investment has taken place.\n\n\n**Data on Financial Performance**\n\n\n**Disbursements (by loan)**\n\n\nProject Loan/Credit/TF Status Currency Original Revised Cancelled Disbursed Undisbursed Disbursed\n\n\nP148591 IDA-56050 Effective XDR 248.30 248.30 0.00 12.12 236.18 5%\n\n\n**Key Dates (by loan)**\n\n\nProject Loan/Credit/TF Status Approval Date Signing Date Effectiveness Date Orig. Closing Date Rev. Closing Date\n\n\nP148591 IDA-56050 Effective 31-Mar-2015 07-May-2015 31-Aug-2015 10-Oct-2020 10-Oct-2020\n\n\n**Cumulative Disbursements**\n\n\n8/22/2016 Page 16 of 17\n\nPublic Disclosure Copy", "output": {"entities": {"named_data": [], "descriptive_data": ["Data on Financial Performance"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016290", "page": 15, "chunk": 0, "title": "Ethiopia - Second Agricultural Growth Project : P148591 - Implementation Status Results Report : Sequence 03", "pdf_url": "https://documents.worldbank.org/curated/en/660091471901725778/pdf/ISR-Disclosable-P148591-08-22-2016-1471901710803.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data on Financial Performance", "label": "DESCRIPTIVE_DATA", "score": 0.5198222994804382, "start": 387, "end": 416, "probe_score": 0.0001, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " maybe taken into consideration. The use of drought-resistant</mark>\n<mark>crop varieties in the rain-fed areas along with soil and water conservation techniques will increase farm</mark>\n<mark>production.</mark>\n\n\nSomali region has a population of 5.3 million with average household size of 6.6 according to CSA\nprojection (CSA 2013). The zone consists of 11 zonal administration, 93 districts, 6 city administrations\nand 1,224 Kebeles. The people rely primarily on pastoralism. In the region, livestock is both considered a\nsocial reputation and a means of accumulating wealth. Therefore, the area has a livestock population of\n30,536,000 million animals, including cattle (24%), goats (36.5%), horse (32.2%), camel (7.2%) and (1%)\nequine (CSA, 2014). The region has 17 rural livelihood zones, generally classified as pastoral, agro-pastoral,\nriverine, and sedentary farming. Livestock is the main livelihood pillar in the Somali region that supports\naround 86 per cent of the population. It provides home-consuming milk and meat, and live animals for\nsale. The conflict with Oromia and Afar regions place many people internally displaced due to various\nreason including ethnic and border conflicts as well as in search of rangeland and water.\n\n\nAccording to Ethiopia Humanitarian Situation Report No. 6, July 2021, in Somali region, drought is\nanticipated to affect large areas of the southern part of the region including Dolo, Korahay, Shabelle, Liban\nand Afdher zones, impacting an estimated 2.4 million people including 300,000 children living within these\nareas. Besides, on 24 July 2021, conflict was reported in the border areas between Afar and Somali Regions\nmainly Gerba-Isse town, which had a devastating impact on children and women; the number of", "output": {"entities": {"named_data": ["CSA\nprojection"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:006574", "page": 10, "chunk": 1, "title": "Revised Rapid Social Assessment Response - Recovery - Resilience for Conflict-Affected Communities in Ethiopia (P177233)", "pdf_url": "https://documents.worldbank.org/curated/en/099345002102242652/pdf/P1772330ET000300Assessment000Clean.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "CSA\nprojection", "label": "NAMED_DATA", "score": 0.8248730897903442, "start": 309, "end": 323, "probe_score": 0.0017, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "</sup>\n\n\n\nversions of the Global Procurement <sup>Plan and the following year's</sup> <sup>annual</sup> <sup>procurement</sup> <sup>plan.</sup> <sup>Participating</sup>\n\n\n\nService Providers will be required <sup>to</sup> <sup>include</sup> <sup>procurement</sup> <sup>plans in</sup> <sup>their subproject proposals.</sup> <sup>The</sup>\n\n\n\ntechnical team reviewing community <sup>subproject proposals must ensure adequacy of a</sup> <sup>sub-project</sup>\n\n\n\nprocurement plan before the <sup>proposal</sup> <sup>is</sup> <sup>approved.</sup> <sup>Each</sup> <sup>quarter,</sup> <sup>NaCSA will</sup> <sup>submit</sup> <sup>to IDA a</sup>\n\n\n\nprocurement monitoring report <sup>as part of the Financial</sup> <sup>Management Report (FMR),</sup> <sup>to show how</sup> <sup>each</sup>\n\n\n\ncontract on the procurement <sup>plan</sup> <sup>has progressed.</sup> <sup>The POM</sup> <sup>will include</sup> <sup>sample formats</sup> <sup", "output": {"entities": {"named_data": [], "descriptive_data": ["procurement monitoring report"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010754", "page": 45, "chunk": 6, "title": "Ethiopia - Second Road Sector Development Support Project (RSDSP II)", "pdf_url": "https://documents.worldbank.org/curated/en/287381468771238509/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "procurement monitoring report", "label": "DESCRIPTIVE_DATA", "score": 0.8535922765731812, "start": 641, "end": 670, "probe_score": 0.0289, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "###### **Colombia**\n\n**_NRC Colombia_**\n\n\n1. What are you planning to do?\n\n\n**A. Immediate plans**\n\n1) Mapping of protection services providers including civil society,\nNGOs and intergovernmental agencies and other groups active in\nJakarta, Makassar, Medan and other key urban areas in\nestablishing a network toward more effective delivery of protection\nservices to urban refugees.\n2) Undertaking a mapping project for unaccompanied minors (UAMs)\nto identify their specific needs, particularly those of homeless\nyounger minors, which will then inform planning for specific projects\nand interventions with the authorities and partners.\n3) Identifying of National Celebrity toward eventual Goodwill\nAmbassador to raise profile of refugees and to help in our advocacy\nwork.\n\n**B. Medium term plans**\n\n1) Establishing Youth Centre(s) where various activities, both\neducational (including skill-based training, such as language or\ncomputer) and recreational (such as sports and cultural), are\nprovided to both refugees and host community youths.\n2) Establishing, in coordination with government counterparts, a\nsystem by which urban refugees are included in national health\ninsurance schemes, appealing to the government to include\nrefugees in national health security policy.\n3) Advocating for limited local integration for refugees married to\nIndonesians.\n\n**C. Longer term plans**\n\n1) Promoting and fostering self-reliance and sustainable Livelihoods\namong persons of concern (PoCs).\na. Advocacy with government to seek necessary permission for\n\nurban refugees to engage in enterprise schemes.\nb. Seek out joint entrepreneurship models to maximize sympathy\n\nand support among host communities (small scale partnerships\nbetween urban refugees + local economically active citizens) establishing joint cottage industry in making Afghan bread\n(which are otherwise imported from Australia or Malaysia).\n\n\n\nBuilding Communities of Practice for Urban Refugees – UNHCR’s Policy Development and Evaluation Service\n\n\n\n**63**", "output": {"entities": {"named_data": [], "descriptive_data": ["mapping project for unaccompanied minors"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000737", "page": 63, "chunk": 0, "title": "Building Communities of Practice for Urban Refugees - Americas Regional Workshop Report", "pdf_url": "https://reliefweb.int/attachments/6ca48499-833b-3b8b-8068-6e9a7c3772d8/americas_workshop_report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "mapping project for unaccompanied minors", "label": "DESCRIPTIVE_DATA", "score": 0.5609734058380127, "start": 399, "end": 439, "probe_score": 0.0462, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "br> <br>DR of Congo<br>76<br> <br>Somalia<br>1,960<br> <br>Colombia<br>1,199<br> <br>Sudan<br>76<br> <br>Eritrea<br>1,905<br> <br>Ethiopia<br>1,140<br> <br>Ethiopia<br>54<br> <br>Pakistan<br>1,765<br> <br>Indonesia<br>1,018<br> <br>Sri Lanka<br>50<br> <br>Sri Lanka<br>1,250<br> <br>Honduras<br>933<br> <br>Eritrea<br>45<br> <br>Nigeria<br>905<br> <br>Iraq<br>734<br> <br>** Data for Serbia might include Montenegro in a few cases where no separate statistics are available for both countries.<br>**** Combination of cases (DHS) and persons (EOIR).<br>|Turkey<br>United Kingdom<br>United States****<br>Iraq<br>3,471<br> <br>Afghanistan<br>2,815<br> <br>China<br>8,572<br> <br>Iran (Islamic Rep.)<br>1,687<br> <br>Iran (Islamic Rep.)<br>2,510<br> <br>El Salvador<br>3,102<br> <br>Somalia<br>1,124<br> <br>Zimbabwe<br>2,300<br> <br>Haiti<br", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Data for Serbia"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001058", "page": 35, "chunk": 8, "title": "Asylum levels and trends in industrialized countries, 2007", "pdf_url": "https://reliefweb.int/attachments/a0f955c8-b460-3603-b1cc-8d2ccc064a5f/BF4CF8525B21A81049257410001BC61A-Full_Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data for Serbia", "label": "VAGUE_DATA", "score": 0.6286047101020813, "start": 375, "end": 390, "probe_score": 0.5622, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "also be provided to properly levy, collect and account for local duties and taxes. NaCSA staff would be\ngiven an opportunity to visit Community Driven Development Projects in comparable countries to\ncapitalize on their experiences. Regional and district line ministry staff would be trained in community\nmobilization, conflict resolution, social capital building, and technical appraisal skills.\n\n\n(b) Substantial IEEC activities linked to the various sub-projects are envisaged. These activities\nwould be undertaken using existing IEC materials endorsed by the various line ministries. For example,\nin the case of the rehabilitation of a health post, IEC messages could be envisaged to inform the\npopulation on the proper use of insecticide treated bed nets as a means of preventing malaria.\n\n\n(c) Monitoring and evaluation at the community, district, regional and central levels would be\ngiven high priority, and linked regularly and directly with NaCSA decision making on NSAP policy,\nstrategy and operational matters. These activities would be directly undertaken, or commissioned by,\nstaff of NaCSA's Planning, Monitoring and Evaluation Directorate. The Project Design Matrix (logical\nframework, Annex 1) would form the basis for monitoring NSAP outputs, outcomes and impact. An\nassessment of project status would accompany each NaCSA work program and budget submitted\nsemi-annually to the NaCSA Board. Other M&E activities would include a pre-project Social\nAssessment; establishment of NSAP baseline data (in conjunction with the collection of data for the\nCRRP Implementation Completion Report); social assessments during implementation; annual technical\naudits; beneficiary assessments; incorporation of NaCSA into GOSL's semi-annual public expenditure\ntracking surveys (PETS); and independent impact assessments.\n\n\nIn addition to conventional sub-project monitoring and evaluation (incorporated in the\nsub-project cycle as outlined in the Operations Manual), a pilot participatory monitoring and evaluation\nsystem would be introduced in a representative sample of the predominant types of CDP sub-projects.\nBeneficiary communities would identify quantitative and qualitative indicators", "output": {"entities": {"named_data": [], "descriptive_data": ["NSAP baseline data", "public expenditure\ntracking surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019286", "page": 36, "chunk": 0, "title": "Kenya - Program Loan Project", "pdf_url": "https://documents.worldbank.org/curated/en/862591468046803369/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NSAP baseline data", "label": "DESCRIPTIVE_DATA", "score": 0.5252031087875366, "start": 1493, "end": 1511, "probe_score": 0.1181, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "public expenditure\ntracking surveys", "label": "DESCRIPTIVE_DATA", "score": 0.7033143043518066, "start": 1743, "end": 1778, "probe_score": 0.481, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**1** **Introduction**\n\nIn Kenya, the transport sector is recognized as a key pillar and a critical enabler in achieving Vision\n2030 long-term development strategy, contributing 8 percent to Gross Domestic Product (GDP) in\n2019. Providing good transport in rural and urban areas has also been recognized as one of the\nmeasures to realize the Big Four Agenda; the 2018-2022 programme focuses on priority areas in the\nThird Medium Term Plan (MTP III) of Kenya Vision 2030. In 2009, the Government of Kenya developed\nthe Integrated National Transport Policy (INTP 2009), which identified several challenges inhibiting\nthe transport sector from performing its role in national, regional, and international economies, and\nprovided policy statements on the way forward.\n\n\nThere is <mark>a significant infrastructure financing deficit estimated at $2.1 billion annually, which</mark>\n<mark>constrains growth and development.</mark> Roads are rated as one of the major problems by ordinary\ncitizens, particularly those residing in rural areas who feel isolated from economic opportunities as\nwell as health, education, and other social services. Infrastructure is rated a major constraint both in\nbusiness surveys and in poverty reduction strategies. During the period 1984-2004, Kenya saw very\nlittle by way of development in the productive sectors, and worse still, the transport sector remained\nmostly stagnant. The quality of transport infrastructure and delivery of services is still highlighted by\nthe private sector as one of the main constraints to growth. Poor and lagging parts of Kenya have\nrudimentary transport infrastructure. Therefore, the focus should be on the utilization of limited\nresources to improve the quality rather than quantity of the network in addition to improving the\nusage and specifically transport safety, comfort, and reliability.\n\n\nThe key challenges in the transport sector include (a) the poor condition of much of the road network\nand accessibility in rural areas; (b) road safety; (c) poor Urban Mobility Systems, (", "output": {"entities": {"named_data": [], "descriptive_data": ["business surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003979", "page": 4, "chunk": 0, "title": "Stakeholder Engagement Plan (SEP) Kenya Urban Mobility Improvement Project (P176725)", "pdf_url": "https://documents.worldbank.org/curated/en/099080923141526762/pdf/P176725097eb5d080a5cb076b3fe6a4f59.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "business surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8878076076507568, "start": 1189, "end": 1205, "probe_score": 0.0176, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "0% <br>0%|**A** <br> **B** <br> **C**<br> **E**|12%<br> 50% <br>9%<br>11%|4% <br> 16% <br>3% <br>3%|**A**<br> **B**<br> **C**<br> **E**|3%<br>47%<br>0%<br>0%|0%<br>4%<br>0%<br>0%|\n\n\nSource: Authors’ calculations using data on NTMs from UNCTAD, data on tariffs from UNCTAD, and data on trade from UN Comtrade accessed through WITS\n\n(2012).\n\n\n14", "output": {"entities": {"named_data": [], "descriptive_data": ["data on NTMs from UNCTAD", "data on tariffs from UNCTAD", "data on trade from UN Comtrade"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005585", "page": 15, "chunk": 18, "title": "wps6434", "pdf_url": "https://local/prwp/wps6434.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on NTMs from UNCTAD", "label": "DESCRIPTIVE_DATA", "score": 0.8213480114936829, "start": 218, "end": 242, "probe_score": 0.9949, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data on tariffs from UNCTAD", "label": "DESCRIPTIVE_DATA", "score": 0.7921133637428284, "start": 244, "end": 271, "probe_score": 0.9962, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data on trade from UN Comtrade", "label": "DESCRIPTIVE_DATA", "score": 0.7697277665138245, "start": 277, "end": 307, "probe_score": 0.994, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", it is equally clear that the\nIranian and Pakistani states — increasingly fragile in themselves — are unlikely to\ncountenance significant moves away from the “securitization” of their borders and\ncontinue to insist that ‘displacement is reversible and all Afghans should/will return\nto Afghanistan’ (Tennant (2008):17).\n\n\n**Resettlement, mobility and return**\n\n\n195.   The two schemes for incorporating mobility into understandings of\nrepatriation outlined in the previous section — namely the introduction of specific\nrepatriate-focused migration channels and general liberalization of regional migration\nregimes — are focused on facilitating intra-regional mobility within and between the\nhost community and the state of origin.\n\n\n196.   Yet as the Afghan case study above demonstrates, post-conflict refugeeproducing states may often be situated within a cluster of weak states (as can also be\nseen in the Great Lakes region and the Horn of Africa) or states without the\nabsorptive capacity to accommodate significant numbers of unanticipated mobile\n“repatriates” seeking to secure economic livelihoods. If mobility is to be fully\nintegrated into the durable solutions framework as part of post-conflict reconstruction\nefforts, the connections between third-country resettlement, mobility and prospects of\nrefugee return also need to be considered.\n\n\n197.   UNHCR offers resettlement places to refugees on the basis of greatest\nprotection need, yet even for those identified as in need of resettlement, there is a\nconsiderable shortage of places (UNHCR Sources). Yet resettlement remains, for\nmany refugees, their preferred — if unobtainable — solution. The 2008 riots in Ghana\n\n\n33", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000782", "page": 34, "chunk": 1, "title": "Home alone? A review of the relationship between repatriation, mobility and durable solutions for refugees", "pdf_url": "https://reliefweb.int/attachments/73318f2a-c240-3c69-b916-a3567ec5146c/98B701E2A0151300852576E2006EE7B7-unhcr-home-alone-mar2010.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEthiopia-Road Sector Development Program APL4 (P106872)\n\n\n**<u>Total</u>** **<u>501.72</u>** **<u>3,289.86</u>** **<u>4,283.68</u>** **<u>30.21</u>**\n\n\n**Impact on Mobility**\n\n\n20. Traffic on Mekenajo-Dembidolo and Wolkite-Hossaina has significantly increased after the\nexisting road was upgraded with asphalt concrete.\n\n\n21. Traffic on Mekenajo-Dembidolo was increased by 330 percent, and on Wolkite-Hossaina by 773\npercent in 2017 after completed the upgrading of the road projects. The increase in traffic on MekenajoDembidolo and Wolkite-Hossaina roads that are upgraded from gravel to asphalt concrete is significant\nand the increase is attributable to significant improvement in roughness and significant reduction in travel\ntime and vehicle operating costs.\n\n\n22. Traffic on Mekenajo-Dembidolo and Wolkite-Hossaina in 2016 after completion of upgrading with\nasphalt concrete is higher than the traffic estimated during their respectively feasibility studies. Therefore,\nupgrading of Mekenajo-Dembidolo and Wolkite-Hossaina road projects under APL4 has a significant\nimpact on traffic mobility.\n\n\n**Figure 12.1.Comparison of Traffic Data on APL IV Road Projects with Feasibility, Appraisal, and Completed Stage**\n\n\n\n\n\n\n\n\n\n\n\n**Economic Impact of APL4 Road Projects**\n\n\n23. The impact on the road projects on regional and national economy is best measured by their\nrespective economic rate of return after upgrading. The economic rate of return is significantly higher\nthan what was estimated during the feasibility study.\n\n\n24. After upgrading the EIRR was found for the base case of Me", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Traffic Data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009185", "page": 91, "chunk": 0, "title": "Ethiopia - Road Sector Development Program Project", "pdf_url": "https://documents.worldbank.org/curated/en/183691528124593286/pdf/ICR00004205-06012018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Traffic Data", "label": "VAGUE_DATA", "score": 0.5813456773757935, "start": 1150, "end": 1162, "probe_score": 0.7896, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " growth quality, poverty has remained elevated and the job content of**\n**growth has been weak.** Based on available but incomplete data, significant progress was made\nin reducing poverty prior to the civil war. Since that date, however, progress has stopped, and\neven reversed as poverty incidence has hovered around 28 percent for the few data points\navailable. Extreme poverty has remained stable at around 8 percent since the end of the civil war.\nThe country’s employment challenge is also daunting as job growth has not kept pace with the\ngrowth of the labor force. Even during periods of relatively rapid economic growth, Lebanon\nexperienced weak private sector job creation with an employment growth elasticity of only 0.2,\nwhich is considerably lower than those observed in other countries in the region. Meanwhile, the\nlabor force has been growing, in part driven by an increase in the working age population. Under\ncurrent conditions, Lebanon is not making significant progress toward increasing shared\nprosperity or eliminating extreme poverty.\n\n\n**B.** **Situations of Urgent Need of Assistance**\n\n\n4. This project is being prepared and implemented in accordance with the provisions of\nparagraph twelve of World Bank OP10.00, “Projects in situations of urgent need of Assistance or\nCapacity Constraints.” This permits the provision of investment project financing with specific\nexceptions in cases where there is an urgent need of assistance because of a natural or man-made\ndisaster or conflict (among other factors). The situation in Lebanon reflects both the impact of a\nconflict in neighboring Syria and of a man-made disaster, in the form of the continuing influx of\n\n\n1 This and the following paragraphs in the Country Context section draw directly from the concept note of the\nLebanon Systematic Country Diagnostic (2015).\n\n\n1", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["available but incomplete data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000099", "page": 9, "chunk": 1, "title": "Lebanon - Emergency Education System Stabilization Project", "pdf_url": "http://documents1.worldbank.org/curated/en/578481467991017996/pdf/PAD1190-PAD-P152848-PUBLIC-Box391435B-LB-EESSP-Final-PAD-for-printing.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "available but incomplete data", "label": "VAGUE_DATA", "score": 0.7144440412521362, "start": 107, "end": 136, "probe_score": 0.0384, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Chapter 7\n\n\n\n**SUDAN** **_. Returnees unable to return to_**\n**_their villages are stranded in an IDP camp._**\n\n\n\n**_“I saw [returning home] as a new_**\n**_beginning, but when we arrived in_**\n**_Sudan I was informed by neighbours in_**\n\n\n\n**_my village that my land was occupied_**\n\n\n\n**_by other people.” explains Rawday._**\n\n\n\n© UNHCR /MODESTA NDUBI\n\n\n\n**UNHCR >** **GLOBAL TRENDS 2019** **71**", "output": {"entities": {"named_data": ["GLOBAL TRENDS 2019"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001657", "page": 70, "chunk": 0, "title": "Global Trends: Forced Displacement in 2019", "pdf_url": "https://reliefweb.int/attachments/ffb577d2-2185-3ba5-bdc7-8130fa9ba6e8/5ee200e37.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "GLOBAL TRENDS 2019", "label": "NAMED_DATA", "score": 0.545343816280365, "start": 370, "end": 388, "probe_score": 0.0416, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " targeting formula that\ngives additional weight to vulnerability criteria along key dimensions, including by sex and gender head of\nhousehold.” The project will address the food security needs of women, who are usually responsible for food\nmanagement at the household level. Households are affected by higher food prices in different ways, with femaleheaded households resorting to harmful coping strategies, such as reducing their own nutrition consumption to\nfeed members of their family or taking on risky jobs to acquire food as a result of having limited access to assets\nand markets, and fewer pathways out of the crisis as compared to their male counterparts. In general, women are\nusually responsible for food management at the household level yet few work in Jordan, with female\nunemployment among those seeking work nearly twice that of men. Moreover, those women who do work tend\nto earn less than men do for comparable jobs limiting their access to resources during times of crises (World Bank\n2021). The project design includes surveys and other monitoring and evaluation activities to inform food security\n\n38 REACH 2020\n\n\nPage 26 of 54", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["surveys"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 30, "chunk": 2, "title": "Jordan - Emergency Food Security Project", "pdf_url": "http://documents.worldbank.org/curated/en/486071652556836130/pdf/Jordan-Emergency-Food-Security-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "surveys", "label": "VAGUE_DATA", "score": 0.5331718921661377, "start": 1041, "end": 1048, "probe_score": 0.0002, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "16\n\n\naddressed the Donors Roundtable and committed to increase Government resources to education to\nover 25% of the budget and noted that the government viewed education as the main source of future\ngrowth in Djibouti.\n\n\n**5. Value added of Bank support in this project**\n\nIDA has been supporting the national consensus building process through the National Education\nForum. The proposed project will help demonstrate that a consensus building approach that involves\n\nall elements of civil society is effective and produces results. In addition the use of an APL\ndemonstrates the long-term commitment by IDA to assist the Government in its strategic goal of\nreaching full enrollment in basic education. It is also hoped that the use of the IDA credit will further\ndecrease the construction unit cost (as IDA is supporting the use of local construction materials which\nshould be cheaper), help develop more cost-effective classroom designs, and provide the environment\nwith a more efficient procurement process.\n\n\n**E. SUMMARY PROJECT ANALYSIS** (Detailed assessments are in the project file, see Annex 8)\n\n\n**1. Economic (see Annex 4)**\n\n\nOther (specify) NPV=US$ million; ERR = ** % (see Annex 4)\n\n\n_** ERR = Over 11% based on system efficiency gains alone without allowing for development_\n_benefits, public goods nature of education and poverty reduction benefits._\n\n\nDjibouti's main resource base is its population and in order to achieve sustained development, the\ncountry needs to improve the quality of its human resource base. Quality starts with improved basic\neducation and school enrollments. In addition, the issue of equity arises. According to the household\nexpenditure survey data, in urban areas, the net enrollment rate (NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey", "output": {"entities": {"named_data": [], "descriptive_data": ["household\nexpenditure survey data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016568", "page": 19, "chunk": 0, "title": "Ethiopia - Sixth Education Project", "pdf_url": "https://documents.worldbank.org/curated/en/678241468252595100/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household\nexpenditure survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8924797177314758, "start": 1661, "end": 1694, "probe_score": 0.9403, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**_Leased Assets_** _as specified under paragraph 5.10_ of the Procurement\nRegulations: Leasing may be used for those contracts identified in the\nProcurement Plan tables. _<u>Not Applicable</u>_\n\n\n**_Procurement of Second Hand Goods_** _as specified under paragraph 5.11_ of\nthe Procurement Regulations – is allowed for those contracts identified in the\nProcurement Plan tables _<u>Not Applicable</u>_\n\n\n**_Domestic preference_** _as specified under paragraph 5.51_ of the Procurement\nRegulations **_(Goods and Works)_** .\n\n\nGoods: Not Applicable\n\n\nWorks: <u>Not Applicable</u>\n\n\n**Other Relevant Procurement Information.**\n\n\n_The Project is an emergency response operation and the procedures on_\n_Procurement in Situations of Urgent Need of Assistance or Capacity_\n_Constraint shall apply_", "output": {"entities": {"named_data": [], "descriptive_data": ["Procurement Plan tables"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011513", "page": 1, "chunk": 0, "title": "Ethiopia - AFRICA EAST- P174206- Ethiopia: COVID-19 Education Response Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/340561637130168790/pdf/Ethiopia-AFRICA-EAST-P174206-Ethiopia-COVID-19-Education-Response-Project-Procurement-Plan.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Procurement Plan tables", "label": "DESCRIPTIVE_DATA", "score": 0.63047194480896, "start": 146, "end": 169, "probe_score": 0.001, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "8|-|\n|**Logone et Chari**|486,997|29,909|6.2|\n|**Mayo Sava**|348,890|9,342|2.0|\n|**Mayo Tsanaga**|699,971|8370016|17.5|\n|**Total**|**2,178,085**|**122,959**|**25.6**|\n\n\n\n13 Cameroon’s eligibility to access WHR financing was already established under IDA18 cycle. The Government has issued an update of its\nstrategy on May 25, 2023 which is included in the project files.\n14 Source: UNHCR Cameroon Statistics, April 2023.\n15 As of April 2023, the total refugee population in Cameroon is 479,533. Source: UNHCR Cameroon Statistics\n16 Out of which 78,722 are at Minawao camp in Mayo Tsanaga\n\n\nPage 17 of 82", "output": {"entities": {"named_data": ["UNHCR Cameroon Statistics"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000003", "page": 16, "chunk": 2, "title": "Cameroon - Enhancing Connectivity and Resilience in the Far North of Cameroon for Inclusiveness Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099053123163547375/pdf/BOSIB0e7334a5d0570a3e40f8ae4d0c1266.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR Cameroon Statistics", "label": "NAMED_DATA", "score": 0.6972492337226868, "start": 382, "end": 407, "probe_score": 0.9997, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " elaboration based on Eurostat\n(Labour Force Survey) data.\n\n\n**Occupational downgrading is**\n**widespread among Ukrainian refugees**\n**in Poland.** SEIS data shows that 40% of\nUkrainian refugees aged 25–64 hold a\ntertiary degree – exceeding the share of\nPolish citizens in the same age bracket,\naccording to Eurostat’s 2023 annual\naverage. While ZUS data available as of\nJune 30, 2024, shows occupational groups\nfor less than half of the socially insured\nin Poland, it reflects a visible mismatch\nbetween the refugees’ education and the\njobs they perform. Only 12% of Ukrainian\nrefugees (less than one-third of the share\nin terms of tertiary education) worked in\noccupational groups which require tertiary\neducation, that is managers, specialists,\nand technicians (ISCO 1-3), compared to\n37% of Polish citizens (almost the same\nas the tertiary education share in the\n25-64 age group).\n\n\n\n2022 2023", "output": {"entities": {"named_data": ["SEIS data", "ZUS data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 13, "chunk": 2, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS data", "label": "NAMED_DATA", "score": 0.7260531783103943, "start": 148, "end": 157, "probe_score": 0.9975, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "ZUS data", "label": "NAMED_DATA", "score": 0.763166606426239, "start": 346, "end": 354, "probe_score": 0.9902, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["M&E data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011381", "page": 29, "chunk": 2, "title": "Uganda - Environmental Management and Capacity Building Project", "pdf_url": "https://documents.worldbank.org/curated/en/331461468177544451/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "M&E data", "label": "VAGUE_DATA", "score": 0.5883201956748962, "start": 530, "end": 538, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "e. income generation for the beneficiary population), a\nrudimentary assessment can be performed to evaluate economic efficacy of this\nsubcomponent. Based on the available data concerning the number of projects and\nbeneficiaries, and assuming that these projects provided all their direct beneficiaries with\nan income equivalent to at least poverty line rate of annual income (403 UShs per hour or\n$1.25 per day <sup>30</sup> ), the result would be a more than 400% return on investment. Such a result\nwould be extraordinary, but it would probably not be prudent to assume that all of these\nprojects were successful and/or all of the projects provided income to all of their direct\nbeneficiaries.\n\nA useful and illustrative exercise in this case would be to estimate at what level of\nadjustment (of project success rates, and of the number of direct project beneficiaries)\nwould the project generate sufficient economic benefit to result in zero net present value of\ncosts and benefits (i.e. breakeven point at a assumed opportunity cost of capital). If the\nactual results are anywhere higher than this adjustment level, then the actual net present\nvalue of the project is also positive and the project is economically beneficial.  Therefore,\nif this adjustment level is sufficiently low to allow for a conservative assessment, it would\nbe safe to declare that this subcomponent likely achieved net positive economic effect.\n\n30 Wage data is based on “Wages in Uganda” survey by wageindicator.org, October 2012:\nhttp://www.wageindicator.org/main/publications/2012/wages-in-uganda-wage-indicator-survey-2012\n\n\n33", "output": {"entities": {"named_data": ["Wages in Uganda"], "descriptive_data": [], "vague_data": ["Wage data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013754", "page": 42, "chunk": 2, "title": "Uganda - Local Government Management and Services Delivery Project", "pdf_url": "https://documents.worldbank.org/curated/en/487401468308686548/pdf/ICR27270ICR0Ug00Box377378B00PUBLIC0.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Wage data", "label": "VAGUE_DATA", "score": 0.5671552419662476, "start": 1428, "end": 1437, "probe_score": 0.544, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Wages in Uganda", "label": "NAMED_DATA", "score": 0.8379174470901489, "start": 1451, "end": 1466, "probe_score": 0.9941, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "made available for use. Monitoring insecticide residues useful to monitor insecticide residues\nafter locust control treatments to evaluate whether the withholding periods recommended by\nthe insecticide manufacturers are valid under local conditions or to confirm that no\ncontamination of protected areas occurs when recommended buffer zones are respected.\nEmergency sampling; emergency situations, e.g. if wildlife mortality has been observed,\naccidental spillage has occurred; beekeepers have claimed that locust control has caused them\ndamage, etc. In these cases, the monitoring team may need to take samples immediately, for\nlater residue analysis. It is important that sampling is carried out as soon as possible.\nSampling will be guided by FAO indicative sample sizes.\n\n\n**V) Finalizing monitoring activities**\n\n\nVarious activities related to environmental and health monitoring will continue for some time\nafter the control activities have stopped.\n\n\n**vi) Post-campaign health examinations**\n\n\nAll control staff will undergo, as soon as possible after the control campaign, a medical\nexamination. When deemed necessary, a final ChE analysis will be carried out (e.g. if the\nstaff member has shown ChE inhibition late in the campaign). The results of these check-ups\nshall be compared with the pre-campaign data. Any staff showing signs of (chronic)\ninsecticide poisoning will continue to be monitored. Based on these results, staff may need to\nbe assigned other tasks during the next control campaign\n\n\n**vii) Long-term monitoring**\n\n\nResidue or ecological monitoring needs to be continued after the last control operation to\ncheck for any adverse ecological effects and impacts. Thus, a few members of monitoring\nteams will task immediately after a campaign.\n\n\n**viii) Sample treatments**\n\n\nOften, both residue and biological samples will be analysed after the control operations (e.g.\nbecause relevant staff were involved in field monitoring). It is important that the campaign\norganization takes into account the time needed for such analysis, as the results may be\nimportant for the technical", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["pre-campaign data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009845", "page": 36, "chunk": 0, "title": "Kenya - National Climate Smart Agriculture Project : Environmental Assessment (Vol. 1 of 3) : Pest Management Plan on Locust Control Contingency Emergency Recovery Implementation Plan", "pdf_url": "https://documents.worldbank.org/curated/en/226761584947023230/pdf/Pest-Management-Plan-on-Locust-Control-Contingency-Emergency-Recovery-Implementation-Plan.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "pre-campaign data", "label": "VAGUE_DATA", "score": 0.7156395316123962, "start": 1301, "end": 1318, "probe_score": 0.5187, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "4 percent of the total budget for FY2019. The\ngovernment thus continues to depend almost entirely on external assistance for service delivery.\n\n14. **This predicament is compounded by additional factors.** The 2015 and 2017 Presidential decrees created new\nstates and counties, increasing the former 10 states and 79 counties to 32 states and 316 counties. County governments\nare now facing by unclear jurisdictions and contested administrative boundaries. Austerity budgeting has prevented the\nrecruitment of new civil servants to staff the new counties. Where staff do exist, county governments struggle with low\ncapacity, high employee turn-over and low morale due to low salary levels (US$15-20/month) as well as months-long\ndelays in salary payments. Newly established counties have few, if any, functional government institutions and are unable\nto fulfill their mandates. This lack of capacity is reflected in public sentiment. According to a World Bank survey, an\noverwhelming 90 percent of the South Sudanese people feel that the government is performing poorly in providing\ninfrastructure and services. <sup>26</sup> [^26: World Bank 2016]\n\n15. **Protracted conflict has also eroded the social fabric and weakened both informal and formal institutions.** In the\nabsence of effective formal governance, particularly in rural areas, people increasingly have come to rely on community\ninstitutions. Yet, as ethnic identities have been politicized and large numbers of armed youth feel less allegiance to\ntraditional authorities, relationships within and between communities have become more strained and the role and\neffectiveness of traditional institutions have been undermined. Consequently, these informal institutions have become\nless capable of managing social tensions and sharing access to resources and services among different groups. This is yet\nanother driver contributing to a marked increase in inter-communal violence and cattle raids, with over 60,000 new\ndisplacements in early 2019. <sup>27</sup>\n\n16. **Provision of basic services and managing social tensions, particularly in areas with high concentration of*", "output": {"entities": {"named_data": ["World Bank survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000014", "page": 6, "chunk": 1, "title": "Concept Project Information Document (PID) - South Sudan Enhancing Community Resilience and Local Governance Project - P169949", "pdf_url": "http://documents.worldbank.org/curated/en/294881573571217860/pdf/Concept-Project-Information-Document-PID-South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project-P169949.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Bank survey", "label": "NAMED_DATA", "score": 0.8241488337516785, "start": 949, "end": 966, "probe_score": 0.9932, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### 1.8 11\n\n\n\nCurrent account balance . **.2**\n\n\n\nFinancing items (net)\nChanges in net reserves .. .\n_Memo:_\nReserves including gold _(US$ millions)_\nConversion rate _(DEC, locaW/US$)_ 177.7 177.7 177.7\n\n\n**EXTERNAL DEBT and RESOURCE FLOWS**\n\n**1979** **1989** **1998** **1999**\n_(US$ millions)_ **Compositlon of total debt, 1998 (USS milIlona)**\nTotal debt outstanding and disbursed 26 **179** 288\nIBRD 0 0 0\nIDA 0 26 50 49 G 15 B\n\nTotal debt service 2 15 6\nIBRD 0 0 0 C: 9\nIDA 0 0 1 1\n\nComposition of net resource flows E: 119\nOfficial grants 5 32 48\nOfficial creditors -1 3 2\nPrivate creditors 0 -1 0\nForeign direct investment 0 0 6 D: **95**\nPortfolio equity 0 0 0\n\nWorld Bank program\n\nCommitments 0 9 3 A  - IBRD E - Bilateral\nDisbursements 0 2 2 1 B - IDA D - Other rrultilateral F **-** Private\nPrincipal repayments 0 0 0 0 C- IMF G - Short-term\nNet flows 0 2 2 1\nInterest payments 0 0 0 0\nNet transfers 0 2 1 1\n\n\nNote: This table was produced from the Development Economics central database. 9/13/00", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011794", "page": 63, "chunk": 1, "title": "Uganda - Industrial Rehabilitation Project", "pdf_url": "https://documents.worldbank.org/curated/en/358481468110934129/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9087857007980347, "start": 960, "end": 998, "probe_score": 0.6996, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Table 12: Distribution of Syrian refugee youth by legal status\n(Percentage)\n\n\n\n\n\nTable 14: Distribution of UNHCR registration status of Syrian refugee youth, by sample and\nrandom selection\n(Percentage)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nRegistration with UNHCR is predominant, with 86 per cent of the surveyed youth confirming\nthat they are registered (table 13). Registration in the South and Nabatieh is relatively lower, possibly\nbecause of the location of the registration centre in the city of Tyre relative to some of the southern\nLebanese villages close to the Syrian border, and also due to the relatively-recent arrival of refugees\nto some of these villages.\n\n\nTable 13: Distribution of Syrian refugee youth by registration with UNHCR and region\n(Percentage)\n\n\n\n\n\nAlthough the figures on legal entry to Lebanon and registration with UNHCR are similar, there appears\nto be no correlation between the two, and refugee youth who entered Lebanon through unauthorized\nchannels are not shying away from registration. Those not registered mentioned the following main\nreasons, in order of importance, for not doing so; recent arrival, time required for the registration\nprocess, perceived unimportance of registration and lack of knowledge how to register (table\n15). This is in line with what was reported also by participants in focus groups.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nIt should be noted that registration figures are biased towards registration, given that 53 per cent of the\nsurveyed refugee youth belong to a randomly-selected sample from UNHCR records. Notably, 8 per\ncent of those on UNHCR records claim not to be registered (table 14), despite them obviously being\nso as their contact details given to the researchers are from UNHCR records of registered refugees.\nThis, as the focus groups indicate, could be because many refugee youth, especially among the\nlower age group, do not know if they are registered. In addition, some perceive the recent decrease\nin UNHCR aid <sup>17</sup> as a sign that they are _“no longer registered”_ or that _“UNHCR", "output": {"entities": {"named_data": [], "descriptive_data": ["UNHCR records", "UNHCR records of registered refugees"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000362", "page": 32, "chunk": 0, "title": "Situation Analysis of Youth in Lebanon Affected by the Syrian Crisis", "pdf_url": "https://reliefweb.int/attachments/2ecf62b5-58f1-3f90-a023-ce0b423455f9/YSA-SyriaCrisis-FullReport.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR records", "label": "DESCRIPTIVE_DATA", "score": 0.5966756939888, "start": 1527, "end": 1540, "probe_score": 0.9127, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHCR records of registered refugees", "label": "DESCRIPTIVE_DATA", "score": 0.723552942276001, "start": 1718, "end": 1754, "probe_score": 0.6089, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " PNDS for the period\n2020–2024 that focuses on five strategic priorities: (i) expanding quality care in all regions; (ii) integrating\npromotive, preventive, and curative care; (iii) increasing accountability and good governance; (iv) strengthening\nhealth financing; and (v) strengthening the Health Management Information System (HMIS). The GoD recently\nannounced plans to undertake extensive reforms in the health sector through a broad consultative process,\nnamed _‘les états-generaux’_ . The World Bank is working closely with the GoD on informing elements of the reform\nprocess that this project closely supports, notably on health system strengthening, focusing on quality\nimprovements of services provided, strengthening of the human resources, to name a few.\n\n41. **The project is fully aligned with the World Bank Group’s Country Partnership Framework (CPF) (FY22-**\n**FY26) (Report No. 147787-DJ).** The project is fully aligned with two CPF focus areas: (i) promoting inclusive private\nsector-led growth, job creation, and human capital; and (ii) strengthening the role and the capacity of the state.\nThe project is also fully aligned with all three cross-cutting themes. It will seek to support the improvement of: (i)\ngender parity by improving the utilization and quality of key RMNCAH-N services by increasing awareness and\ndemand for these services by both women and men; (ii) digital transformation by building on the District Health\nInformation Software 2 (DHIS2) efforts, supported in previous projects as well as including routine household and\nhealth facility surveys to enable the triangulation of data, monitoring, planning and course correction in real time;\n(iii) transparency for good governance by promoting the publication of key RMNCAH-N data in the public domain;\nand (iv) climate change adaptation by bringing RMNCAH-", "output": {"entities": {"named_data": [], "descriptive_data": ["routine household and\nhealth facility surveys", "RMNCAH-N data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000131", "page": 28, "chunk": 1, "title": "Djibouti - Health System Strengthening Project", "pdf_url": "http://documents1.worldbank.org/curated/en/772381653594094662/pdf/Djibouti-Health-System-Strengthening-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "routine household and\nhealth facility surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8554545640945435, "start": 1542, "end": 1587, "probe_score": 0.0302, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "RMNCAH-N data", "label": "DESCRIPTIVE_DATA", "score": 0.6289389729499817, "start": 1757, "end": 1770, "probe_score": 0.0077, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " **Sri** Lanka because it provides a lucrative\nlivelihood to coastal inhabitants. There i s no likelihood o f continued exploitation o f coral reefs resulting\nfrom \"W.\n\n\nWater resources are scarce, particularly in the north where groundwater i s the main source o f water. The\ndestruction to salt water exclusion barrages has led to the salination o f the water table in coastal areas.\nThe lack o f sanitary facilities and poorly designed septic tanks can pose a huge threat in terms o f\n\n\n70", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000115", "page": 73, "chunk": 2, "title": "Sri Lanka - North East Housing Reconstruction Program", "pdf_url": "http://documents1.worldbank.org/curated/en/672131468763807868/pdf/304360LK.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "output": {"entities": {"named_data": [], "descriptive_data": ["household expenditure survey data", "data from the Household Survey"], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011698", "page": 38, "chunk": 1, "title": "Uganda - Water Supply Engineering Project", "pdf_url": "https://documents.worldbank.org/curated/en/352911468349440024/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household expenditure survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8699104189872742, "start": 565, "end": 598, "probe_score": 0.7323, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.5808603167533875, "start": 870, "end": 881, "probe_score": 0.1461, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from the Household Survey", "label": "DESCRIPTIVE_DATA", "score": 0.5346028804779053, "start": 1978, "end": 2008, "probe_score": 0.1121, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEnhancing Community Resilience and Local Governance Project Phase II (P177093)\n\n\nclimate-resilient approaches, including risk assessments, to identify safe locations and elevated building\nstructure options to reduce flood and other disaster risks. The participatory planning process will\nbe supported under Component 2. All _payams_ and _bomas_ within the target counties will be eligible for\nfunding.\n\n\n33. To ensure flexibility, the project can also mobilize resources rapidly to respond to COVID-19 needs\nby funding handwashing facilities at public markets, places of worship, public transportation hubs,\ncommunal water points, women- and girl-friendly spaces, and other densely populated locations. Such\ninvestments will be coupled with hygiene promotion and COVID-19 awareness raising/communication to\nbe financed under Component 2. Communities’ priorities will be validated through local service mapping\nto avoid overlaps and to maximize the use of limited resources by consolidating common priorities among\nneighboring communities, where possible. Community labor will be used, to the extent possible, to\ngenerate income opportunities. The project will establish harmonized salary levels, to the extent possible,\nwith the planned Productive Safety Net for Socioeconomic Opportunities Project (PSNSOP, P177663) _._\n\n\n34. **Geographic targeting.** The selection of counties is guided by four principles: (a) vulnerability, (b)\nfeasibility, (c) equity, and (d) continuity (see Figure 2). The project will continue to target the 10 counties\nwhere ECRP-I has started implementation to consolidate the envisioned development gains in these\nlocations. <sup>48</sup> As indicated in Table 1, ECRP-II will scale up to include refugees in the two refugee-hosting\ncounties that were already targeted under ECRP-I <sup>49</sup> and two new flood-prone vulnerable counties to\nsupport Subcomponent 1", "output": {"entities": {"named_data": [], "descriptive_data": ["local service mapping"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000192", "page": 25, "chunk": 0, "title": "South Sudan - Second Phase of the Enhancing Community Resilience and Local Governance Project", "pdf_url": "https://documents1.worldbank.org/curated/en/543171647442225562/pdf/IBArchive-e8d67f4f-bc76-49af-9b6c-6099c748075b.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "local service mapping", "label": "DESCRIPTIVE_DATA", "score": 0.6748040914535522, "start": 907, "end": 928, "probe_score": 0.4356, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "UNHCR, APRIL 2023 REFUGEES FROM GENERATION TO GENERATION\n\n\nKey informant interviews were also carried out with representatives of the Ministry for Emergency\nManagement (MINEMA), the National Commission for Human Rights, and the Directorate General for\nImmigration and Emigration.\n\n\n<u>South Sudanese and Congolese refugees in Uganda</u>\n\n\nAs of February 2022, Uganda was host to 1,595,405 refugees and asylum seekers <sup>99</sup> [^99: _“Uganda Refugees and Asylum Seekers as of 31st December 2021.”_ Government of Uganda: Office of the Prime\nMinister – Department of Refugees (OPM).] making it the country\nwith the third largest refugee population globally, according to UNHCR statistics. <sup>100</sup> They live in 13 refugee\nsettlements in addition to urban centres. More than 60 percent of these refugees are from South Sudan\nand just over 30 percent from DRC. <sup>101</sup> [^101: Uganda Comprehensive Refugee Response Portal, https://ugandarefugees.org/en/country/uga.]\n\n\nMany of these refugees are relatively recent arrivals, but some have been resident in Uganda for many\ndecades. Of the Congolese refugees, just over 3,000 have lived in Uganda for over 20 years; among the\nSouth Sudanese refugees, 5,015 had been living in Uganda for more than 20 years. In both cases, the\nmajority have lived in Uganda for over 40 years (or been born there), and some are the descendants of\npeople who arrived even before Ugandan independence.\n\n\nThe Uganda research effort targeted long-term refugees of DRC and South Sudan origin residing in\nrefugee settlements in the Southwest, West, Midwest, and Northwest regions of Uganda: Nakivale\n(Isingiro), Kyaka II (Kyegegwa), Kyangwali (Hoima), Kiryandongo (Kiryandongo), and the Mungula and Oliji\n(Adjumani) settlements. Surveys and focus groups were carried out in all these settlements; and focus\ngroups were carried out", "output": {"entities": {"named_data": ["UNHCR statistics"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000434", "page": 46, "chunk": 0, "title": "Refugees from generation to generation - Preventing statelessness by advancing durable solutions in the Great Lakes Region", "pdf_url": "https://reliefweb.int/attachments/3cf8dc89-279a-4132-ac27-8f815265186e/ICGLR-UNHCR-%20Preventing%20Statelessness%20by%20Advancing%20Durable%20Solutions%20In%20The%20Great%20Lakes%20Region.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR statistics", "label": "NAMED_DATA", "score": 0.8138497471809387, "start": 673, "end": 689, "probe_score": 0.9969, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 7. Income of Ukrainian refugee households by source**\n\n\n**2%**\n**0.1%**\n\n\n\nWork (regular, part-time, self-employment, remote, other, remote in Ukraine)\n\n\nRemittances from Ukraine\n\n\nPolish social benefits\n\n\nUkrainian social benefits\n\n\nOther (capital, loans, other)\n\n\n\nSource: Deloitte own elaboration based on SEIS (May-June 2024) UNHCR (2024) survey.\n\nNote: Deloitte worked with disaggregated household-level data, ensuring comparability\n(converting all Ukrainian hryvnia incomes into Polish zloty based on daily exchange rates\nin the time of the interview, and 3-month into 1-month remittance incomes).\n\n\n\n**In 2024, Ukrainian refugee households**\n**increasingly sourced their income from**\n**Poland, rather than from Ukraine.** This\ncan be seen when comparing the MSNA\nsurvey conducted in July-August 2023 and\nSEIS in May-June 2024 (UNHCR, 2024, 2023).\n\n\n\nWhile some methodological differences\napply, we can see that incomes earned\nin Poland grew from 81% in 2023 to 90%\nin 2024. Conversely, incomes from Ukraine\ndeclined from 18% to just 9%. This change\ndemonstrates that Ukrainian refugees\n\n\n\ncontinue to integrate economically.\nIt comes as no surprise, given that\nemployment rates and wages of Ukrainian\nrefugees in Poland increased during that\ntime, which is the focus of the next chapter.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**According to academic literature,**\n**better access to host country’s public**\n**services increases the likelihood of**\n**refugees returning to their country of**\n**origin, while labour market integration**\n**decreases it.** Some evidence shows that\nwhen refugees from Ukraine have access to\neducation, healthcare", "output": {"entities": {"named_data": ["SEIS", "UNHCR (2024) survey", "MSNA\nsurvey", "SEIS"], "descriptive_data": ["disaggregated household-level data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 6, "chunk": 0, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS", "label": "NAMED_DATA", "score": 0.7542990446090698, "start": 392, "end": 396, "probe_score": 0.9986, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHCR (2024) survey", "label": "NAMED_DATA", "score": 0.6158258318901062, "start": 413, "end": 432, "probe_score": 0.9967, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "disaggregated household-level data", "label": "DESCRIPTIVE_DATA", "score": 0.8038139343261719, "start": 462, "end": 496, "probe_score": 0.9675, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "MSNA\nsurvey", "label": "NAMED_DATA", "score": 0.8611496686935425, "start": 849, "end": 860, "probe_score": 0.9869, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "SEIS", "label": "NAMED_DATA", "score": 0.807474672794342, "start": 895, "end": 899, "probe_score": 0.0007, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda COVID-19 Education Response Project (P174033)\n\n\nof schools. Specific stakeholder engagement programs must be prepared for the parents on the benefits of\nkeeping the children in school and attention will be given in the engagements to disadvantaged students\nespecially girl children(who may be likely to be forced into early marriage for economic reasons) and students\nwith disabilities, refugees, displaced persons, ethnic minorities and vulnerable and marginalised groups who may\nbe more impacted by the COVID-19 through stigma and segregation. A Vulnerable and Marginalised Groups (VMG)\nPlan to address the needs of VMGs will be prepared based on the findings of the project social screening.\nComplaints arising out of project activities will be addressed through a Community Grievance Mechanism\ndescribed in the SEP.\n\n69. Cognisant of the measures to prevent further spread of COVID-19, among other preventative measures,\ngood hygiene measures must be reiterated to the teachers, parents and students through stakeholder\nengagements and hygiene trainings and hand washing materials provided at the opening of schools. The provision\ncontracted services including WASH and psycho- social support as well as delivery of hardcopy scholastic materials\nwill lead to interaction between project workers and the communities. A Labour Management Plan will be\nprepared by the project to manage the working conditions and protect the rights of workers. Grievances of\nworkers will be addressed through a Workers Grievance Redress Mechanism. To provide safety measures for the\ncommunities and achieve the benefits of the project proposed in Component 2, all stakeholders including, Local\nGovernments schools, communities, implementing authorities and personnel must be well coordinated and\nengaged. Stakeholder engagement will be carried out as prescribed in the SEP in line with the Technical Note on\nPublic Consultations and Stakeholder Engagement in World Bank-Supported Operations, which applies to\nconstrained stakeholder engagements under emergency situations.\n\n70. The project will benchmark the interventions adopted during the implementation of UTSEP, under which\nthe Ethical Code of Conduct and the model Grievance", "output": {"entities": {"named_data": [], "descriptive_data": ["project social screening"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000034", "page": 29, "chunk": 0, "title": "Uganda - COVID-19 Emergency Education Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/645041598936002560/pdf/Uganda-COVID-19-Emergency-Education-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "project social screening", "label": "DESCRIPTIVE_DATA", "score": 0.7600336074829102, "start": 695, "end": 719, "probe_score": 0.3636, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|\n\n\n\n54 The plan, according to the POM, will contain a complete overview of all activities for the coming year under the DLI 8. The plan will also specify the target areas, districts, urban centers\nand parishes, based on analysis of the needs and coverage. The plan will also specify the allocation formulas, based on quick assessment of the needs of the 7 target areas.\n55 This will clarify the land rights in the wake of pressure on land occasioned by influx of refugees. The data base will provide quick information on land ownership in case any entity needs\nto acquire land for any purpose.\n56 This will encompass, minimum mission p.a. to each target areas to ensure that the LGs mainstream the PDPs in the annual work-plans, support identification of eligible projects, and\nensure that procurement processes are conducted in accordance with the legal framework.\n\n31", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data base"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000006", "page": 38, "chunk": 2, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents.worldbank.org/curated/en/143681526614252328/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data base", "label": "VAGUE_DATA", "score": 0.6851150393486023, "start": 478, "end": 487, "probe_score": 0.0016, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " was over 50 percent, while in rural Kaabong (Karamoja district), it was only 5 percent.\nVariations by welfare quintiles reveal that secondary school enrollment drops with decreasing welfare, it is the lowest\nfor persons in the lowest quintile (7 percent) and highest in the fifth quintile (41 percent). <sup>13</sup> Disparities in completion\nrates are evident between rural, at 6.5 percent, and urban, at just over 14 percent. Variations in secondary\ncompletion rates persist across the country with Kampala (Central) having the highest completion rate of over 17\npercent, while Karamoja (North) having the lowest at just over 4 percent.\n\n\n**Figure 5: Gross Enrollment rates per regions and districts.**\n\n\n\n\n\n\n\nSource: WB based on UBOS and own data.\nNote: refugee data not included.\n\n\n10 Bashir S., Lockheed M., Ninan Dulvy E., Tan J.P. Facing Forward: Schooling with Learning in Africa. World Bank, Washington DC, 2017.\n11 World Development Report, 2018.\n12 UNESCO Institute of Statistics.\n13 National Household Survey 2012/13. [Data on wealth and enrolment disparities not included in the 2016 National Household Survey]\n\n\nAugust 1, 2018 Page 6 of 18", "output": {"entities": {"named_data": ["UBOS", "National Household Survey 2012/13", "2016 National Household Survey"], "descriptive_data": [], "vague_data": ["refugee data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014224", "page": 5, "chunk": 1, "title": "Concept Project Information Document-Integrated Safeguards Data Sheet - Uganda Secondary Education Expansion Project - P166570", "pdf_url": "https://documents.worldbank.org/curated/en/521301533884327735/pdf/Concept-Project-Information-Document-Integrated-Safeguards-Data-Sheet-Uganda-Secondary-Education-Expansion-Project-P166570.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UBOS", "label": "NAMED_DATA", "score": 0.6907140612602234, "start": 733, "end": 737, "probe_score": 0.0731, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "refugee data", "label": "VAGUE_DATA", "score": 0.676545262336731, "start": 758, "end": 770, "probe_score": 0.5345, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "National Household Survey 2012/13", "label": "NAMED_DATA", "score": 0.7626945972442627, "start": 996, "end": 1029, "probe_score": 0.775, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2016 National Household Survey", "label": "NAMED_DATA", "score": 0.6034197807312012, "start": 1093, "end": 1123, "probe_score": 0.9672, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|advanced<br>fuent<br>self-employment<br>intermediate<br>Language|\n\n\n\nNote: Statistically significant results are given in green. Confidence bars reflect standard errors. Sample has been 833 individuals aged 18-64.\n\nSource: Deloitte own elaboration based on SEIS UNHCR survey.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 23. Average number of months since arrival of a Ukrainian refugee by Polish language fluency**\n\nN=702, age 18-64\n\n\n29\n\n\n\nAge Sector\n\n\nNote: Statistically significant results are given in green. n=681, age individuals aged 18-64.\n\nSource: Deloitte own elaboration based on SEIS UNHCR survey.\n\n\n\nFluent\n\n\n\nAdvanced\n\n\n\nIntermediate\n\n\n\nNone\n\n\n\nBeginner\n\n\n\nSource: Deloitte own elaboration based on SEIS UNHCR survey.\n\n\n**Chart 24. What Ukrainian", "output": {"entities": {"named_data": ["SEIS UNHCR survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 16, "chunk": 2, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS UNHCR survey", "label": "NAMED_DATA", "score": 0.8205974102020264, "start": 952, "end": 969, "probe_score": 0.9952, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " be assured.\nSection II, clearly illustrates that there is insufficient information on IDP and HIV\nprogrammes to provide a clear picture of their needs and the gaps. A recent report\nin Northern Uganda reports that basic HIV services are lacking for IDPs. A\ncomprehensive HIV/AIDS needs assessment, combined with assessments from\nother sectors in a multi-sectoral fashion, is needed in all 8 IDP priority countries.\n\n**6.** **Prevention**\nThe same points as for recommendation 5.\n\n**7.** **Support, Care and Treatment**\nThe same points as for recommendation 5. As antiretroviral therapy (ART)\nbecomes available to IDP surrounding host communities, we must ensure that\nIDPs also have access.\n\n**8.** **Assessment, Surveillance, Monitoring and Evaluation**\nSections II and III clearly show a lack of data on HIV and IDP situations. As\nmentioned in recommendation 5, a comprehensive multi-sectoral assessment\nshould occur in all 8 IDP priority countries. Baseline data must be collected to\nallow for monitoring and evaluation of HIV interventions over time. In countries\nundertaking HIV sentinel surveillance or population-based HIV biological and/or\nbehavioural surveys, sample size should provide sufficient power to disaggregate\nbetween IDPs and non-displaced populations, as well as gender and age.\n\n\n8", "output": {"entities": {"named_data": [], "descriptive_data": ["population-based HIV biological and/or\nbehavioural surveys"], "vague_data": ["Baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001616", "page": 7, "chunk": 1, "title": "HIV/AIDS and internally displaced persons in 8 priority countries", "pdf_url": "https://reliefweb.int/attachments/fa83ae60-19ea-39d4-8b52-7cffd15cf4c0/9C98099373994210C12571BF003628F6-unhcr-gen-30jan.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Baseline data", "label": "VAGUE_DATA", "score": 0.6117546558380127, "start": 951, "end": 964, "probe_score": 0.0037, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "population-based HIV biological and/or\nbehavioural surveys", "label": "DESCRIPTIVE_DATA", "score": 0.5074057579040527, "start": 1108, "end": 1166, "probe_score": 0.1936, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "DJIBOUTI\nSchool Access and Improvement Program\n\n\n**Project Appraisal Document**\n\n\nMiddle East and North Africa Region\n\nMNSHD\n\n\n\nDate: November 17, 2000 Team Leader: Qaiser M. Khan\n\n\n\nCountry Director: Inder K. Sud Sector Director: Baudouy\nProject **ID:** P044585 Sector(s): EP - Primary Education, ES - Secondary\n\n\n\n. Education\nLending Instrument: Adaptable Program Loan <sup>(APL)</sup> Theme(s): Education; Gender and development\n\n\n\nPoverty Targeted Intervention: N\n\n\n\nProgram Fin ncing Data\n\n\n\nEstimated\nAPL Indicative Financing Plan Implementation Period (Bank FY) Borrower\n\n\n\n**IBRD** Others **Total** **COMMITMENT** **Closing**\n**US$** m % US$ m US$ m Date Date\nAPL 1 10.00 75.8 3.20 13.20 03/31/2001 06/30/2005 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\n________________ Education\n\n\n\nAPL 2 10.0 65.8 5.20 15.20 07/01/2005 06/30/2008 Republic of\n\n\n\nLoan/ Credit Djibouti\n\n\n\nCredit Ministry of\n\n\n\ni_________ ________________ Education\n\n\n\nAPL 3 10.00 41.0 14.40 24.40 07/01/2008 06/30/2011 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\nEducation\n\n\n\nTotal 30.00 22.80 52.80\nProject Financing Data Credit\nFor Loans/Credits/Others: Amount (US$m): 10.0\n\n\n\nProposed Terms: Standard Credit\n\n\n\nGrace period (years): 10 Years to maturity: 40\nCommitment fee: 0.50% (0% for FY01) Service charge: 0.75", "output": {"entities": {"named_data": ["Project Financing Data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019153", "page": 4, "chunk": 0, "title": "Kenya - Telecommunications Project", "pdf_url": "https://documents.worldbank.org/curated/en/853991468285057419/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Project Financing Data", "label": "NAMED_DATA", "score": 0.5102046728134155, "start": 1106, "end": 1128, "probe_score": 0.1169, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " by Kaabong District to the north, the Republic of Kenya to the east,</mark>\n<mark>by Amudat District to the south, Nakapiripirit District to the southwest, Napak District to the west</mark>\n<mark>and by Kotido District to the northwest It lies on the foot of Mt. Moroto. The district headquarters</mark>\n<mark>at Moroto, are located approximately 210 km (130 mi), by road, northeast of Mbale the nearest</mark>\nlarge city. The coordinates of district are: 02 32N, 34 40E.\n\n<mark>Moroto District is part of the larger Karamoja Sub-region which consists of: Abim, Amudat,</mark>\n<mark>Kaabong, Kotido, Moroto, Nakapiripirit and Napak Districts. In 2002, the population of</mark>\n<mark>Karamoja sub-region was estimated at approximately 800,000, by the National Population and</mark>\n<mark>Housing census conducted that year.</mark>\n\nMoroto District is a plain covered by the Savannah grassland and some low lying rocky hills. It\ncomprises two counties: _Matheniko County_ and _Moroto Municipality_ . It is inhabited by the\nKarimojong, a distinctive ethnic group that highly cherishes its traditions. One peculiar\ncharacteristic of the Karimojong is their dress code which includes a long cultural woven **_suuka_**\nmade by the Masaai in Kenya which is tied on the shoulder sometimes with an under pant or none\nfor the men and the women, especially girls, make skirts out of them which they keep swinging\nfrom one side to another as they walk.\n\n\n**5.3.1** **Population**\n\n\n<mark>In 1991, the National Population and Housing census", "output": {"entities": {"named_data": ["National Population"], "descriptive_data": ["Housing census"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019593", "page": 73, "chunk": 1, "title": "Ethiopia - Women Entrepreneurship Development Project : Additional Financing - Environmental Assessment : Social Assessment", "pdf_url": "https://documents.worldbank.org/curated/en/885781637565765152/pdf/Social-Assessment.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "National Population", "label": "NAMED_DATA", "score": 0.535637617111206, "start": 751, "end": 770, "probe_score": 0.9823, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Housing census", "label": "DESCRIPTIVE_DATA", "score": 0.767873227596283, "start": 788, "end": 802, "probe_score": 0.8116, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " _._ 5 to virtually never included with _m_ = 7; the\nNumber of years open economy has the seventh largest inclusion probability for _m_ = 7 and drops\nto the bottom of the 32 variables shown in the table for _m_ = 20 _._ 5. In sharp contrast, the case with\n_g_ = 1 _/k_ <sup>2</sup> and random _θ_ leads to very similar inclusion probabilities for both values of _m_ .\n\n\nFinally, note that results for model size, chain behavior and inclusion probabilities are quite\nsimilar for the cases where _g_ = 1 _/n_ with fixed _θ_ = 7 _/_ 41 (the preferred implied prior in SDM) and\nwhere _g_ = 1 _/k_ <sup>2</sup> with _θ_ = 0 _._ 5 (the prior used in FLS). This is in line with the negative trade-off\nbetween _g_ and _m_ illustrated in Figure 4, which explains the similarity between empirical results\nusing BACE and the FLS prior on the same data. The same behavior is observed for the other\ndatasets presented in the next subsections.\n\n\n_4.2._ _The Data Set of MP_\n\n\nMP investigate the role of initial conditions at independence from colonial rule on the economic\ngrowth of African countries. They focus on the average growth rate in GDP from 1960 to 1992 and\nconstruct a dataset for _n_ = 93 countries with _k_ = 54 covariates, obtained by combining 32 original\nregressors and 22 interaction dummies.\n\n\nTable 3 records the main characteristics of model size and the MCMC chain, and illustrates that\nresults are quite close to those with the FLS data, leading to the same conclusions. Probably due to\nthe somewhat larger model space, convergence is now even more problematic for the fixed _θ", "output": {"entities": {"named_data": ["Data Set of MP_\n\n\nMP"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003445", "page": 13, "chunk": 1, "title": "wps4238", "pdf_url": "https://local/prwp/wps4238.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data Set of MP_\n\n\nMP", "label": "NAMED_DATA", "score": 0.5684368014335632, "start": 944, "end": 964, "probe_score": 0.935, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " new\neducation law (approved in August 2000) sets in place the conditions for broadening participation in\nDjibouti's education system. It provides for setting up school management committees with parent\n\nand community involvement. The law also provides for the creation of conditions to increase private\nsector participation in education.\n\n\n_6.3 How does the project involve consultations or collaboration with NGOs or other civil society_\n_organizations?_\n\n\nThe National Educational Forum consulted all stakeholders including NGOs and civil society during\nthe initial preparation. In addition, the project foresees the increased involvement of parent\nassociations or community-based associations in the management of project activities on the ground\n(i.e., operations & maintenance).\n\n\n_6.4 What institutional arrangements have been provided to ensure the project achieves its social_\n_development outcomes?_\n\n\nThe DGEN will be responsible for monitoring the gender gap in enrollment issues, and the gap\nbetween the poorest and the richest quintiles, and related education services available to them. The\ndata collection on enrollment will be strengthened by the capacity building support provided to the\nMinistry of Education's planning unit - thus over time these issues can be effectively monitored.\nTriggers are included in the APL phasing to ensure that various social development goals are met e.g.\ndecreasing the enrollment gap between the rich and the poor, decreasing the gender gap and increasing\ncommunity participation in school management.\n\n\n_6.5 How will the project monitor performance in terms of social development outcomes?_\n\n\nThe MOE planning unit will monitor enrollment paying attention to gender gaps, socioeconomic gaps\n\nand performance of students by socioeconomic class through use of surveys of students.", "output": {"entities": {"named_data": [], "descriptive_data": ["surveys of students"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000102", "page": 24, "chunk": 1, "title": "Burundi - Second Social Action Project", "pdf_url": "http://documents1.worldbank.org/curated/en/590301468744270104/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "surveys of students", "label": "DESCRIPTIVE_DATA", "score": 0.8922238349914551, "start": 1811, "end": 1830, "probe_score": 0.3477, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " moving with a companion (all 99%), IDPs (98%) and women moving with a companion (96%).\n\n   - Important needs for all protection services were identified for all population groups. All types of protection services (12 in total) were described as\nneeded but not present for one or more population groups by 50% of covered communities or more.\n\n   - 64% of covered communities reported concerns with humanitarian assistance. Out of the total covered, 11 communities reported that request for\ndocumentation to access assistance as a concern.\n\n   - Among covered communities having reported lack/loss of civil documentation as occurring, expired document (100% of covered communities),\ngovernment services not available (98%) and “never had it” (97%) were mentioned among the reasons while 100% of covered communities\nindicated that restricted freedom of movement was one of the consequences.\n\n   - Among covered communities having reported lack/loss of civil documentation as occurring, all types of documents were difficult to obtain (by 96% of\ncovered communities or more for each document).\n\n   - 88% of covered communities reported housing, land and property issues as occurring. Out of those, 17% identified “property is unlawfully occupied\nby others” and 13% mentioned “rules and processes are unclear/changing” as “common” HLP concerns.\n\n\n**4. PROTECTION ISSUES**\n\n\n**a. Occurrence of protection issues**\n\n**i. Analysis coverage** (Number of communities covered in the analysis and number of those communities reporting occurrence of protection issues)\n\n\nCovered in the analysis Reported as occurring (at least sometimes) Total number of communities in the Governorate\n\n\n\n\n\n\n\n\n\n**ii. Percentage of covered communities reporting protection issues as occurring**\n\n\n\nDomestic violence\n\n\nLack/loss of civil documents\n\n\nChild recruitment\n\n\nHousing/land/property issues\n\n\nEarly marriage\n\n\nFamily separation\n\n\nExplosive hazards*\n\n\nChild labour preventing school attendance\n\n\nEconomic exploitation\n\n\nHarassment\n\n\nSexual harassment\n\n\nKidnapping/Abduction\n\n\nSexual violence\n\n\n\n\n\n\n\n\n\n*For explosive hazards", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000887", "page": 1, "chunk": 1, "title": "Whole of Syria Protection Needs Overview (PNO), 2018: Deir-ez-Zor Governorate", "pdf_url": "https://reliefweb.int/attachments/832458e6-8685-3f85-adc1-d3459b68a268/2018_wos_protection_needs_overview_-_deir-ez-zor_governorate.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "completed sub-projects local authorities provide\nconform to ministry standards, resources and staff to operate\ndesigns and norms. and maintain facilities (e.g.\nprovision of teachers and\n\ntextbooks in the case of\nprimary schools);\n\n\nl(b) Targeted communities are lb. 1 At <sup>least 90%</sup> <sup>of</sup> - Beneficiary/ impact - Sub-projects reflect\nempowered to carry out projects are assessed as assessments and other beneficiary needs and\npriority investments. successful by communities evaluation reports improved access to social and\n(achieve rmnimum expected economic services;\noutputs and\noutcomes/imnpacts).\n\n                                     - Supervision missions                                     - PPA methodology is\nlb.2 All supported                  - Beneficiary Assessments internalized by NaCSA and\ncommunities have conducted                - NSAP quarterly progress partners;\nparticipatory needs reports\nassessments and project                 - Participatory M&E results\nidentification using PPA\napproach.                 - Continuous social                 - Capacity building efforts\nI assessment process provided and/or coordinated\nlb.3 100% of communities                  - Participatory M&E results by NaCSA are appropriate and\nhave project management effective;\nstructures in place and trained\ncommunity members.\n\n**2.** Pilot and Special 2a.1 100 km. of feeder roads - Supervision <sup>missions;</sup> - NaCSA's commitment to\n\n**Programs in** Newly rehabilitated. - NSAP quarterly reports; pilot both programs remains\n**Accessible** **Areas** - Annual technical audits; strong\n2a.2 800,000 person days of                  - NaCSA M&E data\n**2(a)** **Rural Public Works** temporary employment\n**Program:** created.\n\nInfrastructure constructed 2a.3 250,000 \"woman days\" of\nand/or upgraded using labor temporary employment\nintensive techniques. created.\n\n\n2a.4 At mid-term review the\ncost per day", "output": {"entities": {"named_data": ["NaCSA M&E data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019710", "page": 30, "chunk": 0, "title": "Ethiopia - Seed Systems Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/892611468250239546/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NaCSA M&E data", "label": "NAMED_DATA", "score": 0.9113216400146484, "start": 1658, "end": 1672, "probe_score": 0.7359, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " mortality, irrespective of their individual losses.\nThe insurance would pay out to individual herders whenever the mortality rate in the _soum_\nexceeds a specific threshold. Finally, a 33 year time series on adult animal mortality is available\nfor all _soums_ and for the five major species of animals (cattle, horses, camels, sheep and goats).\n\n\n2 In Mongolia a _soum_ is equivalent to a county and an _aimag_ is equivalent to a state or province.\n\n\n2", "output": {"entities": {"named_data": [], "descriptive_data": ["33 year time series on adult animal mortality"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003532", "page": 3, "chunk": 2, "title": "wps4325", "pdf_url": "https://local/prwp/wps4325.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "33 year time series on adult animal mortality", "label": "DESCRIPTIVE_DATA", "score": 0.8230364322662354, "start": 186, "end": 231, "probe_score": 0.7671, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "4 per 100,000) double that among Lebanese (15.8 per 100,000). <sup>5</sup> [^5: Ministry of Public Health; Presentation, Biostatistics Department, March 2017.]\n\n11. **Lebanon also faces epidemiological risks, the reemergence of some diseases that had been**\n**controlled before the Syrian crisis, and a growing need for mental health services.** Despite intensive\nvaccination campaigns, outbreaks of measles, mumps, and waterborne diarrheas are increasing, mainly\nin areas with high concentrations of refugees. While the vulnerable population in Lebanon shares a\ncommon disease burden, especially from chronic illnesses, the disease burden among displaced Syrians\nis largely concentrated around maternal and child health, communicable diseases, and mental health.\nThe majority of displaced Syrians visit providers for infections and communicable diseases (40 percent). <sup>6</sup> [^6: LCRP 2015-2016.]\nThere is also a significant demand for antenatal care. According to an assessment conducted in 2015, 20\npercent of displaced Syrian households have either a pregnant or a lactating woman, compared to 6.5\npercent among Palestinian refugees from Syria. <sup>7</sup> [^7: LCRP 2015-2016; WFP, UNICEF, and UNHCR, Vulnerability Assessment of Syrian Refugees in Lebanon, 2015.] There is also a growing need for specialized mental\nhealth services for both Lebanese and displaced Syrians. A research study conducted in 2016 reported a\nclear increase in mental health disorders among the displaced Syrian youth and adult population. <sup>8</sup> [^8: Lebanon: Mental health system reform and the Syrian crisis. Elie Karam et al. _BJPSYCH International_ 13 (4). November 2016.]\nPrevalence rates of depression were found to be 16.8 percent among displaced Syrians and 13.3 percent\namong Lebanese. Similarly, prevalence rates for anxiety were found to be 56 percent among displaced\nSyrians and 50.7 percent", "output": {"entities": {"named_data": [], "descriptive_data": ["assessment conducted in 2015"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000032", "page": 14, "chunk": 1, "title": "Lebanon - Health Resilience Project", "pdf_url": "http://documents.worldbank.org/curated/en/616901498701694043/pdf/Lebanon-Health-PAD-PAD2358-06152017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "assessment conducted in 2015", "label": "DESCRIPTIVE_DATA", "score": 0.8008165955543518, "start": 975, "end": 1003, "probe_score": 0.9869, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*** (95.66)*** (76.56)*** (75.56)*** (70.65)*** (66.39)***\n\nIGC squared 0.229 0.196 0.225 0.204 0.269 0.207\n\n<u>Proportion of SC explained by IGC</u> <u>0.580</u> <u>0.509</u> <u>0.599</u> <u>0.503</u> <u>0.585</u> <u>0.532</u>\n\n\n<u>No. of observations</u> 34,585 39,562 21,895 23,625 <u>12682</u> 15,937\n\nRobust t statistics in parentheses. Standard errors corrected for clustering at family level\n\n- significant at 10%; ** significant at 5%; *** significant at 1%\n\n\n38", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005227", "page": 39, "chunk": 2, "title": "wps6055", "pdf_url": "https://local/prwp/wps6055.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000161", "page": 62, "chunk": 2, "title": "Cambodia - Social Fund II Project", "pdf_url": "http://documents1.worldbank.org/curated/en/932001468769834027/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**2.2. Access to Livelihoods and economic inclusion**\n\n\nOn average,70% of targeted community members that accessed livelihood opportunities and\nother economic inclusion services in 2023 and 2024 were Females. All the reporting country\noperations attained gender parity index of 1 except Djibouti. Uganda operation had the highest\nproportion of females reached, at 71% as indicated in the table below.\n\n|Uganda|478,519|196,947|675,466|71%|\n|---|---|---|---|---|\n|**Rwanda**|1,091|945|2,036|**54%**|\n|**Somalia**|1,622|1,326|2,948|**55%**|\n|**Djibouti**|275|296|571|**48%**|\n|**Sudan**|42,225|25,785|68,010|**62%**|\n|**Ethiopia**|2,923|1,766|4,689|**62%**|\n|**South Sudan**|8,572|4,775|13,347|**64%**|\n|**Total**|**535,227**|**231,840**|**767,067**|**70%**|\n\n\n\n_Table 2: Number of people reached with livelihoods services, 2023-2024 (Available data)_\n\n\nThe region achieved **Gender Parity Index (GPI) of 1.55**, indicating that more females received\nlivelihood and economic inclusion interventions compared to Males. Initiatives undertaken over\nthe two years include green entrepreneurship, self-employment in sustainable agriculture support,\nand wage employment facilitation", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Available data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000536", "page": 3, "chunk": 0, "title": "East, Horn of Africa and Great Lakes Region - Gender Equality, 2024 Annual Update", "pdf_url": "https://reliefweb.int/attachments/4d35dd4f-2421-484f-8042-99a3f78064f3/EHAGL%20-%20Annual%20Gender%20Equality%20Update%202024%20Final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Available data", "label": "VAGUE_DATA", "score": 0.7759366035461426, "start": 832, "end": 846, "probe_score": 0.5885, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Evaluation**\n\n\n55. **Project monitoring and verification will be undertaken by the implementing agency to ensure**\n**the project is being implemented in line with the proposed objectives and is on track to achieve**\n**expected results.** Project progress reports will be prepared by CDR, with inputs from MPWT and the\nSNRSC where needed, on a semi‐annual basis and submitted to the Bank for review and comments within\n45 days from the end of the reporting period. These reports shall include among others: (a) an update on\nthe results achieved based on the indicators and target values established in the results framework; (b)\nbreakdown of jobs created by type, location, gender, and nationality based on contractors’ and\nsupervision consultants’ reports; (c) the activities carried out throughout the reporting period under each\ncomponent; (d) key issues/constraints or risks affecting project implementation that require attention\nwith corresponding proposed measures to address them; (e) disbursement calendar for the next six\nmonths; and (f) progress achieved in the implementation of the environmental and social safeguards\ninstruments (ESMPs, RAPs, Abbreviated Resettlement Action Plans [ARAPs]). CDR will be responsible for\nproject data collection and compilation as well as the overall project monitoring and evaluation. In\naddition, an in‐depth project implementation progress assessment will be carried out at the midterm\nreview; CDR will prepare a report and make a formal presentation of the progress made during the project\nlife up to that point.\n\n\n56. **The World Bank, with potential support from other donors, will ensure continuous**\n**implementation support.** The key World Bank specialists are based in Beirut and will have regular\ninteraction with CDR and frequent field visits. This will allow the Bank to provide continuous monitoring\nand verification support far exceeding the regular one or two implementation support missions generally\nrequired for such projects. The World Bank will", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["project data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 32, "chunk": 1, "title": "Lebanon - Roads and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/210611486651815142/pdf/Lebanon-Roads-Employment-PAD-P160223-01262017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "project data", "label": "VAGUE_DATA", "score": 0.5414512753486633, "start": 1233, "end": 1245, "probe_score": 0.0086, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " from current conditions. A 2005 survey finds higher profits for peasant compared to\n\ncorporate farms -though no significant differences in total factor productivity (Lerman _et al._ 2007)- but\n\ndoes not reconcile this with expansion by super-large farms. While credit market imperfections have\n\nbeen identified as a key constraint to needed investment in new technology (Zinych and Odening 2009),\n\nthis is not translated into differences in capital costs.\n\n\n**3. Data and descriptive evidence**\n\n\nDetailed panel data illustrate three features. First, yields grew rapidly after 2006, with sunflower-, corn-,\n\nand soybean-yields almost doubling, prompting a marked shift to oilseeds. Second, transformation of the\n\nagricultural sector was due more to new entry than to existing farm growth. Most entrants cultivated\n\nfarms 1,000-3,000 ha in size, which are large by European standards but not super-large. Finally,\n\nalthough land sales are not allowed, there was massive concentration of operational holdings; area\n\nfarmed by units above 10,000 (20,000) ha expanded by more than 2 (1.5) mn. ha (or 10% of the total) in\n\n\n7A ban on sales of agricultural land (moratorium) was established in 2001 making the rental market the only instrument for land transfer among\ncultivators.\n8 The 2012 draft “Law on Land Market” is the country’s 5th attempt to lift the current moratorium on land sales since 2005. Although there is\nbroad consensus about the need to establish secure property rights to land to encourage investment, there was agreement that the Draft Law was\nworse than the status quo resulting in its withdrawal (Lapa 2011) and a decision has now been postponed until 2016.\n\n\n7", "output": {"entities": {"named_data": [], "descriptive_data": ["2005 survey", "panel data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005691", "page": 8, "chunk": 1, "title": "wps6544", "pdf_url": "https://local/prwp/wps6544.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2005 survey", "label": "DESCRIPTIVE_DATA", "score": 0.7620773911476135, "start": 28, "end": 39, "probe_score": 0.6932, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "panel data", "label": "DESCRIPTIVE_DATA", "score": 0.6653093099594116, "start": 507, "end": 517, "probe_score": 0.5983, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "br>in FY 2023/14, if all targets are achieved. Proportional reduction per target<br>not achieved, see the verification narrative for scaling.<br>|\n|6|**DLI 6**<br>Program LGs<br>with Town<br>Clerks in place|8 million<br>US$|0|0|By Program<br>completion|18 Town Clerks<br>in year 1 and 22<br>Town Clerks<br>thereafter|100% of<br>annual amount|<br>US$1.6 million per year with required town clerk in Program Municipal LGs<br>each year FY 2018/19, FY 2019/20, FY 2020/21, FY 2021/22 and FY<br>2022/23.|\n|7|**DLI 7:**<br>Results on<br>Physical<br>Planning, land<br>tenure security<br>and urban<br>infrastructure<br>development in<br>Program LGs<br>hosting<br>refugees|14.6<br>million<br>US$|3.0||Annually,<br>starting in<br>FY 2018/19<br> <br> <br>|<br>MoLHUD plan<br>for support to<br>refugee host areas<br>formulated for the<br>forthcoming year<br>and minimum<br>execution of key<br>results specified<br>achieved for the<br>preceding year.|100% of<br>annual<br>amount.<br> <br> <br> <br> <br> <br>|FY 2018/19: Once MoLHUD submits plan in agreed format, 3", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000014", "page": 50, "chunk": 2, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents1.worldbank.org/curated/en/143681526614252328/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " quickly, even if the presentations are less than fully polished. The papers carry the_\n_names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those_\n_of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and_\n_its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._\n\n\nProduced by the Research Support Team", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001442", "page": 1, "chunk": 1, "title": "idu192123c181b7581448d1903110eb852951475", "pdf_url": "https://local/prwp/idu192123c181b7581448d1903110eb852951475.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nGenerating Growth Opportunities and Productivity for Women Enterprises Uganda Project (P176747)\n\n\n**B. Results Monitoring and Evaluation Arrangements**\n\n\n**Monitoring and Regular Reporting**\n\n79. **Objectives and design** . The objective of the M&E system is to track the project’s implementation progress and\nachievement of expected outcomes to enable the government (national and sub-national) and World Bank to address\nissues as they arise. An integrated web-based data collection platform will be established at the MGLSD into which data\non implementation progress and outcomes will be entered will be entered to track implementation of project\ninterventions and their outcomes. The MGLSD will contract a consulting firm to design and develop the integrated data\nplatform, which will include an interface that allows the persons responsible for M&E at all implementing agencies to\nenter monitoring data that they collect.\n\n80. **The MGLSD will lead the overall M&E efforts.** The MGLSD already has an experienced Planning Unit which has\nbeen responsible for leading the efforts to track government programs. Staff with specialized skills in (a) survey design,\nimplementation, and analysis; (b) operations and maintenance of management information systems; and (c) data\nmanager; and (d) others as needed will comprise the M&E team at the MGLSD.\n\n81. **M&E teams will be established as members of the PITs at both the national.** They will be responsible for collecting\nand sharing information presented in the results framework in accordance with the procedures laid out in the M&E\nmonitoring plan, and entering the data into the integrated data platform. Data from each implementing agency will be\naggregated with the data of others and used as the basis of quarterly progress reports.\n\n82. **Data generation and reporting** . The data to track the key performance indicators come from (", "output": {"entities": {"named_data": [], "descriptive_data": ["Data from each implementing agency"], "vague_data": ["monitoring data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 36, "chunk": 0, "title": "Uganda - Generating Growth Opportunities and Productivity for Women Enterprises Uganda Project", "pdf_url": "http://documents.worldbank.org/curated/en/527091655323259747/pdf/Uganda-Generating-Growth-Opportunities-and-Productivity-for-Women-Enterprises-Uganda-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "monitoring data", "label": "VAGUE_DATA", "score": 0.6173052191734314, "start": 910, "end": 925, "probe_score": 0.0303, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Data from each implementing agency", "label": "DESCRIPTIVE_DATA", "score": 0.7661868333816528, "start": 1678, "end": 1712, "probe_score": 0.1516, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">community consultation,<br>indigenous land<br>management practices,<br>grievance settlement<br>mechanisms|Woreda<br>officials,<br>experts, kebele<br>officials and<br>development<br>agents|Mobilization strategies; capacity<br>constraints, formal and informal<br>institutions, capacity of local<br>institutions, indigenous land<br>management knowledge, self-help<br>and mutual support groups,<br>vulnerable groups in the area,<br>implementation and monitoring,<br>grievance handling mechanism, etc.|\n\n\n\nAmong the secondary data, the Ethiopian government laws and regulations related to land\nexpropriation and compensation, equity and inclusion, World Bank social safeguard policies, project\nappraisal documents, SLMP-II social assessment report (SA) and RPF, periodic reports as well as\nother World Bank flagship programs' safeguard instruments were the major ones. Consultative\nWorkshop was conducted from January 11-21, 2018 with regional environment and social safeguard\nspecialists and representative from regional Environment, Forest and climate change Bureaus.\n\n\n13", "output": {"entities": {"named_data": ["SLMP-II social assessment report"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010201", "page": 17, "chunk": 1, "title": "Ethiopia - Resilient Landscape and Livelihood Project : social assessment : Social assessment", "pdf_url": "https://documents.worldbank.org/curated/en/250681528364951447/pdf/Social-Assessment-RLLP-WB-MEC-SD-REV-May-21-2018-Clean-FOR-DISCLOSURE.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SLMP-II social assessment report", "label": "NAMED_DATA", "score": 0.7146655917167664, "start": 711, "end": 743, "probe_score": 0.4619, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**PAD DATA SHEET**\n\n_Chad_\n\n_Emergency Food and Livestock Crisis Response Project (P151215)_\n\n**PROJECT APPRAISAL DOCUMENT**\n\n\n_AFRICA_\n\nReport No.: PAD1101\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Basic Information|Col2|Col3|Col4|Col5|Col6|Col7|\n|---|---|---|---|---|---|---|\n|Project ID|Project ID|Project ID|EA Category|EA Category|Team Leader|Team Leader|\n|P151215|P151215|P151215|B - Partial Assessment|B - Partial Assessment|Bleoue Nicaise Ehoue|Bleoue Nicaise Ehoue|\n|Lending Instrument|Lending Instrument|Lending Instrument|Fragile and/or Capacity Constraints [X]|Fragile and/or Capacity Constraints [X]|Fragile and/or Capacity Constraints [X]|Fragile and/or Capacity Constraints [X]|\n|Investment Project Financing|Investment Project Financing|Investment Project Financing|Financial Intermediaries [  ]|Financial Intermediaries [  ]|Financial Intermediaries [  ]|Financial Intermediaries [  ]|\n||||Series of Projects [  ]|Series of Projects [  ]|Series of Projects [  ]|Series of Projects [  ]|\n|Project Implementation Start Date|Project Implementation Start Date|Project Implementation Start Date|Project Implementation End Date|Project Implementation End Date|Project Implementation End Date|Project Implementation End Date|\n|14-Oct-2014|14-Oct-2014|14-Oct-2014|30-Apr-2017|30-Apr-2017|30-Apr-2017|30-Apr-2017|\n|Expected Effectiveness Date<br>Expected Closing Date|Expected Effectiveness Date<", "output": {"entities": {"named_data": ["PAD DATA SHEET"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000019", "page": 5, "chunk": 0, "title": "Chad - Emergency Food and Livestock Crisis Response Project", "pdf_url": "http://documents1.worldbank.org/curated/en/179061468215115488/pdf/PAD11010PAD0P1010Box385329B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PAD DATA SHEET", "label": "NAMED_DATA", "score": 0.6321051716804504, "start": 2, "end": 16, "probe_score": 0.1016, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " lodged with the Executive Office of Immigration Review (14,749 individuals).\n\n(10) Australian figures are based on the number of applications lodged for protection visas.\n\n(11) Monthly asylum data for Japan is available from 2002. Figures for Japan are UNHCR estimates.\n\n\n**8** Asylum Trends, First half 2014", "output": {"entities": {"named_data": [], "descriptive_data": ["Monthly asylum data for Japan"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000864", "page": 7, "chunk": 4, "title": "UNHCR Asylum Trends, First half 2014: Levels and Trends in Industrialized Countries", "pdf_url": "https://reliefweb.int/attachments/7f25b7c6-aaf7-3a20-8f40-724aa5597bd5/5423f9699.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Monthly asylum data for Japan", "label": "DESCRIPTIVE_DATA", "score": 0.8789891004562378, "start": 178, "end": 207, "probe_score": 0.2663, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank** Implementation Status & Results Report\nStrengthen Ethiopia’s Adaptive Safety Net (P172479)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Cumulative number of ECD<br>centers in PSNP Woredas<br>(Number)|Comments on<br>achieving targets|Col3|6 ECD centers per region have been completed in PSNP woredas in Central Ethiopia, South<br>Ethiopia, Sidama and Oromia regions; and 4 centers have been completed in Tigray|Col5|Col6|Col7|Col8|Col9|\n|---|---|---|---|---|---|---|---|---|\n|Children enrolled in ECDs<br>(Number)|0.00|Apr/2020|0|30-Jun-2025|548|31-Mar-2026|300.00|Jun/2026|\n|Children enrolled in ECDs<br>(Number)|Comments on<br>achieving  targets|Comments on<br>achieving  targets|According to data provided by MOWSA|According to data provided by MOWSA|According to data provided by MOWSA|According to data provided by MOWSA|According to data provided by MOWSA|According to data provided by MOWSA|\n|Core beneficiary households<br>receiving their benefits in<br>electronic accounts<br>(Number)  PBC|845,487.00|May/2020|1,356,289|30-Jun-2025|1,450,475|31-Mar-2026|1,100,000.00|Jun/2026|\n|Core beneficiary households<br>receiving their benefits in<br>electronic accounts<br>(Number)  PBC|Comments on<br>achieving  targets|", "output": {"entities": {"named_data": [], "descriptive_data": ["data provided by MOWSA"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002529", "page": 8, "chunk": 0, "title": "Disclosable Version of the ISR - Strengthen Ethiopia’s Adaptive Safety Net - P172479 - Sequence No : 13", "pdf_url": "https://documents.worldbank.org/curated/en/099051926135030187/pdf/P172479-98157d07-f768-4a8e-8b64-49208ca184ad.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data provided by MOWSA", "label": "DESCRIPTIVE_DATA", "score": 0.6335739493370056, "start": 703, "end": 725, "probe_score": 0.9765, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nworkers, delivery attended by skilled attendant, and contraceptive prevalence rates against the\ncorresponding rates for the four regions that need special attention.\n\n\n**Table 11. Comparison of selected MDG maternal health indicators between the**\n**<u>national average and corresponding rates for regions that need special attention</u>**\n\n\n\n\n\n|Col1|%|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**_Indicator_**|**_National_**|**_Afar_**|**_Somali_**|**_Ben-_**<br>**_Gumuz_**|**_Gambella_**|\n|Ante-natal care coverage|71.4|25.3|56.5|53.5|31.3|\n|Deliveries attended by skilled personnel|16.8|12.9|213.0|5.7|10.7|\n|Clean and safe delivery service coverage|17.0|0.5|0.9|8.1|0.4|\n|Post-natal care coverage|36.2|9.5|5.2|21.1|3.0|\n|Contraceptive acceptance rate|61.9|13.5|8.6|38.6|13.2|\n\n\n_Source_ : Health and Health Related Indicators: FMOH, 2009/10.\n**Source**\n\n\nIn addition, misconceptions are widely prevalent surrounding female circumcision. It is\nbelieved that uncircumcised women tend to be promiscuous, and are unlikely to find husbands\nand bear children. Such misconceptions have resulted in the widespread practice of genital\nmutilation in the Afar region. Likewise", "output": {"entities": {"named_data": ["Health and Health Related Indicators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012014", "page": 84, "chunk": 1, "title": "Ethiopia - Health Millennium Development Goals Program for Results Project : environmental assessment", "pdf_url": "https://documents.worldbank.org/curated/en/375001468257052548/pdf/E40800REVISION0SSA0SL030JAN130final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Health and Health Related Indicators", "label": "NAMED_DATA", "score": 0.6860172748565674, "start": 801, "end": 837, "probe_score": 0.9885, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nbalanced regional development; c) promoting urban competitiveness and productivity for employment\ncreation; d) promoting urban environmental conservation and protection, climate change, mitigation and\nadaptation mechanisms; and e) promoting good urban governance <sup>12</sup> [^12: The Policy has been adopted but has not yet been launched.] .\n\n8. **_Furthermore, the influx of refugees in Uganda is currently a major challenge, stretching LG_**\n**_capacities for service delivery due to the rapid increase in population._** Uganda is currently the largest host\nof refugees in Africa and the third-largest host in the world, with over 1.4 million refugees. Refugees settled\nin Northern Uganda, predominantly in the West-Nile sub-region, now constitute more than one-third of\ndistrict populations <sup>13</sup> [^13: Data from UNHCR shows that as of December 17, 2017, the districts of Arua, Yumbe, Moyo, Adjumani and Lamwo host a total\nof 971,572 refugees in addition to a host population of 1,832,831 nationals.], with refugee population in Moyo and Adjumani districts constituting close to 60\npercent. Uganda has one of the most progressive refugee regimes in the world, where refugees have right to\nwork, establish business, move freely within the country, access social services, own property, and obtain\ndocumentation. Refugees are also given plots of land on which to cultivate and build houses. This is putting\nenormous pressure on LGs’ ability to provide adequate infrastructure and services to this rapidly increased\npopulation, given that refugees are not limited to refugee settlements and can freely move to urban areas and\naccess services. The influx of around 900,000 refugees from South Sudan since July 2016 is stretching local\nplanning systems and capacities in Northern Uganda to the limit, in one of the poorest and most underserved\nsub-regions in the country. Recently, there has also been an increase in new arrivals from DRC who are\npredominantly settled in the Western and South West", "output": {"entities": {"named_data": ["Data from UNHCR"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000006", "page": 10, "chunk": 1, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents.worldbank.org/curated/en/143681526614252328/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data from UNHCR", "label": "NAMED_DATA", "score": 0.7744526863098145, "start": 818, "end": 833, "probe_score": 0.9961, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " **.** Various\nelements have been introduced into the design of the AF to strengthen participating MLGs impact on\npromoting local economic development (LED) and job creation. Local firms in the formal sector face\nconsiderable constraints in establishing and sustaining their businesses, limiting prospects for the creation\nof more and better jobs. For example, according to World Bank Enterprise Survey Data for Uganda (2013),\nthe main constraints include infrastructure deficits and access to land; regulatory barriers and corruption;\nand access to finance <sup>20</sup> [^20: Highlighted as the biggest obstacles by 33.4, 31.7 and 12.3 percent of firms in Uganda, respectively.\n21World Bank (2016). _Re-positioning Local Governments for Economic Growth_ . The role of Local Governments in Promoting Local\nEconomic Development in Uganda – focusing on Jinja Municipal LG, and Arua and Nwoya District LGs.] . LGs have a role in helping or hindering the alleviation of these constraints to support\nprivate sector development and, consequently, job creation. The recent study undertaken by the World\nBank/Ministry of Local Government (MoLG) on LED <sup>21</sup> highlighted that LGs are currently doing little in\nthis direction, with their main relationship with the private sector centering on tax collection and requests\nfor donations. The study outlined some of the constraints faced by the private sector which are within the\nmandate of LGs. These fell under the four broad categories of infrastructure deficits, regulatory barriers,\nabsence of enterprise support and institutional capacity gaps within LGs.\n\n23. **_In line with the technical assessment and recent studies on LED in Uganda, design elements_**\n**_have therefore been introduced to support and incentivize MLGs to alleviate some of the local constraints_**\n**_that the private sector faces_** **.** LGs need a better understanding of their local economic potentials and the\nconstraints that key sectors face, a closer dialogue with the private sector, and improved incentives and", "output": {"entities": {"named_data": ["World Bank Enterprise Survey Data for Uganda"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000168", "page": 16, "chunk": 1, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents1.worldbank.org/curated/en/946901526654169395/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Bank Enterprise Survey Data for Uganda", "label": "NAMED_DATA", "score": 0.9043983221054077, "start": 374, "end": 418, "probe_score": 0.9896, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "> 11,992,100 13,358,200 100.0<br>100.0<br>100.0<br>48.6<br>49.3<br>49.2<br>49.8<br>50.8<br>52.2<br>56.1<br>61.2<br>60.0<br>_ 2,181,100_<br>_ 2,393,200 2,763,200_|\n\n\n**<mark>Grand Total</mark>** **<mark>11,699,300 14,385,300 16,121,400</mark>**\n\n\n**a** Percentages are based on data available for 9.0 million refugees. Calculation excludes accommodation types which are unknown.\n\n**b** Percentages are based on data available for 12.2 million refugees. Calculation excludes accommodation types which are unknown.\n\n**c** Percentages are based on data available for 12.3 million refugees. Calculation excludes accommodation types which are unknown.\n\n\nUNHCR Global Trends 2015 **53**", "output": {"entities": {"named_data": ["UNHCR Global Trends 2015"], "descriptive_data": ["data available for 12.2 million refugees"], "vague_data": ["data available for 9.0 million refugees", "data available for 12.3 million refugees"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001367", "page": 51, "chunk": 9, "title": "UNHCR Global Trends: Forced Displacement in 2015", "pdf_url": "https://reliefweb.int/attachments/d39729ec-75aa-3628-89e5-6ae32a617930/576408cd7.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data available for 9.0 million refugees", "label": "VAGUE_DATA", "score": 0.6491829752922058, "start": 277, "end": 316, "probe_score": 0.8064, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data available for 12.2 million refugees", "label": "DESCRIPTIVE_DATA", "score": 0.626532256603241, "start": 410, "end": 450, "probe_score": 0.8506, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data available for 12.3 million refugees", "label": "VAGUE_DATA", "score": 0.6033956408500671, "start": 544, "end": 584, "probe_score": 0.7802, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHCR Global Trends 2015", "label": "NAMED_DATA", "score": 0.8085353970527649, "start": 648, "end": 672, "probe_score": 0.9996, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " It will be especially important to include women in the design and construction\nof WASH facilities, for instance, to ensure these facilities are rehabilitated in ways that promote security\nand effective management on completion. The project will harmonize, to the extent possible, the labor\nprovisions adopted by the World Bank’s SSSNP and coordinate salary levels with UN coordination cluster\nstandards.\n\n\n47 Population figures for urban areas would be calculated based on a headcount or by complementing 2008 census with other\ndata sources (for example, DTM.)\n\n\nJune 22, 2020 Page 12 of 23", "output": {"entities": {"named_data": ["DTM"], "descriptive_data": ["2008 census"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000058", "page": 11, "chunk": 1, "title": "Project Information Document - South Sudan Enhancing Community Resilience and Local Governance Project - P169949", "pdf_url": "http://documents.worldbank.org/curated/en/890401593099068599/pdf/Project-Information-Document-South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project-P169949.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2008 census", "label": "DESCRIPTIVE_DATA", "score": 0.6666518449783325, "start": 507, "end": 518, "probe_score": 0.0823, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "DTM", "label": "NAMED_DATA", "score": 0.877101480960846, "start": 557, "end": 560, "probe_score": 0.0, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " d’accès), des indicateurs de santé préoccupants\n(couverture et accès aux services de santé (2 médecins pour mille habitants), mortalité et morbidité\ninfantile et maternelle <sup>3</sup> [^3: Mortalité infantile de 67 pour mille pour le pays entier.], prévalence du Sida), des niveaux d’éducation encore faibles (capacités d’accueil\ninsuffisantes, faibles taux de participation (66.6% dans le primaire), taux élevés d’analphabétisme des\nfemmes (51.5%)), ce qui à son tour entraîne une force de travail non qualifiée vouée au chômage\n(43.5%) <sup>4</sup> [^4: Toutes les données, issues de l’enquête EDIM de 2006, sont présentées pour Djibouti-ville.] .\n\n\n**2.** **Malgré la croissance récente du PNB, Djibouti reste bloqué dans un cercle vicieux de**\n**pauvreté et de chômage.** Les investissements directs étrangers (IDE) ont crû de façon non négligeable\nces dernières années (22% du PNB en 2006, soit une augmentation de 19.5% par rapport à 2005) mais les\neffets de cette croissance ne se sont pas répercutés sur les couches les plus pauvres de la société.\nSeulement quelques postes ont été créés, en nombre bien inférieur à ce que les autorités avaient prévu, et à\nce que le pays aurait besoin d’absorber pour réduire la pauvreté. L’impact de la croissance a été limité\njusqu’à présent et ce, pour trois raisons. Les IDE sont concentrés principalement", "output": {"entities": {"named_data": ["enquête EDIM"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000163", "page": 5, "chunk": 1, "title": "Djibouti - Urban Poverty Reduction Program Project : Djibouti - Projet de Reduction de la Pauvrete Urbaine", "pdf_url": "http://documents1.worldbank.org/curated/en/934951468235146436/pdf/429990PAD0FREN1erni1re0version02008.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "enquête EDIM", "label": "NAMED_DATA", "score": 0.8044724464416504, "start": 591, "end": 603, "probe_score": 0.9713, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "x|x|x|x|x|x|\n|Local (“host”) population|||x|x|x||x|\n\n\n**C. Project Components**\n\n**_Component A: Targeted Food Assistance (US$7 million IDA_** )\n\n7. Under this component, WFP provides a safety net to 31,200 refugees/returnees who\nreceive support for 12 months following their return. Safety nets are notoriously difficult to\ninitiate in crisis situations, and given its current operations in Chad, WFP is well placed to scale\nup an existing safety net that provides both vouchers (for people to purchase food) and direct\nfood transfers (consisting of basic food items as well as specialized foods for children). Targeted\nfood assistance will improve the food security of refugees and returnees and help them\nreestablish livelihoods by preventing them from having to sell their remaining productive assets.\nVouchers will be provided for eight months of the year; in the other four months (the lean\nseason), beneficiaries will receive direct transfers of food. The vouchers cover the cost of a local\nstandard food basket (currently about US$0.30 per day).\n\n8. Lists of individuals who will receive food assistance will be drawn up based on data on\nrefugees and returnees provided by agencies such as IOM, which facilitate the movement of\npeople from CAR to Chad. Informal returnees are identified locally and verified by WFP staff as\n\n\n25", "output": {"entities": {"named_data": [], "descriptive_data": ["data on\nrefugees and returnees"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000007", "page": 34, "chunk": 2, "title": "Chad - Emergency Food and Livestock Crisis Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/179061468215115488/pdf/PAD11010PAD0P1010Box385329B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on\nrefugees and returnees", "label": "DESCRIPTIVE_DATA", "score": 0.927923858165741, "start": 1138, "end": 1168, "probe_score": 0.9682, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " assistance programmes\nas they are deemed able to meet\ntheir needs without external food\nsupport. Similarly, in Lebanon\napproximately 265,000 people have\nbeen removed from food assistance\nthrough an ongoing verification and\ntargeting process, which is expected\nto result in further reductions over\nthe course of the year.\n\n\nBetter assessment data has also\nallowed actors to introduce a\ngradual approach to targeting.\nIn April 2015, a tiered targeting\napproach was adopted in Jordan,\nwhich classified approximately\n190,000 refugees as extremely\nvulnerable, enabling them to\nreceive the full voucher value, and\n240,000 refugees as vulnerable\n\n\n\nallowing them to receive a reduced\nvoucher value.\n\n\nAs of April 2015, at least 1.6 million\nSyrian refugees and other affected\npeople across the region received\ncash-based food assistance in the\nform of e-vouchers - the primary\nassistance modality in the region.\nThe e-card modality reduced\nthe printing, transportation\nand distribution processes per\nhousehold each month, increasing\nthe efficiency of normally lengthy\nmanual interventions and reducing\ntime and transaction costs for\nbeneficiaries and operations for\nfood sector actors. With funds\nautomatically transferred each\nmonth, beneficiaries are no longer\nrequired to attend large-scale\nmonthly voucher distributions,\nthereby reducing their associated\ntransport costs. Moreover, it\nresulted in operational cost savings\nfor food security actors.\n\n\nVouchers and cash-based food\nassistance have injected more than\nUSD 1 billion into local economies\nthroughout the region since the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["assessment data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000205", "page": 15, "chunk": 1, "title": "3RP Regional Progress Report, June 2015", "pdf_url": "https://reliefweb.int/attachments/159eeee2-f61c-3601-a53d-760244ad3201/3RP_Progress_Report_Final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "assessment data", "label": "VAGUE_DATA", "score": 0.6652683615684509, "start": 331, "end": 346, "probe_score": 0.0048, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "China<br>Russian<br>Federation<br>_Source:_ Global Findex database.<br>100<br>75<br>50<br>25<br>Use of different mechanisms for making direct electronic pay<br>Adults using type of payment mechanism in the past year (%), 2014<br>FIGURE 1.16<br>East Asia & Pacific<br>Has acco<br>financial<br>Europe & Central Asia<br>High-income OECD economies<br>Latin America & Caribbean<br>Middle East<br>South Asia<br>Sub-Saharan Africa<br>_Source:_ Global Findex database.<br>0<br>20<br>40<br>60<br>80<br>Used debit card<br>Used credit card<br>Used mobile phone to access account|||||||||||||\n||THE GLOBAL FINDEX DATABASE<br>21<br>How many people access fnancial institution accounts through a mobile phone?<br>While the use of stand-alone mobile money accounts is limited mostly to some Sub-Saharan<br>African countries, even elsewhere people may be using mobile phones in conjunction<br>with an account at a fnancial institution. Globally in 2014, 16 percent of adults with a<br>fnancial institution account reported having used their mobile phone in the past year<br>to access that account and make a transaction. High-income OECD and Sub-Saharan<br>African economies had the largest shares who reported doing so, at just over 20 percent<br>on average, followed by East Asia and the Pacifc with 17 percent. In all other regions the<br>average share was less than", "output": {"entities": {"named_data": ["Global Findex database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006320", "page": 28, "chunk": 35, "title": "wps7255", "pdf_url": "https://local/prwp/wps7255.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Global Findex database", "label": "NAMED_DATA", "score": 0.6603816747665405, "start": 44, "end": 66, "probe_score": 0.9994, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nGreater Beirut Public Transport Project (P160224)\n\n\n**<mark>I.</mark>** **<mark>STRATEGIC CONTEXT</mark>**\n\n\n**A. Country Context**\n\n\n1. **Lebanon is a middle-income country with a population of 4.5 million people in 2015, not taking**\n**into account the approximate 1.5 million Syrian refugees and 450,000 Palestinian refugees residing in**\n**the country.** Real gross domestic product (GDP) growth for 2016 was estimated at 1.8 percent, reflecting\nthe impact of regional turmoil and the absence of reforms **.** The services sector—historically a key growth\ndriver <sup>1</sup> [^1: Between 1997 and 2011—latest utilized final national accounts—the services sector accounted for an average of 74 percent of\nreal GDP.] —has been severely affected by the Syria conflict and has contributed significantly to Lebanon’s\nlow growth in recent years. Tumbling growth since 2011 and the large fiscal burden associated with Syrian\nrefugees’ access to public services and infrastructure have pushed the debt-to-GDP ratio higher again\n(around 140 percent as of end-2015), resulting in a marked deterioration of the country’s macroeconomic\nenvironment. Meanwhile, the growth outlook remains subdued given the ongoing conflict in Syria and\nother regional tensions and economic slowdown. The World Bank projects real growth between 2 percent\nand 2.5 percent yearly over the medium term.\n\n\n2. **Lebanon’s poor infrastructure represents a key constraint to growth.** Despite being an uppermiddle-income country, Lebanon’s infrastructure is in a poor condition. According to the World Economic\nForum’s Competitiveness Index, <sup>2</sup> [^2: World Economic Forum. Global Competitiveness Index 2014/2015.] Lebanon’s infrastructure is the second main constraint to growth and its\nsupply and quality is materially", "output": {"entities": {"named_data": [], "descriptive_data": ["final national accounts"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000074", "page": 12, "chunk": 0, "title": "Lebanon - Greater Beirut Public Transport Project", "pdf_url": "http://documents1.worldbank.org/curated/en/471241521338566907/pdf/PAD-final-02262018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "final national accounts", "label": "DESCRIPTIVE_DATA", "score": 0.6626386642456055, "start": 642, "end": 665, "probe_score": 0.9975, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nThe above results do not distinguish\nbetween Ukrainian refugees improving\nthe labour market outcomes in the\npoviats they arrived in and Ukrainian\nrefugees disproportionately moving to\nthe poviats with better performance,\nwhich continued to perform better in\nsubsequent quarters. This distinction is\nmostly academic, as causality is always\nuncertain in social sciences, as effects can\nrun both ways. However, instrumental\nvariable regressions have been performed\nto ascertain causal effects. This approach\nis widely used in studies focused on the\nimpact of migration on socio-economic\noutcomes. This econometric technique\nadditionally uses variables that correlate\nwell with Ukrainian refugees’ employment\nshares, but do not directly cause changes\nto the Polish citizens' employment rate\nor to the unemployment rate. Two\nvariables have been used: the first was\nthe share of Ukrainian children in Polish\nschools, and the second was the pre-war\ndistribution of Ukrainian citizens based\non notifications of entrusting work to\na foreigner. Unfortunately, panel fixed\neffects regressions with quarterly dummies\nshowed statistically insignificant results\nfor either instruments or both. In addition,\nregressions using only the instrumental\nvariable for the distribution of pre-war\nUkrainian citizens reveal only a modest\nlink to the employment share of Ukrainian\nrefugees.\n\n\nSimilarly to the above results, an early\nanalysis by Gromadzki and Lewandowski\n(2023) found no impact on the employment\nrate or unemployment rate. In a peerreviewed scientific article, they examined\nthe impact of Ukrainian refugees on the\nlabour market outcomes of Polish women\nfrom January to April 2022 (as most\nUkrainian refugees are female). They found\nthat the proportion of Ukrainian refugees\nin a given poviat had no statistically\nsignificant impact on the employment rate\nor unemployment rate of Polish women.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 29. Effect of a 1 pp. change in employment share of Ukrainian refugees on gross wage change**\nCross-section model of all 380 poviat", "output": {"entities": {"named_data": [], "descriptive_data": ["notifications of entrusting work to\na foreigner"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 20, "chunk": 0, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "notifications of entrusting work to\na foreigner", "label": "DESCRIPTIVE_DATA", "score": 0.8123968243598938, "start": 1062, "end": 1109, "probe_score": 0.6331, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### **Introduction**\n\nAs ample evidence of the past ten years\ndemonstrates, cash is an important part of the\nhumanitarian toolbox that can allow people\nto meet their basic needs effectively and with\ndignity. Little evidence however exists on how\nfar multipurpose cash contributes to sectoral\noutcomes in health, WASH, shelter, food security\nand nutrition, education, livelihoods, energy and\nenvironment programming, and how sectoral\ninterventions should include multipurpose cash\nalong with accompanying support activities to best\nreach intended sectoral outcomes that contribute\nto protection.\n\n\nThis case study in Afghanistan is part of a review\ncommissioned by UNHCR to investigate the\ncontribution of multipurpose cash assistance\nin meeting sectoral outcomes, the activities\nand interventions that can best complement\nmultipurpose cash in different sectors, and related\nchallenges, gaps and opportunities. This case\nstudy focuses on the Voluntary Repatriation Cash\nGrant delivered by UNHCR to eligible documented\nreturnees to provide the means to meet basic\nneeds in the first phase upon return.\n\n\nThis case study relied on a mainly qualitative\nmethodology and collected primary and secondary\ndata through key informant interviews with UNHCR\nAfghanistan and other organizations such as UN\nagencies, INGOs and national NGOs. In addition,\nreturnee monitoring data provided by UNHCR on\nthe cash programme under analysis and other\nrelevant studies were used, as well as Focus\nGroup Discussions (FGDs) with beneficiaries of\nmultipurpose cash assistance. More details on the\nmethodology are found in the main review, and\nparticipants of key informant interviews and FGDs\nconducted in Afghanistan can be found in Annex 3.\n\n\n##### **Limitations**\n\nThe case study in Afghanistan was faced with two\nmain limitations. Security concerns restricted field\nvisits to specific locations in the outskirts of Kabul\nand Mazar-i-Sharif (Mazar), Balkh Province, that\nwere deemed safe for the research to take place.\nAlso, UNHCR Sub Office staff in Mazar were unable\nto locate returnees from Iran <sup>1</sup> or other countries. As", "output": {"entities": {"named_data": [], "descriptive_data": ["returnee monitoring data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000080", "page": 6, "chunk": 0, "title": "Afghanistan Case Study: Multi-purpose Cash and Sectoral Outcomes", "pdf_url": "https://reliefweb.int/attachments/020bd31a-6682-30a1-8823-7d27b21d2a9b/5b2cfab97.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "returnee monitoring data", "label": "DESCRIPTIVE_DATA", "score": 0.7359465956687927, "start": 1341, "end": 1365, "probe_score": 0.1045, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".\n92\n87\n91\nIraq\n11\n7\n8\nIreland\n95\n95\n91\nIsrael\n90\n90\n84\nItaly\n87\n83\n83\nJamaica\n78\n78\n70\nJapan\n97\n97\n95\nJordan\n25\n16\n16\nKazakhstan\n54\n56\n46\nKenya\n75\n71\n63\nKorea, Rep.\n94\n93\n92\nKosovo\n48\n36\n42\nKuwait\n73\n64\n66\nKyrgyz Republic\n18\n19\n15\nLatvia\n90\n90\n86\nLebanon\n47\n33\n27\nLithuania\n78\n78\n67\nLuxembourg\n96\n97\n94\nMacedonia, FYR\n72\n64\n62\nMadagascar\n9\n8\n4\nMalawi\n18\n14\n10\nMalaysia\n81\n78\n76\nMali\n20\n15\n13\nMalta\n96\n96\n94\nMauritania\n23\n21\n12\nData for all indicators can be found on the Global Findex \nwebsite (http://www.worldbank.org/globalfindex).", "output": {"entities": {"named_data": ["Global Findex"], "descriptive_data": ["Data for all indicators"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006320", "page": 90, "chunk": 1, "title": "wps7255", "pdf_url": "https://local/prwp/wps7255.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data for all indicators", "label": "DESCRIPTIVE_DATA", "score": 0.6708517670631409, "start": 428, "end": 451, "probe_score": 0.9867, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Global Findex", "label": "NAMED_DATA", "score": 0.5081144571304321, "start": 472, "end": 485, "probe_score": 0.8716, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". **Benefit payments will be made by well-established payment agencies (microfinance**\n**institutions and/or the network of mobile phones operators) after an assessment of their**\n**capacity and needs.** Once the arrangements are assessed as satisfactory by IDA, contracts will\nbe signed between the CFS and such institutions to channel funds to beneficiaries. Funds will be\ntransmitted from the project’s DA to the payment agents who will in turn proceed to make\ntransfers to approved beneficiary households through their branches and points of sale. The\ncontrol processes for cash benefit payments to beneficiaries will be described in the POM and\nwill be developed further during the first year of implementation of the project, under\nComponent 2 (development of safety net systems).\n\n\n63. **The quarterly unaudited IFRs will be submitted to the World Bank within 45 days**\n**after the end of each quarter.** The Financing Agreements will require the submission of annual\naudited project financial statements within six months after year-end. Project financial statements\nwill be audited in accordance with international audit standards by an independent, experienced,\nand internationally recognized audit firm acceptable to the World Bank and recruited on a\ncompetitive basis based on terms of reference acceptable to the World Bank. The audited annual\nproject financial statements will be publicly disclosed according to the World Bank’s disclosure\npolicy.\n\n\n16", "output": {"entities": {"named_data": [], "descriptive_data": ["quarterly unaudited IFRs"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000028", "page": 27, "chunk": 1, "title": "Chad - Safety Nets Project", "pdf_url": "http://documents1.worldbank.org/curated/en/221251471265217930/pdf/Project-Appraisal-Document-PAD-disclosable-version-P156479-08122016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "quarterly unaudited IFRs", "label": "DESCRIPTIVE_DATA", "score": 0.5756779313087463, "start": 799, "end": 823, "probe_score": 0.3598, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Key Findings**\n<u>Paving pathways for inclusion: A global overview of refugee education data</u>\n\n\n**Figure 16:** Number of questionnaires with safety questions by safety indicators and target population\n\n\n**Peer violence and school infrastucture questions were the most commonly asked safety questions.**\n\n\n**Facilities** **Violence**\n\n\n\n0 100 200 300\n\n\nGeneral population\n\nRefugees\n\nOther\n\n\n\nInternet\n\n\nDrinking Water\n\n\nElectricity\n\n\nToilets\n\nHealth Services\n\n\nDistance\n\n\nHand Washing\n\n\nConstruction Materials\n\nAdapted\ninfrastructure/materials\n\nInfrastructure Damage\n\n\n\nPeer Violence\n\n\nSexual Violence\n\n\nCorporal Punishment\n\n\nAttacks on Schools\n\n\nMilitary Use of Facilities\n\n\nChild Recruitment\n\n\n0 100 200\n\n\n\n_Source_ : Based on the analysis of 1,109 questionnaires from 621 data sources.\n\n\n\n**Further, there were often wide discrepancies**\n**between how often and which safety indicators**\n**were captured depending on the target group.** The\nindicators on ‘peer violence’ (24%, n=220) were more\nprevalent in questionnaires targeted at the general\npopulation. ‘Peer violence’ was also where there was the\nlargest gap between refugee and general population\ntargeted questionnaires (22 percentage points in\nfavour of the general population). Comparatively, for\n‘sexual violence’, <sup>16</sup> only 4% of questionnaires (n=6)\ncontained these questions for refugees. The indicators\nof ‘attacks on schools’, ‘child recruitment’, <sup>17</sup> and ‘military\nuse of facilities’ were not found in those targeted at\nthe general population; compared to ‘construction\nmaterials’ and ‘electricity for refugees’. The subindicators that were less prevalent in questionnaires\nwere on ‘sexual violence and corporal punishment’\n(n=11, 1%) for the general population; compared to\n‘health services’, ‘toilets’, ‘child recruitment’, and ‘corporal\npunishment for refugees’ (n=1).\n\n\n*", "output": {"entities": {"named_data": [], "descriptive_data": ["refugee education data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000382", "page": 47, "chunk": 0, "title": "Paving pathways for inclusion: a global overview of refugee education data", "pdf_url": "https://reliefweb.int/attachments/31f00be7-0481-4224-80ce-378c049a02d4/Paving%20pathways%20for%20inclusion%20--%20a%20global%20overview%20of%20refugee%20education%20data.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "refugee education data", "label": "DESCRIPTIVE_DATA", "score": 0.7424919605255127, "start": 72, "end": 94, "probe_score": 0.9761, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**UNHCR recommends the Government of Bulgaria to:**\n\n\n- **Amend legislation to ensure effective access to rights** for individuals in the SDP and those\ngranted stateless status, particularly by removing legal barriers that restrict access to the\nprocedure.\n\n- **Review and consider lifting remaining reservations to the 1954 Convention**, especially those\nrelated to identity and travel documents in line with Bulgaria’s pledges made during the 2023\nGlobal Refugee Forum.\n\n- **Provide free legal assistance to stateless people and people at risk of statelessness**, supporting\ntheir access to nationality, civil status registration, and identity procedures and documents, and\nempowering them to claim their rights. This includes ensuring that free legal assistance is also\navailable at the administrative stage of the SDP.\n\n- **Amend primary and secondary legislation to ensure effective access to rights** for applicants for\nstatelessness status and those granted statelessness status, such as access to national health\ninsurance, employment and social assistance programs.\n\n- **Ensure the collection and recording of data on statelessness throughout the migration**\n**management and asylum process** to protect people against arbitrary detention, and ensure they\nare provided with appropriate assistance. The collection and recording of statelessness data will\nalso assist Bulgaria with their reporting obligations under the EU Pact on Migration and Asylum.\nConsider conducting a comprehensive mapping survey to improve the quantitative data and\nqualitative analysis of the situation of stateless population residing in Bulgaria and engage with\nthe ongoing UNHCR exercise on mapping statelessness in Bulgaria.\n\n- **Join the Global Alliance to End Statelessness**, a collaborative multistakeholder platform, which\nbrings together Governments, regional intergovernmental organizations, stateless-led and civil\nsociety organizations and other stakeholders to increase collective advocacy efforts, catalyse\npolitical commitments and accelerate action to secure permanent solutions to statelessness.\n\n\n**With respect to undocumented Roma communities:**\n\n\n- Provide resources and clear guidance to municipalities and cooperate with civil society", "output": {"entities": {"named_data": [], "descriptive_data": ["comprehensive mapping survey"], "vague_data": ["data on statelessness", "statelessness data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000842", "page": 6, "chunk": 0, "title": "Protection Brief - Bulgaria - Statelessness and the Right to Nationality (April 2025)", "pdf_url": "https://reliefweb.int/attachments/7c44c694-eb3d-5c63-bfd3-3052ccdac6cb/2025%20Brief%207%20-%20Statelessness%20EN.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on statelessness", "label": "VAGUE_DATA", "score": 0.6950112581253052, "start": 1119, "end": 1140, "probe_score": 0.1273, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "statelessness data", "label": "VAGUE_DATA", "score": 0.7305237650871277, "start": 1339, "end": 1357, "probe_score": 0.0724, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "comprehensive mapping survey", "label": "DESCRIPTIVE_DATA", "score": 0.7324808239936829, "start": 1482, "end": 1510, "probe_score": 0.0145, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " percent of women compared with 23 percent of men), and\nmore likely to be self-employed (80 percent compared to men’s 70 percent). <sup>3</sup> In this context, promoting ways for women\nto grow and expand their businesses is a good option to promote economic recovery. Micro, small, and medium\nenterprises (MSMEs) created within the past five years now generate over 50 percent of formal jobs, and household\nenterprises provide employment for another 3.1 million households. <sup>4</sup> Furthermore, women are particularly vulnerable\n\n\n1 The Uganda Bureau of Statistics (UBOS) has recently announced poverty rates based on the UNHS 2019/2020. The data for this survey was\ncollected in two periods with a break during the strictest lockdown period between March–June 2020. The first data collection period started in\nSeptember 2019 and ended in February 2020, then it resumed in July 2020 and ended in November 2020.\n2 Government of Uganda (2020), Third National Development Plan (NDP III).\n3 GoU 2018. National Labour Force Survey.\n4 World Bank. 2019. “Uganda Jobs Strategy for Inclusive Growth.”\n\n\nPage 7 of 77", "output": {"entities": {"named_data": ["UNHS 2019/2020", "National Labour Force Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 11, "chunk": 2, "title": "Uganda - Generating Growth Opportunities and Productivity for Women Enterprises Uganda Project", "pdf_url": "http://documents.worldbank.org/curated/en/527091655323259747/pdf/Uganda-Generating-Growth-Opportunities-and-Productivity-for-Women-Enterprises-Uganda-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHS 2019/2020", "label": "NAMED_DATA", "score": 0.8840423226356506, "start": 628, "end": 642, "probe_score": 0.9952, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "National Labour Force Survey", "label": "NAMED_DATA", "score": 0.8077062964439392, "start": 1003, "end": 1031, "probe_score": 0.9578, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "- MOSA SDCs are responsible for: (i) receiving household applications and\n\ninterface with applicant; (ii) data entry into program application; (iii) conducting\nhousehold visits; (iv) checking possible data errors in application forms against\nprovided official documents; (v) transmitting households’ application data to\nMOSA central unit; and (vi) handling appeals and claims received by households.\n\n     - With respect to the implementation arrangements of the e-card food voucher, the\n\nfollowing arrangements have been agreed upon: (i) WFP will conduct training for\nNPTP field work coordinators and social workers, including on assessments,\ndistribution, monitoring and household visits; (ii) NPTP will be responsible for\ndistribution and training of beneficiaries on the use of the e-card, as well as\nassessing and monitoring of food security indicators; (iii) WFP will provide the\n_Banque Libano-Française_ (BLF) with the necessary information/data based on\nthe NPTP database and operations for the production, activation and loading of ecards; (iv) WFP will in turn share reports from the bank on transactions and\nspending patterns; and (v) WFP and its identified partner(s) will continue to\nsupport NPTP through joint reporting and monitoring in the field. (For more\ndetails on the business processes and implementation, see Annex II).\n\n**Financial Management and Disbursements**\n\n\n_Financial Management_\n\n\n4. The Bank assessed the adequacy of the project FM arrangements proposed by the\nimplementing entity. The arrangements are considered acceptable if the entity budgeting,\naccounting, internal controls, funds flow, financial reporting, and auditing arrangements: (a) are\ncapable of correctly and completely recording all transactions and balances relating to the\nproject; (b) facilitate the preparation of regular, timely, and reliable financial statements; (c)\nsafeguard the project’s assets; and (d) are subject to auditing arrangements acceptable to the", "output": {"entities": {"named_data": ["NPTP database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000047", "page": 42, "chunk": 0, "title": "Lebanon - Emergency National Poverty Targeting Program Project", "pdf_url": "http://documents.worldbank.org/curated/en/810511467987899324/pdf/PAD1030-ENGLISH-P149242-PUBLIC-FINAL-LEB-ENPTP-English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NPTP database", "label": "NAMED_DATA", "score": 0.8667694926261902, "start": 967, "end": 980, "probe_score": 0.0011, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEnhancing Connectivity and Resilience in the Far North of Cameroon for Inclusiveness Project (P178207)\n\n\nimpacts. These roads require rehabilitation or reconstruction as well as maintenance in order to ensure access\nto economic and social opportunities and to facilitate the deployment of humanitarian aid in the Far North.\n\n\n30. **The RAI is estimated at 48 percent using 2020 data.** After the project implementation, the modified RAI—a 5\nkm buffer—is expected to increase from 80 to 95 percent. The population density is higher in Mora and Kousseri,\nwhich are the main urban centers in the Logone-Chari and Mayo-Sava divisions, concentrating more than 80\npercent of businesses and employment opportunities in the Far North region. Kousseri accounts for almost 60\npercent of businesses in the region and has a strategic position next to the Chad border; it is therefore attractive\nto businesses, the number of which has doubled since 2010. Consequently, Kousseri and Mora are subjected to\nan unprecedented flow of refugees looking for employment opportunities. Figure 3 (Section IV) shows the 30 -km buffer along the MDK road and the potential communal and regional road sections to be rehabilitated **.**\n\n\n31. **Under the closed CEMAC-TTFP, and the ongoing MTP projects, implementing socioeconomic infrastructures**\n**along the localities crossed by the roadworks has improved living conditions for the people.** The execution of\nrelated works has had a positive contribution in the local context. Along the Ngaoundéré–Garoua section, the\nCEMAC Project supported the construction of 33 classrooms, 1,800 meters of protective walls for existing\nschools, 22 toilets, and 25 water boreholes, and along the MDK road, it financed the construction of seven public\nschools, two health centers, and four water boreholes. These activities produced positive changes in: (i) the\ndynamics of the key", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["2020 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000003", "page": 22, "chunk": 0, "title": "Cameroon - Enhancing Connectivity and Resilience in the Far North of Cameroon for Inclusiveness Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099053123163547375/pdf/BOSIB0e7334a5d0570a3e40f8ae4d0c1266.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2020 data", "label": "VAGUE_DATA", "score": 0.8284079432487488, "start": 392, "end": 401, "probe_score": 0.9795, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Venezolanos en Chile, Colombia, Ecuador y Perú\n\n- una oportunidad para el desarrollo\n\n\n**Figura 6.1 Población por categoría de ocupación**\n\n\n\n6 Resultados del mercado laboral para\nvenezolanos y locales\n\n\n35\n\n\n\n0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%\n\n\n**Chile**\n\n\nLocal\n\n\n63.9% 6.3% 29.7%\n\n\nMigrante\n\n\n88.6% 4.4% 7.1%\n\n\n**Colombia**\n\n\nLocal\n\n\n63.8% 11.3% 24.9%\n\n\nMigrante\n\n\n62.7% 12.5% 24.8%\n\n\n**Ecuador**\n\n\nLocal\n\n\n77.6% 6.2% 16.3%\n\n\nMigrante\n\n\n89.8% 4.5% 5.7%\n\n\n**Perú**\n\n\nLocal\n\n\n72.2% 6.7% 21.2%\n\n\nMigrante\n\n\n81.2% 6.3% 12.6%\n\n\nEmpleado Desempleado Inactivo\n\n\nFuentes: Elaboración propia a partir de las siguientes encuestas. Chile: Encuesta de Migración (Banco Mundial, SERMIG y Centro UC 2022) y Encuesta Nacional de\nEmpleo (INE 2022). Colombia: Pulso de la Migración (DANE 2022) y Gran Encuesta Integrada de Hogares (DANE 2021). Ecuador: Encuesta a Personas en Movilidad\nHumana y en Comunidades Receptoras en Ecuador (INEC 2019) y Encuestas Telefónicas de Alta Frecuencia ALC (Banco Mundial 2022). Perú: Encuesta dirigida a\nla población venezolana que reside en el país (INEI 2022) y Encuesta Nacional de Hogares (INEI", "output": {"entities": {"named_data": ["Encuesta de Migración", "Encuesta Nacional de\nEmpleo", "Pulso de la Migración", "Gran Encuesta Integrada de Hogares", "Encuestas Telefónicas de Alta Frecuencia ALC"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001322", "page": 34, "chunk": 0, "title": "Venezolanos en Chile, Colombia, Ecuador y Perú - una oportunidad para el desarrollo", "pdf_url": "https://reliefweb.int/attachments/cbb1b9bf-3a48-463c-acb0-a587a681628a/P175780133597e0f11b72c1f7779efcaba1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Encuesta de Migración", "label": "NAMED_DATA", "score": 0.8932756781578064, "start": 641, "end": 662, "probe_score": 0.9983, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Encuesta Nacional de\nEmpleo", "label": "NAMED_DATA", "score": 0.9224890470504761, "start": 706, "end": 733, "probe_score": 0.9948, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Pulso de la Migración", "label": "NAMED_DATA", "score": 0.8596842288970947, "start": 756, "end": 777, "probe_score": 0.9962, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Gran Encuesta Integrada de Hogares", "label": "NAMED_DATA", "score": 0.8962626457214355, "start": 792, "end": 826, "probe_score": 0.9968, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Encuestas Telefónicas de Alta Frecuencia ALC", "label": "NAMED_DATA", "score": 0.920452356338501, "start": 942, "end": 986, "probe_score": 0.9998, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Quigley, P.** 2016. _Providing energy for cooking: an analysis of fuel options in refugee camps in_\n\n_Tanzania._ Geneva, Switzerland, United Nations High Commissioner for Refugees\n(UNHCR).\n\n\n**UNHCR.** 2017. _Tanzania refugee situation statistical report_ . 31 October 2017. United Nations\n\nHigh Commissioner for Refugees (UNHCR) (available at https://data2.unhcr.org/en/\ndocuments/download/60875).\n\n\n**United Republic of Tanzania.** 2015 _. National forest resources monitoring and assessment of_\n\n_Tanzania mainland._ Ministry of Natural Resources and Tourism, Government of Finland\n& FAO.\n\n\n**Verbesselt, J., Hyndman, R., Newnham, G. & Culvenor, D.** 2010. Detecting trend and seasonal\n\nchanges in satellite image time series _._ _Remote Sensing of Environment_, 114(1): 106–115.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001184", "page": 41, "chunk": 0, "title": "Cost–benefit analysis of forestry interventions for supplying woodfuel in a refugee situation in the United Republic of Tanzania, 2018", "pdf_url": "https://reliefweb.int/attachments/b59699e4-4e1a-3c19-95c3-59d679035874/CA0164EN.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nIntegrated Cash Transfer and Human Capital Project (P166220)\n\n\nprogram beneficiaries will also be oriented to the program by social and health workers in the targeted\nregions who will receive communication pamphlets.\n\n   - **Support to Community identification committees** . The project will support the organization of the\ncommunity identification committees that will develop the pre-lists of potential beneficiaries. Support to\ncommunity identification committees will include development of communication material and guidance\nnotes for adopting a community targeting approach. The project will also support additional technical\nassistance to households and community identification committees to further guide them through the\ncommunity targeting process.\n\n   - **Benefit Calculation and Payment Mechanism** . The project will support the analysis of payment levels\nusing the latest household survey data to ensure that benefits paid to households take into consideration\nnumber of household members and consumption poverty level. The project will also support the\nmodernization of the payment mechanism over the lifetime of the project. Specifically, ensuring that a\nmechanism is adopted to (i) robustly identify beneficiaries at point of payment; (ii) reconcile payments;\n(iii) ensuring payments are made regularly and on-time as described in the project manual.\n\n   - **Grievance and Redress.** The program will refine its GRM as part of the program structure. Specifically, the\nMinistry will allow for an ‘enrollment’ and ‘payments’ grievance period following the first payment in each\nof the program’s waves by selected prefecture. The grievance period will last for several weeks and will\nbe broadly advertised and communicated. Rejected candidates as well as beneficiaries with complaints\nrelated to payments will be able to file grievances. As a first step, the grievance system will include a filing\nprocess for grievances (based on a ticketing system). In the medium-term, the project will support\ndigitization of grievances to be managed by the centrally created MIS.\n\n   - **Recertification** . The project will also support the Ministry in adopting", "output": {"entities": {"named_data": [], "descriptive_data": ["household survey data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000154", "page": 41, "chunk": 0, "title": "Djibouti - Integrated Cash Transfer and Human Capital Project", "pdf_url": "http://documents1.worldbank.org/curated/en/893891558231269265/pdf/Djibouti-Integrated-Cash-Transfer-and-Human-Capital-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household survey data", "label": "DESCRIPTIVE_DATA", "score": 0.859646201133728, "start": 908, "end": 929, "probe_score": 0.0001, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019563", "page": 19, "chunk": 1, "title": "Kenya - Third and Fourth Education Projects", "pdf_url": "https://documents.worldbank.org/curated/en/884351468915079179/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7292463183403015, "start": 272, "end": 283, "probe_score": 0.8771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " overall.\nThese connections are important to bear in mind when designing government, development, and humanitarian\nsupport programs.\n\n\nEmployment continues to be closely associated with lower poverty rates, though ultimately, it’s the size of\nincome that is generated by working household members that makes the biggest difference. Considering that\nthe share of working-age refugees that are employed is nearing host population levels after rising further in\n2024, attention should now turn to wages. Data on the latter, which was derived from household level\nindicators, demonstrates that refugees on average make two-thirds of what the local population does per hour\nof work. Low wage premiums for higher education levels and the fact that some 60% of current refugee\nemployees have a background in an entirely different sector of the economy, suggest the presence of\nunderemployment and skills mismatching. This assertion is corroborated by nearly 35% of employed refugees\nin the region reporting few available jobs with adequate pay, lack of positions that match their skills, or issues\nwith getting their qualifications recognized. Moreover, almost the same percentage indicate lack of local\nlanguage knowledge to be a problem, a well-acknowledged barrier to skilled employment.\n\n\n**Based on the above findings it is recommended that:**\n\n\n- Governments, development and humanitarian actors take into account poverty levels when designing their\nsupport programs for Ukrainian refugees. The quality of day to day life, safety, and level of access to key\nservices are directly tied to household income.\n\n- Poverty measures account for differences in housing costs between refugees and host populations.\n\n- A special focus is placed on supporting refugee employment at their skill level, including transition from\ncurrent low-level jobs. The difference between refugee and local population wages could be an important\nmetric to monitor on an ongoing basis\n\n\n1. Compared to the <u>[2023 MSNA data](https://data.unhcr.org/en/documents/details/108068)</u>\n2.", "output": {"entities": {"named_data": ["2023 MSNA data"], "descriptive_data": ["household level\nindicators"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 2, "chunk": 1, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household level\nindicators", "label": "DESCRIPTIVE_DATA", "score": 0.8338796496391296, "start": 544, "end": 570, "probe_score": 0.1331, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2023 MSNA data", "label": "NAMED_DATA", "score": 0.7670543789863586, "start": 1982, "end": 1996, "probe_score": 0.6904, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "output": {"entities": {"named_data": [], "descriptive_data": ["household expenditure survey data", "data from the Household Survey"], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019153", "page": 38, "chunk": 1, "title": "Kenya - Telecommunications Project", "pdf_url": "https://documents.worldbank.org/curated/en/853991468285057419/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household expenditure survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8699104189872742, "start": 565, "end": 598, "probe_score": 0.7323, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.5808603167533875, "start": 870, "end": 881, "probe_score": 0.1461, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from the Household Survey", "label": "DESCRIPTIVE_DATA", "score": 0.5346028804779053, "start": 1978, "end": 2008, "probe_score": 0.1121, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad COVID-19 Strategic Preparedness and Response Project (P173894)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Monitoring & Evaluation Plan: PDO Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **<br>|**Definition/Description **<br>|**Frequency **|**Datasource **|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|Number of designated laboratories with<br>COVID-19 functioning diagnostic<br>equipment, test kits, and reagents per<br>MOH guidelines|Number of existing<br>laboratories with effective<br>capacity for testing COVID-<br>19 <br>|quarterly<br>|MOPH report<br>|<br>routine data<br>|<br>MOH<br>|\n|<br>Percentage of targeted acute healthcare<br>facilities with isolation capacity <br>|<br>Number of available<br>targeted acute healthcare<br>facilities with isolation<br>capacity for COVID-19<br>patients as a percentage of<br>all the target acute<br>healthcare facilities.|weekly<br>|COVID-19<br>report<br> <br>|routine data<br>|MOPH<br>|\n|Number of suspected cases of COVID-19<br>cases reported and investigated based on<br>national guidelines|<br>Number of suspected<br>effectively cases tested <br>|weekly<br>", "output": {"entities": {"named_data": ["MOPH report"], "descriptive_data": [], "vague_data": ["routine data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000039", "page": 36, "chunk": 0, "title": "Chad - COVID-19 Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/717781588366403375/pdf/Chad-COVID-19-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "MOPH report", "label": "NAMED_DATA", "score": 0.527076244354248, "start": 634, "end": 645, "probe_score": 0.8265, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "routine data", "label": "VAGUE_DATA", "score": 0.6240779757499695, "start": 654, "end": 666, "probe_score": 0.8431, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited (DTTL), its\nglobal network of member firms, and their related entities (collectively, the “Deloitte\norganization”). DTTL (also referred to as “Deloitte Global”) and each of its member\nfirms and related entities are legally separate and independent entities, which\ncannot obligate or bind each other in respect of third parties. DTTL and each DTTL\nmember firm and related entity is liable only for its own acts and omissions, and not\nthose of each other. DTTL does not provide services to clients. Please see\nwww.deloitte.com/about to learn more.\n\n\nDeloitte provides industry-leading audit and assurance, tax and legal, consulting,\nfinancial advisory, and risk advisory services to nearly 90% of the Fortune Global\n500® and thousands of private companies. Our people deliver measurable and\nlasting results that help reinforce public trust in capital markets, enable clients\nto transform and thrive, and lead the way toward a stronger economy, a more\nequitable society, and a sustainable world. Building on its 175-plus year history,\nDeloitte spans more than 150 countries and territories. Learn how Deloitte’s\napproximately 457,000 people worldwide make an impact that matters at\nwww.deloitte.com.\n\n\nThis communication contains general information only, and none of Deloitte Touche\nTohmatsu Limited (“DTTL”), its global network of member firms or their related\nentities (collectively, the “Deloitte organization”) is, by means of this communication,\nrendering professional advice or services. Before making any decision or taking any\naction that may affect your finances or your business, you should consult a qualified\nprofessional adviser.\n\n\nNo representations, warranties or undertakings (express or implied) are given as\nto the accuracy or completeness of the information in this communication, and\nnone of DTTL, its member firms, related entities, employees or agents", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 24, "chunk": 0, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nBeirut Housing Rehabilitation and Cultural and Creative Industries Recovery (P176577)\n\n\n**B. Results Monitoring and Evaluation Arrangements**\n\n\n**41.** **UN-Habitat will be responsible for results monitoring and will ensure the frequent monitoring of project**\n**implementation through regular follow-up with its local partners, site visits.** UN-Habitat will ensure that results\nmonitoring is responsive to the changing circumstances on the ground. It will assign a full time M&E officer to collect\nthe relevant data at baseline (i.e., at grant effectiveness) and over monitoring phases in coordination with the other\nproject management team experts. As part of the reporting process, UN-Habitat will provide updated geographic\ninformation system (GIS) maps of the project areas to help monitor progress of infrastructure-related activities. The\nlocal partners will prepare quarterly progress reports that will be reviewed by UN-Habitat and shared with the World\nBank. UN-Habitat will submit technical and financial progress reports on project activities to the World Bank every six\nmonths in accordance with an agreed template.\n\n\n**C. Sustainability**\n\n\n**42.** **The World Bank’s value proposition is to create an enabling environment for a sustainable program-wide**\n**approach to housing and recovery of the culture sector.** The project has been designed with sustainability in mind, so\nthat interventions, institutions, and individuals can continue to benefit after the conclusion of the project. Although\nthe project will intervene in a small portion of the identified reconstruction and recovery needs, it is scalable and can\nbe replicated and expanded throughout the post-explosion recovery of Beirut. The project has the potential to catalyze\nthe revitalization of the neighborhoods’ vibrancy, while establishing an integrated reconstruction framework to scale\nup operations once additional funding becomes available. Building rehabilitation under the BBB approach will ensure\nlong", "output": {"entities": {"named_data": [], "descriptive_data": ["geographic\ninformation system"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 24, "chunk": 0, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "geographic\ninformation system", "label": "DESCRIPTIVE_DATA", "score": 0.7327181696891785, "start": 737, "end": 766, "probe_score": 0.4413, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nRoads and Employment Project (P160223)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Indicator Name|Core|Unit of<br>Measure|Baseline|End Target|Frequency|Data Source/Methodology|Responsibility for<br>Data Collection|\n|---|---|---|---|---|---|---|---|---|\n|<br> <br>|maintenance involve the patching of potholes, sealing cracks, cleaning vegetation, fixing signing among others. They are usually undertaken by local small contractors on<br>newly rehabilitated roads. Roads in bad condition require rehabilitation and structural repairs first before routine maintenance is used/effective.|maintenance involve the patching of potholes, sealing cracks, cleaning vegetation, fixing signing among others. They are usually undertaken by local small contractors on<br>newly rehabilitated roads. Roads in bad condition require rehabilitation and structural repairs first before routine maintenance is used/effective.|maintenance involve the patching of potholes, sealing cracks, cleaning vegetation, fixing signing among others. They are usually undertaken by local small contractors on<br>newly rehabilitated roads. Roads in", "output": {"entities": {"named_data": ["Roads and Employment Project"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 49, "chunk": 0, "title": "Lebanon - Roads and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/210611486651815142/pdf/Lebanon-Roads-Employment-PAD-P160223-01262017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Roads and Employment Project", "label": "NAMED_DATA", "score": 0.610149085521698, "start": 19, "end": 47, "probe_score": 0.8334, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .\n\n28 En el marco del trabajo de campo se asistió a un encuentro organizado por algunas asociaciones venezolanas\nconjuntamente con diversas áreas de gobierno de la Ciudad Autónoma de Buenos Aires y de la Nación, al que concurrieron dos funcionarias del Ministerio de Educación a explicar el mecanismo de convalidación. De la actividad\nparticiparon alrededor de 100 asistentes. Cuando las funcionarias consultaron al público acerca de quiénes tenían\ntítulos universitarios, más del 80% levantó la mano.\n\n\n\n80\n\n\n\n81", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000762", "page": 40, "chunk": 3, "title": "Venezolanos/as en Argentina: un panorama dinámico (2014-2018)", "pdf_url": "https://reliefweb.int/attachments/6f461f17-ddd1-3579-b71a-b676758e4d1b/73587.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nDecentralization and Productive Intermediate Cities Support Project (P169332)\n\n\ncommunes of the three poorest _wilayas_, all three in Southern Mauritania. But those have proved to be\nstill insufficient to bridge the infrastructure gap and improve access to services to levels of Nouakchott\nand Nouhadibou.\n\n\n10. **Bridging the infrastructure gap in southern intermediate cities would enable them to play a**\n**significant role in job creation and economic development along the southern corridor.** The urbanization\nrate in southern regions is low, ranging from 23 percent to 29 percent at most. Over time, several cities\nhave grown to a population of 10,000 to 60,000 inhabitants. Among them, the most important are Kiffa,\nRosso, Kaedi, and Bassikounou. But despite the proven central roles of cities in facilitating access to\nmarkets for agriculture-led regions and offering better access to services than among rural localities, their\ngrowth has been relatively modest. In fact, most of the economic mobility has been attributed to\nNouakchott or Nouhadibou, especially driven by young male migrants. <sup>11</sup> [^11: World Bank. 2019. _Mauritania Country Economic Memorandum, Towards a More Diversified and Structured Urban Growth_ .] Additional investments for\nimproving domestic and regional connectivity, as well as access to electricity and water, have the potential\nto spur a new dynamic for private sector development and transform the existing intermediate cities into\nvibrant secondary cities that would provide better livelihoods and living standards and ultimately\ncontribute to poverty reduction.\n\n\n**_Access to Electricity, Key to Local Growth_**\n\n\n11. **Bridging the gap in access to electricity will have a catalytic effect on service delivery and private**\n**sector development.** The electricity access rate in Mauritania, at 38.8 percent, is low and comparable to\nthe average in Sub-Saharan Africa. In addition, significant disparities exist between urban and rural areas.\nWhile 76.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000083", "page": 15, "chunk": 0, "title": "Mauritania - Decentralization and Productive Cities Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/505861585879349315/pdf/Mauritania-Decentralization-and-Productive-Cities-Support-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "the norm, and registration of IDPs is undertaken in most cases by national or local authorities, <sup>68</sup> [^68: However, in many conflict-affected countries, governments lack the basic capacity to maintain Civil Registration and\nVital Statistics (CRVS) systems including the registration of births and deaths in non-displacement situations, let alone\nthe registration of IDPs displaced due to natural disasters or conflict.] civil society\ngroups or by individual organizations, particularly UNHCR and IOM, although the World Food Programme\n(WFP) might keep records of individuals and communities provided with food assistance.\n\nRegistration data for IDPs present an incomplete or misleading picture. While registration of IDPs can be\nhelpful in estimating the numbers of IDPs in camp and camp-like settings, such data presents an incomplete\npicture since in many contexts the majority of IDPs reside in dispersed settings where they are not\nregistered or counted (UNSD 2014). IDPs may deliberately avoid registration activities to avoid drawing\nattention to themselves due to security concerns and reluctance to provide personal information (especially\nwhen the authorities are perceived as contributing to the causes of displacement) or because they are not\nmotivated to register (e.g. registration does not confer a special legal status, no assistance is given or\nassistance is given in a discriminatory manner) (Brookings 2011). Additionally, IDPs might not be able to\nphysically reach the registration location because of insecurity, medical reasons, limited mobility, distance\nand cost. When national or international actors provide assistance, there may be an incentive for people to\nregister in camps even if they are staying elsewhere, or to register in multiple locations (Brookings 2011). <sup>69</sup> [^69: IOM has introduced biometric registration systems in South Sudan, Sudan, DRC and Nigeria to circumvent these\nproblems.]\nFurthermore, registration data provide only a snapshot of the stock of IDPs at a particular point in time and\nmay be out of date if registers are not maintained regularly.\n\nRegistration methodologies can vary across displacement", "output": {"entities": {"named_data": [], "descriptive_data": ["Registration data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006980", "page": 35, "chunk": 0, "title": "wps7985", "pdf_url": "https://local/prwp/wps7985.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Registration data", "label": "DESCRIPTIVE_DATA", "score": 0.5875410437583923, "start": 633, "end": 650, "probe_score": 0.7652, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 1\nPage 2 of 3\n\n\n**Project Development** **Outcome / Impact** **Project reports:** **(from Objective to Purpose'**\n**Objective:** **Indicators:**\nExpand access to basic Increased number of school Project Reports. It is assumed that\neducation. places. Government's current fiscal\nsituation will be resolved\n\n(salary payment to civil\nservants and teachers).\nEnrollment increases in MOE reports. Expansion of facilities and\nprimary schools from 35,000 quality will contribute to\nto 80,000 increased enrollment\nincluding among girls.\nIncreased availability of It is assumed that the\ntextbooks. Government maintains\ndouble-shifting.\n\n\nTrained primary school head Headteachers have autonomy\nteachers. and authority in managing the\nschools.\nBetter trained contractual Contractual teachers are\nteachers recruited early enough before\nthe school year to allow time\nfor training.\n\n\n**Output from each** **Output Indicators:** **Project reports:** **(from Outputs to Objective)**\n**Component:**\nIncreased number of school 226 classrooms will be built Monthly disbursement Availability of school places\nplaces. increasing capacity by over summary. will increase enrollment.\n20,000 based on double\nshifting.\nProvide textbooks. Numbers of textbooks per Semi-annual Provision of textbooks will\npupil increases. supervision reports. improve learning.\nTrained primary school head- Primary school head-teachers Annual audit reports; Better trained head-teachers\nteachers. trained and Guidebook for site visits. will improve school\nschool management prepared efficiency.\nand distributed.", "output": {"entities": {"named_data": ["MOE reports"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019683", "page": 30, "chunk": 0, "title": "Uganda - Nakivubo Channel Rehabilitation Project - environmental assessment", "pdf_url": "https://documents.worldbank.org/curated/en/890931468760215925/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "MOE reports", "label": "NAMED_DATA", "score": 0.6933835744857788, "start": 385, "end": 396, "probe_score": 0.8075, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "5. Cross Sectors\n\n\n**a.** **National data collection system:** Currently collected socio economic data are not capturing the\n\nstatus of those surveyed, whether they are refugees, asylum-seekers or IDPs. Capturing status-based\ninformation is critical to better inform policies, track progress and impact over time, help shape and\ntarget interventions and prioritize resources. Data segregation providing insights about refugees,\nasylum seekers and internally displaced was not available in past poverty assessments and national\nhousehold surveys.\n**b.** **Access to education and connected learning:** Given that a significant number of refugees come from\n\nNigeria, where they are mainly educated in English, the national curriculum taught in French may not\nsuit their age group. Enabling distance learning through modern technology tools is vital for refugee\nyouth to acquire skills, both for employment and language proficiency in societal integration.\n**c.** **Social protection:** Vulnerable refugees are not specifically targeted in cash or in-kind via national safety\n\nnets beyond the World Bank financed PARCA project closing in September 2023. Systematic inclusion\nwould decrease their vulnerability and facilitate their local integration.\n\n\n16 R E F U G E E P O L I C Y R E V I E W F R A M E W O R K > **N I G E R**", "output": {"entities": {"named_data": [], "descriptive_data": ["national\nhousehold surveys"], "vague_data": ["socio economic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001471", "page": 15, "chunk": 0, "title": "Niger: Refugee Policy Review Framework Country Summary as at 30 June 2023 (Update of Summary as at 30 June 2023)", "pdf_url": "https://reliefweb.int/attachments/e5194222-6740-4475-8065-5465cd3d0666/Niger%20RPRF%20Country%20Update%202020-23.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "socio economic data", "label": "VAGUE_DATA", "score": 0.7757520079612732, "start": 83, "end": 102, "probe_score": 0.5632, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "national\nhousehold surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8637376427650452, "start": 518, "end": 544, "probe_score": 0.4795, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 4 or more ANC<br>visits. Denominator: Total number of expected live births during the reporting period within the host community of<br>Garissa and Turkana<br>|\n|Frequency <br>|Every six months <br>|\n|Data source <br>|KHIS|\n|Methodology for Data<br>Collection <br>|Routine HMIS data collection|\n|Responsibility for Data<br>Collection <br>|MoH <br>|\n|**Percentage of refugee pregnant women attending 4 or more ANC visits in Garissa and Turkana (Percentage)**<br>|**Percentage of refugee pregnant women attending 4 or more ANC visits in Garissa and Turkana (Percentage)**<br>|\n|Description<br>|Numerator: Number of refugee pregnant women attending 4 or more ANC visits.<br>Denominator: Total number of expected live births during the reporting period within the refugee community of Garissa<br>and Turkana<br>|\n|Frequency|Every six months <br>|\n|Data source<br>|UNHCR reports|\n|Methodology for Data<br>Collection<br>|Routine UNHCR data collection|\n|Responsibility for Data<br>Collection<br>|MoH <br>|\n|**Proportion of Children Under 5 with diarrhea treated with Zinc/ORS Co-Pack (Percentage) **|**Proportion of Children Under 5 with diarrhea treated with Zinc/ORS Co-Pack (Percentage) **|\n\n\nFeb 21, 2024 Page 31 of 43", "output": {"entities": {"named_data": ["KHIS", "HMIS data collection"], "descriptive_data": ["UNHCR reports"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000000", "page": 36, "chunk": 2, "title": "Kenya - Building Resilient and Responsive Health Systems Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099022324094562763/pdf/BOSIB1554c314c0a2187c019d7e85bc2a91.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "KHIS", "label": "NAMED_DATA", "score": 0.6442481279373169, "start": 218, "end": 222, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "HMIS data collection", "label": "NAMED_DATA", "score": 0.5894606709480286, "start": 273, "end": 293, "probe_score": 0.2047, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "UNHCR reports", "label": "DESCRIPTIVE_DATA", "score": 0.6351935267448425, "start": 860, "end": 873, "probe_score": 0.0992, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Advocacy, Protection, and Legal Assistance to IDPs vpl.com.ua\n##### 26 27\n\n\n\nbeing reconstructed into a dormitory. Since\nthe Restructuring Credit (KfW) covers only\npart of the cost of reconstruction, there is\na need to raise funds from the local budget.\nZolochiv Amalgamated Territorial Community\n\nhas no funds for the dormitory’s equipment.\nRepairs have been completed, but for now\nit is not possible to buy the necessary furniture and equipment. All facilities are located\nnext to grocery stores, hospitals, ambulances,\npublic transport stops. The common settlement requirements are impoverishment, but\n\n\n**_Kharkiv oblast, Zolochiv, Filatova, 20 str._**\n\n\nUnder the **Affordable Housing** Program in\nKharkiv and Kharkiv region only the Oleksandrivskii housing complex has been put into\nservice, other facilities (Levada, Arkhitektoriv,\nMeredian, Mira‑4, Odeskyi, Raiduzhnyi‑1) are\nstill under final finishing works, commissioning\nis scheduled by the end of 2018. Employees\nof the Kharkiv Regional Department of Derzhmolodshytlo refused to provide information\non the number of apartments received by\nthe program, arguing that such information is\nconfidential. There are grocery stores, public\ntransport stops, pre-school educational institutions close to all housing complexes.\n\n\n\n**_Kharkiv oblast, Lozova, Sosiury, 17 str._**\n\n\nin some settlements, there are additional ones:\nIn Bohodukhiv there was a prerequisite of employment, In Krasnohrad the preference was\ngiven to large families, doctors and teachers,\nand IDPs who were settled and working and\nliving in the local community for about 3 years.\nThe list of IDPs claiming residence has been\n\ndrawn up for some rooms in the Kharkiv oblast.\nThus, in Zolochiv and Krasnohrad the queue\n\nis already closed. In", "output": {"entities": {"named_data": [], "descriptive_data": ["list of IDPs claiming residence"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000706", "page": 13, "chunk": 0, "title": "Analytical Review of Regional Housing Programs for IDPs, June - August 2018 [EN/UK]", "pdf_url": "https://reliefweb.int/attachments/6776f5bb-7e2f-33d5-9f5c-b45157644f93/idps_housing_programs_overview_eng.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "list of IDPs claiming residence", "label": "DESCRIPTIVE_DATA", "score": 0.8774189949035645, "start": 1609, "end": 1640, "probe_score": 0.0367, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**-6-**\n\n\nthe Association **by** electronic means. In full recognition that the Association shall rely upon\nsuch representations and warranties, including without limitation, the representations and\nwarranties contained in the _Terms and Conditions of Use of Secure Identification Credentials in_\n_connection with_ _Use of Electronic Means to Process Applications and Supporting Documentation_\n(\"Terms and Conditions of Use of **SIDC\"),** the Recipient represents and warrants to the\nAssociation that it will cause such persons to abide **by** those terms and conditions.]\n\n\nThis Authorization replaces and supersedes any Authorization currently in the\nAssociation records with respect to this Agreement.\n\n\n[Name], [position] Specimen Signature:\n\n\n[Name], [position] Specimen Signature:\n\n\n[Name], [position] Specimen Signature:\n\n\nYours truly,\n\n\n/ signed /\n\n\n[Position]", "output": {"entities": {"named_data": [], "descriptive_data": ["Association records"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019935", "page": 5, "chunk": 0, "title": "Official Documents- Disbursement Letter for Credit 5386-ET (Closing Package)", "pdf_url": "https://documents.worldbank.org/curated/en/908281468272985081/pdf/RAD921174500.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Association records", "label": "DESCRIPTIVE_DATA", "score": 0.6692295074462891, "start": 653, "end": 672, "probe_score": 0.0007, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "mean flood intensity from the Global Flood Monitoring System (GFMS) data set (Merz et al., 2007),\n\n\nelevation, and distance to river. The flood shock measure takes a value of one where the flood index is\n\n\nmore than 30 percent above the average flood index value. The drought measure is based on the\n\n\ndifference between the National Oceanic and Atmospheric Administration (NOAA) African Rainfall\n\n\nClimatology version 2 (ARC2) flowering period rainfall in the current period versus the historical average.\n\n\nWe use a dichotomous variable that takes a value of one when current period rainfall is at least 30 percent\n\n\nbelow the historical mean and is otherwise equal to zero. <sup>8</sup> [^8: McCarthy et al. (2021) use a slightly different measure for drought. That measure is semi-continuous, taking the\nabsolute value of the percent difference between current period rainfall and the historical mean when more than] Finally, we control for climate conditions by\n\n\nincluding historical flowering period rainfall mean and coefficient of variation, as well as standard\n\n\nproduction function variables. As shown in Online Appendix 1, the flood and drought shocks have\n\n\nsignificant negative impacts on plot-level maize yields.\n\n\n**3.3.** **Aid Distribution and Explanatory Factors**\n\n\nFor aid distribution, we use monthly data on the number of households who received food and\n\n\ncash aid in TA’s where aid was distributed. <sup>9</sup> [^9: We have data on amounts of cash distributed and quantities and caloric equivalent of food aid distributed, but we\nchose to use number of households receiving aid since this variable does not require us to create a variable that has\nthe same unit across different types of aid.] The vast majority of aid was distributed through a consortium\n\n\nof international and local NGOs, coordinated by the Ministry of Disaster Management Affairs and the WFP\n\n\n(Babu et al., 2018). The monthly data are aggregated, starting with the month that distribution began\n\n\nfollowing the end", "output": {"entities": {"named_data": ["Global Flood Monitoring System", "African Rainfall\n\n\nClimatology version 2"], "descriptive_data": [], "vague_data": ["monthly data", "monthly data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002018", "page": 14, "chunk": 0, "title": "recurrent climatic shocks and humanitarian aid impacts on livelihood outcomes in malawi", "pdf_url": "https://local/prwp/recurrent-climatic-shocks-and-humanitarian-aid-impacts-on-livelihood-outcomes-in-malawi.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Global Flood Monitoring System", "label": "NAMED_DATA", "score": 0.7717254161834717, "start": 30, "end": 60, "probe_score": 0.9115, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "African Rainfall\n\n\nClimatology version 2", "label": "NAMED_DATA", "score": 0.8309987187385559, "start": 380, "end": 420, "probe_score": 0.98, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "monthly data", "label": "VAGUE_DATA", "score": 0.6992287635803223, "start": 1315, "end": 1327, "probe_score": 0.843, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "monthly data", "label": "VAGUE_DATA", "score": 0.5635576248168945, "start": 1915, "end": 1927, "probe_score": 0.7337, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### **11. Remote Sensing and GIS Data and Analysis to Enhance** **Humanitarian Shelter Programming**\n\n**11.1.** **Overview**\nExtensive remote sensing work has been done on environmental issues in Syria. This work\nincludes <u>[Amidst the debris - a desktop study on the environmental and public health impact](https://www.paxforpeace.nl/publications/all-publications/amidst-the-debris)</u>\n<u>[of Syria’s conflict, and](https://www.paxforpeace.nl/publications/all-publications/amidst-the-debris)</u> <u>[Scorched earth and charred lives - human health and environmental](https://www.paxforpeace.nl/publications/all-publications/scorched-earth-and-charred-lives)</u>\n<u>[risks of civilian-operated makeshift oil refineries in Syria.](https://www.paxforpeace.nl/publications/all-publications/scorched-earth-and-charred-lives)</u>\n\nThe NW Syria Shelter Cluster does not currently use remote sensing or GIS capacities for\nassessments or assistance programming. The Cluster is undertaking an IDP site verification\nprocess with local authorities. Once this process has been completed a more formal use of\nremote sensing and GIS to map and monitor environmental and other aspects of IDP sites is\npossible.\n\n\n**11.2.** **Suggested Further Action**\nWhen the IDP site verification process has been completed, the Cluster should cooperate\nwith other stakeholders to establish a GIS database of sites to track changes to the sites and\nenvironmental impacts which may occur. The database will also be useful in tracking the\npotential or actual location", "output": {"entities": {"named_data": [], "descriptive_data": ["GIS database of sites"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000745", "page": 21, "chunk": 0, "title": "NW Syria: Environmental Country Profile for Shelter and Settlements - 1st edition, September 2023", "pdf_url": "https://reliefweb.int/attachments/6d95b13e-53c0-414a-ae18-2bea74d5cc11/NW%20Syria%20Environmental%20Shelter%20Country%20Profile_0.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "GIS database of sites", "label": "DESCRIPTIVE_DATA", "score": 0.8854131698608398, "start": 1366, "end": 1387, "probe_score": 0.0819, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "</sup>\n\n\n\nversions of the Global Procurement <sup>Plan and the following year's</sup> <sup>annual</sup> <sup>procurement</sup> <sup>plan.</sup> <sup>Participating</sup>\n\n\n\nService Providers will be required <sup>to</sup> <sup>include</sup> <sup>procurement</sup> <sup>plans in</sup> <sup>their subproject proposals.</sup> <sup>The</sup>\n\n\n\ntechnical team reviewing community <sup>subproject proposals must ensure adequacy of a</sup> <sup>sub-project</sup>\n\n\n\nprocurement plan before the <sup>proposal</sup> <sup>is</sup> <sup>approved.</sup> <sup>Each</sup> <sup>quarter,</sup> <sup>NaCSA will</sup> <sup>submit</sup> <sup>to IDA a</sup>\n\n\n\nprocurement monitoring report <sup>as part of the Financial</sup> <sup>Management Report (FMR),</sup> <sup>to show how</sup> <sup>each</sup>\n\n\n\ncontract on the procurement <sup>plan</sup> <sup>has progressed.</sup> <sup>The POM</sup> <sup>will include</sup> <sup>sample formats</sup> <sup", "output": {"entities": {"named_data": [], "descriptive_data": ["procurement monitoring report"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000117", "page": 45, "chunk": 6, "title": "Sierra Leone - Rehabilitation of Basic Education Project", "pdf_url": "http://documents1.worldbank.org/curated/en/680761468763817221/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "procurement monitoring report", "label": "DESCRIPTIVE_DATA", "score": 0.8535922765731812, "start": 641, "end": 670, "probe_score": 0.0289, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nKenya Water, Sanitation, and Hygiene Program (P179012)\n\n\n**Monitoring & Evaluation Plan: Intermediate Results Indicators by Results Areas**\n\n|Increasing sustainable access to improved water services for climate-vulnerable rural areas|Col2|\n|---|---|\n|**County water and sanitation strategy and investment plans approved (Number) **|**County water and sanitation strategy and investment plans approved (Number) **|\n|Description|The county government executive approved 5-year strategy and investment plan and the implementation roadmap will<br>guide both public and private investments in water supply and sanitation services toward achieving the universal<br>access target by 2030.|\n|Frequency|Annual measurement|\n|Data source|County Government Water Department M&E records|\n|Methodology for Data<br>Collection|Qualitative inspections and quantitative data collection using M&E protocols defined in the POM|\n|Responsibility for Data<br>Collection|County Government Water Department|\n|**Rural water supply schemes constructed under the program in climate-vulnerable rural areas (Number) **|**Rural water supply schemes constructed under the program in climate-vulnerable rural areas (Number) **|\n|Description|This indicator measures the number of rural water schemes constructed by each county to supply improved water to<br>households.|\n|Frequency|Annual measurement|\n|Data source|County Government Water Department M&E records|\n|Methodology for Data<br>Collection|Qualitative inspections and quantitative data collection using M&E protocols defined in the POM|\n|Responsibility for Data<br>Collection|County Government Water Department|\n|||\n|**Rural water supply schemes constructed under the program that adopt a WASH plus approach (provide water for multiple productive uses**<br>**beyond doemstic portable", "output": {"entities": {"named_data": ["County Government Water Department M&E records"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000190", "page": 47, "chunk": 0, "title": "Kenya - Water, Sanitation, and Hygiene Program", "pdf_url": "https://documents1.worldbank.org/curated/en/099120123140034670/pdf/BOSIB-9a6accb6-73d1-4bd1-8307-d41a339a51ab.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "County Government Water Department M&E records", "label": "NAMED_DATA", "score": 0.7756080031394958, "start": 746, "end": 792, "probe_score": 0.778, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nLebanon Health Resilience Project (P163476)\n\n\nwiden income inequality among Lebanese. In this challenging environment, GDP growth in Lebanon is\nestimated to have decelerated to 1.3 percent in 2015 from an estimated 1.8 percent in 2014, despite\ncontinued Central Bank stimulus, an improved security stance, and lower oil prices. Public finances\nremain structurally weak, and they are in urgent need of reforms. Public debt is projected to continue to\nrise (148 percent of GDP by end-2017) because of low growth and the relatively high cost of debt\nfinancing. <sup>27</sup> [^27: . IMF Lebanon Country Report No 17/19, January 2017.]\n\n61. **It is expected that this project will be financially sustainable, but close monitoring of the**\n**macroeconomic and budget situation will be needed.** The proposed project investment, US$120 million\nover a five-year period, accounts for 5 percent of the annual government expenditure on health. <sup>28</sup> [^28: Based on World Bank Development Indicators (2014).]\n\n**B. Technical**\n\n\n62. **The technical design of the project is based on the ongoing EPHRP in PHC, with an additional**\n**focus on the hospital sector.** The interventions are designed not just to meet urgent health care needs,\nbut also to focus on governance, accountability, management, and expansion of essential health care\nservices to the poor. The pro-poor interventions supported under this project are well-known and have\nbeen tested in numerous countries around the world. In addition to reflecting the priority needs\nidentified in the national health plan, the investment rationale is supported by a large body of global\nevidence, including recent analyses of the benefits of prioritizing PHC to reach the poor, and connecting\nsectors and systems to achieve health results. The particular focus on strengthening health care services\nat the lowest level, addressing both demand-", "output": {"entities": {"named_data": ["World Bank Development Indicators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000032", "page": 33, "chunk": 0, "title": "Lebanon - Health Resilience Project", "pdf_url": "http://documents.worldbank.org/curated/en/616901498701694043/pdf/Lebanon-Health-PAD-PAD2358-06152017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Bank Development Indicators", "label": "NAMED_DATA", "score": 0.9162845611572266, "start": 982, "end": 1015, "probe_score": 0.9957, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">goods?<br>Move to a poorer quality shelter?<br>Skip paying rent / debt repayments to meet other needs?<br>Take out new loans or borrowed money?<br>Reduce expenditure hygiene items, water, baby items, health, or<br>education in order to meet household food needs?<br>Total<br>Syrians<br>Other nationalities|\n\n\nCompared to the previous year, there seems to be a slight decrease in 2023 in the overall adoption of negative\ncoping strategies where 2022 year-end PDM survey show that 84 per cent of survey respondents reported resorting\nto at least one coping strategy i.e. five percent points higher than 2023. Also, a marked decrease is noticed in some\ncoping strategies particularly reducing expenditures on various basic household needs (60 per cent in 2023 Vs. 72\nper cent in 2022), skipping rent payment/debt repayment (17 per cent in 2023 vs. 35 per cent in 2022), and asking\nfor money from strangers (6 per cent in 2023 vs. 19 per cent in 2022). This decrease needs further monitoring in the\nupcoming surveys to observe whether it will be sustained over a period of time.\n\n\nAccording to the severity of their implications negative coping strategies are further classified into stress, crisis,\nand emergency coping strategies. Stress strategies reduce the household’s ability to deal with future shocks.\nSkipping rent payment and debt repayment, as well as taking out new loans are examples of stress coping\n\n\n8", "output": {"entities": {"named_data": ["PDM survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001395", "page": 15, "chunk": 2, "title": "Year-End Post-Distribution Monitoring Report: UNHCR’s Multi-Purpose Cash Assistance to Refugees in Egypt - 2023", "pdf_url": "https://reliefweb.int/attachments/d816538a-4c06-4002-b918-3b085c4b1551/MPCA%20PDM%20-%20End%20Year%202023%20-%20Final%20Report%20-%2019%20April%202024-UNHCR.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PDM survey", "label": "NAMED_DATA", "score": 0.6933814287185669, "start": 459, "end": 469, "probe_score": 0.9599, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " **FIGURE 17:** Working-age population\n\n80\n\n\n\n60\n\n\n40\n\n\n20\n\n\n0\n\n\n\nWorking age Younger than working age Older than working age\n\n\nKalobeyei National Turkana County\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n**Source:** Kalobeyei (2018); KIHBS (2015/16).\n\n\n **FIGURE 18:** Labor force status\n\n\n\n100\n\n\n80\n\n\n60\n\n\n40\n\n\n20\n\n\n0\n\n\n\nKalobeyei National Turkana County\n\n\nOutside labor force Unemployed Employed Potential labor force\n\n\n\n\n\n\n\n**Source:** Kalobeyei (2018); KIHBS (2015/16).\n\n\nby the disproportionate number of households that are\n­single-headed female households are explored below.\n\n\n**45. Among those OLF, 6 percent can be described as**\n\n**“potential labor force,” or those who were available to work**\n**but not actively seeking mainly due to lack of jobs, discour-**\n**agement, and skills mismatch.** <sup>67</sup> Seven in 10 refugees who\ndid not search for work cited lack of jobs, discouragement,\nand skills mismatches (Figure 19). Family responsibilities\n(17 percent), and studies (3 percent) were other common\nreasons (Figure 19). This is similar to what is observed for\nother refugee populations in Ethiopia, <sup>68</sup> family reasons\n(22 percent), and nonexistent/poor employment opportunities (17 percent) were some of the most commonly referenced\n\n\n67 \u0007This includes those actively seeking but not available, but this is\nnegligible in the refugee population.\n68 \u0007Pape and Sharma. 2019. Informing Durable Solutions for Internal\nDisplacement In Nigeria, Somalia, South Sudan, and Sudan.\n\n\n\nreasons for not working. Considering that most of the refugee\npopulation is young, and will soon be of working age, it is\nextremely important to generate employment opportunities\nand skills building programs that", "output": {"entities": {"named_data": ["KIHBS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000641", "page": 30, "chunk": 0, "title": "Understanding the Socioeconomic Conditions of Refugees in Kenya | Volume A: Kalobeyei Settlement - Results from the 2018 Kalobeyei Socioeconomic Survey", "pdf_url": "https://reliefweb.int/attachments/5db37855-7edd-3a88-a03c-464668a5c042/6034c5124.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "KIHBS", "label": "NAMED_DATA", "score": 0.5266355872154236, "start": 210, "end": 215, "probe_score": 0.999, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Remittances offer one medium for risk sharing between households. Table 1 provides\n\na summary of the average remittance flows over the past 12 months in 2010 between\n\nthe migrant households and households living in or near their baseline villages. While\n\nnon-migrant households were net receivers of remittances, Table 1 shows that\n\ntransfers flow both ways. This could lead one to think – mistakenly as the analysis\n\nbelow reveals – that these are relationships of reciprocal risk sharing. The data in\n\nTable 1 are self-reported and it is interesting to note that migrants claim to send more\n\nhome than non-migrants acknowledge. A similar discrepancy does not exist in\n\nmigrant-migrant or stayer-stayer dyads <sup>14</sup> [^14: By dyad we refer to a pair of households.] .\n\n\n_[Table 1 here]_\n\n\nTable 2 provides an overview of the reasons for leaving the baseline village. More\n\nthan one-third of the female respondents but none of the male respondents cited\n\nmarriage as the reason for migrating, which is what one would expect in a culture\n\nwith patrilocal marriages. Less than 15 percent of the female respondents reported\n\nthat they left because of work. In contrast, almost 45 percent of the male migrants\n\nreported to have moved because they had found work or went looking for work.\n\n\n_[Table 2 here]_\n\n\nThe consumption data originate from extensive food and non-food consumption\n\nmodules in the survey, carefully designed to maintain comparability across survey\n\nrounds and controlling for seasonality. The aggregates are temporally and spatially\n\ndeflated using data from a price questionnaire included in the survey. Consumption is\n\nexpressed in annual per capita terms using 2010 Tanzanian shillings. <sup>15</sup> [^15: Using adult equivalent units as the denominator instead of household size produces almost\nidentical results across all specifications.]\n\n\nTable 3 provides the summary of the consumption and poverty developments of the\n\npanel respondents with respect to their 2010 location. On average, consumption levels\n\nin the sample almost doubled over 19 years. Individuals who stayed in their\n\ncommunity saw their consumption increase by more than", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["consumption data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005580", "page": 12, "chunk": 0, "title": "wps6429", "pdf_url": "https://local/prwp/wps6429.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "consumption data", "label": "VAGUE_DATA", "score": 0.7240258455276489, "start": 1315, "end": 1331, "probe_score": 0.9479, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### PROTECTION ANALYSIS UPDATE – Q2 4. RESPONSE\n\n#### 4.1 Operational context including access issues\n\n_Figure 6: Geographical distribution of access constraints Q1 vs Q2_\n\n\n**<u>Access</u>**\n\n\nThe access environment for humanitarians in Afghanistan remained challenging in Q2 2021, as the country's\noverall security and political situation have continued to deteriorate systematically throughout the second quarter\nof 2021, resulting in at least 593 access constraints compared to 508 recorded by the Humanitarian Access Group\n(HAG) in Q1 2021.\n\n\nThe overall increase in the number of access constraints was predominantly attributed to kinetic activity and\nmilitary operations. At the same time, interference attempts, levy requests and violence/threats against\nhumanitarians decreased this quarter. It is unlikely that this is the result of a change in behaviour of the parties to\nthe conflict but instead attributed to a limited humanitarian footprint during the Q2, which led to less exposure\nof humanitarian actors. It is important to note that this decrease in humanitarian presence comes during the time\nwhen the humanitarian needs of the Afghan population are increasing, with the impact of conflict further\naggravated by the Covid-19 pandemic causing delays in the conduct of joint assessments to verify displaced\nfamilies. Of note, access issues are compounded by lack of infrastructure, particularly in remote, rural areas,\ndelaying further the provision of protection assistance to populations in need.\n\n\n23", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000210", "page": 23, "chunk": 0, "title": "Afghanistan: Protection Analysis Update 2021 - QUARTER 2", "pdf_url": "https://reliefweb.int/attachments/161c6015-b7f8-3159-9361-72ffae217a11/protection_analysis_update_-_q2.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "hcr.org/statistics/populationdatabase)</u>\n\n18 As demographic breakdown was not available for 2013 at the time of writing, this percentage\nbreakdown has been extrapolated from 2012 data. UNHCR, _Statistical Yearbook 2012_, “Table 14:\nDemographic composition of refugees and people in refugee-like situations, end 2012”, p126.\n\n19 Member states of the Council of Europe, and most other industrialized states formally grant the\nright to work, along with many other social and economic rights to recognized refugees. As well as\nEuropean states, Australia, Canada, New Zealand, and the USA grant refugees the right to work.\nThe rights granted to asylum seekers vary considerably. Other countries recognizing in legislation\nthe right to work of refugees include Burundi, Cameroon, Democratic Republic of Congo, Gabon,\nGuinea, Mali, Mauritania, Republic of South Africa, Rwanda, Senegal, Uganda, Argentina, Brazil,\nPeru, Ecuador, Mexico, Bolivia, Paraguay, Chile, Panama, Venezuela, Costa Rica, Uruguay, Israel.\n\n11", "output": {"entities": {"named_data": ["populationdatabase"], "descriptive_data": [], "vague_data": ["2012 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001036", "page": 10, "chunk": 3, "title": "Which side are you on?: Discussion paper on UNHCR’s policy and practice of incentive payments to refugees", "pdf_url": "https://reliefweb.int/attachments/9df00398-8f8d-31ef-be27-5f53527b95af/5491577c9.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "populationdatabase", "label": "NAMED_DATA", "score": 0.5926913022994995, "start": 19, "end": 37, "probe_score": 0.9814, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "2012 data", "label": "VAGUE_DATA", "score": 0.6348171234130859, "start": 176, "end": 185, "probe_score": 0.8868, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Policy Research Working Paper 10884\n\n#### **Abstract**\n\nThis paper examines the impact of refugee camp hosting on\n\nlocal communities, specifically the Rohingya crisis in Cox’s\nBazar, Bangladesh. It uses remote sensing measurements\nand panel data to compare areas and individuals at varying\ndistances before and after the Rohingya arrived. The results\nhighlight the complex dynamics of areas that host displaced\npopulations. The paper finds that when the proximity of a\ngrid to the refugee camps increases by 30 km (18.6 miles),\nnight light density rises by 1.7 percent and deforestation\nexpands by 0.02 percent. Land use results align with these\n\n\n\nfindings, showing a decline in dense-open forest and an\nincrease in land covered by grass and crops. The analysis of\nindividual-level data suggests that the Rohingya’s presence\nmanifests in higher job formality, better access to aid, and\nmore food consumption—all largely attributable to the\nactivities of humanitarian organizations. However, their\npresence is also associated with heightened safety concerns\nand a higher prevalence of viral diseases such as diarrhea,\nfever, and cough.\n\n\n\nThis paper is a product of the Development Research Group, Development Economics. It is part of a larger effort by the\nWorld Bank to provide open access to its research and make a contribution to development policy discussions around\n\nthe world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors\n[may be contacted at sandrarozo@worldbank.org. A verified reproducibility package for this paper is available at http://](http://reproducibility.worldbank.org)\n[reproducibility.worldbank.org, click](http://reproducibility.worldbank.org) **[here](https://reproducibility.worldbank.org/index.php/catalog/158)", "output": {"entities": {"named_data": [], "descriptive_data": ["panel data", "individual-level data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001347", "page": 1, "chunk": 0, "title": "idu166de58d710bfb14d111942c1dbee4755e885", "pdf_url": "https://local/prwp/idu166de58d710bfb14d111942c1dbee4755e885.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "panel data", "label": "DESCRIPTIVE_DATA", "score": 0.6831632256507874, "start": 235, "end": 245, "probe_score": 0.7292, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "individual-level data", "label": "DESCRIPTIVE_DATA", "score": 0.7102243900299072, "start": 766, "end": 787, "probe_score": 0.0866, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010988", "page": 62, "chunk": 2, "title": "Kenya - Second National Agricultural Extension Project", "pdf_url": "https://documents.worldbank.org/curated/en/304351468046500018/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "flip"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " weaving, embroidery and clothes-making.\n\n\nScarce and poorly paid livelihood opportunities\nwere often indicated as having prompted further\nmigration. In FGDs both in Kabul and Mazar,\nreturnees explained that several male youth,\nmarried and unmarried, in their community had\ndecided to return to Pakistan soon after return\nbecause of extremely limited job opportunities.\nOne male returnee in Kabul estimated that around\n60% of male youth had returned to Pakistan.\nOther FGD participants added that they had male\nrelatives who were currently in Pakistan but “were\ntrying to go to Iran and even Europe”. In parallel,\nthe great majority of returnees stated that they\nwere receiving regular remittances from relatives\nabroad, including males that had returned to\nPakistan. This phenomenon is also captured in the\nreturnee monitoring report of November 2017. Due\nto lack of livelihood opportunities, 8% of the sample\n\n\n\n15", "output": {"entities": {"named_data": [], "descriptive_data": ["FGDs", "returnee monitoring report"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000080", "page": 16, "chunk": 2, "title": "Afghanistan Case Study: Multi-purpose Cash and Sectoral Outcomes", "pdf_url": "https://reliefweb.int/attachments/020bd31a-6682-30a1-8823-7d27b21d2a9b/5b2cfab97.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "FGDs", "label": "DESCRIPTIVE_DATA", "score": 0.6556898951530457, "start": 153, "end": 157, "probe_score": 0.0001, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "returnee monitoring report", "label": "DESCRIPTIVE_DATA", "score": 0.7828972935676575, "start": 808, "end": 834, "probe_score": 0.1948, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\na lack of understanding, expertise or medication for\nthe treatment of chronic illnesses.\n\n\n**Case study: West Darfur, Sudan**\n\nBy 2011, the Darfur emergency of 2003/4 had become\na protracted humanitarian crisis, with as many as\n2 million people becoming internally displaced –\nmany living in camps throughout Darfur. Of these, an\nestimated 8 per cent of the camp population were made\nup of older people.\n\nHelpAge had worked in West Darfur since 2004.\nIn 2005/6, it carried out a series of assessments and\nsurveys to consult older people about their\nvulnerabilities and health and nutrition needs. <sup>19</sup>\nResults showed that older people in Darfur were not\naccessing health services despite clinics being\navailable. This was for a number of complex reasons.\nMany older people were experiencing isolation and\nneglect, and were excluded from food aid and health\nprogrammes, while others with mobility concerns\nlacked transport. These factors left many older people\nreticent and unable to seek medical care.\n\nIn response to this gap in health services provision,\nHelpAge established a roster of community health\nworkers to visit housebound older people, providing\ncare and referral as required. They also introduced a\ndonkey cart ambulance to transport older people to\nclinics for emergency care. Another initiative involved\ndistributing supplementary food baskets to older people\nat risk of malnutrition, or who were caring for multiple\ndependents.", "output": {"entities": {"named_data": [], "descriptive_data": ["assessments and\nsurveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001104", "page": 5, "chunk": 2, "title": "Protecting older people in emergencies: good practice guide", "pdf_url": "https://reliefweb.int/attachments/a7217620-a83f-3548-835e-45a82ee07e37/6-5-protecting-older-people-in-emergencies-helpage-2013.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "assessments and\nsurveys", "label": "DESCRIPTIVE_DATA", "score": 0.5639947056770325, "start": 490, "end": 513, "probe_score": 0.0141, "gold": "DATA_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|80|119|117|426|\n|South Lebanon|37|50|38|27|152|\n|Total|318|330|314|313|1275|\n|percent of total|24.52|25.44|24.21|24.13|98.30|\n\n\n\n6. Based upon the rehabilitation unit costs and existing surface areas presented in Table 3\nbelow, the cost of works was calculated for all 399 eligible schools. As a result, the total needed\nbudget to repair all these schools is US$121 million. With the proposed amount of\nsubcomponent financing, the project can finance the full rehabilitation of the first 10 schools of\nthe priority list.\n\n\n7. Project preparation included the preparation of a database which accounts for many of the\nschool facilities characteristics in order to prepare criteria and indicators for the selection of\npriorities. These show that out of the 1,275 schools during school year 2014-15:\n\n\n    - Some 708 schools do not belong to MEHE and rent is paid for 540 of them;\n\n    - 306 (20 percent) of school buildings were not originally designed as schools;\n\n    - Almost 95 percent of the public schools have Syrian students during the 1st shift;\n\n    - 89 schools have second shifts for Syrians;\n\n    - 652 schools are located in vulnerable areas as per the Education Working Group\n\nstandards.\n\n\n27", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["database"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000099", "page": 35, "chunk": 1, "title": "Lebanon - Emergency Education System Stabilization Project", "pdf_url": "http://documents1.worldbank.org/curated/en/578481467991017996/pdf/PAD1190-PAD-P152848-PUBLIC-Box391435B-LB-EESSP-Final-PAD-for-printing.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "database", "label": "VAGUE_DATA", "score": 0.5580024719238281, "start": 577, "end": 585, "probe_score": 0.4667, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Jordan Home Visits Report 2014 - Living in the shadows**\n\n\n## **5**\n\n**5.1**\n\n\n\nRefugees with both an MOI card issued in the governorate of residence and proof of UNHCR registration were entitled to access public health and education services free of charge at the time of data\ncollection, although the Government policy on access to health services has since changed. As of\nDecember 2013, UNHCR registration and MOI service cards became valid for a period of 12 months. As\nMOI service cards only entitle refugees to access services in the governorate in which they are issued,\nthose who move between governorates must re-register with UNHCR and the Ministry of Interior in\nthe new governorate of residence in order to access public services.\n\n\n**Health**\n\n\n**Utilization of public health services has increased, but lack of documentation continues to be a barrier to access**\n**for some refugees.**\n\n\nAt the time of data collection, free primary, secondary and some tertiary health care at Ministry of Health\nfacilities was available to Syrian refugees with an MOI card and proof of UNHCR registration. Those refugees who lacked the required documentation could access health services at UNHCR partner clinics,\nwhich were free of charge and provide primary and some secondary care.\n\n\n\n**Access to services**\n\n\n###### _“A generous Jordanian doctor helps us get the medication_ _my wife needs. Without him we wouldn’t be able to afford it..._\n\n\n###### _My greatest concern and the thing I think about the most is_\n\n\n###### _the education of my children.”_\n\n\n\n\n- Mohammad", "output": {"entities": {"named_data": ["Jordan Home Visits Report 2014"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001174", "page": 61, "chunk": 0, "title": "Living in the shadows: Jordan Home Visits Report 2014", "pdf_url": "https://reliefweb.int/attachments/b3a9d44a-6721-320e-adfc-ddb6b36422f6/home-visit-report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Jordan Home Visits Report 2014", "label": "NAMED_DATA", "score": 0.5643888711929321, "start": 2, "end": 32, "probe_score": 0.7836, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\ndominated by donor-funded humanitarian assistance, mainly in the form of emergency food aid. <sup>23</sup> [^23: Currently, there are six key SP programs, including a Bank-funded project, reaching around 270,000 poor and vulnerable HHs (i.e., 1.9\nmillion people) across the country, mainly though transfers conditional on work or training.] While in recent years\nhumanitarian cash transfers have been expanding, food aid continues to provide a lion’s share of the humanitarian\nassistance. Most of the humanitarian programs were initiated as emergency response to help the targeted communities\nand HHs survive shocks, and hence have a short-term focus. Furthermore, these programs do not support national\ngovernment-led service delivery systems, which can contribute to the enhanced legitimacy of, and trust in, institutions\nand the government by its citizens. While short-term assistance plays a valuable role in protecting poor and vulnerable\npopulations in South Sudan, more predictable and sustained safety net investments are needed to address vulnerabilities,\nstrengthen resilience to shocks and stresses, and promote human capital for medium-term recovery and longer-term\nresilience and development.\n\n16. **Gaps continue to exist in terms of national safety net coverage, as insecurity and limited infrastructure create**\n**serious difficulties in access.** Thus, states with the highest numbers of people in food insecurity have among the lowest\ncoverage in terms of the percentage of the food insecure population covered by SP programs. This is seen also at the\ncounty level, with some of the most vulnerable counties having the lowest coverage of their food insecure population, in\nsome cases near zero coverage, by any SP program. The balance of instruments (i.e., public works versus\nconditional/unconditional transfers) also varies substantially between and within states, limiting the extent to which\ndifferent instruments can be targeted to relevant groups for human capital accumulation. While robust data on coverage\ndo not", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["robust data on coverage"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 17, "chunk": 0, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "robust data on coverage", "label": "VAGUE_DATA", "score": 0.6502928733825684, "start": 2102, "end": 2125, "probe_score": 0.4217, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " of workers – mostly made up\nof the youngest refugees who might not\nhave worked back in Ukraine. Employment\nin one’s pre-displacement sector appears\nto boost the median net wage by about\n6%, when compared to those who switch\nfields – a back-of-the-envelope calculation\nputs their median net earnings at 89% of\nthe overall median. However, this likely\noverstates the true effect of staying in the\nsame sector, since the higher-paid groups\n(for example, the majority of IT specialists)\n\n\n\nwere more likely to remain in their original\nindustry.\n\n\n**Highly skilled Ukrainian refugees**\n**are likely to suffer from significant**\n**downgrading.** With the median wages\nof Ukrainian refugees estimated at 84%\n(SEIS survey) or 80% (NBP 2024 survey)\nof the national median (see chapter 2),\nthe difference for average wages may be\neven larger. This is because medians are\ninsensitive to high earners who typically\ninflate average earnings. Such high earners\nmay suffer significant downgrading\nconsidering the unfavourable occupational\nstructure of Ukrainian refugees. There are\nmany reasons to this, from occupational\nlicensing to a high level of language fluency\nrequired by high-skill jobs. <sup>28</sup> [^28: Lessem and Sanders (2020) modelled immigrant wage growth in the United States, finding that in a counterfactual model eliminating barriers to occupational entry\nwould lead to only small earnings increase for the average immigrant, but a substantial increase for the most highly skilled.]\n\n\n\nUkrainian\n\nrefugees\n\n\n\n\n\n\n\n\n\n\n\n\n\nPre-war\nUkrainians\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nOther\nforeigners\n\n\n\nPolish\ncitizens\n\n\n\nDrivers (truck, bus)\n\n\nTeachers\n\n\nMedical professions\n(physician, dentist, nurse, midwife)\n\n\nLegal professions\n(legal counsel, barrister, notary, bailiff)\n\n\nTaxi drivers\n\n\nOthers\n\n\nSource: Deloitte own elaboration based on ZUS data\non June 30th 2024.\n\n\n\n26 As described in chapter 2, SEIS measures incomes on the household level. Using it to estimate individual wages likely underrepresents lowest and highest incomes.\nDetails are available in the Online Technical Appendix.\n\n27 Note that the GUS (2024) data for", "output": {"entities": {"named_data": ["SEIS survey", "NBP 2024 survey", "ZUS data", "SEIS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 14, "chunk": 3, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS survey", "label": "NAMED_DATA", "score": 0.8458912372589111, "start": 703, "end": 714, "probe_score": 0.5162, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "NBP 2024 survey", "label": "NAMED_DATA", "score": 0.8435320854187012, "start": 724, "end": 739, "probe_score": 0.8219, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "ZUS data", "label": "NAMED_DATA", "score": 0.8175975680351257, "start": 1825, "end": 1833, "probe_score": 0.9997, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "SEIS", "label": "NAMED_DATA", "score": 0.5956779718399048, "start": 1886, "end": 1890, "probe_score": 0.0004, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", 2024 shows that\n38% of Ukrainian refugees worked in\nelementary occupations, much more than\npre-war Ukrainians (25%), non-Ukrainian\nforeigners (18%), and Polish citizens (10%).\n\n\n\n\n\n\n\n\n\n\n\nMSNA Jul-Aug 2023 SEIS May-Jun 2024\n\n\n\n\n\n\n\n\n\nMSNA Jul-Aug 2023 SEIS May-Jun 2024\n\n\n\nSource: Deloitte own elaboration based on MSNA and SEIS UNHCR surveys conducted in July-August 2023 and May-June 2024.\n\n\n\nWhile the share seems least favourable\namong Ukrainian refugees, their situation\nimproved the most in the two years since\nJune 30, 2022 (by 10 pp. compared with\n9 pp. for the pre-war Ukrainians, 2 pp. for\nnon-Ukrainian foreigners and 1 pp. for\nPolish citizens). On the other hand, in\nQ2 2024, managers and specialists, the\ntwo highest paid occupational groups,\ncomprised 8% of both Ukrainian refugees\nand pre-war Ukrainians, 22% of nonUkrainian foreigners (who include many\n\n\n\nIT specialists and executives), and 28% of\nPolish citizens. Their shares increased\nin the past two years by 3 pp. among\nUkrainian refugees and pre-war Ukrainians,\n2 pp. among other foreigners, and 1 pp.\namong Polish citizens – this data shows\nthat though Ukrainian refugees may be\nlargely employed in the less attractive\noccupational groups, they are also the\nfastest to progress toward more attractive\nprofessions. <sup>11</sup> [^11: Since 2021, ZUS has been requesting information about the occupation of non-agricultural workers who first join the social insurance system (most farmers have a\nseparate social insurance system). Unfortunately, this data is not yet comprehensive, as on June 30, 2022, it included 4.8 million people, and June 30, 2024, 7.2 million]\n\n\n\n**Ukrainian refugees in Poland have**\n**clearly improved their economic**\n**situation over the past year.** As\nindicated in chapter 1, the share of\nUkrainian refugee household incomes\nderived from work in Poland has increased\nfrom 74% in the July-August 2023 MSNA\nsurvey to 76% in the May-June 2024", "output": {"entities": {"named_data": ["SEIS UNHCR surveys", "MSNA\nsurvey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 7, "chunk": 1, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS UNHCR surveys", "label": "NAMED_DATA", "score": 0.6618663668632507, "start": 324, "end": 342, "probe_score": 0.9957, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "MSNA\nsurvey", "label": "NAMED_DATA", "score": 0.8449181914329529, "start": 1902, "end": 1913, "probe_score": 0.645, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "(Y/N)|Estimated<br>Amount (US$)|Actual Amount<br>(US$)|Process<br>Status|Draft Pre-qualification<br>Documents<br><br>|Draft Pre-qualification<br>Documents<br><br>|Prequalification<br>Evaluation Report<br><br>|Prequalification<br>Evaluation Report<br><br>|Draft Bidding<br>Document /<br>Justification<br><br>|Draft Bidding<br>Document /<br>Justification<br><br>|Specific Procurement<br>Notice / Invitation<br><br>|Specific Procurement<br>Notice / Invitation<br><br>|Bidding Documents as<br>Issued<br><br>|Bidding Documents as<br>Issued<br><br>|Proposal Submission /<br>Opening / Minutes<br><br>|Proposal Submission /<br>Opening / Minutes<br><br>|Bid Evaluation Report<br>and Recommendation<br>for Award<br><br>|Bid Evaluation Report<br>and Recommendation<br>for Award<br><br>|Signed Contract<br><br>|Signed Contract<br><br>|Contract Completion<br><br>|Contract Completion<br><br>|\n|Activity Reference No. /<br>Description|Loan / Credit<br>No.|Component|Review Type|Method|Market Approach|Procurement<br>Process|Prequalification<br>(Y/N)|Estimated<br>Amount (US$)|Actual Amount<br>(US$)|Process<br>Status", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:006710", "page": 2, "chunk": 6, "title": "Ethiopia - AFRICA EAST- P151432- Enhancing Shared Prosperity through Equitable Services - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099420001242225363/pdf/Ethiopia000AFR000Procurement0Plan03.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " mitigation\nmeasures.\n\n**94** . **Stakeholder risks** are substantial. There are significant vested interests linked with the wheat sector not\nonly for the government, but also the private sector (mills, bakeries) and civil society. Most importantly, the\n\n\nPage 34 of 54", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 38, "chunk": 2, "title": "Jordan - Emergency Food Security Project", "pdf_url": "http://documents.worldbank.org/curated/en/486071652556836130/pdf/Jordan-Emergency-Food-Security-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " with 2352 firms and 10,580 firm export-years.\n\n\nFor the sample of “continuing” exports we estimate the following regression,\n\n\n\n3\n\n\n\n_x_ =1\n\n\n\n_lnYit_ = _ci_ +\n\n\n\n2\n\n\n\n_n_ =0\n\n\n\n_δ_ <sup>_entry_</sup>\n\n_i,t−n_ <sup>+</sup>\n\n\n\n_δi,t_ <sup>_exit_</sup> + _x_ <sup>+</sup> <sup>_δt_</sup> <sup>+</sup> <sup>_εit_</sup> (1)\n\n\n\nwhere _lnYit_ is the log exports of firm _i_ in year _t_, _δi,t_ <sup>_entry_</sup> _−n_ <sup>is</sup> <sup>an</sup> <sup>indicator</sup> <sup>that</sup> <sup>equals</sup> <sup>one</sup> <sup>if</sup> <sup>firm</sup> <sup>_i_</sup>\n\n\n\nstarted exporting in year _t −_ _n_, i.e. _Yi,t−n−_ 1 = 0, _Yi,t−n_ _>_ 0, and _δi,t_ <sup>_exit_</sup> + _x_ <sup>is</sup> <sup>an</sup> <sup>indicator</sup> <sup", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005837", "page": 14, "chunk": 1, "title": "wps6711", "pdf_url": "https://local/prwp/wps6711.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Annex III: Implementation Arrangements**\n\n\n**LEBANON**\n**Emergency National Poverty Targeting Program Project (P149242)**\n\n**Institutional and Implementation Arrangements**\n\n\n1. With respect to the institutional setup of the NPTP, the program has been managed by the\nMOSA and the Presidency of the Council of Ministers (PCM). This was deemed the best option\nat the time of appraisal of the ESPISP II project, which supported the creation of the NPTP. The\npresent institutional setup will be retained during the implementation of the Emergency NPTP.\nHowever, an external unit (FOT) under the PCM will handle the fiduciary aspects of the project.\n\n2. The SDCs will continue supporting the implementation of the NPTP by hosting the social\nworkers who register beneficiaries, administer household questionnaires, do data entry, and\noverall follow up for the NPTP.\n\n\n3. With respect to the NPTP implementation and institutional structure, the following\nexplains the overall implementation arrangements of the program:\n\n\n     - The Council of Ministers makes policy decisions related to the NPTP, allocates\n\nannual budget, and defines cut-off scores which determine benefits.\n\n     - The Social-IMC reviews progress of NPTP and makes recommendations to the\n\nCouncil of Ministers.\n\n\n     - The NPTP Project Unit in the MOSA is responsible for the following: (i)\n\nmanaging the NPTP database in MOSA; (ii) receiving household applications;\n(iii) interfacing with applicants; (iv) entering data; (v) conducting household\nvisits; (vi) checking for data errors; (vii) transmitting data to the central database\nof the NPTP CMU; (viii) verifying claims from hospitals, schools, and PHCs and\nauthorizing payments; (ix) managing the outreach campaign; (x) managing the ecard food voucher beneficiaries list, delivery of the e-cards to beneficiaries, and\nfollow up; and (xi) monitoring", "output": {"entities": {"named_data": ["NPTP database", "NPTP CMU"], "descriptive_data": ["ecard food voucher beneficiaries list"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000047", "page": 41, "chunk": 0, "title": "Lebanon - Emergency National Poverty Targeting Program Project", "pdf_url": "http://documents.worldbank.org/curated/en/810511467987899324/pdf/PAD1030-ENGLISH-P149242-PUBLIC-FINAL-LEB-ENPTP-English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NPTP database", "label": "NAMED_DATA", "score": 0.5916927456855774, "start": 1371, "end": 1384, "probe_score": 0.0017, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "NPTP CMU", "label": "NAMED_DATA", "score": 0.5934004187583923, "start": 1607, "end": 1615, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "ecard food voucher beneficiaries list", "label": "DESCRIPTIVE_DATA", "score": 0.7079801559448242, "start": 1755, "end": 1792, "probe_score": 0.0001, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the\nWorld Bank and in the procurement plan for the first 18 months, which also will be reflected in the POM.\n\n\n13. **Procurement under the project will be carried out at the central level by the PCU established within MAFS and**\n**MGCSW by a dedicated Procurement Specialist and Financial Management Specialist hired under the project** .\nWhile the PCUs will have the overall responsibility for project coordination, oversight, and management, UNOPS\nwill be hired through output agreements as the technical leads to execute the project activities on cash transfers.\nA procurement capacity assessment of MAFS and MGCSW were conducted in March 2022 as part of project\npreparation and it was noted that at MAFS, the project management will make use of the existing procurement\nmanagement arrangements established under the current World Bank financed projects, ELRP and RALP where\nMAFS is the implementing agency, maintained a small project implementation unit, and contracted UN agencies\nto implement on the ground. Meanwhile MGCSW as the implementing Agency of Component 3, will leverage\nprocurement management arrangement established under another World Bank-funded WSEEP. The project will\nalso hire a senior procurement specialist to provide trainings to MGCSW staff on the new Country Public\nProcurement and Asset Disposal Act 2018 and the procurement regulations. The senior procurement specialist\nwill also support MGCSW to establish and train the Procurement Committee as required under the Procurement\nLaw.\n\n\n14. The proposed project is being prepared and processed under the procedures provided for under the World Bank\nPolicy on Investment Project Financing (hereafter the IPF Policy) Section III, paragraph 12: Projects in Situations\nof Urgent Need of Assistance or Capacity Constraints. In this regard, the Borrower has initiated the preparation\nof PPSD, but the finalization will be deferred to implementation.\n\n\n15. **PPSD and Procurement Plan** . MAFS prepared a PPSD to improve project implementation and help achieve\nproject results. The PPSD provides the basis", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000153", "page": 72, "chunk": 1, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents1.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " enrolment, teacher training,<br>socio‐emotional learning program, school maintenance,<br>student assessment, etc.|MOE (OpenEMIS)|Third Party|The verification agency will check<br>the number of Syrian refugee<br>children enrolled in target schools<br>and will conduct site visits and spot<br>checks in a sample of randomly<br>selected schools to verify<br>enrollment numbers.|\n|**DLR#2**Number of additional<br>children enrolled in public and<br>private KG2|<br> <br> <br>Number of students enrolled in public or freely provided<br>private KG2. Data should be reported disaggregated by type of<br>school, directorate, gender, and nationality.|MOE (OpenEMIS)|Third Party|Enrollment data and disaggregation<br>is provided to the verification<br>agency. The verification agency will<br>conduct site visits and spot checks<br>in a sample of randomly selected<br>schools to verify enrollment<br>numbers. The sampling framework<br>should be acceptable to the WB.|\n|**DLR#3.1**Comprehensive and<br>harmonized quality assurance", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Enrollment data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000127", "page": 43, "chunk": 1, "title": "Jordan - Education Reform Support Program-for-Results Project", "pdf_url": "http://documents1.worldbank.org/curated/en/731311512702123714/pdf/Jordan-Educ-Reform-121282-JO-PAD-11142017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Enrollment data", "label": "VAGUE_DATA", "score": 0.662837028503418, "start": 670, "end": 685, "probe_score": 0.0021, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "required for local government involvement, and arrangements for maintenance, monitoring and\nevaluation (M&E). Social capital enhancing activities would be a mandatory part of all sub-projects, and\nwould be tailored to support activities chosen by the communities.\n\nSupport to Decentralized Government Structures. Most local administrations are beginning\nto operate again with a limited number of staff and other inputs. District and chiefdom authorities are\nvery weak, however, and lack the financial and human resources needed to address their concerns and\npnorities effectively. NGOs have demonstrated their ability to implement successful community-based\nsocial and economic projects and have played a key role in shelter reconstruction activities. With the\ngradual strengthening of local government capacity, partnerships between community groups and local\nauthorities are expected to increase. Upon completion of initial training, district and chiefdom authorities\nwould be required to demonstrate that they have used the training by showing that there have been some\nimprovements in their community. For instance, at the end of each training session, district authorities\nwould be required to develop a simple action plan that specifies some activities that NSAP or other\npartners could support. District and chiefdom authorities would also gain experience in implementing,\nsupporting or overseeing community development activities.\n\nHealth. The unfavorable health indicators in Sierra Leone can be attributed to several factors.\nHigh fertility, female genital mutilation and the presence of HIV/AIDS increase morbidity and mortality\nrisks for women and children. Many risk factors that have contributed to HIV/AIDS epidemics in other\nAfrican countries have long been present in Sierra Leone, and the protracted conflict has created the\nconditions for explosive growth in HIV/AIDS infection rates. The Centers for Disease Control carried\nout a survey in 2002 which found the HIV prevalence among adults (aged 1549) to be 6.1 %; in\nFreetown, 4% in rural areas and 4.9% nationwide. In response to the crisis, Government has developed\na multi-sector HIV/AIDS Program, which is being supported by various", "output": {"entities": {"named_data": [], "descriptive_data": ["survey in 2002"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011268", "page": 10, "chunk": 0, "title": "Ethiopia - Energy Access Project", "pdf_url": "https://documents.worldbank.org/curated/en/323661468749771280/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey in 2002", "label": "DESCRIPTIVE_DATA", "score": 0.6400850415229797, "start": 1950, "end": 1964, "probe_score": 0.9708, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "d'investissements étrangers que Djibouti attire n'ont pas créé beaucoup d'emplois par rapport\nà d'autres pays de la région (Graphique 2). Djibouti compte une petite population jeune - 60\npourcent de la population est âgée de 15 ans et en-dessous - et doit faire face à de faibles\nniveaux d'activité et à un chômage élevé. En 2012, les statistiques gouvernementales\nindiquent qu'environ 26 pourcent de la population âgée de 15 ans et cherchant activement un\nemploi, n'a pas pu en trouver. De la population en âge de travailler, environ quarante- huit\npourcent sont sans emploi, y inclus les travailleurs découragés. Les entreprises publiques\njouent un rôle de premier plan dans des secteurs tels que l'électricité, les transports, les\ntélécommunications et l'immobilier. Le secteur public fournit 44 pourcent de l'emploi formel\nqui représente environ 17 000 emplois. Les femmes sont touchées de manière\ndisproportionnée par le chômage : seulement 35 pourcent des femmes font partie de la\npopulation active et souvent, beaucoup occupent des emplois vulnérables et précaires du\nsecteur informel tels que les vendeuses de rue, les commerçantes (sharshari), la redistribution\nde kat <sup>1</sup> [^1: 2012 profil de la pauvreté élaboré et publié par le Bureau des statistiques.], entre autres. Le coût et la qualité des facteurs de production importants comme la\nmain-d’œuvre, l'électricité et la qualité du climat d'invest", "output": {"entities": {"named_data": [], "descriptive_data": ["statistiques gouvernementales"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000134", "page": 6, "chunk": 0, "title": "Djibouti - Second Urban Poverty Reduction Project : Djibouti - Second Projet de Reduction de Pauvrete Urbaine", "pdf_url": "http://documents1.worldbank.org/curated/en/786961467998828687/pdf/PAD791-FRENCH-P145848-PUBLIC-Box393238B.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistiques gouvernementales", "label": "DESCRIPTIVE_DATA", "score": 0.8918749094009399, "start": 335, "end": 364, "probe_score": 0.9843, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " several qualitative\nfocus groups sessions, Syrians and Lebanese\nraised the issue of the lack of credible representation\namong refugees. The lack of representation\n\n\n\nincreases feelings of anxiety, particularly among\nSyrians, because they perceive the Lebanese\nauthorities to be unable or unwilling to protect them\nin cases of conflict. According to a Syrian male\nfrom Zahrieh in Tripoli, “In Lebanon, it’s every man\nfor himself. You can’t trust anyone, and you have to\nhave the right connections – something we don’t\nhave as Syrians.” <sup>54</sup>\n\n\nLebanese focus group participants also expressed\nthat one of the main challenges for constructive\ndialogue between both nationalities is the lack of\ncredible collective Syrian representation. This is\nlikely the result of different factors. On one side,\nSyrian families tend to move within Lebanon in\nsearch of work and shelter, thus limiting their ability\nto organize themselves. On the other side, the\nfeeling shared by many Syrians of being “guests”\nin Lebanon also affects their propensity to establish\nclear representational structures.\n\n\nMoreover, the lack of refugee camps for Syrians\nin the country minimises the opportunities for\nthe emergence of clearly defined leadership and\ncollective representation. Lebanese participants\nunderstood this clearly and hence were sceptical\nabout the ability of Syrians to enforce any decisions\ntaken during dialogue sessions and preferred to\ndeal with Syrians through local authorities.\n\n\n\n**PROPENSITY TO VIOLENCE**\n\n\nThe conflict scan found that Lebanese and Syrians are generally conflict averse. The majority preferred to\navoid conflicts and said that mediation was the most employed tool of conflict resolution between the two\ngroups. <sup>55</sup> This, however, does not mean that the propensity for violence is low. Contrary to that, focus groups\nhave shown a strong level of tension between the two groups. In South of Lebanon where curfews were\nbeing implemented against Syrian refugees, the level of hostility between the two groups was apparent.\nEven in Tripoli, where", "output": {"entities": {"named_data": [], "descriptive_data": ["conflict scan"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000273", "page": 15, "chunk": 1, "title": "Dialogue and local response mechanisms to conflict between host communities and Syrian refugees in Lebanon", "pdf_url": "https://reliefweb.int/attachments/1ee3c1cd-7b8b-305e-b4c4-a2701b2c3d11/DialogueandLocalResponseMechanismstoConflictbetweenHostCommunitiesandSyrianRefugeesinLebanon.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "conflict scan", "label": "DESCRIPTIVE_DATA", "score": 0.6196444630622864, "start": 1519, "end": 1532, "probe_score": 0.046, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nDevelopment Response to Displacement Impacts Project in the Horn of Africa Phase II (P178047)\n\n\n**Table 3: Selected activities and targets in DRDIP II to promote gender equity and address gender gaps**\n\n|Activities/targets|Phase I|Phase II|\n|---|---|---|\n|Female membership on community committees|34%|40%|\n|Female representation in leadership positions on community committees|Not tracked|30%|\n|Capacity-building for female committee members|Part of general<br>capacity-building|Tailored leadership<br>program for 12,000<br>women|\n|Female beneficiaries of livelihood activities|42%|45%|\n|Female beneficiaries of non-traditional livelihood activities|64%|70%|\n|Female beneficiaries of traditional livelihood activities|37%|40%|\n|GBV focal persons trained|0|120|\n|Independent project gender audit|N/A|Conduct at mid-term|\n|Thematic studies and project learning forums on gender issues|N/A|Annual|\n\n\n\n55. **Recognizing that GBV hinders women’s engagement in development processes, the sub-component will also**\n**support capacity-building to prevent GBV/sexual exploitation and abuse/sexual harassment (SEA/SH).** Activities will\ninclude the following: (a) appointment and training of 120 GBV focal persons in the target _woredas_ ; (b) training and\nawareness-raising on GBV for DRDIP staff and government officials and contractors involved in implementation; (c)\nconsultations and awareness-raising campaign for GBV prevention in project _kebeles_, working with local officials, nongovernmental organizations (NGOs) and schools. Activities will be closely coordinated with the 3R-4-CACE project.\n\n56", "output": {"entities": {"named_data": [], "descriptive_data": ["Independent project gender audit"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000113", "page": 30, "chunk": 0, "title": "Ethiopia - Second Phase Development Response to Displacement Impacts Project in the Horn of Africa Project", "pdf_url": "http://documents1.worldbank.org/curated/en/664141655323352974/pdf/Ethiopia-Second-Phase-Development-Response-to-Displacement-Impacts-Project-in-the-Horn-of-Africa-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Independent project gender audit", "label": "DESCRIPTIVE_DATA", "score": 0.5798665285110474, "start": 782, "end": 814, "probe_score": 0.4563, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " (70 percent refugee/30 percent host community members/60 percent femaleheaded) with a 36-month program of assistance in the five RHDs. Consistent with graduation programs\nimplemented worldwide and in Rwanda (including in refugee contexts), this will provide a combination of: (a) a\nweekly stipend to meet consumption needs; (b) asset transfer (cash); (c) training and coaching on soft skills, job\nskills and business management; and (d) access to savings and finance to build financial resilience. This is expected\nto transition the beneficiaries from dependency on humanitarian assistance (refugees) and safety net programs\n(Rwandese nationals), promote self-reliance and foster economic inclusion. This activity will adopt the “green\ngraduation” approach to support climate resilience, including: (a) awareness-raising on climate change risks in the\ntraining and coaching; and (b) support for climate-sensitive livelihood activities, including climate smart agriculture.\n\n\n**Component 3: Environmental Management & Climate Resilience (US$5.33 million equivalent, of which US$4.3**\n**million equivalent from the WHR)**\n\n\n38. **Most of the refugee camps in Rwanda are located on hilltops, making them and the surrounding areas**\n**vulnerable to climate-induced extreme weather events.** The camps have inadequate drainage systems, causing\n\n\n22 Key elements of the Assessment are: (a) BDF is a Government Business Enterprise established in 2011 an d owned by the GoR and BRD to\n<u>help MSMEs access finance, especially those lacking collateral; and (b) BDF supported over 49,000 businesses and spent over RWF153 billion.</u>\n\n\nPage 11", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000188", "page": 26, "chunk": 2, "title": "Rwanda - Second Phase of the Socio-economic Inclusion of Refugees and Host Communities Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099102225213540444/pdf/BOSIB-3f2311b3-9a20-44d3-b637-b3b2b3d21695.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n## **2.** Ukrainian refugees in the Polish labour market\n\n##### In the past year, as far as labour market integration is concerned, refugees from Ukraine improved in terms of employment and wages, yet they continue to be disproportionately skewed towards elementary occupations. They are also the group to see the fastest improvements, with the gap towards Polish citizens visibly closing across the entire wage distribution (2.1). The current refugee employment rates are only slightly lower than those for Polish citizens, and median net wages are at about four-fifths of the economy as a whole, which may nevertheless be overly optimistic when compared to gross or average wages (2.2).\n\n#### **2.1 Improving economic situation**\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 9. Ukrainian refugee labour status** <sup>**9**</sup> [^9: These employment rates are very close to the ones from the Polish central bank surveys of Ukrainian refugees, which showed 62% in July 2023 and 68% in July] **Chart 10. Ukrainian refugee median net wage** <sup>**10**</sup> [^10: See the note on median wage estimation method in the Online Technical Appendix.]\n\nWorking age (women 15-59, men 15-64) PLN, 18-64 age group\n\n\n4,000\n\n\n69%\n\n\n\n**Ukrainian refugees are more likely**\n**to be employed in elementary**\n**occupations than pre-war Ukrainian**\n**migrants, non-Ukrainian foreigners,**\n**and Polish citizens, but they are**\n**also the group to have improved**\n**the most in the last two years.** The\ndata as of June 30, 2024 shows that\n38% of Ukrainian refugees worked in\nelementary occupations,", "output": {"entities": {"named_data": [], "descriptive_data": ["Polish central bank surveys of Ukrainian refugees"], "vague_data": ["data as of June 30, 2024"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 7, "chunk": 0, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Polish central bank surveys of Ukrainian refugees", "label": "DESCRIPTIVE_DATA", "score": 0.7380416989326477, "start": 1010, "end": 1059, "probe_score": 0.9709, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data as of June 30, 2024", "label": "VAGUE_DATA", "score": 0.604166567325592, "start": 1602, "end": 1626, "probe_score": 0.7759, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "’ for Ksh193,965) and two other significant cheques which\nwere 6 months old (‘Scangraphics’ for Ksh286,262.90 and ‘Ramco Printings’ for\nKsh700,258.60).\n\n79. INT determined that district bank account balances were not necessarily minimal or nil as\nat the beginning or end of a financial period (see Wajir example below). Even the\ncashbook reported balances as reported in Part Six of the FMR were not insignificant\n(e.g. as at 31 March 2007 total cashbook balance was Ksh540.6 million).  INT also\ndetermined that significant numbers of unpresented cheques existed on project bank\naccounts, many of which should have been ‘written back’ or cancelled (this would be\ngood business practice), which raised concerns about the validity or correctness of the\noriginal payment voucher.  INT also identified cheques presented on bank accounts\nwhich did not appear in the cashbook.  Considering the controls and role of the District\nAccountant (one of the mandatory dual signatures required to operate the bank account\nand sign cheques) in the operation of district project bank accounts, such issues are\nindicators that a significant degree of collusion or mutual ineptness existed on a systemic\nbasis, as these problems were identified across a number of the districts sampled.\n\n80. Wajir district’s bank balance, as per its own district FMR (FY06/07: Ksh816,665,\nFY07/08: Ksh1,189,695) had balances that were significantly less than the actual balance\nas per the local banks’ records for both FY06/07 (Ksh16,898,926) and FY07/08\n(Ksh22,148,996), the reported FMR balances were approximately 5% of the local banks’\nrecords.\n\n\nPage 29 of 73", "output": {"entities": {"named_data": ["district FMR"], "descriptive_data": ["local banks’ records", "local banks’\nrecords"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009492", "page": 28, "chunk": 1, "title": "Kenya - Second Phase of the Arid Lands Resource Management Project : INT Redacted Report", "pdf_url": "https://documents.worldbank.org/curated/en/204971449174883589/pdf/Kenya-Second-Phase-of-the-Arid-Lands-Resource-Management-Project-INT-Redacted-Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "district FMR", "label": "NAMED_DATA", "score": 0.5255050659179688, "start": 1320, "end": 1332, "probe_score": 0.1903, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "local banks’ records", "label": "DESCRIPTIVE_DATA", "score": 0.6792792081832886, "start": 1455, "end": 1475, "probe_score": 0.0099, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "local banks’\nrecords", "label": "DESCRIPTIVE_DATA", "score": 0.5247492790222168, "start": 1593, "end": 1613, "probe_score": 0.0001, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_Table 1: Baseline data used for simulation modeling, 2022_\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Province|Population<br>(3-5y)<br>millions|Public<br>Enrollment<br>(3-5y)|Private<br>Enrollment<br>(3-5y)|ECE<br>Classrooms|ECE<br>Teachers|Classroom<br>Construction<br>Cost<br>Millions,<br>PKR|New<br>Teacher<br>Salary<br>(annual)<br>Millions,<br>PKR|WASH<br>Facility<br>Provision<br>Millions,<br>PKR|\n|---|---|---|---|---|---|---|---|---|\n|**Balochistan**|1.36|185,814|66,766|1,430|2,025|3.1|<br>0.3|0.7|\n|**Islamabad Capital**<br>**Territory**|0.15|11,241|79,615|174|298|3|0.42|0.8|\n|**Khyber Pakhtunkhwa**|3.54|693,349|453,363|2,216|2,216|3|0.46|0.21|\n|**Punjab**|9.1|796,756|1,776,028|19,895|18,560|3|0.54|0.6|\n|**Sindh**<br>|4.57|822,675|822,675|6,", "output": {"entities": {"named_data": [], "descriptive_data": ["Baseline data used for simulation modeling"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001508", "page": 8, "chunk": 0, "title": "idu1b0b7a0161caf6147a618ab0168995df4f111", "pdf_url": "https://local/prwp/idu1b0b7a0161caf6147a618ab0168995df4f111.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Baseline data used for simulation modeling", "label": "DESCRIPTIVE_DATA", "score": 0.5881118178367615, "start": 10, "end": 52, "probe_score": 0.9843, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Reliance Index (RSRI) prepared by the GoR, the World Bank and\nUNHCR measures refugee self-reliance in Rwanda. As noted above, the 2022 census and the first round of RSRI data\nshowed that most refugees have good access to basic services, but fare poorly with respect to employment and\nincome. The employment to population ratio for refugees is 15 percent as against 46 percent for the total\npopulation. According to the RSRI survey, just 24 percent of refugees reported doing paid work in the previous seven\ndays (though this increases to 45 percent for refugees living in Kigali) and only eight percent run a business or are\nengaged in farming. Low income is reflected in poor food security, with almost 60 percent of refugee households\nreporting that they typically eat only one meal per day. The main reasons provided for the low employment levels\nwere lack of skills (44 percent) and lack of information about the local labor market (34 percent). Other reasons cited\ninclude the need for investments in roads and connectivity to strengthen market access for agricultural producers\nand traders. A 2024 African Development Bank (AfDB) study on forced displacement in the region concluded that\npriority needs for self-reliance are better road connectivity, access to water and energy, improved educational and\n\n\n6 The GoR’s strategy is consistent with lessons from global experience in the 2023 World Development Report that a sustainable approach to\nmanaging forced displacement requires: (a) policies that provide freedom of movement and the right to work; (b) inclusion of refugees into\n<u>national service delivery systems to shift away from expensive parallel systems; and (c) support for self-reliance through access to jobs.</u>\n\n\nPage 2", "output": {"entities": {"named_data": ["2022 census", "RSRI data", "RSRI survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000188", "page": 17, "chunk": 2, "title": "Rwanda - Second Phase of the Socio-economic Inclusion of Refugees and Host Communities Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099102225213540444/pdf/BOSIB-3f2311b3-9a20-44d3-b637-b3b2b3d21695.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2022 census", "label": "NAMED_DATA", "score": 0.6066291928291321, "start": 130, "end": 141, "probe_score": 0.9221, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "RSRI data", "label": "NAMED_DATA", "score": 0.6971379518508911, "start": 165, "end": 174, "probe_score": 0.8276, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "RSRI survey", "label": "NAMED_DATA", "score": 0.7528892755508423, "start": 419, "end": 430, "probe_score": 0.9514, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on social development issues"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017254", "page": 24, "chunk": 0, "title": "Ethiopia - Capacity Building for Decentralized Service Delivery Project", "pdf_url": "https://documents.worldbank.org/curated/en/723751468771065805/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on social development issues", "label": "VAGUE_DATA", "score": 0.581004798412323, "start": 1670, "end": 1703, "probe_score": 0.333, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "UNHCR IDP Data Report – May 2012\n\n\nbeyond the reach of humanitarian organizations, as most of these displacements are within\nnon-accessible and/ or remote areas.\n\nDue to limited possibilities of speedy return and often linked with deteriorated conditions in\ndisplacement, IDP groups end up in _prolonged displacement_ . Many of them also seek to move\nto other locations for livelihoods, thus leading to _secondary displacement_ (and even _tertiary_\n_displacement_ ). This may include movement to urban areas, where IDPs are indistinguishable\nfrom the masses of urban poor. This report does not include an assessment of urban IDPs, nor\nof situations of secondary or tertiary displacement.\n\nThe last National Profile of Internal Displacement was undertaken in 2008, in relation to the\nrecommendation made by the former Representative of the Secretary-General on the Human\nRights of Internally Displaced Persons, Walter Kalin, during his visit to Afghanistan in 2007.\n\nThe current exercise has determined that – as of end May 2012 - an estimated **396,808**\n**persons/ 62,308 families** across the country remain internally displaced due to reasons of\nconflict. A total of 32% of the reported conflict-induced IDPs originate from the South, while\n23% are from the West followed by 24% from the East. The top 10 provinces of displacement\nare currently led by the South at 34%, followed by the East at 24% and West at 23%. The\nmajority of the recorded IDP populations belong to the Pashtun ethnicity. A total of 36% of\nIDPs refer to armed conflict and 37% refer to general insecurity as the key causes of their\ndisplacement. A total of 12% cite internal tribal conflict, impact of cross border shelling,\nextortion, illegal-taxation and land disputes as causes of displacement.\n\nThe number of new conflict-induced IDPs has been rising steadily since 2009 and 80% of the\ntotal reported conflict-induced IDPs claim", "output": {"entities": {"named_data": ["UNHCR IDP Data Report"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000682", "page": 3, "chunk": 0, "title": "Conflict-Induced Internally Displaced Persons in Afghanistan - Interpretation of Data as of 31 May 2012", "pdf_url": "https://reliefweb.int/attachments/64f811a5-8219-303d-bda5-3c3861e14a28/UNHCR%20IDP%20Report%202012.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR IDP Data Report", "label": "NAMED_DATA", "score": 0.8213600516319275, "start": 0, "end": 21, "probe_score": 0.9813, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " centre (PHC) compared to 75% in 2015 and 54% in\n2014. A lower proportion (49%) knew that medication for acute illnesses is free at PHCs.\n\n- 74% knew that UNHCR financially supports hospital care for life saving treatment compared\nto 77% in 2015. 86% knew that UNHCR contributes to the cost of deliveries.\n\n- 71% of households knew that refugee children have free access to vaccination at MoPH\nfacilities compared to 75% in 2015.\n\n- Self-reported vaccination coverage among children under 5 was 69% for polio and 62% for\nmeasles. However, a significant number of households reported not knowing if the child\nhad been vaccinated (12% for polio and 11% for measles). Note that these findings do not\nrepresent a true vaccination coverage. Actual coverage data will be presented in the report\nof the 2016 national survey.\n\n- 65% of children were reportedly vaccinated against measles at a PHC, with 21% receiving a\nmeasles vaccine through a mobile vaccination team.\n\n- The main reasons reported for not vaccinating children was long waiting time, not knowing\nwhere to go, and being unable to afford it.\n\n\n**Health care access and utilization during the month preceding the interview**\n\n- 65% of households surveyed spent money on health care in the previous month, with an\naverage expenditure of 221,826 LBP (148 USD) and a median expenditure of 150,000 LBP\n(100 USD) compared to an average of 136 USD in 2015 and 90 USD in 2014.\n\n\n2", "output": {"entities": {"named_data": [], "descriptive_data": ["2016 national survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001194", "page": 1, "chunk": 1, "title": "At a glance: Health access and utilization survey among Syrian refugees in Lebanon - September 2016", "pdf_url": "https://reliefweb.int/attachments/b74c4281-ade1-370a-9479-43d0606faf2d/LebanonHAUS2016Final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2016 national survey", "label": "DESCRIPTIVE_DATA", "score": 0.8218269348144531, "start": 796, "end": 816, "probe_score": 0.2858, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "same across the sectors. This method consists of a regression of the log earnings on the\n\n\n\nworkers' observable characteristics, with a dummy variable that represents working in the\n\n\n\nworkers' observable characteristics, with a dummy variable that represents working in the public sector. As before, the following equation by quantile regression: 𝑋𝑖𝑡 denotes the vector of workers' characteristics. We estimate\n\n\n\nthe following equation by quantile regression:\n\n\n\n𝑦𝑖𝑡 = 𝜏𝑡 + 𝜂𝑡 ∗𝑃𝑖𝑡 + 𝛽∗𝑋𝑖𝑡 + 𝜖𝑖𝑡.\n\n\n\nThe quantile regression estimates of the public sector premium are shown in\n\n\n\nfigure 2. The public sector premium is essentially zero in 1993 and 1998 and rises steeply\n\n\nafterward. Interestingly, in the 2000s, the public premium becomes much higher for the\n\n\ntop half of the distribution (over 30 percent at all quantiles above the median). These\n\n\nfindings are coherent with the rise in the returns to skills in the public sector as compared\n\n\nwith the private sector, which we document in the next section.\n\n\nFIGURE 2. The public premium estimated through quantile regression\n\n\n_Source:_ Author’s calculations based on VLSS 1993 and VHLSS 2006 data\n\n\n18", "output": {"entities": {"named_data": ["VLSS", "VHLSS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005499", "page": 19, "chunk": 0, "title": "wps6344", "pdf_url": "https://local/prwp/wps6344.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "VLSS", "label": "NAMED_DATA", "score": 0.7693758010864258, "start": 1125, "end": 1129, "probe_score": 0.9987, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "VHLSS", "label": "NAMED_DATA", "score": 0.5867584943771362, "start": 1139, "end": 1144, "probe_score": 0.9985, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank** Implementation Status & Results Report\nEthiopia Education and Skills for Employability Project (P177881)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Number of students who<br>successfully complete<br>project-supported training<br>programs (Number)|Comments on<br>achieving targets|Col3|This indicator will measure the number of youth enrolled in training training programs<br>supported by the project who complete the program and receive certification.|Col5|Col6|Col7|Col8|Col9|\n|---|---|---|---|---|---|---|---|---|\n|Of which, female<br>(Percentage)|0.00||0||0||50.00||\n|Of which, female<br>(Percentage)|Comments on<br>achieving  targets|Comments on<br>achieving  targets|The sub-indicator will measure the share of female students enrolled in training programs<br>supported by the who complete the training.|The sub-indicator will measure the share of female students enrolled in training programs<br>supported by the who complete the training.|The sub-indicator will measure the share of female students enrolled in training programs<br>supported by the who complete the training.|The sub-indicator will measure the share of female students enrolled in training programs<br>supported by the who complete the training.|The sub-indicator will measure the share of female students enrolled in training programs<br>supported by the who complete the training.|The sub-indicator will measure the share of female students enrolled in training programs<br>supported by the who complete the training.|\n|of which, youth from<br>rural areas<br>(Percentage)|0.00|", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003149", "page": 3, "chunk": 0, "title": "Disclosable Version of the ISR - Ethiopia Education and Skills for Employability Project - P177881 - Sequence No : 2", "pdf_url": "https://documents.worldbank.org/curated/en/099062424054516337/pdf/P177881-6dc18099-75cc-4c90-9559-d611b278a8ab.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " for host country poverty](https://ec.europa.eu/eurostat/web/microdata/european-union-statistics-on-income-and-living-conditions)</u>\nassessments\n\n3. Results for the Czech Republic not individually presented due to\nsampling limitations\n\n4. The host country poverty rate was based on <u>[OECD indicators for](https://stats.oecd.org/)</u>\n<u>[2021 that were indexed towards 2023 using consumer price index](https://stats.oecd.org/)</u>\n(CPI) data\n\n\nRefugee households also report having to engage\nin harmful coping strategies to meet basic needs.\nSome 8% and 15% had to resort to emergency\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n5 Belarus, Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, the Republic of Moldova, Poland, Romania, and Slovakia\n\n\n\n6 Defined as the total after-tax income of the household (including wages, transfers, social protection benefits, etc.) divided by the\nsquare root of the household size\n\n\n\n7 Based on <u>[OECD data from 2021, which was indexed by the CPI for 2022 and 2023 for each respective country](https://stats.oecd.org/)</u>\n\n\n\n**4**", "output": {"entities": {"named_data": ["OECD indicators", "OECD data from 2021"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 3, "chunk": 2, "title": "3", "pdf_url": "https://local/jad_paddy_docs/3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "OECD indicators", "label": "NAMED_DATA", "score": 0.5471193790435791, "start": 287, "end": 302, "probe_score": 0.9908, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "OECD data from 2021", "label": "NAMED_DATA", "score": 0.7533062100410461, "start": 924, "end": 943, "probe_score": 0.8555, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017781", "page": 62, "chunk": 2, "title": "Ethiopia - Small-Scale Irrigation and Soil Conservation Project", "pdf_url": "https://documents.worldbank.org/curated/en/760471506446287737/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "##### **4 Analysis**\n\nWe analyze the intent-to-treat effect of Malawi’s public works program using household\n\nlevel data from two rounds of post-intervention surveys. Recall that our design includes two\n\n\nlevels of randomization: village-level randomization varied PWP availability and payment\n\n\nstructure, while household-level randomization varies eligibility to participate conditional on\n\n\nPWP availability. Our main results pool across the four variants of the intervention in order\n\n\nto estimate the effect of having any public works opportunities in one’s village, and the\n\n\nadditional effect of being a treated household within a PWP village. Therefore, we capture\n\n\nthe direct effect of PWP availability on treated households, and the indirect effect of the\n\n\nprogram on untreated households in PWP villages. The indirect effect is important in the\n\ncontext of rationing. <sup>9</sup>\n\n\nUsing data from the lean season (survey round 2), we pool across treatments and estimate\n\n\nthe equation\n\n_yiv_ = _α_ + _β_ 1PWP _v_ + _β_ 2PWP _v ∗_ Topup _i_ + Γ _d_ + Θ _t_ + _ϵiv_ (1)\n\n\nwhere the indicator PWP _v_ is a village-level indicator for the availability of any PWP program\n\nand Topup _i_ is a household-level indicator that equals one if the household was randomly\n\nselected to be offered (“treated”) the program and zero otherwise. The coefficient _β_ 1 captures\n\n\nthe indirect effect of the program on untreated households in PWP villages. The coefficient\n\n\non the interaction term _β_ 2 captures the marginal effect of being randomly selected for PWP\n\n\nin a village that had a PWP program - that is, the effect of being offered the opportunity to\n\n\nparticipate in program. The sum of the two coefficients _β_ 1 and _β_ 2 captures", "output": {"entities": {"named_data": [], "descriptive_data": ["household\n\nlevel data", "post-intervention surveys", "data from the lean season"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006551", "page": 11, "chunk": 0, "title": "wps7505", "pdf_url": "https://local/prwp/wps7505.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household\n\nlevel data", "label": "DESCRIPTIVE_DATA", "score": 0.7226179838180542, "start": 99, "end": 120, "probe_score": 0.9353, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "post-intervention surveys", "label": "DESCRIPTIVE_DATA", "score": 0.7112990021705627, "start": 140, "end": 165, "probe_score": 0.7063, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from the lean season", "label": "DESCRIPTIVE_DATA", "score": 0.6820386648178101, "start": 902, "end": 927, "probe_score": 0.9441, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " measured by labor productivity and three aspects of financial performance:\nprofitability, financial liquidity, and return on investments. We measure labor productivity as\noperating revenues per worker. Financial performance is assessed through financial liquidity using\n\n\n5 For instance, C is considered as a BOS through 3 layers of ownership in the case where the Ministry of Finance owns (by 10% or more) a company\nA, which owns company B (by 10% or more), which also owns company C.\n6 The WB BOS database does not provide information on golden shares or veto powers, so the level of participation and thresholds proposed are\nused as a proxy of control and influence of the state over the firms.\n7 The ORBIS dataset does not provide a variable to directly identify those with state participation Although a proxy variable in ORBIS denoted\nas the Global Ultimate Owner can serve to identify some companies with state shareholding, it provides an underestimation of the real footprint of\nthe state in the markets and suffer from omission errors that could misclassify SOEs as private firms (Dall'Olio, et al., 2022).\n8 Yet, there is also variation of coverage within these countries as documented by (Bajgar, Berlingieri, Calligaris, Criscuolo, & Timmis, 2020).\n\n\n6", "output": {"entities": {"named_data": ["WB BOS database", "ORBIS dataset"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001299", "page": 7, "chunk": 2, "title": "idu149dc671915bcb141051b0d4105d073392111", "pdf_url": "https://local/prwp/idu149dc671915bcb141051b0d4105d073392111.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "WB BOS database", "label": "NAMED_DATA", "score": 0.875472366809845, "start": 493, "end": 508, "probe_score": 0.1389, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "ORBIS dataset", "label": "NAMED_DATA", "score": 0.8803771138191223, "start": 705, "end": 718, "probe_score": 0.769, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "VNG International\nESAP3 Audit Report and Financial Statements\nFor the period ended 31 December 2020\n\n# **Notes to the financial statements (Continued)**\n\n\n**8.** **Receivables**\n\n\nThe receivables amount is represented by:\n\n\n\n|Details|Amount in USD|\n|---|---|\n|VNG International – YEM monthly Administration fee – covered by Management<br>fee|**6,958**|\n\n\n**9.** **Reserves**\n\n\n<u>The reserves amount is represented by:</u>\n\n\n\n\n\n|Details|Amount in USD|\n|---|---|\n|Surplus of income over expenditure for year ended 31 December 2020|459,609|\n\n\n**10.** **Account payable**\n\n\nThe account payable amount is made up of mainly quarter No.4, Financial Year 2020 expenditure and cross\n<u>charges incurred by the MA Branch Office and was paid in quarter No.1, Financial Year 2021:</u>\n\n|Details|Amount in USD|\n|---|---|\n|Total per the payable listing as at 31 December 2020|1,111,757|\n\n\n\n**11.** **Other liabilities**\n\n\nOther liabilities amount is represented by:\n\n|Details|Amount in USD|\n|---|---|\n|MA office rent|10,888|\n\n\n\n11", "output": {"entities": {"named_data": [], "descriptive_data": ["payable listing"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001536", "page": 9, "chunk": 0, "title": "Ethiopia - AFRICA EAST - P151432 - Enhancing Shared Prosperity through Equitable Services - Audited Financial Statement : Ethiopia - EASTERN AND SOUTHERN AFRICA - P151432 - Enhancing Shared Prosperity through Equitable Services - Audited Financial Statement", "pdf_url": "https://documents.worldbank.org/curated/en/099033023113533202/pdf/P1514320274c7d07d080e10425bf89fc95d.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "payable listing", "label": "DESCRIPTIVE_DATA", "score": 0.6068559885025024, "start": 824, "end": 839, "probe_score": 0.2523, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " despite conflict can help foster the social contract between a government and its citizens, preventing further\ndeteriorations in relations and enhancing support to affected populations. <sup>34</sup> [^34: Cloutier, Mathieu. 2021. “Social Contract in Sub-Saharan Africa: Concepts and Measurements.” Policy Research Working Paper 9788, World\nBank.] PSNP 6 will invest in improving the resilience\nand adaptability of its systems to conflict, building on lessons learned in PSNP 5. <sup>35</sup> [^35: World Bank. 2025. _Third Party Monitoring of the Rural PSNP_ .] A key aspect will be developing and\noperationalizing the fragility risk management plan, making adjustments to targeting and service delivery, and putting\nin place systems that allow for initiation of TPI, as needed; ensuring active and real-time data on conflict prevalence and\nproject implementation through the use of systems such as the World Bank’s Geo-Enabling Monitoring and Supervision\n(GEMS) for remote monitoring; and acquiring data from frontline implementers and payment service providers to\nconfirm beneficiaries’ access to wages and benefits. <sup>36</sup> [^36: Lind, Jeremy, Rachel Sabates-Wheeler, Becky Carter, and Mulugeta Tefera Taye. 2024. _Conflict Disruptions to Social Assistance in a Multi-_\n_Hazard Context: Assessing Responses to the Northern Ethiopia Crisis (2020–22_ ). BASIC research.] Under Subcomponent 3.2, PSNP 6 will also continue to roll out\nthe national (Fayda) ID and electronic payments to contribute toward facilitating the portability of benefits should core\nbeneficiaries become displaced.\n\n\n_Subcomponent 3.2: Systems Strengthening and Digitization (US$28.5 million, of which IDA: US$2.4 million, MDTF:_\n_US$3.6 million)_\n\n\n44. **PSNP 6 will support enhancement, scale-up, and full operationalization of the PSNP digital platform initiated**\n**in PSNP 5, ensuring that digitization is occurring at all levels and in all areas.*", "output": {"entities": {"named_data": [], "descriptive_data": ["data from frontline implementers and payment service providers"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000640", "page": 24, "chunk": 1, "title": "Ethiopia - Sixth Productive Safety Net Project", "pdf_url": "https://documents.worldbank.org/curated/en/099021126194012306/pdf/BOSIB-a7e3e155-9f89-43d5-b7ff-bc4c5b0a5e12.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from frontline implementers and payment service providers", "label": "DESCRIPTIVE_DATA", "score": 0.6165536642074585, "start": 1002, "end": 1064, "probe_score": 0.0036, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Health Sector Transformation Project (HSTP) (P181385)\n\n\n**ANNEX 2: Third Party Monitoring and Data Visualization**\n\n1. TPM is critical for an objective understanding of project progress and to collect data to improve service delivery. Along\nwith monitoring and survey activities, the TPM will develop Government capacity for the design of data collection\ntools, data use, and oversight of health service monitoring. To support high-quality data collected in a conflictsensitive manner, ToR for health service delivery TPM will be developed to ensure robust supervision as well as data\nreview to assess and address data quality. Comprehensive ToRs have proven critical to high-quality TPM arrangements\nin FCV settings. All TPM will pay close attention to ensuring all language groups in the country are incorporated in\nmonitoring through translated tools and representative selection of enumerators. Set data entry, reporting, and\npresentation formats will be established and used by the TPM. The TPM will be expected to produce quarterly reports\nand presentations for national and state level use as well as quarterly reports for IPs detailing results at the facility\nlevel. The TPM will present findings to the State and Federal Level as well as IPs, CHDs, development partners, UNICEF,\nand The World Bank. Under this arrangement, TPM will be contracted by the PMU with input and oversight from the\nWorld Bank. TPM arrangements will include the following:\n**(a)** **Quarterly TPM visits.** All data collection methods will be administered during the same visits, at the frequency\n\nindicated. A phased approach will be used to support the expansion of TPM in the country, with initial sampling\nfor quarterly and bi-annual assessments moving to a bi-annual census of health facilities once monitoring capacity\nis established, anticipated in Year 2. Quarterly TPM visits will incorporate the following:\n(i) **Quarterly health facility functionality assessments.**", "output": {"entities": {"named_data": [], "descriptive_data": ["bi-annual census of health facilities"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000006", "page": 64, "chunk": 0, "title": "South Sudan - Health Sector Transformation Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099121123152529349/pdf/BOSIB12886229a02a1bcdc12ee681b5fe59.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "bi-annual census of health facilities", "label": "DESCRIPTIVE_DATA", "score": 0.7660219073295593, "start": 1777, "end": 1814, "probe_score": 0.0567, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "br>Expected Financing Closing<br>Date:|Program Implementation Period:<br>Expected Financing<br>Effectiveness Date:<br>Expected Financing Closing<br>Date:|Program Implementation Period:<br>Expected Financing<br>Effectiveness Date:<br>Expected Financing Closing<br>Date:|Program Implementation Period:<br>Expected Financing<br>Effectiveness Date:<br>Expected Financing Closing<br>Date:|Program Implementation Period:<br>Expected Financing<br>Effectiveness Date:<br>Expected Financing Closing<br>Date:|Start Date:|Start Date:|September 27, 2016<br> <br>December 22, 2016<br>January 31, 2021|September 27, 2016<br> <br>December 22, 2016<br>January 31, 2021|September 27, 2016<br> <br>December 22, 2016<br>January 31, 2021|End Date:|End Date:|January 31, 2021|January 31, 2021|\n|.|.|.|.|.|.|.|.|.|.|.|.|.|.|\n|||||||||||||||\n|**Program Financing Data**|**Program Financing Data**|**Program Financing Data**|**Program Financing Data**|**Program Financing Data**|**Program Financing Data**|**Program Financing Data**|**Program Financing Data**|**Program Financing Data**|**Program Financing Data**|**Program Financing Data**|**Program Financing Data**|**Program Financing Data**|**Program Financing Data**|\n|[ X", "output": {"entities": {"named_data": [], "descriptive_data": ["Program Financing Data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 5, "chunk": 2, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Program Financing Data", "label": "DESCRIPTIVE_DATA", "score": 0.5955737829208374, "start": 822, "end": 844, "probe_score": 0.3422, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " each of\nthe 47 county governments. The OAG has been facing major capacity challenges in meeting this\nnew mandate with implications on timeliness and quality of audit reports submitted to the\nParliament.\n\n\n13. **Corruption cuts across the challenges mentioned above.** Kenya continues to post poor\nrankings in Transparency International’s Global Corruption Index, dropping from 139 in 2012 to\n146 in 2016 out of 176 countries. With a score of 26, Kenya ranks below the global average of\n43 and the sub-Saharan mean of 31 <sup>4</sup> .\n\n\n14. **The GoK has responded to the challenges with the PFM Reform Strategy (PFMRS).**\nThe Strategy was refreshed following a mid-term evaluation in 2016 including with an updated\nmonitoring and evaluation framework. The National Treasury, the Office of the Accountant\nGeneral and the Ministry of Public Service, Youth and Gender Affairs (MoPSYGA) are key\nimplementing agencies. The PFM Reform Secretariat in the National Treasury has a strong\nrecord of coordination.\n\n\n**Program Scope**\n\n\n15. **The Kenyan Government’s PFMRS has seven substantial themes and program**\n**management as a crosscutting element.** The GESDeK supports five of the seven themes of the\nPFMRS as indicated in Table 2 below, defining the program boundary.\n\n\n**Table 1: PFMRS Themes and Program For Results (PforR) Support**\n\n\n3 The BOOST initiative is a World Bank collaborative effort to facilitate access to budget data and promote effective\nuse for improved decision-making processes, transparency and accountability. More information is available at\nhttp://wbi.worldbank.org/boost/boost-initiative.\n4 Transparency International Corruption Perceptions Index 2016.", "output": {"entities": {"named_data": ["Global Corruption Index", "Transparency International Corruption Perceptions Index"], "descriptive_data": [], "vague_data": ["budget data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017300", "page": 3, "chunk": 1, "title": "Kenya - Program for Results to Strengthen Governance for Enabling Service Delivery and Public Investment Project", "pdf_url": "https://documents.worldbank.org/curated/en/727661497023812265/pdf/Appraisal-Stage-Program-Information-Document-June-12-JKK-002.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Global Corruption Index", "label": "NAMED_DATA", "score": 0.794122040271759, "start": 339, "end": 362, "probe_score": 0.2055, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "budget data", "label": "VAGUE_DATA", "score": 0.5347545742988586, "start": 1422, "end": 1433, "probe_score": 0.1207, "gold": "NON_MENTION", "gold_tier": "flip"}, {"text": "Transparency International Corruption Perceptions Index", "label": "NAMED_DATA", "score": 0.6367056965827942, "start": 1617, "end": 1672, "probe_score": 0.9995, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "OPRC Operational Procurement Review Committee\nPAD Project Appraisal Document\nPDO Project Development Objective\nPFS Project Financial Statement(s)\nPIU Project Implementation Unit\nPLM Person with Limited Mobility\nPIM Project Implementation Manual\nPPP Public-Private Partnership\nPPSD Project Procurement Strategy Development\nQCBS Quality- and Cost-Based Selection\nRAP Resettlement Action Plan\nROW Right-of-Way\nRPA Regional Procurement Adviser\nRPTA Railways and Public Transport Authority\nSOE Statement of Expenditure\nSPS Stated Preference Survey(s)\nSTEP Systematic Tracking of Exchanges in Procurement\nUIFR Unaudited Interim Financial Report\nUN United Nations\nUTDP Urban Transport Development Project\nVAT Value Added Tax\nWA Withdrawal Application", "output": {"entities": {"named_data": ["SPS Stated Preference Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000022", "page": 3, "chunk": 0, "title": "Lebanon - Greater Beirut Public Transport Project", "pdf_url": "http://documents.worldbank.org/curated/en/471241521338566907/pdf/PAD-final-02262018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SPS Stated Preference Survey", "label": "NAMED_DATA", "score": 0.5343804359436035, "start": 514, "end": 542, "probe_score": 0.0389, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nStrengthening Public Sector Efficiency and Statistical Capacity Project (P151155)\n\n\n**ANNEX 5: KEY DATA ON GOVERNANCE AND PUBLIC INVESTMENT MANAGEMENT**\n\n\n**Figure 5.1. Evolution of Cameroon Governance Indicators (maximum = 100)**\n\n\n\n\n\n\n\n_Source:_ [www.govindicators.org.](http://www.govindicators.org/)\n\n\n**Figure 5.2. Cameroon Governance Compared to Peers in 2014 (maximum = 100)**\n\n\n\n\n\n\n\n\n\n\n\n_Source:_ [www.govindicators.org](http://www.govindicators.org/)\n\n\n\nPage 74 of 93", "output": {"entities": {"named_data": ["Cameroon Governance Indicators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000044", "page": 77, "chunk": 0, "title": "Cameroon - Strengthening Public Sector Effectiveness and Statistical Capacity Project", "pdf_url": "http://documents1.worldbank.org/curated/en/305621511406035802/pdf/CAMEROON-PAD2-11012017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Cameroon Governance Indicators", "label": "NAMED_DATA", "score": 0.648613691329956, "start": 201, "end": 231, "probe_score": 0.9603, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "they sought protection. However, government\nstatistics on first-time residence permits or other\nadministrative data sources in general do\nnot enable refugees, persons in a refugee-like\nsituation or persons with a refugee background\nto be identified unless they hold an asylum\nor humanitarian-related permit. <sup>13</sup> The figures\npresented in this report may therefore include\npeople who were admitted directly from one of\nthe seven countries of origin (Afghanistan, Eritrea,\nIran, Iraq, Somalia, Syria, Venezuela) and thus may\nnot have crossed an international border to meet\nthe definition of a refugee prior to arrival in an\nOECD country.\n\nGiven the high asylum recognition rates of\nnationals from the seven countries of origin\nconsidered (see Annex V for details), it can\nhowever be assumed that a large number of\nindividuals covered in this study would have a\nwell-founded refugee claim.\n\nFurther, this data collection exercise focuses\non first-time permits granted, excluding permit\nrenewals or status changes in the destination\ncountry to avoid double-counting individuals in\nthe data. Nevertheless, double-counting may\noccur in a few cases where the renewals and\nstatus changes could not be extracted from a\ncountry’s permit data (see Annex I for details).\nFurther, a few countries count native-born\n\n\n\nchildren of foreign nationals under the residence\npermit of their parents, although to our knowledge\nthis is not likely to lead to a large overestimation.\n\nThe definitional focus on first permits issued for\nentry into the host country excludes individuals\nwho obtain a visa or status regularization following\ntheir entry into the country—which is notably\nthe case for a large population of Venezuelans\nresiding in Chile and Colombia. Finally, while\ndata availability improves year to year, some\ngaps remain for specific country-year figures, but\nthese represent a relatively small percentage of\nundercoverage.\n\n\nThe figures in this report are based on the latest\navailable data in each reporting country. As a\nresult, some past figures have been", "output": {"entities": {"named_data": [], "descriptive_data": ["government\nstatistics on first-time residence permits", "administrative data sources", "permit data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000620", "page": 7, "chunk": 0, "title": "Safe Pathways for Refugees IV: OECD-UNHCR study on pathways used by refugees linked to family reunification, study programmes and labour mobility between 2010 and 2022 [EN/AR]", "pdf_url": "https://reliefweb.int/attachments/5af28923-d4e7-4b35-8b2e-840c03f927c8/UNHCR-OECD%20Safe%20Pathways%20for%20Refugees%20Report%20IV.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "government\nstatistics on first-time residence permits", "label": "DESCRIPTIVE_DATA", "score": 0.9072166681289673, "start": 33, "end": 86, "probe_score": 0.7888, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "administrative data sources", "label": "DESCRIPTIVE_DATA", "score": 0.567233145236969, "start": 96, "end": 123, "probe_score": 0.0163, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "permit data", "label": "DESCRIPTIVE_DATA", "score": 0.7960739135742188, "start": 1230, "end": 1241, "probe_score": 0.9301, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ",000 houses were destroyed dunng the war and only 10,000 have been\nrebuilt so far. Government is particularly concerned with the shelter needs of returnees, IDPs <sup>and</sup>\n\n\n\ngovernment employees such as health workers and teachers. The state of shelter in many <sup>areas is one</sup> <sup>of</sup>\nthe factors constraining the return of government employees and the revitalization of district and local\neconomic activity. The agricultural sector is particularly important because it currently <sup>employs 75%</sup> <sup>of</sup>\nthe country's labor force. The 2000 Baseline Service Delivery Survey reported that between <sup>65%</sup> <sup>and</sup>\n85% of the population do not have access to safe drinking water and sanitation facilities. Recent\nestimates in the most neglected communities of the \"newly accessible areas\", such as Bombali, <sup>suggest</sup>\nthat access to potable water and adequate sanitation are as low as 5% and 3%, respectively.\n\n\n\nWidespread human rights abuses during the civil war included the forced recruitment of children\nas combatants, porters and sex slaves. In addition, tens of thousands of people continue to suffer <sup>from</sup>\nthe traumatic effects of amputation and other injuries, sexual violence, loss of parents, and the general\nstress of living through a civil war. This has greatly increased the need for a kind of <sup>social service</sup>\nsupport that was not as widely needed before the war, integrating traditional health services <sup>with</sup>\npsycho-social care, counselling, foster homes and disability programs. The challenges ahead <sup>will include</sup>\n\nthe provision of community-", "output": {"entities": {"named_data": ["2000 Baseline Service Delivery Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013619", "page": 9, "chunk": 1, "title": "Uganda - Second Environmental Management and Capacity Building Project", "pdf_url": "https://documents.worldbank.org/curated/en/478351468760232992/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2000 Baseline Service Delivery Survey", "label": "NAMED_DATA", "score": 0.8882462978363037, "start": 568, "end": 605, "probe_score": 0.97, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " The interim\nICR (December 2022) used the 2019 survey data to assess achievement of the project outcomes as of 2021\nand judged efficacy to be High, noting that the project had exceeded all applicable (unadjusted) outcome\ntargets at that time. The interim ICR Review, however, rated efficacy as “Substantial, with moderate\nshortcomings,” arguing that, although the targets had been met, it was “unwise to assume that the results\nwould have been maintained, much less improved through 2021, considering the outbreak of the COVID-19\npandemic beginning in 2020.”\n\n\nThe final ICR (July 2025) acknowledges the absence of outcome indicator data after 2019, but explains that\nconducting subsequent impact evaluation surveys had become increasingly difficult and costly: (a) the\nCOVID-19 pandemic made data collection impossible for the survey scheduled in 2021; (b) the conflict in\nnorthern Ethiopia during 2020-2022, followed by renewed conflict in the Oromia and Amhara regions,\ndisrupted activities across the country; and (c) a new impact evaluation survey would now cost an estimated\nUS$1 million and take several years to complete.\n\n\nIn view of these limitations, this ICR Review considers the output indicators to be sufficient substitutes for the\noutcome indicators in assessing the project’s efficacy. The project delivered substantial outputs, providing\nover 29,000 loans to women-owned MSEs, training more than 43,000 women entrepreneurs, and mobilizing\nresources from donors and PFIs amounting to nearly twice the US$150 million IDA credit. Accordingly,\nefficacy is rated Substantial, with moderate shortcomings.\n\n\n**Rating**\nSubstantial\n\n\nPage 9 of 20", "output": {"entities": {"named_data": [], "descriptive_data": ["2019 survey data", "outcome indicator data", "impact evaluation survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001330", "page": 8, "chunk": 1, "title": "Ethiopia - ET:Women Entrepreneurship Development", "pdf_url": "https://documents.worldbank.org/curated/en/099031326115517364/pdf/P122764-a7ca0e2e-d25e-4092-8bfa-8bca0dbee695.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2019 survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8539665937423706, "start": 42, "end": 58, "probe_score": 0.2874, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "outcome indicator data", "label": "DESCRIPTIVE_DATA", "score": 0.6111727952957153, "start": 615, "end": 637, "probe_score": 0.1706, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "impact evaluation survey", "label": "DESCRIPTIVE_DATA", "score": 0.56758713722229, "start": 1028, "end": 1052, "probe_score": 0.0032, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "differences in OSM and employment data quality across the cities.\n\nSince our guiding objective was to design an algorithm to predict employment in un\nseen cities, we apply it to various cities for which we have no employment data, Niamey/Niger,\n\nKhartoum/Sudan, Mumbai/India, Karachi/Pakistan, Port au Prince/Haiti and Guayaquil/Ecuador\n\nare provided as examples in Figure 11. As our results do not point to a clear preference for\n\na model trained on all cities or trained solely on those cities of a given geographical region,\n\nwe deploy the algorithm trained an all cities for better cross city comparison patterns here.\n\n#### 6 Discussion & Conclusion\n\n\nWe set out to tackle a key gap in the policy toolbox, the lack of highly granular data on\n\nemployment within cities, particularly in less developed areas of the world. Using a spatial\n\nadaption of the random forest algorithm, we show that we can predict within-city cells in\n\nour test cities with extremely high accuracy (>95% R <sup>2</sup> ), and cells in out-of-sample cities with\n\nmedium to high accuracy (21% - 72% R <sup>2</sup> at grid level and 31% - 80% at polygon level). While\n\nwe found that our model picked up significant city-specific relationships, the moderate to\n\nhigh R <sup>2</sup> obtained for out-of-sample predictions, particularly for cities with expected higher\n\ndata quality, gives us confidence that the algorithm can be deployed on unseen cities.\n\nOur contribution to the literature and practical toolbox spans multiple levels. First, we\n\nshow that a combination of mapped features and pre-processed satellite data can be used\n\nto fill data gap in developing countries. Importantly, we illustrate this for the tricky within\n\ncity case, generating very high resolution estimates. Distinct from most other related studies\n\n(Jean et al", "output": {"entities": {"named_data": ["OSM"], "descriptive_data": ["satellite data"], "vague_data": ["employment data", "employment data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002432", "page": 31, "chunk": 0, "title": "where are all the jobs a machine learning approach for high resolution urban employment prediction in developing countries", "pdf_url": "https://local/prwp/where-are-all-the-jobs-a-machine-learning-approach-for-high-resolution-urban-employment-prediction-in-developing-countries.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "OSM", "label": "NAMED_DATA", "score": 0.5460955500602722, "start": 15, "end": 18, "probe_score": 0.9649, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "employment data", "label": "VAGUE_DATA", "score": 0.6272890567779541, "start": 23, "end": 38, "probe_score": 0.4702, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "employment data", "label": "VAGUE_DATA", "score": 0.5948416590690613, "start": 214, "end": 229, "probe_score": 0.8623, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "satellite data", "label": "DESCRIPTIVE_DATA", "score": 0.7452253103256226, "start": 1584, "end": 1598, "probe_score": 0.8005, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Regular Surveys on Social Tensions throughout Lebanon: Wave IV September 2018\n\n\nlivelihoods and the capability and fairness of service provision and\n\n\ninternational assistance. Structural drivers of conflict can be defined as the\n\ncornerstone to how the relationship between Syrian refugees and Lebanese\n\n\nhost communities has evolved; the history of relations between these\n\ncommunities; and long-term socio-economic conditions in an area. ARK’s\n\n\nsurvey questionnaire was designed to measure these conflict drivers.\n\n##### **2.1 Survey Questionnaire**\n\n\nThe survey questionnaire was developed to measure the key constructs\n\ndetailed in the SMF, with the intent both to validate the assumptions\n\n\nrepresented in the Framework and also to better understand the\n\nrelationship between the different plausible dimensions of social instability\n\n\nidentified in the Framework. The survey questionnaire (Appendix A) was\n\ndeveloped by ARK in consultation with UNDP and other stakeholders. The\n\n\nsame questionnaire was used in all four waves of surveying conducted to\n\ndate, with only minor modifications to query new topics or priorities that\n\n\nemerged over the course of the research. The survey questionnaire was\n\ndeveloped in English, translated to Arabic, and then back-translated to\n\n\nEnglish before being piloted. Following the pilot of the initial\n\nquestionnaire, only minor modifications to question wording were made.\n\n##### **2.2 Survey Sampling**\n\n\nEach of the four surveys conducted to date were conducted with the same\n\nmulti-stage stratified cluster design. In first stage of stratification, surveys\n\n\nwere allocated over Lebanese districts ( _aqdiya_ ) on the basis of both\n\npopulation size and a ‘vulnerability weight’, which included a measure of\n\n\nthe size of the Syrian refugee population in the area and a prior assessment\n\n\nof cadastre-level vulnerability conducted by the UNDP in 2015. <sup>8</sup> The\n\n\nvulnerability weight was included in stratification to ensure that more\n\nvulnerable areas of Lebanon were adequately included in the sample, even\n\nwhen these more-vulnerable areas were in less-populous regions.\n\n\n8", "output": {"entities": {"named_data": ["Regular Surveys on Social Tensions throughout Lebanon"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000696", "page": 13, "chunk": 0, "title": "Social Stability - Regular Surveys on Social Tensions throughout Lebanon - Wave IV, September 2018", "pdf_url": "https://reliefweb.int/attachments/661ebcaf-9c3c-36ed-b917-ef8a3906a3ea/67048.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Regular Surveys on Social Tensions throughout Lebanon", "label": "NAMED_DATA", "score": 0.7368301153182983, "start": 0, "end": 53, "probe_score": 0.9231, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " development. Not all of these are covered by\nthe PforR. Skills development and vocational training, as well as access to finance, are supported by other\ndonors and other programs.\n\n\n13. **Another core goal of this Bank-supported Program is to improve economic opportunities for**\n**Syrian refugees.** Before 2016, the vast majority of Syrian refugees were not able to work legally in Jordan.\nAlthough there was no law against Syrian refugees working, very few met the requirements of the existing\nwork permit regulations. At the end of 2015, only 5,700 Syrian refugees were working legally in Jordan. A\nmuch larger number worked in the informal sector. Estimates of Syrian refugees working in the informal\n\n\n3", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000137", "page": 11, "chunk": 2, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents1.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and\nthe administration of mob justice. <sup>8</sup>\n\n\n158. UNHCR became involved in the effort to combat such incidents before the\nviolence of 2008. The organization’s ‘Roll back xenophobia’ campaign won the\nrespect of other stakeholders working in this area, and when the May attacks took\nplace, UNHCR was called upon by the government to assist. While the government\nhad disaster management structures and procedures in place, it quickly became clear\nthat they were designed to meet the needs of a short-term natural disaster, rather\nthan a longer-term outbreak of violence which displaced large numbers of people\nand made it impossible for them to return to their usual place of residence.\n\n\n159. When it became clear that the official response to the crisis was not entirely\nadequate, there was a somewhat unrealistic expectation within civil society that\nUNHCR, as an operational organization with a mandate for the protection of\ndisplaced populations, would step in to fill the gap. UNHCR’s perceived inability to\ndo so was heavily and publicly criticized by a number of organizations, prompting\nthe High Commissioner to launch an inquiry into the matter. <sup>9</sup>\n\n\n**_8_** See Loren Landau, ‘Loving the **_<mark>alien</mark>_** <mark>?</mark> Citizenship, law, and the future in South Africa’s demonic\nsociety’, African Affairs, vol. 109, no. 435, 2010.\n\n9 ‘Report of the ad hoc inquiry into UNHCR’s response to the 2008 xenophobic crisis in the Republic of\nSouth Africa’, January 2009. The inquiry found that the expectations of civil society “may in some cases\nhave resulted from misunderstandings of UNHCR’s longstanding refugee protection mandate, as well\nas its more recent role under the UN collaborative mechanism known as the Cluster Approach in\n\n\n28", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001128", "page": 30, "chunk": 1, "title": "Refugee protection and international migration: A review of UNHCR's role in Malawi, Mozambique and South Africa", "pdf_url": "https://reliefweb.int/attachments/ab980053-1a6d-3300-a579-9cd7c250f257/AB0907CCF27B705D8525777C00720EA3-Full_Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "development and growth. Hussein (2002) used savings to GDP as a proxy for financial\ndevelopment where financial savings is the sum of demand, time, and savings deposits held at\ndeposit money banks. He utilized such to assess the response of the savings rate to the liberalization\nof interest rates in Egypt in early 1991. The other three studies on savings in Egypt focused on\ngross domestic savings that include both public and private savings. <sup>10</sup> [^10: See ElSayed (1993), Touny (2008) and the literature review section.]\n\nThis research fills a significant gap on empirical modeling of private savings in Egypt. It employs\na new time series on private savings in Egypt that was compiled by the Central Bank of Egypt\n(CBE) and the Central Authority for Public Mobilization and Statistics (CAPMAS) in Egypt. This\nseries is inclusive of savings in deposits, money banking, post offices, specialized banks,\ninvestment and savings certificates issued by banks in addition to institutional private savings in\npension funds and insurance companies. These were significant components that account for\nalmost 15% of aggregate private savings during 1990-2010.\n\n\n\n\n\n\n\n\n\nSource: CBE and CAPMAS, 2014\n\n\nWhile the new series is available in annual frequency, the Chow-Lin’s Temporal Disaggregation\nMethodology (Chow and Lin 1971) is employed to disaggregate the annual data into a higher\nfrequency quarterly series. This methodology generates the best linear unbiased interpolation,\ndistribution, and extrapolation of time series by using a related series called the indicator variable.\nThe Chow-Lin method uses quarterly indicators to generate the quarterly volatility and transforms\nannual frequency data to quarterly data. To generate a quarterly series of aggregate private savings,\nthe quarterly series of non-government demand and time deposits (obtained from the IMF – IFS\n2015) was used as an indicator variable. <sup>11</sup>\n\nThe generated quarterly series was deflated using CPI and divided by the population count to\nobtain the real gross private saving per capita in logarithm.\n\nMotivated by the Life Cycle Model", "output": {"entities": {"named_data": ["IMF – IFS\n2015"], "descriptive_data": ["time series on private savings in Egypt", "quarterly series of non-government demand and time deposits"], "vague_data": ["annual frequency data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007012", "page": 13, "chunk": 0, "title": "wps8020", "pdf_url": "https://local/prwp/wps8020.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "time series on private savings in Egypt", "label": "DESCRIPTIVE_DATA", "score": 0.8341714143753052, "start": 642, "end": 681, "probe_score": 0.9889, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "annual frequency data", "label": "VAGUE_DATA", "score": 0.7096425890922546, "start": 1685, "end": 1706, "probe_score": 0.3862, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "quarterly series of non-government demand and time deposits", "label": "DESCRIPTIVE_DATA", "score": 0.8328667283058167, "start": 1791, "end": 1850, "probe_score": 0.8804, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "IMF – IFS\n2015", "label": "NAMED_DATA", "score": 0.7422992587089539, "start": 1870, "end": 1884, "probe_score": 0.996, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " of public\nschools. <sup>7</sup>\n\n\n10. Prior to the onset of the Syrian crisis, Lebanon’s adjusted primary net enrollment rates\nwere slightly above the regional average at 96 percent. However, secondary net enrollment rates\nin Lebanon at 67 percent lagged behind the MENA average of 72 percent. Even when compared\nwith countries with similar level of development, Lebanon’s secondary net enrollment rate was\nsignificantly lower than the average of 81 percent. <sup>8</sup>\n\n\n11. Public education in Lebanon tends to serve the poor at low levels of quality. Public\nschools educate about 31 percent of students in Lebanon, despite being free. This revealed\npreference reflects the overall poor quality of public schools, particularly at the primary level,\nand has large and negative implications for the poor. The higher quality associated with private\nschools means that public-school students are likely to learn less and face more difficult job\nprospects upon graduation. This sets up inter-generational transmission of both lower learning\nlevels and lower income. <sup>9</sup> Public schools exhibit lower academic outcomes in international and\nnational assessments. The level of public school students was 10 percent lower than that of\nprivate schools in the 2011 Trends in International Mathematics and Science Study (TIMSS)\nresults. Indeed, based on the 2004 household survey, poverty and education are highly correlated\nin Lebanon.\n\n\n5 Lebanon’s inequality-adjusted HDI is 20.8 percent lower than its HDI, among the largest losses in the group of\ncountries in the high human development category.\n6 World Economic Forum’s 2013 Human Capital Index\n7 Further information about the level of private sector investments is expected from a forthcoming Education\nExpenditure Review.\n8 World Bank Ed Stats\n9 “Poverty, Growth and Income Distribution in Lebanon,” August 2008.\n\n\n3", "output": {"entities": {"named_data": ["Trends in International Mathematics and Science Study"], "descriptive_data": ["2004 household survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000030", "page": 11, "chunk": 1, "title": "Lebanon - Emergency Education System Stabilization Project", "pdf_url": "http://documents.worldbank.org/curated/en/578481467991017996/pdf/PAD1190-PAD-P152848-PUBLIC-Box391435B-LB-EESSP-Final-PAD-for-printing.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Trends in International Mathematics and Science Study", "label": "NAMED_DATA", "score": 0.7560645341873169, "start": 1267, "end": 1320, "probe_score": 0.9973, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2004 household survey", "label": "DESCRIPTIVE_DATA", "score": 0.8910120725631714, "start": 1359, "end": 1380, "probe_score": 0.8236, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Disbursement forecast\n\n\n\nContract number\n*Contract subject\nAwardee\n*Launching date\n-Expected delivery date\n-Non objection date\n*Expected date of final delivery\n*Bidder nationality\n*Contract allocation (general account, budget, loan\ncategory, geographic area)\n*List of contracts\nManagement of financial -Standard financial statements (balance sheet;\naccounts statement of sources and uses of funds/income\nstatement, ...)\n*LACI reports for the project duration\nFixed Assets management -Inventory of Fixed Assets (type, quantity, valuation,\ndate of service, etc.)\n\n\n\nSupplier\nAccounting category ; budgetary and accounting\nallocation of fixed assets\n\n\n\nLocation\nDepreciation\n-Disposal of Fixed assets\n\n\n\n**Module** Functions\nSorting parameters Project ID and currency used\n\n                  - Fiscal years\nCurrency\nDecentralized data entry locations\n\n\n\nChart of accounts, managerial reports, geographic\nareas of intervention, etc.\n\n\n\n\n                - Books of accounts\nDonors\n\n                 - Contracts\nCategories of disbursement\nUser Management Data storage ; restitution ; correction; cleaning; etc.\n\n                - Import/export of data to other Tempro modules\n\n\n\nIt is expected that the application would be modified to differentiate the operations from the\nprojects, as well as funding sources to allow for reporting in financial and accounting terms of the\nproject objectives and activities. The concept should allow for proper monitoring of the project\nduring the life of the credit, namely: (i) chart of accounts; (ii) by category, component, and subcomponent; (iii) by geography (type of establishment, site and district); (iv) by category of\nexpenses; and (v) in local and foreign currency. Reporting of multi-level data is planned, which\n**wiU** bring about a more dynamic approach to the management of the project, and which should", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["multi-level data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017460", "page": 51, "chunk": 0, "title": "Kenya - Highway Sector Project", "pdf_url": "https://documents.worldbank.org/curated/en/738551468048319033/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "multi-level data", "label": "VAGUE_DATA", "score": 0.6651609539985657, "start": 1720, "end": 1736, "probe_score": 0.4661, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " The sustainability of the sanitation measures will be carefully assessed from the point of view\nof good practices, cost effectiveness, affordability and the Djibouti water shortage environment.\n\n\n6. **Social**\n\n\n_6.1 Summarize key social issues relevant to the project objectives, and specify the project's social_\n_development outcomes._\n\n\nDjibouti is a small country and many key social issues were identified in the 1997 Poverty\n\nAssessment. The issues raised included the percentage of the population classified as poor in 1996\n(50-80% reaching the upper-bound when refugees, nomads and homeless are taken into account); large\nnumbers of refugees, nomads, and homeless populations; the majority of the poor live in urban areas\n(85%) even if the incidence of extreme poverty is overwhelmingly rural. Urban households can take\nadvantage of safety nets derived from the commodity market and services, and job opportunities are\nnot available in rural areas. The key problems faced by children include: (a) the high number of street\nchildren who have fled war ravaged Somalia and Ethiopia; (b) late entrance into school by poorer\nchildren (one out of four starts school at age 9 and leaves school at age 14); (c) health issues (diarrhea\n\nand malnutrition) are a leading cause of death for children under age 5. Other problems affecting the\nwhole population include respiratory infections on the increase (due to malnutrition); endemic health\nproblems (AIDS, tuberculosis, malaria, cholera); the widespread practice of Female Genital Mutilation\n(FGM); sanitation costs are high for poorer households not connected on the main water network as", "output": {"entities": {"named_data": ["1997 Poverty\n\nAssessment"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010287", "page": 23, "chunk": 1, "title": "Ethiopia - Second Road Sector Project", "pdf_url": "https://documents.worldbank.org/curated/en/255641468037147480/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1997 Poverty\n\nAssessment", "label": "NAMED_DATA", "score": 0.810173511505127, "start": 420, "end": 444, "probe_score": 0.0723, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 0 3 0 5 4 18\nMiddle East & North\nAfrica 0 0 2 1 7 5 6\n\nNorth America 0 2 0 0 0 0 1\n\nSouth Asia 0 0 0 1 6 0 1\n\n<u>Sub-Saharan Africa</u> <u>0</u> <u>0</u> <u>20</u> <u>3</u> <u>21</u> <u>2</u> <u>2</u>\n\n<u>World</u> <u>20</u> <u>8</u> <u>37</u> <u>26</u> <u>56</u> <u>21</u> <u>50</u>\n\n_Note:_ This table reports the share of regional population (panel a) and the number of countries (panel b)\ncovered by the various data sources used to derive the 2020 welfare distribution. The sources are ordered\nwith the most preferred on the left to the least preferred on the right.\n\n\n8", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data sources"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000634", "page": 9, "chunk": 1, "title": "idu01d94e70603dc804f990b6130751d75dccb52", "pdf_url": "https://local/prwp/idu01d94e70603dc804f990b6130751d75dccb52.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data sources", "label": "VAGUE_DATA", "score": 0.6923816204071045, "start": 417, "end": 429, "probe_score": 0.3255, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "1. Traders: exchange rice or other goods for cocoa to very small-scale producers who\ntypically dry their cocoa on the side of the road.\n2. Mobile intermediaries: drive to farmers and buy on the farm; many times they are\nrepresentatives of exporters or other intermediaries\n3. Stationary intermediaries: set up purchasing centers in larger villages and towns\n4. Export buyers: large exporters who buy directly from producers\n\nMost exporters have a pre-determined marketing margin and set buying prices by subtracting this\nmargin from the international price. While the small number of large exporters makes for an\noligopoly structure between which prices vary little, local intermediaries compete for market\nshare and it is common that prices offered by intermediaries vary. Producers tend to get\ninformation on cocoa prices via radio; prices are broadcast several times a day during harvest\nseason. The internal cocoa marketing system seems fairly transparent and competitive.\n\nHistorically intermediaries have not paid differential prices for better quality beans, even if they\nare fermented, because exporters were mainly targeting export markets in the US, where\nunfermented cocoa is in demand. The long time one-price policy of intermediaries, although fair\nfor producers of low-quality cocoa, has provided a disincentive for other producers to improve\ncocoa quality. A change in pricing practices would require a change in signals from the\nexporters. A clear and transparent system of quality standards is needed before the market can\ntransmit quality signals more effectively. Representatives of the industry noted that such\nstandards will be provided by the Cocoa Council (more below) once it is created.\n\n\n**<u>Table IV.12 Marketing Channels Used by Producers</u>**\n\n|Exporter|34.3%|\n|---|---|\n|Intermediary|38.9%|\n|Cooperative|6.3%|\n|Producer Association|16.6%|\n|Other|9.6%|\n\n\n\nSource: CRMG Survey\n\nThe CRMG survey indicates the importance of", "output": {"entities": {"named_data": ["CRMG Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002596", "page": 63, "chunk": 0, "title": "wps3306", "pdf_url": "https://local/prwp/wps3306.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "CRMG Survey", "label": "NAMED_DATA", "score": 0.8171943426132202, "start": 1895, "end": 1906, "probe_score": 0.9861, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "u>\nImports 348.22 4346.49 0.00 489073.70\nGDP Importer 24.04 2.39 16.97 30.51\n\nGDP Exporter 23.95 2.43 16.97 30.51\nContiguous Indicator 0.02 0.12 0.00 1.00\n\nGATT Member Exporter 0.77 0.42 0.00 1.00\nGATT Member Importer 0.78 0.41 0.00 1.00\nCommon Currency Indicator 0.01 0.11 0.00 1.00\nDistance 8.78 0.76 4.11 9.89\n\nRTA Indicator 0.17 0.37 0.00 1.00\n**Notes:** The data consist of 733,786 observations for all variables with 189 exporters and\n177 importers. The data span 1996 to 2018.\n\nFor annual GDP, we draw upon the World Bank’s World Development Indicators. All monetary\nvariables are in constant (2010) US dollars. Table 1 contains the summary statistics for our final\ndata set. We end up with a panel data set with country pairs being the unit of observation. There\nare 177 importers and 189 exporters for a total of 733,786 observations. Each pair contains\ninformation on the volume of trade during the year, whether or not a trade agreement was in force,\n\n\n9 <u>[http://www.cepii.fr/](http://www.cepii.fr/)</u>\n10 WTO trade agreements include (i) free trade agreement (FTA); (ii) customs union (CU); (iii) partial scope\nagreement (PSA); (iv) economic integration agreement (EIA); and combinations of each group.\n\nPage 9 of 26", "output": {"entities": {"named_data": ["World Development Indicators"], "descriptive_data": ["panel data set"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001738", "page": 11, "chunk": 1, "title": "international trade and labor markets evidence from the arab republic of egypt", "pdf_url": "https://local/prwp/international-trade-and-labor-markets-evidence-from-the-arab-republic-of-egypt.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Development Indicators", "label": "NAMED_DATA", "score": 0.9030472040176392, "start": 531, "end": 559, "probe_score": 0.9787, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "panel data set", "label": "DESCRIPTIVE_DATA", "score": 0.698847770690918, "start": 700, "end": 714, "probe_score": 0.7224, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " el crimen\norganizado. Los móviles son atribuidos al ajuste de cuentas, rapto y secuestros, muerte por maras y pandillas,\nasesinatos de familia, extorsión, narcotráfico y venganza. Entre otras, por parte de parejas o exparejas, por\nviolencia sexual, intrafamiliar y otros. En otro ámbito, las estadísticas indican que las mujeres, en edades comprendidas entre los 15 a 39 años, representan el grupo de mayor vulnerabilidad <sup>60</sup> .\n\n\nSobre la base de las consideraciones precedentes, los hallazgos del monitoreo y análisis estadístico del CONADEH apuntan que de los 688 casos de desplazamiento identificados, el 48.7% corresponde a mujeres. Sin\nembargo, dada la naturaleza de la recepción de quejas, es importante aclarar que casi un cuarto de los casos\n(23.8%) de las mujeres o en proporción al total (79 casos equivalente al 11%) incluyen mujeres que presentaron quejas sobre hechos de violencia que afectaban familiares, amigos o vecinos, y que derivaron en una\nsituación de riesgo o desplazamiento para ellas y su familia.\n\n\nEn otras palabras, el 23.8% de los casos de mujeres, representan afectaciones colaterales o indirectas de hechos violatorios, que (por defender a familiares cercanos, como cónyuges, hijos, hermanos, tíos, abuelos, amigos, entre otros), entran en una dinámica que deriva en la per", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["estadísticas"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000291", "page": 60, "chunk": 1, "title": "Informe Especial: El Desplazamiento Forzado Interno en Honduras", "pdf_url": "https://reliefweb.int/attachments/21e1ba6a-7c7c-34a1-8247-aa2285b055b1/INFORME-DESPLAZAMIENTO-BOCETO-ACNUR.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "estadísticas", "label": "VAGUE_DATA", "score": 0.698455274105072, "start": 293, "end": 305, "probe_score": 0.0, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and the JPD website would include the English version of the<br>advertisement.<br> <br>|**Risk Management:** Adequate training will be provided to an MOF accountant, seconded from MOF Finance Department, on the World<br>Bank financial management and disbursement guidelines. In addition, close implementation support of FM aspects will be carried out by<br>field based staff.<br> <br>To mitigate the risk of unfair advantage to local firms and excluding international firms who may not learn of the opportunities on time,<br>packages above US$500,000 will have timely notification in UNDB online and the JPD website would include the English version of the<br>advertisement.<br> <br>|\n\n\n58", "output": {"entities": {"named_data": ["UNDB online"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000064", "page": 57, "chunk": 12, "title": "Jordan - Emergency Project to Assist Jordan Partially Mitigate Impact of Syrian Conflict", "pdf_url": "http://documents1.worldbank.org/curated/en/419981468271818589/pdf/781290PAD0JO0R0t0Box377365B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNDB online", "label": "NAMED_DATA", "score": 0.7930160164833069, "start": 585, "end": 596, "probe_score": 0.0313, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "No<br> <br>|No<br> <br>|\n|Practice<br>Manager/Manager<br>Senior Global Practice<br>Director<br>Country Director<br>Regional Vice President|Practice<br>Manager/Manager<br>Senior Global Practice<br>Director<br>Country Director<br>Regional Vice President|Practice<br>Manager/Manager<br>Senior Global Practice<br>Director<br>Country Director<br>Regional Vice President|Practice<br>Manager/Manager<br>Senior Global Practice<br>Director<br>Country Director<br>Regional Vice President|Practice<br>Manager/Manager<br>Senior Global Practice<br>Director<br>Country Director<br>Regional Vice President|Practice<br>Manager/Manager<br>Senior Global Practice<br>Director<br>Country Director<br>Regional Vice President|Practice<br>Manager/Manager<br>Senior Global Practice<br>Director<br>Country Director<br>Regional Vice President|\n|Jan Weetjens<br>Ede Jorge Ijjasz-Vasquez Paul Noumba Um<br>Makhtar Diop|Jan Weetjens<br>Ede Jorge Ijjasz-Vasquez Paul Noumba Um<br>Makhtar Diop|Jan Weetjens<br>Ede Jorge Ijjasz-Vasquez Paul Noumba Um<br>Makhtar Diop|Jan Weetjens<br>Ede Jorge Ijjasz-Vasquez Paul Noumba Um<br>Makhtar Diop|Jan Weetjens<br>Ede Jorge Ijjasz-Vasquez Paul Noumba Um<br>Makhtar Diop|Jan Weet", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000148", "page": 6, "chunk": 2, "title": "Mali - Reinsertion of Ex-combatants Project", "pdf_url": "http://documents1.worldbank.org/curated/en/848361679677867655/pdf/Mali-Reinsertion-of-Ex-combatants-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "sup>(DMRCs)</sup> <sup>are</sup>\n\n\n\n**in** place in most districts. <sup>The</sup> <sup>recruitment of additional</sup> <sup>Senior District Officers,</sup> <sup>District Medical</sup>\n\n\n\nOfficers, Inspectors of Schools, <sup>District Agricultural</sup> <sup>Officers</sup> <sup>and/or District</sup> <sup>Land and Housing Officers</sup>\n\nis needed to complete the <sup>initial stage</sup> <sup>of restoration. Once district</sup> <sup>officials have been reinstated,</sup> <sup>efforts</sup>\n\n\n\nwill focus on capacity building <sup>and training in support</sup> <sup>of public sector reform,</sup> <sup>governance and</sup>\n\n\n\ndecentralization. District <sup>Council elections are scheduled</sup> <sup>for mid-2003.</sup> <sup>Efforts are</sup> <sup>also underway</sup> <sup>to</sup>\n\n\n\nrestore the institution of <sup>Paramount</sup> <sup>Chiefs,</sup> <sup>strengthen the capacity</sup> <sup>of chiefdom (sub-district)</sup>\n\n\n\nidministrations, and introduce <sup>the result-based</sup> <sup>model</sup>", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017005", "page": 7, "chunk": 6, "title": "Kenya - Second Highway Project", "pdf_url": "https://documents.worldbank.org/curated/en/707091468090303816/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "3,107<br>|4,155<br>|7,262<br>|34%<br>|1.0<br> <br><br>|1.1<br> <br><br>|25<br>|23<br>|\n|Guinea<br>|3,117<br>|4,014<br>|7,131<br>|29%<br>|1.0<br> <br><br>|1.1<br> <br><br>|24<br>|24<br>|\n|El Salvador<br>|3,611<br>|3,277<br>|6,888<br>|-9%<br>|1.1<br> <br><br>|0.9<br> <br><br>|22<br>|28<br>|\n|Ethiopia<br>|3,152<br>|3,480<br>|6,632<br>|10%<br>|1.0<br> <br><br>|1.0<br> <br><br>|23<br>|27<br>|\n|Algeria<br>|2,888<br>|3,590<br>|6,478<br>|24%<br>|0.9<br> <br><br>|1.0<br> <br><br>|27<br>|26<br>|\n|Stateless<br>|2,720<br>|2,796<br>|5,516<br>|3%<br>|0.8<br>", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000427", "page": 14, "chunk": 7, "title": "Asylum Levels and Trends in Industrialized Countries 2008 - Statistical Overview of Asylum Applications Lodged in Europe and selected Non-European Countries", "pdf_url": "https://reliefweb.int/attachments/3ab13bab-8d4b-3f86-b90a-e2540078aef7/2F800689DD12C5A78525758300561F85-unhcr-asylumtrends-mar2009.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEthiopia: SME Finance Project (P148447) ICR DOCUMENT\n\n\nthriving (e.g., an owner might use personal savings to avoid default). While the initial framework lacked\ngender-disaggregated indicators., it allowed for adding the same during additional financing recording\nadaptability. The inclusion of _Portfolio at Risk (PaR)_ was a notable strength, as a low PaR served as a useful\nproxy for the success of the financed enterprises. While the focus on easily quantifiable outputs like the\nnumber of loans and Business Development Services (BDS) recipients allowed for efficient and uncomplicated\nprogress monitoring, the simplicity came at the cost of depth. A major strength of the overall M&E plan was\nthe decision from the outset to commission a formal impact evaluation. This foresight compensated for the\nweaknesses in the routine results framework.\n\n\n**M&E Implementation**\n\n\n**66.** **The project had a strong monitoring system, designed and implemented by the EP consulting firm** . At\nthe start of the project, it was recognized that DBE had no reporting process for identifying non-paying\nleases. <sup>24</sup> [^24: Enterprise Partners, Small and Medium Enterprises Finance Project (SMEPF) Technical Assistance Facility Closure Report, Sept. 2020, p. 25.] EP assisted DBE in developing a reporting format whereby Head Office would receive the needed\ninformation from the districts. DBE’s progress in portfolio reporting and monitoring and its arrears and NPL\nstatus were tracked in Quarterly Monitoring Reports beginning in November 2017, which also monitored\nDBE’s use of the SMEFP facility. These reports were shared with the WB and senior management of the DBE.\nEP also produced quarterly leasing and working capital insight reports. <sup>25</sup> [^25: Enterprise Partners, SMEPF Technical Assistance Facility Closure Report, Sept. 2020, pp. 53-4.] These reports provided an overview\nof disbursement status both in terms of monetary value and", "output": {"entities": {"named_data": ["Quarterly Monitoring Reports"], "descriptive_data": ["quarterly leasing and working capital insight reports"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003027", "page": 26, "chunk": 0, "title": "Ethiopia - SME Finance Project", "pdf_url": "https://documents.worldbank.org/curated/en/099061726190019014/pdf/BOSIB-506b276d-9bce-4a44-befa-b4140157b718.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Quarterly Monitoring Reports", "label": "NAMED_DATA", "score": 0.5572099685668945, "start": 1507, "end": 1535, "probe_score": 0.88, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "quarterly leasing and working capital insight reports", "label": "DESCRIPTIVE_DATA", "score": 0.6258832216262817, "start": 1707, "end": 1760, "probe_score": 0.1803, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "> t <sup>�</sup> n - е <sup>�</sup> <sup>'-</sup> - [-- - <sup>-</sup> - -,.. <sup>гл</sup> - ' - _\n\n\n\n\" С��\n\n\n\n\n- -, ��� h . е� **�** �� . ^ чг�� 9 . - оои �Ггрм Иа ~ t о� G a оа [' а�� г�� r-. Ф �Ф .. \n- �� .,, �� ; �� \" �� ',rr - гл �г а� cv -- м - а�з ' r �� y - ' г \n    - ; ы 4 ��    - ?    - ¢`    - �з .    - ? r    \n\n\n�ц�             - _ аа             \n- **�** СС��, - - F1 [ �� F �с�� /1 �н�Э �г ty'l �Э� ` . а�у�Сч� �� J' i - . н .+. �у .\nГ \" t - ' м ?- L4S - ` U г h И V5 N\n\n- ti ���,, - �� r'?; t **'** ��� . 8 ����а� ^' �м **'** - 1 t д�и�� ' **'** \" �� - - La а Со _7 Ос °7 N - 'Ci оа� - v- пЭ Сс 7' Г�в ' - ���, {J 4 с� U - n, �", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003450", "page": 54, "chunk": 3, "title": "Kenya - EASTERN AND SOUTHERN AFRICA - P161317 - Kenya Industry and Entrepreneurship - Audited Financial Statement", "pdf_url": "https://documents.worldbank.org/curated/en/099070001312333149/pdf/P16131704d3b210300bde4093558478d790.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " workers in the\neconomy, but also accounts for increased\nproductivity brought about by more\nspecialization. Considering all aspects, the\noverall impact of the refugees has been\npredominantly positive, and it moved the\nPolish economy to a higher growth path.\nRefugees contribute to the economy\nslightly more than their employment\nshare – they increase the labour supply\nas both workers and entrepreneurs and\nexpand demand as consumers. The rise\nin productivity due to more specialization\nacross the labour force further boosts\nthe economy. The impact of refugees\nis lowered by a temporary decrease in\nthe capital-to-labour ratio (companies\nneed time to invest in equipment and\nmachines to match the rise in the number\nof workers), as well as an increase in\ncompetition on the labour market.\n\n\n**The figures are higher than those in**\n**the previous Deloitte (2024) report,**\n**which – due to scant data available**\n**at the time – did not account for the**\n**positive impact on labour productivity.**\nIn the earlier report, the overall positive\nimpact of refugees was reduced based on\nconservative assumptions, in the absence\nof available/clear data on the increased\ncompetition in the labour market. The\n\n\n\nmodel notably considered lower wages\nand higher unemployment among native\nworkers. However, recent data indicates\nthat these concerns did not materialize.\nInstead, Polish workers have moved on to\nbetter paid occupations, and the economy\nhas benefited from a larger pool of talent,\nenabling deeper specialization and\nincreased productivity growth.\n\n##### Remaining challenges\n\n\n**Despite significant progress in**\n**integrating refugees into the labour**\n**market, several challenges persist.**\nRefugees are half as likely to have an\nemployment contract as Polish citizens\nand few of them achieve high incomes.\nAlthough refugees have been moving on\nto more desirable professions at a faster\nrate than other groups in the economy,\ntheir jobs continue to be disproportionately\nskewed towards elementary occupations.\nThese issues are most evident among\nthose with", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["recent data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 2, "chunk": 3, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "recent data", "label": "VAGUE_DATA", "score": 0.5383149981498718, "start": 1299, "end": 1310, "probe_score": 0.4682, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "DHS 2000 and 2008, and authors’ calculations.|_Source_: HIECS 2000 and 2009 survey, EDHS 2000 and 2008, and authors’ calculations.|_Source_: HIECS 2000 and 2009 survey, EDHS 2000 and 2008, and authors’ calculations.|_Source_: HIECS 2000 and 2009 survey, EDHS 2000 and 2008, and authors’ calculations.|_Source_: HIECS 2000 and 2009 survey, EDHS 2000 and 2008, and authors’ calculations.|_Source_: HIECS 2000 and 2009 survey, EDHS 2000 and 2008, and authors’ calculations.|_Source_: HIECS 2000 and 2009 survey, EDHS 2000 and 2008, and authors’ calculations.|_Source_: HIECS 2000 and 2009 survey, EDHS 2000 and 2008, and authors’ calculations.|_Source_: HIECS 2000 and 2009 survey, EDHS 2000 and 2008, and authors’ calculations.|_Source_: HIECS 2000 and 2009 survey, EDHS 2000 and 2008, and authors’ calculations.|_Source_: HIECS 2000 and 2009 survey, EDHS 2000 and 2008, and authors’ calculations.|\n\n\n42", "output": {"entities": {"named_data": ["HIECS 2000 and 2009 survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005325", "page": 43, "chunk": 5, "title": "wps6159", "pdf_url": "https://local/prwp/wps6159.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "HIECS 2000 and 2009 survey", "label": "NAMED_DATA", "score": 0.5591580271720886, "start": 56, "end": 82, "probe_score": 0.9609, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEnhancing Connectivity and Resilience in the Far North of Cameroon for Inclusiveness Project (P178207)\n\n\nfunctioning road asset management system. In addition, unenforced axle load controls pose a serious threat to\nroad assets. This project will provide the necessary technical assistance to the Road Maintenance Fund by\nestablishing a management system to improve the strategic planning for and forecasting of maintenance works.\n\n\n23. **Climate data and risks are not systematically included in the planning of interventions on the transport**\n**network, in project design, construction methods, or in the management of assets and operations.** Decision\nmakers and implementation entities lack the necessary data and analytics on the exposure and vulnerability of\nthe Cameroonian road network to the existing and future effects of climate change. Cameroon’s under-designed\nand undermaintained road infrastructure is particularly vulnerable to natural hazards and climate change\nimpacts.\n\n\n24. **Cameroon loses approximately 9.8 percent of its GDP annually due to its unsafe roads.** The Global Road Safety\nFacility estimates **t** he total annual cost of fatal and serious road crashes in Cameroon to be at least US$3.2 billion,\nwhich represented 9.8 percent of Cameroon’s GDP in 2016. <sup>39</sup> [^39: https://www.roadsafetyfacility.org/country/cameroon] The road fatality rate in Cameroon <sup>40</sup> [^40: Global Health Observatory data repository accessed on February 1, 2022. http://apps.who.int/gho/data/node.main.A997?lang=en] was estimated\nat 30.1 deaths per 100,000 population in 2016. A large gap emerges between the road crash fatalities reported\nby the Government of Cameroon and the World Health Organization (WHO) estimates: whereas the 2016\ngovernment-reported road crash fatalities for the country were 1,879, WHO’s estimate was 7,066, almost", "output": {"entities": {"named_data": ["Global Health Observatory data repository"], "descriptive_data": [], "vague_data": ["Climate data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000003", "page": 20, "chunk": 0, "title": "Cameroon - Enhancing Connectivity and Resilience in the Far North of Cameroon for Inclusiveness Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099053123163547375/pdf/BOSIB0e7334a5d0570a3e40f8ae4d0c1266.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Climate data", "label": "VAGUE_DATA", "score": 0.7516094446182251, "start": 457, "end": 469, "probe_score": 0.7632, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Global Health Observatory data repository", "label": "NAMED_DATA", "score": 0.8718768358230591, "start": 1434, "end": 1475, "probe_score": 0.9735, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "The absence of any clear effect of increasing financial depth on the impact of\n\n\nexternal shocks is arguably the most surprising result of our basic exercises. Here we\n\n\nexamine whether this result is robust to changes in the measurement of financial depth.\n\n\nIn particular, it can be argued that larger financial depth appears not to reduce the impact\n\n\nof shocks because it expands as these shocks occur (this is a variation of the reverse\n\n\ncausality argument). As in the empirical growth literature, we address this possibility by\n\n\nusing the initial measure of private credit/GDP instead of its period average as the proxy\n\n\nfor financial depth. However, the result on the effect of financial depth is basically\n\n\nunchanged and, therefore, the puzzling irrelevance of financial depth continues.\n\n\nThe exchange-rate regime is usually considered a macroeconomic policy and not\n\n\na structural characteristic. That’s why it was not included in the basic set of interactions.\n\n\nHowever, since it has received so much attention in the stabilization literature and could\n\n\nin principle be related to the structural characteristics considered here, we conduct an\n\n\nadditional exercise that includes the exchange rate regime as an additional interaction\n\n\nvariable. We follow the Gosh et al. (2000) classification to separate country-year\n\n\nobservations with a pegged regime from those with intermediate and floating regimes.\n\n\nThis exercise renders very similar results to those of the benchmark: Trade openness is\n\n\nfound to amplify the shocks, financial openness and labor market flexibility to mitigate\n\n\nthem, and financial depth and ease of firm entry to be negligible in this respect. The\n\n\neffect of the exchange rate regime itself is quite small and statistically insignificant. This\n\n\nresult is, however, only tentative. The analysis of the exchange rate regime requires a\n\n\ntreatment of measurement issues that is out of the scope of this paper.\n\n\nAs explained in the methodological section, an alternative to estimating the\n\n\ninteractions model using panel data consists of estimating the simple model (with no\n\n\ninteractions) country-by-country, and then running a cross-country regression of the\n\n\nresulting cumulative impacts", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["panel data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003302", "page": 12, "chunk": 0, "title": "wps4089", "pdf_url": "https://local/prwp/wps4089.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "panel data", "label": "VAGUE_DATA", "score": 0.612366259098053, "start": 2059, "end": 2069, "probe_score": 0.9082, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " <br>SEAS<br>|Households registered in the national<br>social registry<br>Number of unique heads of<br>households in the registry,<br>regardless of poverty status<br>or program eligibility<br>Quarterly<br> <br>Project<br>administrativ<br>e data<br> <br>Routine monitoring<br> <br>SEAS<br>|Households registered in the national<br>social registry<br>Number of unique heads of<br>households in the registry,<br>regardless of poverty status<br>or program eligibility<br>Quarterly<br> <br>Project<br>administrativ<br>e data<br> <br>Routine monitoring<br> <br>SEAS<br>|Households registered in the national<br>social registry<br>Number of unique heads of<br>households in the registry,<br>regardless of poverty status<br>or program eligibility<br>Quarterly<br> <br>Project<br>administrativ<br>e data<br> <br>Routine monitoring<br> <br>SEAS<br>|\n|Beneficiaries with access to basic services<br>infrastructure financed by the project<br>|Number of people<br>estimated to be direct<br>beneficiaries of sub-projects<br>under Component 3|Quarterly<br>|Project<br>administrativ<br>e data<br>|Routine monitoring<br>|SEAS<br>|\n\n\n|Monitoring & Evaluation Plan: Intermediate Results Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|-", "output": {"entities": {"named_data": [], "descriptive_data": ["social registry"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000063", "page": 35, "chunk": 4, "title": "Djibouti - Integrated Cash Transfer and Human Capital Project", "pdf_url": "http://documents1.worldbank.org/curated/en/419881558381476102/pdf/Djibouti-Integrated-Cash-Transfer-and-Human-Capital-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "social registry", "label": "DESCRIPTIVE_DATA", "score": 0.5568135976791382, "start": 55, "end": 70, "probe_score": 0.6005, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "39. The NPTP Project Unit in the MOSA is responsible for the following: (i) managing the\nNPTP database in MOSA; (ii) receiving household applications; (iii) interfacing with applicants;\n(iv) entering data; (v) conducting household visits; (vi) checking for data errors; (vii)\ntransmitting data to the central database of the NPTP CMU; (viii) verifying claims from\nhospitals, schools, and primary healthcare centers (PHCs) and authorizing payments; (ix)\nmanaging the outreach campaign; (x) managing the e-card food voucher beneficiaries list,\ndelivery of the e-cards to beneficiaries, and follow up; and (xi) monitoring of the program\n(specifically inputs and outputs).\n\n40. The NPTP CMU in the PCM is responsible for the following: (i) managing the central\ndatabase; (ii) validating data and cross-checking with national databases; (iii) processing\nhousehold data and generating scores and ranks according to the PMT formula; (iv) maintaining\nthe PMT formula, and providing the list of beneficiaries (v) analyzing national data and reporting\nfindings to the Social Inter-Ministerial Committee (Social-IMC); (vi) monitoring of program\nresults including targeting performance; and (vii) auditing data processing.\n\n41. MOSA SDCs are responsible for: (i) receiving household applications and interface with\napplicant; (ii) data entry into program application; (iii) conducting household visits; (iv)\nchecking possible data errors in application forms against provided official documents; (v)\ntransmitting households’ application data to MOSA central unit; and (vi) handling appeals and\nclaims received by households.\n\n42. With respect to the implementation arrangements of the e-card food voucher, the\nfollowing arrangements have been agreed upon: (i) WFP will conduct training for NPTP field\nwork coordinators and social workers, including on", "output": {"entities": {"named_data": ["NPTP database in MOSA"], "descriptive_data": [], "vague_data": ["household data", "national data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000047", "page": 24, "chunk": 0, "title": "Lebanon - Emergency National Poverty Targeting Program Project", "pdf_url": "http://documents.worldbank.org/curated/en/810511467987899324/pdf/PAD1030-ENGLISH-P149242-PUBLIC-FINAL-LEB-ENPTP-English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NPTP database in MOSA", "label": "NAMED_DATA", "score": 0.5444599986076355, "start": 89, "end": 110, "probe_score": 0.1266, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "household data", "label": "VAGUE_DATA", "score": 0.6485671997070312, "start": 849, "end": 863, "probe_score": 0.0043, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "national data", "label": "VAGUE_DATA", "score": 0.5803805589675903, "start": 1014, "end": 1027, "probe_score": 0.114, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " persons. Information on\nother categories of stateless persons is not available.\n\n**40** A study is being pursued to provide a revised estimate of statelessness figure.\n\nSource: UNHCR/Governments.\n\n\n\nUNHCR > **GLOBAL TRENDS 2016** 65", "output": {"entities": {"named_data": ["GLOBAL TRENDS 2016"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000712", "page": 64, "chunk": 6, "title": "Global Trends: Forced Displacement in 2016", "pdf_url": "https://reliefweb.int/attachments/68295936-5f9b-382c-8466-3e660ac587d3/5943e8a34.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "GLOBAL TRENDS 2016", "label": "NAMED_DATA", "score": 0.7140868902206421, "start": 210, "end": 228, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "#### **9.4 Average monthly temperatures 2015 – 2023**\n\nThe table presented below represents the maximum and minimum temperatures for each of\nthe specified locations. It tries to illustrates the temperature decrease observed during the\nmonth designated as the shelter cluster Cold winter period.\n\n\n23\n\n\n|Col1|Col2|JAN|FEB|MAR|APR|MAY|JUN|JUL|AUG|SEP|OCT|NOV|DEC|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n||**Kiev**|-1|2|7|17|21|25|27|28|23|12|6|3|\n||**Kiev**|-8|-5|-1|5|9|14|15|15|11|3|0|-2|\n||**Odessa**|2|5|10|15|21|27|31|31|26|15|11|7|\n||**Odessa**|-5|-2|1|6|12|17|18|19|14|7|3|-1|\n||**Lviv**|0|4|8|15|20|24|26|28|22|12|7|4|\n||**Lviv**|-7|-3|-1|4|9|13|13|13|10|4|0|-2|\n||**Vinnytsia**|-1|3|8|16|21|24|26|27|23", "output": {"entities": {"named_data": [], "descriptive_data": ["Average monthly temperatures 2015 – 2023"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000363", "page": 23, "chunk": 0, "title": "Ukraine Winterisation Recommendations 2023-2024", "pdf_url": "https://reliefweb.int/attachments/2ee500e9-edc9-4453-8645-c72244bafa61/Winterization%20Recommendations%2023-24%20v01.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Average monthly temperatures 2015 – 2023", "label": "DESCRIPTIVE_DATA", "score": 0.6162984371185303, "start": 11, "end": 51, "probe_score": 0.0385, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nLower secondary completed 0.461 0.454 0.545 0.398 0.444 0.359 0.588 0.508\nSome or completed upper secondary 0.700 0.690 0.790 0.604 0.607 0.343 0.761 0.521\nPost-primary TVET 0.874 0.850 0.894 0.457 0.858 NS 0.979 0.355\nPost-secondary TVET 1.119 1.088 1.154 0.578 1.105 0.320 1.171 0.414\nHigher/tertiary level of education 1.708 1.686 1.669 1.304 1.616 0.935 1.653 1.022\nData on educational level missing NS NS NS NS 0.320 NS 0.470 0.331\n**Secondary versus primary completed**\nLower secondary versus primary 0.090 0.076 0.200 -0.095 0.214 0.036 0.285 0.098\n<u>Upper secondary versus primary</u> <u>0.329</u> <u>0.312</u> <u>0.445</u> <u>0.111</u> <u>0.377</u> <u>0.020</u> <u>0.458</u> <u>0.111</u>\n<u>Source: Tsimpo and Wodon (2020b). Note: NS means not statistically significant.</u>\n\n**Cost-benefit analysis for school construction**\n\n5. **The cost benefit analysis of investments in lower secondary school completion is based on estimates of wage**\n**earnings and data for both investment and recurrent costs.** Earnings gains are based on results from Tables 5.2\nand 5.3. Cost data", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Cost data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 94, "chunk": 1, "title": "Uganda - Secondary Education Expansion Project", "pdf_url": "http://documents.worldbank.org/curated/en/406361595815248191/pdf/Uganda-Secondary-Education-Expansion-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Cost data", "label": "VAGUE_DATA", "score": 0.673726499080658, "start": 1077, "end": 1086, "probe_score": 0.6489, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "s and refugees are likely to return to their original villages or in their vicinity.** Existing data\nshows that a large majority (87 percent) of IDP and refugee returns are primarily to areas of habitual residence while\nrelocations to third areas is quite low at an estimated 6 percent. <sup>15</sup> The majority of the IDPs returned to their places of\nhabitual residence from within the same county (64 percent) or within the same state (23 percent) while only a few (13\npercent) returned from outside the state. <sup>16</sup> Most returnees are therefore likely to be concentrated in rural and peri-urban\nareas except for some who opt to permanently settle in urban centers (e.g. Wau or Malakal) or some who remain in cities\nas they are unable to return to their villages due to security concerns or occupation of their land and houses by other\ngroups (e.g. Bor or Bentiu). <sup>17</sup> This has also been confirmed by a Bank commissioned population movement analysis by IOM\n\n\n13 IOM DTM\n14 UNMISS (August 2019) ( _Mimeo_ )\n15 IOM DTM. The remaining 7 percent demonstrates those whose movement could not be clearly tracked.\n16 IOM DTM\n17 Returnees in this PCN include both IDP returnees as well as refugee returnees.\n\n\nNovember 4, 2019 Page 5 of 14", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Existing data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000014", "page": 4, "chunk": 2, "title": "Concept Project Information Document (PID) - South Sudan Enhancing Community Resilience and Local Governance Project - P169949", "pdf_url": "http://documents.worldbank.org/curated/en/294881573571217860/pdf/Concept-Project-Information-Document-PID-South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project-P169949.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Existing data", "label": "VAGUE_DATA", "score": 0.6272600293159485, "start": 87, "end": 100, "probe_score": 0.9979, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "* **As a result of the speculative housing market, land and real estate prices have risen sharply.** Land prices\nin Beirut increased an exorbitant 600 percent from 2003 to 2013, while real estate prices inflated 200 percent. <sup>79</sup>\n\n\n72 Marot, “Jadaliyya - The End of Rent Control in Lebanon: Another Boost to the ‘Growth Machine?’”\n73 UN-Habitat, “Guide for Mainstreaming Housing in Lebanon’s National Urban Policy.”\n74 UNDP, “Leave No One Behind for an Inclusive and Just Recovery Process in Post-Blast Beirut”; UN-Habitat, “Lebanon Urban Profile,” 2011.\n75 Gebara, Khechen and Marot, “Mapping New Constructions in Beirut (2000-2013).”\n76 Since its independence in 1942, the Lebanese State has rarely engaged in the production of public housing or introduced measures to protect\nor secure affordable housing for low-income groups such as property regularization and neighborhood upgrading\n77 Beirut Urban Lab, “Beirut: A City for Sale?”\n78 MoF, “Public Finance Monitor.”\n79 InfoPro, “Business Opportunities in Lebanon – Year XI. Real Estate in Greater Beirut [Database],” 2014.\n\n\nPage 50 of 66", "output": {"entities": {"named_data": ["Real Estate in Greater Beirut [Database]"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 55, "chunk": 2, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Real Estate in Greater Beirut [Database]", "label": "NAMED_DATA", "score": 0.6075114607810974, "start": 1038, "end": 1078, "probe_score": 0.8369, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " job training.\n\n   - **Sub-component 1.2:** An assessment of data gaps will be conducted to identify and develop solutions to build\n\nany required data infrastructure needed to fully design and operationalize the M&E framework. This will\ninclude: (i) T.A in improving the frequency or depth of demand-side data collected, including adding additional\nmodules to already available surveys building on the experience of the EU-GIZ demand side study of 2017;\n(ii) assisting in the development and consolidation of data currently missing; and (iii) adding relevant indicators\nor modules to supply-side data templates and supervisory templates collected by various agencies;\n\n   - **Sub-component 1.3:** Support the improvement of operating environment of the NFIS implementation unit. The\n\nunit will procure the required equipment and IT, both software and hardware in order to enhancing the data\ncollection, processing and analysis. The sub-component will cover the hiring of experts to support this\nimprovement process.\n\n   - Key outputs envisioned for this component include (i) an operational M&E framework; (ii) the delivery of\n\nmultiple trainings and workshops to build capacity; (iii) data collection templates to consolidate financial\ninclusion data; (iv) the development of a Secretariat policy toolkit (including an M&E tracker to track the\nperformance and completion of NFIS activities); and (v) facilitation of M&E reports, implementation reports\n\n\nApr 05, 2017 Page 7 of 11", "output": {"entities": {"named_data": ["EU-GIZ demand side study"], "descriptive_data": ["demand-side data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000013", "page": 6, "chunk": 1, "title": "Jordan - Promoting Financial Inclusion Policies and Regulations in Jordan Project : Project Information Document (Concept Stage) - Promoting Financial Inclusion Policies and Regulations in Jordan - P163719", "pdf_url": "http://documents.worldbank.org/curated/en/280421491408992654/pdf/IL-AISPID-CP-P163719-04-05-2017-1491408966691.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "demand-side data", "label": "DESCRIPTIVE_DATA", "score": 0.5255459547042847, "start": 293, "end": 309, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "EU-GIZ demand side study", "label": "NAMED_DATA", "score": 0.7858523726463318, "start": 420, "end": 444, "probe_score": 0.0187, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouthern Niger Connectivity and Integration Project (P179770)\n\n\n**Table 4 – Economic Analysis of RN1 Maradi-Zinder Road Section Investment (with SPC and road safety benefits)**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Designation|Linear<br>(km)|Investments<br>(USD million)|IRR with road<br>safety (%)|NPV with road<br>safety (US$ million)|IRR with High<br>SPC (%)|NPV with High<br>SPC (US$ million)|IRR with<br>Low SPC (%)|NPV with Low<br>SPC (US$ million)|\n|---|---|---|---|---|---|---|---|---|\n|**Maradi-**<br>**Zinder**|232.89|248.26|26.4|581.2|24.7|516.9|25.5|549.1|\n\n\n58. **Economic analysis of feeder and rural roads.** The RED Model was applied for the feeder and rural road rehabilitation\nworks. Transport cost reductions are assumed on the basis that the IRI will decrease from about 16 to 6 meters per\nkilometer for road segments that will become 7.00-meter-wide laterite roads. Local traffic is expected to increase by 6.2\npercent per year. In addition to an analysis of time savings and vehicle operating costs, agricultural benefits from improved\naccess to sales markets in production areas and thus increased income from the sale of agricultural products. Field surveys\nat sales markets for key value chains showed that improved accessibility to production sites would lead to the use of faster\nand larger means of transport. This will reduce", "output": {"entities": {"named_data": [], "descriptive_data": ["Field surveys\nat sales markets"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000184", "page": 33, "chunk": 0, "title": "Niger - Southern Niger Connectivity and Integration Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099043025161072911/pdf/BOSIB-850e0c11-07c1-4c9c-8d44-4286704221bd.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Field surveys\nat sales markets", "label": "DESCRIPTIVE_DATA", "score": 0.7136624455451965, "start": 1169, "end": 1199, "probe_score": 0.1276, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "argue that they constitute better proxies for schooling quality and illustrate their\nsignificant contribution to economic growth.\n\n\nOne methodological difficulty with using test results is that they are not available\nas a panel. Internationally comparable testing has been introduced relatively recently and\nonly for a relatively small group of countries. Another, more substantive issue is that it is\nfar from clear that they represent a better measure of schooling quality than attendance\nfigures. For one, basic literacy and math proficiency may only be part of what makes\nschooling quality, and additional components of school experience could be relevant.\nMoreover, the operational concept of school quality may differ across countries, which\nmakes any statistical analysis very tentative. For example, it is conceivable that\nknowledge of foreign languages is a potentially important output of schooling, especially\nin open economies. Or, knowledge of national history may be essential in some countries,\nparticularly those engaged in nation building, but less so in other countries (see Miguel\n2003, who shows the importance of a national curriculum for nation-building efforts by\ncontrasting the experiences of Kenya and Tanzania). Schooling may instill social norms,\ndevelop work habits, and inculcate values (see Gradstein and Justman 2002, and\nreferences therein). As has been noted in the literature, these factors may have various\nbeneficial effects, such as on crime reduction, better informed fertility choices, political\nparticipation, etc., see Haveman and Wolfe (1984). These arguments suggest that\nstandard measures such as school attendance may also have an appeal as quality-related.\nThis is perhaps one of the reasons for their adoption as human capital indicators by\ninternational development agencies. <sup>2</sup> [^2: Indeed, an ambitious program for economic and social world development, the Millennium\nDevelopment Goals, includes achieving universal primary education by the year 2015 as one of its\nobjectives.]\n\n\nThe rest of the paper proceeds as follows. Section 2 sets the stage by describing\nthe intertemporal trends in schooling, educational spending, and incomes. Section 3 then\npresents a", "output": {"entities": {"named_data": [], "descriptive_data": ["test results", "attendance\nfigures"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002550", "page": 4, "chunk": 0, "title": "wps3245educational", "pdf_url": "https://local/prwp/wps3245educational.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "test results", "label": "DESCRIPTIVE_DATA", "score": 0.5311513543128967, "start": 173, "end": 185, "probe_score": 0.5182, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "attendance\nfigures", "label": "DESCRIPTIVE_DATA", "score": 0.534382700920105, "start": 480, "end": 498, "probe_score": 0.9156, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " it is\nprovided, allows over a third of low-income <sup>10</sup> [^10: Those that are below the poverty line]\nhouseholds to de facto live above the poverty line.\nIn Slovakia this effect is the most dramatic –\nsubsidized housing allows an additional 46% of the\nrefugee population to escape poverty.\n\n\n**<u>DECREASE IN THE REFUGEE POVERTY RATE AS A RESULT</u>**\n**OF ACCOMMODATION RENT SUPPORT, %** <sup>**1,2,3**</sup> [^2: Results for the Czech Republic not individually presented due to\nsampling limitations] [^3: Accommodation rent support has been calculated as the difference\nbetween the actual equivalized accommodation expense and the\nmedian equivalized market rent in the region]\n\n\n\nNot adoping\n\ncoping\nstrategies\n\n\n\nStress coping\n\nstrategies\n\n\n\nCrisis coping\n\nstrategies\n\n\n\nEmergency\n\ncoping\nstrategies\n\n\n\nWithout accommodation rent\nsupport\n\n\n\n1. The statistic on emergency strategies may have been affected by\nthe survey wording on illegal work\n\n\nThe Ukrainian refugee population also faces\nfinancial barriers to access critical services: one in\nten households have no health insurance and 22 %\nof those surveyed answered that they cannot afford\nfees at local health care clinics. Households that\ncontain a member with a disability are also more\nlikely to be below the poverty line. This group’s\npoverty rate stands at 59% versus 43% for\nhouseholds with no members with disabilities.\n\n\n**Support with accommodation expenses – an**\n**important vulnerability shield**\nOverall, almost half (48%) of refugee households in\nthe region report receiving accommodation or\nhousing assistance. Twenty percent are living in\n\n\n\n\n\n\n\n\n\n\n\n\n\nWith accommodation rent support\n\n\n\n\n\n\n\nBulgaria Hungary Poland Romania Slovakia Region\n\n\n1. Calculations for Moldova were not conducted, as this country is not\nincluded into the <u>[EU statistics on income and living conditions (SILC)](https://ec.europa.eu/eurostat/web/microdata/european-union-statistics-on-income-and-living-conditions)</u>\n<u>[survey,", "output": {"entities": {"named_data": ["EU statistics on income and living conditions"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 4, "chunk": 1, "title": "3", "pdf_url": "https://local/jad_paddy_docs/3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "EU statistics on income and living conditions", "label": "NAMED_DATA", "score": 0.8749122619628906, "start": 1816, "end": 1861, "probe_score": 0.9743, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Methodology**\n\n\nIn each city, we have collected built environment audits for 50 stations throughout the\n\nmetropolitan area. <sup>39</sup> Each station is assessed based on seven objective parameters (availability\n\n\nof lighting, walking path and security, the openness and visibility of the station, the\n\n\ncrowdedness of the station and the presence of women – see section 2.1 for more details). Each\n\n\nof these parameters is assessed on a 4-item scale, and we compute a general index of safety for\n\n\neach station by averaging the score of these 7 parameters. The final indicator provides an index\n\n\nof safety with values from 0 (worse) to 100% (best).\n\n\nIn order to pair each household with a measure of safety in their neighborhood, we assign to\n\n\neach household location the average index of safety of the three closest audited stations.\n\n\n39 In Amman, there are a total of 49 station as one was considered as an outlier during the data cleaning phase.\n\n\n46", "output": {"entities": {"named_data": [], "descriptive_data": ["built environment audits"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000947", "page": 47, "chunk": 0, "title": "idu09fd403a504f570402a08c2e0e32140f5e54e", "pdf_url": "https://local/prwp/idu09fd403a504f570402a08c2e0e32140f5e54e.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "built environment audits", "label": "DESCRIPTIVE_DATA", "score": 0.6341531872749329, "start": 50, "end": 74, "probe_score": 0.5669, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "المشـاركين، وعـدد التـدريب، خطـة ومحتويات التقديرية، والتكاليف التدريب، فيها سيجرى التي والمؤسسات ،التفقدية\n\n.شروعالم لمكونات الفعلي التنفيذ في المكتسبة المعارف وتجسيد التقديرية، والتكاليف\n\n\n6.\nهذه استخدام ويتم المشروع، تنسيق وحدة على المشروع تنفيذ سير عن فصلية تقارير المنفذون الشركاء سيعرض\n\nالعمل سير عن (سنوية نصف )أشهر ستة كل تقارير في التقارير هذه تجميع وسيتم. للتنفيذ المالية وزارة متابعة في التقارير\n\n. الدولي بنك ال إلى المشروع تنسيق وحدة من بالمشروع\n\n\n7.\nوتستحق جيدا أداء تحقق التي المكونات على الطوارئ لميزانية تخصيص ألي أساسا المدة منتصف مراجعة ستتيح\n\n. مناسبة غير صارت التي أو إنجازها مواعيد عن تتخلف التي األنشطة عن بعيدا الميزانية تخصيص أو الموارد، من المزيد\n\nيقـدم أن لضمان فرصة وسيتيح والمشتريات", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000059", "page": 60, "chunk": 0, "title": "West Bank and Gaza - Capacity-Building for Palestinian Economic and Regulatory Institutions Project", "pdf_url": "http://documents1.worldbank.org/curated/en/396821468329693397/pdf/532780PAD0ARAB1CUMENTS0SEPT02902010.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Appendices**\n<u>Paving pathways for inclusion: A global overview of refugee education data</u>\n\n\n**Access**\n\n\n**Table A2.3:** Access questions by data collection type\n\n\n**Access questions by data collection type**\nNumber of questionnaires with access questions by data collection exercise type\n\n\n100 200\n\n\n\nEnrolment (211)\n\n\nBarriers to Access (146)\n\n\nAttendance (364)\n\n\nAttainment (569)\n\n\n_Source:_ Compiled by authors.\n\n\n\n\n\nCensuses Household\n\nsurveys\n\n\n\nInternational\n\nlearning\nassessments\n\n\n\nNational\nlearning\nassessments\n\n\n\nEMIS School\n\nbased\nsurveys\n\n\n\nOther\n\n\n\n**Table A2.4:** Access questions by target population\n\n\n**Access indicators compared across target populations: refugees vs general population**\n\n\nEducational Attainment: Child or Youth\n\n\nEducational Attainment: Respondent\n\n\nAccess to Language Instruction\n\n\nAccess to Remote Learning\n\n\nEnrolment: Current Year\n\n\nEnrolment: Previous Year\n\n\nAttendance: Current Year\n\n\nAttendance: Previous Year\n\n\nReasons for Non−attendance\n\n\nReasons for Non−enrolment\n\n\n0% 20% 40% 60% 80%\n\n\n\n_Source:_ Compiled by authors.\n\n\n\nGeneral population Refugees\n\n\n\n**69**", "output": {"entities": {"named_data": ["EMIS School\n\nbased\nsurveys"], "descriptive_data": ["Household\n\nsurveys", "International\n\nlearning\nassessments", "National\nlearning\nassessments"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000382", "page": 68, "chunk": 0, "title": "Paving pathways for inclusion: a global overview of refugee education data", "pdf_url": "https://reliefweb.int/attachments/31f00be7-0481-4224-80ce-378c049a02d4/Paving%20pathways%20for%20inclusion%20--%20a%20global%20overview%20of%20refugee%20education%20data.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Household\n\nsurveys", "label": "DESCRIPTIVE_DATA", "score": 0.6435027122497559, "start": 437, "end": 455, "probe_score": 0.4794, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "International\n\nlearning\nassessments", "label": "DESCRIPTIVE_DATA", "score": 0.6565861701965332, "start": 459, "end": 494, "probe_score": 0.4794, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "National\nlearning\nassessments", "label": "DESCRIPTIVE_DATA", "score": 0.5608672499656677, "start": 498, "end": 527, "probe_score": 0.4794, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "EMIS School\n\nbased\nsurveys", "label": "NAMED_DATA", "score": 0.7087201476097107, "start": 531, "end": 557, "probe_score": 0.7194, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "McKenzie, D. and Sansone, D. (2017). Man vs. Machine in Predicting Successful Entrepreneurs:\n\n\nEvidence from a Business Plan Competition in Nigeria. _World Bank Policy Research Working_\n\n_Paper 8271_ .\n\n\nMenzel, A. and Woodruff, C. (2021). Gender wage gaps and worker mobility: Evidence from the\n\n\ngarment sector in Bangladesh. _Labour Economics_, 71(May):102000.\n\n\nMikolajczak, M., Brasseur, S., and Fantini-Hauwel, C. (2014). Measuring Intrapersonal and En\n\nterpersonal EQ: The Short Profile of Emotional Competence (S-PEC). _Personality and Indi-_\n\n_vidual Differences_, 65:42–46.\n\n\nNanda, R. (2016). Financing High-potential Entrepreneurship. _IZA World of Labor_, 252:1–10.\n\n\nO’Brien, P. (1984). Procedures for Comparing Samples with Multiple Endpoints. _Biometrics_,\n\n\n40(4):1079–1087.\n\n\nRahman, L. and Rao, V. (2004). The Determinants of Gender Equity in India: Examining Dyson\n\n\nand Moore’s Thesis with New Data. _Population and Development Review_, 30(2):239–268.\n\n\nRotter, J. B. (1966). Generalized Expectancies for Internal versus External Control of Reinforce\n\nment. _Psychological Monographs:_ _General and Applied_, 80(1):1–27.\n\n\nSabatier, M. (2015). A Women’s Boom in the Boardroom: Effects on Performance? _Applied_\n\n_Economics_, 47(26):2717–2727.\n\n\nSchochet, P. Z. (2008). Technical Methods Report: Statistical Power for Regression Discontinuity\n\n\nDesigns in Educational Evaluations. _NCEE Working", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001147", "page": 38, "chunk": 0, "title": "idu0f776bf4e0723e0481f09732069b5c938c282", "pdf_url": "https://local/prwp/idu0f776bf4e0723e0481f09732069b5c938c282.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and the use of climate friendly technologies. This\nincludes the use of steel beams, instead of timber beams for construction.\n\n\n**V.** **KEY RISKS**\n\n\n126. **The macroeconomic risk: Substantial.** The recent COVID-19 pandemic is expected to significantly disrupt\neconomic activity and raise the macroeconomic risk. To date, official figures indicate that Uganda has been able\n\n\nPage 40 of 96", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["official figures"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 45, "chunk": 2, "title": "Uganda - Secondary Education Expansion Project", "pdf_url": "http://documents.worldbank.org/curated/en/406361595815248191/pdf/Uganda-Secondary-Education-Expansion-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "official figures", "label": "VAGUE_DATA", "score": 0.5399406552314758, "start": 325, "end": 341, "probe_score": 0.1001, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**1** **INTRODUCTION**\n\n\nMore rapid green growth is inconceivable without innovation. Frontier innovations shift out production\npossibilities, allowing the production of more output and newer, more environmentally-friendly outputs\nwith fewer or different inputs. Innovations thereby help to decouple growth from natural capital depletion\nand environmental pollution, for example towards more resource-efficient and cleaner technologies.\nSome innovations can directly increase resilience to environmental shocks. Catch-up innovations, that\nmake the use of existing technologies more widespread by adapting them to local contexts, are even more\nimportant for all countries. They typically reduce production costs and increase enterprise\ncompetitiveness, and are lower risk than frontier innovations. The introduction of new products,\nprocesses, business models and other organizational methods, and marketing techniques, whether through\nfrontier or catch-up innovation, in principle contribute to the expansion of existing markets and the\ncreation of new markets, in the process increasing the job content and poverty alleviation of growth.\n\n\nThis paper examines existing patterns of green innovation, to what extent innovation policies should be\ndesigned differently to address the green growth agenda, and what policy modifications can best help\nyield short-run or at least medium-term impact. The paper discusses the implications of the inherent\n‗double externality‘ of knowledge-related market failures compounding the traditional environmental\nexternalities. It motivates appropriate policy action in the absence of global agreements, answering the\nquestion of why developing countries should undertake green innovation policies, and what types of\npolicies should be pursued depending on existing technological capabilities.\n\n\nIn contrast to most recent empirical analyses that use older patent data to 2005 or at most to 2008 to\ncharacterize international patterns of green frontier innovation (OECD 2011a, Dechezleprêtre et al. 2011,\nAghion et al. 2011), this paper uses patent data to end-2010 and explores patterns across developing\ncountries in greater detail. This matters since there have been significant increases in green patenting over\nthe 2006-2010 period.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["patent data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005107", "page": 3, "chunk": 0, "title": "wps5932", "pdf_url": "https://local/prwp/wps5932.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "patent data", "label": "VAGUE_DATA", "score": 0.5807228088378906, "start": 1891, "end": 1902, "probe_score": 0.7364, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "supplies; the ICR (pp. 14-15) states that better coordination of procurement between UNICEF and EPHI could\nhave resulted in a more timely completion of a micronutrient survey and therefore better assessment of project\nperformance.\n\n\n**c. M&E Utilization:**\n\n\nOperational research studies supported under the project and conducted by the Ethiopia Health and Nutrition\nInstitute generated findings that were used by the government to understand and discuss project performance,\nguide implementation, and inform a new National Nutrition Plan (ICR, p. 14). These included studies on\ncommunity-based nutrition, school-based health and nutrition education, iodized salt coverage, food\nconsumption, and iron folate supplementation for pregnant women (ICR, p. 25).\n\n\nM&E Quality Rating: Substantial\n\n\n**11. Other Issues**\n\n**a. Safeguards:**\n\n\nThe project was rated environmental category “C” and did not trigger any safeguard policies. According to the\nICR (p. 15), no negative environmental impact was identified during project implementation.\n\n\n**b. Fiduciary Compliance:**\n\n\nEarly in the project period, key budgeting, internal controls, financial reporting, and external auditing issues were\nidentified, and an action plan for improvement was developed at the mid-term review in 2011. Nutrition\ncoordinators were hired to work at the regional level, training was provided for financial managers in 144\nworedas, and federal-level accountant training was provided to cascade training to woreda accountants. As a\nresult, statements of expenses were settled more quickly, and overall disbursement patterns improved through\nthe remainder of the project period. An in-depth Financial Management Supervision Report in March 2014\nconfirmed adequate financial management under the project.\n\n\nProcurement processes were cumbersome and slow, resulting in delays in the arrival of goods to end users (ICR,\np. 12). After the mid-term review, improvements were implemented (see Section 9b). However,", "output": {"entities": {"named_data": [], "descriptive_data": ["micronutrient survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017060", "page": 6, "chunk": 0, "title": "Ethiopia - Nutrition Project", "pdf_url": "https://documents.worldbank.org/curated/en/711311468190148402/pdf/ICRR14776-P106228-Box393191B-PUBLIC.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "micronutrient survey", "label": "DESCRIPTIVE_DATA", "score": 0.8997753262519836, "start": 154, "end": 174, "probe_score": 0.2795, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Shall meet the requirements as stated in Regulations**\n\n\n**Prior Review Thresholds:** The details of the Procurement review / oversight are defined in the Annex\nII of the Regulations for borrowers. The following would be subject to Prior review of the Bank\nregardless of the Method of selection:\n\n\n(a). **Consulting Firm** : First procurement under the project irrespective of value and all procurements\nestimated to cost more than USD 0.5 million.\n(b). **Individual Consultant** : all procurements estimated to cost more than USD 0.2 million\n\n\n**Terms of Reference (ToR) for all consultant contracts shall be furnished to the Bank for its prior**\n**review and No Objection.**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:021258", "page": 3, "chunk": 1, "title": "Kenya - AFRICA- P153349- National Agricultural and Rural Inclusive Growth Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/994351586891598590/pdf/Kenya-AFRICA-P153349-National-Agricultural-and-Rural-Inclusive-Growth-Project-Procurement-Plan.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "(for return migrants) and at the time of the survey in 2012 (for current migrants). This\n\nallows us to account for both forced return migration and planned return.\n\n\nWhile conflict occurrence in host countries constitutes a strong predictor of return\n\nmigration, an empirical concern would be if conflicts might have consequences on the\n\nEgyptian economy through, for instance, changes in trade flows, foreign direct invest\nments, or remittances. To address this concern, we additionally rely on data from the\n\nWorld Bank Development Indicators in order to control for FDI (% of GDP), remit\ntances (% of GDP), and the exports and imports of goods and services (% of GDP)\n\nin Egypt in equation (4). We show in the robustness checks section that our results\n\nare robust to these two checks, which provides support to the exclusion restriction of\n\nconflict occurrence.\n\n#### **5 Empirical findings**\n\n###### **5.1 Does the legal status of migrants matter upon return?**\n\n\n**5.1.1** **Hourly** **Wages** **upon** **Return**\n\n\nIn Table 4, we depart from simple OLS regressions to estimate the effect of return\n\nmigration on wages in 2012 upon return. We are interested in examining whether\n\nthe legal status of migrants has a differential effect on their wage premium upon\n\nreturn. In column (1), we focus on the full sample of non-migrants and returnees.\n\nIn column (2), we focus on the subsample of documented migrants compared to non\nmigrants, and in column (3), we compare undocumented migrants to non-migrants.\n\nWithout accounting for any of the selection issues presented earlier, Table 4 shows,\n\nthat controlling for individual and job characteristics, return migration is associated\n\nwith a significant wage premium. However, when we disentangle the effects by legal\n\nstatus, the", "output": {"entities": {"named_data": ["World Bank Development Indicators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002040", "page": 20, "chunk": 0, "title": "return migrants and the wage premium does the legal status of migrants matter", "pdf_url": "https://local/prwp/return-migrants-and-the-wage-premium-does-the-legal-status-of-migrants-matter.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Bank Development Indicators", "label": "NAMED_DATA", "score": 0.8372451066970825, "start": 511, "end": 544, "probe_score": 0.9847, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2018-12-21||2019-02-03||||||||2019-03-05||2019-04-09||2019-05-21||\n|UG-PSFU-89003-CS-CQS /<br>Environmental and Social<br>Audit of UBFC and UHTTI<br>Construction Projects<br>|IDA / 52690|Project Implementation|Post|Consultant<br>Qualification<br>Selection|Open - National<br>||0.00|Pending<br>Implementation|2018-12-03||2018-12-07||2019-01-11||||||||2019-02-15||2019-03-22||2019-09-18||\n|UG-PSFU-89010-CS-CQS /<br>Performance Assessment of<br>the MGF Component<br>|IDA / 52690|Matching Grant Program for<br>MSMEs|Post|Consultant<br>Qualification<br>Selection|Open - National<br>||0.00|Pending<br>Implementation|2018-12-04||2018-12-25||2019-02-07||||||||2019-03-09||2019-04-13||2019-10-10||\n|UG-PSFU-89011-CS-CQS /<br>Performance Assessment of<br>the MGF Component<br>|IDA / 52690|Matching Grant Program for<br>MSMEs|Post|Consultant<br>Qualification<br>Selection|Open - National<br>||0.00|Pending<br>Imple", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012112", "page": 9, "chunk": 9, "title": "Uganda - AFRICA EAST- P130471- Competitiveness and Enterprise Development Project (CEDP) - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/381481620740311721/pdf/Uganda-AFRICA-EAST-P130471-Competitiveness-and-Enterprise-Development-Project-CEDP-Procurement-Plan.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "research seminars**\n**and workshops**, both in Addis and in different parts of the country, to promote dialogue and discussion.\nAnother could be an **online portal** for refugee-related research, designed to make it easy to access and\nnavigate all the research that exists. Thought would need to be given as to how to embed this appropriately\nin Ethiopian institutions to increase the chances of this being a sustainable initiative.\n\n\nConsideration should also be given to developing a **centralised repository** for research data, in line with\nthe global initiative being carried out by the World Bank and UNHCR. If such data could be made more\navailable, this should reduce the need for duplication of effort and allow for greater triangulation of research.\nWhile privacy and data sharing considerations would need to be carefully considered to protect all parties,\nthis should not be an obstacle to developing an appropriate solution.\n\n\nIdeally, all of this work should sit within a **common framework** that both enables joint monitoring of effort\nand progress, and allows for flexibility. Such a framework should also encourage more joint evaluations and\nstudies to reduce overlapping efforts.\n\n\nThere is a need for all involved in research to reflect on the linkages and interdependencies that exist\nbetween the specific research work they are conducting and wider research on similar topics and the policy\nenvironment. By so doing, it could be possible to understand the specific issues at hand in a more **holistic**\n**manner** . The greater emphasis on area-based planning envisaged by the NCRRS suggests work that\nconsiders these linkages more fully will be increasingly important.\n\n\n\n11 12", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["research data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001587", "page": 9, "chunk": 4, "title": "Towards a common research agenda- A research synthesis paper to inform the implementation of the Global Refugee Compact", "pdf_url": "https://reliefweb.int/attachments/f5e7545d-01a8-3674-8598-3114e76fdbd7/Towards-a-common-research-agenda-ONLINE-FINAL-1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "research data", "label": "VAGUE_DATA", "score": 0.6555716395378113, "start": 517, "end": 530, "probe_score": 0.0335, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Analysis of consumer<br>affordability of services being<br>provided by the project and<br>structure of subsidy payments.| Project preparation fieldwork gathered preliminary estimates on<br>affordability levels and consumer characteristics, mainly through<br>stakeholder interviews in a sample of nine localities in both urban and<br>rural areas. This was combined with limited secondary source data<br>available to develop an understanding of household demand, i.e.<br>preferences, affordability constraints, willingness to pay.<br> Although no widely recognized standards exist on the proportion of<br>household income that should be expended on SWM services, it is<br>proposed that SWM costs in a low income country might consume two<br>to three percent of income1, which is in line with the estimates and<br>projections presented here.<br> The Guidelines for SWM Tariff and Fee Collection Systems that will<br>be developed is expected to complement these initial data through<br>further primary data and analysis and, as appropriate, identify cross-<br>subsidization mechanisms to alleviate burden on users with lower<br>affordability levels.<br> Focus groups with residents during project preparation indicate that<br>users are willing to pay for better quality service. Discussions<br>identified specific areas of service improvement that are expected to<br>improve user satisfaction and WTP, e.g. street cleanliness.|\n|---|---|\n|Consideration of realistic<br>objectives given the tight 4 year<br>time frame|OBA Targets were designed to take into account the different approaches<br>that will be necessary in different areas to achieve desired results in SWM<br>service provision, based on consultations with JSC-H&B, JSCs,<br>", "output": {"entities": {"named_data": [], "descriptive_data": ["secondary source data"], "vague_data": ["primary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000056", "page": 7, "chunk": 0, "title": "Middle East and North Africa - Output-Based Aid Pilot Solid Waste Management Project", "pdf_url": "http://documents1.worldbank.org/curated/en/388311468275943106/pdf/84657-PAD-P132268-Project-Commitment-Paper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "secondary source data", "label": "DESCRIPTIVE_DATA", "score": 0.6244382858276367, "start": 379, "end": 400, "probe_score": 0.7632, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "primary data", "label": "VAGUE_DATA", "score": 0.5488924384117126, "start": 994, "end": 1006, "probe_score": 0.6081, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " are able to get access to services during household surveys. Existing services</mark>\n<mark>were denied in the community due to discrimination/exclusion (16%), documentation was</mark>\n<mark>required to have access to services (20%) the assistance was not free (20%) and the assistance</mark>\nwas not what the community needed (29%).\n\n\n\n<mark>The different groups that were unable to have</mark>\n<mark>access to the existing services were child-headed</mark>\n<mark>households, (16%), children at risk headed</mark>\n<mark>households</mark> <mark>(10%),</mark> <mark>Elderly</mark> <mark>person</mark> <mark>headed</mark>\n<mark>households (16%), female-headed households</mark>\n<mark>(17%), persons with disability (14%), persons with</mark>\n<mark>life-threatening health issues (4%), substance</mark>\n<mark>abusers (9%) and women at risk headed household</mark>\nat (9%).\n\n\n\n_“The people who have more power_\n_and have more money they will win_\n_the dispute”_\n\n\n_UR Male HH, Faryab, January_\n\n\n_“The new government do not have_\n_ability to solve the problems they_\n_are illiterate they do not have_\n_familiarity with documentation”_\n\n\n\n<mark>Although 75% of the population access basic</mark> _UR Male HH, Badakhshan February_\n<mark>services based on Key Informant Interviews, only</mark>\n<mark>2% of respondents indicated that there is access to child protection for prevention and", "output": {"entities": {"named_data": [], "descriptive_data": ["household surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000979", "page": 7, "chunk": 1, "title": "Afghanistan: Protection Analysis Update 2022 - Quarter 1", "pdf_url": "https://reliefweb.int/attachments/916826fb-9b1b-4c47-9cf4-d6ed5b7f11ba/protection_analysis_update_pau_-_q1_2022.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household surveys", "label": "DESCRIPTIVE_DATA", "score": 0.9036945700645447, "start": 43, "end": 60, "probe_score": 0.3639, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSocio-economic Inclusion of Refugees & Host Communities in Rwanda\nProject Phase II (P509677)\n\n\nhealth facilities and market-linked skills training. <sup>7</sup> [^7: African Development Bank, UNHCR, IGAD & EAC (2024) _Regional Report:_ _Regional Program on Enhancing the Investment Climate for the_\n_Economic Empowerment of Refugee, Returnee, and Host/Return Community Women in the East and HoA and Great Lakes Region._] The 2024 Rwanda FinScope survey also showed relatively low takeup of finance for investments or credit for productive purposes by Rwandese and refugees, limiting business and\nincome-generating opportunities. <sup>8</sup> [^8: Access to Finance Rwanda (2024) _FinScope 2024 Report_ . The report shows high levels of financial inclusion but low usage of financial services.]\n\n7. **High poverty rates and minimal economic activity in the hosting districts constrain self-reliance prospects**\n**for refugees and host communities alike.** The national non-monetary poverty rate in Rwanda of 30 percent is\nexceeded in all five districts that host refugee camps. Gisagara, where the Mugombwa camp is located, ranked as\nthe poorest district in the country in the 2022 Census at 45 percent. <sup>9</sup> [^9: Non-monetary poverty for the other four host districts is: Nyamagabe (Kigeme camp) 39 percent, Gatsibo (Nyabiheke Camp) 37 percent,\nKirehe (Mahama camp) 35 percent and Karongi (Kiziba camp) 34 percent. Data is from the 2022 Census.] By comparison, the City of Kigali has the lowest\npercentage of poor people (9.5 percent). Core elements of the non-monetary poverty index include health,\neducation and living standards, highlighting the dual need to: (a) invest in economic opportunity and access to\nservices in the hosting districts; and (b) at the same time, facilitate refugee mobility out of the camps and rural areas\ninto urban centers, where more opportunities are", "output": {"entities": {"named_data": ["2024 Rwanda FinScope survey", "2022 Census"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000188", "page": 18, "chunk": 0, "title": "Rwanda - Second Phase of the Socio-economic Inclusion of Refugees and Host Communities Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099102225213540444/pdf/BOSIB-3f2311b3-9a20-44d3-b637-b3b2b3d21695.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2024 Rwanda FinScope survey", "label": "NAMED_DATA", "score": 0.8391026258468628, "start": 444, "end": 471, "probe_score": 0.9978, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2022 Census", "label": "NAMED_DATA", "score": 0.6883416771888733, "start": 1195, "end": 1206, "probe_score": 0.9808, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "hypothesized as follows:\n\n\n  - _Hypothesis_ _1_ _(Extortion_ _to_ _Fear):_ Deportees who were extorted while migrating are\n\nmore likely to avoid a range of situations out of fear in their origin country compared\n\nto deportees who were not victims of such abuse.\n\n\n  - _Hypothesis_ _1a_ _(Extortion_ _to_ _Economic_ _Hardship):_ Deportees who were extorted while\n\nmigrating are more likely to experience economic hardship in their origin country than\n\nthose who were not extorted.\n\n\n  - _Hypothesis_ _2_ _(Fear_ _to_ _Engagement):_ Deportees avoiding activities in their origin coun\ntry because of fear are less likely to be politically engaged compared to those who are\n\nnot avoiding activities out of fear.\n\n\n  - _Hypothesis_ _2a_ _(Economic_ _Hardship_ _to_ _Engagement):_ Deportees who experience eco\nnomic hardship in their origin country are more likely to be politically engaged than\n\ndeportees who do not experience economic hardship.\n\n\nIf fear and economic hardship both mediate the relationship between extortion and po\nlitical engagement, a final hypothesis should concern which mechanism plays a larger role. If\n\nthe emotional consequences of extortion are larger than the financial ones, extortion should\n\nbe correlated with decreased rather than increased levels of political engagement. However,\n\nwe have no prior reason to believe that one mechanism is more or less important than the\n\nother. Thus, any conclusions about the overall relationship between extortion and political\n\nengagement is exploratory.\n\n#### **4 Research Design: Data and Methods**\n\n###### **4.1 Deportee Survey**\n\n\nWe employ data from an original survey of recent migrants deported from from the United\n\nStates and returned to Guatemala (“deportees” or “returnees”", "output": {"entities": {"named_data": ["Deportee Survey"], "descriptive_data": ["original survey of recent migrants"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000637", "page": 12, "chunk": 0, "title": "idu02026f74207fd304e610a1160b8141ae76d28", "pdf_url": "https://local/prwp/idu02026f74207fd304e610a1160b8141ae76d28.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Deportee Survey", "label": "NAMED_DATA", "score": 0.80329829454422, "start": 1581, "end": 1596, "probe_score": 0.1532, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "original survey of recent migrants", "label": "DESCRIPTIVE_DATA", "score": 0.8190979957580566, "start": 1624, "end": 1658, "probe_score": 0.0079, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "accordance with the appropriate standards. The Government Financial Management Information System\n(GFMIS) is used for budget preparation.\n\n\n10. The proposed Program will be included in the annual budget of the state under the respective\nministries and independent institutions’ budgets, starting FY17 and up to 2020 (the Program period).\nBudgets of respective ministries and IPUs will include budget line items to reflect the Program proceeds.\n\n\n11. Budget classification systems allow tracking the Program expenditures according to: (a)\nadministrative units (participating ministries <sup>40</sup> [^40: MoITS and MOL.] and IPUs <sup>41</sup> [^41: JIC, Technical and Vocational Education and Training Fund, and JSMO.] ); (b) economic categories (recurrent, capital\nspending, and so on); (c) functions (health, education, and so on); and (d) government programs,\nsubprograms, and activities. The budget is comprehensive, covering the activities of the central government\nand independent institutions. The budget is published on the GBD website, while final accounts and the\nmonthly General Government Finance Bulletin (includes budgetary Government finance statistics\naggregated according to the economic and functional classifications) are published on the GBD website\n(http://www.gbd.gov.jo).\n\n\n12. Jordan adopts an early budget preparation calendar (starts in January of each year) that allows more\ntime for budget policy and strategy analysis and development. The calendar comprises four distinct phases\ncovering: (a) initial strategic review and planning; (b) medium-term budget preparation; (c) draft budget\nfinalization; and (d) budget approval. This would include preparation and discussion of (a) budget policy\nand priorities paper, which contains an updated macro-fiscal outlook and sets out the underlying policy\nstance and spending priorities to be addressed in the preparation of the budget, and (b) Medium-Term\nExpenditure Framework.\n\n\n_Budget Execution_\n\n\n13. **Jordan has a robust system", "output": {"entities": {"named_data": [], "descriptive_data": ["budgetary Government finance statistics"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 75, "chunk": 0, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "budgetary Government finance statistics", "label": "DESCRIPTIVE_DATA", "score": 0.8599792122840881, "start": 1129, "end": 1168, "probe_score": 0.0516, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "we provide unambiguous support for the sensitivity of the plot-level IR to the choice of the method\nby which maize production and yield are computed. While farmer-reported production-based\nmaize yield regressions consistently imply diminishing returns to GPS-based plot area, the\ncomparable regressions estimated with maize yields based on sub-plot crop cutting, full-plot crop\ncutting, and high-resolution satellite imagery-based remote sensing point towards constant returns\nto scale.\n\n\n<mark>In view of the aforementioned hypotheses put forth for the IR, it is important to note that the results</mark>\n<mark>are robust to the inclusion of objective measures of soil fertility, maize genetic heterogeneity and</mark>\n<mark>edge effects at the plot-level; a rich set of plot, household and plot manager attributes; as well as</mark>\n<mark>household and parcel fixed effects in select specifications that exploit the panel nature of the data.</mark>\n<mark>In other words, irrespective of the exhaustive list of controls and panel estimation, the IR exists</mark>\n<mark>while using farmer-reported maize production, and ceases to do so when maize yield is anchored</mark>\n<mark>in objective measurement methods. In fact, the IR persists throughout the distribution of plot-level</mark>\n<mark>maize yields that are based on farmer-reported production, while constant returns to scale prevails</mark>\n<mark>across the productivity distribution when one uses objective yield measures.</mark>\n\n\n<mark>Our core finding is driven by persistent over-estimation of farmer-reported maize production and</mark>\n<mark>yield vis-à-vis their crop cutting-based counterparts, particularly in the lower half of the plot area</mark>\n<mark>distribution.</mark> <mark>Though our findings contribute to a larger", "output": {"entities": {"named_data": [], "descriptive_data": ["farmer-reported maize production"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000209", "page": 5, "chunk": 0, "title": "could the debate be over errors in farmer reported production and their implications for the inverse scale productivity relationship in uganda", "pdf_url": "https://local/prwp/could-the-debate-be-over-errors-in-farmer-reported-production-and-their-implications-for-the-inverse-scale-productivity-relationship-in-uganda.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "farmer-reported maize production", "label": "DESCRIPTIVE_DATA", "score": 0.6666443943977356, "start": 1082, "end": 1114, "probe_score": 0.6846, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Asylum Levels and Trends in Industrialized Countries - 2010      13\nIraqis lodged asylum applications in 40 out of the 44 industrialized countries covered by this report. One \nquarter of all Iraqi claims were lodged in Germany (5,600), with another quarter being submitted in Turkey \n(3,700; UNHCR procedure) and Sweden (2,000). In particular, the latter experienced a rather dramatic de-\ncrease in Iraqi claims in the past three years, with figures having fallen from as high as 18,600 in 2006.\nThe number of asylum-seekers originating from the Russian Federation dropped in 2010. Some 18,900 \nasylum-seekers were registered in 2010, roughly 7 per cent less than the previous year (20,500). Poland \nremained the prime destination with 4,800 claims or one quarter of all Russian asylum requests being \nlodged in that country. France and Austria also received a significant number of Russian asylum-seekers \nwith 4,300 and 2,300 claims respectively. While the numbers of Russian asylum-seekers in France went up \nby 27 per cent in 2010, they dropped in Poland and Austria (-16% and -35% respectively).\nOther important source countries of asylum-seekers in the 44 industrialized countries in 2010 were Somalia \n(17,000), the Islamic Republic of Iran (14,400), Pakistan (10,800), Nigeria (9,500), and Sri Lanka (8,900). In the \ncase of Somalia, the number of asylum claims has dropped by one quarter compared to 2009. \nIn total, 15 countries among the top 40 coun-\ntries of origin showed an increase between \n2009 and 2010. The highest relative increase \nwas recorded for people originating from \nThe former Yugoslav Republic of Macedonia \nwhose asylum claims went up twelve-fold \nfrom 910 to 6,400. The second highest relative \nincrease was registered for people originating \nfrom Serbia whose numbers reached 28,900 \nclaims during 2010, compared to 18", "output": {"entities": {"named_data": ["Asylum Levels and Trends in Industrialized Countries"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000381", "page": 12, "chunk": 0, "title": "Asylum figures fall in 2010 to almost half their 2001 levels", "pdf_url": "https://reliefweb.int/attachments/31bc4ca9-e978-3381-b95a-cfc86e39e16b/0C4784C3270B952CC125785E002F12B5-Full_Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Asylum Levels and Trends in Industrialized Countries", "label": "NAMED_DATA", "score": 0.5810700058937073, "start": 0, "end": 52, "probe_score": 0.988, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n#### **Productivity shock rationale**\n\n\n\nAs Ukrainian refugees entered the labour\nmarket, the economy adapted in line\nwith expectations based on scientific\nliterature, resulting in greater specialisation\nand higher productivity. In a simplistic\nsupply-demand framework akin to the\n“canonical model”, the influx of Ukrainian\nrefugees should have caused some Polish\nworkers to become unemployed or leave\nthe labour force, or real wages to fall.\nEven in the Deloitte D.Climate model,\nUkrainian refugees add 0.4 percentage\npoints to the unemployment rate and\nlower real wages by 1.35% in 2024 when\nit is not counterbalanced by an additional\npositive productivity shock. However,\nthis is not what we observe in empirical\ndata. First, Polish citizens employment\n\n\n\nrates have grown, and unemployment\nrates have fallen. Second, poviats in\nwhich the employment share of Ukrainian\nrefugees has grown by 1 percentage point,\nexperienced higher by 0.5 percentage\npoint Polish citizens employment rates, and\n0.3 percentage point lower unemployment\nrates. Third, there is no evidence of\nlowered wages; in fact, the limited available\ndata suggests that Ukrainian refugees\nmay have caused higher wage growth in\npoviats to which they have moved. These\nare common findings in the scientific\nliterature quoted in the previous section,\nthat as immigrants enter the labour\nmarket, native workers tend to specialise\nin higher-value, complementary tasks.\nThis is evident in Polish workers moving to\n\n\n\nmore attractive occupational groups. This\nconstitutes a positive productivity shock,\ncounterbalancing labour market pressures.\n\n\nFirst, the employment rate of Polish citizens\nhas been growing since the Ukrainian\nrefugee influx, while the unemployment\nrate has been falling. This is particularly\nevident among women, who make up the\nmajority of refugees. The employment\nrate for women aged 20-64 has grown\nconsistently from 68.2% in Q2 2021 to\n70.2% in Q2 2022, 71.7%", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["empirical\ndata", "limited available\ndata"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 19, "chunk": 0, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "empirical\ndata", "label": "VAGUE_DATA", "score": 0.6013816595077515, "start": 780, "end": 794, "probe_score": 0.9833, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "limited available\ndata", "label": "VAGUE_DATA", "score": 0.5904356241226196, "start": 1175, "end": 1197, "probe_score": 0.0328, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000170", "page": 19, "chunk": 1, "title": "Albania - Water Supply Urgent Rehabilitation Project", "pdf_url": "http://documents1.worldbank.org/curated/en/949361468742522118/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7292463183403015, "start": 272, "end": 283, "probe_score": 0.8771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "## **HELPING HANDS** THE ROLE OF HOUSING SUPPORT AND EMPLOYMENT FACILITATION IN ECONOMIC VULNERABILITY OF REFUGEES FROM UKRAINE\n#### An inter-agency exploration of socio-economic data April 2024", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["socio-economic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 11, "chunk": 0, "title": "3", "pdf_url": "https://local/jad_paddy_docs/3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "socio-economic data", "label": "VAGUE_DATA", "score": 0.7593560814857483, "start": 164, "end": 183, "probe_score": 0.5559, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Disbursement forecast\n\n\n\nContract number\n*Contract subject\nAwardee\n*Launching date\n-Expected delivery date\n-Non objection date\n*Expected date of final delivery\n*Bidder nationality\n*Contract allocation (general account, budget, loan\ncategory, geographic area)\n*List of contracts\nManagement of financial -Standard financial statements (balance sheet;\naccounts statement of sources and uses of funds/income\nstatement, ...)\n*LACI reports for the project duration\nFixed Assets management -Inventory of Fixed Assets (type, quantity, valuation,\ndate of service, etc.)\n\n\n\nSupplier\nAccounting category ; budgetary and accounting\nallocation of fixed assets\n\n\n\nLocation\nDepreciation\n-Disposal of Fixed assets\n\n\n\n**Module** Functions\nSorting parameters Project ID and currency used\n\n                  - Fiscal years\nCurrency\nDecentralized data entry locations\n\n\n\nChart of accounts, managerial reports, geographic\nareas of intervention, etc.\n\n\n\n\n                - Books of accounts\nDonors\n\n                 - Contracts\nCategories of disbursement\nUser Management Data storage ; restitution ; correction; cleaning; etc.\n\n                - Import/export of data to other Tempro modules\n\n\n\nIt is expected that the application would be modified to differentiate the operations from the\nprojects, as well as funding sources to allow for reporting in financial and accounting terms of the\nproject objectives and activities. The concept should allow for proper monitoring of the project\nduring the life of the credit, namely: (i) chart of accounts; (ii) by category, component, and subcomponent; (iii) by geography (type of establishment, site and district); (iv) by category of\nexpenses; and (v) in local and foreign currency. Reporting of multi-level data is planned, which\n**wiU** bring about a more dynamic approach to the management of the project, and which should", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["multi-level data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012126", "page": 51, "chunk": 0, "title": "Kenya - Third Nairobi Water Supply Engineering Credit Project", "pdf_url": "https://documents.worldbank.org/curated/en/382531468047331935/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "multi-level data", "label": "VAGUE_DATA", "score": 0.6651609539985657, "start": 1720, "end": 1736, "probe_score": 0.4661, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on social development issues"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010464", "page": 24, "chunk": 0, "title": "Ethiopia - Ethiopian Social Rehabilitation and Development Fund Project", "pdf_url": "https://documents.worldbank.org/curated/en/268241468023106890/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on social development issues", "label": "VAGUE_DATA", "score": 0.581004798412323, "start": 1670, "end": 1703, "probe_score": 0.333, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nfetching water in almost all age categories, except for the age category of 6–17years, where the share of\nboys and girls who fetch water is almost equal. At the same time, in most cases, water is fetched by women\nor children. In some households, this responsibility is assigned to school or preschool children. This may\nbe explained by the fact that girls after 17 enter family life, get married, and become fully responsible for\nhousehold chores, including fetching of water. In the assessed settings, water is collected at least twice a\nday, with the time spent in a round trip to the source and queuing for water collection ranging from 25 to\n40 minutes in case of the public tap and from 25 to up to 80 minutes for other sources. Results of the\nsurvey are reported in table 1.2.\n\n\nPage 66 of 89\n``", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000162", "page": 69, "chunk": 2, "title": "Tajikistan - Water Supply and Sanitation Investment Project", "pdf_url": "http://documents1.worldbank.org/curated/en/932351655916461178/pdf/Tajikistan-Water-Supply-and-Sanitation-Investment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey", "label": "VAGUE_DATA", "score": 0.5130101442337036, "start": 750, "end": 756, "probe_score": 0.0, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "under study were similar between the treatment group and the proposed control group. If the pre\n\nintervention and “mid-term” (past baseline and probably without implemented intervention) outcome\n\n\nmeasures were not significantly different between treatment and control schools, there is no compelling\n\n\nreason to believe they would be significantly different in the post-intervention periods had the SBM\n\n\nprogram not been put in place. However, if we observe changes between pre-intervention and mid-term,\n\n\nwe can consider the possibility that the two groups would have diverged with respect to their outcomes\n\n\neven in the absence of the SBM intervention. We can test this assumption for the proposed treatment and\n\n\ncontrol groups by running the following equation on the pre-SBM data (i.e. 2002-2003):\n\n\n_Yst_   0   1 ( _Year_ 2002  0 / 2003  1 )   2 ( _Year_ 2002  0 / 2003  1      - _SBM_ 1 / 0 )   _p_   _ts_\n\n-------------------(eq. 3)\nY is the outcome measure including: school level composite test scores and test scores individually in\n\n\nmath, science, and English. _Year_ is a dummy variable that takes value = 1, if year =2003-04 and =0 if\n\n\nyear=2002-03 (both pre-intervention and implementation years). SBM is a dichotomous variable that is\n\nequal to 1 if the school _s_ received SBM support ( _SBM_ =1). As in eq. (2),  _p_ is intended to capture\n\n\ndivision-specific aggregate fixed effects and  _t_, _s_ is the error term. We are interested in two issues: first,\n\n\nwas there a pre-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["pre-SBM data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004440", "page": 9, "chunk": 0, "title": "wps5248", "pdf_url": "https://local/prwp/wps5248.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "pre-SBM data", "label": "VAGUE_DATA", "score": 0.7155699133872986, "start": 776, "end": 788, "probe_score": 0.8406, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " The sustainability of the sanitation measures will be carefully assessed from the point of view\nof good practices, cost effectiveness, affordability and the Djibouti water shortage environment.\n\n\n6. **Social**\n\n\n_6.1 Summarize key social issues relevant to the project objectives, and specify the project's social_\n_development outcomes._\n\n\nDjibouti is a small country and many key social issues were identified in the 1997 Poverty\n\nAssessment. The issues raised included the percentage of the population classified as poor in 1996\n(50-80% reaching the upper-bound when refugees, nomads and homeless are taken into account); large\nnumbers of refugees, nomads, and homeless populations; the majority of the poor live in urban areas\n(85%) even if the incidence of extreme poverty is overwhelmingly rural. Urban households can take\nadvantage of safety nets derived from the commodity market and services, and job opportunities are\nnot available in rural areas. The key problems faced by children include: (a) the high number of street\nchildren who have fled war ravaged Somalia and Ethiopia; (b) late entrance into school by poorer\nchildren (one out of four starts school at age 9 and leaves school at age 14); (c) health issues (diarrhea\n\nand malnutrition) are a leading cause of death for children under age 5. Other problems affecting the\nwhole population include respiratory infections on the increase (due to malnutrition); endemic health\nproblems (AIDS, tuberculosis, malaria, cholera); the widespread practice of Female Genital Mutilation\n(FGM); sanitation costs are high for poorer households not connected on the main water network as", "output": {"entities": {"named_data": ["1997 Poverty\n\nAssessment"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014241", "page": 23, "chunk": 1, "title": "Kenya - Rural Water Supply Project", "pdf_url": "https://documents.worldbank.org/curated/en/522771468046142855/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1997 Poverty\n\nAssessment", "label": "NAMED_DATA", "score": 0.810173511505127, "start": 420, "end": 444, "probe_score": 0.0723, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**KENYA** **AIRPORTS** AUTIlORZITy WORLD **BANK** **FUNDED** PROJECT ACCOUNTS\n\n\n\n**(KENYA** TRANSPORT **SECTOR** **SUPORT** **PROJIECT (KTSSP»**\n**ANNUAL** RIIPORTS **AND** **FINANCIAL** **STATLMENTS**\n\n\n\nFOR THE VI AR **ENDEiD** **JUNE** **30,** **2020**\n\n\n\n**1.** **PROJECT INFORMATION** **AND** **OVERALL** **PERFORMAxNC**\n\n\n**.1** **Name** **and** **registered** **office**\n\n\nProject Name: Kenya Transporti _Sector_ Project **(KTSSP).**\n\n\nObjective: To enhance aviation safety and securitv to mect inleimtionaiI standards\n\n\n**Address:** The address of registe-ed office is:\n\n\nKenya Airports Authority- Headquarters\nAirport North Road\n\nP. **O.** Box **19001-00501**\nNAIROBI\n\n\nTel: +254-020-6822l **11/661** **[000/66** 12000\n\nMobile: +254 **722** **205** **061/2/3/4/516/7/8**\nEmail: talk2us)k•aago.ke info@kja4go.ke\n```\n   www kaa.go.ke\n\n```\n\n1.2 Project Information\n\n\nProject **Start** Da[e 4926-_K L (Oriinal", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010418", "page": 4, "chunk": 0, "title": "KTSSP 1-merged.pdf", "pdf_url": "https://documents.worldbank.org/curated/en/265231612161152672/pdf/KTSSP-1-merged-pdf.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Table 1: Self-reported reasons for not having a bank account|Col2|\n|---|---|\n|**              Reason**|**Respondents saying**<br>**“Yes”**<br>**(%)**|\n|I haven't had money to do it<br>I haven't wanted one<br>I don't have confidence in the institution<br>The required initial deposit is too high<br>Interest rates are too low<br>Too many requirements<br>The membership fee is too high<br>The fees are too high<br>The branch is too far away<br>I don't know what is required to open an account<br>I haven't had a permanent job<br>The staff doesn't treat the clientele|88.84<br>6.12<br>1.91<br>0.75<br>0.65<br>0.51<br>0.37<br>0.33<br>0.23<br>0.14<br>0.09<br>0.05|\n\n\n_Note: Based on responses of 2141 unbanked households to the question “What_\n_is your main reason for not having a bank account?”_", "output": {"entities": {"named_data": [], "descriptive_data": ["responses of 2141 unbanked households"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003854", "page": 19, "chunk": 0, "title": "wps4647", "pdf_url": "https://local/prwp/wps4647.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "responses of 2141 unbanked households", "label": "DESCRIPTIVE_DATA", "score": 0.6917124390602112, "start": 679, "end": 716, "probe_score": 0.1736, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Mitigation**\n**Finance as**\n**part of Total**\n**Climate**\n**Finance**\n**($M)**\n\n\n\n\n\n\n\n**Component/Subcomponent (SC) /**\n**Prior Action (PA) / Disbursement**\n**Linked Indicator (DLI)**\n\n\n\n\n\n\n\n\n\n\n\n\n\n<u>classrooms</u>\n\n\n<u>training</u>\n\n\n\n<u>DLI #3: Teachers receiving minimum</u>\nnumber of quality in-classroom support\n<u>visits</u>\n\n\n\n\n\nEarly Grade Mathematics program\n\n\n\n<u>DLI #5. Schools meeting standards for</u>\nphysical infrastructure, safety, and\n<u>inclusion</u>\n\n\n\n\n\n<u>student-level data in EMIS</u>\n\n|t<br>Total Total Dual-<br>Total Total<br>IBRD/IDA Climate Benefit<br>Adaptation Joint MDB Adaptation Finance Category Mitigation Joint MDB Mitigation Finance Category<br>Financing Finance Finance<br>Finance ($M) Finance ($M)<br>($M) ($M) ($M)|Adaptation<br>Finance as<br>part of Total<br>Climate<br>Finance<br>($M)|\n|---|---|\n|10.00<br>5.20<br>5.20 Cross-cutting sectors<br>5.00 12. CROSS-SECTORAL ACTIVITIES<br>5.00<br>2.70<br>12.00<br>6.43<br>6.43 Cross-cutting sectors<br>6.00 12. CROSS-SECTORAL ACTIVITIES<br>6", "output": {"entities": {"named_data": [], "descriptive_data": ["student-level data in EMIS"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003898", "page": 0, "chunk": 0, "title": "Climate Finance Assessment (P179397)", "pdf_url": "https://documents.worldbank.org/curated/en/099080225111231893/pdf/P179397-2ec8965a-6a62-4988-9644-073734cd18fc.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "student-level data in EMIS", "label": "DESCRIPTIVE_DATA", "score": 0.5980862975120544, "start": 480, "end": 506, "probe_score": 0.0002, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "OCHA Office of Commission for Humanitarian <sup>Assistance</sup>\nPAMC Project Approval and Monitoring Committee\nPETS Public Expenditure Tracking Survey\nPOM Project Operational Manual\nPPA Participatory Poverty Assessment\nQER Quality Enhancement Review\nRUF Revolutionary United Front\nSAPA Social Action and Poverty Alleviation <sup>Program</sup>\nSHARP Sierra Leone HIV/AIDS Response Project\nSLRA Sierra Leone Roads Authority\nSOCAT Social Capital Assessment Tool\nSPP Strategic Planning and Action Process\nTEP Training and Employment Program\nTSS Transitional Support Strategy\nUNAMSIL United Nations Mission for Sierra <sup>Leone</sup>\nUNHCR United Nations High Commission for <sup>Refugees</sup>\nUNICEF United Nations Children's Fund\nUNOPS United National Operations Support\n\n\nVice President: Mr. Callisto Madavo\nCountry Director: Mr. Mats Karlsson\nSector Manager: Mr. Alexandre Abrantes\nTask Team Leader/Task Manager: Ms. Eileen Murray", "output": {"entities": {"named_data": ["PETS Public Expenditure Tracking Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000138", "page": 2, "chunk": 0, "title": "Burundi - Multisectoral HIV/AIDS Control and Orphans Project", "pdf_url": "http://documents1.worldbank.org/curated/en/805311468769526269/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PETS Public Expenditure Tracking Survey", "label": "NAMED_DATA", "score": 0.6079578399658203, "start": 112, "end": 151, "probe_score": 0.0351, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "sup>recently</sup> <sup>come</sup> <sup>under Government control.</sup>\n\n\n\n**2.** **Main sector** issues **and** <sup>**Government strategy:**</sup>\n\n\n\n_Sector Issues._\n_Poverty in Sierra Leone._ Sierra <sup>Leone has</sup> <sup>the lowest</sup> <sup>Human Development Index</sup> <sup>**in**</sup> <sup>the world</sup>\n\n\n\nand has a GNP per capita <sup>of only US$130</sup> <sup>compared</sup> <sup>to the average</sup> <sup>for Sub-Saharan</sup> <sup>Africa</sup> <sup>of $470.</sup>\n\n\n\nOver 82% of the population <sup>currently</sup> <sup>lives below</sup> <sup>the poverty line and life expectancy is only</sup> <sup>38 years.</sup>\n\n\n\nFertility, infant and child <sup>mortality are</sup> <sup>high</sup> <sup>and over</sup> <sup>a third</sup> <sup>of children and</sup> <sup>a fourth</sup> <sup>of adults</sup> <sup>are</sup>\n\n\n\nmalnourished. The pnmary <sup>school enrollment</s", "output": {"entities": {"named_data": ["Human Development Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000052", "page": 7, "chunk": 1, "title": "Croatia - Municipal Environmental Infrastructure Project", "pdf_url": "http://documents1.worldbank.org/curated/en/367181468770702078/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Human Development Index", "label": "NAMED_DATA", "score": 0.6837996244430542, "start": 251, "end": 274, "probe_score": 0.0779, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSocio-economic Inclusion of Refugees & Host Communities in Rwanda Project (P164130)\n\n\n70. The project results framework includes three indicators related to community engagement, as follows: (i)\nbeneficiaries participating in project planning activities; (ii) beneficiaries that feel project investments reflected their\nneeds; and (iii) grievances registered related to delivery of benefits that are addressed. Together these three indicators\nwill measure participation in the planning process, the extent to which the process is reflective of community priorities\nand the effectiveness of project mechanisms to handle and respond to community feedback.\n\n\n**Table 4: Implementation Arrangements per Component**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Component|Indicative subprojects|Agency<br>Responsible|Key roles|\n|---|---|---|---|\n|Component 1:<br>Access to Basic<br>Services and<br>Socioeconomic<br>investments|• Construction, upgrade and/or<br>rehabilitation of health facilities.<br>• Construction, upgrade and/or<br>rehabilitation of education<br>facilities.<br>• Equipment and facilities for health<br>centers & schools<br>• Technical vocational training<br>• Community water systems<br>• Road rehabilitation/upgrading<br>• Market construction/<br>rehabilitation|Districts,<br>supported<br>by MINEMA|• Define development problems and identify<br>solutions, including through consultations<br>with project beneficiaries and stakeholders<br>• Propose subprojects for financing to the<br>Steering Committee<br>• Validate and report back to beneficiaries on<br>final subproject decisions.<br>• Implement subprojects<br>• Monitor and report on progress<br>• Ensure O&M budget is allocated to sustain<br>the investments", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000030", "page": 28, "chunk": 0, "title": "Rwanda - Socio-Economic Inclusion of Refugees and Host Communities in Rwanda Project", "pdf_url": "http://documents1.worldbank.org/curated/en/222811556935409836/pdf/Rwanda-Socio-Economic-Inclusion-of-Refugees-and-Host-Communities-in-Rwanda-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " (Highly Satisfactory), S (Satisfactory), U (Unsatisfactory), HU (Highly Unsatisfactory)\n\nDevelopment Partners supporting NaCSA include: the African Development Bank, British Department\nfor International Development (DflD); French Agency for Development; United Nations Development\nProgram.\n\n\n                               - 12", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010449", "page": 16, "chunk": 1, "title": "Uganda - Capacity and Performance Enhancement Program (CAPEP) Project", "pdf_url": "https://documents.worldbank.org/curated/en/267541468760510994/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Annex 1:** **Project** **Design** **Summary**\n\n**SIERRA LEONE:** **NATIONAL** **SOCIAL ACTION** **PROJECT**\n\n\n. **Hierarchy o.Qbijctives -'**  - . **diator** **r**, t **,P** **jCitidaI** **r!** **As's-umptIons,Y-**\n**Sector-related** **CAS** **Goal:** **Sector** **Indicators:** **Sector/ country reports:** **(from** **Goal** **to Bank** **Mission)**\nMitigate the risk of renewed 1. National conflict/security- - UNHCR/OCHA reports - Continued peace and\n**conflict** **and lay foundation** related indicators - Household Income and regional security\n**for** **poverty reduction and** 2. Inter-regional disparities in Expenditure Surveys - Economic and political\n**improvements** **in nutrition,** I-PRSP & PRSP core - PETS surveys stability\n**health, education** **and** indicators - Strategic Planning and\n**targeting** **the rural** 3. Inter-regional disparities in Action Process (SPP) reports\n**population,** women **and** Popular Benchmarks\n**children.**\n\n\n**Project** **Development** **Outcome** **/** **Impact** **Project reports:** **(from** *", "output": {"entities": {"named_data": ["Inter-regional disparities in Expenditure Surveys", "PETS surveys"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000050", "page": 29, "chunk": 0, "title": "Albania - Social Services Delivery Project", "pdf_url": "http://documents1.worldbank.org/curated/en/357561468742548905/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Inter-regional disparities in Expenditure Surveys", "label": "NAMED_DATA", "score": 0.5622888207435608, "start": 590, "end": 639, "probe_score": 0.0005, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "PETS surveys", "label": "NAMED_DATA", "score": 0.6322475075721741, "start": 721, "end": 733, "probe_score": 0.0465, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nGenerating Growth Opportunities and Productivity for Women Enterprises Uganda Project (P176747)\n\n\n**_Subcomponent 1C: Support for trade/sector specific skills (total IDA US$15 million equivalent, including WHR US$3.75_**\n**_million)_**\n\n38. **This subcomponent will support advanced, sector-specific training (for example, in climate smart agri-business,**\n**e-commerce, hotel management, tourism, and others) for women entrepreneurs who successfully complete the core**\n**course and want to avail trade specific trainings.** This sector specific trainings will be part of the continuum of enterprise\ndevelopment services provided to women enterprises that have growth potential and want to move to the next stage.\nThe subcomponent will also support women that have existing enterprises and do not necessarily need the core course\nbut would benefit from sector-specific training that allows for value-addition and expansion of their enterprise.\n\n39. **The PSFU will implement this subcomponent** . The subcomponent will finance the activities of operational and\nmanagement cost of the PSFU, communications campaigns for launch of the specific trainings, selection of training\nproviders (that will include operational costs, fees of trainers, transportation costs for trainers and beneficiaries, childcare\nservices, and the like), monitoring costs, and establishment of a beneficiary database. The implementation and selection\nof service providers will be similar to that of the successful Skills Development Fund, implemented by the PSFU under the\nWorld Bank-financed education project. In refugee settlements the PSFU will liaise with the OPM and ensure appropriate\nservice providers that can deliver trade-specific trainings within the refugee settlements.\n\n\n**_Subcomponent 1D: Women entrepreneurship work placement program (total IDA: US$8 million equivalent, including_**\n**_WHR US$1.5 million", "output": {"entities": {"named_data": [], "descriptive_data": ["beneficiary database"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 23, "chunk": 0, "title": "Uganda - Generating Growth Opportunities and Productivity for Women Enterprises Uganda Project", "pdf_url": "http://documents.worldbank.org/curated/en/527091655323259747/pdf/Uganda-Generating-Growth-Opportunities-and-Productivity-for-Women-Enterprises-Uganda-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "beneficiary database", "label": "DESCRIPTIVE_DATA", "score": 0.8133137822151184, "start": 1390, "end": 1410, "probe_score": 0.008, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " with the scale is that different respondents may interpret\n\n\nthe scales differently, and that the scale can be related with the “true” probability of rainfall, but\n\n\n2 The interested reader can consult Chapter 10 in Tourangeau, Rips and Rasinski (2000) for a critical comparison of\ndifferent modes of data collection.\n3 An example is the survey of the top academic achievers from a number of Pacific Islands discussed in Gibson and\nMcKenzie (2008), which used the percent chance formulation to ask expectations questions about migration using\nonline and in-person questionnaires.\n\n\n                           - 3", "output": {"entities": {"named_data": [], "descriptive_data": ["survey of the top academic achievers"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004019", "page": 4, "chunk": 1, "title": "wps4824", "pdf_url": "https://local/prwp/wps4824.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey of the top academic achievers", "label": "DESCRIPTIVE_DATA", "score": 0.9239624738693237, "start": 339, "end": 375, "probe_score": 0.0232, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Policy Research Working Paper 7363\n\n#### **Abstract**\n\nUsing the universe of all externally issued bonds by corporates and sovereigns in emerging and developing economies\nduring 2000–14, this paper analyzes various issuance trends,\nincluding the unprecedented post-crisis surge. The paper\nfocuses on external issuance at the country-industry and\nindividual bond levels and finds that global factors matter\ngreatly for emerging and developing economies issuance. A\ndecrease in U.S. expected equity market (or interest rate)\nvolatility, U.S. corporate credit spreads, and U.S. interbank\nfunding costs and an increase in the Federal Reserve’s balance sheet (i) raise the odds that the monthly issuance\nvolume of a country-industry is above its historical average; (ii) decrease individual bond yields and spreads; and\n(iii) raise bond maturities, after controlling for country pull\n\nfactors, bond characteristics (for example, type of issuer,\n\n\n\nindustry, and riskiness). Additionally, we document support\nthat the risk-taking channel of exchange rate appreciation\nalso operates for external bond issuance. Moreover, while\nthe paper finds that country pull factors affect the impact\nof global factors, it does not find consistent evidence for\nthis across the board. This result suggests that, during loose\nglobal funding conditions, flows are mostly driven by push\nfactors and do not systematically discriminate between\nemerging and developing economies. Taken together, the\nfindings suggest that although issuers might be able to\nbenefit from benign international funding conditions, the\nlarge issuance volumes, currency risks, and high exposure to\nglobal factors could pose external and domestic challenges\nfor policy makers, particularly when global cycles reverse.\n\n\n\nThis paper is a product of the Finance and Markets Global Practice Group. It is part of a larger effort by the World Bank\nto provide open access to its research and make a contribution to development policy discussions around the world. Policy\nResearch Working Papers are also posted on the Web at http://econ.worldbank", "output": {"entities": {"named_data": [], "descriptive_data": ["universe of all externally issued bonds"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006419", "page": 1, "chunk": 0, "title": "wps7363", "pdf_url": "https://local/prwp/wps7363.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "universe of all externally issued bonds", "label": "DESCRIPTIVE_DATA", "score": 0.5715684294700623, "start": 65, "end": 104, "probe_score": 0.6347, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "THE ROLE OF HOUSING SUPPORT AND EMPLOYMENT FACILITATION IN ECONOMIC VULNERABILITY OF REFUGEES FROM UKRAINE\n\n\n### **Background**\n\nOver two years have elapsed since the start of the\nfull-scale war in Ukraine leading to a protracted\ndisplacement and a humanitarian crisis. The\nresponse by the refugee-hosting countries\ncontinues to be overall characterized by a spirit of\nwelcomeness and generosity and much has been\ndone to make ensure that those fleeing the war are\nable to meet basic needs and have access to\naccommodation, healthcare, education, social\nassistance, and employment. Despite these efforts,\nthe situation remains a source of deep concern,\nnecessitating a continued and coordinated\nhumanitarian response at the regional level.\n\n\nAs of the end of 2023, 5.9 million refugees from\nUkraine were recorded across Europe, close to 2\nmillion of whom are in the countries covered by the\n<u>[Regional Refugee Response Plan (RRP)](https://data.unhcr.org/en/documents/details/105903)</u> <sup>5</sup> [^5: Belarus, Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, the Republic of Moldova, Poland, Romania, and Slovakia] . To better\nunderstand their evolving situation, unpack risks\nand vulnerabilities and inform planning across\nsectors, Multi-Sectoral Needs Assessments (MSNA)\nwere conducted under the RRP between June and\nSeptember 2023 by UNHCR’s Regional Bureau for\nEurope and its Inter-Agency partners. This\npublication focuses on the results for livelihoods\nand socio-economic inclusion and attempts to draw\nconclusions based on survey data of 11,496\nhouseholds (and 26,857 individuals) living in\nBulgaria, the Czech Republic, Hungary, the Republic\nof Moldova, Poland, Romania, and Slovakia.\n\n\n### **Socio-economic** **inclusion – key** **findings**\n\n**Refugee households demonstrate a high degree**\n**of economic vulnerability**\nThe MSNA survey data demonstrates that refugee", "output": {"entities": {"named_data": ["MSNA survey data"], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 3, "chunk": 0, "title": "3", "pdf_url": "https://local/jad_paddy_docs/3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7565656900405884, "start": 1550, "end": 1561, "probe_score": 0.7979, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "MSNA survey data", "label": "NAMED_DATA", "score": 0.7983078956604004, "start": 1855, "end": 1871, "probe_score": 0.5615, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "particular situation, of proven, low-cost technologies, workable financing modalities, and\nguidelines for community participation/acceptance developed in the first phase.\n**(ii) fine tune and strengthen the institutional framework** in light of any difficulties\nencountered by sub-project developers, and increase the extent of decentralization in\nterms of responsibilities for program support and management, monitoring, and\nexpansion,\n**(iii) mainstreaming of successful pilots**, with any necessary adjustments, undertaken in the first\n\nphase, and implement fresh pilots that reflect fresh opportunities as well as the experience with\nearlier pilots.\n\n\nThe activities specific to renewable energy will follow from those initiated in the first phase, and will\nconsist of building in-country capabilities, resource data dissemination, and continuing dissemination\npromotion of international best practices. Phase II of the Energy for Rural Transformation ERT project\nis expected to run for three years starting mid 2009.\n\n\n- **Third phase:** **_Rapid scale-up and consolidation of institution build-up_**\n\n\nThe third phase's central objective will be to shift the focus to exponential growth in investments so as to\nreach the Government's long-term targets for rural electrification and renewable energy development,\nwith rural transformation facilitated by scale-up of the successful pilots from the earlier phases. While\ncapacity building will continue, its focus would shift from fresh initiation to consolidation of the\noutcomes of the first and second phase activities. The _ERT_ program is expected to be fully operational on\na national scale and functioning in a highly decentralized mode.\n\n## **3.0 ERT II PROGRAM COMPONENTS**\n\n\nThe ERT II program covers six broad areas/components, namely (i) Main grid related power\ndistribution and generation (ii) Developing of independent grid systems (iii) Solar PV systems\n(iv)Cross sectoral energy packages for health, education, and water services. (v) Capacity\nbuilding, technical assistance training and M", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["resource data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012267", "page": 6, "chunk": 0, "title": "Uganda - Second Energy for Rural Transformation (ERT II) Project : resettlement plan (Vol. 1 of 4) : Resettlement policy framework", "pdf_url": "https://documents.worldbank.org/curated/en/390451468318292827/pdf/RP7300P11233401amework0ERT0II0Final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "resource data", "label": "VAGUE_DATA", "score": 0.6175870895385742, "start": 807, "end": 820, "probe_score": 0.0881, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "problem solving and feedback (positive or negative). The grievance log will be submitted to the\nAssociation on a semi-annual basis for review.\n\n**6.4.3** **Verify, Investigate and Act**\n\nThe project implementation unit (PIU) will investigate the claim within 5 working days and share\nfindings with relevant stakeholders. Where an incident was reported, the PIU will, in addition, follow\nthe incident management protocol. Where a negotiated grievance solution is required, the PIU will\ninvite the aggrieved party (or a representative) and decide on a solution, which is acceptable to both\nparties and allows for the case to be closed – based on the agreement of both parties.\n\nThe project management team will be responsible for the Grievance Redress Mechanism. The\nresponsibilities for the management of the GRM system include the following and may be updated\nfrom time to time in consultation with KRC and the World Bank task teams.\n\n  - Overall management of the GRM system\n\n  - Developing and maintaining awareness-building\n\n  - Collection of complaints\n\n\n**28 |** P a g e", "output": {"entities": {"named_data": [], "descriptive_data": ["grievance log"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003979", "page": 31, "chunk": 0, "title": "Stakeholder Engagement Plan (SEP) Kenya Urban Mobility Improvement Project (P176725)", "pdf_url": "https://documents.worldbank.org/curated/en/099080923141526762/pdf/P176725097eb5d080a5cb076b3fe6a4f59.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "grievance log", "label": "DESCRIPTIVE_DATA", "score": 0.7397220730781555, "start": 57, "end": 70, "probe_score": 0.0022, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Venezuelans in Chile, Colombia, Ecuador and\nPeru – A Development Opportunity\n\n\n\n1 Introduction\n\n\n15\n\n\n**As of December 2022, an estimated 7.13 million people had left Venezuela (R4V**\n**2023b), and the figure is expected to reach nearly 8.4 million by 2025** (Arena\nand others, 2022). The vast majority of Venezuelan migrants and refugees—over\nsix million—have crossed international borders within the Latin American and\nCaribbean region (LAC), establishing themselves mainly in Colombia, Peru, Ecuador,\nand Chile (R4V 2023b). <sup>1</sup> At the end of 2018, more than 2.4 million Venezuelans\nhad settled in these four countries; by the end of 2022, the figure had more than\ndoubled to more than 4.9 million. <sup>2</sup> [^2: The Interagency Coordination Platform for Refugees and Migrants (R4V) presents information on migrants from 2018 on.] Between the end of 2018 and the end of 2022,\nthe share of Venezuelans in these countries had risen by a factor of 1.60 in Chile,\n2.00 in Ecuador, 2.13 in Colombia, and 2.17 in Peru. <sup>3</sup> [^3: Estimates are based on the latest published data from R4V (accessed May 9, 2023) for each month. Where data were not available, the figure from the last\nmonth for which data were available was used.]\n\n\n**In December 2022, Colombia, Peru, Ecuador, and Chile hosted 82 percent**\n**of Venezuelan migrants and refugees in LAC** . Colombia was home to about\n2.5 million (41 percent of the total), Peru to 1.5 million (25 percent), Ecuador to\n500,000 (8.3 percent), and Chile to 440,000 (7.4 percent) (R4V 2023a) (figure 1", "output": {"entities": {"named_data": [], "descriptive_data": ["data from R4V"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001190", "page": 14, "chunk": 0, "title": "Venezuelans in Chile, Colombia, Ecuador and Peru: A Development Opportunity", "pdf_url": "https://reliefweb.int/attachments/b6b504c8-f3b2-4e0d-a2e0-3955b4beb78c/P17578013f69d804019f8516ffbb072fc34.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from R4V", "label": "DESCRIPTIVE_DATA", "score": 0.5712757706642151, "start": 1090, "end": 1103, "probe_score": 0.9546, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " project attempts to address\nthe identified capacity gaps in the selected Ministries, Departments and Agencies to address the major\nchallenges in the urban development and management.\n\n\nSectoral and Institutional Context\nUganda is currently only 18% urbanized but with high urbanization rate of 5.2% according to the Uganda\nBureau of Statistics figures 2014. The number of residents living in urban areas is expected to quadruple to\nmore than 20 million by 2040. Urbanization plays a key role in the economic development of the Country.\nNearly 70 percent of the country’s non-agricultural GDP is generated in urban areas and 70 percent\nof manufacturing activities are conducted in urban areas. Similarly, 65 percent of new jobs over the past\ndecade were created in cities and urban communities. Ugandan cities are creating many non-agricultural jobs\nand improving the economic position of urban residents. However, the limited infrastructure is constraining\nmobility of people and goods, and more than 60 percent of the residents of urban areas live in slums.\nWhereas Physical Development Plans are in place for most urban centers, these are often on paper but they\nhave not been translated into practice on the ground leading to urban sprawl, poor land use, environment\ndegradation and inadequate access to infrastructure and social services. Ensuring urbanization is well\nmanaged, with appropriate urban planning policies and enforcement, accompanied by the appropriate\nprovision of public services, reliable transport and affordable housing is therefore critical. Some of the key\npriority areas in the urban sector include: (i) Strengthening capacity of physical planning and urban\n\n\nOct 02, 2019 Page 3 of 9", "output": {"entities": {"named_data": ["Uganda\nBureau of Statistics figures 2014"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011520", "page": 2, "chunk": 1, "title": "Project Information Document (PID) - Support to Institutional Capacity Enhancement for Urban Development and Management - P170732", "pdf_url": "https://documents.worldbank.org/curated/en/341191570029472768/pdf/Project-Information-Document-PID-Support-to-Institutional-Capacity-Enhancement-for-Urban-Development-and-Management-P170732.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Uganda\nBureau of Statistics figures 2014", "label": "NAMED_DATA", "score": 0.7022019028663635, "start": 317, "end": 357, "probe_score": 0.0792, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda: Investment for Industrial Transformation and Employment (P171607)\n\n\n\n\n\n\n\n\n\n\n\n\n|Indicator Name|PBC|Baseline|Intermediate Targets|Col5|Col6|Col7|End Target|\n|---|---|---|---|---|---|---|---|\n|<br>|||**1 **|**2 **|**3 **|**4 **||\n|manufacturing sectors<br>(Number)||||||||\n|**Firm Acess to Finance**|**Firm Acess to Finance**|**Firm Acess to Finance**|**Firm Acess to Finance**|**Firm Acess to Finance**|**Firm Acess to Finance**|**Firm Acess to Finance**|**Firm Acess to Finance**|\n|Beneficiaries reached with<br>financial services (CRI,<br>Number)||0.00|50,000.00|100,000.00|130,000,000.00<br>|170,000,000.00|200,000.00|\n|Number of SMEs with a loan<br>or line of credit (CRI,<br>Number)|<br>|0.00|2,700.00||||5,300.00|\n|**Number of formally employed in the manufacturing sector according to PAYE data collected by URA TIN**|**Number of formally employed in the manufacturing sector according to PAYE data collected by URA TIN**|**Number of formally employed in the manufacturing sector according to PAYE data collected by URA TIN**", "output": {"entities": {"named_data": ["PAYE data collected by URA TIN", "PAYE data collected by URA TIN"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000021", "page": 56, "chunk": 0, "title": "Uganda - Investment for Industrial Transformation and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/469061641926083502/pdf/Uganda-Investment-for-Industrial-Transformation-and-Employment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PAYE data collected by URA TIN", "label": "NAMED_DATA", "score": 0.6152309775352478, "start": 817, "end": 847, "probe_score": 0.8746, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PAYE data collected by URA TIN", "label": "NAMED_DATA", "score": 0.5309934020042419, "start": 921, "end": 951, "probe_score": 0.9709, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "completed sub-projects local authorities provide\nconform to ministry standards, resources and staff to operate\ndesigns and norms. and maintain facilities (e.g.\nprovision of teachers and\n\ntextbooks in the case of\nprimary schools);\n\n\nl(b) Targeted communities are lb. 1 At <sup>least 90%</sup> <sup>of</sup> - Beneficiary/ impact - Sub-projects reflect\nempowered to carry out projects are assessed as assessments and other beneficiary needs and\npriority investments. successful by communities evaluation reports improved access to social and\n(achieve rmnimum expected economic services;\noutputs and\noutcomes/imnpacts).\n\n                                     - Supervision missions                                     - PPA methodology is\nlb.2 All supported                  - Beneficiary Assessments internalized by NaCSA and\ncommunities have conducted                - NSAP quarterly progress partners;\nparticipatory needs reports\nassessments and project                 - Participatory M&E results\nidentification using PPA\napproach.                 - Continuous social                 - Capacity building efforts\nI assessment process provided and/or coordinated\nlb.3 100% of communities                  - Participatory M&E results by NaCSA are appropriate and\nhave project management effective;\nstructures in place and trained\ncommunity members.\n\n**2.** Pilot and Special 2a.1 100 km. of feeder roads - Supervision <sup>missions;</sup> - NaCSA's commitment to\n\n**Programs in** Newly rehabilitated. - NSAP quarterly reports; pilot both programs remains\n**Accessible** **Areas** - Annual technical audits; strong\n2a.2 800,000 person days of                  - NaCSA M&E data\n**2(a)** **Rural Public Works** temporary employment\n**Program:** created.\n\nInfrastructure constructed 2a.3 250,000 \"woman days\" of\nand/or upgraded using labor temporary employment\nintensive techniques. created.\n\n\n2a.4 At mid-term review the\ncost per day", "output": {"entities": {"named_data": ["NaCSA M&E data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020161", "page": 30, "chunk": 0, "title": "Uganda - Structural Adjustment Credit Project", "pdf_url": "https://documents.worldbank.org/curated/en/923551498750109199/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NaCSA M&E data", "label": "NAMED_DATA", "score": 0.9113216400146484, "start": 1658, "end": 1672, "probe_score": 0.7359, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "br>**procurement performance:**<br> <br>Piloting individual performance contract approach in the<br>procurement system<br> <br>RRI to support procurement process performance in the pilot|**3.3m**||\n|**Improved**<br>**decision-**<br>**making process**<br>**based on**<br>**reliable**<br>**statistical data**|**Component 4: Enhancing the use of statistics**<br>**for policy making**<br> <br>Timely production of reliable statistical<br>data<br> <br>Statistics widely disseminated|**Subcomponent 4.1: Improvement of poverty-related data**<br> <br>Production of a series of Poverty Notes (based on ECAM 4 and high-<br>frequency surveys)<br> <br>Production of ECAM 5<br> <br>Analysis of the population census<br> <br>Production of the LFS|**5.4m**||\n|**Improved**<br>**decision-**<br>**making process**<br>**based on**<br>**reliable**<br>**statistical data**|**Component 4: Enhancing the use of statistics**<br>**for policy making**<br> <br>Timely production of reliable statistical<br>data<br> <br>Statistics widely disseminated|**Subcomponent 4.2: Strengthening the national accounts production**<br> <br>Quarterly production of improved national accounts", "output": {"entities": {"named_data": ["ECAM 4", "ECAM 5", "LFS"], "descriptive_data": ["population census"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000044", "page": 82, "chunk": 1, "title": "Cameroon - Strengthening Public Sector Effectiveness and Statistical Capacity Project", "pdf_url": "http://documents1.worldbank.org/curated/en/305621511406035802/pdf/CAMEROON-PAD2-11012017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.58969646692276, "start": 290, "end": 306, "probe_score": 0.1435, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "ECAM 4", "label": "NAMED_DATA", "score": 0.6722064018249512, "start": 599, "end": 605, "probe_score": 0.4584, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "ECAM 5", "label": "NAMED_DATA", "score": 0.6340987682342529, "start": 661, "end": 667, "probe_score": 0.0927, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "population census", "label": "DESCRIPTIVE_DATA", "score": 0.7384703159332275, "start": 693, "end": 710, "probe_score": 0.7417, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "LFS", "label": "NAMED_DATA", "score": 0.7386197447776794, "start": 738, "end": 741, "probe_score": 0.9679, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "4.3 Impact of relaxing FAR regulations on estimated land value creation\nThere are Floor-Area Ratio (FAR) regulations in place in the Buenos Aires region, and in particular in the\ncity of Buenos Aires proper (CABA). We account for these in the model by adding a map that provides\ninformation about the maximum Floor Area Ratios – the ratio between the maximum amount of space\nbuilt for residential or other purposes and the land area the structure is built-on – in _CABA_ together with\nthe type of use allowed in each zone. We thus limit the maximum height of buildings within _CABA_ . We\nalso exclude zones that are uniquely destined to commercial or industrial uses from being urbanized for\nresidential purposes. To do so we intersected our grid with data from the 2011 Cόdigo de Planeamiento\nUrbano (CPU). <sup>15</sup> [^15: Accessible at: http://data.buenosaires.gob.ar/.] The CPU map provides for each zone the classification of buildings that can be built. From\nthis information we can retrieve the type of buildings (residential commercial etc.) and the maximum\nallowed height. For each grid cell we averaged the data to obtain the average building height for\nresidential purposes in _CABA_ (Figure 6). Beyond _CABA_ however we do not introduce maximum building\nheights. It should be noted that FARs only have a loose connection to the number of floors that can be\nbuilt on a given land plot so that equating both is a simplification that is valid for our modeling purposes\nonly. Indeed, a residential FAR of 1, for example, is the ratio between the amount of living space that can\nbe built and the area of a plot of land. This can correspond to one floor if the building occupies the total\nspace of the land plot, two floors if the building occupies only half the land plot area or even 4 floors if it\noccupies 25% of the land plot.\n\n\n_Figure 6: Maximum number of floors", "output": {"entities": {"named_data": ["2011 Cόdigo de Planeamiento\nUrbano", "CPU map"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000444", "page": 22, "chunk": 0, "title": "flood protection and land value creation not all resilience investments are created equal", "pdf_url": "https://local/prwp/flood-protection-and-land-value-creation-not-all-resilience-investments-are-created-equal.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2011 Cόdigo de Planeamiento\nUrbano", "label": "NAMED_DATA", "score": 0.6818838715553284, "start": 766, "end": 800, "probe_score": 0.9402, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "CPU map", "label": "NAMED_DATA", "score": 0.7015387415885925, "start": 881, "end": 888, "probe_score": 0.9333, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Protocols**\n\n\n**28.** **A total of 10 DLIs (Table 3) have been selected** using the following selection criteria: (1) they reflect objective and\ntangible results, as officially targeted in government policy documents (including budget documents); (2) they are\nunderpinned by a substantial program of expenditure in the government budget; (3) they mobilize government digital\nsystems that are already operational; and (4) they often target specific social groups (including women, elders, and\nrefugees) for the sake of social inclusion. Among a range of options meeting those criteria, they have been selected\nbased on their readiness for achievement, and their measurability and verifiability, as well as the likelihood that they\ncan be achieved during the Program’s timeline considering the institutional capacity of implementing agencies. The\n\n\n[11 Centre for Strategic Studies-University of Jordan. 2022. Public Opinion Poll: Tawjihi, Universities and the Unified Admission](https://view.officeapps.live.com/op/view.aspx?src=https%3A%2F%2Fjcss.org%2Fwp-content%2Fuploads%2F2022%2F10%2FThe-pulse-of-the-Jordanian-street31English.docx&wdOrigin=BROWSELINK)\n<u>[System. https://view.officeapps.live.com/op/view.aspx?src=https%3A%2F%2Fjcss.org%2Fwp-](https://view.officeapps.live.com/op/view.aspx?src=https%3A%2F%2Fjcss.org%2Fwp-content%2Fuploads%2F2022%2F10%2FThe", "output": {"entities": {"named_data": ["Public Opinion Poll"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000181", "page": 21, "chunk": 2, "title": "Jordan - People-Centric Digital Government Program for Results", "pdf_url": "https://documents1.worldbank.org/curated/en/099030724150040202/pdf/BOSIB-70f97ae8-b741-401c-82cc-e87615cc5487.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Public Opinion Poll", "label": "NAMED_DATA", "score": 0.7633889317512512, "start": 909, "end": 928, "probe_score": 0.0499, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|PI-25.1|Segregation of duties|A|A|A|A|A|A|A|\n|---|---|---|---|---|---|---|---|---|\n|PI-25.2|Effectiveness of<br>expenditure<br>commitment controls|C|B|B|C|C|C|C|\n|PI-25.3|Compliance with<br>payment rules and<br>procedures|B|A|B|B|B|B|B|\n|**PI-26**|**Internal audit**|**D+**|**D+**|**C+**|**C+**|**C+**|**C+**|**C+**|\n|PI-26.1|Coverage of internal<br>audit|A|A|B|B|A|A|A|\n|PI-26.2|Nature of audits and<br>standards applied|C|C|C|C|C|C|C|\n|PI-26.3|Implementation of<br>internal audits and<br>reporting|C|C|B|B|A|A|A|\n|PI-26.4|Response to internal<br>audits|D|D*|C|A|B|B|A|\n|**PI-27**|**Financial data**<br>**integrity**|**B **|**B **|**B+**|**B **|**C+", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Financial data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017679", "page": 29, "chunk": 0, "title": "Final Addendum to Fiduciary Systems Assessment - ENHANCING SHARED PROSPERITY THROUGH EQUITABLE SERVICES (ESPES) Second Additional Financing - P176354", "pdf_url": "https://documents.worldbank.org/curated/en/753251619454227055/pdf/Final-Addendum-to-Fiduciary-Systems-Assessment-ENHANCING-SHARED-PROSPERITY-THROUGH-EQUITABLE-SERVICES-ESPES-Second-Additional-Financing-P176354.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Financial data", "label": "VAGUE_DATA", "score": 0.6091313362121582, "start": 585, "end": 599, "probe_score": 0.0173, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Figure 9: Distribution of Syrian refugee youth by friendship with Lebanese, by sex and age\ngroup\n(Percentage)\n\n\n\nTable 60: Distribution of Syrian refugee youth by reasons restricting friendship with Lebanese,\nby sex and age group\n(Percentage)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThe common reason for not befriending the Lebanese is often simply a lack of opportunity, as\nstated by 28 per cent. Findings suggest a possible segregation between the lives of refugees and of\nLebanese in host communities, and the fact that they feel Lebanese look down at them, as mentioned\nby 27 per cent (table 60). Syrian refugee youth and their parents, however, try not to generalize\nabout the Lebanese in their discussions, pointing out that some are good, helpful and kind. Around\n75 per cent of youth aged 15-18 years do not have Lebanese friends, as compared to almost 58\nper cent among the 19-24-year-olds. Close to half of the surveyed youth, or 47 per cent, agree that\ncoexistence with the Lebanese is almost impossible; with this share rising to a high of 85 per cent of\nSyrian refugee youth in the North, reflecting a strong feeling of segregation there, versus a low of 25\nper cent in the South and Nabatieh.\n\n\n\nSyrian refugee youth think that the Lebanese attitude combines both the positive and the\nnegative, with negative attitudes being more prevalent. Half the surveyed refugee youth think it is\nan attitude of disdain, hate or exploitation; however, 24 per cent describe the behaviour of Lebanese\nas “normal” (figure 10), and 6 per cent think the Lebanese are indifferent towards them. Just 5 per cent\nregard the Lebanese as having feelings of solidarity with, and sympathy towards Syrians.\n\n\nThe qualitative data also shows mixed views. The attributes that Syrian youth and their parents use\nin describing the Lebanese attitude include despising, exploiting, intimidating, pressuring, harassing,\nrejecting, etc. _“The Lebanese treat us like rubbish,”_ a male Syrian youth in", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["qualitative data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000362", "page": 79, "chunk": 0, "title": "Situation Analysis of Youth in Lebanon Affected by the Syrian Crisis", "pdf_url": "https://reliefweb.int/attachments/2ecf62b5-58f1-3f90-a023-ce0b423455f9/YSA-SyriaCrisis-FullReport.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "qualitative data", "label": "VAGUE_DATA", "score": 0.7988742589950562, "start": 1703, "end": 1719, "probe_score": 0.9795, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "/en/data/<br>dataset/jrc-10112-<br>10004/resource/609a472e-7e26-4b63-<br>8003-17298cb45e2a <br> <br>https://mars.jrc.ec.europa.eu/asap/files/<br>gaul1_asap.zip <br>|Europa.EU<br>http://data.europa.eu/eli/dec/2011/8<br>33/oj.<br>|\n|Crop coverage –<br>Copernicus Global<br>Land Cover Layers<br>|<br>Mapped crop coverage data layer (2019<br>vintage).<br>|<br>https://land.copernicus.eu/global/produ<br>cts/lc <br> <br>|Buchhorn, M., B. Smets, L. Bertels, B.<br>De Roo, M. Lesiv, N.-E. Tsendbazar, M.<br>Herold, and S. Fritz. Copernicus Global<br>Land Service: Land Cover 100m:<br>Collection 3: epoch 2019: Globe 2020.<br>|\n|Population – GHS-<br>POP R2019A|This spatial raster data set depicts the<br>distribution of population, expressed as the<br>number of people per cell.|https://ghsl.jrc.ec.europa.eu/ghs_pop20<br>19.php|<br>GHS population grid multi-temporal<br>(1975–1990–2000–2015).|\n\n\n\n36", "output": {"entities": {"named_data": ["Mapped crop coverage data layer", "POP R2019A", "GHS population grid multi-temporal"], "descriptive_data": ["spatial raster data set"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001505", "page": 37, "chunk": 2, "title": "idu1ae0eac0e145d214c6218002156b672eb8155", "pdf_url": "https://local/prwp/idu1ae0eac0e145d214c6218002156b672eb8155.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Mapped crop coverage data layer", "label": "NAMED_DATA", "score": 0.6575095653533936, "start": 297, "end": 328, "probe_score": 0.8224, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "POP R2019A", "label": "NAMED_DATA", "score": 0.7471014857292175, "start": 642, "end": 652, "probe_score": 0.9964, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "spatial raster data set", "label": "DESCRIPTIVE_DATA", "score": 0.5700768828392029, "start": 658, "end": 681, "probe_score": 0.9976, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "GHS population grid multi-temporal", "label": "NAMED_DATA", "score": 0.6965088248252869, "start": 826, "end": 860, "probe_score": 0.9331, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010477", "page": 62, "chunk": 2, "title": "Ethiopia - Second Coffee Processing and Marketing Project", "pdf_url": "https://documents.worldbank.org/curated/en/268971468023104794/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Ministry of Finance<br>Human Capital Project<br>Designated Account Activity Statement<br>For the quarter ended<br>in USD|Col2|\n|---|---|\n|**Line description**<br>**Opening balance as at the quarter end/i**<br>**IDA advance during the quarter**<br>**Refund to IDA from DA during the quarter**<br>**Less: Transfers out of the DA to the pooled account during the quarter**|**IDA**|\n|||\n|**DA closing balance as at the quarter end carried forward to the next**<br>**period**||\n|||\n|**Bank balance per bank statement**||\n|||\n|**Difference**||\n|/I - enter the amount shown in the previous IFR|/I - enter the amount shown in the previous IFR|", "output": {"entities": {"named_data": ["Designated Account Activity Statement"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005204", "page": 12, "chunk": 0, "title": "Official Documents- 1ST RESTATED DFIL 10182023.pdf", "pdf_url": "https://documents.worldbank.org/curated/en/099112123033023878/pdf/P17228409d1e9b0930be5c0c18552522f97.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Designated Account Activity Statement", "label": "NAMED_DATA", "score": 0.6740662455558777, "start": 49, "end": 86, "probe_score": 0.0589, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "-union-statistics-on-income-and-living-conditions)</u>\n<u>[survey, which the OECD uses as the basis for host country poverty](https://ec.europa.eu/eurostat/web/microdata/european-union-statistics-on-income-and-living-conditions)</u>\nassessments\n\n2. Results for the Czech Republic not individually presented due to\nsampling limitations\n\n3. Accommodation rent support has been calculated as the difference\nbetween the actual equivalized accommodation expense and the\nmedian equivalized market rent in the region\n\n\n\n8 A household is defined to fall below the poverty line if its members fall below the poverty line on individual basis (the\nequivalized income of all household members is the same)\n\n\n\n9 Its magnitude can be computed as the difference between the median equivalized market rent in the region and the actual\nequivalized accommodation expense\n\n\n\n10 Those that are below the poverty line\n\n\n\n**5**", "output": {"entities": {"named_data": ["union-statistics-on-income-and-living-conditions"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 4, "chunk": 2, "title": "3", "pdf_url": "https://local/jad_paddy_docs/3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "union-statistics-on-income-and-living-conditions", "label": "NAMED_DATA", "score": 0.7163968086242676, "start": 1, "end": 49, "probe_score": 0.9359, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "FOR OFFICIAL USE ONLY \nReport No: PAD3682  \n \nINTERNATIONAL DEVELOPMENT ASSOCIATION \n \n \nPROJECT APPRAISAL DOCUMENT \n \nON A \n \nPROPOSED GRANT \n \n \nIN THE AMOUNT OF SDR 92.7 MILLION \n(US$130.8 MILLION EQUIVALENT) \n \nOF WHICH SDR 77.2 MILLION (US$109 MILLION EQUIVALENT) FROM THE  \nWINDOW FOR HOST COMMUNITIES AND REFUGEES  \n \n \nTO THE \n \nREPUBLIC OF UGANDA \n \nFOR THE \n \nROADS AND BRIDGES IN THE REFUGEE HOSTING DISTRICTS / KOBOKO-YUMBE-MOYO \nROAD CORRIDOR PROJECT \n \nSEPTEMBER 24, 2020 \n \n \n \nTransport Global Practice \nAfrica Region \n \n \n \n   \nThis document has a restricted distribution and may be used by recipients only in the performance of \ntheir official duties.  Its contents may not otherwise be disclosed without World Bank authorization. \nPublic Disclosure Authorized\nPublic Disclosure Authorized\nPublic Disclosure Authorized\nPublic Disclosure Authorized", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 0, "chunk": 0, "title": "Uganda - Roads and Bridges in the Refugee Hosting Districts/Koboko-Yumbe-Moyo Road Corridor Project", "pdf_url": "http://documents.worldbank.org/curated/en/834931600048847296/pdf/Uganda-Roads-and-Bridges-in-the-Refugee-Hosting-Districts-Koboko-Yumbe-Moyo-Road-Corridor-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Capítulo 3\n\n\n**Estadísticas demográficas del**\n**desplazamiento interno**\n\n\nLos desplazamientos afectan a personas de todas las\nedades y géneros, y a todas las formas de diversidad.\nTambién puede agravar riesgos preexistentes de\nviolencia, vulnerabilidad, discriminación y marginación, o\nendurecer las barreras de acceso a servicios, asistencia\ny derechos básicos. La pandemia mundial de COVID-19\nha demostrado lo vital que es abordar las necesidades\nespecíficas de protección, como la violencia de género,\ny el abuso o la explotación de mujeres, niños y niñas.\n\n\nEn función de 22 de las 34 operaciones en las que se\ndisponía de datos demográficos a finales de 2020,\nlas mujeres constituían, en promedio, el 52% de todas\nlas PDI, algo que se mantuvo en consonancia con los\naños anteriores. Las proporciones más altas de mujeres\nse registraron en Sudán (57%), Mali, Ucrania y Chad\n(todos con un 56%). Si bien las mujeres y las niñas\nconstituyen la mayoría de las personas desplazadas,\nes de vital importancia mejorar su representación en\nlas estructuras de gestión y liderazgo de la comunidad\npara que puedan participar de forma significativa en los\nprocesos de toma de decisiones que las afectan, como\nasí también a sus familias y sus comunidades.\n\n\nLas niñas y los niños siguieron estando sumamente\nafectados por el desplazamiento", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["datos demográficos"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000160", "page": 27, "chunk": 0, "title": "Tendencias Globales: Desplazamiento Forzado en 2020", "pdf_url": "https://reliefweb.int/attachments/0cdfdecc-4b31-3c18-999d-3e220227e7e3/60cbddfd4.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "datos demográficos", "label": "VAGUE_DATA", "score": 0.7415690422058105, "start": 629, "end": 647, "probe_score": 0.8313, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " are protecting within their land on<br>the western side of the road to cross over to the eastern side. Although part of<br>Soysambu property, the eastern side of the road is characterized by a more<br>important number of human settlements which represents a greater risk of<br>poaching for the giraffes. Furthermore, they have sold part of their land on the<br>eastern side for future development and are considering selling additional land<br>in the same area.<br> <br>|\n|1 and 3|The consideration of endemic<br>small mammals, including the<br>Naivasha African mole-rat<br>(_Tachyoryctes naivashae_)<br>|Small mammals are not specifically taken into account in the wildlife<br>movement study, but they were covered by the biodiversity surveys. The<br>crossing structures in Marula Estate, Soysambu and in the Forest Reserves will<br>also accommodate small mammals and they are located in the best habitat and<br>thus be most useful for small mammals.<br> <br>The only endemic small mammal which distribution overlapped with the RAA,<br>is the Aberdare mole shrew (_Suridisorex norae_). This species is endemic to the<br>east side of the Aberdare Mountain Range. The distribution of this species<br>probably follows the top of this mountain range hence it is unlikely to be found<br>in the LAA, close to the road and no impacts are foreseen.<br> <br>With regards to the African mole-rat, IUCN does not consider T. naivashae as<br>an endemic species, and rather follows Happold (in press) by including <br>_ankoliae, annectens, audax", "output": {"entities": {"named_data": [], "descriptive_data": ["biodiversity surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015028", "page": 28, "chunk": 1, "title": "Kenya - Infrastructure Finance/ PPP Project : Environmental and Social Impact Assessment (Vol. 9 of 11) : Appendices 8-2", "pdf_url": "https://documents.worldbank.org/curated/en/576021645575890094/pdf/Appendices-8-2.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "biodiversity surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8630123138427734, "start": 724, "end": 744, "probe_score": 0.3775, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "needed). As in this report it is stated that only some of the WGs have hired the\nFacilitators by their retained earnings, it seems that the recommendation of the AideMemoire (like many others) has not been met, despite its relevancy in ensuring WGs'\nsustainability.\n\n\nPage 23: At the end of the page it is stated that the Component 2 of the project, for\nInstitutional Building, by means of the IEC sub-component not only could inform\nwomen, their spouse and leaders of their villages about health and education issues, but\nalso could protect women and their families against Harmful Traditional Practices (HTP).\nWe wonder if it would be possible to substantiate the statement with affordable data.\n\n\n45", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["affordable data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016635", "page": 44, "chunk": 0, "title": "Ethiopia - Women Development Initiatives Project", "pdf_url": "https://documents.worldbank.org/curated/en/682741468032069242/pdf/ICR1340REPLACE1LIC01disclosed081211.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "affordable data", "label": "VAGUE_DATA", "score": 0.8028149008750916, "start": 681, "end": 696, "probe_score": 0.2144, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " from PASEC,\nthere exist no standardized tools used to assess of student learning at the national level. At the\nsecondary and higher education levels, except for passing rates on the end-of-cycle exam, evidence\non quality outcomes is lacking.\n\nEvidence from PASEC surveys in Chad (see Table 7 in Annex 7) suggest that conditioning on\nschool socioeconomic status, and teacher and student characteristics, availability of class materials\n\n\nPage 5 of 8", "output": {"entities": {"named_data": ["PASEC surveys"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000020", "page": 4, "chunk": 2, "title": "Project Information Document (Appraisal Stage) - Chad Education Sector Reform Project Phase 2 - P132617", "pdf_url": "http://documents.worldbank.org/curated/en/444901468229746611/pdf/PID-Appraisal-Print-P132617-05-14-2013-1368525900048.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PASEC surveys", "label": "NAMED_DATA", "score": 0.7455888986587524, "start": 258, "end": 271, "probe_score": 0.5711, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " financing<br>leveraged by WSPs. For the corresponding DLI, US$1,000,000 per WSP to match an equal amount leveraged from<br>private capital for up to 5 WSPs.|\n|Frequency|Annual measurement|\n|Data source|WSP and Water Fund M&E records|\n|Methodology for Data<br>Collection|Qualitative inspections and quantitative data collection using M&E protocols defined in the POM|\n|Responsibility for Data<br>Collection|County Government Water Department, WSP, and Water Fund|\n|**WSP customers satisfied with their water supply services (Percentage) **|**WSP customers satisfied with their water supply services (Percentage) **|\n|Description|This indicator measures the number of WSPs that measure at least 80% satisfaction in customers supplied by WSPs<br>under the Program in the areas of continuity and reliability of supply, water quality, and cost. Monitoring includes<br>metadata on the nature of service problems, time to resolution, and other elements as defined in the County-WSP<br>contract.|\n|Frequency|Annual measurement|\n|Data source|WSP M&E records|\n|Methodology for Data|Qualitative inspections and quantitative data collection using M&E protocols defined in the POM|\n\n\n\nPage 45 of 58", "output": {"entities": {"named_data": ["WSP and Water Fund M&E records", "WSP M&E records"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000190", "page": 49, "chunk": 2, "title": "Kenya - Water, Sanitation, and Hygiene Program", "pdf_url": "https://documents1.worldbank.org/curated/en/099120123140034670/pdf/BOSIB-9a6accb6-73d1-4bd1-8307-d41a339a51ab.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "WSP and Water Fund M&E records", "label": "NAMED_DATA", "score": 0.8257080316543579, "start": 203, "end": 233, "probe_score": 0.1133, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "WSP M&E records", "label": "NAMED_DATA", "score": 0.5585346817970276, "start": 1034, "end": 1049, "probe_score": 0.049, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">14.5<br>25.5<br>36.2<br>17.8<br>21.0<br>29.6<br>18.3<br>30.8<br>32.4<br>6.6<br>11.8<br>17.0<br> <br>17.3<br>24.3<br>17.5<br>18.0<br>28.0<br>26.4<br>14.7<br>19.7<br>15.7<br>14.3<br>19.8<br>21.6|\n\n\n\nNote: Data is based on two-year averages of 1991-92, 2001-02, and 2007-08.\n\nSource: Based on UN COMTRADE Statistics (trade data) and UNIDO database (production data).\n\n\n29", "output": {"entities": {"named_data": ["UN COMTRADE Statistics", "UNIDO database"], "descriptive_data": [], "vague_data": ["trade data", "production data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005529", "page": 30, "chunk": 4, "title": "wps6375", "pdf_url": "https://local/prwp/wps6375.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UN COMTRADE Statistics", "label": "NAMED_DATA", "score": 0.9526460766792297, "start": 291, "end": 313, "probe_score": 0.9999, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "trade data", "label": "VAGUE_DATA", "score": 0.8228805661201477, "start": 315, "end": 325, "probe_score": 0.1918, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNIDO database", "label": "NAMED_DATA", "score": 0.928263247013092, "start": 331, "end": 345, "probe_score": 0.9982, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "production data", "label": "VAGUE_DATA", "score": 0.7076169848442078, "start": 347, "end": 362, "probe_score": 0.0881, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda Secondary Education Expansion Project (P166570)\n\n\nthe highest completion rate of over 17 percent, while Karamoja (North) having the lowest at just over 4 percent.\n\n\n12. **Girls’ secondary education experience is characterized by lower access, higher dropout, and lower**\n**transition rates compared to boys** . In 2016, the enrollment rate for boys was four percent higher than for girls\nwith 29 and 25 percent respectively, and the Gender Parity Index (GPI) was at 86 percent. About 25 percent of\ngirls drop out of school because of pregnancy and the levels are higher in Eastern Uganda at 37.3 percent and\nWest Nile at 32.3 percent (Ministry of Education and Sports, MoES, 2015). Completion rates for Senior 4 boys\nstood at 40 percent, compared to 36 percent for girls (Education Management Information System, EMIS 2016).\nThis is due partly to several factors including poverty, the practice of son preference, low value attached to girls’\neducation, and high levels of violence against children in schools, home, and communities. The disparity widens\nat the transition point to Senior 5 with 34 percent of boys and only 24 percent of girls transitioning to upper\nsecondary **.** Learning outcomes tend to be lower for girls in certain subjects. For instance, in 2016 only 33 percent\nof girls in Senior 2 were proficient in mathematics in comparison with 49 percent of boys. <sup>17</sup> [^17: Education and Sports Sector Annual Performance Report, FY16-17, pp. 200 – 201.]\n\n13. **A district-specific perspective reveals important trends in disparity between boys and girls.** Over 75\npercent of all districts have enrollment skewed positively towards boys. Districts with the largest disparity\nbetween enrollment rates of boys and girls include large urban centers, such as Soroti, Mbale and Kampala which\nall have high GERs of 47, 60 and 53 percent respectively. Indeed,", "output": {"entities": {"named_data": ["Education Management Information System"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 16, "chunk": 0, "title": "Uganda - Secondary Education Expansion Project", "pdf_url": "http://documents.worldbank.org/curated/en/406361595815248191/pdf/Uganda-Secondary-Education-Expansion-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Education Management Information System", "label": "NAMED_DATA", "score": 0.6124680042266846, "start": 798, "end": 837, "probe_score": 0.9513, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Project** **Manaeem2nt** <sup>**and**</sup> <sup>million)</sup> administrative data appropriate, and clear in\n\n\n\ndefining the and\n**Innovative Activities**\n\n\n\nresponsibilities of all parties;\nNaCSA retains competent\n**(a) Capacity Building**\n\n\n\nstaff;\n\n                                             - Other governnent and donor\n**(b)** **Information and**\n\nsupport mobilized for\n\n\n\nsupport mobilized for\n**Sensitization**\ndecentralization to\ncomplement NaCSA efforts;\n(c) **Monitoring and**\n\n\n\n**Evaluation**\n\n\n\n**(d)** **Technical Assistance**\n\n\n(e) **Operating** Expenses\n\n\n\n-28", "output": {"entities": {"named_data": [], "descriptive_data": ["administrative data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015858", "page": 32, "chunk": 1, "title": "Kenya - Second Highway Project", "pdf_url": "https://documents.worldbank.org/curated/en/631051468915131261/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "administrative data", "label": "DESCRIPTIVE_DATA", "score": 0.6927050352096558, "start": 64, "end": 83, "probe_score": 0.562, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Annex 1. Key Performance Indicators/Log Frame Matrix**\n\n\n**<u>Outcome / Impact Indicators:</u>**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Indicator/Matrix|1<br>Projected in last PSR|Actual/Latest Estimate|\n|---|---|---|\n|HIV prevalence rate among people aged<br>15-24 years<br>HIV prevalence rate among people aged<br>15-49<br>Median age at first intercourse in people aged<br>20-24<br>Reported condom use at last sex with<br>non-regular partner in people aged 15-19<br>Percentage of people aged 20-24 reporting<br>having a sexually transmitted disease during<br>the previous 12 months<br>Primary school enrollment and completion<br>rates among orphans<br>Mean number of sexual partners among<br>non-married people aged 15-19 in the last 12<br>months|6.7% KDHS 2003<br>9.4% ANC<br>24,000 new infections 0-15 year group in<br>2003<br>62,000 new infections 15-49 year group in<br>2003<br> <br>17.8 years KDHS 2003<br>17.8 years KDHS 2003<br>10.3% men, 0.9% women, KDHS 2003<br>10.3% men, 0.9% women, KDHS 2003|0.4% male, 3% female, 1.6% total (15-19<br>years) KDHS 2003<br>2.4% male, 9% female, 6.0% total (15-24<br>years) KDHS 2003<br>0.9% male", "output": {"entities": {"named_data": ["KDHS 2003"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010728", "page": 29, "chunk": 0, "title": "Kenya - HIV/AIDS Disaster Response Project", "pdf_url": "https://documents.worldbank.org/curated/en/285401468273049624/pdf/36852.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "KDHS 2003", "label": "NAMED_DATA", "score": 0.5649766325950623, "start": 735, "end": 744, "probe_score": 0.9704, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " within the Ministry and<br>broader context of the country; South<br>Sudan is ranked second most corrupt<br>country in the world on transparency<br>corruption perception index.|Project to be implemented with<br>the support of UN Agencies as<br>the main suppliers of goods and<br>services. In addition, direct<br>payments are proposed.|MAFS/MGCS|Throughout the<br>project period.|\n|4|High inflation of local currency<br>resulting lack/limited participation of<br>service providers/suppliers in<br>tendering process especially for low<br>value contracts and NCB.|Bidders given options in the<br>bidding document to bid in other<br>foreign currencies other than<br>local currency.|MAFS/MGCSW|Throughout the<br>project period.|\n|5|Lack of knowledge of the stakeholders<br>involved in procurement and related<br>activities.|The project implementation<br>manual will include a<br>procurement section clearly<br>describing the procurement<br>arrangement, roles, and<br>responsibilities|MAFS/MGCS|Effectiveness.|\n|6|Lack of continuous availability of<br>designated procurement counterpart<br>staff at MAFS/MGCSW hinders transfer<br>of knowledge.|MAFS/MGCSW shall ensure<br>continuous availability of<br>qualified counterpart staff in PCU<br>to work alongside the senior<br>procurement specialist.|MAFS/MGCSW|Throughout the<br>project period.|\n\n\n\n20. **Procurement and Selection Methods:** The procurement of goods, works and non-consulting services will use\nmethods such as international", "output": {"entities": {"named_data": [], "descriptive_data": ["corruption perception index"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 74, "chunk": 1, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "corruption perception index", "label": "DESCRIPTIVE_DATA", "score": 0.7016309499740601, "start": 148, "end": 175, "probe_score": 0.0853, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " construct a more complete disaggregation of aggregate aid into all of its constituent parts according to\n\n\na number of dimensions but focuses almost exclusively on commitments.\n\n\n13Current US$ GDP from World Bank (2006c) is used to express sectoral aid disbursements as a percentage of the GDP.\n\n\n14These data are not publicly available, although they have been used in a variety of publications (e.g., Gupta, Clements, and\n\n\nTiongson, 1998; Baqir, 2002). I am grateful to Gerd Schwartz for sharing these data and to Ali Abbas for assistance in obtaining them.\n\n\n15For Fiji, the observation in 1998 for both sectors is approximately ten times smaller than that in the surrounding years, most\n\n\nlikely due to a typographical error. For instance, public education expenditures account for 0.572% of the GDP in 1998, whereas these\n\n\nexpenditures range from 5.19% to 6.37% of the GDP in all other years from 1993 to 2002. Hence, I change this value to 5.72. Similarly,\n\n\nI adjust the public health expenditure value for 1998 from 0.253% to 2.53% of GDP.\n\n\n16Only for Paris Club concessional debt reorganizations is the net present value reduction in debt achieved by the current rescheduling\n\n\nrecorded (OECD, 2000b, p. 17).\n\n\n17I am grateful to Ibrahim Levent for sending me the updated data (received December 2006) and the Dikhanov paper.\n\n\n18Mokoro (2008) expressly warns against the assumption that aid projects are always off-budget (p. 7) but suggests that the degree\n\n\nto which these projects are captured in budgets is low. (See, e.g., p. 23: “levels of aid on budget are strongly driven by budget support\n\n\naid (which, by definition, is on budget). In many cases, off budget proportions for other aid modalities still remain very high” and p.\n\n\n28", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["updated data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005501", "page": 30, "chunk": 2, "title": "wps6346", "pdf_url": "https://local/prwp/wps6346.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "updated data", "label": "VAGUE_DATA", "score": 0.5854695439338684, "start": 1277, "end": 1289, "probe_score": 0.4607, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**_programme implemented across school districts in the city. Syrian_**\n**_and Palestinian refugee children worked alongside Jordanian host_**\n\n\n\n**_community children to produce this mural. The programme also_**\n**_involved a refugee calligraphy artist and focused on connecting_**\n\n**_communities through creative social cohesion and relationship-_**\n\n\n\n**_building activities. © Artolution, German Corporation for_**\n\n\n\n**_International Cooperation (GIZ), Qudra_**\n\n\n\n<mark>CHAPTER 3</mark>\n# **The extent of** **burden- and** **responsibility-** **sharing**\n\n\nBurden and responsibility sharing is the defining principle of the GCR affirmed by the United Nations\nGeneral Assembly in 2018. This is a testament to the recognition that the predicament of refugees and host\ncommunities is a common responsibility of humankind. As refugee situations increased in scope, scale,\nand complexity and an increasing number of refugees required protection, assistance, and solutions, the\ninternational community committed to lighten the burden of host countries more predictably and sustainably.\nFive years later and in the lead-up to the second Global Refugee Forum, where States and other actors will\ncome together to discuss how to reach the goals of the GCR, it is necessary to assess the extent to which the\ninternational community has lived up to this commitment.\n\n\n26 GLOBAL COMPACT ON REFUGEES INDICATOR REPORT", "output": {"entities": {"named_data": ["GLOBAL COMPACT ON REFUGEES INDICATOR REPORT"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000435", "page": 25, "chunk": 0, "title": "2023 Global Compact on Refugees Indicator Report", "pdf_url": "https://reliefweb.int/attachments/3d407ba2-2493-4519-a8d6-c8b8911d1346/2023-gcr-indicator-report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "GLOBAL COMPACT ON REFUGEES INDICATOR REPORT", "label": "NAMED_DATA", "score": 0.5491639375686646, "start": 1366, "end": 1409, "probe_score": 0.9851, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "data on naturalized refugees are usually uneven and\nincomplete. In instances where refugees acquired citizenship through naturalization, statistical data are often limited, as countries may not distinguish between\nthe naturalization of refugees and that of non-refugees. Thus, many gaps and challenges exist in measuring local integration by the number of naturalized\nrefugees, and the reported number of naturalized\nrefugees in a given period is not a true reflection of\nlocal integration. During 2015, 28 countries reported\nat least one naturalized refugee, two countries more\nthan the previous year ~~FIGURE 11~~ .\n\n\n\n**~~feelings about their move to Afghanistan; they will~~**\n\n**~~miss Pakistan, but they are also excited to see their~~**\n\n**~~own country for the first time.~~**\n\n\nThe total number of naturalized refugees stood at\n32,000 during 2015, compared to 32,100 reported in\n2014. As in the previous year, Canada reported the\nlargest number of naturalized refugees in 2015, with\n25,900. This represents approximately 81 per cent\nof all naturalized refugees reported during the year.\nOther countries that reported large numbers of naturalized refugees included France (2,500), Belgium\n(1,700), and Austria (1,000). ●\n\n\nUNHCR Global Trends 2015 **27**", "output": {"entities": {"named_data": ["UNHCR Global Trends 2015"], "descriptive_data": ["data on naturalized refugees"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001367", "page": 25, "chunk": 0, "title": "UNHCR Global Trends: Forced Displacement in 2015", "pdf_url": "https://reliefweb.int/attachments/d39729ec-75aa-3628-89e5-6ae32a617930/576408cd7.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on naturalized refugees", "label": "DESCRIPTIVE_DATA", "score": 0.5446591377258301, "start": 0, "end": 28, "probe_score": 0.8041, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "statistical data", "label": "VAGUE_DATA", "score": 0.6970078349113464, "start": 137, "end": 153, "probe_score": 0.7249, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHCR Global Trends 2015", "label": "NAMED_DATA", "score": 0.7176787853240967, "start": 1231, "end": 1255, "probe_score": 0.9956, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 15,902\n\n\n**7. Szczecin** 14,318\n\n\n**8. Poznanski** 14,028\n\n\n**9. Pruszkowski** 12,206\n\n\n\n\n\n\n\n18-59 female and male\n\n\n\n\n\n60+ female and male\n\ntwo 18-59 or 60+ females\n\nother households\n\n\n\n\n\n\n\n18-59 female with one or\nmore 60+ individuals\n\n\n\ntwo 18-59\n\nfemales\n\n\n\n0.3% 7.4%\n\n\n\n\n\n**10. Katowice** 11,591\n\n\n\nNote that poviat-level population does not include Ukrainian refugees, who were added to calculate their appropriate shares.\n\nSource: Deloitte own elaboration based on the PESEL database as of September 2024 and GUS population data as of mid-2024.\n\n#### **1.3 Households income sources**\n\n\n\n18-59 female\nand male\n\n\nother\nhouseholds\n\n\n\n\n\nNote: Some groups that constituted less than 2% of households have been omitted.\n\nSource: Deloitte own elaboration based on SEIS (May-June 2024) UNHCR (2024) survey.\n\n\n\n**The majority of refugees settled in**\n**major cities, especially Warsaw and**\n**Wroclaw, and their vicinities.** Eight most\npopulous poviats in Poland <sup>5</sup> comprising\n16% of the host population, are also the\ntop eight poviats in terms of the number\nof Ukrainian refugees, 29% of whom\nreside there. This shows that Ukrainian\nrefugees are more concentrated in the\nlargest cities than the host population,\nas they migrated to the most attractive\n\n\n5 Seven cities and Poznański poviat.\n\n\n10\n\n\n\n11\n\n\n\nlabour markets, where they have better\nchances of supporting themselves.\nUkrainian refugees make up the largest\nshares of the population in the city of\nWroclaw (7.4%), Przemysl, a city on the\nUkrainian border (6.5%), and in Pruszkowski\npoviat", "output": {"entities": {"named_data": ["PESEL database", "GUS population data", "SEIS", "UNHCR (2024) survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 5, "chunk": 1, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PESEL database", "label": "NAMED_DATA", "score": 0.9089705348014832, "start": 477, "end": 491, "probe_score": 0.9914, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "GUS population data", "label": "NAMED_DATA", "score": 0.8659365773200989, "start": 517, "end": 536, "probe_score": 0.9517, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "SEIS", "label": "NAMED_DATA", "score": 0.7088881134986877, "start": 766, "end": 770, "probe_score": 0.4326, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHCR (2024) survey", "label": "NAMED_DATA", "score": 0.6554114818572998, "start": 787, "end": 806, "probe_score": 0.9423, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " fully mitigated. Lebanese\npoliticians at the highest level have expressed to the donor community and the WB their\nreadiness to expedite and facilitate the approval of development loans and grants, especially\nthose linked to the GCFF. The WB has also been engaging with government counterparts to raise\nawareness of the importance of timely implementation and to seek political commitment to\nensure swift loan ratification and approval that are required for effectiveness and the\ncommencement of activities.\n\n\nb) **Technical design** **risks** associated with the contracting process involving NGOs and the inability\n\nto attract and enroll targeted beneficiaries is substantial. There are also risks related to potential\nerrors and fraud in enrollment of beneficiaries. _Mitigation:_ The proposed project builds on the\nexisting interventions and lessons learned from the ongoing health project. Risks related to the\ncontracting process will be mitigated by requiring PHCCs and hospitals to develop a detailed\nproject implementation readiness plan, based on the results of rapid facility assessments that\nfocus on the project’s goals, design, and expected outcomes. The readiness plans will clearly\n\n\nPage 27 of 54", "output": {"entities": {"named_data": [], "descriptive_data": ["rapid facility assessments"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000032", "page": 29, "chunk": 1, "title": "Lebanon - Health Resilience Project", "pdf_url": "http://documents.worldbank.org/curated/en/616901498701694043/pdf/Lebanon-Health-PAD-PAD2358-06152017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "rapid facility assessments", "label": "DESCRIPTIVE_DATA", "score": 0.8033580183982849, "start": 1072, "end": 1098, "probe_score": 0.0474, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " larger share of data being collected from more\nvulnerable households.\n\n\nThere was also a notably high non-response rate regarding questions related to income and expenditure,\nwhich likely resulted in non-response bias. The income module of the SEIS was also materially different from\nthe one employed by the EU SILC and the Republic of Moldova’s Household Budget Survey, which may limit\ncomparability of this data to that of host populations.\n\n\nIt is also important to highlight that there were slight differences in the questionnaire across countries. Not all\nquestions were consistently included in all country-level surveys, and some answer options were individually\nadjusted.\n\n\nLastly, the survey was conducted during the summer months, coinciding with both host country and Ukraine\nschool holidays. This period often sees many households temporarily visiting Ukraine, which impacted the\naccessibility of households and posed challenges in meeting targets, particularly in certain countries and\ngeographic locations.\n\n\n**15**", "output": {"entities": {"named_data": ["Household Budget Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 14, "chunk": 1, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Household Budget Survey", "label": "NAMED_DATA", "score": 0.7651577591896057, "start": 347, "end": 370, "probe_score": 0.0183, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "output": {"entities": {"named_data": [], "descriptive_data": ["random survey"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000102", "page": 16, "chunk": 0, "title": "Burundi - Second Social Action Project", "pdf_url": "http://documents1.worldbank.org/curated/en/590301468744270104/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7714613080024719, "start": 379, "end": 395, "probe_score": 0.582, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "random survey", "label": "DESCRIPTIVE_DATA", "score": 0.7173007130622864, "start": 1487, "end": 1500, "probe_score": 0.012, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**<u>Asylum Levels and Trends in Industrialized Countries 2007</u>**\n\n|Table 20. Asylum applications lodged in 43 industrialized countries by origin, fourth quarter 2007<br>Covering 29 major asylum countries which provided monthly data to UNHCR. Values between 1 and 4 have been replaced with an asterisk.<br>See Annex I for country codes used.|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|Col10|Col11|Col12|Col13|Col14|Col15|Col16|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n|Origin<br>|AUL<br><br>|AUS<br><br>|BEL<br><br>|BUL<br><br>|CAN<br><br>|CYP<br><br>|CZE<br><br>|DEN<br><br>|FIN<br><br>|FRA<br><br>|GBR<br><br>|GFR<br><br>|GRE<br><br>|HUN<br><br>|IRE<br><br>|\n|Iraq<br>|46<br> <br><br>|124<br> <br><br>|218<br> <br><br>|221<br> <br><br>|93<br> <br><br>|58<", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["monthly data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001058", "page": 31, "chunk": 0, "title": "Asylum levels and trends in industrialized countries, 2007", "pdf_url": "https://reliefweb.int/attachments/a0f955c8-b460-3603-b1cc-8d2ccc064a5f/BF4CF8525B21A81049257410001BC61A-Full_Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "monthly data", "label": "VAGUE_DATA", "score": 0.688606321811676, "start": 223, "end": 235, "probe_score": 0.688, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad COVID-19 Strategic Preparedness and Response Project (P173894)\n\n\n\nPage 6", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000039", "page": 10, "chunk": 0, "title": "Chad - COVID-19 Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/717781588366403375/pdf/Chad-COVID-19-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nKenya: Integrated Devolution and Urban Support Program (P177048)\n\n\n\n\n\n**B. Introduction and Context**\n\n\nCountry Context\n\n\n**1.** **Kenya experienced steady economic growth and declining poverty levels up to 2019 but the COVID-19 pandemic**\n**has had a severe impact on the economy and poverty levels since then.** From 2004 until 2019, Kenya’s GDP grew at an\nannual average of 5.3 percent, with absolute poverty numbers declining. <sup>1</sup> [^1: Draft Kenya County Partnership Framework FY 22-27, World Bank Group] The share of the population living below the\nnational poverty line decreased from 46.8 percent in 2005 to 36.8 percent in 2016 and to 33.4 percent in 2019. Kenya’s\nHuman Development Index rose by 9.1 percent to 0.60 in the decade leading up to 2019, as a result of significant\ninvestments in health care and basic education. GDP contracted by 0.3 percent in 2020. <sup>2</sup> [^2: GoK (2021) Economic Survey 2021, Kenya National Bureau of Statistics] Poverty increased sharply in\n2020 due to jobs and earnings losses. Poverty levels increased by 4 percentage points during 2020.\n\n\n**2.** **However, Kenya’s economy has been recovering and real gross domestic product (GDP) is expected to increase**\n**by an estimated 5.0 percent in 2021 and by 4.9 percent over the period 2022/23, close to its pre-pandemic rate** . <sup>3</sup> [^3: The World Bank Group (2021), Kenya Economic Update: From Recovery to Better Jobs] This\nis supporting renewed job creation and poverty reduction. Government revenues have also rebounded, facilitating fiscal\nconsolidation efforts. However, some sectors (such as tourism) still face major difficulties, and further COVID-19", "output": {"entities": {"named_data": ["Human Development Index", "GoK (2021) Economic Survey 2021"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007536", "page": 2, "chunk": 0, "title": "Concept Stage Program Information Document (PID) - Kenya: Integrated Devolution and Urban Support Program - P177048", "pdf_url": "https://documents.worldbank.org/curated/en/099810005042230106/pdf/P177048015281f040bbf20739d365b7cd4.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Human Development Index", "label": "NAMED_DATA", "score": 0.5891095399856567, "start": 701, "end": 724, "probe_score": 0.9254, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "GoK (2021) Economic Survey 2021", "label": "NAMED_DATA", "score": 0.8535968065261841, "start": 919, "end": 950, "probe_score": 0.9985, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " conflict already in full flight, from the international community acting, as\nit usually does, within a ‘discipline of crisis’ (Charlesworth 2002).\n\n\nThe causal links between structural inequality and mass atrocity crimes which Bellamy\nneeds as proof of worth will vary with context and will not come sign-posted as leading\nto genocide, and might happen at a blisteringly rapid pace. It is more likely that the link\nto genocide and mass atrocity will not be found in relation to minority groups or weak\nstates. Is the link between military intervention and protection of civilians backed by any\nfirm evidence? Rwanda is the situation the world wants to avoid, but even in Rwanda\nevents may unfold differently in the future.\n\n\nA preventative approach to the risk of mass atrocity means that such interventions may\nsometimes be proved wrong, because judgments are made genuinely before the fact.\nGetting that judgment as correct as possible will be crucial. Fears that the intervention\npillar has the capacity to undermine the neutrality of humanitarian assistance are wellfounded, and this will affect the credibility of the prevention and reaction pillars.\n\n\nIn my view, the best basis of protection of civilians in a time of conflict is trust in the\ninternational community during peacetime, and the best chance of an early warning is to\nhold a legitimate place of trust in the affected community beforehand, as a neutral\nsupporter and provider of human rights protections and development assistance. This is a\ncontention which requires research data to test it.\n\n\n12", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["research data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001456", "page": 13, "chunk": 1, "title": "Refugees, internally displaced persons and the 'responsibility to protect'", "pdf_url": "https://reliefweb.int/attachments/e2537dbd-a79e-305a-9a90-75e03a893f25/E02F5556457A246E852576E200700470-unhcr-responsibility-to-protect-mar2010.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "research data", "label": "VAGUE_DATA", "score": 0.7979031801223755, "start": 1538, "end": 1551, "probe_score": 0.0121, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " GBVIMS, July 2015 – February 2016. Data is only from reported cases and is in no way representative of the total\nincidence or prevalence of GBV in Iraq. Statistics are generated exclusively by GBV service providers who use the GBVIMS\nfor data collection in GBV response activities in a limited number of locations across Iraq and with the consent of survivors.\n13 “Iraq Woman Integrated Social and Health Survey (I-WISH) Summary Report”, March 2012.\n14 “Uncertain Futures: The impact of displacement on Syrian refugee and Iraqi internally displaced youth in Iraq”. Save the\nChildren, 2016.\n15 “Initial Findings of GBV Risk Assessment in IDP Camps and Critical Shelter Arrangements across Iraq”. IOM, September\n2015.\n16 GBVIMS, July 2015 – February 2016. This statistic represents all GBV cases, not just sexual violence.\n17 GBV risks amongst IDPs Living in Critical Shelters and Camps, International Organization for Migration (IOM), September\n2015\n\n\n7", "output": {"entities": {"named_data": ["GBVIMS", "GBVIMS", "Iraq Woman Integrated Social and Health Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000831", "page": 6, "chunk": 2, "title": "Iraq GBV Sub-Cluster Strategy for 2016", "pdf_url": "https://reliefweb.int/attachments/7b5840ee-6ff0-3698-b5db-fef3cc2dca0f/gbv_sub-cluster_strategy_iraq_2016_full_endorsed.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "GBVIMS", "label": "NAMED_DATA", "score": 0.6019001603126526, "start": 1, "end": 7, "probe_score": 0.9582, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "GBVIMS", "label": "NAMED_DATA", "score": 0.520457923412323, "start": 228, "end": 234, "probe_score": 0.935, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Iraq Woman Integrated Social and Health Survey", "label": "NAMED_DATA", "score": 0.7759695649147034, "start": 366, "end": 412, "probe_score": 0.3596, "gold": "DATA_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "similarly detailed household data not only from the three districts analyzed here but also from all\n\n\nthe districts in the province. <sup>20</sup>\n\n\nIn their haste to adopt a type of program that has been successful elsewhere,\n\n\npolicymakers incorporated some elements (the conditionality and relative size of the transfer) but\n\n\nchanged others (the targeting based on gender). If the literature on program evaluation has taught\n\n\nus anything it is that generalizing from one setting to another is at best optimistic and at worst an\n\n\nexercise doomed to failure. This seems particularly true of evaluations of programs in developing\n\n\ncountries where program design and implementation frequently are found to diverge.\n\n\nConsequently policymakers in these countries should be more careful to incorporate data\n\n\ncollection at baseline and at follow-up to ensure that context-specific evaluations are possible.\n\n\nThe analysis presented here and existing evidence on the effects of the program suggest\n\n\nthat it is successful in sending girls to school. A substantial body of evidence exists on the\n\n\nbenefits to society of educating women. <sup>21</sup> [^21: See for instance the arguments in Schultz, 2001 on the need for governments the world over to invest more in\ngirls’ education and the evidence in Andrabi et. al., 2007 on how educated girls transition from being students today\nto teachers tomorrow in the Pakistani districts studied in the present paper.] The children of more educated mothers have better\n\n\neducational and health outcomes. Such evidence alone should justify the continuation of this\n\n\ngender-targeted stipend program – with obvious attention being paid to capacity constraints that\n\n\nare known to emerge in schools and education systems. However, an examination of data from\n\n\nthe PSLM suggests another channel through which society could benefit from such programs.\n\n\nThere is a stark correlation between regional levels of maternal literacy and the sex ratios of\n\n\nchildren within households (Figure 8). Specifically it appears that in regions with lower levels of\n\n\nliteracy there is a substantially higher ratio of boys to girls. If we are to take this correlation\n\n\nseriously then it appears that in", "output": {"entities": {"named_data": ["data from\n\n\nthe PSLM"], "descriptive_data": ["household data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004448", "page": 23, "chunk": 0, "title": "wps5256", "pdf_url": "https://local/prwp/wps5256.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household data", "label": "DESCRIPTIVE_DATA", "score": 0.7423122525215149, "start": 19, "end": 33, "probe_score": 0.5252, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "data from\n\n\nthe PSLM", "label": "NAMED_DATA", "score": 0.8233944773674011, "start": 1790, "end": 1810, "probe_score": 0.872, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "We also entertain an additional instrumental variable in the form of government effectiveness obtained\n\n\nfrom the Worldwide Governance Indicators. This variable specifically captures perceptions of the quality\n\n\nof public services, the quality of the civil service and the degree of its independence from political pressures,\n\n\nthe quality of policy formulation and implementation, and the credibility of the government's commitment\n\n\nto such policies. Better public and civil service as well as the quality of policy formulation are likely to be\n\n\npositively correlated with data transparency. We take the average score for the years available predating\n\n\nthe sample - 1996-2003 – to aim for some level of exogeneity. While government effectiveness alone may\n\n\nbe a harder sell in terms of satisfying the exclusion restriction, the fact that we account for other governance\n\n\nmeasures such as Voice and Accountability, Political Stability, Rule of Law and Control of Corruption,\n\n\nmay limit the direct effects of government effectiveness as defined on economic growth.\n\n\nThe results for the Instrumental Variables estimations using legal origins as instruments are presented in\n\n\nTable 2. Columns 1 and 2 provide the second stage and first stage results respectively for the estimations\n\n\nwith legal origins as instrumental variables. The first stage results show that French and German legal\n\n\norigins are positively correlated with the SCI, statistically significant at the 1 percent level. The second\n\n\nstage shows that SCI has a positive coefficient, statistically significant at the 5 percent level. The magnitude\n\n\nis somewhat larger than all the other panel and OLS cross-section estimates, indicating an elasticity of 0.04\n\n\npercent (annualized). The Hansen test of overidentifying restrictions does not reject the joint null that the\n\n\ninstruments are valid. The underidentification test rejects the null that the instruments are underidentified,\n\n\nindicating that they are relevant. The weak identification test shows that the F-stat is greater than most of\n\n\nthe Stock and Yogo thresholds (with the exception of the 10% maximal IV size) implying the instruments\n\n\nare not weak. <sup>11</sup> Do", "output": {"entities": {"named_data": ["Worldwide Governance Indicators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000236", "page": 25, "chunk": 0, "title": "data transparency and long run growth", "pdf_url": "https://local/prwp/data-transparency-and-long-run-growth.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Worldwide Governance Indicators", "label": "NAMED_DATA", "score": 0.904852032661438, "start": 114, "end": 145, "probe_score": 0.9826, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nRoads and Employment Project (P160223)\n\n\n7. **Meanwhile, the Syria conflict has also exacerbated the labor market situation** . Since the refugee\ninflux, the labor force in Lebanon increased by as much as 35 percent. Because of the low level of\neducation of the Syrian refugees ‐ 87 percent of working age refugees have less than a secondary level\neducation ‐ the refugee crisis has also led to an oversupply of low skilled workers and to an increase in\ninformality. Almost all Syrian refugees are working informally. The construction sector is the second\nlargest employer of Syrian refugees in Lebanon (24.1 percent), after household work (26.5 percent), and\nis followed by wholesale/retail (11.1 percent), manufacturing (10.6 percent), agriculture (9.1 percent),\nfood and beverages (4.9 percent), and others. The lack of opportunities for unskilled and low‐skilled\nLebanese and refugee workers is important, given that unemployment that affects specific social groups\nmore than others (in this case refugees and lower‐skilled Lebanese males, and youth within both groups)\ncan lead to inter‐group grievances that in turn fuel extremism and conflict.\n\n\n8. **To weather the crisis, Lebanon is adopting a two‐pronged approach aimed at programs to**\n**stimulate the economy and create jobs, while meeting Lebanon’s longer‐term development needs**\n**particularly in the infrastructure sectors.** Given the slowing economy and the impact of the Syria conflict,\nLebanon is in urgent need to rapidly inject investments to stimulate its economy and create jobs as the\npresence of a large number of unskilled and unemployed Lebanese and Syrians has a significant negative\nsocial, economic, and security impacts that could further destabilize the country. The Government of\nLebanon’s (GOL) strategy is to rapidly increase its public investments in key sectors, particularly the\ninfrastructure sectors,", "output": {"entities": {"named_data": ["Roads and Employment Project"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 15, "chunk": 0, "title": "Lebanon - Roads and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/210611486651815142/pdf/Lebanon-Roads-Employment-PAD-P160223-01262017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Roads and Employment Project", "label": "NAMED_DATA", "score": 0.5720702409744263, "start": 19, "end": 47, "probe_score": 0.4142, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 13,330 13,330 13,330 13,330\nR-squared 0.679 0.682 0.682 0.679 0.681\nTreatment Obs 5342 5342 5342 5342 5342\n<u>Control Obs</u> <u>7988</u> <u>7988</u> <u>7988</u> <u>7988</u> <u>7988</u>\n<u>Notes: Robust standard errors in parentheses;</u> <sup>***</sup> <u>p<0.01,</u> <sup>**</sup> <u>p<0.05,</u> <sup>*</sup> <u>p<0.1; avg_radBuff05 ranges from 0.14 to 16.64.</u>\n\n### Limitation and Discussion\n\n\nAssessing the quantitative impact of disasters on populations and economies is particularly\nchallenging in poor and conflict-affected regions, where reliable socio-economic data may be\nlacking. Our analysis of descriptive statistics has indicated a tendency towards lower nightlight\ndensity in rural areas, which could potentially lead to an underestimation of economic activity due\nto the limitations in spatial resolution. Nightlight radiance in rural settings is typically less intense\nthan in urban centers, and a higher incidence of such readings could result in a skewed sample.\nFurthermore, sectors like agriculture, which are less dependent on electricity, might not be fully\nrepresented by nightlight data. This is particularly true for poorer households in rural areas that may\nnot have access to electricity, rendering them invisible in satellite-based observations.\nConsequently, vital aspects of a developing economy might be missed when relying exclusively on\nnightlight data for analysis.\n\n\nNonetheless, and despite these limitations, access to advanced earth observation", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["socio-economic data", "nightlight data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001351", "page": 29, "chunk": 2, "title": "idu167bd455d1907a14d67194fd18951da0a2ff3", "pdf_url": "https://local/prwp/idu167bd455d1907a14d67194fd18951da0a2ff3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "socio-economic data", "label": "VAGUE_DATA", "score": 0.5973384380340576, "start": 558, "end": 577, "probe_score": 0.5285, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "nightlight data", "label": "VAGUE_DATA", "score": 0.5930321216583252, "start": 1099, "end": 1114, "probe_score": 0.9139, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "24\n\n\n**During negotiations the following assurances were received:**\n\n\n1. Agreement on triggers for subsequent phases\n2. Agreement on monitoring and impact assessment studies\n3. Agreement on project monitoring indicators\n4. Agreement on finalized bidding documents for the first batch of schools\n\n\n**Actions to be included in Development Credit Agreement:**\n\n\n_Financial_\n\n\n1. Audits and Project Management Reports.\n2. Dated covenant on the selection of the auditor before March 31, 2001.\n\n\n_Management_\n\n\n1. Daied covenant on a baseline survey to establish gender and social class distribution of students\nbefore December 31, 2001.\n2. Provide regular reports on monitoring indicators and prepare a draft midterm report for review\nwith IDA before September 15, 2002.\n\n\n**In addition the following Management conditions are included in supplemental letters attached**\n**to the Developinent Credit Agreement:**\n\n\n1. Triggers from Phase I to Phase II in APL\n2. Triggers from Phase II to Phase III in APL\n\n\nH. READINESS **FOR IMPLEMENTATION**\n\n\nL. a) The engineering design documents for the first year's activities are complete and ready for the\n\nstart of project implementation.\nD b) Not applicable.\n\n3 2. The procurement documents for the first year's activities are complete and ready for the start of\nproject implementation.\n\n\nK/ 3. The Project Implementation Plan has been appraised and found to be realistic and of satisfactory\n\nquality.\n##### D 4. \"he following 7tems are lacking and are discussed under loan conditions (Section G):", "output": {"entities": {"named_data": [], "descriptive_data": ["baseline survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016767", "page": 27, "chunk": 0, "title": "Kenya - Animal Health Services Project", "pdf_url": "https://documents.worldbank.org/curated/en/690781468047696262/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "baseline survey", "label": "DESCRIPTIVE_DATA", "score": 0.810932993888855, "start": 529, "end": 544, "probe_score": 0.1317, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 11\nPage 2 of 4\n\n\nThe country's General Environmental Law, expected to be promulgated very shortly, is divided into four\nmajor titles:\n\n\nTitle 1: Concepts, Objectives and General Principles, and Institutional\nOrganization\nTitle 2: Protection of Environments\nTitle 3: Protection of Animal and Plant Species\nTitle 4: Regulation of Pollution\n\n\nImplementing decrees should quickly specify the conditions for putting the main chapters of this\nframework legislation into effect.\n\n\n_Other Agencies And Bodies Involved_\n\n\nAs regards environmental education, the Directorate of the Environment maintains close collaboration\nwith the National Education Research and Pedagogic Information Center _[Centre de Recherche, et de_\n_Production dInformation de l 'Education Nationale-_ CRIPEN], in particular through the formulation of an\n\nawareness campaign strategy on environmental problems.\n\n\nInfrastructure facilities in the education sector are provided by the Directorate of Housing, Urban\nDevelopment, Environment, and Regional Development (DHU). However, as the current reform process\nis not yet completed, a number of serious malfunctions are preventing the Directorate from perforning\nthe role of executing agency assigned to it in the past. The Planning Unit of the Ministry of Education\nwill be the contracting authority's representative for implementation of this project.\n\n\nBecause the system for gathering and analyzing data on the public health system is no longer operational,\nas was confirmed during the visit made to Djibouti's Pelletier Hospital and to the Djibouti-City health\ndistrict, reliable country-wide epidemiological data are unfortunately unavailable. This state of affairs\napplies to the school population in particular. Under these conditions, it will be difficult to define and use\nindicators capable of measuring the success of actions to mitigate the environmental impacts of the\nproject.\n\n\n**Potential Impacts of the Project**\n\n\nThe mission by an IDA environment specialist to the Republic of Djibouti in June 2000 confirmed the\ndegraded situation of the sanitary facilities in all of the schools visited. Discussions with school staff and\nparents of students revealed the concern felt by the latter regarding the", "output": {"entities": {"named_data": [], "descriptive_data": ["country-wide epidemiological data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015713", "page": 65, "chunk": 0, "title": "Kenya - Animal Health Services Project", "pdf_url": "https://documents.worldbank.org/curated/en/621531468046806478/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "country-wide epidemiological data", "label": "DESCRIPTIVE_DATA", "score": 0.8293556571006775, "start": 1605, "end": 1638, "probe_score": 0.3437, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**DEPARTAMENTO DE ARAUCA** | Agosto de 2024\n\n\n**Metodología**\n\n\nLa metodología de esta actualización de análisis de protección ha combinado monitoreo periódicos del Equipo Local de\nCoordinación de Arauca, el subgrupo de trabajo de Niñez y el Subgrupo de trabajo de VBG, al igual que insumos cualitativos\nde las reuniones y consultas con los socios locales, informantes clave y población afectada. El proceso de análisis ha seguido\nla metodología de severidad y las estimaciones de Personas en Necesidad (PIN) y el Marco Analítico de Protección (PAF).\n\n\n**Limitaciones**\n\n\nEl presente análisis ha seguido una lógica de análisis cualitativo y cuantitativa derivado de datos oficiales para posterior\ninterpretación por parte de expertos. Por otra parte, para evitar los potenciales riesgos que se podrían llegar a generar\npara las comunidades, se limitó el encuentro con las mismas.\n\n\nPor lo tanto, los ejercicios de recolección de información y análisis de la situación humanitaria se centraron en datos\nsecundarios y entrevistas con referentes en el territorio.\n\n\nPara obtener más información, póngase en contacto con: **Sebastián Díaz Parra** <u>[diazj@unhcr.org |](mailto:diazj@unhcr.org)</u> **Gabriela Villota** <u>[gabriela.villota@drc.ngo](mailto:", "output": {"entities": {"named_data": [], "descriptive_data": ["datos oficiales"], "vague_data": ["datos\nsecundarios"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000549", "page": 9, "chunk": 0, "title": "Colombia: Análisis de protección | ARAUCA - Análisis de los riesgos de protección relacionados con el conflicto armado (agosto de 2024)", "pdf_url": "https://reliefweb.int/attachments/4fdc9fbd-e142-44ac-9081-aea9737d1b9b/pau_arauca_aug-24_espanol.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "datos oficiales", "label": "DESCRIPTIVE_DATA", "score": 0.6429951786994934, "start": 666, "end": 681, "probe_score": 0.4966, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "datos\nsecundarios", "label": "VAGUE_DATA", "score": 0.5616969466209412, "start": 996, "end": 1013, "probe_score": 0.5031, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " top\nsource countries of asylum-seekers in the\n44 industrialized countries in 2012. This\nis comparable to 2011, when Afghani\n\n\nstan, China, Iraq, Serbia and Pakistan\nwere the top-ranking source countries.\n\nIn 2012, **Afghanistan** remained the\nmain country of origin of asylum-seekers in industrialized countries. Provisional data indicate that some 36,600\nAfghans requested refugee status in\n2012. This was virtually unchanged\ncompared to 2011 (36,200 claims). The\ncontinued volatile situation in the country may be one reason why Afghans\ncontinue to seek asylum abroad. The\nshare of asylum-seekers from Afghanistan in the total number of asylum\nclaims has remained stable at 8 per cent\nin the past two years [ _see_ **Figure 6** ].\n\nAfghan asylum-seekers sought international protection in almost all of the\n44 industrialized countries. The levels\nwere highest in Germany (7,500 claims)\nand Sweden (4,800 claims). In Germany,\nthe number of Afghan asylum claims\ndropped by 3 per cent while in Sweden\nit went up by 13 per cent. Other important destination countries were Turkey\n(4,400 claims; UNHCR procedure),\nAustria (4,000 claims), and Australia\n(3,100). In all three cases, figures went\nup, with increases ranging from 11 per\n\n\n\n\n\ncent (Austria) to 79 per cent (Australia).\nSerbia (and Kosovo: S/RES/1244 (1999))\nemerged as a new destination country\nfor Afghan asylum-seekers in 2011:\n1,700 asylum claims were lodged during\nthe year. In 2012, this figure was halved.\n\nWith 24,800 asylum applications\nsubmitted by **Syrians** in 2012, this is the\nhighest figure on record [ _see_ **Figure 7** ].\nThe number almost tripled compared\nto 2011 (8,500 claims). This made the\nSyrian Arab Republic the second highest-ranking source country of asylumseekers", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Provisional data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000259", "page": 15, "chunk": 1, "title": "Asylum Trends 2012: Levels and Trends in Industrialized Countries", "pdf_url": "https://reliefweb.int/attachments/1d378692-f0b2-38f8-b665-26b190296276/UNHCR%20ASYLUM%20TRENDS%202012_WEB.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Provisional data", "label": "VAGUE_DATA", "score": 0.7592722773551941, "start": 314, "end": 330, "probe_score": 0.0585, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSupport for Social Recovery Needs of Vulnerable Groups in Beirut (P176622)\n\n\n**17.** **An exacerbating economic and political crisis, COVID-19 and the POB blast have further heightened negative**\n**feelings and experiences for many, particularly vulnerable people in Beirut.** Traumatizing events, loss, separation,\nfinancial struggles or drastic changes in social and living conditions are likely to lead to people experiencing several\ndistressing psychological reactions, which might have short or long-term impacts on people’s mental health and\npsychosocial wellbeing. The explosion as well as its political and economic shockwaves have affected most families,\ntheir community structures, schools and workplaces, increased risks and exacerbated pre-existing vulnerabilities and\ninequalities. The results of several surveys undertaken since the blast have shown that a significant number of\nrespondents have experienced and continue to experience mental health issues. <sup>37</sup> Many refer to this as negatively\nimpacting on their personal well-being and their sense of social inclusion and connection to their families and\ncommunities.\n\n\n**18.** **The mental health sector in Lebanon has been undergoing a major reform, initiated by the National Mental Health**\n**Programme in 2015.** Progress has been made as shown by the external mid-term evaluation conducted in 2018, <sup>38</sup> for\nthe implementation of the National Mental Health and Substance Use Prevention, Promotion, and Treatment Strategy\n(2015-2020). <sup>39</sup> That being said, the COVID-19 pandemic as well as the severe economic crisis and the Beirut port blast\nsignificantly increased the toll on the mental health of the population and highlighted even more the need for scalable\nevidence-based mental health interventions. The inter-sectoral Mental Health and Psychosocial Support (MHPSS)\naction plan developed for", "output": {"entities": {"named_data": [], "descriptive_data": ["surveys undertaken since the blast"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000054", "page": 7, "chunk": 0, "title": "Concept Project Information Document (PID) - Support for Social Recovery Needs of Vulnerable Groups in Beirut - P176622", "pdf_url": "http://documents.worldbank.org/curated/en/883871626924990781/pdf/Concept-Project-Information-Document-PID-Support-for-Social-Recovery-Needs-of-Vulnerable-Groups-in-Beirut-P176622.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "surveys undertaken since the blast", "label": "DESCRIPTIVE_DATA", "score": 0.5641555190086365, "start": 837, "end": 871, "probe_score": 0.8316, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an age when they think they can help around the household.", "output": {"entities": {"named_data": [], "descriptive_data": ["Household Survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000147", "page": 38, "chunk": 2, "title": "Rwanda - Human Resources Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/837731468759911848/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Household Survey", "label": "DESCRIPTIVE_DATA", "score": 0.6743227243423462, "start": 166, "end": 182, "probe_score": 0.4582, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "schools who return to<br>school once the school<br>system is reopened|Annual<br>|The<br>enrollment<br>will be<br>monitored<br>through the<br>EMIS data.<br>|The enrollment will be<br>monitored through the<br>EMIS data.<br>|MoES/PCU<br>|\n\n\n|Monitoring & Evaluation Plan: Intermediate Results Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **|**Definition/Description **|**Frequency **|**Datasource **|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|IRI 1: Awareness and health safeguarding<br>messages disseminated to students,<br>teachers, parents and community<br>members through various media (SMS,<br>text, TV and radio) (number)|Defn: Awareness and health <br>safeguarding messages are<br>designed to reach a specific<br>audience (in this case:<br>students, teachers and<br>parents) to stop the spread|Bi-annual<br>|Approved m<br>aterials<br>|Reports on materials<br>disseminated<br>|CIM, Gender Unit<br>|\n\n\nPage 31 of 43\n\n\nOfficial Use\n\n\n\n**ME PDO Table SPACE**", "output": {"entities": {"named_data": ["EMIS data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000034", "page": 35, "chunk": 1, "title": "Uganda - COVID-19 Emergency Education Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/645041598936002560/pdf/Uganda-COVID-19-Emergency-Education-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "EMIS data", "label": "NAMED_DATA", "score": 0.7207796573638916, "start": 141, "end": 150, "probe_score": 0.6811, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Nicoletti, Giuseppe, Stefano Scarpetta, and Olivier Boylaud. 1999. “Summary Indicators of\nProduct Market Regulation with an Extension to Employment Protection Legislation,” OECD\nEconomics Department Working Paper, No. 226. Paris.\n\nOECD. 2002. Regulatory Policies in OECD Countries: From Interventionism to Regulatory\nGovernance. Paris.\n\nOECD. 2005. OECD Economic Surveys. Brazil. Paris.\n\nOECD. 2007. OECD Economic Surveys. Ukraine. Paris.\n\nSchultze, Charles. 1977. The Private Use of public Interest. Brookings Institution. Washington,\nDC.\n\n\n28", "output": {"entities": {"named_data": ["OECD Economic Surveys", "OECD Economic Surveys"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004293", "page": 29, "chunk": 0, "title": "wps5100", "pdf_url": "https://local/prwp/wps5100.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "OECD Economic Surveys", "label": "NAMED_DATA", "score": 0.6565430760383606, "start": 349, "end": 370, "probe_score": 0.0724, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "OECD Economic Surveys", "label": "NAMED_DATA", "score": 0.5249531865119934, "start": 400, "end": 421, "probe_score": 0.0623, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000029", "page": 19, "chunk": 1, "title": "West Bank and Gaza - Health System Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/221361468779450522/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7292463183403015, "start": 272, "end": 283, "probe_score": 0.8771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda Secondary Education Expansion Project (P166570)\n\n\nthat 40 percent of teachers in schools have been placed there based on factors other than the class time\nrequired by students. <sup>9</sup> [^9: UNESCO 2014, Teacher Issues in Uganda: A shared vision for an effective teachers’ policy.] Old curricula (replaced in 2020) used to further complicate teacher allocation\nacross schools by imposing too many subjects that required specialized teachers. This inefficiency was\nresolved by the new curricula.\n\n\n8. **In spite of increased access to schooling, the average level of education of the work force remains low**\n**and does not meet labor market requirements.** Uganda has been absorbing 600,000 new entrants to the labor\nmarket each year since 2014. In order to sustainably increase welfare, these entrants must find productive\nemployment. <sup>10</sup> [^10: Uganda job diagnostics/strategy, World Bank, 2018, draft.] Estimates from the Uganda National Household Survey (UNHS) (2016) show that only entrants\nwith post-secondary education can escape informal sector work. In order to increase the employability and\nproductivity of the expanding workforce, supply of quality education, especially for low-income, rural households\nand girls, is critical. According to the UNHS, only one in five people aged 15 and above completed full secondary\neducation. Thus, a large number of youth enter the job market without foundational skills of basic literacy and\nnumeracy, as well as generic skills essential for life and work.\n\n\n9. **Uganda is a pioneer in SSA in terms of setting the goal of achieving universal access to secondary**\n**education.** The secondary education sub-sector in Uganda is centrally managed and comprises six grades, Senior\n1 (S1) to Senior 6 (S6). S1-S4 is categorized as ordinary (‘O’) level, or lower secondary, while S5-S6 is Advanced\n(‘A’", "output": {"entities": {"named_data": ["Uganda National Household Survey", "UNHS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000060", "page": 14, "chunk": 0, "title": "Uganda - Secondary Education Expansion Project", "pdf_url": "http://documents1.worldbank.org/curated/en/406361595815248191/pdf/Uganda-Secondary-Education-Expansion-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Uganda National Household Survey", "label": "NAMED_DATA", "score": 0.9097748398780823, "start": 964, "end": 996, "probe_score": 0.9795, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHS", "label": "NAMED_DATA", "score": 0.5107841491699219, "start": 1296, "end": 1300, "probe_score": 0.9429, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "s/average-</u>\n<u>gross-wage-in-the-second-quarter-2024,281,43.html</u>\n\n\n14\n\n\n\n9 These employment rates are very close to the ones from the Polish central bank surveys of Ukrainian refugees, which showed 62% in July 2023 and 68% in July\n2024 (NBP, 2024). NBP (2024) age group was slightly different, describing adults as 18 years or older.\n\n10 See the note on median wage estimation method in the Online Technical Appendix.\n\n11 Since 2021, ZUS has been requesting information about the occupation of non-agricultural workers who first join the social insurance system (most farmers have a\nseparate social insurance system). Unfortunately, this data is not yet comprehensive, as on June 30, 2022, it included 4.8 million people, and June 30, 2024, 7.2 million\n\n- out of about 16 million socially insured workers. Nevertheless, it is still a very large sample and thus a useful proxy, especially in the case of Ukrainian refugees who\npresumably all should have their occupations listed as they did not arrive before 2022.\n\n\n15", "output": {"entities": {"named_data": ["Polish central bank surveys of Ukrainian refugees"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 7, "chunk": 3, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Polish central bank surveys of Ukrainian refugees", "label": "NAMED_DATA", "score": 0.6532855033874512, "start": 141, "end": 190, "probe_score": 0.9856, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_Share who are 35 and older_ 59.3\n(1.4)\n\n\n\n48.8\n\n\n55.1\n\n\n31.9\n\n\n42.2\n\n\n\n_Share who have less than secondary_\n_education_\n\n\n\n4.1\n(0.6)\n\n\n\n65.8\n(0.7)\n\n54.4\n(1.0)\n\n37.0\n(0.7)\n\n42.1\n<u>(2.0)</u>\n\n\n\n_Share who report working in past week_ 59.7\n(1.5)\n\n_Share who are refugees_ 46.5\n<u>(1.4)</u>\n\n\n\nNotes: All survey sample shares are of individuals aged 18 and older. Clustered standard errors are reported in parentheses\nfor survey estimates. Population shares by region, gender, and age are derived from population projections provided by PCBS\nin early 2022 and refer to individuals aged 18 and older. Population shares by educational attainment are based on population\nprojections published by PCBS for 2021 and refer to individuals aged 15 and older. Population shares by labor force status\noriginate in the 2021 Palestinian Labor Force Survey and refer to individuals aged 15 and older; the share reported here is of\nemployed individuals. Population shares by refugee status come from 2017 estimates published by PCBS and refer to all\nindividuals.\n\n\nPrecision-comparability tradeoffs in calibrating the Facebook weights to population proportions\n\n\nThe initial weighting strategy for the Facebook survey imposed a substantial set of calibration constraints\nto try to maximize comparability with the PPCS and correct for a skewed achieved sample. PPCS weights\nwere calibrated to population proportions using two sets of constraints based on population projections\nbased on the most recent census: (1) the number of households by governorate and urban/rural/camps,\nand (2) the number of adults by region, five-year age groups, and gender. The weighting approach for the\nFacebook survey followed a slightly simplified version of this calibration structure using population\nproportions by governorate", "output": {"entities": {"named_data": ["population projections provided by PCBS", "2021 Palestinian Labor Force Survey"], "descriptive_data": ["population\nprojections published by PCBS for 2021"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000821", "page": 14, "chunk": 0, "title": "idu06ae9560f0dd1004b440b9c90c0ee1da42011", "pdf_url": "https://local/prwp/idu06ae9560f0dd1004b440b9c90c0ee1da42011.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "population projections provided by PCBS", "label": "NAMED_DATA", "score": 0.5941640138626099, "start": 500, "end": 539, "probe_score": 0.9402, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "population\nprojections published by PCBS for 2021", "label": "DESCRIPTIVE_DATA", "score": 0.558862566947937, "start": 655, "end": 704, "probe_score": 0.9899, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2021 Palestinian Labor Force Survey", "label": "NAMED_DATA", "score": 0.8831800818443298, "start": 806, "end": 841, "probe_score": 0.9772, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " in green. n=681, age individuals aged 18-64.\n\nSource: Deloitte own elaboration based on SEIS UNHCR survey.\n\n\n\nFluent\n\n\n\nAdvanced\n\n\n\nIntermediate\n\n\n\nNone\n\n\n\nBeginner\n\n\n\nSource: Deloitte own elaboration based on SEIS UNHCR survey.\n\n\n**Chart 24. What Ukrainian refugee groups have weakest Polish language fluency?**\n\nOdds ratio of Ukrainian refugees intermediate and below knowledge of Polish language\nLogistic regression model\n\n\n2.38\n\n\n\n\n\n\n\n\n\n**Ukrainian refugees visibly improve**\n**their Polish language fluency over**\n**time.** In the SEIS UNHCR survey, on\naverage, Ukrainian refugees who said\nthey were fluent in Polish had stayed in\nPoland for 29 months, while those with an\nintermediate level – for only 22 months.\nThe results are interesting, especially the\nfact that the average time required to\n\n\n32\n\n\n\n33\n\n\n\nprogress from advanced to fluent language\nlevels was longer than from intermediate\nto advanced, or beginner to intermediate\n(although not from zero to beginner). It\nis likely that the highest level of fluency,\nwhich may be required in some of the most\nattractive occupations, is also the hardest\nto achieve, and such language courses are\nnot as readily available.", "output": {"entities": {"named_data": ["SEIS UNHCR survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 16, "chunk": 3, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS UNHCR survey", "label": "NAMED_DATA", "score": 0.7365857362747192, "start": 89, "end": 106, "probe_score": 0.9995, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " loss of\nincome which is due to either poor business activities or loss of job. The challenge brought\nthe majority (76%) to a very low income of below N20,000. Further disaggregation revealed\nthat the incidence of reduced income and restriction to income cut across different classes\nof households’ size and occupation (Appendix I: Figure 41 - 42). The situation must have\nforced most of the PoCs to be solely dependent on remittances being provided by UNHCR\nand other humanitarian actors.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001132", "page": 18, "chunk": 1, "title": "Socio-economic impact assessment of COVID-19 pandemic among persons of concern in Nigeria (July 2020)", "pdf_url": "https://reliefweb.int/attachments/abd6c9f8-0ad1-3eed-9a20-ccfff76b766a/Report%20on%20Assessment%20of%20Socio-Economic%20Impact%20of%20COVID-19%20on%20PoCs_19082020.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "32\n\n\nCastells-Quintana, David, “Malthus living in a slum: Urban concentration, infrastructure and economic growth,” _Journal_\n\n_of Urban Economics_, 2017, _98_, 158–173. Urbanization in Developing Countries: Past and Present.\n\n\nand Hugh Wenban-Smith, “Population dynamics, urbanisation without growth, and the rise of megacities,” _The_\n_Journal of Development Studies_, 2020, _56_ (9), 1663–1682.\n\n\nand Vicente Royuela, “Agglomeration, inequality and economic growth,” _The_ _Annals_ _of_ _Regional_ _Science_, 2014, _52_,\n343–366.\n\nChauvin, Juan Pablo, Edward Glaeser, Yueran Ma, and Kristina Tobio, “What is different about urbanization in rich and\n\npoor countries? Cities in Brazil, China, India and the United States,” _Journal of Urban Economics_, 2017, _98_ (C), 17–49.\n\nChen, Jiandong, Ming Gao, Shulei Cheng, Wenxuan Hou, Malin Song, Xin Liu, and Yu Liu, “Global 1 km _×_ 1 km gridded\n\nrevised real gross domestic product and electricity consumption during 1992–2019 based on calibrated nighttime light\ndata,” _Scientific Data_, 2022, _9_ (1), 202.\n\nCombes, Pierre-Philippe and Laurent Gobillon, “The empirics of agglomeration economies,” in “Handbook of regional\n\nand urban economics,” Vol. 5, Elsevier, 2015, pp. 247–348.\n\nDuranton, Gilles and Diego Puga, “Micro-foundations of urban agglomeration economies,” in J. V. Henderson and J. F.\n\nThisse, eds., _Handbook_ _of_ _Regional_ _and_ _Urban_ _Economics", "output": {"entities": {"named_data": [], "descriptive_data": ["calibrated nighttime light\ndata"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001342", "page": 34, "chunk": 0, "title": "idu1656c109c19b45142331af8916d39792d10d2", "pdf_url": "https://local/prwp/idu1656c109c19b45142331af8916d39792d10d2.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "calibrated nighttime light\ndata", "label": "DESCRIPTIVE_DATA", "score": 0.6704956889152527, "start": 985, "end": 1016, "probe_score": 0.1866, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " poverty, labor markets,\nand other welfare indicators at the country level. Including\nthem can contribute to filling socioeconomic data gaps on\ninternational displacement, while providing crucial inputs\n\n\n\nto inform targeted responses, policies, and programs for refugees and host communities. Particularly, increasing panel\ndata across refugee and host communities would provide\na rich learning to assess how welfare and social cohesion\ntrends change over time. Investigating this hypothesis and\nothers underlines our earlier point, the need for panel data\nto monitor changes of the same household over times of war\nand forced displacement.\n\n\n**74. Socioeconomic data with a focus on the displacement**\n**trajectory can further enhance the design of solutions**\n**for displacement.** Socioeconomic surveys are essential to\nunderstand the current living conditions of households to\ninform policies, for example, on labor markets and safety\nnets as well as health and education. However, they usually\ndo not consider the specific displacement trajectory of refugees who are affected by traumatic episodes causing them to\ncross international borders. It is critical to understand refugees’ vulnerabilities and needs in order to find solutions. It is\nrecommended that a forcibly displaced module be developed\nby development organizations in collaboration with national\nstatistics offices, to serve as an input for existing surveys,\nsuch as national surveys that measure poverty, Living Standards Measurement Surveys, and beyond. A standardized\nforced displacement module that measures the vulnerabilities faced by refugees and other forcibly displaced persons\nis essential to complete the picture needed for informing\noptimal national policies and programming. A newly developed framework by the World Bank has been administered\nto displaced populations in Ethiopia, Nigeria, Somalia, South\nSudan, and Sudan—and should be considered for future data\ncollection of refugees in Kenya and other countries in the\nregion. <sup>93</sup>\n\n\n93 \u0007Pape and Sharma. 2019. Informing Durable Solutions for Internal\nDisplacement in Nigeria, Somalia, South Sudan, and Sudan.\n\n\n33", "output": {"entities": {"named_data": ["Living Standards Measurement Surveys"], "descriptive_data": ["Socioeconomic surveys", "national surveys that measure poverty"], "vague_data": ["panel\ndata", "Socioeconomic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000641", "page": 45, "chunk": 1, "title": "Understanding the Socioeconomic Conditions of Refugees in Kenya | Volume A: Kalobeyei Settlement - Results from the 2018 Kalobeyei Socioeconomic Survey", "pdf_url": "https://reliefweb.int/attachments/5db37855-7edd-3a88-a03c-464668a5c042/6034c5124.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "panel\ndata", "label": "VAGUE_DATA", "score": 0.600263774394989, "start": 319, "end": 329, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Socioeconomic data", "label": "VAGUE_DATA", "score": 0.5705335140228271, "start": 650, "end": 668, "probe_score": 0.0908, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Socioeconomic surveys", "label": "DESCRIPTIVE_DATA", "score": 0.7092121243476868, "start": 785, "end": 806, "probe_score": 0.3435, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "national surveys that measure poverty", "label": "DESCRIPTIVE_DATA", "score": 0.837342381477356, "start": 1437, "end": 1474, "probe_score": 0.2719, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Living Standards Measurement Surveys", "label": "NAMED_DATA", "score": 0.795458972454071, "start": 1476, "end": 1512, "probe_score": 0.0687, "gold": "NON_MENTION", "gold_tier": "human-final"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " se definen\nen función de su lugar de nacimiento.\nLa muestra no ponderada incluyó\na 3,018 ecuatorianos y 1,261\nvenezolanos.\n\n\nPerú\n\n\n**El análisis de venezolanos en Perú**\n**se hizo con base en la ENPOVE**,\nrealizada por el INEI y financiada por\nel Banco Mundial.\n\n\nLa encuesta se realizó en dos rondas.\nLa primera se ejecutó en noviembrediciembre del 2018. La segunda se\nrealizó en febrero-marzo del 2022,\ncon el apoyo del Centro Conjunto de\nDatos (JDC por sus siglas en inglés)\nde ACNUR y el Banco Mundial.\nAmbas rondas fueron conducidas\nde manera presencial. Aportan\ninformación detallada sobre las\ncaracterísticas de la vivienda, y de\nlos miembros del hogar, como por\nejemplo, estatus migratorio, salud,\neducación, empleo, discriminación,\ngénero y victimización. El presente\ninforme utiliza información de la\nronda 2022, que cuenta con una\nmuestra de 7,751 individuos.\n\n\n**La** **información** **sobre** **las**\n**comunidades de acogida se obtuvo**\n**de la ENAHO** . Implementada por\nel INEI, la ENAHO permite obtener\n\n\n\nVenezolanos en Chile, Colombia, Ecuador y Perú\n\n       - una oportunidad para el desarrollo\n\n\ninformación detallada sobre las\ncaracterísticas de la vivienda y\nlos miembros del hogar. Se utiliza\npara monitorear la evolución de los\nindicadores de pobreza, bienestar\ny condiciones", "output": {"entities": {"named_data": ["ENPOVE", "ENAHO"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001322", "page": 55, "chunk": 2, "title": "Venezolanos en Chile, Colombia, Ecuador y Perú - una oportunidad para el desarrollo", "pdf_url": "https://reliefweb.int/attachments/cbb1b9bf-3a48-463c-acb0-a587a681628a/P175780133597e0f11b72c1f7779efcaba1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "ENPOVE", "label": "NAMED_DATA", "score": 0.8077191710472107, "start": 197, "end": 203, "probe_score": 0.0024, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "ENAHO", "label": "NAMED_DATA", "score": 0.5345560312271118, "start": 961, "end": 966, "probe_score": 0.0, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Factors theorised to affect resettled refugees' labour market integration and their studies**<br>**(Grey for quantitative correlationsand white for qualitative findings)**<br>|\n|||||||\n|||||||\n||**Factor**|**Work cited**|**Country(city &**<br>**population) **|**Correlate**|**More detail**|\n|<br>|<br>|<br>|<br>|<br>|<br>|\n|**Demographic Variables**|**Demographic Variables**|**Demographic Variables**|**Demographic Variables**|**Demographic Variables**|**Demographic Variables**|\n|||||||\n||Gender|Bevelander <br>Hagström, &<br>Rönnqvist, 2009|Sweden<br>|employment<br>rate|do not control for other<br>variables|\n||Gender|<br>Codell et al,<br>2011|US (Salt Lake<br>City); 50%<br>Burmese, 25%<br>Bhutanese, 25%<br>Iraqis|wage<br>|85, Based on admin data;<br>young earn more; women<br>earned less|\n||Gender|Franz, 2003<br>|<br>US (NYC,<br>Bosnian)|selection of<br>employment<br>(more low-<br>skilled, low-<br>paid)|qualitative, also looked at<br>them in Bosnia<br>|\n||Gender|Ib", "output": {"entities": {"named_data": [], "descriptive_data": ["admin data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001008", "page": 44, "chunk": 1, "title": "The labour market integration of resettled refugees", "pdf_url": "https://reliefweb.int/attachments/97c91085-db0b-389e-8aa0-5cd80b1ee5a3/the%20labour%20market%20integration%20of%20resettled%20refugees.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "admin data", "label": "DESCRIPTIVE_DATA", "score": 0.8064637184143066, "start": 742, "end": 752, "probe_score": 0.9664, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " school after getting\n\n\n20 Sabit et al. (2013). Sociocultural beliefs and practices influencing institution delivery service in three\ncommunities of Ethiopia: qualitative study\n21 Central Statistical Agency (CSA) [Ethiopia] and ICF. 2016. _Ethiopia Demographic and Health Survey 2016_ . Addis Ababa, Ethiopia, and Rockville,\nMaryland, USA: CSA and ICF.\n22 FMoH. (2016a). Federal Democratic Republic of Ethiopia Maternal and Child Health Directorate Child Stunting and Community Based\nNutrition in Ethiopia: Current Evidence and Policy Implications, 2006(21), 1–7\n23 Ethiopian Public Health Institute (EPHI) [Ethiopia] and ICF. 2021 _. Ethiopia Mini Demographic and Health Survey 2019: Final Report_ . Rockville,\nMaryland, USA: EPHI and ICF.\n24 Ali, D., Saha, K. K., Nguyen, et al (2013). Household Food Insecurity Is Associated with Higher Child Undernutrition in Bangladesh, Ethiopia,\nand Vietnam, but the Effect Is Not Mediated by Child Dietary Diversity. Journal of Nutrition, 143(12), 2015–2021.\n25 Tariku et al. (2014). Tariku, B., Mulugeta, A., Tsadik, M. and Azene, G. (2014) Prevalence and Risk Factors of Child Malnutrition in Community\nBased Nutrition Program Implementing and No implementing Districts from South East Amhara, Ethiopia. Open Access Library Journal, 1.\n26 Parkes, J., Heslop, J., Johnson Ross, F., Westerveld, R. & Unterhalter, E. 2017b. Addressing SRGBV in Ethiopia: A scoping study of policy and\npractice to reduce gender-based violence in and around schools. UCL Institute of Education.\n27 MOFED, MOE, UNICEF and British Council (2010). Guideline for Gender Sensitive Budgeting on Girl’s Education in Ethiopia.\n28 M", "output": {"entities": {"named_data": ["Ethiopia Mini Demographic and Health Survey 2019"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002502", "page": 2, "chunk": 2, "title": "Final Technical Assessment - Ethiopia Human Capital Operation - P172284", "pdf_url": "https://documents.worldbank.org/curated/en/099051723114023878/pdf/P1722840472c3e0f092f300d88c3d9e675.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Ethiopia Mini Demographic and Health Survey 2019", "label": "NAMED_DATA", "score": 0.537330687046051, "start": 635, "end": 683, "probe_score": 0.2798, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Needs or Survivors of\nViolence and/or Torture categories (28 and 27 per cent,\nrespectively). This was followed by Lack of Foreseeable\nAlternative Durable Solutions (20 per cent) and Women\n\n\n\nand Girls at Risk (13 per cent), Children and Adolescents at\nRisk (eight percent) and Medical Needs (four per cent).\n\n\nIn terms of urgency of resettlement cases, slightly\nmore than two per cent (489 cases) were deemed an\n“emergency priority”, requiring evacuation in 72 hours,\noften with support from States hosting emergency transit\nfacilities. This is almost a 69 per cent increase from 2017.\nAbout 15 per cent (3,451 cases) were considered “urgent\npriority” needing removal within weeks (almost a doubling\nof cases compared to 2017).\n\n\nIn 2018, Emergency Transit Facilities (ETFs) continued\nto be utilized as a protection tool for refugees who were\nin need of resettlement on an urgent basis, as well as an\nalternative site for case processing of refugee populations\nnot accessible to resettlement states. During the last year,\n215 refugees departed for resettlement from the ETFs in\nthe Philippines and Romania.\n\n\nAt the end of 2017, the Government of Niger agreed to\nthe establishment of an Evacuation Transit Mechanism\n(ETM) on its territory. The ETM is a special and atypical\nevacuation programme aimed at responding to the lifethreatening and compelling protection needs of refugees\nand asylum-seekers stranded in Libya and facilitating\ntheir access to solutions. Since September 2017, 2,211\nindividuals have been submitted for resettlement through\nthe ETM and 1,403 of them have departed from Niger. <sup>6</sup>\n\n\n6 Data through 11 June 2019.\n\n\n\n13", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Data through 11 June 2019"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000739", "page": 13, "chunk": 1, "title": "UNHCR Projected Global Resettlement Needs 2020", "pdf_url": "https://reliefweb.int/attachments/6ce5b0b3-c2b0-3a37-afa5-11faad94047c/5d1384047.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data through 11 June 2019", "label": "VAGUE_DATA", "score": 0.7794829607009888, "start": 1618, "end": 1643, "probe_score": 0.6076, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">0.32</mark></u>** **<u><mark>1.54</mark></u>**\nDemographic component **0.53**\n<u>Annual % change in GVA per capita</u> **<u>2.07</u>**\n\n\n\nSource: Author’s estimation based on data described in Section 2.\n\n\n**Appendix Table 5. Burkina Faso: Sectoral decomposition of GDP per capita**\n\n**<u>growth: 2005-2014 (Annual percentage changes)</u>**\n% Contribution of\n\n\n\n\n\n\n\n\n\n\n\nAgriculture -0.05 -1.27 0.35 0.06 0.41 -0.91\nMining 0.32 0.04 0.21 0.00 0.21 0.58\nUtilities -0.89 0.12 0.52 -0.01 0.51 -0.26\nManufacturing 0.43 -0.02 -0.31 0.00 -0.31 0.11\nConstruction -0.37 0.06 0.39 0.00 0.39 0.08\nCommerce -0.20 0.25 0.13 0.00 0.12 0.18\nTransport 0.24 0.04 0.34 0.00 0.34 0.63\nFinance 0.52 -0.05 -0.31 0.00 -0.31 0.16\nOther services -0.27 0.04 0.41 -0.01 0.40 0.18\n\n\n**Appendix Table 6. Cote d’Ivoire: Sectoral decomposition of GDP per capita**\n\n**<u>growth: 2008-2014 (Annual percentage changes)</u>**\n% Contribution of\n\n\n\n\n\n\n\n\n\n\n\nAgriculture -0.23 0.06 0.69 0.16 0.84 0.67\nMining -0", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data described in Section 2"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007286", "page": 31, "chunk": 1, "title": "wps8336", "pdf_url": "https://local/prwp/wps8336.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data described in Section 2", "label": "VAGUE_DATA", "score": 0.757590651512146, "start": 176, "end": 203, "probe_score": 0.9786, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and (b) improved quality of agricultural products in the Beqaa governorate <sup>21</sup>, due to\nreduced utilization of pesticides and nutrients. It is thus considered that indirect beneficiaries cover the\npopulation of Beqaa governorate, which is estimated at around **800,000**, or 18 percent of the country’s\npopulation. <sup>22</sup> [^22: Estimated based on a total population of 4.5 million (World Bank 2014. Data Development Platform) and a ratio of 17.8 percent for Beqaa (Central\nAdministration Statistics of Lebanon online).] Furthermore, an additional 525,000 refugees currently residing in the Beqaa area will\nindirectly benefit from the project <sup>23</sup> [^23: UNHCR estimate that 35% of Syrian Refugees reside in the Bekaa Governorate] .\n\n\n   - Direct project beneficiaries (number) of which female (percentage) (Core indicator)\n\n   - Quantity of municipal wastewater collected and treated under the project (daily flow in m <sup>3</sup> )\n\n   - Nutrient load reduction (Nitrogen[N]) achieved under the project (tons/year) (Core indicator)\n\n   - Number of locations monitored monthly for water quality (no.)\n\nIII. **PROJECT DESCRIPTION**\n\n\n**Description**\n\n\n21. **_Rationale for the proposed project_** . River clean-up and pollution prevention require sustained\npolitical will and resources over a long period. The Business Plan provides a set of actions that need to\nbe implemented to reduce the pollution of Qaraoun Lake. While the most critical sources of pollution\nneed to be addressed first, the nature and scale of challenges will evolve with time and, therefore, the\n\n\n19 This represents a population of 306,430 in 2015 (Zahlé sewers subcomponent [167,590]; Anjar sewers subcomponent [116,150]; and Aintanit sewers\nsubcomponent [22,690]), expected to grow at 1.75 percent", "output": {"entities": {"named_data": ["Central\nAdministration Statistics of Lebanon online"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000036", "page": 15, "chunk": 1, "title": "Lebanon - Lake Qaraoun Pollution Prevention Project", "pdf_url": "http://documents1.worldbank.org/curated/en/279341468589482380/pdf/PAD860-PAD-P147854-R2016-0133-1-Box396255B-OUO-9.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Central\nAdministration Statistics of Lebanon online", "label": "NAMED_DATA", "score": 0.7873669266700745, "start": 482, "end": 533, "probe_score": 0.999, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\n**9/31/2022** **NERAMP/USD/23/03** Sept'22 bank charges **1,981** **1**\n\n**11/30/2022** **NERAMP/USD/23/04** November'22 bank charges 522,941 140\n\n**12/31/2022** **NERAMP/USD/23/05** December'22 bank charges **260,031** **71**\n\n**1/31/2023** **NERAMP/USD/23/06** January'23 bank charges **385,722** **105**\n\n**2/28/2023** **NERAMP/USD/23/08** Feb'23 bank charges **74,833** 21\n\n**3/31/2023** **NERAMP/USD/23/08** March'23 bank charges **1,997** **1**\n\n4/30/2023 **NERAMP/USD/23/09** April'23 bank charges **2,027** **1**\n\n**5/31/2023** **NERAMP/USD/23/10** May'23 bank charges **132,385** **36**\n\n\n\n**6/30/2023** **NERAMP/USD/23/12** June'23 bank charges **722,062** **197**\n\n**2,669,650** **720**\nSub-Total: **USD**\n\n\n\n**b)** **UGX** Designated <sup>Account</sup> <sup>at BoU</sup>", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001618", "page": 70, "chunk": 1, "title": "Uganda - EASTERN AND SOUTHERN AFRICA - P125590 - Uganda North-Eastern Road Corridor Asset Management Project (NERAMP) - Audited Financial Statement", "pdf_url": "https://documents.worldbank.org/curated/en/099040324025010660/pdf/P12559013e16060d8197e01d566ff107e77.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Project Development Objective Indicators|Col2|\n|---|---|\n|**Indicator Name : **|**Description (indicator definition etc.) **|\n|Direct project beneficiaries of safety net programs<br>(individuals), of which women (%)|Direct beneficiaries of safety net programs are the number of NPTP card holders.|\n|Beneficiaries of safety net programs (number), of<br>which are e-card food vouchers|The breakdown of beneficiaries of which are e-card food voucher beneficiaries.|\n|NPTP beneficiaries from extremely poor households<br>as a share of total NPTP beneficiaries.|Beneficiaries=NPTP card holders.<br>Extreme poverty=$3.84/day per person in 2012 prices.|\n|Number of NPTP Applicants|Households that have applied to the program.|\n|Time Lapse between application and eligibility<br>notification|Acceptance notification must be accompanied by a benefits card (not<br>cumulative).|\n|Household awareness of NPTP|Percentage of respondents to the opinion poll survey that have head of the NPTP.|\n|Proportion of assisted people informed about the e-<br>card food program (who is included, what people<br>receive, and where they can complain)|Households that have been provided training in SDCs on the e-card food voucher<br>system.|\n|||\n\n\n24", "output": {"entities": {"named_data": [], "descriptive_data": ["opinion poll survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000047", "page": 34, "chunk": 0, "title": "Lebanon - Emergency National Poverty Targeting Program Project", "pdf_url": "http://documents.worldbank.org/curated/en/810511467987899324/pdf/PAD1030-ENGLISH-P149242-PUBLIC-FINAL-LEB-ENPTP-English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "opinion poll survey", "label": "DESCRIPTIVE_DATA", "score": 0.8390054702758789, "start": 932, "end": 951, "probe_score": 0.8978, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nGreater Beirut Public Transport Project (P160224)\n\n\nprojects being implemented. The complexity of dealing with several donors and their\nregulations also adds to the strain on its staff, increasing the possibility of mistakes.\nThe RPTA has 240 employees, of whom 16 are administrative and technical staff and\nwill be supported by key experts through the project to assist with the management of\nthe project.\n\n\n**(c)** **Record keeping.** All the records of procurement activities are maintained at the CDR by the\nprocurement team.\n\n\n**(d)** **Procurement planning.** The CDR has extensive experience with procurement planning,\n\nespecially the units working on World Bank projects.\n\n\n**(e)** **Audit.** The institution exercises internal audit and appoints an external independent auditor\n\nwho covers all implemented projects. Usually, the auditor is appointed for three years. Till\ndate, audit opinion was clean (‘unqualified’) and audit reports are received on time and of\nsatisfactory quality.\n\n\n**(f)** **Procurement assessment risks and mitigations.** The overall procurement implementation\nrisk is assessed as Substantial mitigated to Moderate. Risks identified are the following: (i)\ndelay in procurement processing and implementation; (ii) delay in decisions toward contract\npackaging; (iii) coordination and inclusiveness of other concerned stakeholders, ministries,\nand so on; (iv) bidding document and technical specifications development; and (v) contract\nmanagement. The following mitigation measures are proposed: (i) mapping procurement\nprocessing to meet reasonable efficiency; (ii) readiness of contracts packaging by Loan\nAgreement signing; (iii) development of first bidding documents by effectiveness; and (iv)\nassigning technical staff, engineers, field supervision consultants, and experts to support\nprocurement bidding documents development and to monitor contracts. RPTA capabilities\nare not yet proven and risks are inherent to managing PPP", "output": {"entities": {"named_data": [], "descriptive_data": ["records of procurement activities"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000022", "page": 59, "chunk": 0, "title": "Lebanon - Greater Beirut Public Transport Project", "pdf_url": "http://documents.worldbank.org/curated/en/471241521338566907/pdf/PAD-final-02262018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "records of procurement activities", "label": "DESCRIPTIVE_DATA", "score": 0.568008303642273, "start": 464, "end": 497, "probe_score": 0.1373, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "participation and community-dnven <sup>development activities);</sup> <sup>(ii)</sup> <sup>accelerating</sup> <sup>economic</sup> <sup>growth; and (iii)</sup>\n\n\n\nexpanding access of the poor <sup>to basic social</sup> <sup>services,</sup> <sup>infrastructure, and markets.</sup> <sup>The National</sup> <sup>Social</sup>\n\nAction Project (NSAP) <sup>is</sup> <sup>the principal</sup> <sup>World Bank lending instrument intended</sup> <sup>to provide support</sup> <sup>for</sup>\n\nNaCSA. The project is expected <sup>to reduce</sup> <sup>the risk of renewed</sup> <sup>conflict and</sup> <sup>generate sustained</sup> <sup>poverty</sup>\n\n\n\nreduction through temporary <sup>employment and</sup> <sup>re-establishing</sup> <sup>basic service</sup> <sup>delhvery.</sup> <sup>Priority will</sup> <sup>be</sup>\n\n\n\ngiven to areas that have <sup>recently</sup> <sup>come</sup> <sup>under Government control.</sup>\n\n\n\n**2.** **Main sector** issues **and**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013578", "page": 7, "chunk": 0, "title": "Ethiopia - Rangelands Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/475521468022460472/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000102", "page": 62, "chunk": 2, "title": "Burundi - Second Social Action Project", "pdf_url": "http://documents1.worldbank.org/curated/en/590301468744270104/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank** Implementation Status & Results Report\nEnhancing Shared Prosperity through Equitable Services (P151432)\n\n\n**Data on Financial Performance**\n\n\n**Disbursements (by loan)**\n\n\nProject Loan/Credit/TF Status Currency Original Revised Cancelled Disbursed Undisbursed % Disbursed\n\n\nP151432 IDA-57160 Effective USD 600.00 600.00 0.00 597.66 5.92 99%\n\n\nP151432 IDA-61310 Effective USD 600.00 600.00 0.00 580.29 19.11 97%\n\n\nP151432 IDA-68830 Effective USD 250.00 250.00 0.00 59.81 176.80 25%\n\n\nP151432 IDA-D2290 Effective USD 100.00 100.00 0.00 71.63 28.03 72%\n\n\nP151432 TF-A7523 Effective USD 7.67 7.67 0.00 7.67 0.00 100%\n\n\nP151432 TF-A9293 Effective USD 20.57 20.57 0.00 11.68 8.89 57%\n\n\n**Key Dates (by loan)**\n\n\nProject Loan/Credit/TF Status Approval Date Signing Date Effectiveness Date Orig. Closing Date Rev. Closing Date\n\n\nP151432 IDA-57160 Effective 15-Sep-2015 22-Oct-2015 11-Dec-2015 01-May-2019 31-May-2023\n\n\nP151432 IDA-61310 Effective 14-Sep-2017 29-Sep-2017 05-Feb-2018 31-May-2023 31-May-2024\n\n\nP151432 IDA-68830 Effective 20-May-2021 04-Jun-2021 27-Aug-2021 31-May-2024 31-May-2024\n\n\nP151432 IDA-D2290 Effective 14-Sep-2017 29-Sep-2017 05-Feb-2018 31-", "output": {"entities": {"named_data": ["Data on Financial Performance"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005913", "page": 1, "chunk": 0, "title": "Disclosable Version of the ISR - Enhancing Shared Prosperity through Equitable Services - P151432 - Sequence No : 16", "pdf_url": "https://documents.worldbank.org/curated/en/099134502282333329/pdf/P15143202c2f2d02e0bf86044f1c4647030.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data on Financial Performance", "label": "NAMED_DATA", "score": 0.6553305387496948, "start": 127, "end": 156, "probe_score": 0.0031, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "6\n\n\nThere is strong support in the Government for increasing resources for education, and the Government\nmade a commitment to increase education's share of budget from 16% in 2001-02 to 25% in 2009-10.\n\n\nOne of the reasons for choosing an APL with a ten-year perspective is that the education budget\nshortages will continue to be a constraint in the next few years. Over this period, Government\n\nexpenditures in non-priority areas will be brought under control and Government expenditures on\neducation can be expected to increase significantly. Despite the manageability in the long-run, the\nshort-run prospects on the budget are more challenging and donors will need to finance some recurrent\ncosts. The proposed APL will be implemented in three phases with distinct triggers (see Section B. 4).\nAs a result, a 10-year projection of enrollments and education costs has been developed (which is the\noverall framework for the APL), and a detailed five year plan and project proposals have been\nprepared (which is the framework for the first phase of the APL).\n\n\n3. Sector issues **to be addressed by the project and strategic choices**\n\nThe project will directly address all the issues below except for higher education.\n\n\n_Issues/Sector Problems_ _Government strategy and project proposal_\n\n**School Places**\n\nThe immediate problem in Djibouti City and The Government's strategy includes a combination\nsurrounding suburbs and other towns is the lack of of building more schools and continuing with the\nschool places due to the strong demand for schooling. double-shifting policy. The project will finance new\nclassrooms, sanitation services, and school furniture.\n\n**Equity, Gender, Disparities**\n\nChildren from poorer families, rural children, and The Government will construct schools in underespecially girls do not always attend school. The served areas, particularly in poorer parts of Djiboutirecent Household Expenditure Survey states that Ville where almost 70% of the population lives.\nmajor reasons for the", "output": {"entities": {"named_data": [], "descriptive_data": ["Household Expenditure Survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000072", "page": 9, "chunk": 0, "title": "Jordan - Health Sector Reform Project", "pdf_url": "http://documents1.worldbank.org/curated/en/466121468773744158/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Household Expenditure Survey", "label": "DESCRIPTIVE_DATA", "score": 0.6417368054389954, "start": 1906, "end": 1934, "probe_score": 0.9529, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " database (Timmer et al., 2015).\n**Note:** Productivity growth is defined as the compound annual growth rate in average labor productivity (%). See appendix B2 for details\non decomposition methodology\n\n\n8 We can quantify the contribution of structural change to labor productivity growth using a set of decomposition\nformulas (McMillan et al. 2014; Vries et al., 2015; see appendix B.2 for details on the methodology). Essentially, the\ndecomposition splits the change in aggregate labor productivity into a component that results from productivity growth\n_within_ individual sectors (i.e., innovation) and changes that result from a shift of employers between sectors.\n\n\n8", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["database"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007606", "page": 9, "chunk": 1, "title": "wps8699", "pdf_url": "https://local/prwp/wps8699.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "database", "label": "VAGUE_DATA", "score": 0.5295016169548035, "start": 1, "end": 9, "probe_score": 0.0001, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " BAEC, PITE, Bureau of Curriculum and Extension Center, DoS, and BISE.\n41 It includes (a) allocating DDO code to the cluster head; (b) LECs preparing cluster plans and budgets; and (c) organizing\ntrainings of head teachers at the cluster head level on participatory planning, school‐based budgeting, cluster‐level\nprocurements, and conducting of summative and formative student assessments; and (d) EMIS cells gathering cluster data and\nsubmitting to the District Education Authority (DEA) and SED.\n\n\nPage 16 of 47", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["cluster data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000085", "page": 20, "chunk": 2, "title": "Pakistan - Balochistan Human Capital Investment Project", "pdf_url": "http://documents1.worldbank.org/curated/en/519111593223468766/pdf/Pakistan-Balochistan-Human-Capital-Investment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "cluster data", "label": "VAGUE_DATA", "score": 0.6411250829696655, "start": 420, "end": 432, "probe_score": 0.0288, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "to identify extremely poor households in areas known to be facing chronic poverty, yet also\nsupport the data requirements to build the HEA baseline model to cover areas where transient\nfood security is the more pressing concern. Data collection will therefore be harmonized with a\nsingle questionnaire, but different formulas or methodological approaches will then be applied\ndepending on whether beneficiary households are in areas of chronic poverty (in the south) or\nfood insecurity (Sahel).\n\n\n28. **The proposed project will use a combination of targeting mechanisms.** Beneficiary\nhouseholds will be selected combining geographic poverty targeting with a census of households\nin selected villages, followed by categorical targeting (households with children under the age of\n10) and a PMT screening which will then be discussed and validated by the community. Once\nthe village is selected, data will be collected for all households, following a list of variables and\nbased on the experience of other targeting techniques, namely the HEA. This will allow the\ncalculation of a PMT score to be used to select among those households that have passed the\ncategorical filter. The community will then discuss the list and validate it if in agreement. This\napproach will, reduce potential inclusion errors, link with existing approaches such as the HEA,\nand lay the foundation of a methodological approach to support the establishment of a social\nregistry.\n\n\n29. **Registration system and social registry.** Based on the harmonized data collection\nprocedures and survey instruments, the project will support the Government in developing a\nsocial registry, which will eventually function as a single registry. A social registry is a database\nthat is capable of collecting, analyzing and storing the following information: personally\nidentifying data (either at an individual level or grouped into family or households); socioeconomic data which would be used to classify individual identities into poverty or vulnerability\ncategories through the application of PMT. Hence, the social registry supports targeting, scoring,\nselection, on-boarding, identification, and, verification processes all linked to", "output": {"entities": {"named_data": [], "descriptive_data": ["census of households", "personally\nidentifying data"], "vague_data": ["socioeconomic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000028", "page": 44, "chunk": 0, "title": "Chad - Safety Nets Project", "pdf_url": "http://documents1.worldbank.org/curated/en/221251471265217930/pdf/Project-Appraisal-Document-PAD-disclosable-version-P156479-08122016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "census of households", "label": "DESCRIPTIVE_DATA", "score": 0.7007957696914673, "start": 660, "end": 680, "probe_score": 0.3762, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "personally\nidentifying data", "label": "DESCRIPTIVE_DATA", "score": 0.5858445763587952, "start": 1818, "end": 1845, "probe_score": 0.106, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "socioeconomic data", "label": "VAGUE_DATA", "score": 0.7194641828536987, "start": 1916, "end": 1934, "probe_score": 0.0518, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad - Refugees and Host Communities Support Project (P164748)\n\n\n**<mark>ANNEX 2: GEO-SPATIAL ANALYSIS</mark>**\n\n\n1. A major obstacle to effective targeting of development projects in many developing\ncountries is the lack of existing datasets. One option to overcome this obstacle is remote sensing.\nFor this project, preliminary work has been done to determine the host population around selected\ncamps using remote sensing imaging analysis. To generate population estimates, the analysis uses\nworld population census data and statistical modeling based on the relationship between\npopulations and physical socioeconomic characteristics such as land uses, dwelling units and\nimage pixel characteristics.\n\n2. The figure shows the population layer within 25 km of selected camps, and the table shows\npopulation estimates at 50 km, 25 km, 15 km, 10 km and 5 km from the camps. Since village\nboundary information for Chad is not available in world population data, satellite imagery and\nestimates of average village size from the most recent census will be used to approximate the\nnumber of host villages around each camp.\n\n\n**Population Layer within 25 km of Selected Camps in the East, South, and Lake Chad**\n\n**Regions**\n\n\nSource: World Bank Geospatial Operations Support Team (GOST).\n\n\nPage 77", "output": {"entities": {"named_data": [], "descriptive_data": ["world population census data", "world population data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000112", "page": 81, "chunk": 0, "title": "Chad - Refugees and Host Communities Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/658761536982256019/pdf/PAD2809-PAD-PUBLIC-disclosed-9-12-2018-IDA-R2018-0286-1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "world population census data", "label": "DESCRIPTIVE_DATA", "score": 0.7022085785865784, "start": 514, "end": 542, "probe_score": 0.9326, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "world population data", "label": "DESCRIPTIVE_DATA", "score": 0.5788262486457825, "start": 958, "end": 979, "probe_score": 0.997, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "women, youth, people with disabilities, ARRA, UNHCR, NRDEP delegations were participated\n\n\nand engaged. Local officials, kebele administration, host community representatives, regional\n\n\nsteering committee chairman and bureau of agriculture and natural resources and woreda office\n\n\nof environment and forest protection, WSC, WTC and respective level RPCU and WPCU of\n\n\nDRDIP specialists and coordinators were also sources of information’s during focus group\n\n\ndiscussion. A total of 546 of which 93 individuals were engaged.\n\n\nThe consultations were focused on providing information and receiving the concerns and opinions\n\n\nof the participants regarding the overall project objectives, project׳s main and sub- components\n\n\nfor which the SA was prepared. A verbal presentation of the DRDIP objectives and main\n\n\ncomponents were made to the stakeholder and community consultation participants and\n\n\ndiscussions were conducted to identify the adverse environmental and social issues affecting the\n\n\nhost communities and the environment, to capture their concerns, opinions, and to indicate the\n\n\ninstitutional capacity gaps and other constraints that may impede implementation of the SA.\n\n\nFurthermore information was also collected on the workshop by focusing on the existing\n\n\nsituations in terms of integration and collaboration in between the refugee and the host\n\n\ncommunities and hence strengthening the social cohesion among the communities and the\n\n\nresponsible stakeholders and partners. Moreover consultation with project coordination unit and\n\n\nwith stakeholders at woreda and regional level was also held by using telephone communication.\n\n\n**C. Baseline Assessment**\n\n\nThe baseline assessment, previously prepared for implementation of DRDIP I was reviewed and\n\n\nused as the main information source with updating information of newly incorporated kebeles\n\n\nand woredas and city administrations as part of the overall study to prepare this SA document.\n\n\nSecondary data was also collected from DRDIP-II project documents, project baseline survey\n\n\nand midterm impact assessment reports and from federal and regional project performance\n\n\nquarterly and annual reports . The following issues among others which are pertinent with the\n\n\ndevelopment of DRDIP-II have been addressed and incorporated in this SA preparation:\n\n  - Existing", "output": {"entities": {"named_data": [], "descriptive_data": ["project baseline survey", "midterm impact assessment reports", "federal and regional project performance\n\n\nquarterly and annual reports"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007033", "page": 14, "chunk": 0, "title": "Revised Social Assessment Ethiopia Development Response to Displacement Impacts Project Phase II (P178047)", "pdf_url": "https://documents.worldbank.org/curated/en/099555103192224175/pdf/P1780470431bc0070b1030374978de7ad8.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "project baseline survey", "label": "DESCRIPTIVE_DATA", "score": 0.789640486240387, "start": 2033, "end": 2056, "probe_score": 0.1957, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "midterm impact assessment reports", "label": "DESCRIPTIVE_DATA", "score": 0.5265450477600098, "start": 2063, "end": 2096, "probe_score": 0.1293, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "federal and regional project performance\n\n\nquarterly and annual reports", "label": "DESCRIPTIVE_DATA", "score": 0.7059197425842285, "start": 2106, "end": 2177, "probe_score": 0.2355, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "(b) Participating households that graduate from the Economic Inclusion Program (EIP) <sup>8</sup> [^8: The criteria for graduation from the program include achieving all of the following: improved food security, establishing a\nsustainable and stable source of income, increased household assets, increased savings and access to credit, improved social\ninclusion, participation in all graduation interventions.]\n\n(Percentage).\n(c) Participating adolescent girls (ages 10 to 18) with improved educational attainment <sup>9</sup> [^9: Educational attainment is measured as completing at least one additional year of schooling or, for those out of school at\nbaseline, re-entering primary or secondary school.]\n\n(Percentage).\n(d) Eligible households who have received emergency cash transfers within nine months of a\n\nqualifying climate or weather event (Percentage).\n(e) Coverage and accuracy of ESR increased through On-Demand Registration (Number).\n\n\n**1.3** **Project Beneficiaries**\n10. The project targets to benefit all 1.8 million existing NSNP households with improved delivery\nsystems for GoK-financed cash transfers, 150,000 households will be supported under the NICHE\nprogram, 20,000 households will be supported under the adolescents’ program and 50,000 households will\nbe supported under EIP.There can be overlap between households that participate in various programs\ngiven there will be (intentional) geographic overlap across some counties, and households may be eligible\nand interested to participate in multiple programs. Beneficiary households of all programs must be poor\nbut do not necessarily need to already be enrolled in NSNP to be eligible. Beneficiary households will be\nselected using ESR data to assess their poverty status along with other relevant eligibility criteria for each\nrespective program. Beneficiaries of HSNP’s shock responsive program will be pre-registered using ESR\ndata to assess poverty status and residence in qualifying HSNP areas in ASAL counties.\n\n**2. OBJECTIVE OF THE LMP**\n\n11. Under the World Bank’", "output": {"entities": {"named_data": ["ESR data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005219", "page": 8, "chunk": 0, "title": "Labor Management Procedures Second Kenya Social and Economic Inclusion Project (P504218)", "pdf_url": "https://documents.worldbank.org/curated/en/099112124160085462/pdf/P504218-db7ea05d-bae7-4e97-b4f8-a0b168f7b96b.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "ESR data", "label": "NAMED_DATA", "score": 0.7544082403182983, "start": 1710, "end": 1718, "probe_score": 0.9331, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**5.2 Mean and variability changes due to climate change**\n\nBecause it is likely that in the future the variability of rainfall in Malawi will increase\nrather than decrease (see Tadross et al., 2007), it is important to incorporate possible\neffects in the analysis. Ideally, one would estimate the variance of the future projections\nto get an estimate of the magnitude of change. However, due to data limitations with only\n20 years of data available, such an exploration is not feasible. Accordingly, possible\nchanges in future variance are implemented by way of sensitivity analysis. The future\nvariance based on the empirical data is increased by a factor of 1.4 and decreased by a\nfactor of 0.78 in the future, which corresponds roughly to a doubling and halving of the\npast variance (see Mearns, Rosenzweig and Goldberg, 1997). The probability density\nfunction of the gamma distribution has the following form\n\n\n\n<u>x</u>\nf(x | α,β) = <u>1</u> x α - 1e - β,  x ≥\n\nβ αΓ(α)\n\n\n\n\n  \n- 1e\n\n\n\nx α    - 1e β,  x ≥ 0\nβ αΓ(α)\n\n\n\nwhere � is the shape parameter and � is the scale parameter. The mean of the\ndistribution is �� and the variance is �� <sup>�</sup> . Hence, an increase of � of 1.4 can be seen\nas doubling the rainfall variability compared to the baseline case, while a decrease of 0.78\ncan be interpreted as a one-half decrease of the variance compared to the baseline case.\nThus, both parameters of the gamma distribution are now changing.\n\n<u>Table 7:</u> <u>Probability of ruin for baseline, MM5 and PRECIS with mean and variability changes</u>\n\n\n\n\n\n\n\n\n\n\n\n|Year\\ Probability", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["empirical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003838", "page": 18, "chunk": 0, "title": "wps4631", "pdf_url": "https://local/prwp/wps4631.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "empirical data", "label": "VAGUE_DATA", "score": 0.7523413300514221, "start": 618, "end": 632, "probe_score": 0.9718, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nUgandan research institutions will be a key partner in implementing the M&E framework building on existing data\nreports and in partnership with local research institutions. The PSFU PIU will work closely with Ugandan research\ninstitutions for three reasons. First, to coordinate the various data collections so as to be more efficient in utilizing\nall existing firm-level data. Second to identify and collect additional data with respect to jobs and firm productivity.\nThird, to use the data collected on an ongoing basis make suggestions to the PSC to improve the project impact. <sup>48</sup> [^48: The objective is to develop an actional M&E system that is used as instrument to monitor and improve project effectiveness along\nimplementation rather than just a system for ex-post accountability.]\nAll data will be disaggregated by gender, refugee, host community, and non-host community nations to ensure\nadequate targeting and collection of results for targeted populations.\n\n\n**C. Sustainability**\n\n\n79. In principle, the project components are based on implementing interventions that are fully financially\nsustainable while generating the largest possible impact. Although the rebates offered to borrowers under\nWindow 1 of Component 1 are not recoverable, from a cost-benefit perspective the extension of the amortization\nperiod of MSME loans is consistent with the BoU policy and will contribute to a reduced probability of default of\nMSMEs and to the stability of the financial sector by reducing NPLs and also to preserving functioning MSMEs and\njobs that might otherwise get impaired. It will also support revival of otherwise viable enterprises and therefore,\ncontribute to growth and to protecting institutional, social and financial capital, that might otherwise have been\nlost. Windows 2 and 3 of Component 1 are financially self-sustaining: Tier 3 and 4 institutions (MFDs, MFIs, and\nSACCOs) will be provided with access to concessional credit lines. These credit lines will be limited in volume and\nhave an 18-month maturity so as to be available over the COVID-19 period only and so as not to distort the market\nfor loan capital. All participants along the chain", "output": {"entities": {"named_data": [], "descriptive_data": ["firm-level data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000021", "page": 36, "chunk": 1, "title": "Uganda - Investment for Industrial Transformation and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/469061641926083502/pdf/Uganda-Investment-for-Industrial-Transformation-and-Employment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "firm-level data", "label": "DESCRIPTIVE_DATA", "score": 0.826204240322113, "start": 362, "end": 377, "probe_score": 0.6154, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " som axtendus. Conformnemcnt aux mesures arretees par le 0ouvernoment. los boursds\nlocales sont supprimees et le oiomnbre d'6tudiants boursiers a ['etranger, doint Ie cout es.\nactueilerneent exorbitanr, va dimninucr progressivemenL _De_ 936 erudiants boursiers er. 1999/00,\nOn passera A moi.ns de 200 en 2010. Les economies realisees dans le cadre de cette nouveilo\npoiitique vont etrc reparties entre i'enseignement foridamental **et** l'enscignerment .echnique ot\nprofessionnel. Par ailleurs. l'accent sera mis sur l'utilisation des nouvciles technologies de\ni'information et de la communication ( NTiTC ) afin de permettre aux universitaires et aut.es\nutalisateurs d'avoir acc&s _a_ tous les avantages qu ofEent ces nouvelles technologics.\n\n\nEn maniere d'ernseignement secoindaire gdnCrai, I'accenE sera rnis particuiirement\n**su-** le renforcement de la qualit6 avec la mise en place d'uae v6ritable politique de formation des\nenisci gtants **sur** le plan initial et continu.\n\nL'enseignement de I'arabe va etre renforce en vue de lui permnee ae jouer\npieinc.mernt ie rolc qui lui revieM dans un pays de culture arabo-islamiquc. A cet cffet, les\n\ndispositions suivantes seront prises", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000038", "page": 69, "chunk": 2, "title": "Africa - Multi - Country HIV/AIDS Program for the Africa Region (Ethiopia and Kenya)", "pdf_url": "http://documents1.worldbank.org/curated/en/287591468768313907/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nindependent variables constant.\n\n\nIn line with previous studies, some variables\nhave the expected effect on economic\nvulnerability. The household size affects the\neconomic vulnerability, with the higher the\nhousehold size the more economically\nvulnerable the household is. Vulnerability is also\nclosely linked to asset ownership where assets\nincluding livestock, phone, motorbike, and\nsewing machine are positively correlated with\nlower economic vulnerability. Indeed, the more\nassets a household has, the less vulnerable they\nare (Oluwatayo and Babalola 2020).The housing\n\n\n\ntype does not so much determine the household\neconomic vulnerability. This is likely due to\nrefugee housing stock being fairly uniform in\nrefugee settlements due to all refugees receiving\ncommon shelter supplies.\n\n\nImportantly, and in line with the above\ndescriptive analysis, the regression results\nconfirm that refugee households with persons\nwith specific needs are more economically\nvulnerable than other refugee households.\n\n\n**Conclusion and Implications**\n\nRefugees with specific needs face heightened\nrisks. UNHCR proactively identifies and supports\nthem with protection or assistance interventions\nto reduce the risk of lasting physical and\npsychological harm. Further, using recent data\nfrom a vulnerability and needs assessment\nsurvey, the authors of this brief found that\nhouseholds with members who have specific\n\n\n\nwww.unhcr.org/livelihoods 5", "output": {"entities": {"named_data": [], "descriptive_data": ["vulnerability and needs assessment\nsurvey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000517", "page": 4, "chunk": 1, "title": "Uganda Policy Brief: Targeting assistance programmes to persons with specific needs - December 2020", "pdf_url": "https://reliefweb.int/attachments/4a1f9402-c62c-3d9e-9c6e-66cfad7553bc/6012b2fd4.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "vulnerability and needs assessment\nsurvey", "label": "DESCRIPTIVE_DATA", "score": 0.8752859234809875, "start": 1281, "end": 1322, "probe_score": 0.8774, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and Monitoring and Evaluation**|**Project Management and Monitoring and Evaluation**|\n|**Percentage of project-related grievances addressed (Percentage) **|**Percentage of project-related grievances addressed (Percentage) **|\n|Description|This indicator will be tracked by PIU through data collected through the Project Management Information System (MIS).|\n|Frequency|**Quarterly**|\n|Data source|**MSEA’s and KDC’s registry of project benefeciary firms**|\n|Methodology for Data<br>Collection|**Project progress reports**|\n|Responsibility for Data<br>Collection|** PIU**|\n|**of which women (Percentage) **|**of which women (Percentage) **|\n|Description||\n|Frequency|**Quarterly**|\n|Data source|**MSEA’s and KDC’s registry of project benefeciary firms**|\n|Methodology for Data<br>Collection|**Project progress reports**|\n\n\n\nNov 16, 2023 Page 42 of 60", "output": {"entities": {"named_data": ["Project Management Information System", "MSEA’s and KDC’s registry of project benefeciary firms"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005133", "page": 46, "chunk": 2, "title": "Kenya - Jobs and Economic Transformation Project", "pdf_url": "https://documents.worldbank.org/curated/en/099111623110021564/pdf/P179381-1beb4c9b-493d-42b3-9c46-bf6ccb2fb675.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Project Management Information System", "label": "NAMED_DATA", "score": 0.7064891457557678, "start": 313, "end": 350, "probe_score": 0.1482, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "MSEA’s and KDC’s registry of project benefeciary firms", "label": "NAMED_DATA", "score": 0.5034163594245911, "start": 400, "end": 454, "probe_score": 0.0376, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n## Executive summary\n\n\n##### Progress in market integration\n\n**Ukrainian refugees have been**\n**increasingly successful in terms of**\n**labour market integration.** The large\ninflux of refugees since February 2022,\nhas further increased and changed the\ndemographics of the already significant\nUkrainian migrant population in Poland.\nRefugees from Ukraine are primarily\nwomen and children, with over 67% of\nfemale-headed households. Poland was\nquick to open its labour market to refugees\nfrom Ukraine, who – despite difficulties\n\n- surprisingly promptly began their\neconomic integration and soon supported\nthemselves primarily from employment.\nIn the past year, refugees’ employment\nrate grew from 61% to 69%, with the\nmedian net wage rising from PLN 3,100 to\nPLN 4,000 and narrowing the gap to the\nmedian net wage in the entire economy.\n**As Ukrainian refugees entered the**\n**labour market, the economy adapted,**\n**resulting in more specialization and**\n**higher productivity.** In a simplistic\nsupply-demand framework, the influx\nof Ukrainian refugees would have had\na negative impact on Polish workers\nemployment or caused a decline in real\nwages. However, this has not occurred.\nFirst, Polish citizens employment rates\nhave grown, and unemployment rates\nhave fallen. Second, poviats in which the\nemployment share of Ukrainian refugees\nhas grown by 1 pp. saw 0.5 pp. higher\nemployment rates among Polish citizens,\nand 0.3 pp. lower unemployment rates.\nThird, there is no evidence of lowered\nwages, in fact the limited available data\nindicates that a higher share of Ukrainian\nrefugees in a poviat may have caused local\nwages to rise. Such findings are in line with\nacademic literature, which documents\na positive impact of migrants on native\nworkers. With foreigners entering the\n\n\n04\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n*", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["limited available data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 2, "chunk": 0, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "limited available data", "label": "VAGUE_DATA", "score": 0.7306715250015259, "start": 1588, "end": 1610, "probe_score": 0.8446, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "RR in excess of\nthe social discount rate of 6 percent across all cost-benefit analyses under the baseline scenario and the sensitivity\nanalysis. While data limitations make it difficult to analyze the economic impact of the project on refugees and host\ncommunities, specifically, it is important to note that benefits will flow to these communities similarly as to other targeted\nproject communities. Further, UNHCR has recently initiated a ‘Flagship Survey’ that will provide rich new data on the\nsocioeconomic conditions of refugees and hosts in South Sudan, which could enable focused economic analysis of project\nimpact on these two communities as implementation moves forward.\n\n\nPage 40 of 74", "output": {"entities": {"named_data": ["Flagship Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 44, "chunk": 2, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Flagship Survey", "label": "NAMED_DATA", "score": 0.8423442244529724, "start": 442, "end": 457, "probe_score": 0.1591, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n\n# Health analysis\n\n### **Health remains a** **priority need**\n\nAccess to health services has remained a priority\nneed and is ranked among the top three priorities\nby 33% of households, second only to employment\nand livelihoods support. The identification of health\nas a priority is consistent with 2023, where 34% of\nhouseholds ranked health among their top three\nneeds.\n\n\nVariations exist across countries, health care was\nthe top priority need for respondents in half the\ncountries (Bulgaria, Hungary, Moldova, Romania,\nand Latvia). In 2024, health care became a top\npriority for 49% of households in Romania, a shift\nfrom 38% in 2023, potentially indicating barriers and\nchanges in the level of access.\n\n\n\n(2023 N=9,466, 2024 N=7,140)\n\n- Not included in 2023 survey\n\n\n\n**<u>TOP 10 PRIORITY NEEDS (OUT OF THOSE WHO REPORTED)</u>**\n\n\n2023 2024\n\n\n\nEmployment,\n\nlivelihoods\n\n\nHealthcare\n\nservices\n\n\nAccommodation\n\n\nLanguage course\n\n\nEducation for\n\nchildren\n\n\nMedicines\n\n\nFood\n\n\nTrainings,\neducation adults\n\n\nLegal status*\n\n\nRegistration,\nlegal assistance\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n                                   - Not included in 2023 survey\n\nRegionally, women and men prioritized health care\nnearly equally with respectively 34% and 32%\nidentifying it as a priority need. For women, health was the second highest priority after employment\ncompared to men who prioritized it third after\nemployment and accommodation.\n\n\n\n**<u>TOP 10 PRIORITY NEEDS (OUT OF THOSE WHO REPORTED), BY COUNTRY</u>**\n\n\nTop 1 Top 2 Top 3 priority\n\n\n\n|Col1|Regional|Bulgaria|Czechia|Estonia|Hungary|Latvia|Lithuania|Moldova|Poland|Romania|Slovakia|\n|---|---|---|---|---|---|---|", "output": {"entities": {"named_data": [], "descriptive_data": ["2023 survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000004", "page": 9, "chunk": 0, "title": "NAVIGATING HEALTH AND WELL BEING CHALLENGES FOR REFUGEES FROM UKRAINE   2nd Edition", "pdf_url": "https://local/jad_paddy_docs/navigating health and well-being challenges for refugees from ukraine - 2nd edition.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2023 survey", "label": "DESCRIPTIVE_DATA", "score": 0.688954770565033, "start": 829, "end": 840, "probe_score": 0.9978, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ": Alto Comisionado de las Naciones Unidas para los Refugiados.\n\n\nRodríguez, Ernesto (2011). Asilo, refugio y otras formas de protección humanitaria en el México\n\ndel siglo XXI”. En Katya Somohano y Pablo Yankelevich (coords.), _El refugio en México._\n_Entre la historia y los desafíos contemporáneos_ . México: Secretaría de Gobernación, Comisión\n\n\nRefugiados en México **[ 51 ]**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001151", "page": 46, "chunk": 2, "title": "Refugiados en México: Perfiles sociodemográficos e integración social", "pdf_url": "https://reliefweb.int/attachments/ae3528ad-fb2a-3583-946b-2e91aad12d47/Refugiados%20en%20Mexico_Perfiles%20sociodemograficos%20e%20integracion%20social.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "..................................................................................... - 22 -_\n\n\n**List of Tables**\n\nTable 1: Physical road conditions, GIS+HDM4, by road class ............................................. - 6 Table 2: The determinants of tobacco transport costs to markets: all tobacco farmers ......... - 7 Table 3: The determinants of tobacco transport costs to markets: tobacco farmers using lorry\ntransportation ......................................................................................................................... - 8 Table 4: Trucking Survey - Summary of main findings .................................................", "output": {"entities": {"named_data": ["Trucking Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004326", "page": 3, "chunk": 1, "title": "wps5133", "pdf_url": "https://local/prwp/wps5133.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Trucking Survey", "label": "NAMED_DATA", "score": 0.6875244975090027, "start": 567, "end": 582, "probe_score": 0.8747, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " services and infrastructure. Operational policy documents in the form of Refugee Sector\nResponse Plans have been developed for education, health, water and environment, jobs and livelihoods, and\ndrafts are being developed for energy and private sector engagement. These plans provide agreed priorities and\nactivities for development partners to support the GoU in strengthening of services, employment opportunities,\nand safeguards to build the self-reliance of refugees and host communities. This project will be essential in\nsupporting the full development of the PSES and implementation of both the PSES and JLIRP. These key policy\ndocuments will see an integrative approach to meet the employment and MSME needs of refugees and host\ncommunities in a strategic and prioritized manner.\n\n\n**II.** **PROJECT DESCRIPTION**\n\n\n**A. Project Development Objective**\n\n**PDO Statement**\n\n\n34. To mitigate the effect of COVID-19 on private sector investment and employment and to support new\neconomic opportunities including in refugee and hosting communities.\n\n\n**PDO Level Indicators**\n\n\n35. The project will measure: (a) the number offirms benefiting from private sector initiatives, (b) the value\nof investment in manufacturing, (c) the number of income generating opportunities for refugees, (d) the number\nof firms benefiting in RHD, (e) the percentage of jobs saved that would otherwise have been lost due to COVID19 <sup>37</sup>, and (f) The number of new loans issued to firms in the manufacturing sectors.\n\n\n37 The Economic Policy Research Center conducted a rapid survey of businesses which indicated that three-quarters of businesses have laid\noff employees due to the risks and subsequent containment measures presented by COVID-19 and estimated that 3.8 million workers\n\n\nPage 19 of 92", "output": {"entities": {"named_data": [], "descriptive_data": ["rapid survey of businesses"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000073", "page": 24, "chunk": 1, "title": "Uganda - Investment for Industrial Transformation and Employment Project", "pdf_url": "http://documents1.worldbank.org/curated/en/469061641926083502/pdf/Uganda-Investment-for-Industrial-Transformation-and-Employment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "rapid survey of businesses", "label": "DESCRIPTIVE_DATA", "score": 0.9292266964912415, "start": 1563, "end": 1589, "probe_score": 0.0705, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA M&E data - NaCSA maintains lean and\n**community** **sub-projects and** decision-making by NaCSA; efficient organizational\n**NSAP** **partners monitored** structure\n**and evaluated** **in order to**\n**improve** **program**\n**effectiveness.**\n\n\n**3(d)** **Technical** **Assistance** 3d. 1 NaCSA staff indicate - IDA aide-memoires and\n**services** **effectively** **provided** satisfaction with technical project status reports\n**to support program** assistance, including skill\n**implementation** transfer activities\n\n\n**3(e)** NaCSA **management** 3e. 1 Project management - IDA Project Status reports\n**systems** **functioning** costs (NaCSA staff salaries at (including disbursement\n**effectively** **to ensure** all levels as well as operating reports);\n**program success** expenditures) are 13.5% or - NaCSA proposed annual\nless than total budgeted annual work program and budget\nexpenditures;                 - Annual audit reports;\n3e.2 NaCSA staff and                  - GOSL semi-annual PETS\npartners indicate satisfaction reports\nwith the performance of\nNaCSA's management;\n3e.3 NaCSA performance in\n\n\n                                  - 27", "output": {"entities": {"named_data": ["NaCSA M&E data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015266", "page": 31, "chunk": 1, "title": "Kenya - Energy Sector Reform and Power Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/592221532724064535/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NaCSA M&E data", "label": "NAMED_DATA", "score": 0.6971123814582825, "start": 170, "end": 184, "probe_score": 0.0004, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSudan Basic Education Emergency Support Project (P172812)\n\n\n2020. The IMF has already forecasted an overall economic stagnation in 2020 in Sudan. GDP is expected to decrease\nbetween 4-10 percent in 2020 due to the combined impact of the economic crisis exacerbated by the social\ndistancing measures to curb the spread of COVID-19. Slowing growth and COVID-19 policy responses will have a\nsignificant negative impact on government revenue. Slowing activity will automatically translate into lower levels of\ntax and other government revenue collection. The combined effect on government revenues is projected to be\nsignificant.\n\n6. **Poverty reduction stagnated in 2018 mainly due to weak economic growth, political and macroeconomic**\n**instability and the shortage of essential food items such as bread.** According to the most recent official estimates\nof poverty based on the 2014/15 National Household Budget and Poverty Survey (NHBPS), 36.1 percent of Sudanese\npopulation (or 13.4 million people) are poor. However, the overall/national poverty rate masks wide disparities\nacross Sudan’s 18 states. For example, Central Darfur State in western Sudan recorded the highest rate of poverty\n(67.2 percent). Generally, the states of South Kordofan, West and Central Darfur, in which two in three people are\npoor, are the states with the highest poverty rate followed by Red Sea, East and South Darfur. However, when\npoverty was measured against the World Bank’s international poverty line for lower middle-income countries\n(US$3.2 per capita per day), 46.1 percent was deemed poor. The poor are particularly affected by rising inflation\ngiven their high food share in consumption, and limited means to preserve the erosion of the value of their savings.\n\n\n**B. Sectoral and Institutional Context**\n\n\n7. **Education provision in Sudan is a shared responsibility among various administrative layers", "output": {"entities": {"named_data": ["National Household Budget and Poverty Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000024", "page": 11, "chunk": 0, "title": "Sudan - Basic Education Emergency Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/208261588781212409/pdf/Sudan-Basic-Education-Emergency-Support-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "National Household Budget and Poverty Survey", "label": "NAMED_DATA", "score": 0.8903918862342834, "start": 905, "end": 949, "probe_score": 0.9887, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "consumed (because this VAT cannot be captured by an analysis based on data from a single year). <sup>25</sup> [^25: Similarly, current expenditure, and the VAT incurred on it, may have been funded from income earned in a\nprevious year. See Thomas (2022a) for a more detailed discussion.]\nBecause savings rates tend to increase with income, this biases income-based VAT burden results\ndownwards at higher income levels – driving the finding that the VAT is regressive.\n\nIn contrast, studies that measure VAT burdens as a proportion of expenditure (across either the income\nor expenditure distribution) tend to find that VAT systems are relatively proportional, or even slightly\nprogressive (see, e.g., Thomas, 2022a; Bird and Smart, 2016; IFS, 2011a; Metcalf, 1994). The largest crosscountry study favoring the expenditure-based approach is Thomas (2022a), who finds the VAT to be either\nroughly proportional or slightly progressive in 23 of 27 OECD countries examined. However, results for\nfour countries show that broad-based VAT systems with very few reduced VAT rates or exemptions can\nproduce a small degree of regressivity.\n\nMost recently, Bachas et al. (2023) have considered the impact of informality in developing countries on\nthe distribution of VAT burdens. They estimate informality Engel curves (relating the informal budget\nshare to log total expenditure) for 32 low and middle-income countries. They find that informality\ndecreases as household expenditure increases, and conclude that this will create a degree of progressivity\nin the VAT in developing countries. Similarly, Jenkins et al. (2006) find that informality creates\nprogressivity in the VAT in the Dominican Republic.\n\n4.1.2 The ability of reduced VAT rates to target poorer households\n\nA number of empirical studies examine who benefits from reduced rates, finding the VAT to be a poorly\ntargeted tool for supporting poorer households. For example, two large scale studies consider who\nbenefits from reduced VAT rates in nine European (IFS, 2011a) and", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data from a single year"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001256", "page": 13, "chunk": 0, "title": "idu12d02d19f1336a14e0c1b53714d134b306a9f", "pdf_url": "https://local/prwp/idu12d02d19f1336a14e0c1b53714d134b306a9f.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from a single year", "label": "VAGUE_DATA", "score": 0.7706519365310669, "start": 70, "end": 93, "probe_score": 0.9765, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "16\n\n\naddressed the Donors Roundtable and committed to increase Government resources to education to\nover 25% of the budget and noted that the government viewed education as the main source of future\ngrowth in Djibouti.\n\n\n**5. Value added of Bank support in this project**\n\nIDA has been supporting the national consensus building process through the National Education\nForum. The proposed project will help demonstrate that a consensus building approach that involves\n\nall elements of civil society is effective and produces results. In addition the use of an APL\ndemonstrates the long-term commitment by IDA to assist the Government in its strategic goal of\nreaching full enrollment in basic education. It is also hoped that the use of the IDA credit will further\ndecrease the construction unit cost (as IDA is supporting the use of local construction materials which\nshould be cheaper), help develop more cost-effective classroom designs, and provide the environment\nwith a more efficient procurement process.\n\n\n**E. SUMMARY PROJECT ANALYSIS** (Detailed assessments are in the project file, see Annex 8)\n\n\n**1. Economic (see Annex 4)**\n\n\nOther (specify) NPV=US$ million; ERR = ** % (see Annex 4)\n\n\n_** ERR = Over 11% based on system efficiency gains alone without allowing for development_\n_benefits, public goods nature of education and poverty reduction benefits._\n\n\nDjibouti's main resource base is its population and in order to achieve sustained development, the\ncountry needs to improve the quality of its human resource base. Quality starts with improved basic\neducation and school enrollments. In addition, the issue of equity arises. According to the household\nexpenditure survey data, in urban areas, the net enrollment rate (NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey", "output": {"entities": {"named_data": [], "descriptive_data": ["household\nexpenditure survey data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009785", "page": 19, "chunk": 0, "title": "Kenya - Universities Investment Project", "pdf_url": "https://documents.worldbank.org/curated/en/222611468285582145/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household\nexpenditure survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8924797177314758, "start": 1661, "end": 1694, "probe_score": 0.9403, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " positive\neffect on job retention in Jordan, but we find no evidence in either country that other policy supports\npreserved jobs significantly. This underscores the importance of designing and scaling policy support\nmeasures carefully to preserve viable firms and jobs in the face of large demand shocks.\n\n\nWe find that our model-based method predicts the level of further job losses in the winter of 2020 fairly well,\nbased on a comparison of predictions with a COVID-period labor force survey for Jordan. Whereas it predicts\nthe distributional impacts by gender, nationality, and educational attainment well, it fails to predict the\ndifferences by age group and wage level. Predicted and actual results show a greater rate of job loss for men\nemployed in the formal private sector than for women and for those with less education. In addition, the rates\nof job loss by productive sector generally rank similarly to those observed, with some exceptions. We also\ndocument differences in the two countries’ performance in restoring formal permanent jobs versus other\ntypes of jobs (informal, temporary, self-employment) in the private sector. In Georgia, with its stronger export\nmarket presence and more flexible regulation of formal employment, formal firms were able to boost sales\nand hire full time workers back. <sup>54</sup> [^54: Other drivers of this difference could be policy measures to boost local demand or better containment of the virus;\nhowever, the evidence we present herein is not consistent with either explanation. Another key difference may be\nGeorgia’s more educated workforce that is easier to train. However, this does not seem a likely explanation, since the\nrehiring rates are a function of a rebound in sales, rather than labor supply.] Moreover, they did so at a significantly faster rate than appears to have\nbeen the case for informal firms, for which there was no clear sign of such a formal job recovery. In contrast, in\nJordan, formal sector jobs continued to decline through the fall and early winter, and at a faster rate than\ninformal and temporary", "output": {"entities": {"named_data": [], "descriptive_data": ["COVID-period labor force survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002359", "page": 44, "chunk": 1, "title": "understanding and predicting job losses due to covid 19 empirical evidence from middle income countries", "pdf_url": "https://local/prwp/understanding-and-predicting-job-losses-due-to-covid-19-empirical-evidence-from-middle-income-countries.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "COVID-period labor force survey", "label": "DESCRIPTIVE_DATA", "score": 0.8638767600059509, "start": 463, "end": 494, "probe_score": 0.5303, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "OCHA Office of Commission for Humanitarian <sup>Assistance</sup>\nPAMC Project Approval and Monitoring Committee\nPETS Public Expenditure Tracking Survey\nPOM Project Operational Manual\nPPA Participatory Poverty Assessment\nQER Quality Enhancement Review\nRUF Revolutionary United Front\nSAPA Social Action and Poverty Alleviation <sup>Program</sup>\nSHARP Sierra Leone HIV/AIDS Response Project\nSLRA Sierra Leone Roads Authority\nSOCAT Social Capital Assessment Tool\nSPP Strategic Planning and Action Process\nTEP Training and Employment Program\nTSS Transitional Support Strategy\nUNAMSIL United Nations Mission for Sierra <sup>Leone</sup>\nUNHCR United Nations High Commission for <sup>Refugees</sup>\nUNICEF United Nations Children's Fund\nUNOPS United National Operations Support\n\n\nVice President: Mr. Callisto Madavo\nCountry Director: Mr. Mats Karlsson\nSector Manager: Mr. Alexandre Abrantes\nTask Team Leader/Task Manager: Ms. Eileen Murray", "output": {"entities": {"named_data": ["PETS Public Expenditure Tracking Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012833", "page": 2, "chunk": 0, "title": "Uganda - Third Power Project and Supplemental Credit", "pdf_url": "https://documents.worldbank.org/curated/en/424641468317662124/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PETS Public Expenditure Tracking Survey", "label": "NAMED_DATA", "score": 0.6079578399658203, "start": 112, "end": 151, "probe_score": 0.0351, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a high acceptance of the project, largely based on the\nexpectations that there will be opportunities for employment of local people and\nincreased income. In practice, employment opportunities will be rather limited and of\nshort duration. In the final analysis, these benefits are counter weighed by the\npotential for inflation, conflict between in-migrants, and increased competition for\nresources during the construction phase. If to this are added the long-term effects of\ninduced development, it **is** likely that the _most_ vulnerable members of the community\nmay be further marginalized.\n\n\nThe implementation of post project monitoring of social impacts is key. This has been\nprovided for be the collection off base-line socio-economic data for this project.\nHowever, this activity must be planned and budgeted by the EMB.\n\n\nLocal communities are the owners of all local resources and have the first right to **use**\nand harvest. To achieve this, local communities must be empowered by adequate and\neffective consultation. Public participation in road projects is a new activity in Ethiopia.\nThe challenge is to implement a public consultation process that is effective for all\nparties. This will require specialist input and careful planning and coordination of\nrelated activities and follow-up. It is proposed that contact with local communities have\nexpert facilitation.\n\n\nAwareness of the important biodiversity of the area must be raised on all levels.\n\n\nThe area in the direct zone of influence of the road has yet unrealised tourist potential\nin the form of birding tours. The presence of rare orchids and other endemic plant\nspecies is also of great interest internationally. _It_ has been estimated that some 70%\nof all bird species occurring in Ethiopia can be found in the project vicinity. To achieve\nthis potential, local biodiversity must be maintained and intensified wherever possible.\nAll remaining wetland areas must be preserved. Soil erosion must be controlled.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["socio-economic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014233", "page": 9, "chunk": 1, "title": "Ethiopia - Second Road Sector Development Support Project : environmental assessment and resettlement plan - executive summaries", "pdf_url": "https://documents.worldbank.org/curated/en/522361468744327460/pdf/29131.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "socio-economic data", "label": "VAGUE_DATA", "score": 0.6877528429031372, "start": 728, "end": 747, "probe_score": 0.021, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Jordan Home Visits Report 2014 - Living in the shadows**\n\n\n**_Utilization of health services_**\n\n\nThe majority of visited refugee households (87%) stated that they had utilized health services in Jordan.\nOf those who had not, the most common reason was that they had no need to approach a health service.\nLack of MOI card was another reason given for not having accessed health services. Of those refugees\nwithout an MOI card who reported on health service utilization, 21% had not utilized health services,\ncompared to 12% of those with an MOI card. Of those without a valid asylum seeker certificate, 8% had\nnot used health services, compared to 13% of those with a valid certificate. This suggests that lack of\nrequired documentation remains a barrier to accessing health care. The percentage of visited households reporting utilization of some form of health care was lowest in Tafieleh (68%) and Amman (79)%.\n\n\n**_Type of health care_**\n\n\nAt the time of data collection, Syrian refugees’ access to public health care had increased, with public\nservices representing 77% of health service utilization by refugees in 2014 compared to 72% in 2013.\nUse of NGO health services fell from 20% to 16% between 2013 and 2014, and private health care remained around 8%. <sup>1</sup> This positive trend in public health care utilization points to the effectiveness of the\nGovernment’s former policy of free access for refugees, and of efforts by the humanitarian community to\nstrengthen these services and increase the proportion of refugees who are eligible to access them. This\napproach of supporting the provision of services to non-camp refugees through public systems rather\nthan creating parallel structures is in line with UNHCR’s Urban Refugee Policy as well as internationallyrecognized good practice. <sup>2</sup>\n\n\nAs in 2013, Mafraq is an exception", "output": {"entities": {"named_data": ["Jordan Home Visits Report 2014"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001174", "page": 63, "chunk": 0, "title": "Living in the shadows: Jordan Home Visits Report 2014", "pdf_url": "https://reliefweb.int/attachments/b3a9d44a-6721-320e-adfc-ddb6b36422f6/home-visit-report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Jordan Home Visits Report 2014", "label": "NAMED_DATA", "score": 0.825415849685669, "start": 2, "end": 32, "probe_score": 0.9929, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and the US Committee\nfor Refugees and Immigrants. <sup>13</sup> Any range in IDP numbers for a particular country\nexemplifies uncertainty and potential discord regarding the number of people affected\nby conflict. A search for IDPs and refugees was conducted in the following countryspecific documents: HIV/AIDS NSP, World Bank MAP as well as World Bank\nCountry Assistance Strategies (CAS), PEPFAR, and the GFATM proposals for\nRounds 1 to 4. The key words used include ‘HIV’, ‘IDP’, ‘displaced’ and ‘refugee’.\nDocuments in Spanish and French were searched with the appropriate translations.\nAny mention of IDPs and/or refugees was followed by a search for listed HIV\nactivities. These have been referenced in the appendices for further consultation. The\nfindings are also displayed graphically in the tables and pie charts of this section.\n\n<u>Literature Review:</u>\nThe literature review is based on articles found on the internet and from reports\ncirculated by several UN agencies and non-governmental organizations (NGOs).\nPubMed and Google were the main internet search engines used, and their sites were\nlast visited in September 2005. Only documents with data on HIV and IDPs were\nfurther analyzed. For both the PubMed and Google searches, the following key terms\nwere used in the search: ‘HIV and IDP’, ‘HIV and displaced’, ‘HIV sentinel\nsurveillance’, and ‘HIV prevalence.’ From more than 400 results found on PubMed,\nonly 3 references are relevant to this research. They have been used in the literature\nreview below and full references have been provided at the end of this document.\n\n\n17", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on HIV and IDPs"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001301", "page": 16, "chunk": 1, "title": "HIV/AIDS and Internally Displaced Persons in 8 Priority Countries", "pdf_url": "https://reliefweb.int/attachments/c8c8b3b8-f895-3dad-a60c-a2ec5d4a4858/534B8D5834508B4BC12571BF0031EEF9-UNHCR-Jan2006.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on HIV and IDPs", "label": "VAGUE_DATA", "score": 0.5577023029327393, "start": 1161, "end": 1181, "probe_score": 0.0084, "gold": "NON_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the life of the\nproject. This will be an important step in ensuring that communities understand the project and\nthat program management at the local and central level can investigate and take appropriate\nactions to address complaints. The grievance management system will enhance the transparency\nof the project management and its accountability to beneficiaries and stakeholders.\n\n\n32. **Management Information Systems.** The MIS will be developed to provide a\ncomputerized system for the targeting instrument and registry, and for the management of the\nvarious benefits of the two safety nets piloted under the project. Modules will include (a)\nbeneficiary data and registration; (b) monitoring of beneficiaries´ participation in trainings and\naccompanying measures, and/or co-responsibilities (for example attendance at work for the\nCfW); (c) payment of benefits to the beneficiaries; (d) complaints and their resolution.\n\n\n**Component 3: Project Management, Communication, and Monitoring and Evaluation**\n**(US$1.9 million equivalent – IDA Financed)**\n\n\n33. **The objective of this component is to develop the institutional capacity within the**\n**Government of Chad to deliver the activities outlined under components 1 and 2, and**\n**ultimately improve its ability to effectively respond to the needs of vulnerable households.**\nThe project will therefore support the establishment and capacity development of the newly\nestablished CFS, which will effectively be managing the project.\n\n\n34. **The component will finance the salaries of the CFS key staff members deemed**\n**essential to the implementation of the proposed pilot.** This includes a project coordinator, a\nprocurement officer, a FM officer, an accountant, and an M&E expert (who will also serve as a\n\n\n34", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["beneficiary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000028", "page": 45, "chunk": 1, "title": "Chad - Safety Nets Project", "pdf_url": "http://documents1.worldbank.org/curated/en/221251471265217930/pdf/Project-Appraisal-Document-PAD-disclosable-version-P156479-08122016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "beneficiary data", "label": "VAGUE_DATA", "score": 0.6461737751960754, "start": 648, "end": 664, "probe_score": 0.0204, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "The country’s economy is largely dominated by the agriculture and extractive industries, especially\noil. Since 2000, with the advent of the oil era and the high-level of investment in this sector, the\ngross domestic product (GDP) expanded rapidly. Nominal GDP grew by 15% between 2000 and\n2011, with a peak growth rate of 48.3% in 2003-04 and real GDP reached US$10 billion in 2011.\nBoosted by oil revenues, public revenues also grew significantly and contributed to significant\nincreases in infrastructure investments. The average annual deficit is FCFA131 billion and external\ndebt service represents on average FCFA20 billion a year. Price patterns are erratic as a result of the\ncountry’s dependence on food imports and the international oil market; the inflation rate was\nnegative in recent years but it picked up in 2012 and was 2%.\n\nThe economic performance of the last decade was not accompanied by similar improvements in\npoverty level and human development (HD) indicators. Chad remains one of the ten poorest\ncountries in the world, with more than one-half (53.2%) of its population living on less than US\n$1.25 per day and is ranked 183 out of 187 on the UNDP Human Development Index (HDI)\n(2011) . Achieving most Millennium Development Goals (MDGs) by 2015 therefore remains out of\nreach. And this is particularly worrisome given the high population growth rate of 3.4 % (or 3.6%\nincluding refugees. The current population is estimated to be about 12 million people. The\ncountry’s high population growth rate is largely a result of having the highest high fertility rates (7\nchildren per woman) in the world. The population is unevenly distributed across the territory – 47%\nof the population is concentrated on only 10% of the total area of the country – and largely in rural\nareas, with only 21.7% of the population living in urban areas.", "output": {"entities": {"named_data": ["UNDP Human Development Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000020", "page": 1, "chunk": 0, "title": "Project Information Document (Appraisal Stage) - Chad Education Sector Reform Project Phase 2 - P132617", "pdf_url": "http://documents.worldbank.org/curated/en/444901468229746611/pdf/PID-Appraisal-Print-P132617-05-14-2013-1368525900048.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNDP Human Development Index", "label": "NAMED_DATA", "score": 0.8612409234046936, "start": 1167, "end": 1195, "probe_score": 0.9972, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nKenya Inclusive Growth and Fiscal Management DPO 2 (P172321)\n\n\n**PDO3/Pillar 3: Create Fiscal Space and Crowd in the Private Sector to Advance the Government’s Inclusive**\n**Growth Agenda**\n\nDPO1: PA7 & PA8. DPO2: PA5, PA6, & PA7\n\n26. Under DPO1 PA7, value added tax (VAT) exemptions were rationalized through the passage by\nParliament of the Finance Act 2018, which contained a provision for the removal of VAT exemptions on\npetroleum products and through the adoption of a governance framework that limited the number of tax\nexemptions that were granted to arrest the decline in VAT tax revenues. Under DPO2, PA5 an additional\nmeasure to reverse the decline in tax revenues was promoted by the Cabinet approving for submission to\nParliament the Income tax bill 2019 that also limited the number of tax income exemptions.\n\n27. DPO1 PA8 addressed corruption issues by establishing procedures for the investigation of collusive\nbehavior in public procurement bids. It also provided for the verification and reconciliation of external debt\nrecords in order to improve the accuracy of Kenya’s electronic debt registry. DPO2 PA6 increased the\ntransparency of public procurement through publishing online, details of contracts and tenders, including\ntender documents. It also would publish details of companies that had been awarded tenders as well as the\nnames of the directors of the companies. The Cabinet also approved under this PA new regulations that\nallowed for standard bidding documents to be revised in order to provide greater details on bidders.\nParliament also enacted the Competition Amendment Act that included penalties for collusive behavior with\nrespect to public procurement. DPO2 PA7 contained a provision for Cabinet approval of the Debt and\nBorrowing Policy that allowed for the Central Bank to launch the Treasury Mobile Direct System which\nprovided for institutional and retail investors to participate through an electronic online platform in the\nissuance of government securities that would enhance the transparency", "output": {"entities": {"named_data": [], "descriptive_data": ["external debt\nrecords", "electronic debt registry"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000459", "page": 18, "chunk": 0, "title": "Kenya - Inclusive Growth and Fiscal Management Development Policy Operation", "pdf_url": "https://documents.worldbank.org/curated/en/099020009212237369/pdf/BOSIB043bedfa208d0a5850e3ca385021ad.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "external debt\nrecords", "label": "DESCRIPTIVE_DATA", "score": 0.6809601783752441, "start": 1043, "end": 1064, "probe_score": 0.183, "gold": "NON_MENTION", "gold_tier": "flip"}, {"text": "electronic debt registry", "label": "DESCRIPTIVE_DATA", "score": 0.6983352899551392, "start": 1109, "end": 1133, "probe_score": 0.0169, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "PH<br>|\n|Number of suspected cases of COVID-19<br>cases reported and investigated based on<br>national guidelines|<br>Number of suspected<br>effectively cases tested <br>|weekly<br>|COVID-19<br>report<br>|routine data<br>|MOPH<br>|\n|<br>Number of laboratory confirmed cases of<br>COVID-19 treated per approved protocol <br> <br>|Number of laboratory<br>confirmed cases of COVID-<br>19 treated per approved<br>protocol/ number of<br>laboratory confirmed cases<br>of COVID-19|weekly<br>|<br>COVID-19<br>report<br>|routine data<br>|MOPH<br>|\n\n\n\nPage 32", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["routine data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000039", "page": 36, "chunk": 1, "title": "Chad - COVID-19 Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/717781588366403375/pdf/Chad-COVID-19-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "routine data", "label": "VAGUE_DATA", "score": 0.5357637405395508, "start": 205, "end": 217, "probe_score": 0.2931, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the global average. Incidence of GBV reflect longstanding acceptance and\nnormalization of the use of violence for certain acts, particularly against women and girls, as well as perpetuation of\ndiscriminatory norms and practices such as wife inheritance, early and forced marriages, abduction, high bride wealth,\nand ghost marriages. <sup>12</sup> [^12: Ghost marriages are a form of levirate marriage practiced by the Nuer and other Nilotic tribes. These marriages take place in the name of a man\nwho died without marrying or without producing any children. A male relative will stand in for the deceased and marry a woman in order to\nproduce a (male) heir for the “ghost” and to carry on the deceased’s bloodline.] Displacement, the continuing militarization of South Sudan and of Sudanese masculinities,\n\n\n4 United Nations Development Programme 2018 Human Development Reports.\n5 UNOCHA South Sudan Humanitarian Situation Report September 16, 2019.\n6 Checchi, F. et. al. (2018). “Estimates of crisis-attributable mortality in South Sudan, December 2013- April 2018: A statistical analysis”. London School\nof Hygiene & Tropical Medicine.\n7 Integrated Food Security Phase Classification. (2019). <mark>“South Sudan: Acute Food Insecurity and Acute Malnutrition Situation for August 2019 – April</mark>\n<mark>2020”</mark>\n8 HDI’s life-course gender gap compiles 12 indicators that analyze gender gaps in choices and opportunities across the lifespan including education,\nlabor and work, political representation, time use and social protection. HDI’s women’s empowerment dashboard compiles 13 woman-specific\nempowerment indicators in three categories – reproductive health and family planning, violence against women and girls and socioeconomic\nempowerment.\n9 UNDP (2018). Human Development Indices and Indicators: 2018 Statistical Update – South Sudan.\n10 Ministry of Health, National Bureau of Statistics and UNICEF (2013). South Sudan Household Survey 2010. It should be noted that comparative\n_educational_ _outcomes_ are not very different between", "output": {"entities": {"named_data": ["South Sudan Household Survey 2010"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000014", "page": 3, "chunk": 2, "title": "Concept Project Information Document (PID) - South Sudan Enhancing Community Resilience and Local Governance Project - P169949", "pdf_url": "http://documents.worldbank.org/curated/en/294881573571217860/pdf/Concept-Project-Information-Document-PID-South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project-P169949.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "South Sudan Household Survey 2010", "label": "NAMED_DATA", "score": 0.8222670555114746, "start": 1925, "end": 1958, "probe_score": 0.7128, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEmergency Food Security Project (P178936)\n\n\n|Indicator Name|PBC|Baseline|End Target|\n|---|---|---|---|\n|Monitoring tool for access to animal feed developed and<br>accessible to the public (Yes/No)||No|Yes|\n|External users of monitoring tool for access to bread satisfied<br>with information provided (Percentage)||0.00|90.00|\n|External users of monitoring tool for access to animal feed<br>satisfied with information provided (Percentage)<br>||0.00|90.00|\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Monitoring & Evaluation Plan: PDO Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **|**Definition/Description **|**Frequency **|**Datasource **|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|Cumulative amount of wheat procured<br>through the project|Cumulative amount of<br>wheat imports procured<br>with project financing since<br>the start of the project and<br>delivered to the port of<br>Aqaba|Monthly and<br>at the end of<br>the project<br>implementati<br>on period.<br>|MOITS<br>|Data collected regularly<br>and reported by the<br>MOITS<br>|Project Coordination<br>Team<br>|\n|Cumulative amount of barley procured", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Data collected regularly"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 42, "chunk": 0, "title": "Jordan - Emergency Food Security Project", "pdf_url": "http://documents.worldbank.org/curated/en/486071652556836130/pdf/Jordan-Emergency-Food-Security-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data collected regularly", "label": "VAGUE_DATA", "score": 0.5489227771759033, "start": 1054, "end": 1078, "probe_score": 0.0148, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nnumber, web sites, e-mails, in-person, anonymous, suggestion box among others.\n\nGrievances received be written down by the Community Development Officer on the grievance registration\nform and logged into the Grievance Register. A copy of the logged grievance will be signed by aggrieved\nperson and Community Development Officer\n\nThe Community Development Officers will explain the possibilities and ways to raise a grievance to local\ncommunities during meetings organised in each affected area at the time of RAP preparation. The GRM\nprocedures will be disclosed through the Project’s website and will also be advertised on billboards/posters in\neach community and at the entrance of the contractor’s yard. Information material on the GRM will also be\nmade available at the information desks in districts traversed by the project.\n\nIn order to ensure that all grievances are captured, the implementing agency will explain how the grievances\nreceived by district GRC members may be channelled through the Project’s GRM. Training will be conducted\nfor all GRC members on their roles and responsibilities and the implementing agency shall regularly monitor\nto ensure no grievances are missed.\n\n\n36", "output": {"entities": {"named_data": ["Grievance Register"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003663", "page": 40, "chunk": 1, "title": "Stakeholder Engagement Framework May 2024 Electricity Access Scale-up Project (EASP) (P166685)", "pdf_url": "https://documents.worldbank.org/curated/en/099071924094527025/pdf/P166685-cb0ec8b0-1b95-4f26-aed9-55a3a9f98f46.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Grievance Register", "label": "NAMED_DATA", "score": 0.6345371603965759, "start": 209, "end": 227, "probe_score": 0.001, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "In this paper, we present three analyses that shed light on the distribution of economic opportunity\n\n\nwithin highly localized regions, analyses that are only possible with high resolution data like the\n\n\nSHRUG.\n\n\nWe begin by examining the effectiveness of nighttime lights as a measure of local development.\n\n\nNighttime lights, as measured from outer space, have been widely used in recent years to examine\n\n\npatterns of development in places where local economic data is not available. Nighttime lights are\n\n\nparticularly used in analyses of programs which have geographic variation which is more precise than\n\n\nwhat can be observed in aggregate data; the ability to observe an economic outcome in a 1km x 1km\n\n\ncell is a key comparative advantage of night lights. Given the lack of high-precision economic data in\n\n\nmost developing countries, the assumption that night lights have the same elasticities at both very high\n\n\nand very low levels of geographic aggregation with a range of outcome variables is largely untested. <sup>2</sup>\n\n\nOur results confirm that night lights are a highly statistically significant log-linear proxy for a range\n\n\nof development outcomes—population, employment, per capita consumption, and electrification—at\n\n\na very narrow geographical level, even in specifications with regional fixed effects, in the both the\n\n\ncross section and in the time series. However, there are two significant caveats. First, because night\n\n\nlights have independent correlations with each of these outcomes, it is difficult to tell from night\n\n\nlights alone which of these proxy variables are being measured. Researchers have used night lights\n\n\nas a proxy for GDP growth, cross-sectional GDP, urban extent, public expenditure, and electricity\n\n\nsupply and demand, among other variables (Henderson et al., 2011; Baum-Snow et al., 2017; Bleakley\n\n\nand Lin, 2012; Min et al., 2013; Hodler and Raschky, 2014; Baskaran et al., 2015; Burlig and\n\n\nPreonas, 2016; Harari, 2020;", "output": {"entities": {"named_data": ["SHRUG"], "descriptive_data": [], "vague_data": ["local economic data", "economic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000265", "page": 6, "chunk": 0, "title": "development research at high geographic resolution an analysis of night lights firms and poverty in india using the shrug open data platform", "pdf_url": "https://local/prwp/development-research-at-high-geographic-resolution-an-analysis-of-night-lights-firms-and-poverty-in-india-using-the-shrug-open-data-platform.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SHRUG", "label": "NAMED_DATA", "score": 0.7379194498062134, "start": 205, "end": 210, "probe_score": 0.1144, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "local economic data", "label": "VAGUE_DATA", "score": 0.5558873414993286, "start": 450, "end": 469, "probe_score": 0.4818, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "economic data", "label": "VAGUE_DATA", "score": 0.5638312101364136, "start": 800, "end": 813, "probe_score": 0.7672, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 2019 to 55.3% in 2020, bringing the total number of poor Lebanese to about 2.7\nmillion. <sup>12</sup> [^12: Lebanon Economic Monitor, Fall 2020] These developments increase pressures for emigration, especially among the middle class. Such deprivations\nhave further degraded the relationship between people and the state. Grievances with the political system and\ndissatisfaction with the state’s mismanagement of the economy and its entrenched corruption resulted in nationwide\nprotests in late 2019. Since, intermittent social unrest highlights the needs for a new social contract between citizens\nand the government. In a survey conducted by the World Bank among victims of the blast, the overwhelming majority\nof respondent’s report having “no trust at all” in political parties, the Council for Development and Reconstruction, or\nmunicipalities. <sup>13</sup> [^13: Ranking on a 5 point scale, where 1 = “no trust at all” and 5= “complete trust.” Average score was 1.2 for political parties, 1.5 for CDR, and 1.7 for municipalities.\nSurvey not strictly representative due to its design. Source: http://documents1.worldbank. org/curated/en/899121600677984471/pdf/Beirut-Residents-Perspectiveson-August-4-Blast-Findings-from-a-Needs-andPerception-Survey.pdf]\n\n\n6 Bank Byblos (February 2020) Lebanon This Week ‘Lebanon’s expats’ remittances drop by 20% in H1 of 2020 in Xinhuanet.\n7 World Food Program (December 202) Lebanon, VAM Update of Food Price and Market Trends.\n8 <u>[https://www.unicef.org/lebanon/media/5616/file](https://www.unicef.org/lebanon/media/5616/file)</u>\n9 <u>[https://reliefweb.int/report/lebanon/vasyr-2020-key-findings-2020-vulnerability-assessment-syrian-refugees-lebanon](https://reliefweb.int/report/lebanon/vasyr-2020-key-findings-2020-vulnerability-assessment-syrian-refugees-lebanon)</u>\n10 <u", "output": {"entities": {"named_data": ["Lebanon Economic Monitor"], "descriptive_data": ["survey conducted by the World Bank"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000054", "page": 3, "chunk": 2, "title": "Concept Project Information Document (PID) - Support for Social Recovery Needs of Vulnerable Groups in Beirut - P176622", "pdf_url": "http://documents.worldbank.org/curated/en/883871626924990781/pdf/Concept-Project-Information-Document-PID-Support-for-Social-Recovery-Needs-of-Vulnerable-Groups-in-Beirut-P176622.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Lebanon Economic Monitor", "label": "NAMED_DATA", "score": 0.6788351535797119, "start": 109, "end": 133, "probe_score": 0.9945, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey conducted by the World Bank", "label": "DESCRIPTIVE_DATA", "score": 0.7682328224182129, "start": 624, "end": 658, "probe_score": 0.9067, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "schools who return to<br>school once the school<br>system is reopened|Annual<br>|The<br>enrollment<br>will be<br>monitored<br>through the<br>EMIS data.<br>|The enrollment will be<br>monitored through the<br>EMIS data.<br>|MoES/PCU<br>|\n\n\n|Monitoring & Evaluation Plan: Intermediate Results Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **|**Definition/Description **|**Frequency **|**Datasource **|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|IRI 1: Awareness and health safeguarding<br>messages disseminated to students,<br>teachers, parents and community<br>members through various media (SMS,<br>text, TV and radio) (number)|Defn: Awareness and health <br>safeguarding messages are<br>designed to reach a specific<br>audience (in this case:<br>students, teachers and<br>parents) to stop the spread|Bi-annual<br>|Approved m<br>aterials<br>|Reports on materials<br>disseminated<br>|CIM, Gender Unit<br>|\n\n\nPage 31 of 43\n\n\nOfficial Use\n\n\n\n**ME PDO Table SPACE**", "output": {"entities": {"named_data": ["EMIS data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016065", "page": 35, "chunk": 1, "title": "Uganda - COVID-19 Emergency Education Response Project", "pdf_url": "https://documents.worldbank.org/curated/en/645041598936002560/pdf/Uganda-COVID-19-Emergency-Education-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "EMIS data", "label": "NAMED_DATA", "score": 0.7207796573638916, "start": 141, "end": 150, "probe_score": 0.6811, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nGenerating Growth Opportunities and Productivity for Women Enterprises Uganda (P176747)\n\n\n\n|Col1|including childcare and<br>those community and<br>household members.|Col3|Col4|the infrastructure<br>facilities.|Col6|\n|---|---|---|---|---|---|\n|Women beneficiaries (percentage)|<br>|||<br>||\n|Women in RHD||||||\n|Refugee women||||<br>||\n|Value of credit provided to women<br>enterprises (Amount)|This indicator measures the<br>value of credit provided by<br>the PFIs under the project,<br>disaggregated by refugee<br>status, district, age, and<br>disability status.|Continuous.<br>|PFI data.<br>|The PFIs will maintain<br>databases of the value<br>of the credit disbursed,<br>disaggregated by<br>refugee status, district,<br>age, and disability<br>status.<br>|The MGLSD to collect<br>the data from the PFIs<br>each month, and<br>compile and report it.<br>|\n|Women enterprises in RHDs||||<br>||\n|Refugee-owned enterprises||<br>||||\n|Beneficiaries of job-focused interventions||Enterprise<br>baseline<br>survey,<br>annual<br>surveys from<br>year 2.<br>|Surveys of<br>enterprises.<br>|This indicator measures<br>", "output": {"entities": {"named_data": [], "descriptive_data": ["PFI data", "data from the PFIs"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000088", "page": 50, "chunk": 0, "title": "Uganda - Generating Growth Opportunities and Productivity for Women Enterprises Uganda Project", "pdf_url": "http://documents1.worldbank.org/curated/en/527091655323259747/pdf/Uganda-Generating-Growth-Opportunities-and-Productivity-for-Women-Enterprises-Uganda-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PFI data", "label": "DESCRIPTIVE_DATA", "score": 0.7937891483306885, "start": 599, "end": 607, "probe_score": 0.3346, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "data from the PFIs", "label": "DESCRIPTIVE_DATA", "score": 0.8375282287597656, "start": 805, "end": 823, "probe_score": 0.8123, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "/sup> Furthermore, 13.2 percent of firms are majority owned by women while 18.1 percent have women in top\nmanagement positions. Additionally, the average percentage of women in permanent full-time jobs is 31.6. <sup>13</sup> [^13: <u>[WBG (2019) World Bank Enterprise Surveys (WBES) https://www.enterprisesurveys.org/en/data/exploreeconomies/2018/kenya#gender](https://www.enterprisesurveys.org/en/data/exploreeconomies/2018/kenya#gender)</u>] To address\ngaps related to natural resource management and environmental conservation, KEWASIP will promote women’s\nparticipation in sustainable land and water management (SLWM) and the inclusion of women in income-generating\nactivities related to landscape restoration.\n\n\n12. **The project will establish quotas for women's representation in Common Interest Groups (CIGs).** Training for\nwomen will be provided to strengthen decision-making, enhance technical capabilities, and promote participation in\nSLWM activities. Indicators in the Results Framework (RF) will be used to measure the ‘Share of women representation in\nlocal natural resource management bodies (target 30 percent)’. Under the project, 30 percent of the financial grants for\nnature-based enterprises will be reserved for women-led or women-owned nature-based enterprises, and dedicated\ncommunications and direct technical support will be provided to these enterprises to ensure effective disbursement of\nfunds. Training programs will also be implemented to boost income-generating activities related to alternative livelihood\nand climate-smart agriculture practices. An indicator in the RF will measure ‘Share of women-led or -owned nature-based\nenterprises receiving financial support’ (target 30 percent) as well as ‘Female share of beneficiaries directly benefiting\nfrom Payment for Ecosystem Services contracts’ (target: 30 percent). Additionally, KEWASIP will provide training in\nsustainable practices and alternative livelihoods, targeting female-headed and labor-constrained households. This training\nwill be designed to accommodate all varieties of family units and encourage the", "output": {"entities": {"named_data": ["World Bank Enterprise Surveys"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000168", "page": 16, "chunk": 1, "title": "Kenya - Watershed Services Improvement Project", "pdf_url": "https://documents.worldbank.org/curated/en/099011226203531036/pdf/BOSIB-e310faa6-3e32-4172-a4d8-a7c41cebe642.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Bank Enterprise Surveys", "label": "NAMED_DATA", "score": 0.8939488530158997, "start": 246, "end": 275, "probe_score": 0.9918, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n\n\nmeasles vaccination coverage for children\nstood at 83%, similar to 84% in 2023, falling\nshort of the 95% target.\n\n\n\n\n\n\n\nInformal support also played a vital role, with\n33% receiving help from family or friends and\n12% accessing spiritual support. Overall, 88%\nof those who received support reported\nimproved wellbeing, though there are notable\ndifferences depending on gender and age.\n\n\nThe recommendations drawn from this analysis\nfocus on addressing the health and mental health\nand psychosocial needs and barriers identified in\nthe SEIS, tailoring them to the specific data and\ncontext of each country. To enhance policy\ndevelopment, it will be crucial to improve monitoring\nof refugees’ health, including sexual and\nreproductive health and mental health, through\ninclusion of disaggregated refugee data into\nnational data systems. This will require effective\ncollaboration among health organizations, statistical\noffices, and partners. Addressing capacity issues in\nnational health systems, such as workforce\nshortages and long wait times, can be supported\nthrough telemedicine and temporarily integrating\nUkrainian healthcare workers. Refugees with\nchronic illnesses and disabilities require targeted\ninterventions to meet their health and MHPSS\nneeds, including through health financing\nmechanisms. Continued efforts are also required to\naddress persistent access barriers through contextspecific strategies, including providing refugees\nwith information on navigating health systems and\npreventive health services such as vaccination.\n\n\nExpanding community-based MHPSS services that\nintegrate formal services and promote the use of\ninformal supports will enhance service delivery.\nPublic awareness campaigns, tailored to both\nrefugees and host communities, should aim to\nreduce stigma and improve knowledge of available\nsupport. Gender-responsive and age-sensitive\napproaches are necessary, particularly for adult men\nand adolescent boys, to encourage help-seeking\nbehaviours and ensure that services are tailored to\nthe specific needs of children and adolescents.\nLastly, further research is required to gain a deeper\nunderstanding of unmet health needs—including\nSRH and MHPSS needs—and the barriers to access", "output": {"entities": {"named_data": ["SEIS"], "descriptive_data": ["disaggregated refugee data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000004", "page": 3, "chunk": 0, "title": "NAVIGATING HEALTH AND WELL BEING CHALLENGES FOR REFUGEES FROM UKRAINE   2nd Edition", "pdf_url": "https://local/jad_paddy_docs/navigating health and well-being challenges for refugees from ukraine - 2nd edition.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS", "label": "NAMED_DATA", "score": 0.5449971556663513, "start": 608, "end": 612, "probe_score": 0.6005, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "disaggregated refugee data", "label": "DESCRIPTIVE_DATA", "score": 0.759947657585144, "start": 853, "end": 879, "probe_score": 0.4115, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "3RP 2016 reporting:\nInformation Management as Coordination Support\n\n\n\nTo support coordination, an online\nplatform is rolled-out to collect reports on the\n9 Sectors’ activities carried out by about 80\npartners. Reporting on ActivityInfo enables each\npartner/user to:\n\n- Collect, Manage, analyse and geo-locate their\nown activities.\n\n- View and extract reports on all the activities of\nother agencies in the response.\n\n- Integrate their activities within the entire\nresponse.\n\n- Reinforce partnerships and reduce costs and\ntime on reporting.\nTo familiarize the partners with the tool, training\nsessions were provided to more than 500 staff of\nall agencies with users access to the databases.\n\nA time line for reporting is also agreed upon as shown below:\n\n\n\nA screen-shot of **www.activityinfo.org** while partners are entering\nachievement data on their activities:\n\n\n\n**2016** : Information flow/roles and responsibilities/timeframes for monthly reporting on ActivityInfo\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Col2|\n|---|---|\n|||\n\n\n\n**irqerbim@unhcr.org**\n\n17", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["achievement data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001629", "page": 17, "chunk": 0, "title": "3RP Regional Refugee & Resilience Plan/Iraq Humanitarian Inter-Agency Interventions for Syrian Refugees: Information Kit No. 16 - End-Year Report 2016 (Published March 2017)", "pdf_url": "https://reliefweb.int/attachments/fc0722a5-d40e-3745-979f-f7e470a2fc9c/InformationKit163RPEndYear2016Inter-AgencyInterventionsforSyrianRefugees-Iraq%20small.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "achievement data", "label": "VAGUE_DATA", "score": 0.6139749884605408, "start": 826, "end": 842, "probe_score": 0.1662, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_ basis as well\nas those who have been newly registered and\ngranted temporary protection. An additional\n398,500 persons were granted refugee status or a\ncomplementary form of protection following refugee\nstatus determination during the reporting period.\n\n\nThe conflict in Syria continued to cause people to\nflee that country, with 280,700 new refugees in the\nfirst half of the year alone as well as some 209,600\ngranted refugee status or a complementary form of\n\n\n**3** Operational data show that daily arrivals to countries transited\nen-route to Germany such as Serbia and Austria decreased\nfrom highs of 10,000 per day seen in October 2015 to highs of\n300 by April 2016 and 200 by September 2016.\n[www.data.unhcr.org](http://www.data.unhcr.org)\n\n\n\n10 u n h c r > **m i d - y e a r t r e n d s** **2 0 1 6**", "output": {"entities": {"named_data": [], "descriptive_data": ["Operational data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001232", "page": 9, "chunk": 1, "title": "UNHCR Mid-Year Trends 2016", "pdf_url": "https://reliefweb.int/attachments/bd4cde9b-006d-3a90-9480-0feece6c9207/58aa8f247.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Operational data", "label": "DESCRIPTIVE_DATA", "score": 0.6537729501724243, "start": 470, "end": 486, "probe_score": 0.9883, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Disbursement forecast\n\n\n\nContract number\n*Contract subject\nAwardee\n*Launching date\n-Expected delivery date\n-Non objection date\n*Expected date of final delivery\n*Bidder nationality\n*Contract allocation (general account, budget, loan\ncategory, geographic area)\n*List of contracts\nManagement of financial -Standard financial statements (balance sheet;\naccounts statement of sources and uses of funds/income\nstatement, ...)\n*LACI reports for the project duration\nFixed Assets management -Inventory of Fixed Assets (type, quantity, valuation,\ndate of service, etc.)\n\n\n\nSupplier\nAccounting category ; budgetary and accounting\nallocation of fixed assets\n\n\n\nLocation\nDepreciation\n-Disposal of Fixed assets\n\n\n\n**Module** Functions\nSorting parameters Project ID and currency used\n\n                  - Fiscal years\nCurrency\nDecentralized data entry locations\n\n\n\nChart of accounts, managerial reports, geographic\nareas of intervention, etc.\n\n\n\n\n                - Books of accounts\nDonors\n\n                 - Contracts\nCategories of disbursement\nUser Management Data storage ; restitution ; correction; cleaning; etc.\n\n                - Import/export of data to other Tempro modules\n\n\n\nIt is expected that the application would be modified to differentiate the operations from the\nprojects, as well as funding sources to allow for reporting in financial and accounting terms of the\nproject objectives and activities. The concept should allow for proper monitoring of the project\nduring the life of the credit, namely: (i) chart of accounts; (ii) by category, component, and subcomponent; (iii) by geography (type of establishment, site and district); (iv) by category of\nexpenses; and (v) in local and foreign currency. Reporting of multi-level data is planned, which\n**wiU** bring about a more dynamic approach to the management of the project, and which should", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["multi-level data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000041", "page": 51, "chunk": 0, "title": "Jordan - Community Infrastructure Project", "pdf_url": "http://documents1.worldbank.org/curated/en/294581468773394111/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "multi-level data", "label": "VAGUE_DATA", "score": 0.6651609539985657, "start": 1720, "end": 1736, "probe_score": 0.4661, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "3\n\n\nbinding <sup>4</sup> . Internal restrictions on rice trade which prevented rice produced in the south from\n\nbeing traded in the north of Vietnam were also lifted in 1997 <sup>5</sup> . Import quotas on chemical\n\nfertilizers were also relaxed over this interval. Poverty rates fell sharply from 59 percent to 37\n\n\npercent over this interval, leading some to attribute this remarkable outcome to global\n\nintegration <sup>6</sup> . Income inequality rose, driven mainly by differences between urban and rural\n\nareas <sup>7</sup> . Over 80 percent of Vietnam’s population in 1993 resided in rural areas and were\n\nengaged primarily in agricultural work, making the analysis of their welfare pertinent in\n\n\nlearning about rural poverty. The distinctive feature of this paper is the availability of a\n\nhousehold panel dataset that spans a period of agricultural trade reforms in Vietnam between\n\n\n1993 and 1998. The use of panel data arguably allows for a much better identification of the\n\neffects of trade liberalization on household welfare.\n\n\nThe approach used in this study goes beyond existing work in four different\n\n\ndimensions. First, I consider welfare and poverty outcomes among urban _and_ rural\n\nhouseholds. Second, actual price changes are used instead of simulated or hypothetical\n\n\nchanges seen in other studies. As Edmonds and Pavcnik (2002) observed, the degree of price\n\nchanges varies across regions which implies that geographically dispersed households will be\n\naffected differently by trade liberalization <sup>8</sup> . Third, household welfare measures consistent with\n\nutility maximizing and profit maximizing behavior are computed as opposed to relying on\n\n\nproducer and consumer surplus approximations. These welfare measures include second\norder responses by producers and consumers in reacting to changes in rice and fertilizer\n\n\nprices. Fourth, in analyzing the farm household, I depart from the usual assumption of\n\ncomplete labor markets which allows for separability between household labor demand and\n\n\nsupply decisions. Household members face binding constraints in seeking off", "output": {"entities": {"named_data": [], "descriptive_data": ["household panel dataset"], "vague_data": ["panel data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002761", "page": 2, "chunk": 0, "title": "wps3541", "pdf_url": "https://local/prwp/wps3541.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household panel dataset", "label": "DESCRIPTIVE_DATA", "score": 0.8803739547729492, "start": 799, "end": 822, "probe_score": 0.3869, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "panel data", "label": "VAGUE_DATA", "score": 0.5366111397743225, "start": 920, "end": 930, "probe_score": 0.9824, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "53. Under the Uganda rainfall condition, the frequency of flooding in most municipalities is between\n10 to 15 times in a year lasting 3 to 4 hours per flooding. Private and commercial vehicles are disrupted\nleading to loss of time and income. Improved drainage also leads to improvements to the environment and\nhealth benefits from reduced incidence of water borne disease. The internal rate of return obtained in\nprevious studies in similar environments was used to estimate the stream of benefits generated by improved\ndrainage. The EIRR of drainage under USMID was calculated at 6%.\n\n**Increase in Property Values**\n\n54. Improvements in urban roads in all the municipalities sampled has led to increases in value of\nproperties (land, buildings) and rental prices of properties in the adjacent areas of the constructed roads\nranging from 20% to 100% as per the table below. In Hoima municipality, the sharp increase in both rent\nand land values can also be attributed to speculations about oil extraction impact on the local economy.\n\n**Table 9: Changes in Rent and Land values**\n\n\n**Employment Creation**\n\n55. Construction of urban roads created direct and indirect jobs during construction. However, most of\nthe urban road infrastructure projects visited had been completed or partially completed. It was only\nNyakana road in Fort Portal where construction was still ongoing and therefore data on employment was\nobtained. The construction of Nyakana road in Fort Portal with a length of 0.94km, was directly employing\n56 workers out of which, 10% were highly skilled, 10% were skilled and 80 % unskilled. The highly skilled\nworkers, skilled workers and unskilled workers were earning UGX35,000, UGX25,000 and UGX12,000\nper day respectively. The construction of the road was also indirectly employing approximately 70 workers.\nThe construction of the road was expected to last for one year and three months.\n\n56. It can therefore be estimated from this data that construction of one kilometer creates", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on employment"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000006", "page": 69, "chunk": 0, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents.worldbank.org/curated/en/143681526614252328/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on employment", "label": "VAGUE_DATA", "score": 0.6891720294952393, "start": 1393, "end": 1411, "probe_score": 0.4287, "gold": "NON_MENTION", "gold_tier": "human-final"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "), which falls under the authority of the Deputy Prime\nMinister and Minister of State for Public Sector Modernization.\n\n**8.** **Jordan consistently ranks above average among middle-income countries on government effectiveness, rule of law,**\n**regulatory quality, and control of corruption, but below average on voice and accountability.** <mark>International benchmarks</mark>\n<mark>and opinion surveys suggest that improvement is needed in transparency and access to information, social accountability,</mark>\n<mark>and grievance redress mechanisms to support citizens’ trust in government. This is an objective of the government reform</mark>\n<mark>agenda which aims at promoting e-participation, enforcing public access to information, institutionalizing stakeholder</mark>\n<mark>consultation to inform policy making and implementation, and at improving government responsiveness to citizen</mark>\n<mark>feedback.</mark> According to the United Nations (UN) e-government index and the World Bank (WB) GovTech Maturity index, <sup>6</sup> [^6: See Jordan’s detailed rating in Technical Assessment.]\ndespite significant progress in digital government, there is an opportunity for improvement to voice and accountability,\nas well as to access to and quality of services. Internet and mobile connectivity and the use of internet social media is\nwidespread, with close to 10 million internet users in 2023 (an 88 percent penetration rate). There are over 8.5 million\nactive cellular mobile connections, and over 6.5 million social media users (that is, 58 percent of the population), with 45\npercent of users being women. <sup>7</sup> [^7: Kemp, Simon. 2023. “Digital 2023: Jordan.” Datareportal. https://datareportal.com/reports/digital-2023-jordan.]\n\n**9.** **Jordan has been actively working on the digitalization of public services", "output": {"entities": {"named_data": ["e-government index", "GovTech Maturity index"], "descriptive_data": ["opinion surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000181", "page": 12, "chunk": 1, "title": "Jordan - People-Centric Digital Government Program for Results", "pdf_url": "https://documents1.worldbank.org/curated/en/099030724150040202/pdf/BOSIB-70f97ae8-b741-401c-82cc-e87615cc5487.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "opinion surveys", "label": "DESCRIPTIVE_DATA", "score": 0.6967850923538208, "start": 389, "end": 404, "probe_score": 0.9865, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "e-government index", "label": "NAMED_DATA", "score": 0.6782131195068359, "start": 963, "end": 981, "probe_score": 0.9043, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "GovTech Maturity index", "label": "NAMED_DATA", "score": 0.786600649356842, "start": 1006, "end": 1028, "probe_score": 0.9266, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["M&E data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017874", "page": 29, "chunk": 2, "title": "Kenya - Arid Lands Resource Management Project", "pdf_url": "https://documents.worldbank.org/curated/en/766091468272459520/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "M&E data", "label": "VAGUE_DATA", "score": 0.5883201956748962, "start": 530, "end": 538, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "ener el estatuto de refugiado o que sea refugiado de conformidad con el derecho\ny los procedimientos correspondientes reciba la protección y asistencia humanitaria\nadecuada (art.22).\n\n\n\n\n\n_N I Ñ O S, N I Ñ A S Y A D O L E S C E N T E S M I G R A N T E S . A M É R I C A C E N T R A L Y M É X I C O_", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000894", "page": 43, "chunk": 2, "title": "Niños, niñas y adolescentes migrantes: América Central y México", "pdf_url": "https://reliefweb.int/attachments/84452fd2-85ab-3bb3-b914-4237ab4a84bc/ninez_america_latina.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "u> <u>0.053</u>\n\n_Notes:_ The sample in Panel A is all parents with a child aged 15 and under (N=1614); the sample in Panel B is all\nchildren aged 15 and under (N=2996). Children age 12-15 are \"Ineligible\" and children under 11 are \"Eligible\".\nAbove regressions are estimated coefficients from 2SLS-IV estimates where \"Parent Enrolled\" is instrumented with\nrandom assignment status; Ineligible*Parent Enrolled is instrumented with random assignment status*Ineligible. The\ndependent variable are various measures of health status: whether the child had a checkup in the past year, whether\nthe child had ever been sick in the past year, and the number of times sick. Regressions control for household size,\nhousehold size squared, the inverse hyperbolic sine of parental income, parent's years of education, age of child, age\nof child squared, gender, whether the child was sick in the past year, the number of times sick, total number of health\nvisits, and survey round and market fixed effects. Individuals without valid income data were imputed to be the\nmedian and regressions were run with a dummy variable indicating the missing value. Robust standard errors in\nparentheses, clustered at the family level. *** p<0.01, ** p<0.05, * p<0.1\n\n\n_Source:_ Authors’ analysis based on data described in paper.\n\n\n13", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["income data", "data described in paper"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007094", "page": 42, "chunk": 1, "title": "wps8115", "pdf_url": "https://local/prwp/wps8115.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "income data", "label": "VAGUE_DATA", "score": 0.6525024175643921, "start": 1021, "end": 1032, "probe_score": 0.8972, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data described in paper", "label": "VAGUE_DATA", "score": 0.7529206275939941, "start": 1280, "end": 1303, "probe_score": 0.9732, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "~~<br>ia<br>lic<br>anmar<br>Namibia<br>El S lv dor|\n|~~Bu~~rkina ~~Faso~~<br>Como~~ro~~s<br>Mali<br>Niger<br>Ch~~ad~~|~~Bu~~rkina ~~Faso~~<br>Como~~ro~~s<br>Mali<br>Niger<br>Ch~~ad~~|~~B~~|~~B~~|~~B~~|~~B~~|~~B~~|~~B~~|~~B~~|~~B~~|\n|||||||||||\n\n\n6 8 10 12\nLog Real GDP Per Capita at PPP\n\n\nNotes:  This graph plots the HCI disaggregated by quintiles of socioeconomic status (on the vertical axis) against log\nreal GDP per capita (on the horizontal axis) for the most recent cross-section of 51 countries in the SES-HCI dataset.\nThe solid dot indicates the average across quintiles, and the top (bottom) end of the vertical bar indicates the value\nfor the top (bottom) quintile. The light grey data points show the global HCI for countries for which the SESdisaggregated HCI is not available.\n\n\n35", "output": {"entities": {"named_data": ["SES-HCI dataset"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000030", "page": 36, "chunk": 3, "title": "a socioeconomic disaggregation of the world bank human capital index", "pdf_url": "https://local/prwp/a-socioeconomic-disaggregation-of-the-world-bank-human-capital-index.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SES-HCI dataset", "label": "NAMED_DATA", "score": 0.8857940435409546, "start": 510, "end": 525, "probe_score": 0.7343, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nRoads and Employment Project (P160223)\n\n\nworks are generally financed from either the budget or borrowing. Although road transport is already\ncostly as Lebanon has relatively high taxes on gasoline and on vehicle registration, these taxes are not\ndedicated or linked to expenditures in the road sector and are mainly used to reduce the gap in the\nnational fiscal balance. The legacy of underinvestment and poor maintenance has also resulted in costly\nretrofitting of the network with little resources allocated to routine and periodic maintenance, therefore\nincreasing inefficiency of expenditures.\n\n\n14. **Weak road safety management, including poor road infrastructure quality, together with bad**\n**behavior and lack of enforcement, has had detrimental effects on road safety in Lebanon.** Lebanon road\nsafety record is among the worst globally. Traffic related accidents and injuries have been increasing at a\nhigh rate in the past few years, from 508 fatalities and 6,050 injuries in 2012 to 655 fatalities and 6,472\ninjuries in 2014, as reported by the Internal Security Forces (ISF). These figures cover all accidents in\nLebanon, including those involving Syrians. Syrians in Lebanon have witnessed a particularly sharp\nincrease in their reported fatalities between 2012 and 2014, from 52 fatalities to 162 fatalities. The ISF’s\nfigures however are widely considered to be underreported. The World Health Organization (WHO)\nestimates the total number of road traffic fatalities in Lebanon in 2015 at 1,088 and the associated\neconomic cost between 3 to 5 percent of GDP, higher than most other countries in the world. <sup>7</sup> [^7: WHO. Global Road Safety Status Report. 2015.]\n\n\n15. **To deal with increasing road traffic and safety challenges, the Lebanese Parliament has passed**\n**in October 2012 a new and modern traffic law.** Several key actions of the law are now under\nimplementation, in particular the creation of the National Road Safety Council (NRSC) chaired by the", "output": {"entities": {"named_data": ["Global Road Safety Status Report"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 17, "chunk": 0, "title": "Lebanon - Roads and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/210611486651815142/pdf/Lebanon-Roads-Employment-PAD-P160223-01262017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Global Road Safety Status Report", "label": "NAMED_DATA", "score": 0.7253859043121338, "start": 1666, "end": 1698, "probe_score": 0.9987, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "We address this challenge by first estimating the “true” rate of exit for each cohort of firms\n\n\n(e.g., firms born between 1974 and 1976). Figure 3 shows the pattern of survival observed for each\n\n\ncohort. In each year, we then consider the potential pool of exiting firms (i.e., firms we do not\n\n\nobserve in any subsequent year), and use one of several algorithms to assign exit to the number\n\n\nof the firms we estimate to have exited from each cohort. The remaining firms are assigned to the\n\n\ngroup of survivors.\n\n\nThere are a number of ways to select firms for exit from the potential pool of exiters. To choose\n\n\nan appropriate strategy, we examined the distribution of TFP for potential exiters versus survivors,\n\n\nfor two years (1999-2000) in which observed exit rates are relatively close to estimated exit rates,\n\n\nindicating that the pool of potential exiters is likely to be representative of “true” exiters (Figure\n\n\n4, Panels (a) and (c)). We also examined TFP distributions in two years (1995 and 2004) when\n\n\nthe observed exit rate is significantly higher than the estimated, true exit rate, indicating that many\n\n\ntrue survivors are classified as exiters (Figure 4, Panels (b) and (d)). In both cases, the distributions\n\n\nof potential exiters are slightly left-shifted, indicating that exiters are, on average, less productive\n\n\nthan survivors. However, the two distributions of potential exiters are similarly left-shifted relative\n\n\nto the distributions of survivors, suggesting that one way to assign exit in years with significant\n\n\namounts of false exit, is to select a random sample of firms from the pool of potential exiters.\n\n\nFigure 5 shows the results of the MP decomposition model when exit is assigned in this man\n\nner. <sup>15</sup> The MP decomposition tells a similar story as the OP decomposition. Aggregate produc", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004938", "page": 19, "chunk": 0, "title": "wps5761", "pdf_url": "https://local/prwp/wps5761.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " budget for the supply of soap and cleaning products for latrines; civic\nassociations – who will be implicated in the campaigns during project implementation – and the DRHAs, who will\nprovide technical support for any major upgrades or repairs.\n\n\n**IV.** **PROJECT APPRAISAL SUMMARY**\n\n# A. Technical, Economic and Financial Analysis\n\n\n**Technical Analysis**\n\n\n59. **No major technical issues are expected because the technologies being considered for WSS are proven and**\n**well established** . Special attention will be paid to (a) ensuring a maximal use of solar pumping; and (b) considering\nbeneficiaries’ preferences in the construction of latrines to ensure the safety of women and girls, provide\nmenstrual hygiene essentials, lighting and other necessary features.\n\n\n60. **As for sectoral reforms, the proposed activities draw on initial analysis undertaken in the sector** (e.g. the\nWorld Bank’s _Note Sectorielle_ of March 2017), developed to complement the PER. The proposals also draw\nguidance from impactful reforms implemented in Mauritania or similar countries. For example, proposals to\nstrengthen CNRE’s capacities and protocols for groundwater data and to improve SNDE’s performance through a\nframework contract with the state, are both good practices for boosting the capacity of sector institutions.\n\n\n**Summary of Economic Analysis**\n\n\n61. **The economic analysis consists of a cost-benefit analysis (CBA) to assess the economic impact of the water**\n**and sanitation related activities of the project (66 percent of total project costs)** . The full description of costs\nand benefits is presented in Annex 4. In summary, the water and sanitation benefits include: increased water\nconsumption; time savings for women collecting water; incremental revenues from new connections; reduced\nenergy consumption; reduction of technical losses; health care cost savings; increase in female school attendance\n\n\nPage 23 of 65", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["groundwater data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000106", "page": 27, "chunk": 1, "title": "Mauritania - Water and Sanitation Sectoral Project", "pdf_url": "http://documents1.worldbank.org/curated/en/605151585879430844/pdf/Mauritania-Water-and-Sanitation-Sectoral-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "groundwater data", "label": "VAGUE_DATA", "score": 0.6154564619064331, "start": 1149, "end": 1165, "probe_score": 0.0022, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Annex 1:** **Project** **Design** **Summary**\n\n**SIERRA LEONE:** **NATIONAL** **SOCIAL ACTION** **PROJECT**\n\n\n. **Hierarchy o.Qbijctives -'**  - . **diator** **r**, t **,P** **jCitidaI** **r!** **As's-umptIons,Y-**\n**Sector-related** **CAS** **Goal:** **Sector** **Indicators:** **Sector/ country reports:** **(from** **Goal** **to Bank** **Mission)**\nMitigate the risk of renewed 1. National conflict/security- - UNHCR/OCHA reports - Continued peace and\n**conflict** **and lay foundation** related indicators - Household Income and regional security\n**for** **poverty reduction and** 2. Inter-regional disparities in Expenditure Surveys - Economic and political\n**improvements** **in nutrition,** I-PRSP & PRSP core - PETS surveys stability\n**health, education** **and** indicators - Strategic Planning and\n**targeting** **the rural** 3. Inter-regional disparities in Action Process (SPP) reports\n**population,** women **and** Popular Benchmarks\n**children.**\n\n\n**Project** **Development** **Outcome** **/** **Impact** **Project reports:** **(from** *", "output": {"entities": {"named_data": ["Inter-regional disparities in Expenditure Surveys", "PETS surveys"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015859", "page": 29, "chunk": 0, "title": "Uganda - Environmental Management Capacity Building Project", "pdf_url": "https://documents.worldbank.org/curated/en/631101468760808042/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Inter-regional disparities in Expenditure Surveys", "label": "NAMED_DATA", "score": 0.5622888207435608, "start": 590, "end": 639, "probe_score": 0.0005, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PETS surveys", "label": "NAMED_DATA", "score": 0.6322475075721741, "start": 721, "end": 733, "probe_score": 0.0465, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Table 1.a. Agricultural Production in Mexico by Source and Product (2008)** <sup>**1/**</sup>\n\n|Irrigation|Rain‐fed|\n|---|---|\n|**(a)**<br>**(b)**<br>**(a)/(b)**<br>**Maize**<br>**Total**<br>**% **|**(c)**<br>**(d)**<br>**(c)/(d)**<br>**Maize**<br>**Total**<br>**% **|\n|1,590,111.2<br>5,612,662.3<br>28.33%<br>1,541,559.9<br>5,413,056.9<br>28.48%<br>15,835,037.6<br>355,037,345.1<br>4.46%<br>10.3<br> <br> <br>32.0<br> <br> <br>2.2<br> <br> <br>1,523<br> <br>|6,853,725.7<br>16,289,910.4<br>42.07%<br>6,288,549.7<br>15,089,776.8<br>41.67%<br>20,022,737.6<br>118,791,025.7<br>16.86%<br>3.2<br> <", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006607", "page": 30, "chunk": 0, "title": "wps7565", "pdf_url": "https://local/prwp/wps7565.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**_Public Financial Management Reforms Secretariat_**\n**_Annual Report and Financial Statements for the financial year_** <sup>**_ended June 30,_**</sup> <sup>**_2025_**</sup>\n\n\n**b)** In efforts to ensure compliance with the revised professional framework <sup>among</sup> <sup>the</sup>\n\npublic procurement workforce, a syllabus review and mapping <sup>were</sup> <sup>done,</sup> <sup>and a draft</sup>\n\ninvestigation manual developed. These foundational steps are crucial <sup>for establishing</sup>\n\na structured training approach that aligns with the updated professional standards,\n\npaving the way for future workforce development and improved <sup>compliance.</sup>\n\n\n**v.** Value for money, performance **&** accountability in staffing for <sup>service</sup> <sup>delivery:</sup>\n\n\nThe achieved reforms were:\n\n\na) The payroll module was automated and successfully <sup>integrated with the Unified Payroll</sup>\n\nNumber **(UPN)** module. This integration is a positive step toward centralizing HR data,\n\nallowing for more efficient data management <sup>and</sup> <sup>streamlined processes.</sup>\n\n\n**b)** Twenty four percent (24%) of the State Corporations <sup>and</sup> <sup>**_50%_**</sup> <sup>of the</sup> <sup>MDAs</sup> <sup>had", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["HR data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000055", "page": 18, "chunk": 0, "title": "Kenya - EASTERN AND SOUTHERN AFRICA - P180287 - Second Program for Strengthening Governance for Enabling Service Delivery and Public Investment in Kenya - Audited Financial Statement", "pdf_url": "https://documents.worldbank.org/curated/en/099010326091535800/pdf/P180287-32a7bd69-90e4-437c-9296-de7df2890c16.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "HR data", "label": "VAGUE_DATA", "score": 0.5752993822097778, "start": 1002, "end": 1009, "probe_score": 0.447, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " reports\ndetailing progress in meeting implementation and development objectives (detailed in the\nprocurement plan and in t h s annex) will be prepared and submitted to IDA. **_An_** evaluation report will\nalso be prepared for the mid-term review and at the close of the program.\n\n\nResponsibility for reporting rests with NEHRU. The results o f the monitoring will be used to analyze and\nimprove program management and to inform subsequent management decisions. The MTR Evaluation\nreport will be used to implement changes in the program design, if necessary.\n\n\nThe data required will be collected through qualitative means such as focus group discussions and\ninterviewing o f key informants. Quantitative data collection will occur through beneficiary surveys and\nthrough the monitoring o f program outputs by the community audits, thrd party technical audit and\ndistrict and divisional secretary technical supervision.\n\n\nForms for monitoring will be designed by NEHRU together with the relevant consultants. Forms will\nappropriately contain, but will not be restricted to, the following data (in addition to that required by the\n**FMR)** :\n\n\n_Benejkiary Selection for Villages, Divisions and Districts_\n\n**_0_** DistrictDivisionNillage\nPercentage damage\nVillage ranlung (for villages)\n\n\n**28**", "output": {"entities": {"named_data": [], "descriptive_data": ["beneficiary surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000115", "page": 32, "chunk": 1, "title": "Sri Lanka - North East Housing Reconstruction Program", "pdf_url": "http://documents1.worldbank.org/curated/en/672131468763807868/pdf/304360LK.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "beneficiary surveys", "label": "DESCRIPTIVE_DATA", "score": 0.9182562828063965, "start": 740, "end": 759, "probe_score": 0.0331, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "## **Introduction**\n\nIn February 2021, the Mixed Migration Centre (MMC)\npartnered with the United Nations High Commissioner\nfor Refugees (UNHCR) to organise a virtual Policy\nWorkshop on Protection Challenges on the Central\nand Western Mediterranean Migration Routes. The\nworkshop brought together a diverse group of 41\nparticipants, including researchers, humanitarian and\ndevelopment programming partners, policy actors and\npeople with a displacement experience from North,\nWest, East and the Horn of Africa as well as Europe\nand North America. Over the course of three days,\nparticipants actively engaged in identifying persistent\nchallenges and gaps and sharing their experiences\nand lessons learned on how to enhance the protection\nof refugees and migrants in mixed movements (also\nreferred to as “people on the move”).\n\n\nDiscussions around humane asylum and migration\npolicies affecting people on the move are as timely as\never. We still witness grave abuses along the various\nmixed movement routes towards the Mediterranean\nCoast. On a daily basis, people intercepted at sea are\nbrought back to Libya, with many ending up in detention\nand in horrific conditions. In July 2020, UNHCR and MMC\nlaunched a joint report, offering compelling evidence on\nthe scale of violations faced by refugees and migrants\nengaged in mixed movement, where these violations\nare happening and who the perpetrators are. <sup>1</sup> [^1: UNHCR and MMC (2020). <u>[‘On this journey, no one cares if you live or die’. Abuse, protection and justice along routes between East and West](https://mixedmigration.org/resource/on-this-journey-no-one-cares-if-you-live-or-die/)</u>\n<u>[Africa and Africa’s Mediterranean Coast.](https://mixedmigration.org/resource/on-this-journey-no-one-cares-if-you-live-or-die/)</u>] Such\nreliable data are needed as a first step towards effective\naction, and more humane and smarter approaches to\nstrengthen protection in mixed movements.\n\n\nThis brief presents the key recommendations arising\nfrom 25 research papers and firsthand", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["reliable data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001515", "page": 2, "chunk": 0, "title": "A Roadmap for Advocacy, Policy Development, and Programming: Protection in Mixed Movements along the Central and Western Mediterranean Routes 2021 [EN/AR]", "pdf_url": "https://reliefweb.int/attachments/ea0f7adb-6164-3733-9637-c1aa18cc6533/MMC-UNHCR-SYNTHESIS-Roadmap-A4-20pp-web.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "reliable data", "label": "VAGUE_DATA", "score": 0.5976870059967041, "start": 1797, "end": 1810, "probe_score": 0.6219, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "00<br>|عدد بطاقات الهوية اللكترونية الصادرة<br>للنساء|\n|15.00<br>|15.00<br>|10.00<br>|0.00<br>|0.00<br>|0.00<br>|نسبة زيادة المعاملت التي يشرع فيها<br>كل مركز لخدمة المواطن في السنة|\n|300.00<br>|300.00<br>|200.00<br>|100.00<br>|50.00<br>|0.00<br>|المواطنون المشاركون في تصميم<br>الخدمات اللكترونية وتقديمها|\n|100.00<br>|100.00<br>|75.00<br>|50.00<br>|10.00<br>|0.00<br>|عدد النساء المشاركات في تصميم<br>الخدمات اللكترونية وتقديمها|\n|20.00<br>|20.00<br>|10.00<br>|0.00<br>|0.00<br>|0.00<br>|حصة اليرادات الضريبية المودعة<br> إلكترونيا|\n|20.00<br>|20.00<br>|10.00<br>|0.00<br>|0.00<br>|0.00<br>|حصة التصريحات", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000140", "page": 33, "chunk": 2, "title": "Djibouti - Public Administration Modernization Project", "pdf_url": "http://documents1.worldbank.org/curated/en/810531524548674826/pdf/PAD2604-ARABIC-PUBLIC-Project-Appraisal-Document-PAD-AR.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Disbursement‐Linked Result<br>(DLR)|Definition of DLI and proof of accomplishment|Protocol to evaluate achievement of the DLRs and data/results<br>verification|Col4|Col5|\n|---|---|---|---|---|\n|**Disbursement‐Linked Result**<br>**(DLR)**|**Definition of DLI and proof of accomplishment**|**Data Source**|**Verification**<br>**Entity**|**Verification Procedure**|\n|management of the education<br>system|||||\n|**DLR#8.2**Approved annual MOE<br>budget reflects an increase of<br>US$134 million for the Program|On an annual basis, MOE updates its expenditure framework<br>and the Ministry of Finance approves the following:<br> <br>Approved MOE 2019 budget reflects the minimum<br>amount of JOD 949,555,000 as indicated in 2017<br>budget law; <br> <br>Approved MOE 2020 budget reflects an increase of a<br>minimum of US$50 million based on the 2019<br>indicative budget (as reflected in the 2017 budget law)<br>of JOD 945", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000041", "page": 48, "chunk": 0, "title": "Jordan - Education Reform Support Program-for-Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/731311512702123714/pdf/Jordan-Educ-Reform-121282-JO-PAD-11142017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "lot of time spent on the document, the time was not wasted because while conducting the\nassessment other ongoing projects could be monitored and a lot more was learned about the refugee\ncommunity.\n\nSince all the work was completed internally, additional budgeting was not necessary. The only extra\nexpenses (tea, coffee, biscuits) were made when organising the workshop and discussion forums.\n\nObstacles Faced\nMuch of the assessment was quite straightforward for UNHCR staff. They were already well aware\nhow to conduct participatory assessments (by previous interaction with refugees); how to monitor\nprograms; run focus group discussions; hold interviews with key people; and make site visits, as these\nwere just a continuation of their daily tasks.\n\nHowever, it was often difficult to find employment data or information on market trends, but due to\nsupport from the ILO, UNDP and World Bank websites, a number of resources were able to be\nobtained. On the other hand, it would have been helpful to have established links with real experts in\nthe field, particularly with those who understand the local context well.\n\nInitially it was a challenge to compile a comprehensive overview of the situation in Jordan because\nthere were already a number of existing programs and resources available. In the future this could\npotentially hinder coordination as information that has already been examined may be omitted, or\npre-existing information may be repeated.\n\nStrategy Follow-up\nThe follow-up actions will be coordinated by a livelihoods working group. The group will consist of all\nNGO actors who are currently involved with refugee livelihoods activities. There will also be a monthly\nmeeting held to discuss updates, lessons learned, and to ensure the smooth transfer of beneficiaries.\n\nUNHCR Jordan will be focusing on protection efforts for the right to work for various groups of\nrefugees. The upcoming participatory assessment (a process of building partnerships with refugees by\npromoting meaningful participation through structured dialogue) will focus on social capital, as staff\nknowledge in this area is limited. A microfinance project will also be developed and implemented as", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["employment data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000323", "page": 3, "chunk": 0, "title": "Developing a livelihoods assessment and strategy - Case study from UNHCR Jordan", "pdf_url": "https://reliefweb.int/attachments/263aa69b-faa0-3889-9c05-f9041a0cafa4/2F7661C28B5274E585257656005BD5F2-Full_Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "employment data", "label": "VAGUE_DATA", "score": 0.7816551923751831, "start": 793, "end": 808, "probe_score": 0.1177, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " sources point to the substantial participation of working-age refugees in informal jobs.\nAlthough most refugees are poor and vulnerable, many can work (around 430,000), but work informally\n(86 percent) for relatively low wages (TL 1,300 [US$220 equivalent] per month on average) (Livelihoods\n\n\n5 The latest official monthly data refer to July 2019.\n\n\nPage 10 of 86", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["monthly data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000025", "page": 14, "chunk": 2, "title": "Turkey - Formal Employment Creation Project", "pdf_url": "http://documents1.worldbank.org/curated/en/211181585965751622/pdf/Turkey-Formal-Employment-Creation-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "monthly data", "label": "VAGUE_DATA", "score": 0.7955541610717773, "start": 317, "end": 329, "probe_score": 0.0857, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "- les taux de mortalité des enfants les plus élevés sont enregistrés dans la région des\nSavanes : 111p 1000 (mortalité infantile) et 186 p 1000 (mortalité infanto-juvénile)\n\n- 13 % enfants n’ont reçu aucune dose des vaccins du PEV.\n\n- 8.2% des ménages ont des toilettes couvertes\n\n- 5.5% des ménages ont accès à l’eau à moins de 30 min de marche\n\nLes cas les plus couramment traités au niveau des CS sont le paludisme, les douleurs\nabdominales et les infections respiratoires- ce qui confirme les dires des populations\nlors des discussions de groupe.\n\nL’évaluation de l’assistance médicale réalisée par le HCR au mois de Juin avait montré\nque toutes les cases de santé ont un registre de consultation et un cahier de suivi du\nstock de médicament remplis régulièrement. La consultation des registres de\nconsultation dans les 3 cases de santé montrait une sur-prescription de la Quinine, du\nParacétamol, des antibiotiques et des injections. Ces médicaments étaient en rupture\nde stock dans 2 cases de santé sur 3, ce qui démontre une certaine sur-utilisation des\nservices. Les capacités limitées et le manque de maitrise de la situation par les\nauxiliaires de santé avaient été constatés.\n\nLa gratuité des soins de santé pour les réfugiés et les autochtones (qui normalement\npaient les consultations, actes et médicaments), contribuait à cette sur-utilisation des\nservices et aux abus de parts", "output": {"entities": {"named_data": [], "descriptive_data": ["registres de\nconsultation"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001429", "page": 11, "chunk": 0, "title": "MISSION D'EVALUATION CONJOINTE-HCR-PAM: Des besoins des Nouveaux Réfugiés Ghanéens au TOGO", "pdf_url": "https://reliefweb.int/attachments/de3a446e-3437-3a7e-9f40-b36bea7eeee3/7C3DB8C9A3A25EA4492578160020FD2E-Rapport_Complet.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "registres de\nconsultation", "label": "DESCRIPTIVE_DATA", "score": 0.7196552753448486, "start": 789, "end": 814, "probe_score": 0.2849, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nmembers were unable to access existing services (compared to 36%\nin household survey), mainly livelihood support (13%), health (12%),\nsupport for persons with special needs, women protection and\npsychosocial support (8 %), education, WASH and rehabilitation for\n\n\n\npersons with disabilities (7%), documentation (6%) and shelter (4%).\nThe most affected groups are female headed-HHs (12%) persons with\ndisabilities, women at risk-HHs, child headed-HHs and elderly person\nheaded-HHs (10% each), persons with life-threatening health issues\n(9%), single male headed-HHs (6%), and unaccompanied and\nseparated children (4%).\n\nThe main reasons for being unable to access these services are being\nunable to pay for the service 21% (compared to 22% in the Q3),\nassistance not being what people need 19% (compared to 14% in Q3)\nassistance not reaching people in need 17% (compared to 16% in Q3),\nfacing discrimination/exclusion (16%), and lacking documentation\n14% (compared to 19% in Q3). While 65% of IDPs reported on\ninability to access available services upon arrival to displacement\nlocation, specifically on health and livelihood services, the barrier for\naccess is indicated as a lack of information on available service and\nrequired documentation to get access. Furthermore, the protection\nmonitoring household data indicated that IDPs plan to integrate to\nthe existing community due to have access to services and\ninfrastructure (9%).\n\n**Social Cohesion**\n\nSimilar to the third quarter of 2021, quantitative data gathered\nthrough HHS and KIIs indicates populations of concern experience\ngenerally positive relationships within communities and between\ndifferent groups. However, FGDs and qualitative findings convey a\nmore complex picture with strains much more evident, particularly in\nEastern provinces of Kandahar and Zabul", "output": {"entities": {"named_data": [], "descriptive_data": ["household survey", "protection\nmonitoring household data"], "vague_data": ["quantitative data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001660", "page": 14, "chunk": 1, "title": "Afghanistan: Protection Analysis Update 2021 - Quarter 4", "pdf_url": "https://reliefweb.int/attachments/ffeb800e-1702-39ba-b790-dae700cb707b/Afghanistan%20-%20Protection%20Analysis%20Update%20-%20Quarter%204.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household survey", "label": "DESCRIPTIVE_DATA", "score": 0.7265274524688721, "start": 69, "end": 85, "probe_score": 0.9972, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "protection\nmonitoring household data", "label": "DESCRIPTIVE_DATA", "score": 0.8817257881164551, "start": 1277, "end": 1313, "probe_score": 0.9494, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "quantitative data", "label": "VAGUE_DATA", "score": 0.6654056906700134, "start": 1494, "end": 1511, "probe_score": 0.9437, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", see World Bank, 2016b).\n\n\nHowever, information which draws particular attention to inequities in input distribution may be\nmore likely to have impact than those which more generally address service quality. Analysis of\nimpact evaluations relating to transparency and citizen engagement in education found that\nproviding information to parents on inputs at school level, along with information on parents’\nrights and responsibilities, was more impactful than providing information on school outcomes\n(Read and Atinc, 2017).\n\n\nEvidence from other developing countries suggests that increasing awareness of PTR disparities\ncan improve distributions: in the Philippines, for example, PTR disparities were reduced between\n2002 and 2004 using a simple, highly public categorization of schools by PTR, with schools with\na PTR of below 24 labeled ‘blue’ and those with a PTR over 50 labeled ‘red’. This publiclyavailable categorization proved highly effective at driving better targeting of teacher allocations\nby giving “marginal schools a voice they previously lacked” (Genito, Roces and Somerset, 2005).\n\n\nPolicy makers and officials within the Government of Malawi and at local level are now aware of\nthe extent of PTR inequities and of the potential for these and other policy innovations to reduce\ninefficient distribution of teachers. The revised remote school allowance scheme is also expected\nto move towards implementation in 2018. In addition, the government has recently entered into an\nagreement with the Global Partnership for Education, a collection of donors, to implement a\nUS$45 million Education Sector Improvement Project. This includes results-based financing\nincentives for improvement in PTR in eight disadvantaged districts, a measure which is expected\n\n\n27", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007211", "page": 28, "chunk": 1, "title": "wps8253", "pdf_url": "https://local/prwp/wps8253.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and/or income rehabilitation. Lack of\nlegal right to the assets lost will not bar the PAP from entitlement to such compensation,\nrehabilitation and relocation measures;\n(d) The rehabilitation measures to be provided are: (i) compensation at full replacement cost for\nhouses and other structures; (ii) compensation for land acquisition; (iii) dislocation allowance and\ntransition subsides; (iv) full compensation for crops, trees and other similar agricultural products at\nmarket value; and (v) other assets, and appropriate rehabilitation measures to compensate for loss of\nlivelihood;\n(e) Land-for-land is the preferred option. Land-for-land may be substituted by cash provided\nthat: (i) land is not available in the proximity of the subproject area; (ii) PAP willingly accept cash\ncompensation for land and all assets on it; and receive full replacement value without any deductions\nfor depreciation; and (iii) cash compensation is accompanied by appropriate rehabilitation measures\nwhich together with project benefits results in restoration of incomes to at least pre-subprojects\nlevels;\n(f) Resettlement plans will be implemented following consultations with the PAPs, and will\nhave the endorsement of the PAPs;\n(g) Any acquisition of, or restriction on access to resources owned or managed by PAP as\ncommon property will be mitigated by arrangements ensuring access of those PAP to equivalent\nresources on a continuing basis.\n\n53. _Valuation Method of Compensation:_ The valuation of losses in physical assets will be carried\nout by a compensation committee. The value of compensation will be determined based on the\nmarket value of the assets, if known, and estimating the replacement cost. Replacement cost is\nsimply calculated as the cost of replacing the lost assets plus any transaction costs associated with\nbrining the asset to pre-displacement value. The valuation of crops will be mainly relied upon the\nprice lists developed by the Agriculture directorate and revisited annually.\n\n\n43", "output": {"entities": {"named_data": [], "descriptive_data": ["price lists developed by the Agriculture directorate"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000003", "page": 53, "chunk": 1, "title": "Lebanon - Municipal Services Emergency Project", "pdf_url": "http://documents.worldbank.org/curated/en/119441469672145615/pdf/PAD10180PAD0P14972400PUBLIC00Box391431B.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "price lists developed by the Agriculture directorate", "label": "DESCRIPTIVE_DATA", "score": 0.677704393863678, "start": 1920, "end": 1972, "probe_score": 0.329, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Project** **Manaeem2nt** <sup>**and**</sup> <sup>million)</sup> administrative data appropriate, and clear in\n\n\n\ndefining the and\n**Innovative Activities**\n\n\n\nresponsibilities of all parties;\nNaCSA retains competent\n**(a) Capacity Building**\n\n\n\nstaff;\n\n                                             - Other governnent and donor\n**(b)** **Information and**\n\nsupport mobilized for\n\n\n\nsupport mobilized for\n**Sensitization**\ndecentralization to\ncomplement NaCSA efforts;\n(c) **Monitoring and**\n\n\n\n**Evaluation**\n\n\n\n**(d)** **Technical Assistance**\n\n\n(e) **Operating** Expenses\n\n\n\n-28", "output": {"entities": {"named_data": [], "descriptive_data": ["administrative data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000096", "page": 32, "chunk": 1, "title": "Guinea - Multi-Sectoral AIDS Project (MAP)", "pdf_url": "http://documents1.worldbank.org/curated/en/570211468749964429/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "administrative data", "label": "DESCRIPTIVE_DATA", "score": 0.6927050352096558, "start": 64, "end": 83, "probe_score": 0.562, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the implementation of the project’s socioeconomic infrastructures through a\ndecentralized PIU to be established in Maroua.\n\n\n83. **Both CPR–FC and PSRDREN will be reinforced with additional staff to facilitate the implementation of the**\n**proposed project.**\n\n\n84. **Implementation coordination and oversight responsibility for the proposed project will be exercised by a joint**\n**coordination and steering committee cochaired by MINTP and MINEPAT.** The steering committee will be\nsupported by a technical monitoring committee in charge of monitoring project activities and the\nimplementation of steering committee decisions. The technical committee will be staffed by qualified technical\nexperts to be chosen for the most part from the line ministries.\n\n\n85. **A collaboration framework agreement will be signed between the MINDEF, MINTP, and MINEPAT for the**\n**protection of works.** This agreement will provide the framework for operations, security, and a code of conduct\nfor the military personnel involved in the provision of security for the road rehabilitation and maintenance works\n(Component 1), and the community infrastructure works (Component 2).\n\n\n**B.** **Results Monitoring and Evaluation Arrangements**\n\n\n86. **Framework for M&E of outcomes and results.** The project will establish a real time and comprehensive M&E\nsystem that will rely on a system of primary and secondary data to monitor project implementation, and assess\nprogress toward achievement of the PDO. This system will help to identify gaps and necessary adjustments for\nthe project’s successful implementation. The M&E system will also support project supervision by ensuring that\nbaseline and follow-up survey data on key performance indicators are available and regularly updated.\n\n\n87. **Use of the geo-enabling initiative for monitoring and supervision (GEMS):** The project will rely on the World\nBank’s GEMS initiative to systematically enhance the M&E system", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000003", "page": 35, "chunk": 1, "title": "Cameroon - Enhancing Connectivity and Resilience in the Far North of Cameroon for Inclusiveness Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099053123163547375/pdf/BOSIB0e7334a5d0570a3e40f8ae4d0c1266.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.5695176720619202, "start": 1692, "end": 1703, "probe_score": 0.044, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and monitoring reports content analysis) and climate adaptation\nstrategies. The component includes support to the Department of Geology in digitalization\nof the registry of wells used for water supply purposes as part of the water cadaster, with\nparticular focus on the Khatlon region. Climate change is expected to lead to diminished\ngroundwater recharge in some areas because of reduced precipitation and decreased\nrunoff. Monitoring data for aquifer water level, changes in chemistry, and detection of\n\n\nPage 24 of 89", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Monitoring data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000162", "page": 27, "chunk": 2, "title": "Tajikistan - Water Supply and Sanitation Investment Project", "pdf_url": "http://documents1.worldbank.org/curated/en/932351655916461178/pdf/Tajikistan-Water-Supply-and-Sanitation-Investment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Monitoring data", "label": "VAGUE_DATA", "score": 0.6874256134033203, "start": 426, "end": 441, "probe_score": 0.0056, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "recent post-conflict period.\n\n\nTable 4: Unit Cost of a 6-Classroom Primary School\nComponents NaCSA (Provincial prices in MOEST (Freetown prices in\nLeones) Leones)\nCost of main building 120,865,000 106,078,530\nCost of hand pump well 7,000,000 9,500,000\nCost of 6-pit latrine 7,500,000 6,500,000\nTotal 135,365,000 122,078,530\n\n\nTo ensure that NaCSA investments are cost-effective, during implementation, a database of unit\ncosts by type of sub-project and by region will be established and updated at least twice a year. In\naddition, international experience suggests that moving to community management of resources leads to\na 25-40% reduction in unit costs of small-scale infrastructure. NaCSA will initiate direct financing of\ncommunities, and the effect on unit costs will be analyzed during implementation. Moreover, in the\nprevious project (ERSF), the actual beneficiaries were difficult to estimate as populations were just\nresettling. Available figures are therefore not reliable during appraisal and implementation. During\nimplementation, NaCSA will maintain more reliable information on cost per beneficiary for each\ncategory of sub-project.\n\n\nAdministrative Efficiency\n\n\nCompared to other govemment's agencies, NaCSA has the reputation of executing projects with\nrelative speed and efficiency in difficult communities. For example, the time lag between request\nsubmission by communities and payment of first tranche can be about 60 days. Also, the staff are\ncapable of delivering training and other services to communities with little international expertise. They\ncan work under pressure and can produce results on time. The series of training activities planned for\n\nstaff under the project will further build their capacities for such activities.\n\n\nHowever, it should be noted that the previous ERSF project had high overhead costs. This was\nbasically due to the fact that a new institution (NCRRR now NaCSA) was", "output": {"entities": {"named_data": [], "descriptive_data": ["database of unit\ncosts"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000050", "page": 40, "chunk": 0, "title": "Albania - Social Services Delivery Project", "pdf_url": "http://documents1.worldbank.org/curated/en/357561468742548905/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "database of unit\ncosts", "label": "DESCRIPTIVE_DATA", "score": 0.916168749332428, "start": 404, "end": 426, "probe_score": 0.1083, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda Secondary Education Expansion Project (P166570)\n\n\nnearest primary school is used for primary enrollment and completion, while the nearest secondary school is used for\nsecondary enrollment and completion.\n\n**Earnings benefits from educational attainment**\n\n3. **There is also clear evidence that higher educational attainment leads to higher earnings in adulthood.** Estimates\nof wage earnings for Uganda using the 2012/13 and 2016/17 UNHS are provided in Table 5.2. Wages are higher\nin 2016/17 than in 2012/13 in part because of inflation between the two years. After accounting for inflation, the\ndata suggest modest gains in real wages between the two surveys. There seems to be a clear wage benefit from\ncompleting lower secondary education versus completing only primary education in terms of average wages. This\nis the case in 2016/17 whether one considers monthly or hourly wages, with a preference for estimates based on\nmonthly wages since a higher level of education may increase the number of hours worked apart from increasing\nproductivity and hourly wages. The gains from lower secondary schools are not very large, but they tend to be\npositive across measures and years.\n\n**<u>Table 5.2: Average Nominal Wage for Wage Earners by Education Level, 2012/13 and 2016/17</u>**\n\n<u>2012/13</u> <u>2016/17</u>\n\n\n\n<u>Monthly</u>\n\n\n\n<u>Hours worked</u>\n\n\n\nper week\n\n\n\n<u>Hourly</u>\n\n\n\nwage\n<u>(USh)</u>\n\n\n\n<u>Monthly</u>\n\n\n\nwage\n<u>(USh)</u>\n\n\n\n<u>Hours worked</u>\n\n\n\nper week\n\n\n\n<u>Hourly</u>\n\n\n\nwage per week wage wage per week wage\n<u>(USh)</u>", "output": {"entities": {"named_data": ["UNHS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 93, "chunk": 0, "title": "Uganda - Secondary Education Expansion Project", "pdf_url": "http://documents.worldbank.org/curated/en/406361595815248191/pdf/Uganda-Secondary-Education-Expansion-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHS", "label": "NAMED_DATA", "score": 0.8744267821311951, "start": 460, "end": 464, "probe_score": 0.9794, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 335,000 hectares that require only modest\ninvestments in infrastructure to become productive. This resource, coupled with the country’s\nagro-ecological diversity, creates huge potential for crop diversification.\n\n\n16. The livestock subsector contributes significantly to the Chadian economy, although its\ncontribution to export revenues is suboptimal owing to the enormous uncontrolled migration of\nherds to markets in Nigeria each year. The dominant herding practices in Chad, affecting 80\npercent of livestock, are transhumance and extensive herding. Cattle herding is the primary\nagricultural activity in the Sahel and a secondary activity in the Sudanian zone, although the\nrelatively greater availability of food, agricultural by-products, and agro-industrial operations in\nthe Sudanian zone attract many herders from the north. In some instances, the herders’\ncoexistence with the agro-pastoralists poses land management problems and can be a source of\nconflict.\n\n\n17. Food security is volatile in Chad because agricultural production systems rely largely on\nrainfall rather than irrigation. Numbers of food-insecure individuals more than triple when\ndroughts deplete harvests and food prices soar. In southern Chad, where most of the refugees and\nreturnees are being settled, agriculture is dominated by small-scale farmers producing a\nmoderate, locally marketed surplus. Cross-border trade with Cameroon and CAR is also\nimportant. While local trade with CAR has been significantly curbed by the conflict, markets in\nthe areas where vouchers are being implemented continue to be well stocked and no unusual\nprice movements have been observed in the past few months since voucher transfers became\noperational. A January 2014 market assessment indicated that food production surpluses were\n\n\n4", "output": {"entities": {"named_data": [], "descriptive_data": ["January 2014 market assessment"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000007", "page": 13, "chunk": 1, "title": "Chad - Emergency Food and Livestock Crisis Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/179061468215115488/pdf/PAD11010PAD0P1010Box385329B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "January 2014 market assessment", "label": "DESCRIPTIVE_DATA", "score": 0.7166662216186523, "start": 1719, "end": 1749, "probe_score": 0.0022, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_Sierra Leone_\n\n\nPRICES and GOVERNMENT FINANCE\n\n1981 1991 2000 2001 Inflation (%)\n_Domest)c_ _pHces_\n_(% change)_ c 1\nConsumer prices 16 7 102 7 -0.9 3 0 30 _< _\nImplicit GDP deflator 8 7 128 8 6 2 6 1 20\n\n_Govemment finance_ _10_\n_(% of GDP,_ _includes curent_ grants) 0\nCurrentrevenue .. 112 182 178 .10. 98 97 93 99 00 01\nCurrent budget balance .. -5 8 -4.5 -7 1 - GDP deflator _ CPI\nOverall surplus/deficit -10 4 -10.6 -12 3\n\n\nTRADE\n\n1981 1991 2000 2001 Export and Import levels (USS mnIll.)\n_(US$ millions)_\nTotal exports (fob) 147 176 75 78 400\nRutile . 72\nDiamonds (recorded) 32 10 21 300\nManufactures\nTotal imports (cHf) 317 158 161 303 20\nFood . 53 66 72 100\nFuel and energy 26 29 3d _ _8_\nCaptal goods .. 38 18 22  - __\n96 D6 97 9o 99 00 01\nExport price index _(1995=100)_ 90 86 87\nImport price Index (1995=100) 93 93 92 mExports ***Mrrports**\nTerms of trade (1995-100) 97 93 94\n\n\n\nBALANCE of PAYMENTS\n\n\n\n1981 1991 2000 2001 Curmnt account balance to GDP _(%)_\n_(US$_ _millions)_\nExports of goods and services 163 244 110 116 0\nImports of goods and services 349 226 212 252\nResource balance -186 18 -102 -137 .a*\n\n\n\nExports of goods and services 163 244 110 116 0\nImports of goods and services 349 226 212 252\nResource balance -186 18 -102 -137 .a*\n\nNet income -28 -60 -18 -20\nNet current", "output": {"entities": {"named_data": [], "descriptive_data": ["Export price index", "Import price Index"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018740", "page": 61, "chunk": 0, "title": "Kenya - AIDS Disaster Response Project (APL)", "pdf_url": "https://documents.worldbank.org/curated/en/824011468773422502/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Export price index", "label": "DESCRIPTIVE_DATA", "score": 0.6043785214424133, "start": 751, "end": 769, "probe_score": 0.209, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Import price Index", "label": "DESCRIPTIVE_DATA", "score": 0.5586132407188416, "start": 792, "end": 810, "probe_score": 0.8072, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 25 kW. The proposal however did not specify the level of the energy\nand fixed charges and left the determination of these prices to state level regulators.\n\nThe paper uses the consumption categories proposed in MOP’s notification to construct the\nfirst counterfactual tariff schedule. To illustrate the welfare impacts of this tariff schedule, we assign\nenergy charges from JVVNL’s 2016-17 tariff order to the consumption tiers in the notification. This\nillustration also uses the consumption tiers of the notification to assign fixed charges instead load\ncategories varying by the sanctioned load. This is because the sanctioned load variable in JVVNL’s data\nset is either missing or noisily estimated, rendering it unusable for fixed cost imputations at the\nhousehold level. Since the range of consumption in each tier of MOP’s notification is larger than the\nrange in JVVNL’s tariff order (for instance, the first tier of consumption in JVVNL’s tariff order ends\nat 50 units, whereas the first tier in MOP’s proposal ends 200 units) for the same energy and fixed\ncharge, one can expect this tariff design to result in higher consumer surpluses across all households\nbut also lead to a revenue shortfall compared to the current tariff.\n\nTo study the welfare impacts of this tariff schedule and all other counterfactual schedules\nthereafter, the following methodology is used. A short-run linear demand curve is calibrated for each\nhousehold using estimates of electricity demand own-price elasticities in the range of -0.1 to -0.4, which\nare consistent with the magnitudes estimated from our structural demand model. The calibrated\nhousehold demand curve passes through the household consumption observed in household level\nbilling data set and the corresponding marginal prices observed in JVVNL’s 2016-17 tariff order. Using\nthis demand curve, consumer surplus at current tariff rates and under counterfactual tariffs can be\ncalculated as the area under the short-run demand curve and above the step-wise marginal price curve,\nless the", "output": {"entities": {"named_data": ["JVVNL’s data\nset"], "descriptive_data": ["household level\nbilling data set"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000020", "page": 16, "chunk": 1, "title": "a household level model of demand for electricity services and welfare analysis of electricity prices in rajasthan", "pdf_url": "https://local/prwp/a-household-level-model-of-demand-for-electricity-services-and-welfare-analysis-of-electricity-prices-in-rajasthan.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "JVVNL’s data\nset", "label": "NAMED_DATA", "score": 0.8450028896331787, "start": 648, "end": 664, "probe_score": 0.8719, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "household level\nbilling data set", "label": "DESCRIPTIVE_DATA", "score": 0.890112578868866, "start": 1711, "end": 1743, "probe_score": 0.4948, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nFormal Employment Creation Project (P171766)\n\n\n      - The establishment of an Emerging Companies Market at Borsa Istanbul where the shares of\nthe SMEs are exclusively traded. Since 2011 SMEs have access to the capital markets via this\nchannel.\n\n      - Angel investment program has been launched in 2013 to encourage angel investment as a\nnew instrument for SMEs at their early stages.\n\n      - Promoting SME financing with the regulations that allows the use of movable assets as\ncollateral.\n\n      - The Portfolio Guarantee System has been included into the scope of Treasury-backed\nguarantee mechanism enabling Credit Guarantee Fund to access more firms and to perform\nmore efficiently.\n\n      - State-backed credit insurance has been launched in order to cover the losses of SMEs.\n\n\n15. **SMEs make more use of internal funds to finance investments and working capital and face**\n**higher collateral requirements than their peers in Eastern Europe and Central Asia.** <sup>13</sup> [^13: Enterprise Surveys (database), International Finance Corporation and World Bank, Washington, DC,\nhttps://www.enterprisesurveys.org/.] The share of SMEs\nin total credit declined by 5 percentage points to slightly more than 20 percent in the aftermath of the\nglobal crisis in 2008–2009 and peaked at 28 percent in mid-2018 following the economic upturn and the\nhighly utilized credit guarantee scheme. However, it declined to 23 percent, in 2019, despite several statefinanced policy stimulus programs. This fluctuation demonstrates how SMEs are among the first and most\naffected frontiers of the financing cycle.\n\n\n16. **SMEs account for most firms in Turkey, but they have been facing difficulties in growing and**\n**expanding.** Firm composition is highly skewed toward microenterprises and small firms. Firms with fewer\nthan 10 employees represent 84 percent of all firms that have employees; yet, they employ only 20\npercent of the workforce. Firms with fewer than 50 employees represent 97 percent of all firms and\nemploy 44 percent of the workforce,", "output": {"entities": {"named_data": ["Enterprise Surveys (database)"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000025", "page": 16, "chunk": 0, "title": "Turkey - Formal Employment Creation Project", "pdf_url": "http://documents1.worldbank.org/curated/en/211181585965751622/pdf/Turkey-Formal-Employment-Creation-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Enterprise Surveys (database)", "label": "NAMED_DATA", "score": 0.8469049334526062, "start": 1012, "end": 1041, "probe_score": 0.0001, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "www.scientificamerican.com/article.cfm?id=ddt-use-to-combat-malaria](http://www.scientificamerican.com/article.cfm?id=ddt-use-to-combat-malaria)</u>\n\n\nCox S, Niskar AS, Narayan KM & Marcus M (2007) Prevalence of self-reported diabetes and exposure to\norganochlorine pesticides among Mexican Americans: Hispanic Health and Nutrition Examination\nSurvey, 1982–1984. Environ Health Perspect, **115** : 1747–1752.\n\n\nDe Jager C, Farias P, Barraza-Villarreal A, Avila MH, Ayotte P, Dewailly E, Dombrowski C, Rousseau F,\nSanchez VD & Bailey JL (2006) Reduced seminal parameters associated with environmental DDT\nexposure and _p_, _p_ ′-DDE concentrations in men in Chiapas, Mexico: a cross-sectional study. J Androl, **27** :\n16–27.\n\n\nDobson, J. E., E. A. Bright, P. R. Coleman, R. C. Durfee, and B. A. Worley (2000). LandScan: a global\npopulation database for estimating populations at risk, Photogram. Eng. Remote Sens. 66, 849–857.\n\n\nEriksson P, Talts U. (2000). Neonatal exposure to neurotoxic pesticides increases adult susceptibility: a\nreview of current findings. Neurotoxicology, **21:** 37-47.\n\n\nEskenazi B, Marks AR, Bradman A, Fenster L, Johnson C, Barr DB & Jewell NP (2006) In utero exposure to\ndichlorodiphenyltrichloroethane (DDT) and dichlorodiphenyldichloroethylene (DDE) and\nneurodevelopment among young Mexican American children. Pediatrics, **118** :", "output": {"entities": {"named_data": ["Hispanic Health and Nutrition Examination\nSurvey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005367", "page": 18, "chunk": 1, "title": "wps6203", "pdf_url": "https://local/prwp/wps6203.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Hispanic Health and Nutrition Examination\nSurvey", "label": "NAMED_DATA", "score": 0.702643632888794, "start": 302, "end": 350, "probe_score": 0.0414, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "## **PROTECTION ANALYSIS UPDATE – Q1 2022**\n\n\n\n<mark>In this regard, rapid assessments conducted by UNHCR covering various population groups</mark>\n<mark>between October – December 2021 showed, major challenges with 67% of households</mark>\n<mark>indicating an inability to work and cover needs and thereby having to resort to various harmful</mark>\n<mark>copies strategies, including selling assets (85%), additional members of the household having</mark>\n<mark>to work (75%), requiring children to work (64%) and accruing debt to cover basic needs (93%).4</mark>\n<mark>The findings from the rapid assessment, when comparing male and female-headed households</mark>\n<mark>amongst IDP and IDP returnee families, are mostly similar although the situation is marginally</mark>\n<mark>worse for female-headed households and more pronounced for IDP returnee households that</mark>\n<mark>are headed by females. On average, 72 percent of male-headed IDP households indicated not</mark>\n<mark>being able to work and cover daily expenses while amongst female-headed households the</mark>\n<mark>number leaped to 81 percent. Similarly, amongst IDP returnee households, the rates are 68%</mark>\nfor MHHs and 76% for FHHs, respectively.\n\n\n<mark>Among respondents who indicated that the security situation had worsened, contributing</mark>\n<mark>factors indicated at the HH level included increased criminality (52%), competition for</mark>\n<mark>resources (34%), and increased protests/civil demonstrations (11%). This shows that the</mark>\n<mark>contributing factors cited for a worsened security situation have changed from the first and</", "output": {"entities": {"named_data": [], "descriptive_data": ["rapid assessments conducted by UNHCR"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000979", "page": 6, "chunk": 0, "title": "Afghanistan: Protection Analysis Update 2022 - Quarter 1", "pdf_url": "https://reliefweb.int/attachments/916826fb-9b1b-4c47-9cf4-d6ed5b7f11ba/protection_analysis_update_pau_-_q1_2022.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "rapid assessments conducted by UNHCR", "label": "DESCRIPTIVE_DATA", "score": 0.7072892189025879, "start": 69, "end": 105, "probe_score": 0.9817, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nKhyber Pakhtunkhwa Human Capital Investment Project (P166309)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|(Cumulative)|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|Health Promotion Grants activities<br>completed|Number of Innovation and<br>Health Promotion Grants<br>completed (Cumulative)|Bi-<br>annually (st<br>arting from<br>the second<br>year)<br>|Progress and<br>Implementati<br>on reports<br>and IMU<br>|Pilot Study/Data<br>collected by IMU during<br>regular monitoring<br>|IMU, PMU, DOH<br>|\n|Campaigns to increase girls participation<br>in education completed<br>|N. campaigns led NGOs or<br>community associations<br>carried out to increase<br>demand for girls ed.|Bi-annually<br>|PMU records<br>|PMU records<br>|PMU<br>|\n\n\n\n\n\nPage 42 of 48", "output": {"entities": {"named_data": [], "descriptive_data": ["PMU records", "PMU records"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000126", "page": 46, "chunk": 0, "title": "Pakistan - Khyber Pakhtunkhwa Human Capital Investment Project", "pdf_url": "http://documents1.worldbank.org/curated/en/730431593223315167/pdf/Pakistan-Khyber-Pakhtunkhwa-Human-Capital-Investment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PMU records", "label": "DESCRIPTIVE_DATA", "score": 0.7751354575157166, "start": 688, "end": 699, "probe_score": 0.9376, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "PMU records", "label": "DESCRIPTIVE_DATA", "score": 0.6987625956535339, "start": 704, "end": 715, "probe_score": 0.0389, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " under terms of reference satisfactory to the Bank. Apart from this, the\nPMU will be entrusted with compiling the annual financial statements and preparing any ad hoc financial\nreports to follow up on the Program financial activities, as necessary.\n\n\n**E.** **Capacity Building and Institutional Strengthening**\n\n\n46. **The World Bank and other development partners are undertaking substantial capacity**\n**building and institutional strengthening efforts in coordination with the PforR.** Some highlights of\nthis support include the following:\n\n\n(a) **Investment climate reform:** (i) Jordan Economic Legislation Reform (ASA financed by the\n\nMiddle East and North Africa Transition Fund), tackling the regulatory reform pillar; (ii)\nDoing Business Reform aiming at improving the business environment in areas measured by\nthe Doing Business report, including reforms on secured lending (collateral registry) that is\nkey to access to finance; and (iii) Inspections Reform (ongoing ASA), aiming at streamlining\nand simplifying the inspection regimes;\n\n\n(b) **Investment Promotion:** Jordan Competitiveness and Investment Promotion and Jordan\n\nInvestment Policy and Promotion projects (also financed by the Middle East and North Africa\nTransition Fund) are supporting the JIC—including relevant functions of the JIC: (i)\n\n\n14", "output": {"entities": {"named_data": ["Doing Business report"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 22, "chunk": 1, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Doing Business report", "label": "NAMED_DATA", "score": 0.6732035279273987, "start": 826, "end": 847, "probe_score": 0.0037, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " est de 69% comparé à 55% pour les hommes.\nLes jeunes et les femmes doivent faire face à de nombreux problèmes de deuxième génération\n(VIH/SIDA, drogue et alcool chez les hommes jeunes, prostitution chez les jeunes femmes). Le manque\nd’accès à l’eau, l’électricité, et le mauvais état des routes et des infrastructures crée des barrières\nphysiques pour l’accès à l’éducation, les services de santé, et les opportunités d’emploi.\n\n**3.** L’éducation et l’analphabétisme présentent de grands défis pour les femmes. Malgré une hausse\ndes taux de scolarisation des filles dans le primaire, ceux-ci sont toujours de 36%, soit un tiers de la\nmoyenne de l’Afrique du Nord et du Moyen Orient, et moins de la moitié de la moyenne de l’Afrique subsaharienne. Le ratio des taux de scolarisation femmes-hommes dans le tertiaire et le secondaire a baissé.\nL’analphabétisme touche 85% des femmes, 52% des plus jeunes (15-24 ans).\n\n**Activités de développement communautaire et programmes du PDSTP**\n\n**4.** Toutes les activités d’alphabétisation, de post-alphabétisation, de soutien à l’artisanat, de collecte\ndes ordures ont été notées comme satisfaisantes selon l’ « état d’avancement, composante B du PSDTP »", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000163", "page": 63, "chunk": 1, "title": "Djibouti - Urban Poverty Reduction Program Project : Djibouti - Projet de Reduction de la Pauvrete Urbaine", "pdf_url": "http://documents1.worldbank.org/curated/en/934951468235146436/pdf/429990PAD0FREN1erni1re0version02008.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "ikoni 64 1,050 1,221 1,336 1,418 1,506\nIsland 21 6,082 7,066 7,732 8,210 8,717\nChangamwe 71 1,598 1,857 2,032 2,157 2,291\nKisauni 126 1.217 1,414 1,547 1,643 1,744\nTotal 282 1,637 11,902 2,082 12,210 2,347\nSource:1989 population census, Vol 1\n\nIn 1989, Kisauni had the largest population followed by Island and Changamwe while Likoni\nhad the least. Both the 1999 Population and Housing Census (Vols 1 & 2) and the Mombasa\nDistrict Development Plan do not show the population figures up to the location level.\n\nHowever, according to the 1999 census, Changamwe division had a population of 173,930\npeople with 53,012 households. According to the chief of Chaani location the Population of\nChaani location in Changamwe division was 44,945 in the year 1999. (Source: Chief, Chaani\nLocation).\n\n\nFINAL KenGen ckm edit 7-12\nIssue 2.0 / February 2004", "output": {"entities": {"named_data": ["1989 population census", "1999 Population and Housing Census"], "descriptive_data": ["1999 census"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017108", "page": 36, "chunk": 2, "title": "Kenya - Energy Sector Recovery Project : environmental assessment (Vol. 2 of 2) : EIA for the conversion of Kipevu open cycle gas turbine to combined cycle operation", "pdf_url": "https://documents.worldbank.org/curated/en/714501468753323174/pdf/e8990vol-02.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1989 population census", "label": "NAMED_DATA", "score": 0.7680255770683289, "start": 213, "end": 235, "probe_score": 0.9623, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "1999 Population and Housing Census", "label": "NAMED_DATA", "score": 0.8607403039932251, "start": 358, "end": 392, "probe_score": 0.9947, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "1999 census", "label": "DESCRIPTIVE_DATA", "score": 0.5626162886619568, "start": 536, "end": 547, "probe_score": 0.9965, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nKenya Water, Sanitation, and Hygiene Program (P179012)\n\n\n**Monitoring & Evaluation Plan: PDO Indicators by PDO Outcomes**\n\n|Increased sustainable access to improved water services for rural households in selected counties|Col2|\n|---|---|\n|**People provided with sustainable access to improved climate resilient water services under the Program (Number) **|**People provided with sustainable access to improved climate resilient water services under the Program (Number) **|\n|Description|This indicator measures the cumulative number of people who access to water from an improved and climate resilient<br>water source that have been constructed through the Program.|\n|Frequency|Annual measurement|\n|Data source|County Government Water department M&E records|\n|Methodology for Data<br>Collection|Qualitative inspections and quantitative data collection using M&E protocols defined in the POM|\n|Responsibility for Data<br>Collection|County Government Water Department|\n|**Increased sustainable access to improved sanitation services and elimination of open defecation**|**Increased sustainable access to improved sanitation services and elimination of open defecation**|\n|**Villages that achieve and sustain open defecation free (ODF) status (Number) **|**Villages that achieve and sustain open defecation free (ODF) status (Number) **|\n|Description|ODF status requires (a) no exposed human excreta within the community/households, (b) all households have access<br>to a toilet (individual or shared), and (c) all households have a handwashing facility near the latrine with soap/ash and<br>water.|\n|Frequency|Annual measurement|\n|Data source|County Government, MoH M&E records|\n|Methodology for Data<br>Collection", "output": {"entities": {"named_data": ["County Government Water department M&E records"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000190", "page": 46, "chunk": 0, "title": "Kenya - Water, Sanitation, and Hygiene Program", "pdf_url": "https://documents1.worldbank.org/curated/en/099120123140034670/pdf/BOSIB-9a6accb6-73d1-4bd1-8307-d41a339a51ab.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "County Government Water department M&E records", "label": "NAMED_DATA", "score": 0.5914576649665833, "start": 730, "end": 776, "probe_score": 0.9574, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_Figure 1-Number of Ukrainian Refugees students in the Italian school system across grades and academic years_\n\n_(Source: MoE, academic years 2021-22 to 2023-24)_\n\n\n\n\n\n\n\n**INVALSI data.** INVALSI is a national institute that monitors the performance of the Italian school\nsystem and administers national standardized testing. Students are tested in Italian, Mathematics and\nEnglish in their 2nd, 5th, 8th, 10th, and 13th years of school. <sup>12</sup> The dataset used for this study includes\ntest scores from Grades 8, 10 and 13. Along with test scores across the three subjects, the INVALSI\ndataset contains key individual-level characteristics, including gender, age and origin, background\ninformation on parental education and employment status, as well as the availability of learning\ndevices. Table 2 presents the number of participants at INVALSI tests for each category of students.\n\nA close look at the numbers in Tables 1 and 2 suggests that the share of Ukrainian refugee students\n\n\n\ndevices. Table 2 presents the number of participants at INVALSI tests for each category of students.\n\nA close look at the numbers in Tables 1 and 2 suggests that the share of Ukrainian refugee students\ntested through INVALSI in 2022-23 was 88% in grade 8, 58% in grade 10 and 53% in grade 13. These\nrates are comparable to those of newly arrived foreigners but remain signi�icantly lower than the\nparticipation rates of other students. While INVALSI participation generally declines in higher grades\nacross all groups, the disparity is more pronounced among Ukrainian refugees and newly arrived\n\n_Table 2- Number of participants at INVALSI tests by group and grade (Source: INVALSI, a.y. 2022-23)_\n\n<u>foreigners.</u>\n\n\n\n_Table 2- Number of participants at INVALSI tests by group and", "output": {"entities": {"named_data": ["INVALSI data", "INVALSI\ndataset"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001389", "page": 9, "chunk": 0, "title": "idu1780fb6571d73b14abb19c0710a41787d61dd", "pdf_url": "https://local/prwp/idu1780fb6571d73b14abb19c0710a41787d61dd.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "INVALSI data", "label": "NAMED_DATA", "score": 0.73453688621521, "start": 172, "end": 184, "probe_score": 0.9948, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "INVALSI\ndataset", "label": "NAMED_DATA", "score": 0.703765869140625, "start": 585, "end": 600, "probe_score": 0.9937, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|\n|Cumulati<br>ve|7.00|17.00|32.00|32.00|32.00|32.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|0.00|\n|**Institutional Data**|**Institutional Data**|**Institutional Data**|**Institutional Data**|**Institutional Data**|**Institutional Data**|**Institutional Data**|**Institutional Data**|**Institutional Data**|**Institutional Data**|**Institutional Data**|**Institutional Data**|**Institutional Data**|**Institutional Data**|**Institutional Data**|**Institutional Data**|**Institutional Data**|\n|**Practice Area (Lead)**|**Practice Area (Lead)**|**Practice Area (Lead)**|**Practice Area (Lead)**|**Practice Area (Lead)**|**Practice Area (Lead)**|**Practice Area (Lead)**|**Practice Area (Lead)**|**Practice Area (Lead)**|**Practice Area (Lead)**|**Practice Area (Lead)**|**Practice Area (Lead)**|**Practice Area (Lead", "output": {"entities": {"named_data": [], "descriptive_data": ["Institutional Data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000030", "page": 5, "chunk": 2, "title": "Lebanon - Emergency Education System Stabilization Project", "pdf_url": "http://documents.worldbank.org/curated/en/578481467991017996/pdf/PAD1190-PAD-P152848-PUBLIC-Box391435B-LB-EESSP-Final-PAD-for-printing.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Institutional Data", "label": "DESCRIPTIVE_DATA", "score": 0.5228521823883057, "start": 165, "end": 183, "probe_score": 0.1218, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " to disease and undernutrition, represented nearly 1 in 5 refugees. Older\nchild refugees were at risk of not having their\neducational needs met. Women made up 63 per cent\nof the refugee adult population and working age men\n(aged 18 to 59) were a small minority of the entire\nrefugee population.\n\n\nThis refugee crisis is overwhelmingly rural in nature,\nwith 91 per cent of refugees from South Sudan living\nin rural locations in countries of asylum.\n\n\n**CONFLICT DEEPENING**\n\n\nUnfortunately there was little evidence of a resolution\nto the conflict in 2016 and UN reports warned of\nlooming food insecurity for 5.5 million people –\n\n\n\n**32** **UNHCR >** **GLOBAL TRENDS 2016**", "output": {"entities": {"named_data": ["GLOBAL TRENDS 2016"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000712", "page": 31, "chunk": 1, "title": "Global Trends: Forced Displacement in 2016", "pdf_url": "https://reliefweb.int/attachments/68295936-5f9b-382c-8466-3e660ac587d3/5943e8a34.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "GLOBAL TRENDS 2016", "label": "NAMED_DATA", "score": 0.6207899451255798, "start": 653, "end": 671, "probe_score": 0.0046, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "CP (Child Protection)\nSectoral Impact and Needs Analysis\nSectoral  Priority Response  and Recovery\nLife Saving Activities (Up to Maximum Five Months)\n•\nUndertake activities to document and trace the children who are unaccompanied or separated from \nfamily and /or living on the street\n•\nSocial Workers need to be deployed to identify and address risks and barriers that prevent children \nwith disabilities from accessing goods, services, spaces and information equally\n•\nProvision for Cash and/or voucher assistance as immediate support needs to be undertaken to help \nfamilies provide for their children’s needs and prevent exploitation or school dropout.\nEarly Recovery Activities (Up to Nine Months)\n•\nRecruit and train 128 Social Workers (01 SW will cover 05 affected unions) for conducting Child \nProtection related activities related to identification and support until the protection risks of affected \nchildren are fully addressed\n•\nDeploy adequate number of Social Workers for conducting Case management especially for \nunaccompanied, separated, street-based, survivors of sexual violence, intellectual/physically disable \nchildren\n•\nImplement activities for alternative care for the children who are not with family/caregiver\n•\nPlan and implement activities for preventing trafficking by supporting family and community for \nchildren. \n•\nPrevention works need to be implemented to reduce or eliminate risk of abuse, neglect, exploitation \nand violence following ethical considerations and considering knowledge gaps \n•\nThough GoB assured safety of children in 13 districts, we still need to plan activities which involve \nSocial Worker/case workers’ for addressing Child protection perspective in all the districts.\nAs per the primary data, total 3.3 million people are affected by the monsoon flood, and 40% (11.68 lac) of\nthem should be estimated as children. However, collected data shows 14 Lac children are affected of which\nat least 7.5 Lac are girls. It is anticipated that many of the affected children are likely to fall under different\ntypes of child protection risks and problems such as family separation, Becoming homeless, economic\nexploitation, drowning / injury / death, physical or sexual", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["primary data", "collected data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001664", "page": 28, "chunk": 0, "title": "Impact of the monsoon & COVID-19 containment measures: Shelter and infrastructure damage in the Rohingya refugee camps | Flash report – 20 August 2020", "pdf_url": "https://reliefweb.int/sites/reliefweb.int/files/resources/nawg_monsoon_flood_preliminary_impact_and_kin_20200725_final_draft.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "primary data", "label": "VAGUE_DATA", "score": 0.7586601972579956, "start": 1737, "end": 1749, "probe_score": 0.0023, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "collected data", "label": "VAGUE_DATA", "score": 0.6749191284179688, "start": 1881, "end": 1895, "probe_score": 0.0009, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "UNHCR ETHIOPIA **PROTECTION BRIEF |** AUGUST 2024\n# **Gender-Based** **Violence in the** **Sudan Refugee** **Response – Ethiopia**\n\n\n\nThis August 2024 protection brief\nanalyzes gender-based violence (GBV) as\nfaced by refugees fleeing the Sudan\nsituation into Ethiopia. The brief is\nintended to be actionable and to take\nstock of the effectiveness of the current\nGBV interventions that include a\ncoordinated approach prioritizing timely\naccess to appropriate psychosocial,\nmedical, safety and legal services. It will\nalso provide recommendations for areas\nwhere immediate improvement is\nneeded. Relevant UNHCR guidance on\nbest practices is used as a benchmark.\nInterventions in (1) coordination and\nresponse (2) prevention (3) risk mitigation\nare considered.\n\nThe situation of both new arrivals and\npersons who arrived before April 2023 is\n\n\n\nconsidered. The brief covers the\nresponse in the Amhara and Benishangul\nGumuz regions, and also looks at some\nactivities in Gambella and Addis Ababa.\n\nFurthermore, the brief provides\ninformation on the funding constrains that\nrequire immediate attention from donors\nand partners. Based on the gaps\nidentified below, the overall\nrecommendation is that the **GBV**\n**response interventions in the Amhara**\n**and Benishangul Gumuz regions must**\n**be immediately expanded** . The current\nresponse capacity which survivors can\naccess is not sufficient. While UNHCR\nhas an important role to play, other actors\nalso need to strengthen their\ninterventions.\n\n\n1", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000939", "page": 0, "chunk": 0, "title": "UNHCR Ethiopia: Gender-Based Violence in the Sudan Refugee Response –Protection Brief | August 2024", "pdf_url": "https://reliefweb.int/attachments/8bee8cf4-6df6-4ed7-a325-1ab78e15a818/UNHCR%20Ethiopia%20-%20Protection%20Brief%20on%20GBV%20-%20Final%20-%20August%202024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["M&E data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000138", "page": 29, "chunk": 2, "title": "Burundi - Multisectoral HIV/AIDS Control and Orphans Project", "pdf_url": "http://documents1.worldbank.org/curated/en/805311468769526269/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "M&E data", "label": "VAGUE_DATA", "score": 0.5883201956748962, "start": 530, "end": 538, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " men and women highlighted\nthat access to quality education was the most prevalent issue facing refugee women and girls. Impediments\nto primary, secondary and tertiary level schooling for both refugee and Pakistani girls include a lack of\nqualified female teachers (particularly at higher grades); school facilities that do not meet sociocultural and\nreligious expectations; long distances and lack of transport; safety concerns and sociocultural practices\n[such as early marriages (see UNHCR publication Mapping of Education Facilities and Refugee Enrolment](https://reliefweb.int/sites/reliefweb.int/files/resources/document_42.pdf)\n<u>[in Main Refugee Hosting Areas and Refugee Villages in Pakistan (2018)).](https://reliefweb.int/sites/reliefweb.int/files/resources/document_42.pdf)</u>\n\n\nSignificant numbers of refugee children also enter the informal labour market at a young age.\n\n\n8 R E F U G E E P O L I C Y R E V I E W F R A M E W O R K - C O U N T R Y S U M M A R Y > **PA K I S TA N**", "output": {"entities": {"named_data": ["Mapping of Education Facilities and Refugee Enrolment"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000581", "page": 7, "chunk": 2, "title": "Pakistan: Refugee Policy Review Framework Country Summary as at 30 June 2020 (March 2022)", "pdf_url": "https://reliefweb.int/attachments/560b3d37-8ae8-3e97-82a2-de06cb83559d/Pakistan%20-%20Refugee%20Policy%20Review.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Mapping of Education Facilities and Refugee Enrolment", "label": "NAMED_DATA", "score": 0.5367791652679443, "start": 505, "end": 558, "probe_score": 0.0687, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "ographic data will<br>be monitored in<br>through the progress<br>reports<br>|Project Management<br>Team/UN-Habitat<br>|\n|Rental contracts signed for rehabilitated<br>units|Number of rental contracts<br>signed for units that have<br>been rehabilitated under<br>subcomponent 1.1. for<br>socio-economic vulnerable<br>renters|Annual<br>|Progress<br>Reports. Mon<br>itoring and<br>Evaluation<br>Reports.<br>|The progress report will <br>monitor the number of<br>rehabilitated apartment<br>units with preferable<br>rental contracts for<br>tenants of buildings<br>rehabilitated under<br>component 1.1.<br>|Project Management<br>Team/UN-Habitat<br>|\n|Of which, are signed with renters|Number of rental contracts|Annual|Progress|The progress report will|Project Management|\n\n\nPage 37 of 66", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["ographic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000034", "page": 42, "chunk": 1, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents1.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "ographic data", "label": "VAGUE_DATA", "score": 0.6607747673988342, "start": 0, "end": 13, "probe_score": 0.033, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "% 30% 40% 50% 60% 70% 80% 90% 100%\n\n\n**Chile**\n\n\n\n**Ecuador**\n\n\n\n2.2%\n\n\n\n0.6%\n\n\nEconomic reasons Family reasons Violence/security Lack of services Others\n\n\nSources: Authors, based on the following surveys. Chile: Encuesta de Migración (World Bank, SERMIG, and Centro UC 2022). Ecuador: Encuesta a Personas en\nMovilidad Humana y en Comunidades Receptoras en Ecuador (INEC 2019).\n\n\nNote: For a list of specific reasons see appendix B\n\n\n11 This survey was administered in Venezuela in 2022 by Universidad Católica Andrés Bello. It is one of the few sources of information on the socioeconomic\nconditions of the population.", "output": {"entities": {"named_data": ["Encuesta de Migración"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001190", "page": 24, "chunk": 1, "title": "Venezuelans in Chile, Colombia, Ecuador and Peru: A Development Opportunity", "pdf_url": "https://reliefweb.int/attachments/b6b504c8-f3b2-4e0d-a2e0-3955b4beb78c/P17578013f69d804019f8516ffbb072fc34.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Encuesta de Migración", "label": "NAMED_DATA", "score": 0.9472639560699463, "start": 213, "end": 234, "probe_score": 0.9966, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Figure A4:** Infant Mortality Rate in 2015<br>_Source:_ Authors’ analysis using data from CIESIN (2018).<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|||||||||||||||||||||||||||||||||||||||||||||||||||||||||\n|**Figure A4:** Infant Mortality Rate in 2015<br>_Source:_ Authors’ analysis using data from CIESIN (2018).<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|**Figure A4:** Infant Mortality Rate in 2015<br>_Source:_ Authors’ analysis using data from CIESIN (2018).<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|**Figure A4:** Infant Mortality Rate in 2015<br>_Source:_ Authors’ analysis using data from CIESIN (2018).<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|**Figure A4:** Infant Mortality Rate in 2015<br>_Source:_ Authors’ analysis using data from CIESIN (2018).<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|**Figure A4:** Infant Mortality Rate in 2015<br>_Source:_ Authors’ analysis using data from CIESIN (2018).<br>_he", "output": {"entities": {"named_data": ["data from CIESIN"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000171", "page": 51, "chunk": 333, "title": "climate anomalies and international migration a disaggregated analysis for west africa", "pdf_url": "https://local/prwp/climate-anomalies-and-international-migration-a-disaggregated-analysis-for-west-africa.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from CIESIN", "label": "NAMED_DATA", "score": 0.6016932725906372, "start": 82, "end": 98, "probe_score": 0.9844, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 15. Ukrainian refugees wages median net wage by age group**\n\n\nMonthly net wage (PLN) Percengate of all workers total economy average\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 16. Median net wages of Ukrainian refugees median net wage by sector**\n\n\nin PLN Percentage of total economy average\n\n\n\n126%\n\n\n\n\n\n\n\n\n\n\n\n15 to 24 25 to 34 35 to 44 45 to 54 55 to 64 15 to 24 25 to 34 35 to 44 45 to 54 55 to 64\n\n\nUkrainian refugees All workers\n\n\nSource: Deloitte own elaboration based on SEIS UNHCR survey and GUS data.\n\n\n\n**The Ukrainian refugee groups to earn**\n**the highest wages compared to the**\n**wages in the economy as a whole are**\n**the younger age groups.** Ukrainian\nrefugee incomes from employment are\nhighest in the 25–34 and 35–44 age\ngroups. However, relative to the economy\nas a whole, the wages of Ukrainian\nrefugees are the highest in the youngest\nage groups and decrease with age. This\ncan be explained by three facts. First,\nwages in the youngest age groups are\nmost compressed, because they diverge\nwith time and accumulated professional\nexperience. Second, younger persons have\nless experience and so lose least from\nmigration. Third, younger persons often\nfind it easier to learn the language of the\nhost country.\n\n\n\n**The earnings of Ukrainian refugees**\n**differ across sectors in nominal**\n**terms and as a percentage of the**\n**economy as a whole – only education**\n**ranked lowest on both measures.**\nUkrainian refugees earn the highest\nwages in manufacturing, health, and\naccommodation and food service activities,\nwhile the lowest in education, other\nservices, and construction. A comparison\nto median earnings in these sectors in the\neconomy as a whole (after re", "output": {"entities": {"named_data": ["SEIS UNHCR survey", "GUS data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 10, "chunk": 0, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS UNHCR survey", "label": "NAMED_DATA", "score": 0.8987571001052856, "start": 604, "end": 621, "probe_score": 0.9906, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "GUS data", "label": "NAMED_DATA", "score": 0.8474438190460205, "start": 626, "end": 634, "probe_score": 0.9429, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "………………….6\n\n\nFigure 4. Types of GBV reported in the South Sudan GBV IMS, per quarter, 2015…………………………………8\n\n\nFigure 5. Incidents of grave violations reported to the MRM per State, per quarter, 2015………………….9\n\n\nFigure 6. Hazardous Areas cleared and devices destroyed, January 2014-September 2015……………....19\n\n\nTable 1. Number of Incidents of grave violations reported to the MRM, per quarter, 2015………………..10\n\n\nTable 2. Official estimated number of IDPs living in UNMISS POC sites, per quarter, 2015………………….11\n\n\nii", "output": {"entities": {"named_data": ["GBV IMS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000601", "page": 1, "chunk": 6, "title": "Protection Trends South Sudan No 6 | July-September 2015 - South Sudan Protection Cluster, November 2015", "pdf_url": "https://reliefweb.int/attachments/589205c5-62ff-3033-8221-c68e4b07017a/protection_trends_paper_no_6_jul-sep_2015_final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "GBV IMS", "label": "NAMED_DATA", "score": 0.5122778415679932, "start": 63, "end": 70, "probe_score": 0.132, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "capital, the country faces large inequality of opportunities and outcomes among its citizens. <sup>5</sup> [^5: Lebanon’s inequality-adjusted HDI is 20.8 percent lower than its HDI, among the largest losses in the group of\ncountries in the high human development category.]\nInequality in Lebanon is particularly stark in income and in education, and less pronounced in\nhealth. This inequality is linked to the weakness of the state in delivering high quality public\nservices, a difficulty that is compounded in poorer regions of the country. With low rates of\nreturn on skilled human capital at home, Lebanon is facing severe difficulties in retaining talent:\nthe emigration rate of the tertiary educated reached 43.9 percent. <sup>6</sup> [^6: World Economic Forum’s 2013 Human Capital Index] Inequality is also undermining\nLebanon’s poverty reduction and social and economic inclusion efforts as social/economic\nmobility is difficult for individuals born into low skilled households. The Syrian crisis and the\nassociated large influx of refugees have severely stressed the quality of public services in\nLebanon, especially those related to human capital (Economic and Social Impact Assessment of\nthe Syrian Conflict, World Bank 2013).\n\n\n9. Education in Lebanon is characterized by a multitude of parallel systems which together\nenroll a majority of children of school age. Overall, 516,627 students were enrolled in private\nschools, representing 52.9 percent of all students in the 2012-13 school year. The public sector\nenrolled 299,245 students or 30.7 percent, another 13.1 percent were in publically subsidized\nprivate schools and 3.3 percent of students were in United Nations Relief and Works Agency for\nPalestine Refugees in the Near East (UNRWA) schools in school year 2012-13. Investments by\nthe public sector include both free public schooling as well as subsidies to a group of private\nschools that are generally considered to perform as poorly or even below the level of public\nschools. <sup>7</", "output": {"entities": {"named_data": ["2013 Human Capital Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000030", "page": 11, "chunk": 0, "title": "Lebanon - Emergency Education System Stabilization Project", "pdf_url": "http://documents.worldbank.org/curated/en/578481467991017996/pdf/PAD1190-PAD-P152848-PUBLIC-Box391435B-LB-EESSP-Final-PAD-for-printing.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2013 Human Capital Index", "label": "NAMED_DATA", "score": 0.8394094109535217, "start": 768, "end": 792, "probe_score": 0.9992, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank** Implementation Status & Results Report\nEthiopia General Education Quality Improvement Program for Equity (P163050)\n\n\n<u>Baseline</u> <u>Actual (Previous)</u> <u>Actual (Current)</u> <u>End Target</u>\n\n\nValue N -- N Y\n\n\nDate 07-Jul-2016 -- 22-Mar-2018 07-Jul-2022\n\n\n\n\n\n\n\n\n\n\n\n\n\n**Disbursement Linked Indicators**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n4/9/2018 Page 11 of 13", "output": {"entities": {"named_data": ["Disbursement Linked Indicators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015414", "page": 10, "chunk": 0, "title": "Disclosable Version of the ISR - Ethiopia General Education Quality Improvement Program for Equity - P163050 - Sequence No : 01", "pdf_url": "https://documents.worldbank.org/curated/en/603181523329981924/pdf/Disclosable-Version-of-the-ISR-Ethiopia-General-Education-Quality-Improvement-Program-for-Equity-P163050-Sequence-No-01.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Disbursement Linked Indicators", "label": "NAMED_DATA", "score": 0.8020687699317932, "start": 297, "end": 327, "probe_score": 0.7971, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\ntransport systems summarized by generalized transport costs to reach the CBD for each mode at the grid\ncell level, land use including areas that cannot be built, housing regulations such as FARs, construction\ncosts, households and developers’ behavior, the NEDUM-2D model can reproduce the structure of Buenos\n\n\n4 Some of the following paragraphs in section 3.1 describing the NEDUM-2D model appear in a similar form in Avner\net al. (2017). For the purposes of making this paper self-standing, it was deemed important to include them here as\nwell.\n5 This mono-centric hypothesis is a clear simplification but that finds some support in the data for the specific case\nof Buenos Aires, the Buenos Aires region displays a strong mono-centric structure. For instance, in 2012 more than\n40% of all jobs in the Buenos Aires region are localized in the _Ciudad Autónoma de Buenos Aires_ (CABA) even though\nCABA only represents 5.3% of _Region Metropolitana_ ’s area.\n6 For a version of NEDUM-2D that represents multiple job centers and household types differing by annual average\nincome and work location see Pfeiffer et al. (2019).\n\n\n12", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data for the specific case\nof Buenos Aires"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000444", "page": 13, "chunk": 2, "title": "flood protection and land value creation not all resilience investments are created equal", "pdf_url": "https://local/prwp/flood-protection-and-land-value-creation-not-all-resilience-investments-are-created-equal.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data for the specific case\nof Buenos Aires", "label": "VAGUE_DATA", "score": 0.5061139464378357, "start": 641, "end": 683, "probe_score": 0.9571, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " devices\nand after-sales service. Finding local solutions will ensure availability of technical expertise, including ease\nof availing service and parts which fall under warranty, and positive environmental outcomes by reduced\ntransport-related carbon emissions.\n\n\nCost estimates per unit cookstoves and fuel supplies amounts should be based on up-to-date market\ncosts information from the country or international price lists in case of international procurement.\nThis approach will provide quantities during the tendering process to cover the highest number of\nhouseholds for the longest time within the available budget.\n\n\nTechnical specifications of cooking fuels should follow international standards in terms of chemical contents\n(e.g., Sulphur for LPG), fuel quality and fuel certifications. Transport, distribution, storage, and handling of cooking\nfuels should follow the highest environmental health and safety standards (both national and international)\nto preserve the health of the beneficiaries and surrounding communities. Training and capacity building of\nrefugees and IDPs on cookstove and fuel use and refill handling shall be included in the request for proposal.\n\n\nAll cooking solutions should include provision for testing and inspecting components, products, and services\nbefore, during, and after the delivery to ensure compliance with the specifications and designs. This should\nbe taken into consideration during the contractual agreement preparation.\n\n\nAs stoves differ greatly in technical performance, testing is necessary to identify clean stoves and\ncompare different models. Stoves technical performance is verified through internationally agreed test\nprotocols. Emissions and fuel use must be tested at the same time to avoid running a test to achieve\ngood fuel economy at the expense of emissions and vice versa. The need for guidance in stove\nselection has led to the development of ISO/TC 285, an international standard which rates stoves\n[based on the criteria of durability, safety, fuel-efficiency, and cleanliness. Stove & fuel technical tests.](https://energypedia.info/wiki/Testing_of_Woodfuel_Stoves)\n\n\n\n22", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["market\ncosts information"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001524", "page": 21, "chunk": 1, "title": "Compendium: Protection-Sensitive Access to Clean Cooking - October 2021", "pdf_url": "https://reliefweb.int/attachments/ec39c21c-4536-32dc-88b4-854469ff945c/61af71194.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "market\ncosts information", "label": "VAGUE_DATA", "score": 0.6643717885017395, "start": 355, "end": 379, "probe_score": 0.0034, "gold": "DATA_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nLebanon Health Resilience Project (P163476)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPage 4 of 54", "output": {"entities": {"named_data": ["Lebanon Health Resilience Project"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000108", "page": 6, "chunk": 0, "title": "Lebanon - Health Resilience Project", "pdf_url": "http://documents1.worldbank.org/curated/en/616901498701694043/pdf/Lebanon-Health-PAD-PAD2358-06152017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Lebanon Health Resilience Project", "label": "NAMED_DATA", "score": 0.5618278384208679, "start": 19, "end": 52, "probe_score": 0.0303, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "nés\nauraient été enlevés dans leurs champs, près du village de Marangara,\npar des éléments d’un groupe armé. Ces victimes auraient été assimilées\nà des éléments du groupe armé rival et auraient été emmenées dans un\ncampement d’un groupe armé à Butare.\n\n\nEn outre, le 20 octobre, 9 civils retournés soupçonnés de liens avec des\ngroupes armés rivaux, dont un enfant de 16 ans, auraient été tués à la\nmachette par des éléments de ce groupe dans le village de Kishishe,\ndans le groupement de Bambu.\n\n\n- Il a été noté en septembre qu’un groupe armé **recruterait des enfants**\n**pour percevoir des taxes illégales** aux barrières dans le nord-ouest du\nterritoire. Le 6 septembre, trois enfants âgés de 14 à 16 ans auraient été\nrecrutés par ce groupe armé au village de Butare, dans le groupement\nde Tongo, et positionnés à deux barrières pour collecter ces taxes.\n\n\n\nSi vous avez des commentaires, questions, ou données supplémentaires, veuillez contacter :\n[Steve Ndikumwenayo (ndikumwe@unhcr.org) ou Lorraine de Limelette (lorraine.delimelette@nrc.no)](mailto:ndikumwe@unhcr.org) 7", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001485", "page": 6, "chunk": 3, "title": "République démocratique du Congo | Points Saillants de Protection | septembre et octobre 2024", "pdf_url": "https://reliefweb.int/attachments/e70a650c-41d1-4fb6-a92d-5ae499629187/points_saillants_situation_de_protection_en_rd_congo_sepoct_2024_fin.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|PAD DATA SHEET|Col2|Col3|Col4|Col5|Col6|Col7|\n|---|---|---|---|---|---|---|\n|_Lebanon_|_Lebanon_|_Lebanon_|_Lebanon_|_Lebanon_|_Lebanon_|_Lebanon_|\n|_Emergency Education System Stabilization (P152898)_|_Emergency Education System Stabilization (P152898)_|_Emergency Education System Stabilization (P152898)_|_Emergency Education System Stabilization (P152898)_|_Emergency Education System Stabilization (P152898)_|_Emergency Education System Stabilization (P152898)_|_Emergency Education System Stabilization (P152898)_|\n|**PROJECT APPRAISAL DOCUMENT**|**PROJECT APPRAISAL DOCUMENT**|**PROJECT APPRAISAL DOCUMENT**|**PROJECT APPRAISAL DOCUMENT**|**PROJECT APPRAISAL DOCUMENT**|**PROJECT APPRAISAL DOCUMENT**|**PROJECT APPRAISAL DOCUMENT**|\n|_MIDDLE EAST AND NORTH AFRICA_|_MIDDLE EAST AND NORTH AFRICA_|_MIDDLE EAST AND NORTH AFRICA_|_MIDDLE EAST AND NORTH AFRICA_|_MIDDLE EAST AND NORTH AFRICA_|_MIDDLE EAST AND NORTH AFRICA_|_MIDDLE EAST AND NORTH AFRICA_|\n|Report No.: PAD1190|Report No.: PAD1190|Report No.: PAD1190|Report No.: PAD1190|Report No.: PAD1190|Report No.: PAD1190|Report No.: PAD1190|\n|**Basic Information", "output": {"entities": {"named_data": ["PAD DATA SHEET"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000030", "page": 4, "chunk": 0, "title": "Lebanon - Emergency Education System Stabilization Project", "pdf_url": "http://documents.worldbank.org/curated/en/578481467991017996/pdf/PAD1190-PAD-P152848-PUBLIC-Box391435B-LB-EESSP-Final-PAD-for-printing.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PAD DATA SHEET", "label": "NAMED_DATA", "score": 0.5337613224983215, "start": 1, "end": 15, "probe_score": 0.1531, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "99 data may be due to sampling issues and/or lower level of comparability.\n\n\n_What are the dynamic implications of the 25 percent average difference between public sector and_\n_private formal sector wages during the 1991‐2005 period?_\n\n\nNote that this 25 percent difference reflects a 10 percent union premium plus a remaining 15 percent\n“real” average public sector wage premium during this period. <sup>12</sup> The first implication one would expect\nfrom this difference would be that it might place a barrier to the expansion of employment in the\nprivate formal sector, since higher public sector wages bid up private formal sector wages, which in turn\nsqueeze private sector profits, leading as a result to lower levels of investments. Lower investments\nimply in turn lower increases in labor productivity and lower job creation. <sup>13</sup> The second, and related,\nimplication one would expect from the slow growth in private formal sector employment would be to\nconsign most of employment to the private informal sector. <sup>14</sup>\n\n\nThese expectations are confirmed by the data available from the Ghana Living Standards Survey. The\ntotal of formal and informal employment increased more slowly than the labor force, rising by 45\npercent between 1991 and 2005 (from 5.5 to 8 million people), while the labor force expanded by 55\npercent, rising from 7.3 to 11.3 million people. This constraint to the growth in overall employment is\nlikely the explanation for the very slow shift away from employment in agriculture, with the agriculture\nsector still employing 54 percent of the labor force in 2005, down from 56 percent in 1991. <sup>15</sup>\n\n\nIf public sector wages were to rise more closely in line with productivity improvements in the rest of the\neconomy, there would be more space for the private formal sector to increase employment. Increased\nemployment in private sector urban activities would create a pull effect for rural", "output": {"entities": {"named_data": ["Ghana Living Standards Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004342", "page": 16, "chunk": 1, "title": "wps5150", "pdf_url": "https://local/prwp/wps5150.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Ghana Living Standards Survey", "label": "NAMED_DATA", "score": 0.9139106869697571, "start": 1111, "end": 1140, "probe_score": 0.9873, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**<u>Table 6.1: Shocks other than conflict suffered in the past 12 months</u>**\n\n\n\n\n\n|Category|Shock type|Amhara<br>(1,014 households)|Col4|Oromiya<br>(1,255 households)|Col6|\n|---|---|---|---|---|---|\n|**Category**|**Shock type**|**Yes (%)**|**Yes (count)**|** Yes (%)**|**Yes (count)**|\n|Environment|Drought|46.6|472|||\n||Drought (late start of the rains)|||80|1,002|\n||Drought (long dry spell causing crop damage)|||75|939|\n||Drought (short rainy season or early end of rains)|||71|894|\n||Too much rain or floods|23.8|241|1.5|9|\n||Pests/locusts destroying crops|4.9|50|3|33|\n||Erosion|19.8|201|2|25|\n||Frost or hailstorms|38.2|387|0.5|6|\n|Economy|Large increase in input prices|62.8|637|48.8|612|\n||Large decrease in output prices|9.7|98|10.1|127|\n|Personal|Death of household member|6.7|68|4.2|53|\n||Illness of household member|26.5|269|15.9|200|\n\n\n_Source: Authors’ own. Created using data from the quantitative", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data from the quantitative"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000561", "page": 25, "chunk": 0, "title": "Can Social Protection Programmes Promote Livelihoods and Climate Resilience in Conflict‑Affected Settings? Evidence from Ethiopia’s Productive Safety Net Programme", "pdf_url": "https://reliefweb.int/attachments/52e51023-be1a-5cb4-a8d9-02b4718bea3a/BASIC_WP37.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from the quantitative", "label": "VAGUE_DATA", "score": 0.5407091379165649, "start": 890, "end": 916, "probe_score": 0.9756, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nPublic Administration Modernization Project (P162904)\n\n\nsupported by the Social Safety Net Project (P130138). <sup>16</sup> [^16: The Djibouti Social Safety Net Project is a World Bank-funded project, with an Additional Financing that also supports the\nSocial Registry and National Social Protection Strategy. The registry currently contains information about 42,000 households,\nexceeding the target of 20,000. The collection of biometric data about these households has been launched and biometric\ninformation about 33,000 beneficiaries has been registered. The Djibouti Public Administration Modernization Project will be\ncollaborating closely with the safety net project team. The Project will build on lessons learned from the enrollment and\nregistration phase conducted by the Social Affairs Department.] The experiences, capabilities, information\ncollected, and possibly some of the technology resources will be leveraged to derisk the project and\noptimize the use of available resources. The same coordination effort between ANSIE and sector\nministries is being followed in the development of e-services.\n\n\n53. The theory of change, as presented through the Results Chain in annex 1, is that supporting\ninstitutional and capacity building on access to information, asset disclosure, transparency, and\naccountability—as well as putting in place a solid foundation of e-government (unique ID, cybersecurity,\nPKI, and so on) and modernizing revenue administration services—will increase access to services and\nreduce transaction costs. In addition, it will reduce opportunities for fraud by disintermediating the\ninteractions between citizens, businesses, and civil servants. This will give more credibility to the\ncommitment by the authorities to improve services, governance, accountability, and fight corruption.\nFurthermore, the provision of more information to the citizenry, public feedback about the quality of\nservices delivered, and citizen interaction with the digital platform including public data disclosure (open\ndata) will increase engagement and cooperation in the public service delivery system. This would\nultimately contribute to greater legitimacy and stability.\n\n\n54. **Tax and customs administration modernization.** The", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["open\ndata"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000142", "page": 26, "chunk": 0, "title": "Djibouti - Public Administration Modernization Project", "pdf_url": "http://documents1.worldbank.org/curated/en/826531523301322820/pdf/Djibouti-Public-Admin-PAD-PAD2604-04062018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "open\ndata", "label": "VAGUE_DATA", "score": 0.5964937806129456, "start": 2045, "end": 2054, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "</sup>\n\n2. **Lower economic activity in the industry and services sectors will lead to job losses and, with the shift of**\n**labor back to agriculture, will result in increased vulnerabilities and increased poverty levels.** Growth in\nmanufacturing decelerated to 1.3 percent from June 2019 to June2020, from 6.5 percent from June 2018 to June\n2019, while growth in trade and tourism-related activities, such as hotel accommodation and restaurants, is\nexpected to shrink from an average annual growth of 3.5 percent to about 1 percent over the same period. <sup>2</sup> [^2: Uganda Economic Update, 15th Edition, July 2020.] Supply\nchain disruptions, increasing lead times for critical inputs and unanticipated delivery cancellations, are\nconstraining firm-level activity, which will affect industrial output. The number of people that could be pushed\ninto poverty is estimated at 780,000. <sup>3</sup> [^3: Statement on the Economic Impact of COVID-19 by the Ministry of Finance, Planning and Economic Development (MoFPED).] Overall, the poverty rate could increase between 1.8 and 7.3 percentage\npoints, from the current level of 25.3 percent. This would add between 0.5 and 2.07 million to the rural poor\n(which stood at 7.2 million in 2016/17).\n\n\n3. **Poverty has increased significantly in Uganda after the first COVID-19 lockdown in March–June 2020**\n**given the shift of workers to agriculture and the slow recovery of household incomes** <sup>**4**</sup> [^4: UBOS has recently announced poverty rates based on UNHS 2019/20.] . Despite an improvement\nbetween October 2020 and April 2021, income levels were still below pre-COVID levels for at least one third of\nhouseholds before the onset of the second COVID-19 wave in June 2021. This is concerning given the", "output": {"entities": {"named_data": ["UNHS 2019/20"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000021", "page": 13, "chunk": 1, "title": "Uganda - Investment for Industrial Transformation and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/469061641926083502/pdf/Uganda-Investment-for-Industrial-Transformation-and-Employment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHS 2019/20", "label": "NAMED_DATA", "score": 0.8801239132881165, "start": 1519, "end": 1531, "probe_score": 0.9904, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "place. Hence a screening of this will have to take part prior to the finalisation of the\nplanning process jointly with NLC and NLMB to determine ownership of all land public,\nprivate and communal.\n\n\nAll public land encroached by communities will be ineligible for implementing a KDSP\ninvestment until and unless the County governments duly compensate the encroachers for\nlosses of assets.\n\n\nEMCA regulations enforced by NEMA require the promotion of environmental and\nsocial sustainability in Program designs so as to avoid, minimize, or mitigate adverse\nimpacts, and promote informed decision-making relating to the Program’s environmental\nand social impacts. EMCA, requires that all projects listed in the Schedule 2, be subjected\nto full EIA studies. In recognition that certain projects may not require full EIA, the\nEMCA gives NEMA the power to direct a project proponent to forego the submission of\nan EIA report in certain cases if there are no major environmental and social impacts.\n\n\n**Fourth**, compliance with this investment menu is a “minimum condition” for counties to\naccess grants for investments. The annual capacity and performance assessment will\nreview whether each county has followed the investment menu; if a county has not, it will\nbe excluded from competing for grants in the following year.\n\n\n**Fifth**, despite limited county capacity, the government’s overall capacity to screen\nproposed projects and require EIAs of projects with significant risks is quite robust. The\nESSA found that excluding projects that require EIAs would effectively limit most of the\npossible environment and social risks.\n\n\n**Finally**, the PforR is designed to annually assess and gradually strengthen county\ncapacity to manage social and environmental risks. The annual assessment of counties\nwill measure key aspects of county social and environmental management capacity.\nAdditional measures based on the ESSA of the capacity of implementing institutions for\nenvironmental and social management will be incorporated into the Program Action Plan\n(PAP). During the Program implementation phase, the borrower will monitor program\neffectiveness and share", "output": {"entities": {"named_data": [], "descriptive_data": ["annual capacity and performance assessment", "annual assessment of counties"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010894", "page": 10, "chunk": 0, "title": "Kenya - Devolution Support Project : environmental assessment : Environmental and social systems assessment", "pdf_url": "https://documents.worldbank.org/curated/en/298241468039256110/pdf/E4843-REVISED-EA-P149129-ESSA-PUBLIC-Disclosed-2-28-2016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "annual capacity and performance assessment", "label": "DESCRIPTIVE_DATA", "score": 0.5048172473907471, "start": 1119, "end": 1161, "probe_score": 0.5386, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "annual assessment of counties", "label": "DESCRIPTIVE_DATA", "score": 0.8312146067619324, "start": 1770, "end": 1799, "probe_score": 0.2014, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<u>11,530</u>** **<u>27,302</u>** **<u>Jun-Sep</u>**\n\n\n\nSample distribution by geographical strata,\nfollowed by random selection of districts, and\n<u>convenience sampling for household selection.</u>\n\nSample distribution by geographical strata, and\nsimple random selection of households from cash\n<u>enrolment lists.</u>\n\nTwo strata (collective sites vs. private\naccommodation); random selection of districts and\n<u>convenience sampling for household selection.</u>\n\n\n### **Limitations**\n\nThe statistical significance of the MSNA results is\nlimited by the non-probabilistic selection of\nrespondents. Moreover, the use of convenience\nsampling likely led to a larger share of data being\ncollected from more vulnerable households.\n\n\nThere was also a notably high non-response rate\nregarding questions related to income and\nexpenditure, which likely resulted in non-response\nbias. The income module of the MSNA was also\nmaterially different from the one employed by EU\nSILC, which may limit comparability of this data to\nthat of host populations.\n\n\n\nIt is also important to highlight that there were slight\ndifferences in the questionnaire across countries.\nNot all questions were consistently included in all\ncountry-level surveys, and some answer options\nwere individually adjusted. To mitigate the impact of\nthese differences, the regional analysis focused on\ndata that could be matched. Certain indicators that\nmay have been available by country have thus been\nexcluded from this assessment.\n\n\nLastly, the survey was conducted during the\nsummer months, coinciding with both host country\nand Ukraine school holidays. This period often sees\nmany households temporarily visiting Ukraine,\nwhich impacted the accessibility of households and\nposed challenges in meeting targets, particularly in\ncertain countries and geographic locations.\n\n\n**11**", "output": {"entities": {"named_data": [], "descriptive_data": ["enrolment lists", "country-level surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 10, "chunk": 1, "title": "3", "pdf_url": "https://local/jad_paddy_docs/3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "enrolment lists", "label": "DESCRIPTIVE_DATA", "score": 0.5976282358169556, "start": 300, "end": 315, "probe_score": 0.5108, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "country-level surveys", "label": "DESCRIPTIVE_DATA", "score": 0.6057842969894409, "start": 1206, "end": 1227, "probe_score": 0.0037, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "br>Description:This indicator will measure the increase in percentage of population with access to jobs and services located at the CBD using public transport services. This<br>indicator captures the improved accessibility objective of the project for public transport passengers.|<br>Description:This indicator will measure the increase in percentage of population with access to jobs and services located at the CBD using public transport services. This<br>indicator captures the improved accessibility objective of the project for public transport passengers.|<br>Description:This indicator will measure the increase in percentage of population with access to jobs and services located at the CBD using public transport services. This<br>indicator captures the improved accessibility objective of the project for public transport passengers.|\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Name: Average travel time<br>by public transport from<br>Tabarja station to Charles<br>Helou terminal at morning<br>peak hours|Col3|Minutes|75.00|45.00|Biannual|Data to be obtained from<br>the ITS.|CDR / the RPTA<br>BRT operators|Col10|\n|---|---|---|---|---|---|---|---|---|---|\n||<br>Description:Average rush hour in-vehicle travel time by the PT services from Tabarja station to Beirut (Charles Helou terminal) at morning peak hours between 7:00am<br>and 9:00am. This indicator measures the improved speed objective of the project  for public transport services.|<br>Description:Average rush hour in-vehicle travel time by the PT services from Tabarja station to Beirut (Charles Helou terminal) at morning peak hours between 7:00am<br>and 9:00am. This indicator measures", "output": {"entities": {"named_data": ["ITS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000022", "page": 47, "chunk": 2, "title": "Lebanon - Greater Beirut Public Transport Project", "pdf_url": "http://documents.worldbank.org/curated/en/471241521338566907/pdf/PAD-final-02262018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "ITS", "label": "NAMED_DATA", "score": 0.7365570664405823, "start": 1057, "end": 1060, "probe_score": 0.424, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nThird Additional Financing for the Ethiopia COVID-19 Emergency Response Project (P178821)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Col2|Col3|Col4|Indicator|Col6|\n|---|---|---|---|---|---|\n|Number of communication material<br>leaflets, posters, job aids, wall chart,<br>banners) distributed||Quarterly<br>|Project<br>Reports<br>|Review of Project<br>Reports with defined<br>methodology for data<br>collection for each<br>Results Framework<br>Indicator<br>|MOH<br>|\n|Percentage of grievances addressed<br>within the time specified in the project<br>implementation manual|This indicator will measure<br>citizens’ participation in<br>planning and providing<br>feedback on project<br>activities to encourage<br>informed feedback to<br>develop appropriate<br>solutions|Quarterly<br>|MOH Reports<br>|MOH surveys and<br>routine data<br>|EPHI<br>|\n|Number of vaccine laboratory renovated<br>and equipped.|Number of vaccine<br>laboratory renovated and<br>equipped.|Quarterly<br>|Project<br>Reports<br>|Review of Project<br>Reports with defined<br>methodology for data<br>collection for each<br>Results Framework<br>Indicator<br>|EFDA/MOH<br>|\n|Number of monthly assessed (using<br>checklist) PoEs, isolation and quarantine<br>centers|Result will be updated on<br>the upcoming<br>implementation support<br>mission.", "output": {"entities": {"named_data": [], "descriptive_data": ["MOH surveys"], "vague_data": ["routine data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017203", "page": 52, "chunk": 0, "title": "Ethiopia - COVID-19 Emergency Response Project : Additional Financing", "pdf_url": "https://documents.worldbank.org/curated/en/721611617069718773/pdf/Ethiopia-COVID-19-Emergency-Response-Project-Additional-Financing.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "MOH surveys", "label": "DESCRIPTIVE_DATA", "score": 0.7575415968894958, "start": 791, "end": 802, "probe_score": 0.0655, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "routine data", "label": "VAGUE_DATA", "score": 0.529336154460907, "start": 810, "end": 822, "probe_score": 0.2444, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**1.** **Introduction**\n\n\nThe shock associated with the COVID-19 pandemic has been large and persistent. As documented\n\nin Apedo-Amah et al. (2020) and Cirera et al. (2021), the private sector has experienced a large,\n\n\npersistent negative impact on sales across all regions of the world. Most firms had still not recovered\n\n\nthe levels of sales in 2019 more than a year after the beginning of the pandemic (Cirera et al., 2021)\n\n\nand some sectors are experiencing structural changes in the way products or services are produced\n\nand demanded. These changes and the associated reallocation of resources have already been\n\n\nidentified in the data from the United States (Barrero et al., 2021).\n\n\nA critical question for policy is how these changes will affect firm growth and aggregate produc\ntivity. Are surviving firms coming out stronger from the pandemic? The answer to this question\n\n\ndepends on many different channels that affect productivity, which in many cases are in opposing\n\n\ndirections. For example, Harris and Moffat (2021) implemented a survey of UK firms and found that,\n\non the one hand, 18% of firms have stopped and 45% reduced doing R&D but, on the other hand,\n\n40% of firms have increased ICT investments. Andrews et al. (2021) find a positive reallocation\n\neffect for three OECD countries, mainly driven by technology readiness to face the shock and the\n\nadditional investments in technology. This paper explores firms’ digitalization trends during the\n\nCOVID-19 pandemic using a novel firm-level data set of 57 countries across three periods of time\n\nsince the start of the pandemic. The paper identifies the digitalization effects on firms’ resilience,\n\n\ndifferences in adoption, and changes in market share distribution.\n\n\nThere are at least two forces associated with the pandemic, in opposite directions, driving the\n\n\ndecision of businesses to invest in and expand the use of digital technologies. On the one hand,", "output": {"entities": {"named_data": [], "descriptive_data": ["survey of UK firms", "firm-level data set of 57 countries"], "vague_data": ["data from the United States"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000561", "page": 3, "chunk": 0, "title": "idu003954df4097d60473d0b65906fce19f25ce6", "pdf_url": "https://local/prwp/idu003954df4097d60473d0b65906fce19f25ce6.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from the United States", "label": "VAGUE_DATA", "score": 0.6842592358589172, "start": 641, "end": 668, "probe_score": 0.9659, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey of UK firms", "label": "DESCRIPTIVE_DATA", "score": 0.9111248254776001, "start": 1052, "end": 1070, "probe_score": 0.9731, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "firm-level data set of 57 countries", "label": "DESCRIPTIVE_DATA", "score": 0.9099205136299133, "start": 1508, "end": 1543, "probe_score": 0.9809, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "49 Syrian Observatory for Human Rights (2015) Available at: http://www.syriahr.com/?option=com_news&nid=16470&Itemid=2&task=displayne\nws. Accessed 10 April 2015.\n\n50 World Health Organisation, United Nations Office on Drugs and Crime, United Nations Development Programme (2014) Global Status Report on\nViolence Prevention 2014\n\n51 In counties less affected or not affected, there was no increase in the incidence rate. Other U.S. studies have also shown post-disaster increases\nin child abuse reports. See World Health Organization (2005) Violence and disasters\n\n52 In counties less affected or not affected, there was no increase in the incidence rate. Other U.S. studies have also shown post-disaster increases\nin child abuse reports. See World Health Organization (2005) Violence and disasters\n\n53 Jeannie Annan, Tom Bundervoet, Juliette Seban, Jaime Costigan (2013) Urwaruka Rushasha: A Randomized Impact Evaluation of Village Savings\nand Loans Associations and Family-Based Interventions in Burundi, International Rescue Committee\n\n54 Data on the number of deaths in conflict settings is for the most part not disaggregated between intentional killings, and accidental death. In this\nsection on killings we have tried to list data that indicate death due to hostilities in conflict affected countries. Any unintentional deaths resulting\neither from natural disasters or due to the presence of landmines and unexploded ordinance are listed elsewhere I the report.\n\n55 Olara Otunnu, ‘Special Comment’ on Children and Security, Disarmament Forum, No. 3, United Nations Institute for Disarmament Research, Geneva, 2002, pp. 3-4, cited in Save the Children Child Protection Initiative (2013) Save the Children’s Child Protection Strategy 2013-2015: Making\nthe world a safe place for children\n\n56 Save the Children (2014) State of the World’s Mothers : Saving Mothers and Children in Humanitarian Crises\n\n57", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Data on the number of deaths in conflict settings"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001360", "page": 51, "chunk": 0, "title": "A matter of Life and Death: Child Protection programming’s essential role in ensuring child wellbeing and survival during and after emergencies", "pdf_url": "https://reliefweb.int/attachments/d2c273e6-b3b1-323b-b226-b51d7ed0be12/A_Matter_of_life_and_death_LowRes.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data on the number of deaths in conflict settings", "label": "VAGUE_DATA", "score": 0.5480924844741821, "start": 1041, "end": 1090, "probe_score": 0.9258, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nGenerating Growth Opportunities and Productivity for Women Enterprises Uganda Project (P176747)\n\n\nthan one in ten refugees receive any form of credit. <sup>31</sup> [^31: World Bank. 2019 Informing the Refugee Policy Response in Uganda: Results from the Uganda Refugee and Host Communities 2018 Household\nSurvey (English). Washington, DC: World Bank.] Lack of national identification, distance to services, and charges\nand fees present significant barriers to accessing financial services, especially for women.\n\n\n**_Programming Gaps for Supporting Women Entrepreneurs with Growth Potential_**\n\n19. **The delivery of enterprise support services is fragmented and rarely customized to the needs of female**\n**entrepreneurs.** There are multiple enterprise development service providers available across the country, including\nbusiness development services, skills and training, incubation services, and digital literacy and digitalization initiatives. A\nrange of private firms, government institutions, nongovernment organizations (NGOs), and civil society organization\n(CSOs) provide these services in both rural and urban areas, but particularly in urban centers. However, these services\nare fragmented, difficult to access, and often delivered using methods and at times not amenable to female\nentrepreneurs, according to an ecosystem assessment and consultations with entrepreneurs. The support is usually\ndelivered with limited linkages between financial/credit services and skills support. There is a lack of women-focused\nbusiness development services at a national scale. Most business skills trainings focus on a few districts/regions or are\ntargeted at building capacity of formal training institutions. Those which target individual women and youths are\noccasional and short-term There are limited enterprise development services that support creation of networks and\nplatforms for women entrepreneurs, which is an important vehicle for market access, technological innovations,\nknowledge sharing, and peer to peer learning.\n\n20. **There is a programming gap to support female productivity and growth-oriented entrepreneurs.** The\ngovernment has helped women start the smallest-size businesses, particularly microenterprises through initiatives such", "output": {"entities": {"named_data": ["Uganda Refugee and Host Communities 2018 Household\nSurvey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000025", "page": 16, "chunk": 0, "title": "Uganda - Generating Growth Opportunities and Productivity for Women Enterprises Uganda Project", "pdf_url": "http://documents.worldbank.org/curated/en/527091655323259747/pdf/Uganda-Generating-Growth-Opportunities-and-Productivity-for-Women-Enterprises-Uganda-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Uganda Refugee and Host Communities 2018 Household\nSurvey", "label": "NAMED_DATA", "score": 0.8949094414710999, "start": 273, "end": 330, "probe_score": 0.7867, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA M&E data - NaCSA maintains lean and\n**community** **sub-projects and** decision-making by NaCSA; efficient organizational\n**NSAP** **partners monitored** structure\n**and evaluated** **in order to**\n**improve** **program**\n**effectiveness.**\n\n\n**3(d)** **Technical** **Assistance** 3d. 1 NaCSA staff indicate - IDA aide-memoires and\n**services** **effectively** **provided** satisfaction with technical project status reports\n**to support program** assistance, including skill\n**implementation** transfer activities\n\n\n**3(e)** NaCSA **management** 3e. 1 Project management - IDA Project Status reports\n**systems** **functioning** costs (NaCSA staff salaries at (including disbursement\n**effectively** **to ensure** all levels as well as operating reports);\n**program success** expenditures) are 13.5% or - NaCSA proposed annual\nless than total budgeted annual work program and budget\nexpenditures;                 - Annual audit reports;\n3e.2 NaCSA staff and                  - GOSL semi-annual PETS\npartners indicate satisfaction reports\nwith the performance of\nNaCSA's management;\n3e.3 NaCSA performance in\n\n\n                                  - 27", "output": {"entities": {"named_data": ["NaCSA M&E data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020925", "page": 31, "chunk": 1, "title": "Uganda - Institutional Capacity Building Project", "pdf_url": "https://documents.worldbank.org/curated/en/971821468760214176/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NaCSA M&E data", "label": "NAMED_DATA", "score": 0.6971123814582825, "start": 170, "end": 184, "probe_score": 0.0004, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "likely to tighten up environmental policy in sectors that are facing strong import\n\ncompetition, then if this is not accounted for one might falsely conclude that weak\n\nenvironmental policy leads to reduced international competitiveness.\n\n\nMuch of this recent work has found evidence in support of the weak version of the\n\npollution haven hypothesis – that is, in many recent studies more stringent environmental\n\nregulation in the manufacturing sector has a statistically significant negative effect on\n\nvarious measures of competitiveness in the affected sectors. <sup>6</sup> [^6: For reviews of this work, see Brunnermeier and Levinson (2004) and Copeland and Taylor\n(2004).] For example, Becker and\n\nHenderson (2000) and several other studies have found that increases in the stringency of\n\nenvironmental regulations induced by the US Clean Air Act tend to reduce the likelihood\n\nthat a new plant will locate in the affected jurisdiction. Keller and Levinson (2002) found\n\nthat high abatement costs have a negative effect on foreign investment inflows, while\n\nHanna (2010) found evidence that the US Clean Air Act induced some multinationals to\n\nrelocate production away from affected jurisdictions. Ederington and Minier (2003) and\n\nLevinson and Taylor (2008) found that higher abatement costs tend to have a positive\n\neffect on net imports (or equivalently, reduce net exports) in affected sectors.\n\n\nThere are a few studies that use data from newly industrializing countries, mostly\n\nfocusing on incoming foreign investment. The results here have been mixed, with most\n\nstudies finding little or no evidence that environmental policy affects the pattern of\n\ninvestment, but with some finding a negative effect and others a positive effect. Dean,\n\nLovely, and Hwang (2009) used data on variations across provinces in China in charges\n\nfor water pollution to determine whether the stringency of environmental policy affected\n\nincoming foreign investment. They found that more stringent regulation had a negative\n\neffect on investment from ethnically Chinese source countries (Hong Kong SAR, China;\n\nMacao; and Taiwan, China) in highly polluting sectors. However, environmental policy\n\nhad no", "output": {"entities": {"named_data": [], "descriptive_data": ["data from newly industrializing countries", "data on variations across provinces in China"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005399", "page": 12, "chunk": 0, "title": "wps6235", "pdf_url": "https://local/prwp/wps6235.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from newly industrializing countries", "label": "DESCRIPTIVE_DATA", "score": 0.7981486916542053, "start": 1441, "end": 1482, "probe_score": 0.9438, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data on variations across provinces in China", "label": "DESCRIPTIVE_DATA", "score": 0.8878932595252991, "start": 1785, "end": 1829, "probe_score": 0.9932, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "economic, social and environmental efficiency of cities. Well-managed urban development will\nbe a critical success factor for Cameroon to unleash its untapped economic potential and achieve\nupper-middle income status.\n\n\n12. **However, Government capacity to develop and implement inclusive and resilient**\n**urban development strategies that tackle the multiple intertwined dimensions of urban**\n**poverty and vulnerability remains limited** . Despite recent efforts to develop a variety of urban\nplanning instruments at the city level, only few have been finalized and approved to date. The\nquality of the plans is usually poor with the need to improve approaches regarding precarious\nsettlements, social or environmental and climate change considerations, and their implementation\nis questionable. Efforts to involve and engage marginalized urban communities remain scattered\nand ad-hoc. The Ministry of Housing and Urban Development (MINHDU) has recently developed\na slum upgrading strategy that needs to be operationalized and is looking to develop a pro-poor\nhousing policy and technical guidelines. However, due to the lack of sufficient data on urban areas,\nurban strategies and investment choices remain ill-informed. To address high land tenure\ninsecurity, which poses a serious challenge to inclusive urban planning, the Ministry of State\nProperty, Surveys, and Land Tenure (MINDCAF) launched a land reform in 2009 aimed at making\nland a real tool for development, and a broad program to modernize the cadaster in 2011, which is\nbeing supported by the African Development Bank (AfDB). However, the outcomes of this reform\nremain to be seen and the modernization of land supply chains is advancing very slowly given the\nweak institutional and technical capacity. Lengthy and cumbersome resettlement and\ncompensation procedures remain a serious bottleneck in any infrastructure development project.\n\n\n13. **The GoC has shown its commitment to implement decentralization, but progress to**\n**date has been relatively slow and the definition of decentralized functions has not yet been**\n**finalized.** The", "output": {"entities": {"named_data": [], "descriptive_data": ["cadaster"], "vague_data": ["data on urban areas"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000144", "page": 17, "chunk": 0, "title": "Cameroon - Inclusive and Resilient Cities Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/832091503626454254/pdf/CAMEROON-PAD-NEW-08032017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on urban areas", "label": "VAGUE_DATA", "score": 0.5071318745613098, "start": 1144, "end": 1163, "probe_score": 0.1215, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "cadaster", "label": "DESCRIPTIVE_DATA", "score": 0.5722782015800476, "start": 1512, "end": 1520, "probe_score": 0.5192, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017781", "page": 19, "chunk": 1, "title": "Ethiopia - Small-Scale Irrigation and Soil Conservation Project", "pdf_url": "https://documents.worldbank.org/curated/en/760471506446287737/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7292463183403015, "start": 272, "end": 283, "probe_score": 0.8771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 1\nPage 2 of 3\n\n\n**Project Development** **Outcome / Impact** **Project reports:** **(from Objective to Purpose'**\n**Objective:** **Indicators:**\nExpand access to basic Increased number of school Project Reports. It is assumed that\neducation. places. Government's current fiscal\nsituation will be resolved\n\n(salary payment to civil\nservants and teachers).\nEnrollment increases in MOE reports. Expansion of facilities and\nprimary schools from 35,000 quality will contribute to\nto 80,000 increased enrollment\nincluding among girls.\nIncreased availability of It is assumed that the\ntextbooks. Government maintains\ndouble-shifting.\n\n\nTrained primary school head Headteachers have autonomy\nteachers. and authority in managing the\nschools.\nBetter trained contractual Contractual teachers are\nteachers recruited early enough before\nthe school year to allow time\nfor training.\n\n\n**Output from each** **Output Indicators:** **Project reports:** **(from Outputs to Objective)**\n**Component:**\nIncreased number of school 226 classrooms will be built Monthly disbursement Availability of school places\nplaces. increasing capacity by over summary. will increase enrollment.\n20,000 based on double\nshifting.\nProvide textbooks. Numbers of textbooks per Semi-annual Provision of textbooks will\npupil increases. supervision reports. improve learning.\nTrained primary school head- Primary school head-teachers Annual audit reports; Better trained head-teachers\nteachers. trained and Guidebook for site visits. will improve school\nschool management prepared efficiency.\nand distributed.", "output": {"entities": {"named_data": ["MOE reports"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000161", "page": 30, "chunk": 0, "title": "Cambodia - Social Fund II Project", "pdf_url": "http://documents1.worldbank.org/curated/en/932001468769834027/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "MOE reports", "label": "NAMED_DATA", "score": 0.6933835744857788, "start": 385, "end": 396, "probe_score": 0.8075, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " comprehensive\nunderstanding of the economic situation in displacement settings, including a market\nassessment with baseline data, and available informal or formal financial services in\nthe displacement situation.\n\n\nThis would also allow for a better identification of the various livelihood interventions\n(for example grants, in-kind loans or skills training) besides credit that might be a\nmore appropriate tool for certain segments of the population. This would also avoid\nthe situation of a simple “rebranding” of care and maintenance programmes or a\nquick-fix perspective of microfinance interventions, something that, according to\nsome interviewees, has been relatively commonplace.\n\n\nAccording to the Alchemy project <sup>35</sup>, microfinance programmes for refugees should\nnot necessarily have to aim for operational or financial sustainability. All refugees are\nnot likely to be able to meet stringent repayment conditions. This means that there is a\ngreater likelihood that programmes for refugees will be in need of external support in\norder to continue.\n\n\n33 Hulme, “Is micro debt good for poor people? A note on the dark side of microfinance”, in Dichter &\nHarper (Eds.) “What’s wrong with microfinance?”, 2007\n34 Dichter, “The chicken and the egg dilemma in microfinance: An historical analysis of the sequence\nof growth and credit in the economic development of the ‘north’” in Dichter & Harper (Eds.), “What’s\nwrong with microfinance?”, 2007\n35 Jacobsen, “Microfinance in protracted refugee situations: Lessons from the Alchemy Project”, 2004\n\n\n18", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000726", "page": 19, "chunk": 1, "title": "Microfinance and refugees: lessons learned from UNHCR's experience", "pdf_url": "https://reliefweb.int/attachments/6a160d0d-4f03-34ea-8f39-5276d9b4392f/B7A06E825A37D3F88525781D0073FA22-Full_Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "baseline data", "label": "VAGUE_DATA", "score": 0.7685373425483704, "start": 116, "end": 129, "probe_score": 0.0752, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|110.46|100.03|100|\n|Soleure|91.51|102.51|88.46|103.52|95.2|87|\n|Glaris|113.65|90.98|80.86|77.3|92.01|78|\n|Vaud|98.77|87.8|98.47|106.17|97.96|95|\n|Valais|74.23|71.99|70|81.19|73.9|30|\n|Neuchâtel|87.53|76.48|84.35|88.65|84.59|58|\n|Geneva|112.65|85.49|126.35|111.1|111.02|130|\n|Jura|70|73.41|72.27|84.98|74.36|31|\n|**Switzerland**|**100**|**100**|**100**|**100**|**100**|**100**|\n|Max/min ratio|1.11|1.61|1.75|1.41|1.63|5.06|\n\n\nSources: Finances publiques en Suisse 2001, A.F.F., Berne: 76; Ordonnance du 17 novembre\n\n1999 fixant la capacité financière des cantons pour les années 2000 et 2001, RS 613.11", "output": {"entities": {"named_data": ["Finances publiques en Suisse 2001"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002869", "page": 68, "chunk": 2, "title": "wps3655", "pdf_url": "https://local/prwp/wps3655.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Finances publiques en Suisse 2001", "label": "NAMED_DATA", "score": 0.7243483066558838, "start": 435, "end": 468, "probe_score": 0.9944, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "proxy for a firm’s capital-intensity. Including the firm’s age serves as a proxy for its experience\n\n\nand strength of its business network.\n\n\nGuided by the observation of Marques (2015) that the gender of an entrepreneur affects the\n\n\nfirm’s decision whether and how much to export, we include a dummy for whether the firm’s\n\n\nowners are women. We control for whether a firm has foreign ownership, as this can be expected\n\n\nto influence export decisions. We control for whether the firm offers training, following Dixit and\n\n\nPal (2010), who evaluated the effects of training, among others, on firm performance. We include\n\n\nwhether the firm uses foreign technology and whether it imports inputs, as we would expect these\n\n\nto influence the firm’s propensity to export. To proxy innovation, we include an indicator for\n\n\nwhether the firm has introduced a new product or service in the last 3 years (Srinivasan and\n\n\nArchana, 2011). While the ES data are restricted to formal firms, to include a past indicator of\n\n\ninformality we control for whether the firm was registered at the time it began operations. We\n\n\ninclude a dummy to indicate whether the firm exports directly or if it instead sells to an\n\n\n\nintermediary that then sells abroad. Finally, we include year dummies.\n\n\n\nintermediary that then sells abroad. Finally, we include year dummies. The other parameters are 𝛼𝛼, the overall intercept parameter, 𝜇𝜇𝑖𝑖 is a time-invariant\n\n𝜀𝜀𝑖 **𝑖** is an unobservable time-varying error term assumed to be well\n\n\n\nThe other parameters are 𝛼𝛼, the overall intercept parameter, 𝜇𝜇𝑖𝑖 is a time-invariant\n\nbehaved. unobservable effect, and 𝜀𝜀𝑖 **𝑖** is an unobservable time-varying error term assumed to be well\n\n\n\nbehaved. **𝑖**\n\n\n\nNext, we turn to the intensive margin to determine how a firm’s employment relates to its\n\n\n\nexport sales. For this,", "output": {"entities": {"named_data": ["ES data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000621", "page": 20, "chunk": 0, "title": "idu019885cc80edd20439d081a405a1e85b643b5", "pdf_url": "https://local/prwp/idu019885cc80edd20439d081a405a1e85b643b5.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "ES data", "label": "NAMED_DATA", "score": 0.7994531393051147, "start": 942, "end": 949, "probe_score": 0.9274, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Lamentablemente, los dos programas dentro de\nla categoría A (consulte la tabla 2), uno de RAC\n(2012) y uno de Zimbabue (2010), nunca se\nfinanciaron. Entre las 37 propuestas, solo el 32 %\nno recibió financiamiento (n=12): siete programas\nfueron totalmente financiados y cinco fueron\nfinanciados de manera parcial. Entre los programas\nfinanciados de manera total o parcial, siete se\npudieron verificar y, por lo tanto, fueron incluidos\nen el mapeo de programas.\n\n\n**Tabla 2: categorías de financiamiento**\n\n|Categoría Cantidad total de<br>propuestas, de 2009 a 2012|Col2|\n|---|---|\n|**A **|2|\n|**B **|6|\n|**C **|7|\n|**D **|13|\n|**E **|9|\n\n\n\n**III.II Estudios de casos que demuestran**\n**buenas prácticas**\nEntre los 21 programas que ofrecieron planificación\nfamiliar, se identificaron tres como los que más\ncumplieron con los criterios de estudio de casos\ny pudieron ser visitados. Cuatro programas\ndemostraron elementos prometedores. Los\nprogramas que no fueron seleccionados para los\nestudios de casos fueron limitados en lo que\nrespecta a la recopilación de datos, la débil\nintervención de adolescentes para garantizar la\natención centrada en los éxitos, la capacidad para\nmejorar la aceptación de anticonceptivos o las\ncomunicaciones para recopilar más información.\n\n\nLos tres", "output": {"entities": {"named_data": [], "descriptive_data": ["mapeo de programas"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000914", "page": 16, "chunk": 0, "title": "Programas de salud sexual y reproductiva para adolescentes en entornos humanitarios: una mirada profunda a los servicios de planificación familiar", "pdf_url": "https://reliefweb.int/attachments/87b02fb5-060f-3a98-9062-8429700662a2/ASRH_good_practice_documentation_1-25-2013_SPANISH_FINAL_4_logos.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "mapeo de programas", "label": "DESCRIPTIVE_DATA", "score": 0.5464172959327698, "start": 440, "end": 458, "probe_score": 0.3568, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " be the one corresponding to the median level income of the base country, India). It may be\n\nemphasized that ��� <sup>�</sup> �, ��� <sup>�</sup> �and ��� <sup>�</sup> - are estimated as composite variables and no explicit algebraic\n\n\nforms for these functions are assumed. This confers the advantage that the estimated PPPs are not\n\n\ndependent on a priori specified particular functional forms such as, for example, the specification\n\nproposed by Banks, Blundell and Lewbel (1997).\n\n\n**Comparison with the ICP PPPs**\n\n\n[Table 5 about here]\n\n\nTable 5 presents the counterfactual PPPs based on World Bank data on broad item groups by\n\n\nincome categories for rural and urban sectors, <sup>22</sup> [^22: See Appendix A for description of income category level.] with India as base. The table also presents the\n\n\n2011 ICP Consumption PPPs, where the base country has been shifted from the US to India by\n\n\ndividing all the PPPs (with respect to US $) by the PPP of India with US as base. In case of a\n\n\nfew countries, for example, Chad, Ethiopia and Ghana, the two PPPs are nearly identical, but\n\n\nthis is not always the case. The bias in the 2011 ICP PPPs in relation to the counterfactual PPP\n\n\nis not unidirectional. In general, the 2011 ICP PPPs in the African region exceed the\n\n\ncounterfactual PPPs, and the reverse is the case in the Asia/Pacific region. While in case of\n\n\nseveral countries, for example, South Africa, China and Indonesia, there is a large difference\n\n\nbetween the 2011 ICP PPP and its 2011 counterfactual, overall, there is a positive correlation\n\n\nbetween the two. The overall correlation coefficient, over all countries taken together, turns\n\n\nout to be 0.9134. The region specific correlations are 0.9189, 0.9996, 0.99", "output": {"entities": {"named_data": ["World Bank data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006449", "page": 27, "chunk": 1, "title": "wps7395", "pdf_url": "https://local/prwp/wps7395.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Bank data", "label": "NAMED_DATA", "score": 0.6856421232223511, "start": 593, "end": 608, "probe_score": 0.8241, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "-06  2.46e-06   2.14  0.032   4.44e-07  .0000101\nlongitud00 | -5.63e-07  1.84e-06  -0.31  0.760  -4.17e-06  3.05e-06\nlatitud00 | -1.65e-06  1.74e-06  -0.95  0.343  -5.07e-06  1.76e-06\naltitud00 | -.0001506  .000023  -6.55  0.000  -.0001957  -.0001055\nocup00 |  .3560121  .077375   4.60  0.000   .2043585  .5076658\nanal00 |  .0182514  .002619   6.97  0.000   .0131182  .0233846\nspri00 |  .0146275  .0020881   7.01  0.000   .0105349  .0187202\nsani00 | -.0033446  .0007385  -4.53  0.000   -.004792  -.0018971\nelec00 |  .0059956  .0007938   7.55  0.000   .0044397  .0075514\nagua00 | -.0016647  .0004879  -3.41  0.001  -.0026209  -.0007085\ntier00 |  -.013339  .0009844  -13.55  0.000  -.0152683  -.0114096\ningr00 | -.0285047  .0015145  -18.82  0.000   -.031473  -.0255364\n<u>_cons |  8.374729  1.540578   5.44  0.000   5.355223  11.39423</u>\n\n\n40", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003249", "page": 40, "chunk": 5, "title": "wps4036", "pdf_url": "https://local/prwp/wps4036.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "’Amortissement\n(CAA);\n\nc. Government Delegates of the city council of Yaoundé, Douala, Ngaoundéré, Kumba\nand Maroua and Mayors of the urban communes of Batouri and Kousseri, as well as\nof the participating sub-divisional councils;\n\nd. Representatives of civil society, and association of urban planners.\n\n\n3. **A Project Coordinating Unit (PCU),** placed under the MINHDU, will ensure overall\nproject coordination including reporting, communication, M&E and will report to the PSC. It will\nalso carry out its secretarial functions. The PCU will prepare annual work plans, quarterly and\nother periodic progress reports, coordinate external audits, consolidate project data, and manage\nrelationships with the World Bank and other project stakeholders.\n\n4. The PCU will also be directly responsible for implementing Component 1, and will support\nCTDs to implement their activities under component 2, retaining fiduciary responsibility for these\nactivities vis-à-vis the World Bank.\n\n5. The PCU will be composed of consultants financed by the project and Government staff,\nincluding: a coordinator, a senior advisor, a civil engineer, a municipal/urban development\nspecialist, a procurement specialist, an administrative and financial officer assisted by an\n\n\n42", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["project data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000144", "page": 55, "chunk": 1, "title": "Cameroon - Inclusive and Resilient Cities Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/832091503626454254/pdf/CAMEROON-PAD-NEW-08032017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "project data", "label": "VAGUE_DATA", "score": 0.6863837242126465, "start": 659, "end": 671, "probe_score": 0.0471, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**1.** **Introduction**\n\nThe contribution of non-farm activities (such as non-farm wage employment and non-farm\nenterprises) to household income in Sub-Saharan Africa (SSA) is substantial and has increased\nover time (Haggblade et al., 2010, Start, 2001, Lanjouw and Lanjouw, 2001, Lanjouw and Shariff,\n2004, Reardon et al., 1998). Recent estimates indicate that 44 percent of rural African households\n(on average) participate in non-farm wage employment or self-employment. The average income\nshare from non-farm sources is 23%, with an overall positive correlation between diversification\nand GDP per capita (Davis et al., 2014). Consequently, rural non-farm employment (RNFE) has\nbecome an essential part of discussions on poverty reduction in rural Africa, being a potential\npathway out of poverty for many.\n\nDespite the extent and growth in importance of the RNFE in SSA, there are still limited\nempirical analyses of the welfare effects of the subsector and how this varies across different kinds\nof rural households. Though evidence of positive correlations between RNFE participation and\nincome exists, many studies are outdated while an ongoing debate still questions whether RNFE\nimproves welfare or if indeed it is the wealthy who are able to engage in RNFE. Consequently,\nthis paper uses nationally representative data and a combination of empirical approaches to\nexamine links between RNFE participation and welfare. We explore a key mechanism through\nwhich welfare effects of RNFE are likely to operate in rural SSA and the heterogeneity of such\neffects across different types of rural households.\n\nThe paper significantly enriches the discussion on RNFE and rural development in SSA in\nthree main ways. First, we use panel data methods to address time invariant sources of\nheterogeneity in the estimation of the welfare effects of non-farm employment participation. Bezu\net al. (2012) also use panel data from", "output": {"entities": {"named_data": [], "descriptive_data": ["nationally representative data", "panel data", "panel data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007079", "page": 3, "chunk": 0, "title": "wps8096", "pdf_url": "https://local/prwp/wps8096.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "nationally representative data", "label": "DESCRIPTIVE_DATA", "score": 0.7753700017929077, "start": 1299, "end": 1329, "probe_score": 0.8292, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "panel data", "label": "DESCRIPTIVE_DATA", "score": 0.5292302966117859, "start": 1731, "end": 1741, "probe_score": 0.5441, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "panel data", "label": "DESCRIPTIVE_DATA", "score": 0.5421868562698364, "start": 1908, "end": 1918, "probe_score": 0.9086, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Programme of Action (NAPA), the National Capacity Self Assessment\n(NCSA) and the National Strategy for Sustainable Development. The release of adaptation funds\nsuch us under the UNFCCC Least Developed Countries Fund (LDC Fund) is contingent on these\ncore documents and requires government processes to be streamlined.\n\nThe availability and proper management of climate data and information is paramount for\nplanning and implementing adaptation measures ( _e.g.,_ Dilley, 2000; Hulme et al., 2005).\nHowever, data collection and information management is limited in Mozambique which\nrepresents a main barrier to mainstreaming. The national climate data network requires", "output": {"entities": {"named_data": [], "descriptive_data": ["national climate data network"], "vague_data": ["climate data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003915", "page": 16, "chunk": 2, "title": "wps4711", "pdf_url": "https://local/prwp/wps4711.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "climate data", "label": "VAGUE_DATA", "score": 0.5988355278968811, "start": 362, "end": 374, "probe_score": 0.0673, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "national climate data network", "label": "DESCRIPTIVE_DATA", "score": 0.8159592747688293, "start": 630, "end": 659, "probe_score": 0.0861, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_Child laborers are highly concentrated within the North_ . If the South constituted its own\ncountry, nearly all 7-14 year olds would not be working (92.2%), while if the North formed\nits own country, one third of children would be engaged in labor activities (33.1%). In the\nNorth, about half of the children of this age are only attending school (50.6%) and 18.9% are\nonly working while 14.1% combine work with school and 16.3% are doing neither. The fact\nthat only 1.6% of Southern children are working while not schooling compared to 18.9% of\nNorthern children illustrates the extent of the latter group’s strong marginalization (Table 2).\nChildren affected by harmful child labor (conflicting with their education) live therefore\nnearly entirely in the North.\n\n_Children’s usefulness or value on the farm increases as they get older or (more accurately)_\n_physically bigger and stronger_ . Child labor rises incrementally from 9.9% for 7-8 year olds to\n15.4% for 9-11 year olds followed by 19.6% for 12-14 year olds. Such trends are also found\ninternationally (Edmonds 2008). In addition, there is an increasing demand for older children\nto only be working, as age-specific data in Figure 2 shows (see appendix).\n\n_There appears to be a strong intergenerational relationship between child labor and parental_\n_education as well as agricultural livelihoods (Table 2)_ . The kinds of livelihoods that parents\npursue seem closely related to whether children work or not, as nearly all child laborers are\nworking in family farming, with only 6.3% engaged in non-agricultural work. This, together\nwith the fact that only 3.8% of child laborers receive payment for their work (see Table 2),\ndoes not", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["age-specific data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005662", "page": 12, "chunk": 0, "title": "wps6513", "pdf_url": "https://local/prwp/wps6513.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "age-specific data", "label": "VAGUE_DATA", "score": 0.6550095081329346, "start": 1166, "end": 1183, "probe_score": 0.829, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " low-skilled men.\nSuch displacement of Turkish citizens from the labor markets presents a threat to social cohesion, with\n\n\n5 TRC Livelihood Survey 2018; International Crisis Group. 2018. _Turkey’s Syrian Refugees: Defusing Metropolitan Tensions_ .\nEurope Report No. 248.\n6 TRC Livelihood Survey 2018.\n7 Turkish Red Crescent. 2018. _Livelihoods Analysis_ . Unpublished.\n8 Without a certification of skills, employers may also be more likely to statistically discriminate against refugees. Taste-based\ndiscrimination can also be another factor inducing employers to pay less wages to an otherwise similarly skilled refugee (see\nBecker 1971).\n9 Del Carpio, X., and M. Wagner. 2015. “The Impact of Syrian Refugees on the Turkish Labor Market.” World Bank Policy\nResearch Working Paper No. 7402.\n\n\nPage 9 of 85", "output": {"entities": {"named_data": ["TRC Livelihood Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000114", "page": 12, "chunk": 2, "title": "Turkey - Agricultural Employment Support for Refugees and Turkish Citizens through Enhanced Market Linkages Project", "pdf_url": "http://documents1.worldbank.org/curated/en/671481617301015363/pdf/Turkey-Agricultural-Employment-Support-for-Refugees-and-Turkish-Citizens-through-Enhanced-Market-Linkages-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "TRC Livelihood Survey", "label": "NAMED_DATA", "score": 0.5770952701568604, "start": 126, "end": 147, "probe_score": 0.9914, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " budget.|4.71|\n|D-2|Ilgin Wastewater<br>Treatment Plant Project|• <br>Construction of Ilgin Wastewater Treatment Plant Project|3.85|\n|D-3|Cumra Wastewater<br>Treatment Plant Project|• <br>Construction of Cumra Wastewater Treatment Plant Project|5.38|\n\n\n\n**Osmaniye Municipality**\n\n27. **Osmaniye context.** In 2018, the total population in Osmaniye province was 534,415 people out of which 51,160\n(or 9.6 percent of the total population) are SuTP’s. There is one refugee camp, the Cevdetiye Container Camp, in\nthe province of Osmaniye which hosts about 12,610 SuTP’s <sup>57</sup> [^57: UNHCR Turkey: Syrian Refugee Camps and Provincial Breakdown of Syrian Refugees Registered in South East Turkey (January 2020):\n_[https://data2.unhcr.org/en/documents/details/73300](https://data2.unhcr.org/en/documents/details/73300)_, accessed on January 15, 2020] .\n\n\n28. The city center of Osmaniye municipality receives drinking water from three main sources, which are: Zorkun\nSprings (400 l/s; by gravity), Yenikoey Wells (360 l/s; by pump) and 7 groundwater wells (270 l/s; by pump). The\ndesign report indicates that the existing resources are only capable to meet water demand until 2026. For this\nreason, Osmaniye Municipality has contacted DSİ and 786 l/s water allocation from Aslantaş Dam is received.\n\n\n29. The existing water distribution network has high NRW (56 percent) and real losses (49 percent) in the system <sup>58</sup> [^58: According to PID for Osmaniye] .\nThere are no ‘as built drawings’ of the existing water distribution network available, hence, the Municipality\nreceives around 200", "output": {"entities": {"named_data": ["PID for Osmaniye"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000125", "page": 68, "chunk": 1, "title": "Turkey - Municipal Services Improvement Project", "pdf_url": "http://documents1.worldbank.org/curated/en/726481585965774365/pdf/Turkey-Municipal-Services-Improvement-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PID for Osmaniye", "label": "NAMED_DATA", "score": 0.6084345579147339, "start": 1448, "end": 1464, "probe_score": 0.6968, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "rrea-Velez,<br>Barnett, &<br>Gifford, 2013|Australia<br>(Southeast<br>Queensland, male<br>refugees)|employment<br>status|N=233, 232 resettled; logistic<br>regression at time 1 and GEE<br>longitudinal predictor for a) all<br>participants and b) excluding<br>those not looking for work<br>|\n|<br> <br> <br> <br> <br> <br> <br> <br>|Time in<br>country<br> <br> <br>|Cortes, 2004|USA|earnings and<br>hours worked<br>|<br>census data (arrivals 1975-1980<br>from Afghanistan, Cuba, the<br>Soviet Union, Ethiopia, Haiti,<br>Cambodia, Laos, and Vietnam<br>classified as refugees)<br>|\n|<br> <br> <br> <br> <br> <br> <br> <br>|Time in<br>country<br> <br> <br>|Hugo, 2011|Australia|labour force<br>participation<br>|600 refugee-humanitarian<br>settlers<br>|\n|<br> <br> <br> <br> <br> <br> <br> <br>|Time in<br>country<br> <br> <br>|Marsh, 1980|USA<br>(‘Indochinese’)|<br>income per<br>week and<br>employment<br>rates|<br>1975 Indochinese arrivals,<br>surveys by the Department of<br>Health, Education, and<", "output": {"entities": {"named_data": [], "descriptive_data": ["census data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001008", "page": 46, "chunk": 1, "title": "The labour market integration of resettled refugees", "pdf_url": "https://reliefweb.int/attachments/97c91085-db0b-389e-8aa0-5cd80b1ee5a3/the%20labour%20market%20integration%20of%20resettled%20refugees.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "census data", "label": "DESCRIPTIVE_DATA", "score": 0.8079138994216919, "start": 417, "end": 428, "probe_score": 0.9692, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " MINSANTE as well as the Director General\n(DG) ARMP, DG INS, and DG BUCREP. The Committee will meet at least every three months to monitor\nimplementation and address early any institutional bottlenecks.\n\n\n**B. Results Monitoring and Evaluation**\n\n\n50. **The project’s M&E framework relies on the ‘Guide On Operational-Level Public Financial**\n**Management Reform Indicator’.** The M&E framework will be a key instrument to monitor progress\ntoward achieving the PDOs and providing reports on performance including potential bottlenecks as\nthey arise. The M&E framework presented in section VII captures the high- and medium-level results\nthat are expected to be achieved. MINEPAT will be in charge of assessing and reviewing the projects’\nresult indicators data. A midterm review (2019) will be carried out to ensure the project is on track and\nwill recommend any needed actions or adaptations to address challenges and improve implementation\ntoward achievement of the PDO. During implementation, the team will revisit the currently agreed\nindicators to make adjustments as required in consultation with the Government and other partners.\n\n\n**C. Sustainability**\n\n\n51. **The sustainability of the project is underscored by the results-driven approach adopted** . The\nproject draws on diagnostics and recommendations for improving procurement and program budget\nprocesses. The introduction of public sector performance-based management and results and the\ndevelopment of robust systems and tools will provide a sound basis for ensuring Government\neffectiveness. The project’s design also includes activities shifting the incentives of key targeted civil\nservants in the Public Investment Management chain toward performance, using existing available\nbudget as much as possible (for example, per diem budgeted for the Procurement Committee). The\n\n\nPage 29 of 93", "output": {"entities": {"named_data": [], "descriptive_data": ["result indicators data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000044", "page": 32, "chunk": 1, "title": "Cameroon - Strengthening Public Sector Effectiveness and Statistical Capacity Project", "pdf_url": "http://documents1.worldbank.org/curated/en/305621511406035802/pdf/CAMEROON-PAD2-11012017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "result indicators data", "label": "DESCRIPTIVE_DATA", "score": 0.6430470943450928, "start": 738, "end": 760, "probe_score": 0.0241, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "## **The Quality of the Legal System, Firm Ownership, and Firm Size**\n\n**Abstract:** Employment in developing countries is disproportionately concentrated in\n\n\nvery small firms. We examine the extent to which the distribution of firm size is related\n\n\nto the quality of the legal system using data from Mexico. We combine Lucas’ (1978)\n\n\nmodel of firm size with Himmelberg, Hubbard and Love’s (2001) consideration of\n\n\nidiosyncratic risk in a framework in which the distribution of entrepreneurial talent and\n\n\naversion to idiosyncratic risk combine to determine the optimal size of firms. Our data\n\n\nallow us to focus on the differential impact of the legal system on proprietorships and\n\n\ncorporations. Moreover, by focusing on firms in a single country, the data draw attention\n\n\nto the importance of variation in the administration of justice and the enforcement of\n\n\nlegal verdicts. We find that Mexican states with more effective legal systems have larger\n\n\nfirms. A one-standard deviation improvement in the quality of the legal system increases\n\n\nthe average firm size by about 10-15 percent. The impact of the legal system is greatest in\n\n\nsectors in which proprietorships dominate. This pattern is consistent with better legal\n\n\nsystems increasing the investment of firm owners by reducing the idiosyncratic risk they\n\n\nface. All of these findings are upheld when we instrument for institutional variables using\n\n\nthe log of indigenous population in 1900 and the active presence of the drug trade in the\n\n\nstate.\n\n\n1", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data from Mexico"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002551", "page": 1, "chunk": 0, "title": "wps3246legal", "pdf_url": "https://local/prwp/wps3246legal.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from Mexico", "label": "VAGUE_DATA", "score": 0.6899071335792542, "start": 293, "end": 309, "probe_score": 0.9936, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "of the key infrastructure gaps to be addressed is improving road transport, which meets 90\npercent of transport requirements of the country, but where only four percent of roads are paved.\nIn Kampala only 10 percent of roads are paved.\n\n\n**B.** **SECTORAL AND INSTITUTIONAL CONTEXT**\n\n\n9. **Analysis of population movements in Uganda shows a predominance of migration**\n**towards the central region with the largest numbers moving to, Kampala, and the GKMA**\n**more broadly** . The gradual transformation of Uganda, both in terms of what it produces and\nwhere, is driving economic concentration and greater population density <sup>7</sup> [^7: Recent analysis showed that 88 percent of migrants moved to the central region,] . However,\ninfrastructure and services provision in the central region generally, and in Kampala specifically,\nare not keeping pace. Access to key urban services (roads, drainage, solid waste management,\nhousing, green parks, education and health) in Kampala is declining - overwhelmed by the flow\nof both daily and long term migrants. As a result of inefficient infrastructure and unaffordable\nservices, the poor and those seeking economic opportunities pay the heaviest price, including\nhigher costs of services, lower economic productivity, poor health and economic hardship.\n\n\n10. **Although Kampala is lagging behind in the provision of most infrastructure and**\n**services, poor mobility is particularly challenging.** The spatial growth of Kampala and the\nefficiency of its economy are negatively impacted by congestion, and the challenges posed by\ncongestion are compounded by the proliferation of public transport modes in Uganda dominated by 14-seat private mini buses and the rapid growth in motorbike taxi services - and an\nexplosion in private motor vehicle ownership (estimated at 11 percent per year). <sup>8</sup> Traffic jams\nare a regular feature of day time travel in Kampala, which involves one million commuters daily.\nA better urban transport system is", "output": {"entities": {"named_data": [], "descriptive_data": ["population movements in Uganda"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014004", "page": 11, "chunk": 0, "title": "Uganda - Second Kampala Institutional and Infrastructure Development Project (KIIDP-2)", "pdf_url": "https://documents.worldbank.org/curated/en/504911468115450273/pdf/PAD8000P133590010Box382156B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "population movements in Uganda", "label": "DESCRIPTIVE_DATA", "score": 0.5353880524635315, "start": 303, "end": 333, "probe_score": 0.8243, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "sectors). <sup>11</sup> [^11: For technical reasons, we have to take the average of our trade facilitation indicators across the importing and\nexporting countries. This is because importer- and exporter-specific measures, although time varying, are very\nstrongly correlated with the time-invariant fixed effects we use to take account of market size and relative price\neffects. Estimation using separate measures of exporter and importer infrastructure does not produce meaningful\nresults because of the strength of this correlation.] Data on these variables are sourced from the World Economic Forum’s _Global_\n\n\n_Competitiveness Report_ . We also control for the presence of tariffs (sourced from WITS-Trains),\n\n\nin addition to standard geographical and historical factors (Mayer and Zignago, 2006). Our trade\n\n\ndata come from WITS-Comtrade, and are disaggregated by BEC 1-digit sector. <sup>12</sup> [^12: This is a very broad product classification, and is intended to give a first indication of potential cross-sectoral\ndifferences in the impact of trade facilitation measures.] We estimate\n\n\nthe model over the period 2000-2005. (See Tables 5-6 for a description of our data, sources, and\n\n\nsample.)\n\n\n**_4.1_** **_Model Specification_**\n\n\nInitially used because of its explanatory power in empirical settings, the gravity model is now\n\n\nknown to be consistent with a rigorous theoretical derivation. In this paper, we use the micro\n\nfounded gravity model of Anderson and Van Wincoop (2003, 2004). It is now the standard\n\n\napproach taken in the trade literature.\n\n\nFrom basic microeconomic principles, Anderson and Van Wincoop (2003, 2004) show that it is\n\n\npossible to derive a gravity-like model of exports from country i to country j in sector k at time t\n\n\n( _X_ _ijtk_ ):\n\n##### log ( X ijtk ) = log ( E kjt )+ log ( Yitk )− log ( Ytk )+ ( 1 −σ k ) log ( tijtk )−( 1 −σ k )", "output": {"entities": {"named_data": ["WITS-Trains", "WITS-Comtrade"], "descriptive_data": [], "vague_data": ["trade\n\n\ndata"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003822", "page": 15, "chunk": 0, "title": "wps4615", "pdf_url": "https://local/prwp/wps4615.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "WITS-Trains", "label": "NAMED_DATA", "score": 0.6031598448753357, "start": 699, "end": 710, "probe_score": 0.9182, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "trade\n\n\ndata", "label": "VAGUE_DATA", "score": 0.6236082911491394, "start": 806, "end": 818, "probe_score": 0.996, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "WITS-Comtrade", "label": "NAMED_DATA", "score": 0.6063221096992493, "start": 829, "end": 842, "probe_score": 0.9687, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "MEMDIREA Environment and Social Management Framework (ESMF) September 2006\n\n\nAny other group of persons that has not been mentioned above but is\nentitled to compensation according to the laws of Uganda and World Bank\npolicies.\n\n\nPersons who encroach the area after the resettlement survey (census and\nvaluation) are not eligible to compensation or any form of resettlement\nassistance.\n\n\n**9.** **System for Complaints and Grievances**\n\n\nIt is envisaged that a number of issues (grievances) will arise as a result of land\nacquisition by the project. A system ought to be put in place to settle these issues\namicably through recognised institutions to the satisfaction of involved parties.\n\n\nAlthough affected people will be given an opportunity to review the survey results and\ncompensation policies during the process of resettlement planning and\nimplementation, a number of issues may arise among the settlers during\nimplementation. If a person is not satisfied with the compensation or rehabilitation\nmeasure given, he could raise a complaint through the mechanism that will have been\nput in place.\n\n\nIn order to address the above concerns, a Grievance Committee shall be formed before\nimplementation. Such a committee should be formed at the village level and may\ninclude Local Council members, representatives of the affected persons (1 man and 1\nwoman) and one representative from the sponsor. Issues concerning the way the\ncompensation /benefits have been handled in families should also be brought to the\ncommittee.\n\n\nIf the person complaining still does not agree with the decision of the committee, he\ncould appeal to the Probation Officer of the local government based at every district. If\nhe still does not agree to the decision, he could go to the court as a last option.\n\n\nI **10.** **Resettlement funding, Time Frame and Budget**\n\n\nThe resettlement budget for the proposed ERT project components will be fully\nincluded in the total project cost, which will be funded by the sponsor. Approval of the\nproject proposal by a sponsor will be dependent on", "output": {"entities": {"named_data": [], "descriptive_data": ["resettlement survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013016", "page": 70, "chunk": 0, "title": "Uganda - Energy for Rural Transformation Project : environmental impact assessment", "pdf_url": "https://documents.worldbank.org/curated/en/436491468110939027/pdf/E470ocr0Vol-01.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "resettlement survey", "label": "DESCRIPTIVE_DATA", "score": 0.8791078329086304, "start": 269, "end": 288, "probe_score": 0.2883, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**<br>(-2.98)|0.920***<br>(3.62)|-0.308<br>(-1.48)|\n|Hard peg dummy|-4.34***<br>(-8.60)|0.593*<br>(1.76)|-0.978***<br>(-6.44)|\n|Political stability<br>(0 to 100)|0.455***<br>(19.36)|-0.0290**<br>(-2.58)|0.0994***<br>(11.80)|\n|n|1,286|1,232|1,128|\n|R-squared|0.275|0.083|0.107|\n|RMSE|7.75|3.90|3.04|\n\n\n_Note:_ Figures in parentheses are robust t-statistics. *, **, ***: significant at 10, 5, and 1 percent\n\n\nrespectively. Annual data from 1996–2013 for low- and middle-income countries. RMSE = root\n\n\nmean square error, or sample standard deviation.\n\n\n19", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Annual data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006594", "page": 20, "chunk": 1, "title": "wps7552", "pdf_url": "https://local/prwp/wps7552.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Annual data", "label": "VAGUE_DATA", "score": 0.7095738649368286, "start": 421, "end": 432, "probe_score": 0.9887, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["M&E data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016466", "page": 29, "chunk": 2, "title": "Uganda - Second Structural Adjustment Credit (SAC II)", "pdf_url": "https://documents.worldbank.org/curated/en/672071468782392987/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "M&E data", "label": "VAGUE_DATA", "score": 0.5883201956748962, "start": 530, "end": 538, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Table 11. Origin of asylum applicants in Europe by quarter, 2008<br>Covering 38 European countries which provided monthly data to UNHCR.|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|Col10|Col11|Col12|Col13|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|\n|Origin|No. of applications|No. of applications|No. of applications|No. of applications|No. of applications|Change (%)|Change (%)|Change (%)|Share (%)|Share (%)|Share (%)|Share (%)|\n|Origin|Q1|Q2|Q3|Q4|Total|Q2-Q1|Q3-Q2|Q4-Q3|Q1|Q2|Q3|Q4|\n|Iraq|10,327<br>|8,491<br>|10,135<br>|10,030<br>|38,983<br>|-18%|19%|-1%|16.6<br>|13.8<br>|13.2<br>|12.4<br>|\n|Somalia|3,335<br>|4,110<br>|6,486<br>|7,114<br>|21,045<br>|23%|58%|10%|5.4<br>|6.7<br>|8.5<br>|8.8<br>|\n|", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["monthly data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000810", "page": 21, "chunk": 0, "title": "Asylum Levels and Trends in Industrialized Countries 2009 - Statistical Overview of Asylum Applications Lodged in Europe and selected Non-European Countries", "pdf_url": "https://reliefweb.int/attachments/771525db-5c40-325c-8321-aedadd127619/1EAB689A39141C4EC12576EF004A52BC-UNHCR_Mar2010.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "monthly data", "label": "VAGUE_DATA", "score": 0.693744957447052, "start": 115, "end": 127, "probe_score": 0.7569, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and associated\nsanctions would likely affect Djibouti’s external account through higher import bills.\n\n4. **Although classified as a lower middle-income country, high rates of inequality persist, as reflected in a**\n**Gini coefficient of 0.42** . Despite recent economic growth and trend of decreasing inequality, an estimated 17\npercent of Djiboutians live in extreme poverty (less than US$ 1.90/day) based on the 2017-18 household survey.\nThis extreme poverty rate is estimated to have increased to 23-30 percent due to the impoverishing effects of the\nCOVID-19 pandemic. Poverty is pervasive in Djibouti with 74 percent of refugees living on less than US$3 per day <sup>1</sup> .\nWhile rural areas comprise only 15 percent of the total population, they account for 45 percent of the poor. There\nare significant regional disparities in poverty levels: 10 percent in Djibouti City (mostly concentrated in the suburb\n\n\n1 United Nations High Commissioner for Refugees (UNHCR), 2017 data.\n\n\nPage 7 of 64", "output": {"entities": {"named_data": [], "descriptive_data": ["2017-18 household survey"], "vague_data": ["2017 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000131", "page": 11, "chunk": 2, "title": "Djibouti - Health System Strengthening Project", "pdf_url": "http://documents1.worldbank.org/curated/en/772381653594094662/pdf/Djibouti-Health-System-Strengthening-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2017-18 household survey", "label": "DESCRIPTIVE_DATA", "score": 0.9037479162216187, "start": 416, "end": 440, "probe_score": 0.9386, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2017 data", "label": "VAGUE_DATA", "score": 0.6559169292449951, "start": 977, "end": 986, "probe_score": 0.9804, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "CURRENCY EQUIVALENTS\n\n\n(Exchange Rate Effective: March 6, 2015)\n\n\nCurrency Unit = LBP Lebanese Pound\n\n1,503.51 Lebanese Pounds = US$1\n\nFISCAL YEAR\nJanuary 1                  - December 31\n\n\nABBREVIATIONS AND ACRONYMS\n\n\nCMU Country Management Unit (WB)\nCPS Country Partnership Strategy\nDfID Department for International Development (UK)\nDG Director General\nDOPS Pedagogical and Scholastic Guidance Office ( _Direction d’Orientation_\n_Pédagogique et Scolaire_\nECD Early Childhood Development\nECE Early Childhood Education\nECERS Early Childhood Environment Rating Scale\nECRD Educational Center for Research and Development\nECU Engineering Coordination Unit (MEHE)\nEDI Early Development Instrument\nEDP Education Development Project\nEDP II Second Education Development Project\nEESSP Emergency Education System Stabilization Project\nEMIS Education Management Information System\nESDS Educational Sector Development Secretariat\nESIA Economic and Social Impact Assessment\nESPISP II Second Emergency Social Protection Implementation Support Project\nETF European Training Foundation\nEU European Union\nGDP Gross Domestic Product\nGIS Geographic Information System\nGOL Government of Lebanon\nIBRD International Bank for Reconstruction and Development\nICB International Competitive Bidding\nIE Impact Evaluation\nKG Kindergarten\nLAES Lebanese Association for Educational Studies\nLAQA Lebanese Agency of Quality Assurance\nLSIN Lebanon School Improvement Network", "output": {"entities": {"named_data": ["GIS Geographic Information System"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000099", "page": 1, "chunk": 0, "title": "Lebanon - Emergency Education System Stabilization Project", "pdf_url": "http://documents1.worldbank.org/curated/en/578481467991017996/pdf/PAD1190-PAD-P152848-PUBLIC-Box391435B-LB-EESSP-Final-PAD-for-printing.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "GIS Geographic Information System", "label": "NAMED_DATA", "score": 0.6262727975845337, "start": 1117, "end": 1150, "probe_score": 0.0042, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<br>|\n|Jhalakathi Pourashava<br>|2015<br>|\n|SHP, Sherpur<br>|2015<br>|\n|Brahmanbaria Pourashava<br>|2015|\n\n\n\n_10._ _Vietnam:_ We have information about the tariff structure for only three utility providers\nserving some of the largest of the five provinces covered by the household survey. We\nuse that information for households, plus impute unit prices and quantities for the other\ntwo areas using the median of the estimated price and quantities for those for which\nwe have area-specific information. Vietnam has a large number of utility providers\n(around 180) scattered over the roughly 60 provinces in the national territory. Table A.5\nlists the information from IBNET that we use in practice in the analysis.\n\n\n\n\n\n\n\n\n|le A.5 Utilities and tariff structure in Vietnam Utility|Year of tariff structure used|\n|---|---|\n|<br>Utility<br>|Year of tariff structure used<br>|\n|Hanoi Water Supply Co. Ltd, Ha Noi City<br>|2015<br>|\n|Sai Gon Water Supply Corporation, Ho Chi Minh City<br>|2013|\n|Binh Duong Water Supply, Sewerage and<br>Environment Co. Ltd, Thu Dau Mot City<br>|2016|\n\n\n\n26", "output": {"entities": {"named_data": ["IBNET"], "descriptive_data": ["household survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002124", "page": 27, "chunk": 1, "title": "study of the distributional performance of piped water consumption subsidies in 10 developing countries", "pdf_url": "https://local/prwp/study-of-the-distributional-performance-of-piped-water-consumption-subsidies-in-10-developing-countries.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household survey", "label": "DESCRIPTIVE_DATA", "score": 0.8712669014930725, "start": 271, "end": 287, "probe_score": 0.9627, "gold": "DATA_MENTION", "gold_tier": "flip"}, {"text": "IBNET", "label": "NAMED_DATA", "score": 0.816826581954956, "start": 667, "end": 672, "probe_score": 0.9555, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "UFA 1 corresponds to the Old City of Homs, a traditional,\nmiddle-income area that housed mixed-use functions,\nincluding residential, commercial and light crafts. The area\nwas severely destroyed during the war. UFAs 2 and 4 are\ncontemporary extension areas with a modern building typology\nand service networks housing mostly upper-income groups. In\nthis classification, UFA 2 refers specifically to the first planned\nexpansion outside the historic boundaries of the city, while UFA 4\nrefers to the post-1980s modern expansion of the city. Unlike the\nabove-mentioned three areas, UFAs 3 and 5 comprised mostly\ninformal housing and market areas developed at the outskirts of\nthe old city on the eastern, southern and northern sides for UFA\n3, and further away to the east for UFA 5.\n\n\n\nof confidence. Household samples for each of the five UFAs\nwere randomly drawn from the UNHCR registration database,\nwhich records sub-city place of origin in Syria, and these were\nthen geolocated in Lebanon. The number of registered cases in\nLebanon from each UFA in Homs City was determined through a\nfirst round of pre-sampling via phone interviews **(Table 1)** .\n\n\nSubsequently, both quantitative and qualitative data-collection\ntools were used. In the summer of 2017, a household (HH) survey\nwas conducted in Lebanon with a cluster of 1,514 households\n(covering 6,767 persons) from the five UFAs of Homs. The survey\ncovered questions on HLP issues in both Lebanon and Syria,\nrefugees’ civil documentation, displacement (from Syria and\nwithin Lebanon), mobility within Lebanon, perceived barriers\nto return and access to information about their HLP rights.\nIndividuals who responded to the questionnaire were asked\nto identify themselves as, or their relation to, the head of the\nhousehold. The survey enquired households about how they\naccessed shelter, what percentage of their income they spent\non rent and other housing costs, what condition their shelter", "output": {"entities": {"named_data": ["UNHCR registration database"], "descriptive_data": ["household (HH) survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000666", "page": 12, "chunk": 0, "title": "Housing, Land and Property Issues of Syrian Refugees in Lebanon from Homs City: Implications of the Protracted Refugee Crisis - November 2018", "pdf_url": "https://reliefweb.int/attachments/6238875a-e7b0-3fcd-966d-e03e4d130ae9/UNHABITAT-UNHCR_HLP%20ISSUES%20OF%20SYRIAN%20REFUGEES%20IN%20LEBANON%20FROM%20HOMS_NOV%202018_web.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR registration database", "label": "NAMED_DATA", "score": 0.8951225876808167, "start": 871, "end": 898, "probe_score": 0.9853, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "household (HH) survey", "label": "DESCRIPTIVE_DATA", "score": 0.7916990518569946, "start": 1259, "end": 1280, "probe_score": 0.939, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "lines in the first years of primary school. <sup>13</sup> [^13: According to MOE data for the 2015‐2016 academic year, enrollment is similar for girls and boys.] Limited specialized in‐service training opportunities and\npedagogical support constrain KG teachers’ ability to structure learning around age‐appropriate and\nplay‐based activities that stimulate child development and early noncognitive skills. This, coupled with\na lack of an efficient quality assurance system for KGs means that there is no mechanism to monitor\nprogress or incentivize continuous quality improvements, and likely is restricting the ECE’s\ncontribution to children’s school readiness in the country. The 2014 Early Development Instrument,\nfor example, revealed that a quarter of children enrolled in public KG2 in Jordan are “not ready to\nlearn”, mainly due to inadequate levels of socioemotional development. As such, expanding access\nand ensuring quality in the provision of KG are likely to transform Jordanian and non‐Jordanian\nstudents’ ability to learn and succeed in school.\n\n12. **Poor student learning outcomes at all levels are a challenge in Jordan.** One in five students in\ngrade 2 cannot read a single word from a reading passage, while nearly half are unable to perform a\nsingle subtraction task correctly, thus lacking the foundational literacy and numeracy skills that enable\nfurther cognitive skill development. <sup>14</sup> [^14: Latest (2012) EGRA and EGMA scores for Jordan.] With a weak start, skills deficits compound such that by age 15,\ntwo‐thirds of students do not meet the most basic level of proficiency in mathematics, and half are\nbelow basic proficiency in reading and science, as measured by the 2015 Program for International\nStudent Assessment (PISA). Furthermore, learning outcome data show a reverse gender gap with girls\nperforming better than boys in reading, mathematics, and science. <sup>15</sup> [^15: PISA 2015] International comparisons place\nJordan in", "output": {"entities": {"named_data": ["MOE data", "2015 Program for International\nStudent Assessment"], "descriptive_data": [], "vague_data": ["learning outcome data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000127", "page": 11, "chunk": 0, "title": "Jordan - Education Reform Support Program-for-Results Project", "pdf_url": "http://documents1.worldbank.org/curated/en/731311512702123714/pdf/Jordan-Educ-Reform-121282-JO-PAD-11142017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "MOE data", "label": "NAMED_DATA", "score": 0.6684749722480774, "start": 77, "end": 85, "probe_score": 0.9723, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2015 Program for International\nStudent Assessment", "label": "NAMED_DATA", "score": 0.6974319219589233, "start": 1708, "end": 1757, "probe_score": 0.9959, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "learning outcome data", "label": "VAGUE_DATA", "score": 0.6706512570381165, "start": 1779, "end": 1800, "probe_score": 0.9547, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**SECTION 3**\n\n\n**3.** **DATA SOURCES**\n\n\nAt the start of the process, SWGs developed a list of information needs (i.e. those themes that they required\ninformation on within their sector). These were built from RRP6 indicators and a consultation within the\nworking group. For the purpose of Phase 1, MSNA analysts reviewed and examined the available data on\neach theme. See Section 4 for results.\n\n\nThe table below highlights the information needs and whether or not they were met by the available data. Note\nthere is data available across all information needs. However, the quality in terms of representativeness of\nlocal conditions and severity of needs is variable across groups and geographical areas.\n\n\n_Table [1]: information needs and availability of existing data/information_\n\n\n**<u><mark>Theme</mark></u>** **<u><mark>Information Need</mark></u>**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Preferred modality|Preferred modality for new arrivals (cash, vouchers or in-kind)|\n|---|---|\n|<br>Preferred modality<br>|Reasons for preference|\n|Availability of basic<br>needs<br>|Availability of essential items in local markets disaggregated<br>geographically|\n|Access to basic<br>needs|Household access to these essential items|\n|Access to basic<br>needs|Access to markets, market assessment<br>|\n|<br>Cash<br>income and<br>expenditure|Main sources of expenditure|\n|<br>Cash<br>income and<br>expenditure|Monthly income (and variety of sources, such as loans, employment,<br>remittances, etc.) and monthly expenditures (and proportion of each<br>", "output": {"entities": {"named_data": ["RRP6 indicators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000617", "page": 8, "chunk": 0, "title": "MSNA sector chapters - Basic needs", "pdf_url": "https://reliefweb.int/attachments/5ad2f3e6-32d7-35d0-bc93-27ca53c5d55b/BASIC%20NEEDS%20CHAPTER%20-%20FINAL%20April%2022.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "RRP6 indicators", "label": "NAMED_DATA", "score": 0.7985392212867737, "start": 211, "end": 226, "probe_score": 0.8645, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad Energy Access Scale Up Project (P174495)\n\n\nfor bulk procurement, for instance of popular-size solar water pumps, will be explored to reduce costs\nthrough economies of scale. Furthermore, the subcomponent will support related awareness-raising\nactivities and technical assistance for the adoption of technical standards.\n\n46. In addition, the subcomponent will provide financing to electrify about 1,000,000 households,\nincluding about 200,000 households residing in refugee camps and host communities and with targeted\nactions to support female-headed ones. The project design is informed by the outcomes of the Survey on\nExpenditure of Households and Informal Sector in Chad ( _Enquête sur la Consommation des Ménages et le_\n_Secteur Informel au Tchad_ [ECOSIT 4] 2019) and a survey on ability and willingness of rural households to\npay for electricity services, conducted in three provinces of Chad in the first half of 2021. <sup>24</sup> [^24: Select outcomes of the survey are in annex 6.] The outcomes\ninclude the following information: (a) 70 percent of the rural population and 27 percent of the urban\npopulation have financial constraints to spend more than US$10 per month for electricity; <sup>25</sup> [^25: Assuming that a household can spend up to 5 percent of its total expenditure for electricity.] (b) about 70\npercent of rural households are interested in acquiring Tier 1 SHSs, assuming that these are of good quality\nand can be made available at the price equivalent to up to three months of household expenditures on\nlighting and phone charging, that is about CFAF 10,000 (US$17.4 equivalent).\n\n47. In an effort to kick-start the market and discover market prices, the first intervention will be\norganized in the form of bulk procurement of up to 200,000 Tier 1 SHSs, split into several lots to attract\nreputable suppliers to the Chad SHS market. These SHSs will be sold in cash with the cost split between", "output": {"entities": {"named_data": [], "descriptive_data": ["survey on ability and willingness of rural households"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000193", "page": 28, "chunk": 0, "title": "Chad - Energy Access Scale Up Project", "pdf_url": "https://documents1.worldbank.org/curated/en/860701648216750651/pdf/IBArchive-bd2c789e-ee04-4df7-a219-9409a5f705d3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey on ability and willingness of rural households", "label": "DESCRIPTIVE_DATA", "score": 0.7308420538902283, "start": 801, "end": 854, "probe_score": 0.9382, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Col1|Col2|\n|---|---|\n|187,600|187,600|\n\n\n\n**IRAQ**\n246,300\n\n\n**JORDAN**\n\n641,900\n\n\n**YEMEN**\n241,300\n\n\n\n**USA**\n263,600\n\n|204,300|Col2|\n|---|---|\n|||\n\n\n\n**BOLIVARIAN**\n\n**REP. OF**\n**VENEZUELA**\n\n\nAmericas\n\n\nAsia and Pacific\n\n\nEurope\n\n\n\n**GERMANY**\n\n\n**FRANCE**\n\n232,500\n\n\n**CHAD**\n434,500\n\n\n\n**TURKEY**\n609,900\n\n\n\n**ISLAMIC**\n**REP. OF IRAN**\n\n857,400\n\n\n\n**CHINA**\n301,000\n\n\n**INDIA**\n188,400\n\n\n**BANGLADESH**\n\n\n\n**PAKISTAN**\n1.6 MILLION\n\n\n\n**SOUTH**\n**SUDAN**\n229,600\n\n\n\n**LEBANON**\n\n**856,500**\n\n\n**EGYPT**\n230,100\n\n\n**ETHIOPIA**\n\n433,900\n\n\n\nMiddle East and North Africa\n\n\n\n\n|220,600|Col2|\n|---|---|\n|||\n\n\n\nmany. Refugee figures were reduced\nfrom 589,700 at the beginning of 2013\nto 187,600 by year-end, due to an alignment of the definitions used to count\nrefugees. As a result, only those with a\nparticular protection status <sup>**(15)**</sup> are now\nincluded in the statistics reported by\nUNHCR. Persons potentially of concern\nto UNHCR but who cannot be identified as such based on the nature of their\nrecorded status are no longer taken into\naccount for statistical purposes. This\nfigure is consistent with the one used", "output": {"entities": {"named_data": [], "descriptive_data": ["statistics reported by\nUNHCR"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001229", "page": 12, "chunk": 0, "title": "UNHCR Global Trends 2013: War's Human Cost", "pdf_url": "https://reliefweb.int/attachments/bccf108d-67b2-3a0c-9f57-b3c1e40ca740/Global_Trends_report_2013_V07_web_embargo_2014-06-20.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistics reported by\nUNHCR", "label": "DESCRIPTIVE_DATA", "score": 0.7101621031761169, "start": 875, "end": 903, "probe_score": 0.5726, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "> Informality reached 42 percent among women in\n2018 and 50 percent among people with less than high-school education. Informal employment is more\nextensive in provinces that have been affected by the Syrian influx, especially the southeastern provinces,\nreflecting the absorption of Syrians able to work in informal jobs.\n\n\n10. **The influx of Syrian refugees has added additional pressure on the labor market.** As previously\nnoted, Turkey is the largest refugee-hosting country in the world, with 3.6 million Syrians. Turkey also\nhosts refugees from other countries (for example, Afghanistan and Iraq). The Syrian inflows to Turkey\nbegan in 2011, and the number of Syrian refugees in the country increased dramatically between 2013\nand 2016. The surge represented a large labor supply shock to the economy. Many Syrians able to work,\nmostly low skilled, began taking up informal jobs that paid less than the minimum wage, thereby crowding\nout native formal workers.\n\n\n11. **The high unemployment rates in refugee-hosting areas—up to 27 percent—signal the**\n**seriousness of the challenges facing local and refugee job seekers.** Most provinces, hosting high numbers\nof refugees, were already among the most disadvantaged in economic welfare and economic\nopportunities before the Syrian crisis, including a higher incidence of low-skilled workers, lower labor\nforce participation rates, and high unemployment rates relative to the national average. To prevent\nfurther deterioration in labor markets, promoting permanent formal job creation is critical.\n\n\n12. **The socioeconomic integration of refugees into the economy and improvements in livelihoods**\n**in areas with high incidence of Syrians Under Temporary Protection (SuTP) are a major challenge.** The\nfew available data sources point to the substantial participation of working-age refugees in informal jobs.\nAlthough most refugees are poor and vulnerable, many can work (around 430,000), but work informally\n(86 percent) for relatively low wages (TL 1,300 [", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data sources"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000025", "page": 14, "chunk": 1, "title": "Turkey - Formal Employment Creation Project", "pdf_url": "http://documents1.worldbank.org/curated/en/211181585965751622/pdf/Turkey-Formal-Employment-Creation-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data sources", "label": "VAGUE_DATA", "score": 0.6611426472663879, "start": 1775, "end": 1787, "probe_score": 0.2619, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### PROTECTION ANALYSIS UPDATE – Q2\n\n#### 3.6 Mine Action\n\nThe HH survey revealed that a majority (86%) lack awareness about mines and other explosives. However, KII\nfindings reported the opposite wherein 42% confirmed awareness.\n\n\nKey effects of mines reported by those who had awareness or information are primarily related to access, in\nparticular safety for children when playing (33%), and children not being able to go to school (22%), while others\nreported concerns on, people not being able to access services (16%), effects on livelihood such as cannot graze\n(14%), and household chores such as collecting water (13%).\n\n\nDRC has conducted Rapid Protection Assessment (RPA) in Kandahar province in February 2021, which revealed\nthat IDPs reported that all of their orchards, streets and main routes have been contaminated with dangerous\nIEDs (improvised explosive devices) in their area of origin (AoO) i.e. Panjwaye, Arghandab, and Zhari districts of\nKandahar province.\n\n\nDuring RPA in Ghazni Province in May 2021, IDPs reported Explosive Remnants of War (ERW) and mines on the\nway from Qarabagh district to displaced location (Saqafat Islamia). They reported that these were placed by\nArmed Opposition Groups (AoGs). They further reported that they are unaware of mine placements, therefore,\nwere very scared en route to displacement locations.\n\n\nDuring another RPA in Ghazni province in June, IDPs reported landmines on the main route from Khawaja Omari\ndistrict to displaced locations, placed by AOGs. IDPs further reported ERWs and mines in Nawabad village (area of\ndisplacement). They reported that these were placed by AOGs. They further specified that mines are handmade.\nMen reported that they are aware of mines and take necessary precautions, but women and children are unaware", "output": {"entities": {"named_data": ["HH survey", "KII\nfindings"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000210", "page": 18, "chunk": 0, "title": "Afghanistan: Protection Analysis Update 2021 - QUARTER 2", "pdf_url": "https://reliefweb.int/attachments/161c6015-b7f8-3159-9361-72ffae217a11/protection_analysis_update_-_q2.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "HH survey", "label": "NAMED_DATA", "score": 0.7693900465965271, "start": 63, "end": 72, "probe_score": 0.976, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "KII\nfindings", "label": "NAMED_DATA", "score": 0.5589842796325684, "start": 162, "end": 174, "probe_score": 0.9879, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Figure 1: Centrality of Fortune 500 Agribusiness Companies\n\n\n\n\n\n\n\n\n\n\n\n**Note:** The graph shows the average number of customer and supplier links (“degree centrality”) for actively\ncovered U.S. Fortune 500 agribusiness companies and other U.S. firms over time. Fortune 500 agribusinesses are identified from the March 2022 list of U.S. Fortune 500 companies. The left graph depicts the\ndegree centrality of actively covered enterprises based on their links to all firms observed in the network in\na given year, the right graph depicts the degree centrality of actively covered enterprises while including\nonly links between firms that are constantly observed in the sample (that is excluding any entrants or exiters between 2014 and 2024).\n\n\nRecent data reveal a strategic shift among U.S. Fortune 500 companies, with a dis\n\ncernible focus since 2018 towards strengthening intra-corporate linkages—particularly\n\n\nownership ties—over external customer and supplier relationships. This shift towards\n\n\ninternal consolidation is clearly illustrated in Figure 2 (left panel), which demonstrates a\n\n\nnotable increase in ownership-related ties, all consolidated under the same ultimate par\n\nent entity, within these prominent corporations. The trend is visible both at the average\n\n\n(upper left panel) and at the median (lower left panel). While U.S. non-Fortune 500 and\n\n\nagri-food firms from the rest of the world also exhibit an increase in ownership-related\n\n\naffiliations by 2021, the growth in these connections significantly lags behind their expan\n\nsions in supplier and customer links, especially when analyzed at the median level. This\n\n\nindicates a more subdued inclination toward internal network densification among either\n\nsmaller corporations or non-U.S. firms. <sup>18</sup> Moreover, the rise in ownership links among\n\n\nU.S. Fortune 500 companies within the agribusiness sector closely tracks their increase\n\n\nin traditional business connections, suggesting a strategic integration of their corporate\n\n\nstructure with their primary business operations. In stark", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Recent data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001443", "page": 18, "chunk": 0, "title": "idu19259bafa1bb4d142ff1911e17c9fd0189bda", "pdf_url": "https://local/prwp/idu19259bafa1bb4d142ff1911e17c9fd0189bda.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Recent data", "label": "VAGUE_DATA", "score": 0.5288823843002319, "start": 742, "end": 753, "probe_score": 0.9982, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "10\n\n\n**_3.3 The financial cost of corruption_**\n\n\n**Figure 5: Average bribes to “get things done” (%**\n\n**of sales) and to secure public contracts (% of**\n\n**contract)**\n\n10\n\n\n7.8\n7.0\n6.2\n\n\n\nOn average, Mauritanian firms\n\n\nmake informal payments to “get\n\n\nthings done” of about 4.8 percent\n\n\nof the annual sales and of 7.7\n\n\npercent of the contract value to\n\n\nsecure contracts with the\n\n\ngovernment. Survey results show\n\n\nbribes in percentage of the sales\n\n\nincrease with size up to a point\n\n\nand then decrease. Medium\n\n\ncompanies are the ones that pay\n\n\n\n5\n\n\n0\n\n\n\n|Col1|Col2|\n|---|---|\n|||\n\n\n|Col1|Col2|\n|---|---|\n|||\n\n\n|Col1|Col2|\n|---|---|\n|||\n\n\n|Col1|Col2|\n|---|---|\n|||\n\n\nMicro Small Medium Large\n\n\n\n_Source: Mauritania ICS, 2006_\n\n\n\na larger percentage of their sales (7.8 percent). <sup>8</sup> [^8: The size categories are (number of employees): micro (1-5); small (6-10); medium (11-20), and large\n(more than 21). Employment is a variable with a left-skewed distribution, which makes it difficult to create\nan even distribution for the four size categories.] To secure government contracts, medium\n\n\nand large firms report to pay, on average, 7.8 and 7.0 percent of the contract value,\n\n\nrespectively, while micro and small firms pay on average 4.5 and 6.2 percent (See Figure\n\n\n5). Furthermore, the payment of bribes as a percentage of sales are, on average, larger for\n\n\nfirms with foreign capital, and with accounts audited externally (see Annex 6).\n\n\n\nThe average payment of firms", "output": {"entities": {"named_data": [], "descriptive_data": ["Survey results"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003646", "page": 11, "chunk": 0, "title": "wps4439", "pdf_url": "https://local/prwp/wps4439.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Survey results", "label": "DESCRIPTIVE_DATA", "score": 0.5740684270858765, "start": 400, "end": 414, "probe_score": 0.9992, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the GOJ, while providing a buffer\nto help mitigate the impact of price risks driven by the current volatility and uncertainty in international\ncommodity markets, in particular on vulnerable households in Jordan. On the other hand, the investment and\nadvisory activities supported under Component 2 will contribute directly to strengthening the GOJ’s physical and\ninstitutional capacities over the medium-term to address future shocks in global commodity markets. These\ncapacity improvements will be driven by expanded physical grain storage capacities and an improved knowledge\nand information base to guide targeted investments and policy reforms in commodity value chains and regional\ntrading systems.\n\n**43.** **The ultimate results, going beyond the scope and lifetime of this project but being facilitated by it, are**\n**expected to be** : (i) more efficient and resilient import supply chains for basic agricultural commodities in Jordan,\n(ii) a more fiscally sustainable policy framework to strengthen food security and protect the most vulnerable\nhouseholds, and (iii) improved regional collaboration on managing supply and price risks associated with imports\nof basic agricultural commodities. To achieve this, the following gradual approach has been embedded in the\nproject design:\n\n\n(i) _In the short term (0-9 months)_, the focus will be on (i) ensuring minimum required levels of strategic\nreserves of wheat and barley are maintained; and (ii) analyzing options for improving import supply chain\nlogistics for selected agricultural commodities and for broader food policies to mitigate future shocks in basic\nagricultural commodity markets.\n(ii) _In the medium term (9-18 months)_, the focus will be on (i) investing in strategic grain storage capacities;\n\n\n34 The vulnerable households (poor Jordanian population and refugees, respectively) will be drawn and sampled based on the current WFP\nand UNHCR databases, respectively. The indicator will track bread consumption, specifically, rather than food security more broadly; the\nactual values will be determined through the high frequency surveys foreseen during project", "output": {"entities": {"named_data": ["UNHCR databases"], "descriptive_data": ["high frequency surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 24, "chunk": 1, "title": "Jordan - Emergency Food Security Project", "pdf_url": "http://documents.worldbank.org/curated/en/486071652556836130/pdf/Jordan-Emergency-Food-Security-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR databases", "label": "NAMED_DATA", "score": 0.7530885338783264, "start": 1911, "end": 1926, "probe_score": 0.9411, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "high frequency surveys", "label": "DESCRIPTIVE_DATA", "score": 0.7829908728599548, "start": 2089, "end": 2111, "probe_score": 0.2232, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["M&E data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000086", "page": 29, "chunk": 2, "title": "Uganda - El Nino Emergency Road Repair Project", "pdf_url": "http://documents1.worldbank.org/curated/en/519721468760234014/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "M&E data", "label": "VAGUE_DATA", "score": 0.5883201956748962, "start": 530, "end": 538, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\n24. Combined with quick wins, the ECRP will target both conflict-affected and more stable counties\nas shown below.\n\n\n**Figure 2. Vulnerable Counties with Quick Wins**\n\n\n25. **Subproject budget allocation.** The subproject budget allocation for the new counties will be\ncalculated on a per capita basis using humanitarian agencies’ latest population data. There will be two\nrounds of allocations per county to maximize communities’ learning by doing. Counties will need to meet\na set of basic performance indicators to be eligible for the second allocation. These include (a)\nparticipation rate of women, youths, IDPs, and returnees in the subproject planning and implementation;\n(b) satisfactory collaboration during community mobilization; (c) timely implementation of the\nsubprojects; and (d) continued accessibility and permissive security. Allocations to the _payam_ level will\nfollow the Government’s fiscal transfer formula of 60 percent equal allocation and 40 percent based on\npopulation (utilizing IOM’s DTM projections) whereas all _bomas_ within target _payams_ will receive equal\namount of funding as no population data are available. <sup>47</sup> [^47: Population figures for urban areas would be calculated based on a headcount or by complementing 2008 census with other\ndata sources (for example, DTM.)]\n\n\n26. **Use of community labor.** The project will encourage contractors to utilize local labor in the\ninfrastructure construction or rehabilitation to the extent possible. Emphasis will be placed on the\ninclusion of various social groups facing marginalization or barriers to participation (for example, women,\nyouth, returnees, ethnic minority groups, and people with disabilities) and ensuring their access to daily\nwage labor opportunities. It will be especially important to include women in the design and construction\nof WASH facilities, for instance, to ensure these facilities are rehabilitated in ways that promote security\nand effective management on completion. The project will harmonize", "output": {"entities": {"named_data": ["DTM projections"], "descriptive_data": [], "vague_data": ["population data", "population data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000058", "page": 11, "chunk": 0, "title": "Project Information Document - South Sudan Enhancing Community Resilience and Local Governance Project - P169949", "pdf_url": "http://documents.worldbank.org/curated/en/890401593099068599/pdf/Project-Information-Document-South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project-P169949.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "population data", "label": "VAGUE_DATA", "score": 0.6232211589813232, "start": 441, "end": 456, "probe_score": 0.9692, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "DTM projections", "label": "NAMED_DATA", "score": 0.5524219870567322, "start": 1116, "end": 1131, "probe_score": 0.9413, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "population data", "label": "VAGUE_DATA", "score": 0.5372234582901001, "start": 1219, "end": 1234, "probe_score": 0.7169, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " of\nemployment in urban areas is in the informal sector <sup>2</sup>, characterized by low productivity and wages. In\naddition, congestion and lack of public transport options in many cities restricts the movement of goods and\npeople. The quality of housing remains inadequate for a large proportion of the urban population, with more\nthan 60 percent of the residents of urban areas living in slums. Finally, the delivery of social services of an\nadequate quality to a rapidly expanding urban population is also a source of concern <sup>3</sup> .\n\n4. **_Rapid Urbanization has resulted in a huge infrastructure backlog_** **.** For example, the backlog of\nbituminized roads in the 14 Municipalities targeted in the current phase of USMID was estimated at around\n\n\n1 Currently the Program targets 14 municipalities, namely: Arua, Gulu, Lira, Mbale, Soroti, Tororo, Jinja, Entebbe, Masaka, Mbarara,\nKabale, Fort Portal, Hoima, and Moroto.\n2 Uganda Urban Labor Force Survey 2009.\n3 World Bank. 2015. _The growth challenge: Can Ugandan cities get to work?_ . Washington, DC: World Bank Group.\n\n\n1", "output": {"entities": {"named_data": ["Uganda Urban Labor Force Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000014", "page": 8, "chunk": 2, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents1.worldbank.org/curated/en/143681526614252328/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Uganda Urban Labor Force Survey", "label": "NAMED_DATA", "score": 0.8546139597892761, "start": 939, "end": 970, "probe_score": 0.9985, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">full<br>documentation<br>for all changes<br>made to<br>personnel<br>records each<br>month and<br>checked<br>against the<br>previous<br>month's<br>payroll data.<br>Staff hiring and<br>promotion is<br>controlled by a<br>list of<br>approved staff<br>positions.|Col7|value of<br>procurement,<br>and who has<br>been awarded<br>contracts; (iii)<br>Approved staff<br>lists, personnel<br>database, and<br>payroll are<br>directly linked<br>to ensure<br>budget<br>control, data<br>consistency,<br>and monthly<br>reconciliation.|Col9|\n|---|---|---|---|---|---|---|---|---|\n||Comments on<br>achieving targets|Comments on<br>achieving targets|On track|On track|On track|On track|On track|On track|\n|**Enhanced External Audit and Oversight**|**Enhanced External Audit and Oversight**|**Enhanced External Audit and Oversight**|**Enhanced External Audit and Oversight**|**Enhanced External Audit and Oversight**|**Enhanced External Audit and Oversight**|**Enhanced External Audit and Oversight**|**Enhanced External Audit and Oversight**|**Enhanced External Audit and Oversight**|\n|Indicator Name|Baseline|Baseline|Actual (Previous)|Actual (Previous)|Actual (Current)|Actual (Current)|Closing Period", "output": {"entities": {"named_data": [], "descriptive_data": ["payroll data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003145", "page": 7, "chunk": 1, "title": "Disclosable Version of the ISR - Second Program for Strengthening Governance for Enabling Service Delivery and Public Investment in Kenya - P180287 - Sequence No : 4", "pdf_url": "https://documents.worldbank.org/curated/en/099062325062042541/pdf/P180287-fdba7ace-0c1a-411d-8b72-34ffeff258d6.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "payroll data", "label": "DESCRIPTIVE_DATA", "score": 0.8210453987121582, "start": 147, "end": 159, "probe_score": 0.4954, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " captured in the Health\nInformation System.\n**Contracting and Provider Payment Mechanism**\nThe MoPH purchases the package of services for the beneficiary population from PHCCs. Provider payment is\nbased on capitation and is output-based. The average per capita cost is estimated at US$60, based on the actual\nprices that prevail in the markets for medical goods and services and MoPH rates. Contracts between the MoPH\nand PHCCs define the responsibilities and obligations of each party, the number of NPTP beneficiaries to be\ntargeted, services offered, contract value, clinical and financial reporting requirements, disbursement\nrequirements, and payment mechanisms. The PHCCs are responsible for ensuring that all diagnostic tests are\nreceived according to clinical guidelines set by the MoPH. To set correct incentives for PHCCs, the per capita\npayment is divided into three parts: (i) one part is a contract advance, (ii) the second is based on the use of\nservices by beneficiaries, and (iii) the third is based on user satisfaction, which is monitored through third party\nassessment and internally by the MoPH.\n\n\n14. **While the EPHRP has generated some promising results, it has also highlighted some early**\n**lessons, including the need to expand the scale and scope of primary-level service delivery.**\nConcerning the _scale_, there is an urgent need to support the Government’s plan to expand the ability of\nthe PHC system to meet the growing demand by increasing the capacity and the number of contracted\nnetwork centers from 75 to 204 and the number of beneficiaries from 350,000 to 925,000 for both\ndisplaced Syrians and host communities (see Table 1). The _scope_ of the services also requires expansion\nto take into account the growing needs in the areas of reproductive care (including GBV dimensions),\nmental health, NCDs, and elderly care. Because of the growing social and behavioral challenges", "output": {"entities": {"named_data": [], "descriptive_data": ["Health\nInformation System"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000032", "page": 16, "chunk": 1, "title": "Lebanon - Health Resilience Project", "pdf_url": "http://documents.worldbank.org/curated/en/616901498701694043/pdf/Lebanon-Health-PAD-PAD2358-06152017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Health\nInformation System", "label": "DESCRIPTIVE_DATA", "score": 0.5583975315093994, "start": 17, "end": 42, "probe_score": 0.1107, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Polish women.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 29. Effect of a 1 pp. change in employment share of Ukrainian refugees on gross wage change**\nCross-section model of all 380 poviats in 2023. Results are statistically significant at a 0.01 level.\n\n\n200\n\n\n150\n\n\n100\n\n\n50\n\n\n0\n\nOLS IV (pupils) IV (2019) IV (both)\n\nSource: Deloitte own elaboration based on GUS and ZUS data, as well as data for instrumental variables from Public Employment Services Portal and Open Data\ngovernmental portal. OLS is the standard Ordinary Least Squares model, IV are Instrumental Variables Two Stage Least Squares models with instrumental variables of\nthe share of Ukrainian pupils in Polish schools, distribution of Ukrainians from declarations on entrusting work to a foreigner in Poland in 2019, or both. For details see\nthe Online Technical Appendix.\n\n\n\nFurthermore, consistent with a positive\nproductivity shock, Polish citizens have\nbeen moving to better-paid occupations –\nas predicted by the theory of occupational\nupgrading (e.g., Beerli and Peri, 2018; Foged\nand Peri, 2016; Peri and Sparber, 2009).\nDeloitte has acquired quarterly data on\nthe occupational groups of Polish citizens\nwho are insured with ZUS from Q1 2022 to\nQ2 2024. This data is not exhaustive as ZUS\nonly began requiring such information in\n\n\n\ntowards higher-paid occupational groups.\nThe share of Poles in the two lowest\nsalary brackets (earning less than gross\nPLN 4,000 and PLN 4,000-6,000 in 2022)\ndecreased by 0.4 and 1.8 percentage\npoints, respectively, while the subsequent\nhigher salary brackets increased by\n1.4 pp. (PLN 6,000-8,000), 0.6 pp.\n(PLN 8,000-10,000), and 0.3 pp. (above\nPLN 10,000) (see", "output": {"entities": {"named_data": ["GUS", "ZUS data"], "descriptive_data": ["data for instrumental variables"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 20, "chunk": 1, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "GUS", "label": "NAMED_DATA", "score": 0.7296446561813354, "start": 405, "end": 408, "probe_score": 0.0061, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "ZUS data", "label": "NAMED_DATA", "score": 0.7645020484924316, "start": 413, "end": 421, "probe_score": 0.969, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data for instrumental variables", "label": "DESCRIPTIVE_DATA", "score": 0.6019461154937744, "start": 434, "end": 465, "probe_score": 0.8616, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", WFP and partners (international/national NGOs) will support governance oversight.|Risk Management: <br>Strong fiduciary, technical implementation and management oversight will be established. Communication and<br>awareness campaigns will be carried out to facilitate access to information that all stakeholders need for effective<br>decision-making. FAO, WFP and partners (international/national NGOs) will support governance oversight.|Risk Management: <br>Strong fiduciary, technical implementation and management oversight will be established. Communication and<br>awareness campaigns will be carried out to facilitate access to information that all stakeholders need for effective<br>decision-making. FAO, WFP and partners (international/national NGOs) will support governance oversight.|Risk Management: <br>Strong fiduciary, technical implementation and management oversight will be established. Communication and<br>awareness campaigns will be carried out to facilitate access to information that all stakeholders need for effective<br>decision-making. FAO, WFP and partners (international/national NGOs) will support governance oversight.|Risk Management: <br>Strong fiduciary, technical implementation and management oversight will be established. Communication and<br>awareness campaigns will be carried out to facilitate access to information that all stakeholders need for effective<br>decision-making. FAO, WFP and partners (international/national NGOs) will support governance oversight.|Risk Management: <br>Strong fiduciary, technical implementation and management oversight will be established. Communication and<br>awareness campaigns will be carried out to facilitate access to information that all stakeholders need for effective<br>decision-making. FAO, WFP and partners (international/national NGOs) will support governance oversight.|\n||Risk Description: <br>Political interference and capture of investments by elites: Local<br>leaders may not be fully on board with the project; local elites or<br>political leaders may intervene to divert some investments from<", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000007", "page": 53, "chunk": 7, "title": "Chad - Emergency Food and Livestock Crisis Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/179061468215115488/pdf/PAD11010PAD0P1010Box385329B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 0.61 0.09 0.43 -0.10* -0.04 -0.04\nAutomated process with machines or tractors 0.08 0.43 0.06 0.36 -0.03 0.00 0.01\n**Storage**\nHigh-end central storage facilities 0.13 0.45 0.12 0.44 -0.01 0.01 0.00\nContinuous temperature monitoring device 0.08 0.37 0.02 0.20 -0.06*** -0.05** -0.07**\n**Packing**\nAutomated packing 0.14 0.52 0.13 0.48 -0.01 0.02 0.02\n<u>Modified</u> <u>atmosphere</u> <u>packing</u> <u>0.08</u> <u>0.41</u> <u>0.06</u> <u>0.34</u> <u>-0.02</u> <u>-0.01</u> <u>-0.01</u>\n\n\nNote: Table shows averages for baseline using sampling weights. The fifth column presents the unconditional difference, the\nsixth column presents the coefficients of linear regressions of each variable on female top management controlling for country\nfixed effects, and the seventh column adds sector and size group dummies. - p _<_ 0.10, ** p _<_ 0.05, *** p _<_ 0.01.\n\n\nTable B4: Difference in technology adoption between female and male top managers in Food\nProcessing\n\n\nMale Female Difference\n\n\nMean SD Mean SD Uncond. Cond. Cond.\n<u>VARIABLES</u> <u>(1)</u> <u>(", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001468", "page": 37, "chunk": 1, "title": "idu19d64fdd31725014bd11a04b1ee26fb7aba61", "pdf_url": "https://local/prwp/idu19d64fdd31725014bd11a04b1ee26fb7aba61.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEmergency Food Security Project (P178936)\n\n\n<mark>of water available per capita per year – well below the absolute water scarcity threshold of 500 cubic meters per</mark>\n<mark>capita per year), but those resources are increasingly vulnerable to climate-related hazards (Jordan ranks 72 out</mark>\n<mark>of 182 countries in the ND-GAIN index for climate vulnerability in 2019), including droughts</mark> <sup>12</sup> [^12: In 2021, Jordan experienced one of the most severe droughts in its history.\n_13_ [Jordan - Vulnerability | Climate Change Knowledge Portal (worldbank.org)](https://climateknowledgeportal.worldbank.org/country/jordan/vulnerability#:~:text=Climate%2Drelated%20hazards%20in%20Jordan,include%20periodic%20earthquakes%20and%20epidemics.)] <mark>, extreme</mark>\n<mark>temperature, storms, landslides and flash floods</mark> <sup>13</sup> <mark>.</mark> <mark>These changes are likely to have negative effects on crop</mark>\n<mark>production as they will decrease the availability of water for irrigation, diminishing the suitability of key crops and</mark>\n<mark>increase the vulnerability of smallholder farmers who are already extremely vulnerable to the impacts of climate</mark>\n<mark>change due to their low-incomes, poor access to technical capacities and lack of technology to increase</mark>\n<mark>productivity under extreme weather conditions</mark> <sup>14</sup> [^14: IPCC projections for the future indicate that by 2030 temperatures are projected to increase by 1–2ºC and that there will be a significant\nincrease in the number of crop heat stress days throughout Jordan. Climate models from the Coupled Model Intercomparison Project Phase] <mark>. In the", "output": {"entities": {"named_data": ["ND-GAIN index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000024", "page": 13, "chunk": 0, "title": "Jordan - Emergency Food Security Project", "pdf_url": "http://documents.worldbank.org/curated/en/486071652556836130/pdf/Jordan-Emergency-Food-Security-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "ND-GAIN index", "label": "NAMED_DATA", "score": 0.8144020438194275, "start": 347, "end": 360, "probe_score": 0.9709, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a proportion that has grown significantly\nover the past five years, especially among women. <sup>25</sup> [^25: See The National Employment Strategy 2011–2020: An Update and Future Directions (ILO, 2015) based on\ndata for 2009–2014.] Approximately half of Jordanian employment is\ninformal. <sup>26</sup> [^26: ILO and FAFO. “Impact of Syrian Refugees on the Jordanian Labor Market.”]\n\n\n46. A large number of highly skilled Jordanians move abroad as economic migrants, largely to\nGCC, where it is easier for them to find the salaries they aspire to. According to the MOL, there are\n425,000 Jordanians working in the GCC. <sup>27</sup> [^27: Ibid.]\n\n\n47. Among less-skilled Jordanians, there is a strong preference for work in the public sector (in\ncivil service or the army) where job security, benefits, and working hours are better than the private\nsector. As a result of the high reservation wage, many Jordanians remain unemployed as they queue for\n\n\n21 West Asia North Africa Institute. 2015. “Forging New Strategies in Protracted Refugee Crises: Syrian\nRefuges and the Host State Economy.”\n22 Mercy Corp. 2012. “Analysis of Host Community-Refugee Tensions in Mafraq, Jordan.”, Amman Net see\nammannet/sy/ and Su, A. 2015. “The Mighty Pen (2014).” _Columbia Journalism Review,_ August.\n23,23 UNHCR regularly disseminates information on evolving policies by short messaging services and other\nmeans. Most recently, UNHCR disseminated responses to frequently asked questions regarding work permit\nrequirements and procedures and impact on refugee status. http://unhcr.us6.listmanage1.com/track/click?u=21ac4d661afc676782cbf14bc&id=8bb817deb6&e=cd2e73ef4f\n24 Employment Unemployment Survey for 2015. Available online at:\n<u>http://www.dos.gov.jo/", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data for 2009–2014"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 67, "chunk": 1, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data for 2009–2014", "label": "VAGUE_DATA", "score": 0.8170782923698425, "start": 214, "end": 232, "probe_score": 0.2691, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "sup>9</sup> . This figure is almost double that of host country nationals (12%), implying a\nlarge gap in economic vulnerability. Compared to 2023, poverty rates have decreased substantially (from\n36% <sup>10</sup> ), suggesting an overall improvement in the economic well-being of Ukrainian refugees over time.\n\n\n**<u>REFUGEE VERSUS HOST POVERTY RATES BY COUNTRY</u>**\n\n\nUkrainian refugees (2024) Host country nationals (2023)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nBulgaria Czechia Hungary Moldova Poland Romania Slovakia Estonia Latvia Lithuania Region\n\n\nNote: Poverty rates for all countries apart from the Republic of Moldova are based on a calculation that follows Eurostat’s at-risk-of-poverty (AROP)\nmethodology with the at-risk-of-poverty threshold set at 50% of the national median disposable income after social transfers. Refugee disposable\nincome has been computed based on survey data. For the Republic of Moldova, the poverty threshold was taken to be the 4Q23 absolute poverty line\nreported by the National Bureau of Statistics of Moldova.\n\n\nSource: Survey data, <u>[Eurostat,](https://ec.europa.eu/eurostat)</u> <u>[National Bureau of Statistics of Moldova, SAG estimates](https://statistica.gov.md/en)</u>\n\n\n7. The MSNA, which ran in 7 countries: Bulgaria, Czech Republic, Hungary, Republic of Moldova, Poland, Romania, and Slovakia\n8. Equivalized as per <u>[Eurostat methodology. Essentially income per person, but with household members beyond the first one](https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Glossary:Equivalised_income)</u>\nassigned weights less than", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 3, "chunk": 1, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.6003801226615906, "start": 872, "end": 883, "probe_score": 0.9577, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".\n\nMany \n people \n do \n not \n possess \n a \n Citizenship \n Scrutiny \n Card \n (or \n “CSC”) \n either \n because \n they\nlive \n or \n used \n to \n live \n in \n conflict \n areas \n controlled \n by \n ethnic \n armed \n groups \n with \n no\nGovernment \n representation, \n or \n simply \n because \n they \n do \n not \n have \n access \n to \n the\nadministrative \n mechanisms \n that \n issue \n these \n documents. \n Furthermore, \n the \n Government\nin \n the \n past \n limited \n distribution \n of \n CSCs \n in \n border \n areas \n to \n contain \n movement \n of \n people\nlinked \n to \n ethnic \n armed \n groups. \n Very \n few \n IDPs \n held \n CSCs \n before \n their \n displacement, \n and \n it\nmay \n be \n extremely \n difficult \n for \n people \n who \n have \n been \n displaced \n as \n refugees \n or \n IDPs,\nparticularly \n from \n areas \n controlled \n by \n ethnic \n armed \n groups, \n to \n provide \n the \n necessary\ndocumentation \n to \n obtain \n CSCs. \n Additionally, \n persons \n not \n belonging \n to \n one \n of \n the\nofficially \n recognized \n “ethnic \n groups” \n face \n difficulty \n in \n acquiring \n CSCs, \n despite \n the \n fact\nthat \n there \n are \n relevant \n provisions \n available \n for \n them \n under \n the \n Myanmar \n Citizenship\nLaw. \n In \n July \n 2011, \n the \n Immigration \n and \n National \n Registration \n Department \n of \n the\nMinistry \n of \n Immigration \n and \n Population \n initiated \n the \n Moe \n Pwint \n Operation, \n which \n is \n an\naccelerated \n procedure \n to \n issue \n CSCs, \n especially \n in \n areas \n that \n were \n remote \n and/or\ndifficult \n to \n access \n in \n the \n past \n because \n of \n the \n presence \n of \n non-­‐state \n armed \n groups.\n\nThere \n are \n no \n mine \n maps \n currently \n available \n and \n the \n extent \n of \n the \n threat \n is \n impossible \n to\naccurately \n assess. \n However, \n it \n is \n suspected \n that \n Myanmar \n is \n one \n of \n the \n most \n highly\nlandmine-­‐contaminated \n countries \n in \n the \n world, \n with \n these \n devices \n continuing \n to \n claim\nseveral \n hundred \n civilian \n victims \n each \n year. \n Myanmar \n has \n not \n acceded \n to \n the \n Mine \n Ban\nTreaty \n but \n has \n recently \n set \n up \n a \n Myanmar \n Mine \n Action \n Centre, \n under \n the \n Myanmar\nPeace \n Centre \n (MPC) <sup>4</sup> to \n co-­‐ordinate \n and \n oversee \n the \n implementation \n of \n a \n national\n\n\n3 _Changing \n Realities, \n Poverty \n and \n Displacement \n In \n South \n East \n Burma/Myanmar_, \n The \n Border \n Consortium, \n 31\nOctober \n 2012, <u>http://www.tbbc.org/resources).</u>\n\n4", "output": {"entities": {"named_data": [], "descriptive_data": ["mine \n maps"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000255", "page": 2, "chunk": 1, "title": "Supporting durable solutions in south-­east Myanmar: A framework for UNHCR engagement", "pdf_url": "https://reliefweb.int/attachments/1c6a661d-c5d0-3ea4-86b1-74f6fdec12e1/SupportingDurableSolutionsinSEMyanmar-finalJune2013.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "mine \n maps", "label": "DESCRIPTIVE_DATA", "score": 0.7319046854972839, "start": 1632, "end": 1643, "probe_score": 0.7359, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">dropouts and learning outcomes, a few different scenarios were considered.</mark>\n\n<mark>43.</mark> **<mark>It was assumed that those households in the bottom quintiles (the poorest 40 percent) would be the</mark>**\n**<mark>most affected by the pandemic.</mark>** <mark>According to the</mark> <mark>Uganda National Household Survey (UNHS) 2016/17, these</mark>\n<mark>households account for 54 and 24 percent of the total children and youth currently enrolled in public primary and</mark>\n\n\nPage 18 of 43\n\n\nOfficial Use", "output": {"entities": {"named_data": ["Uganda National Household Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000034", "page": 22, "chunk": 2, "title": "Uganda - COVID-19 Emergency Education Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/645041598936002560/pdf/Uganda-COVID-19-Emergency-Education-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Uganda National Household Survey", "label": "NAMED_DATA", "score": 0.9151933193206787, "start": 301, "end": 333, "probe_score": 0.9868, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "government capital, and higher human capital, respectively, and are expected to be positive. The\n\n\nlast term summarizes the effect of additional private capital on the marginal product of private\n\n\ncapital, which is negative in the presence of diminishing returns to private capital because an\n\n\nincrease in private capital drives down the return to private capital. Along the first-order\n\n\ncondition in Equation (2), these effects must balance to zero. This implies that the larger is the\n\n\npositive effect of MDB-financed interventions on productivity, government capital and human\n\n\ncapital, the larger will be the induced increase in private capital required to restore the equality in\n\n\nEquation (2). Therefore, within this framework, _identifying projects that increase A and/or H,_\n\n\n_and the elasticity of output with respect to A and/or H_, is crucial for crowding in private\n\n\ninvestment, an insight which carries through much of the discussion in this paper.\n\n\nTo calibrate how much private investment MDB-financed activities typically catalyze\n\n\nusing readily available data sources, Chelsky and Kraay (2017) rely on a standard Cobb-Douglas\n\n\n\nproduction function of the form:\n\n\n\n(4) 𝑌𝑌 = 𝐴 𝛼𝛼𝐺𝐺𝛽𝛽𝐻𝐻𝛾𝛾\n\n\n\nSubstituting this functional form into Equation (3) and re-arranging terms yields the\n\n\n\nfollowing more tractable and intuitive expression:\n\n𝐴 𝜕 𝑋 𝐴 𝐺 𝜕 𝑋 𝐺\n\n\n\n<u>𝐾</u>\n\n~~𝐻~~ 𝐻\n\n\n\n<u>𝜕</u>\n\n~~𝜕~~ 𝜕 ~~𝑋~~ 𝑋 ~~𝐴~~ 𝐴 <sup>𝑑𝑑𝑋𝑋𝐴𝐴</sup> <sup>+ 𝛽𝛽</sup>\n\n\n\n<u>𝐾</u>\n\n~~𝐺~~ 𝐺\n\n\n\n<u>𝜕</u>\n\n~~𝜕~~ 𝜕 ~~𝑋~~ 𝑋 ~~𝐺~~ 𝐺 <", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data sources"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001539", "page": 9, "chunk": 0, "title": "idu1c22e2ec41eee514d2d19dfb115b648d7fa6f", "pdf_url": "https://local/prwp/idu1c22e2ec41eee514d2d19dfb115b648d7fa6f.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data sources", "label": "VAGUE_DATA", "score": 0.7660652995109558, "start": 1082, "end": 1094, "probe_score": 0.7304, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|**Figure A4:** Infant Mortality Rate in 2015<br>_Source:_ Authors’ analysis using data from CIESIN (2018).<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|**Figure A4:** Infant Mortality Rate in 2015<br>_Source:_ Authors’ analysis using data from CIESIN (2018).<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|**Figure A4:** Infant Mortality Rate in 2015<br>_Source:_ Authors’ analysis using data from CIESIN (2018).<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|**Figure A4:** Infant Mortality Rate in 2015<br>_Source:_ Authors’ analysis using data from CIESIN (2018).<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|**Figure A4:** Infant Mortality Rate in 2015<br>_Source:_ Authors’ analysis using data from CIESIN (2018).<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|**Figure A4:** Infant Mortality Rate in 2015<br>_Source:_ Authors’ analysis using data from CIESIN (2018).<br>_he figure shows the average infant mortality rate at the cell level for 2015 using a gr_|**Figure A4:** Infant Mortality", "output": {"entities": {"named_data": ["data from CIESIN"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000171", "page": 51, "chunk": 435, "title": "climate anomalies and international migration a disaggregated analysis for west africa", "pdf_url": "https://local/prwp/climate-anomalies-and-international-migration-a-disaggregated-analysis-for-west-africa.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from CIESIN", "label": "NAMED_DATA", "score": 0.578767716884613, "start": 175, "end": 191, "probe_score": 0.9801, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**<u><<</u>** **<u>PROCESS FRAMEWORK (PF) >></u>**\n\n#### 7 MONITORING AND EVALUATION OF PROCESS FRAMEWORK\n\n##### 7.3 Purpose and Scope of Process M & E\n\n\n90. The purpose of the process framework M&E system is to monitor the extent and the\nsignificance of adverse impacts and the effectiveness of measures designed to assist displaced\nperson to improve or restore incomes and livelihoods. It is expected that stakeholders\nespecially fishing community who are likely to be affected by the implementation of\nKEMFSED project activities partly due to introduction of new regulations or reinforcing\nexisting regulations due to implementation of new governance structures, controlling of overfishing, maintenance of fish stock levels and modernizing of fish landing sites and fishing ports\nwill actively participate in the M&E process. Those who benefit from livelihoods restoration\nand mitigation assistance will also be expected to monitor and evaluate the effectiveness of the\nalternative livelihood measures being undertaken by the project.\n\n##### 7.4 Approach and Data Sources\n\n\n91. Stakeholders will be involved in monitoring and evaluating project measures at different stages\nand at different times. Their participation in discussing restrictions and upgrading of port\nfacilities will be from the outset of the project. They will assist with developing equitable\ncriteria for obtaining development assistance and will also assist in determining and validating\nthe effects of the new regulations and infrastructural upgrade in the fishing ports and landing\nsites being put in place. Stakeholder participation will follow both the project and subproject\ncycle starting from planning to implementation and evaluation. Sources of routine and nonroutine data to ensure proper monitoring and evaluation include the following.\n\n##### 7.5 Information Management\n\n\n92. **Staff Field Reports** - Staff will be required to document and report their activities engaging\nwith community members for every session or event. Reports will capture date and time of\nevents, attendance", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["routine and nonroutine data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018254", "page": 59, "chunk": 0, "title": "Kenya - Marine Fisheries and Socio-Economic Development Project : Resettlement Plan (Vol. 1 of 2) : Process Framework", "pdf_url": "https://documents.worldbank.org/curated/en/791671561698737668/pdf/Process-Framework.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "routine and nonroutine data", "label": "VAGUE_DATA", "score": 0.5945174098014832, "start": 1727, "end": 1754, "probe_score": 0.2266, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", even the staff substantively\nappointed do not have previous experience in handling activities to the magnitude expected under USMID\nAF.\n\n42. **An analysis of the staffing levels for a sample of 7 USMID and 4 coming MLGs** indicates that\nthere are gaps in both USMID and 4 additional MLIGs, see the summary table below. The sample shows\nthat the coming 4 additional USMID MLGs have significant gaps in especially procurement and\nengineering whereas the Finance and IA positions are filled with gaps as per the current 14 MLGs.\n\n\n**Table 8: Overview of Required Staffing Positions**\n\n\n\n\n\n\n\n\n\n\n\n\n\n_Source: Self-reported data during field level collections, October 2017._\n\n43. **The capacity gaps identified across all the 18 municipal LGs assessed** still falls into three broad\ncategories, namely: (i) gaps in numbers of key positions filled, (ii) operation skills to backup academic\nqualifications, and (iii) inadequate tools, equipment and facilities. The USMID Program will contribute to\naddressing the last two gaps. The first gap is structural and can only be addressed with the involvement of\nMinistry of Finance, Ministry of Public Service, and Ministry of LGs. Although the municipal LGs can use\npart of the Program fund for investment servicing cost (procurement of technical support for engineering\ndesign, preparation of bidding documents and supervision), there is need to continue building their technical\nand managerial capacity to handle the significant increase in development funds. For the additional\n\n\n59", "output": {"entities": {"named_data": [], "descriptive_data": ["Self-reported data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000168", "page": 66, "chunk": 1, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents1.worldbank.org/curated/en/946901526654169395/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Self-reported data", "label": "DESCRIPTIVE_DATA", "score": 0.6312465071678162, "start": 605, "end": 623, "probe_score": 0.8776, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Cage_ **_Ref._** **_Motor Veh._** **_No.1 Sedal No._** **_Model_** **_Purchase Value_** **_-USD_** _UGX_\n\n**1** 25/01/2018 Desktop Computer TCL/STBGP/042 **7GZ2NK2/7BZH692** Dell Optiplex **2,227 62** **8,100,000**\n\n2 25/01/2018 Desktop Computer TCL/STBGP/042 **7HP2NK2/6VNCT82** Dell Optiplex **2,227 62** **8,100,000**\n\n3 **25/01/2018** Desktop Computer TCL/STBGP/042 7HDYMK2/50ZH692 Dell Optiplex **2,227** **62** **8,100,000**\n\n4 **25/01/2018** Desktop Computer TCL/STBGP/042 **7HLXMK2/J8ZH692** Dell Optiplex **2,227 62** **8,100,000**\n\n5 25/01/2018 Desktop Computer TCL/STBGP/042 )H4YMK2/6SNCTB2 Dell Optiplex 2,227.2 8,100,000\n\n6 **25/01/2018** Desktop Computer TCL/STBGP/042 7H6XMK2/3VNCT82 Dell Optiplex **2.227.62** **8,100,000**\n\n**7** 25/01/2018 Desktop Computer TCL/STBGP/042 7H7ZMK2", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001559", "page": 41, "chunk": 1, "title": "Uganda - AFRICA EAST - P133305 - Uganda Grid Expansion and Reinforcement Project (GERP) - Audited Financial Statement", "pdf_url": "https://documents.worldbank.org/curated/en/099035002232216903/pdf/GERP0AUDITOR000ORT0FY30TH0JUNE02021.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\n**food insecurity and access to basic services.** The economy is estimated to have recovered with a growth rate of 3.2\npercent in fiscal year (FY) 2019. This reflects a strong rebound in the oil sector while non-oil economy such as\nmanufacturing, agriculture, and services continue to underperform. The oil sector thus continues to be the sole source of\ngrowth in South Sudan. It is worth noting that this growth is unlikely to improve the distribution of income as very little is\nspent on improving food security and basic service delivery. The economy is beset with high inflation and soaring foreign\nexchange rate premium. Inflation averaged 60.8 percent in FY2019 compared to 121.4 percent in FY 2018, partly reflecting\nreduced central bank financing of the budget deficit and the positive impact of peace on trade and the functioning of\nmarkets. The gap between the official exchange rate and the parallel market rate remains high and increased from 65\npercent in December 2018 to 85 percent in June 2019. The external sector current account deficit, excluding grants, rose\nto 6.5 percent of GDP in FY2019 from 4.5 percent in FY 2018. Expenditures continue to be skewed toward defense at the\nexpense of poverty reduction. Security and accountability/public administration accounted for 83 percent of total\nspending during FY2019. By contrast, combined expenditures on health, education, and rural development are estimated\nto make up around 3 percent of total government spending, worse than in previous years. <sup>1</sup> [^1: World Bank (2019). “South Sudan Macro-Poverty Outlook, September 2019”.]\n\n3. **Poverty in South Sudan has reached unprecedented levels.** Over 8 out of every 10 people in South Sudan lived\nbelow the poverty line (US$1.90 per day) in 2017, a considerable increase from 51 percent in 2009. The urban poverty\nrate stood at over 70 percent – a sharp increase from 40 percent in 2015. <sup>2", "output": {"entities": {"named_data": ["South Sudan Macro-Poverty Outlook"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000014", "page": 2, "chunk": 1, "title": "Concept Project Information Document (PID) - South Sudan Enhancing Community Resilience and Local Governance Project - P169949", "pdf_url": "http://documents.worldbank.org/curated/en/294881573571217860/pdf/Concept-Project-Information-Document-PID-South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project-P169949.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "South Sudan Macro-Poverty Outlook", "label": "NAMED_DATA", "score": 0.5412085056304932, "start": 1555, "end": 1588, "probe_score": 0.9994, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "output": {"entities": {"named_data": [], "descriptive_data": ["random survey"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012483", "page": 16, "chunk": 0, "title": "Kenya - Cotton Processing and Marketing Project", "pdf_url": "https://documents.worldbank.org/curated/en/404651468273298562/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7714613080024719, "start": 379, "end": 395, "probe_score": 0.582, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "random survey", "label": "DESCRIPTIVE_DATA", "score": 0.7173007130622864, "start": 1487, "end": 1500, "probe_score": 0.012, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "output": {"entities": {"named_data": [], "descriptive_data": ["random survey"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010834", "page": 16, "chunk": 0, "title": "Uganda - Agricultural Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/293931468350199576/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7714613080024719, "start": 379, "end": 395, "probe_score": 0.582, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "random survey", "label": "DESCRIPTIVE_DATA", "score": 0.7173007130622864, "start": 1487, "end": 1500, "probe_score": 0.012, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " America and Caribbean. For Barbados, Trinidad and Tobago, and\n\n\nJamaica—the three Caribbean countries included in their survey of studies on Latin America—\n\n\nthe authors conclude that “the effects of job security on employment are statistically insignificant\n\n\nand the signs are positive in some cases.”\n\n\nDespite this evidence pointing towards a comparatively flexible labor market in Jamaica,\n\n\nsome signs of regulatory issues can still be identified. In their study on labor markets and\n\n\nregulations in the Caribbean, Downes et al (2000) found for the case of Jamaica some negative\n\neffect on aggregate employment stemming from the imposition of minimum wages <sup>4</sup> .\n\n\nAdditionally, recent IMF reports list further reform of the labor markets among the most urgent\n\n\nstructural reforms the government should adopt (IMF 2004a, IMF 2004b). In particular, the\n\n\nreports cite that government spending on public wages exceeds 12% of GDP (in 2003), signaling\n\n\nvery high public sector employment level; besides, high redundancy costs, according to private\n\n\n2 The observed nominal wage growth during the 1990s suggests that workers have been setting their wage\ntargets through backwards-looking expectations—nominal wage increases tend to be higher in the years\nfollowing periods with high consumer price inflation.\n3 See Forteza and Rama (2001).\n4 The authors use aggregate employment and specify a coverage-weighted minimum wage index, so their\naggregate data include many workers whose wage and employment are unlikely to be affected by changes\nin minimum wages.\n\n\n4", "output": {"entities": {"named_data": [], "descriptive_data": ["survey of studies on Latin America"], "vague_data": ["aggregate data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003354", "page": 3, "chunk": 1, "title": "wps4143", "pdf_url": "https://local/prwp/wps4143.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey of studies on Latin America", "label": "DESCRIPTIVE_DATA", "score": 0.7092843651771545, "start": 121, "end": 155, "probe_score": 0.9961, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "aggregate data", "label": "VAGUE_DATA", "score": 0.7185730934143066, "start": 1454, "end": 1468, "probe_score": 0.3494, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">(0.129)</mark> <mark>(0.067)</mark> <mark>(0.090)</mark> <mark>(4.765)</mark>\n<mark>Observations</mark> <mark>5,984</mark> <mark>2,412</mark> <mark>2,046</mark> <mark>992</mark> <mark>534</mark>\n<u><mark>R-squared</mark></u> <u><mark>0.062</mark></u> <u><mark>0.036</mark></u> <u><mark>0.071</mark></u> <u><mark>0.113</mark></u> <u><mark>0.546</mark></u>\n<mark>Standard errors in parentheses</mark>\n<mark>*** p<0.01, ** p<0.05, * p<0.1</mark>\n_Source_ : Enterprise Survey, 2008, 2013–14, and 2015–16\n_Note_ : Explanatory variables include firm size and age, firm’s ownership status, industry, region, and year. Control\ngroup for credit constraint status is FCC.\n\n\n\n<u>All firms</u>\n\n\n\nFirm size:\nLess than\n\n5\n<u>employees</u>\n\n\n\nPage 80 of 86", "output": {"entities": {"named_data": ["Enterprise Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000025", "page": 84, "chunk": 2, "title": "Turkey - Formal Employment Creation Project", "pdf_url": "http://documents1.worldbank.org/curated/en/211181585965751622/pdf/Turkey-Formal-Employment-Creation-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Enterprise Survey", "label": "NAMED_DATA", "score": 0.8420374989509583, "start": 455, "end": 472, "probe_score": 0.9964, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<mark>TABLE 7</mark> **Asylum applications lodged in Southern Europe** <sup>*****</sup> **by origin\u0003**\n| First quarter 2012 to second quarter 2014\n\n***** See Table 1 for the 8 countries included. Top-40 ranking of countries based on applications lodged during second quarter of 2014.\n\n\n\n\n\nOrigin\n\n\n\n\n\nSerbia (and Kosovo:\nS/RES/1244 (1999))\n\n|2012|Col2|Col3|Col4|2013|Col6|Col7|Col8|2014|Col10|First semester change|Col12|Col13|‘14-’13|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n|Q1<br> 1,468<br> 1,085<br> 144<br> 487<br> 1,028<br> 259<br> 55<br> 970<br> 460<br> 316<br> 29<br> 342<br> 149<br> 261<br> 121<br> 390<br> 106<br> 57<br> 60<br> 56<br> 4<br> 258<br> 90<br> 69<br> 95<br> 225<br> 43<br> 141<br> 17<br> 58<br> 31<br> 27<br> 101<br> 58<br> 15<br> 9<br> 72<br> 43<br> 17<br> 24<br> 815|Q2<br> 1,904<br> 1,", "output": {"entities": {"named_data": [], "descriptive_data": ["Asylum applications lodged in Southern Europe"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000864", "page": 23, "chunk": 0, "title": "UNHCR Asylum Trends, First half 2014: Levels and Trends in Industrialized Countries", "pdf_url": "https://reliefweb.int/attachments/7f25b7c6-aaf7-3a20-8f40-724aa5597bd5/5423f9699.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Asylum applications lodged in Southern Europe", "label": "DESCRIPTIVE_DATA", "score": 0.6641261577606201, "start": 23, "end": 68, "probe_score": 0.142, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " banks) further strengthens\nthat effect. In total, general government\nrevenue increased by 2.0% in 2022, 2.75%\nin 2023, and 2.94% in 2024. In monetary\nterms this amounts to PLN 25.0 billion\nin 2022, PLN 39.1 billion in 2023, and\nPLN 47.0 billion in 2024 <sup>22</sup> . In the long term,\nrefugees should increase annual general\ngovernment revenue by around 2.7%.\n\n\n**Ultimately, Ukrainian refugees**\n**generate additional output and**\n**demand.** This results in an increase in real\nGDP, and is especially beneficial for public\nfinance. Although the influx of refugees\nwas costly at the start, the additional\ngeneral government revenue they provided\nwas more than enough to compensate\nfor the expense <sup>23</sup> . Tight labour market\nhelped absorb the increase in labour force,\nmitigating negative impacts of increased\ncompetition on the native workforce. Over\ntime, increased productivity should benefit\nnative workers, as it is the primary driver of\nlong-term wage growth. <sup>24</sup> [^24: For a discussion on the stable long-term relationship between wages and labour productivity, see for example Meager & Speckesser (2011).]\n\n\n\n22 Deloitte own calculations based on <u>Informacja kwartalna o stanie finansów publicznych - Ministerstwo Finansów - Portal Gov.pl for respective years. The general</u>\ngovernment income share in GDP in 2024 was calculated based on the data for Q1–Q3 and based on that total general government income was calculated using\nforecast for GDP from <u>Wytyczne dotyczące wskaźników makroekonomicznych - Ministerstwo Finansów - Portal Gov.pl.</u>\n\n23 Model treats general government sector as a whole, as such cost and income internal structure may differ creating institutions with financial loses while other may\nhave disproportionate increase of income.\n\n24 For", "output": {"entities": {"named_data": ["Informacja kwartalna o stanie finansów publicznych"], "descriptive_data": [], "vague_data": ["data for Q1–Q3"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 12, "chunk": 1, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Informacja kwartalna o stanie finansów publicznych", "label": "NAMED_DATA", "score": 0.7636986970901489, "start": 1180, "end": 1230, "probe_score": 0.955, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data for Q1–Q3", "label": "VAGUE_DATA", "score": 0.8093973398208618, "start": 1376, "end": 1390, "probe_score": 0.9504, "gold": "DATA_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "); the\nProject uses the same reference points.\n\n\n(i) **Unlocking land for affordable housing supply:** Land with proximity to services (transport, jobs, schools)\n\nand infrastructure is a critical enabler to affordable homes. The GoK intends to make serviced land\navailable to private developers and enter into public-private schemes to support the supply of affordable\nhomes on a large scale. It is surveying parcels of public land to assess whether they are properly registered\nand can be suitable for public-private arrangements and has prioritized 44 locations for large-scale\ndevelopments.\n\n(ii) **Providing bulk infrastructure:** The GoK is committed to servicing parcels of land by providing bulk\n\ninfrastructure (water, sewage, power, access roads) to attract the private sector. It is supporting rapid\n\n\n2 Hass Consult, House Price Index, Fourth Quarter 2017\n\n\nPage 8 of 52", "output": {"entities": {"named_data": ["House Price Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012491", "page": 11, "chunk": 1, "title": "Kenya - Affordable Housing Finance Project", "pdf_url": "https://documents.worldbank.org/curated/en/405151556935423068/pdf/Kenya-Affordable-Housing-Finance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "House Price Index", "label": "NAMED_DATA", "score": 0.7856946587562561, "start": 828, "end": 845, "probe_score": 0.9177, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " provided prompt support to\n190,000 Jordanian households soon after\nthe onset of the crisis. In Lebanon, the\ngovernment is planning to expand its existing\nsafety net from covering the poorest 8 percent\nto cover the poorest 24 percent. KRI is piloting\na targeted cash transfer as well. UNHCR, WFP,\nother UN agencies and Non-Governmental\nOrganizations (NGOs) have expanded their\ncash assistance programs in 2020. The\nexistence of well-established registration and\ncash delivery systems prior to the COVID-19\ncrisis enabled many organizations to scale-up\nquickly in response.\n\n\n\nTaken together, the impact of the COVID-19\ncrisis on poverty has been very serious. The\nwelfare consequences can be transient,\npossibly recovering with the rebound in the\ngeneral economy, or they may be longer\nterm. For this reason, this study has applied\na dynamic simulation model that shows the\neffects of the crisis on a monthly basis over\n2020 and 2021. The mitigation strategies that\ngovernments or international organizations\nadopted in response to the pandemic are also\nmodelled.\n\nThis study first outlines the potential channels\nof the impact of the pandemic on households\nand their welfare. Next, a description is\nprovided of the data sources and baseline\ncharacteristics and vulnerabilities of these\nhouseholds, and of the macroeconomic\nassumptions that shape these\nmicrosimulations and the results. Finally, this\nstudy concludes with a preliminary discussion\non policy implications.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data sources"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000383", "page": 13, "chunk": 1, "title": "Compounding Misfortunes - Changes in Poverty since the Onset of COVID-19 on Syrian Refugees and Host Communities in Jordan, the Kurdistan Region of Iraq and Lebanon [EN/AR]", "pdf_url": "https://reliefweb.int/attachments/3259e81a-0a06-3628-80b9-78422fb24586/Compounding-Misfortunes-Changes-in-Poverty-Since-the-Onset-of-COVID-19.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data sources", "label": "VAGUE_DATA", "score": 0.6155090928077698, "start": 1216, "end": 1228, "probe_score": 0.0003, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "# **HIGH EMPLOYMENT** **RATES, BUT LOW** **WAGES: A POVERTY** **ASSESSMENT OF** **UKRAINIAN REFUGEES** **IN NEIGHBORING** **COUNTRIES**\n## **An inter-agency exploration of** **socio-economic data** March 2025", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["socio-economic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 15, "chunk": 0, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "socio-economic data", "label": "VAGUE_DATA", "score": 0.7424743175506592, "start": 176, "end": 195, "probe_score": 0.3146, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Col1|Col2|\n|---|---|\n|Table of|**Contents**|\n|||\n\n\nExecutive Summary 9\n\n\nIntroduction 15\n_<u>Purpose of the Dialogue with Refugee Women</u>_ <u>15</u>\n\n_<u>Purpose of this Report</u>_ <u>15</u>\n\n_<u>Proceedings of the Dialogue with Refugee Women</u>_ <u>16</u>\n\n\nTheme one: **Safety and Security**\n\n_<u>Right to Personal Safety and Security</u>_ <u>17</u>\n\n\nSexual and Gender-Based Violence\n\n\nDomestic Violence\n\n_<u>Right to Seek and Enjoy Asylum</u>_ <u>20</u>\n\n\nDocumentation and Freedom of Movement\n\n\nDetention\n\n\nAccess to Asylum Procedures\n\n_<u>Right to Return to One’s Country</u>_ <u>23</u>\n\n\nTheme two: **Livelihoods**\n\n_<u>Basic Needs and Access to Services</u>_ <u>26</u>\n\n\nCamps and Rural Settings\n\n\nUrban Settings\n\n_<u>Right to Access Employment</u>_ <u>28</u>\n\n_<u>Right to Education</u>_ <u>29</u>\n\n_<u>Land and Property Rights</u>_ <u>30</u>\n\n\n_<u>Promote Refugee Women’s Participation, Leadership and Decision-making</u>_ <u>31</u>\n\n_<u>Build Women’s Resources</u>_ <u>34</u>\n\n_<u>Develop Long-term, Integrated Approaches</u>_ <u>35</u>\n\n_<u", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001025", "page": 4, "chunk": 0, "title": "Respect Our Rights: Partnership for Equality - Report on the Dialogue with Refugee Women", "pdf_url": "https://reliefweb.int/attachments/9bcea38a-d58f-3ac8-8a9f-52dc29610dc8/683057DF01AFEEC5C1256C17003A04C6-unhcr-womencd-22jun.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the situation that was agreed upon with\nthe Borrower.\n\nSigned by:\nFinancial Management v I _N_\n##### Specialist K {dO'.i1, O0\n\n(FMS-OPR) Rafika Chaouali, MNSHD Date\n\n\n**Part II:** **Procurement/Contract Management** System\n\nI have reviewed the procurement/contract management system relating to this project, including\nthe format and content of the section on Project Management Reports (PMRs) on procurement\n\nmonitoring. The objective of the review was to determine whether the procurement/contract\nmanagement system adopted by the project conforms to IDA's guidelines for procurement in\ninvestment projects. My review was based on the \"Assessment of Agency's Capacity to\nImplement Project Procurement, Setting of Prior Review Thresholds and Procurement\nSupervision Plan\" guidelines issued by IDA.\n\nI confirm that the project satisfies IDA's minimum procurement management requirements.\nHowever, in my opinion, the project does not have in place an adequate procurement/contract\nmanagement system that can provide the appropriate data on major procurement and contract\nmanagement (PMR - Section 3) as required by IDA.", "output": {"entities": {"named_data": [], "descriptive_data": ["data on major procurement and contract\nmanagement"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000147", "page": 54, "chunk": 1, "title": "Rwanda - Human Resources Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/837731468759911848/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on major procurement and contract\nmanagement", "label": "DESCRIPTIVE_DATA", "score": 0.6258809566497803, "start": 1032, "end": 1081, "probe_score": 0.0015, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " is responsible for doing so.\n\n<u>[[Source]](https://www.unhcr.org/protection/children/4098b3172/inter-agency-guiding-principles-unaccompanied-separated-children.html)</u>\n\nA \" **refugee** \" is a person who owing to a well-founded fear of\nbeing persecuted for reasons of race, religion, nationality,\nmembership of a particular social group, or political opinion, is\noutside the country of his nationality and is unable to or, owing\nto such fear, is unwilling to avail himself of the protection of that\ncountry (Article 1 A 1951 Refugee Convention).\n\n\n##### Family Reunification\n\nIn the first six months of 2018, IOM assisted **4,882** refugees and\nmigrants with family reunification in the European Economic Area\n(EEA).\n\nThe people assisted were primarily nationals of Afghanistan, the\nSyrian Arab Republic, Somalia, Ethiopia and Côte d’Ivoire who\nre-united with their family members residing in EEA. The majority\nof cases were processed in Italy (30%), the United Kingdom\n(22%), North European countries (Finland, Iceland and Sweden\ncomprised 29% of the total) and 13 different countries in the EEA.\n\n##### Children Resettled to Europe\n\nOf the total number of resettlement submissions to Europe in\n2018 ( **22,998** ), **50%** were children (27% boys and 23% girls).\nMost children in Europe were resettled to the United Kingdom,\nFrance, Sweden, Germany and Netherland. During the year,\n**16,526** resettled refugees departed to European countries. <sup>18</sup>\n\n\n_Sources: Hellenic_ _<u>Police, Greek National Centre for Social Solidarity (EKKA), Italian Ministry of Interior, Bulgarian", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001140", "page": 6, "chunk": 1, "title": "Refugee and Migrant Children in Europe: Accompanied, Unaccompanied and Separated: Overview of Trends (January - June 2018)", "pdf_url": "https://reliefweb.int/attachments/acd81b9f-ff4b-3428-9941-a8afd9c68764/67831.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "** **Cultural and Creative Industries (CCI) are key drivers of the creative economy and represent important sources**\n**of employment, economic growth, and innovation that contribute to city competitiveness and sustainability.** A\nrecent World Bank report points out that through their contribution to urban regeneration and sustainable urban\n\n\n6 Income headcount poverty rates based on upper poverty line of $14 income per day and lower poverty line of $8.5 per day. For the lower\npoverty line, the corresponding increase is from 8.2 percent to 23.2 percent, bringing the total number of poor Lebanese to 1.1 million for the\nlower poverty line and 2.7 million for the upper one. Source: Fakih, Ali, Makdissi, Paul, Marrouch, Walid, Tabri, Rami V., Yazbeck, Myra,\n“Confidence in Public Institutions and the Run up to the October 2019 Uprising in Lebanon,” Working Paper, 2020.\n7 Marot, “Jadaliyya - The End of Rent Control in Lebanon: Another Boost to the ‘Growth Machine?’”\n8 UNDP, “Leave No One Behind for an Inclusive and Just Recovery Process in Post-Blast Beirut”; UN-Habitat, “Lebanon Urban Profile,” 2011.\n9 Since its independence in 1942, the Lebanese State has rarely engaged in the production of public housing or introduced measures to protect\nor secure affordable housing for low-income groups such as property regularization and neighborhood upgrading\n10 InfoPro, “Business Opportunities in Lebanon – Year XI. Real Estate in Greater Beirut [Database],” 2014.\n\n\nPage 7 of 66", "output": {"entities": {"named_data": ["Real Estate in Greater Beirut [Database]"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 12, "chunk": 2, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Real Estate in Greater Beirut [Database]", "label": "NAMED_DATA", "score": 0.627589762210846, "start": 1423, "end": 1463, "probe_score": 0.7441, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "21\n\n\nthey have to purchase water from trucks which costs four times as high than a household connection;\nand qat consumption poses a major social, income and productivity issue.\n\n\nIn order to capture as much of the school-age population presently out of school due to the lack of\nexisting places, the project will construct additional/rehabilitate classrooms. In addition, sanitation\n\nservices will be rehabilitated, and a study will be undertaken on which sanitation services best serve\nthe area, especially in a drought-prone area, and the most cost-effective methods of implementation\nand maintenance. The project will finance a study to analyze the factors that hinder girls' attendance\nand achievement, and of the feasibility of measures to overcome them, including the issues\n\nsurrounding access to education by the poor. The problems are cross-sectoral which the project, in\nPhase I, will not address (unemployed youth, health issues, non-Djiboutian school-age population,\netc.). See Section C above for program details.\n\n\nThe IDA's regional team will discuss with Government on updating the initial 1997 poverty\n\nassessment in order to produce a better picture of the issues as they exist now. In addition, it is\nenvisaged that IDA will discuss the rising health issues with the Government and the best ways for\naddressing these problems.\n\n\n_6.2 Participatory Approach: How are key stakeholders participating in the project?_\n\n\nKey stakeholders participated in the National Educational Forum _(Etats-Generaux de l'Education)_\nwhich was held in December 1999. This included officials, teachers, parents, students, members of\nparliament and the general public. The project is based on the outcome of the conference. The new\neducation law (approved in August 2000) sets in place the conditions for broadening participation in\nDjibouti's education system. It provides for setting up school management committees with parent\n\nand community involvement. The law also provides for the creation of conditions to increase private", "output": {"entities": {"named_data": [], "descriptive_data": ["1997 poverty\n\nassessment"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016416", "page": 24, "chunk": 0, "title": "Ethiopia - Second Agricultural Minimum Package Project", "pdf_url": "https://documents.worldbank.org/curated/en/668801468273905637/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "1997 poverty\n\nassessment", "label": "DESCRIPTIVE_DATA", "score": 0.8141470551490784, "start": 1107, "end": 1131, "probe_score": 0.6186, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " older persons, 10% are persons with disabilities, 4% are pregnant women and more than half of returnees\n[are children (UNHCR-IOM Flash Update #23). This is significant considering the current restrictions imposed on girls’ access to](https://data.unhcr.org/fr/documents/details/109680)\neducation post-primary. Some 94% of returnees have no education and around 85% are low-skilled workers who mainly have\n[worked in urban environments, suggesting significant vulnerability to poverty (ARRNA 2024;](https://reliefweb.int/report/afghanistan/afghanistan-returnees-rapid-needs-assessment-may-2024) <u>[UNHCR Data story, May 2024, Returns](https://dataviz.unhcr.org/products/gotm/2024-05-28/forced-returns-to-afghanistan.html)</u>\n<u>[to Afghanistan;](https://dataviz.unhcr.org/products/gotm/2024-05-28/forced-returns-to-afghanistan.html)</u> <u>[IOM Dashboard).](https://app.powerbi.com/view?r=eyJrIjoiNjMwYjJmMzMtOGYwNS00MzA4LTk1N2MtZWQ1OTk3MjU2OTE4IiwidCI6IjE1ODgyNjJkLTIzZmItNDNiNC1iZDZlLWJjZTQ5YzhlNjE4NiIsImMiOjh9)</u> Most movements from Pakistan have", "output": {"entities": {"named_data": ["UNHCR Data story"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001053", "page": 1, "chunk": 4, "title": "Afghanistan Protection Analysis Update - January -June 2024", "pdf_url": "https://reliefweb.int/attachments/a05ab0ac-1fbd-4657-9d24-8dd3c381edf5/pau24_protection_analysis_update_brief_protection_risks_areas_of_return_afghanistan_june_2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR Data story", "label": "NAMED_DATA", "score": 0.6889980435371399, "start": 599, "end": 615, "probe_score": 0.9755, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nKenya Affordable Housing Finance Project (P165034)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Verification Protocol Table: Disbursement Linked Indicators|Col2|\n|---|---|\n|<br>**DLI 1**|<br>The Project Implementing Entity is legally established, has the required regulatory capital and approvals to start<br>operations|\n|**Description**|The Borrower has established, operationalized and capitalized the Project Implementing Entity and the Project<br>Implementing Entity has received the relevant licenses, permits, and approvals required to start operations.|\n|**Data source/ Agency**|NT|\n|**Verification Entity**|NT|\n|**Procedure **<br> <br>|_Supporting documents:_ <br>• <br>Copy of KMRC license by CBK.<br>• <br>KMRC Bank Record showing funding provided by National Treasury and Planning<br> <br>|\n|<br> <br>**DLI 2**|<br>The Borrower has provided Tier 2 Capital to the Project Implementing Entity|\n|**Description**|The Borrower has executed a Subordinated Debt Agreement with the Project Implementing Entity pursuant to which EUR<br>8,800,000 equivalent has been paid to the Project Implementing Entity.|\n|**Data source/ Agency**|KMRC|\n|**Verification Entity**|NT|\n|**Procedure **<br>|_Supporting documents:_ <br>• <br>Letter from NT indicating that it has provided Tier 2 capital to KMRC<br>• <br>Copy of Subordinated debt agreement amended, signed by KMRC and NT<br>|\n|<br> <br>**", "output": {"entities": {"named_data": ["KMRC Bank Record"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012491", "page": 35, "chunk": 0, "title": "Kenya - Affordable Housing Finance Project", "pdf_url": "https://documents.worldbank.org/curated/en/405151556935423068/pdf/Kenya-Affordable-Housing-Finance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "KMRC Bank Record", "label": "NAMED_DATA", "score": 0.6639106273651123, "start": 711, "end": 727, "probe_score": 0.0124, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**PAD DATA SHEET**\n\n_Chad_\n\n_Emergency Food and Livestock Crisis Response Project (P151215)_\n\n**PROJECT APPRAISAL DOCUMENT**\n\n\n_AFRICA_\n\nReport No.: PAD1101\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Basic Information|Col2|Col3|Col4|Col5|Col6|Col7|\n|---|---|---|---|---|---|---|\n|Project ID|Project ID|Project ID|EA Category|EA Category|Team Leader|Team Leader|\n|P151215|P151215|P151215|B - Partial Assessment|B - Partial Assessment|Bleoue Nicaise Ehoue|Bleoue Nicaise Ehoue|\n|Lending Instrument|Lending Instrument|Lending Instrument|Fragile and/or Capacity Constraints [X]|Fragile and/or Capacity Constraints [X]|Fragile and/or Capacity Constraints [X]|Fragile and/or Capacity Constraints [X]|\n|Investment Project Financing|Investment Project Financing|Investment Project Financing|Financial Intermediaries [  ]|Financial Intermediaries [  ]|Financial Intermediaries [  ]|Financial Intermediaries [  ]|\n||||Series of Projects [  ]|Series of Projects [  ]|Series of Projects [  ]|Series of Projects [  ]|\n|Project Implementation Start Date|Project Implementation Start Date|Project Implementation Start Date|Project Implementation End Date|Project Implementation End Date|Project Implementation End Date|Project Implementation End Date|\n|14-Oct-2014|14-Oct-2014|14-Oct-2014|30-Apr-2017|30-Apr-2017|30-Apr-2017|30-Apr-2017|\n|Expected Effectiveness Date<br>Expected Closing Date|Expected Effectiveness Date<", "output": {"entities": {"named_data": ["PAD DATA SHEET"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000007", "page": 5, "chunk": 0, "title": "Chad - Emergency Food and Livestock Crisis Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/179061468215115488/pdf/PAD11010PAD0P1010Box385329B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PAD DATA SHEET", "label": "NAMED_DATA", "score": 0.6321051716804504, "start": 2, "end": 16, "probe_score": 0.1016, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "from 2001 onward, the last two of these—arts and business—were removed\n(Orlale 2000, Kremer, Miguel, and Thornton 2009). As a consequence, the\nKLPS data include observations in which the maximum score is 700, and\nobservations where the maximum is 500. Throughout this paper, I normalize\nall scores to the 500-point scale.\n\nThose who are not admitted to any government school have several options if they wish to continue their education: they may repeat eighth grade\nand re-take the KCPE; they may still have access to private secondary schools\nand vocational schools; or they may travel to Uganda to enroll in school there.\n\n\n**A.1.3** **Re-taking** **the** **KCPE**\n\n\nOne clear pattern both from the survey data and the administrative records is\nthat students sometimes re-take the test. In the 2003-2005 round of surveying\n(KLPS1), the questionnaire asked not only for respondents’ KCPE score, but\nalso how many times they had taken the KCPE. Of KCPE-takers in the older\ncohorts (who had reached eighth grade before being interviewed in KLPS2),\napproximately 87 percent said they took it exactly once, 13 percent said that\nthey had taken the exam twice, and around one tenth of one percent said\nthey took it three times. The reason such a small fraction re-take such an\nimportant examination, according to my interviews with with both teachers\nand pupils, is that it is costly: they have to repeat eighth grade in order to do\nit. The survey data are in agreement: more than 98 percent of respondents\nwho report re-taking the KCPE also report repeating standard 8; conversely,\nof those who take the KCPE only once, comparatively few respondents (less\nthan 3 percent) repeat standard 8 for any reason. While a pupil’s decision to\nre-take", "output": {"entities": {"named_data": ["KLPS data"], "descriptive_data": ["administrative records"], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006439", "page": 53, "chunk": 0, "title": "wps7384", "pdf_url": "https://local/prwp/wps7384.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "KLPS data", "label": "NAMED_DATA", "score": 0.8351299166679382, "start": 143, "end": 152, "probe_score": 0.921, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.6114461421966553, "start": 702, "end": 713, "probe_score": 0.7988, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "administrative records", "label": "DESCRIPTIVE_DATA", "score": 0.6731788516044617, "start": 722, "end": 744, "probe_score": 0.9405, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\n**Recently arrived Ukrainian refugees,**\n**those with below tertiary education**\n**and in older age group are most**\n**likely to communicate in Polish at**\n**intermediate and lower levels.** Based\non the SEIS UNHCR survey, a logistic\nregression has been performed to\nfind out which categories of Ukrainian\nrefugees may most require Polish language\nimprovement. <sup>29</sup> [^29: A dummy variable that takes the value of 1 in case of none, beginner, or intermediate language knowledge, and 0 for other levels has been regressed against a\nnumber of explanatory variables.] Results show that the\nodds of only zero to intermediate Polish\nknowledge decrease with every month\nsince arrival. Ukrainian refugees in the\n18 to 29 age group have the lowest odds\nof having an intermediate or lower level of\nPolish. It translates into a 38% probability,\neven lower than the 41% for refugees with\ntertiary education. The group with the\nhighest odds (70% probability) of zero to\n\n\n\nintermediate Polish are Ukrainian refugees\naged 50 to 64. The results by employment\nsectors are not statistically significant,\nother than for manufacturing. The results\nare intuitive, with the best language skills\namong refugees working in health and\neducation, and the lowest among those\nworking in construction, other services,\nand trade.\n\n\n**Addressing the gap in language**\n**fluency would yield significant**\n**macroeconomic benefits.** To illustrate\nthe macroeconomic impact of public\nintervention, we have assumed that half\nof the current language gap is addressed,\nso that the share of working refugees not\nspeaking Polish fluently falls from 82%\nto 41%. Assuming that the productivity\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n#### **4.5 Recommendations**\n\n##### Language courses\n\n\n**Ukrainian refugees in Poland earn higher wages when they", "output": {"entities": {"named_data": ["SEIS UNHCR survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 17, "chunk": 0, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS UNHCR survey", "label": "NAMED_DATA", "score": 0.9030843377113342, "start": 280, "end": 297, "probe_score": 0.9807, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " يعرب ا لناس\nعن رغبته\nم \n في ا ن يا خذ هللا حياتهم\nك وسيلة\nيوصِلون لالآخ رين من\nخاللها \n ا نهم في محنة، مع عدم وجود ا ي.نية إلنهاء حياتهم \n \n الجدول1 \n (النسخة العربية السورية) والجدول2 (النسخة الكردية \n الكيرمانجي\n) تعطي لمح ة موجزة عن\nالتعابير \n و مصطلحات لكرب ا \n الشائعة ،\n التي\nتستخدم من قبل الشعب السوري مع ا\nلمش اكل\nالمتعلقة بالصحة العقلية و المعافاة النفسية والمشاكل االج.تماعية", "output": {"entities": {"named_data": [], "descriptive_data": ["النسخة العربية السورية", "النسخة الكردية \n الكيرمانجي"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001033", "page": 21, "chunk": 2, "title": "Culture, Context and the Mental Health and Psychosocial Wellbeing of Syrians: A Review for Mental Health and Psychosocial Support Staff Working with Syrians Affected by Armed Conflict [EN/AR]", "pdf_url": "https://reliefweb.int/attachments/9d4eaadc-02cf-34a6-a3e0-17440f1433de/Culture_Mental_Health_Syria_Arabic_FINAL.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "النسخة العربية السورية", "label": "DESCRIPTIVE_DATA", "score": 0.6743009090423584, "start": 153, "end": 175, "probe_score": 0.0106, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "النسخة الكردية \n الكيرمانجي", "label": "DESCRIPTIVE_DATA", "score": 0.6974326968193054, "start": 187, "end": 214, "probe_score": 0.0462, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\ndata, and highlight countries’ promising practices,\nthey remain localized evidence which is often not\nrepresentative of refugees at the national level, for\nexample in Cameroon, Chad, Colombia, Ecuador, Peru,\nTürkiye, Zambia, Ethiopia, and South Sudan (Mert and\nKesbiç, 2019; Hure and Taylor, 2019; Acar, Pinar-Irmak,\nand Martin, 2019; Pinna, 2020; UNHCR, 2022d; World\nBank, 2023).\n\n\nA key point from the literature is that data beyond\naccess at the primary and secondary levels, <sup>14</sup> such as\nECCE, pre-primary, vocational, and tertiary education,\n\n\n\n**Introduction and background**\n<u>Paving pathways for inclusion: A global overview of refugee education data</u>\n\n\nare largely missing (see Lobos, 2022; Mert and Kesbiç\n2019; UNESCO, 2020; UIS and UNHCR, 2021). Based on\nUIS and UNHCR (2021) the most pressing information\ngaps lie in the domains of education quality (e.g.\nlearning and teachers) and school safety (e.g. peer\nviolence). On quality, a recent review of publicly\navailable data on learning for refugees found that\nthe availability of data is limited in scope and mainly\nproduced to serve donor reporting needs, and that\ngovernment data on refugee learners were not publicly\navailable. Further, their critical appraisal was challenged\nby insufficient information on the research methods of\nthe included studies (UNHCR, Oxford MeasureEd and\nCambridge Education, 2023).\n\n\nThe number of countries that disaggregate their\nnational assessments or examinations to allow insights\ninto refugee learning is limited, and they often do so\nby using proxies for refugee status, such as nationality\n(e.g. Colombia, Chad). This may not be useful in\ncontexts where refugees hold multiple nationalities\nor where there is a long history of migration between\nthe", "output": {"entities": {"named_data": [], "descriptive_data": ["refugee education data", "publicly\navailable data on learning for refugees", "government data on refugee learners"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000382", "page": 20, "chunk": 1, "title": "Paving pathways for inclusion: a global overview of refugee education data", "pdf_url": "https://reliefweb.int/attachments/31f00be7-0481-4224-80ce-378c049a02d4/Paving%20pathways%20for%20inclusion%20--%20a%20global%20overview%20of%20refugee%20education%20data.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "refugee education data", "label": "DESCRIPTIVE_DATA", "score": 0.5413362979888916, "start": 647, "end": 669, "probe_score": 0.9236, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "publicly\navailable data on learning for refugees", "label": "DESCRIPTIVE_DATA", "score": 0.7283377051353455, "start": 977, "end": 1025, "probe_score": 0.9226, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "government data on refugee learners", "label": "DESCRIPTIVE_DATA", "score": 0.8713743090629578, "start": 1143, "end": 1178, "probe_score": 0.1086, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "800,000**<br>**3,576,369**<br>directly targeted members<br>of impacted communities<br>in 2019<br>**TURKEY**<br>**REGIONAL TOTAL**<br>**5,520,729**<br>registered refugee population<br>as of 31 December 2019<br>**Voluntary Syrian Refugee Returns**<br>**Syrian Refugee Resettlement Targets**<br>**and Submissions**<br>Population in Need<br>Achievements<br>Syrian refugees who have been<br>engaged in community-led<br>initiatives (**95% of target**)<br>Syrian refugee children enrolled<br>in formal general education<br>(**77% of target**)<br>people receiving food assistance<br>(cash, voucher or in-kind)<br>(**84% of target**)<br>the number of households outside<br>camps supported with shelter/<br>shelter upgrades (**35% of target**)<br>**> 1.5**<br>**million**<br>**> 1**<br>**million**<br>**> 3.3**<br>**million**<br>**> 496**<br>**thousand**<br>**> 63**<br>**thousand**<br>**> 44**<br>**thousand**<br>**> 1**<br>**million**<br>**> 1.9**<br>", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000166", "page": 1, "chunk": 13, "title": "3RP Regional Refugee and Resilience Plan in response to the Syria Crisis | 2019 Annual Report", "pdf_url": "https://reliefweb.int/attachments/0d34cd24-6e01-3f5c-8c00-0f3d92eaea8d/76670.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**35%**|**36.4%**|**40%**|**34.9%**|**41%**|**35.7%**|**41%**|**37.0%**|**41%**|**37.0%**|\n|_c) _<br>_Enhance_<br>_the_<br>_enabling_<br>_environme_<br>_nt for post_<br>_primary_<br>_education_<br>_and_<br>_training_|||||||||||||||\n|**c.2) Transition**<br>**rate to S5**||**Baseline**<br>**200827 **|||||||||||||\n\n\n\n24 Ministry of Education and Sport (MoES) is yet to pronounce itself on the 2014 EMIS statistics\n\n\n25 UBOS – Uganda Bureau of Statistics\n\n\n67", "output": {"entities": {"named_data": ["2014 EMIS statistics"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013394", "page": 78, "chunk": 2, "title": "Uganda - Post Primary Education and Training Adaptable Program Lending Project", "pdf_url": "https://documents.worldbank.org/curated/en/462481468306254644/pdf/ICR32340P110800IC0disclosed02020150.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2014 EMIS statistics", "label": "NAMED_DATA", "score": 0.8399609923362732, "start": 392, "end": 412, "probe_score": 0.9747, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\n(b) Factories receive a draft of the full assessment report regarding compliance on all assessment\n\nquestions, including information on whether the issues subject to public reporting are in\nnoncompliance.\n\n\n(c) When the assessment report is finalized, the factory’s compliance with the 29 publicly\n\nreported issues is published online, on the Better Work Transparency Portal (for all factories\nthat have had at least two assessments).\n\n\n(d) In response, factories can upload documents and photos on the public reporting website\n\n(including information from assessment reports).\n\n\n(e) A factory’s compliance findings remain on the website until a new assessment report is\n\npublished, at which point the website is updated to reflect the factory’s most recent assessment\ndata.\n\n\n(f) Every time a new assessment is completed for a factory, new compliance data replaces old\ndata.\n\n\n(g) Compliance data on factories that had not yet had two assessments when public reporting was\n\nlaunched is published following a factory’s second assessment.\n\n\n27", "output": {"entities": {"named_data": [], "descriptive_data": ["assessment\ndata", "compliance data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 35, "chunk": 1, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "assessment\ndata", "label": "DESCRIPTIVE_DATA", "score": 0.5295774340629578, "start": 759, "end": 774, "probe_score": 0.0491, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "compliance data", "label": "DESCRIPTIVE_DATA", "score": 0.565024197101593, "start": 842, "end": 857, "probe_score": 0.1116, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " in the July-August 2023 MSNA\nsurvey to 76% in the May-June 2024 SEIS\nsurvey. <sup>7</sup> This is not surprising, as the\nsituation of Ukrainians in the Polish labour\nmarket has clearly improved. First,\nemployment rate of working-age refugees\n\n\n\nfrom Ukraine has increased from 61% to\n69%, while their unemployment rate has\nhalved from 15% to 8%. Second, median\nnet wage of Ukrainian refugees grew from\nPLN 3,100 to PLN 4,000, i.e. by 29%. While\nhalf of this wage growth came from the\noverall high earnings growth in the country\ndue to high inflation (gross wages in the\ngeneral economy grew by 15% <sup>8</sup> ), it was still\na major improvement. Gross wage gains\nappear lower, with ZUS social insurance\ncontributions data for the period from\n\n\n\nJune 30, 2023 and June 30, 2024 showing\nan increase of 18% (compared to 15% for\nPolish citizens). As of June 30, 2024, only\n44% of ZUS-insured Ukrainian refugees\nhad an employment contract (compared\nto 82% of Polish citizens). Many may opt for\ncivil law contracts and self-employment to\nlimit their social insurance contributions to\nthe level of minimum wage.\n\n\n\n7 Together with refugees working remotely in Ukraine, their income from work would add up to 80% in the SEIS survey.\n\n8 From Q2 2023 to Q2 2024, <u>https://stat.gov.pl/en/latest-statistical-news/communications-and-announcements/list-of-communiques-and-announcements/average-</u>\n<u>gross-wage-in-the-second-quarter-2024,281,43.html</u>\n\n\n14\n\n\n\n9 These employment rates are very close to the ones from the Polish central bank", "output": {"entities": {"named_data": ["SEIS\nsurvey", "ZUS social insurance\ncontributions data", "SEIS survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 7, "chunk": 2, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS\nsurvey", "label": "NAMED_DATA", "score": 0.7722834944725037, "start": 65, "end": 76, "probe_score": 0.0, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "ZUS social insurance\ncontributions data", "label": "NAMED_DATA", "score": 0.8229132890701294, "start": 685, "end": 724, "probe_score": 0.6881, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "SEIS survey", "label": "NAMED_DATA", "score": 0.5829117894172668, "start": 1215, "end": 1226, "probe_score": 0.4802, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " diverse population. For example, our study suggests that men and women\npursue businesses that are very different in nature and this difference can drive some of the gender gaps in\nbusiness success. Future programs may wish to equalize business characteristics to help close the gendergap in micro-enterprise earnings (Delecourt and Ng, 2021).\n\n\n   - Future work studying the impact of business mentorship should directly test the assertion that a mentors’\nnetwork size predicts mentee success. While this assertion holds true in our study data, we do not causally\nestablish it. Such a test would allow for a more deliberate selection of mentors for future programs that is\nbased on characteristics known to predict mentee success.\n\n   - Future research could evaluate programs that directly aim to increase the network size for microentrepreneurs\nby introducing them to relevant stakeholders (suppliers, buyers, investors, other en- trepreneurs) and\nfacilitating a network of micro-entrepreneurs. This could help test whether lack of connections and networks\nare a direct impediment to micro-enterprise growth.\n\n\n   - Future qualitative work would benefit from examining a puzzle from the current study that the cash transfer\n(alone and with mentorship) does not result in any improvement in psychological well-being for refugee\nmen and women. This finding is in contrast to much of the literature that suggests, at minimum, a short\nterm positive impact of cash transfers on general well-being.\n\n\n   - To maximize learning from such a study, researchers and practitioners alike would benefit from more closely\ntracking the 1:1 interactions of mentors and mentees. Although such tracking may alter the nature of the\ninteractions, it could also help shed light on fidelity to research design and on mechanisms through which\nmentorship may influence outcomes.\n\n\n5.2 For city and national governments\n\n\n   - Policy makers should work to expand formal economic opportunities for women in general, and for refugee\nwomen in particular. Labor market failures can be a reason why many women are self-employed in the first\nplace and remain stuck", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["study data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001171", "page": 10, "chunk": 1, "title": "IRC Re:BUILD - Wave 1 RCT Research Brief - May 2025: Benefits of cash alone and cash+mentorship for Kenyan and refugee microentrepreneurs in Nairobi, Kenya", "pdf_url": "https://reliefweb.int/attachments/b30fa862-7cba-581b-87e5-82668953a4f4/Wave%201%20RCT%20-%20Research%20Brief-ReBUiLD.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "study data", "label": "VAGUE_DATA", "score": 0.7662088871002197, "start": 534, "end": 544, "probe_score": 0.0, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "ment est resté élevé et constant et les participants à l’enquête auprès des donateurs ont estimé à l’unanimité\nque le financement était suffisant.\n\n\n24 Communication avec le coordonnateur du groupe de travail sur la protection de l’enfance.\n\n\n25 Primauté du droit et justice; prévention et lutte contre la GBV; protection de l’enfance ; protection des personnes ou\ndes groupes de personnes ayant des besoins particuliers (p. ex. DI, ménages ayant une seule personne à leur tête,\nminorités, personnes âgées, personnes handicapées, etc.); prévention et réponse face aux menaces à la sûreté et\nà la sécurité physiques et autres violations des droits humains; lutte antimines; questions relatives au logement, au\nfoncier et à la propriété; promotion et facilitation de solutions; logistique et appui à la gestion des informations pour\nle module.\n\n\n26 http://www.refworld.org/cgi-bin/texis/vtx/rwmain?page=type&type=THEMREPORT&publisher=IASC&coi=&docid\n=4ae9acb6d&skip=0\n\n\n27 Primauté du droit et justice; protection des personnes ou des groupes de personnes ayant des besoins particuliers;\nprévention et réponse face aux menaces à la sûreté et à la sécurité physiques et autres violations des droits humains;\npromotion et facilitation de solutions; logistique et appui à la gestion des informations pour le module.\n\n\n28 Le point focal rend", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001007", "page": 73, "chunk": 2, "title": "Placer la protection au cœur de l’action humanitaire: Etude sur le financement de la protection dans les situations d’urgence humanitaire complexes", "pdf_url": "https://reliefweb.int/attachments/97ac79d1-3da2-30e3-a535-139a5c135b12/GPC_funding_study_print_FR.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Project** **Manaeem2nt** <sup>**and**</sup> <sup>million)</sup> administrative data appropriate, and clear in\n\n\n\ndefining the and\n**Innovative Activities**\n\n\n\nresponsibilities of all parties;\nNaCSA retains competent\n**(a) Capacity Building**\n\n\n\nstaff;\n\n                                             - Other governnent and donor\n**(b)** **Information and**\n\nsupport mobilized for\n\n\n\nsupport mobilized for\n**Sensitization**\ndecentralization to\ncomplement NaCSA efforts;\n(c) **Monitoring and**\n\n\n\n**Evaluation**\n\n\n\n**(d)** **Technical Assistance**\n\n\n(e) **Operating** Expenses\n\n\n\n-28", "output": {"entities": {"named_data": [], "descriptive_data": ["administrative data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015753", "page": 32, "chunk": 1, "title": "Uganda - Agriculture Sector Management Project", "pdf_url": "https://documents.worldbank.org/curated/en/624411468760537699/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "administrative data", "label": "DESCRIPTIVE_DATA", "score": 0.6927050352096558, "start": 64, "end": 83, "probe_score": 0.562, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**2. Trends in economic growth, inequality, and poverty**\n\n\n**2.1. Data**\n\n\nWe compile data from the Vietnam Household Living Standards Surveys (VHLSSs), which\n\n\nhas been widely employed by the government, the international community, and academic\n\n\nresearchers for poverty and inequality analysis for the country. The VHLSSs have been conducted\n\n\nby the General Statistics Office of Vietnam with technical support from the World Bank every two\n\n\nyears since 2002. We compile data on all 58 provinces and five centrally controlled municipalities\n\n\nand supplement this data with other data that we collected. <sup>2</sup> In particular, provincial government\n\n\nspending data for the period 2018-2020 is currently unavailable for all the 63 provinces in any\n\n\nofficial document. To get the most updated data, we manually collected the state spending and\n\n\ninvestment spending data for 2018-2020 from several sources including the Ministry of Finance’s\n\n\nwebsite, provincial finance departments’ websites, and relevant official documents.\n\n\nThe VHLSSs contain detailed data on individuals and households. Household-level data are\n\n\ncollected on durables, assets, production, income, and participation in government programs.\n\n\nIndividual-level data are collected on demographics, education, employment, health, and\n\n\nmigration. The 1999 Population and Housing Census was used as the sampling frame of the\n\n\nVHLSSs during 2002-2008, while the 2009 and 2019 Population and Housing Censuses were used\n\n\nas the sampling frame of the VHLSSs respectively for 2010-2016 and 2018-2020. Around 3,100\n\n\ncommunes were chosen as the primary sampling units out of the list of 10,000 communes for the\n\n\n2 These municipalities are Can Tho, Da Nang, Hai Phong, Hanoi, and Ho Chi Minh City.\n\n5", "output": {"entities": {"named_data": ["Vietnam Household Living Standards Surveys", "1999 Population and Housing Census", "2009 and 2019 Population and Housing Censuses"], "descriptive_data": ["provincial government\n\n\nspending data", "state spending and\n\n\ninvestment spending data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001252", "page": 6, "chunk": 0, "title": "idu12961e752165591458f1a01510cf5982fb3d9", "pdf_url": "https://local/prwp/idu12961e752165591458f1a01510cf5982fb3d9.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Vietnam Household Living Standards Surveys", "label": "NAMED_DATA", "score": 0.9110437035560608, "start": 101, "end": 143, "probe_score": 0.987, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "provincial government\n\n\nspending data", "label": "DESCRIPTIVE_DATA", "score": 0.8160399198532104, "start": 636, "end": 673, "probe_score": 0.8911, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "state spending and\n\n\ninvestment spending data", "label": "DESCRIPTIVE_DATA", "score": 0.8139411211013794, "start": 833, "end": 878, "probe_score": 0.8431, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "1999 Population and Housing Census", "label": "NAMED_DATA", "score": 0.8824930191040039, "start": 1329, "end": 1363, "probe_score": 0.9374, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2009 and 2019 Population and Housing Censuses", "label": "NAMED_DATA", "score": 0.5904537439346313, "start": 1439, "end": 1484, "probe_score": 0.9746, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Such an adjustment can be done for a particular year, or by taking the average ratio for a country\n\nover a longer time period. We estimate such country specific IPLs for use with national accounts\n\nfor 1990, ensuring that poverty estimates from national accounts and surveys are aligned in that\n\nyear. The results for global poverty are shown in Panel C of Figure 5. While the poverty\n\nestimates are equal (by design) in 1990, there is considerable variation over time, and, in global\n\nmeasures the rate of decline is much larger, due to the faster growth rates of national accounts\n\nmeans compared with survey means.\n\n\nAcross all the methods which involve substituting survey means with national accounts\n\nmeans, poverty is estimated to be lower and falling faster when compared to traditional survey\n\nmeasures. The more rapid decline seen in the poverty measures using national accounts points to\n\na concern with current use of national accounts growth rates in extrapolating household survey\n\nestimates for years with missing surveys. Even if household survey means are used for poverty\n\nestimation for survey years, national accounts growth rates are used to interpolate such estimates\n\nto non-survey years and for nowcasts and projections of poverty in the future. Current methods\n\nuse actual or projected national accounts growth rates to align poverty estimates to non-survey\n\nyears for global aggregation. Removing the bias implicit in this method suggests a slower global\n\ndecline in poverty than the World Banks official poverty numbers.\n\n\nBecause India, Indonesia and China, countries which historically have been the home of a\n\nlarge share of the global poor, typically have household surveys for most reference years for\n\nwhich the World Bank reports poverty, the effect on global numbers is of less concern. However,\n\nthe lack of recent surveys available for India, the home to a large share of the world’s poor, has\n\ngenerated greater uncertainty about poverty estimates from national accounts based extrapolation\n\nof the latest available survey. <sup>31</sup> Extrapolations or projections of poverty beyond the World\n\nBank’s", "output": {"entities": {"named_data": [], "descriptive_data": ["national accounts", "national accounts", "household surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001880", "page": 25, "chunk": 0, "title": "mind the gap disparities in assessments of living standards using national accounts and household surveys", "pdf_url": "https://local/prwp/mind-the-gap-disparities-in-assessments-of-living-standards-using-national-accounts-and-household-surveys.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "national accounts", "label": "DESCRIPTIVE_DATA", "score": 0.531441867351532, "start": 179, "end": 196, "probe_score": 0.9677, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "national accounts", "label": "DESCRIPTIVE_DATA", "score": 0.5714645981788635, "start": 245, "end": 262, "probe_score": 0.988, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "household surveys", "label": "DESCRIPTIVE_DATA", "score": 0.7580846548080444, "start": 1687, "end": 1704, "probe_score": 0.8888, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Goods: is applicable for those contracts identified in the Procurement Plan\ntables;\n\n\nWorks: is applicable for those contracts identified in the Procurement Plan\ntables", "output": {"entities": {"named_data": [], "descriptive_data": ["Procurement Plan\ntables", "Procurement Plan\ntables"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011288", "page": 2, "chunk": 0, "title": "Ethiopia - AFRICA EAST- P172479- Strengthen Ethiopia?s Adaptive Safety Net - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/325521634653883124/pdf/Ethiopia-AFRICA-EAST-P172479-Strengthen-Ethiopia-s-Adaptive-Safety-Net-Procurement-Plan.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Procurement Plan\ntables", "label": "DESCRIPTIVE_DATA", "score": 0.6941680312156677, "start": 59, "end": 82, "probe_score": 0.0014, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Procurement Plan\ntables", "label": "DESCRIPTIVE_DATA", "score": 0.518972635269165, "start": 145, "end": 168, "probe_score": 0.0002, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " sexual abuse. A more recent study of violence in\nBrazilian schools found that 8% of students from 5 <sup>th</sup> to 8 <sup>th</sup> grade had witnessed sexual\nviolence within the school environment (Abramovay and Franco, 2004). <sup>37</sup> [^37: The study covered middle schools in 14 Brazilian state capitals. The percentage of students who had\nwitnessed sexual violence ranged from a low of 5% in Vitoria (Espirito Santo) and Fortaleza (Ceara) to a high\nof 12% in Cuiaba (Mato Grosso).  The way in which the question was formulated does not permit identifying\nwhat percentage of girls were victimized by sexual violence.] Data on sexual\nviolence, however, remain spotty for Latin America and the Caribbean.\n\n\n35 An unsafe environment in school may dissuade parents from enrolling girls in school or may lead to\nincreased rates of school abandonment (WCRW, n/d). While this has been documented for the African context,\nit may or may not be important in Latin America and the Caribbean, where girls’ enrollment rates typically\nexceed boys’ rates.\n36 According to recent studies in six African countries, between 16% and 47% of girls in primary and\nsecondary schools report sexual abuse or harassment, with both male fellow students and male teachers\nresponsible for the abuse (Leach et al., 2003). In Botswana, 20% of female students reported having being\nasked by teachers for sexual relations (Rosetti, 2001, cited in Leach, 2003). In Cameroon, 8% of sexual abuse\ntowards girls was accounted for by teachers (Mbassa Menick, 2001, reported in Leach, 2003). The DHS survey\nin South Africa, surveying women between 15 and 49 years of age, found that 37.7% of all rape victims\nidentified a teacher or principal as the rapist (Medical Research Council, 2000). At the same time, girls in\nSouth Africa are more", "output": {"entities": {"named_data": ["DHS survey"], "descriptive_data": [], "vague_data": ["Data on sexual\nviolence"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002693", "page": 46, "chunk": 1, "title": "wps3438", "pdf_url": "https://local/prwp/wps3438.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data on sexual\nviolence", "label": "VAGUE_DATA", "score": 0.638717532157898, "start": 628, "end": 651, "probe_score": 0.0038, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "DHS survey", "label": "NAMED_DATA", "score": 0.8732020258903503, "start": 1566, "end": 1576, "probe_score": 1.0, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "POST DISTRIBUTION MONITORING APRIL – 2019\n\n\n**Chart 6:** Score on usefulness of items\n\n\nuseful item (4.18) and antiseptic liquid rated the least useful (4.13) compared to other items in the kit.\n\n\nQuantity of items received versus entitlement\n\n\nThe refugees were asked whether they received the quantity of NFIs as entitled. Chart 7 shows their responses are divided between those who received the correct number of items according to UNHCR standard operating procedure for NFIs, and refugees who received more and less than their entitlements.\n\n\nNinety-two percent of the refugees reported receiving the same quantity as per their entitlement, an increase of 15% compared to September 2018 PDM. An average of 3% of the respondents stated that they\nreceived more items than they were entitled in 17 out of the 31 individual items distributed, in particular jerrycans, which are distributed as part of the WASH hygiene kit (19% of the respondents saying they received\nmore than their entitlement). An average of 4% of the respondents reported receiving less items than they\nwere entitled to in 22 out of 31 relief items provided in all standard NFI packages, particularly for non-disposable sanitary cloths which are included in the WASH hygiene kit (23% of the respondents said they received\nless than their entitlement). Unlike in the September 2018 PDM, rope was reported to be received in the\nexact quantity in shelter kits and only 3% of the respondents reported receiving more than their entitlements. 4% of the respondents reported receiving less than their entitlements in the Pre-Monsoon Kit.\n\n\nRefugees reported receiving the exact quantity for all items within the shelter kit except for tool kit. Only 2%\nof the respondents reported receiving more and less than entitled.\n\n\nSimilar to the March and September 2018 PDMs, more refugees reported receiving more or less than their\nentitlements for the WASH Hygiene Kit. A sensitization for refugee on the contents of the package and advice on the way to use the items", "output": {"entities": {"named_data": ["September 2018 PDM"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000426", "page": 11, "chunk": 0, "title": "Post-Distribution Monitoring: Shelter and Non-Food Items, Bangladesh Refugee Situation (April 2019)", "pdf_url": "https://reliefweb.int/attachments/3aa5c6b9-74ce-3996-bf77-a4c672b01f7c/73047.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "September 2018 PDM", "label": "NAMED_DATA", "score": 0.6064453721046448, "start": 676, "end": 694, "probe_score": 0.9928, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " EDSM 2021. Même dans les zones rurales, la part est supérieure à 83% au niveau national.\n\n\nÉ T U D E C O M P A R A T I V E S U R L A S I T U A T I O N S O C I O   - É C O N O M I Q U E D E S R É F U G I É S E T D E S\n\nC O M M U N A U T É S H Ô T E S D A N S L A R É G I O N D U H O D H C H A R G U I, M A U R I T A N I E\n\n\n3 9", "output": {"entities": {"named_data": ["EDSM 2021"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001566", "page": 41, "chunk": 2, "title": "Étude comparative sur la situation socio-économique des réfugiés et des communautés hôtes dans la région du Hodh Chargui, Mauritanie", "pdf_url": "https://reliefweb.int/attachments/f2fc6590-4389-4bcc-901d-df4bf063819e/Syspons_Rapport_Etude%20comparative%20et%20profilage%20Mauritanie%20GIZ%20UNHCR%20_final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "EDSM 2021", "label": "NAMED_DATA", "score": 0.8437929153442383, "start": 1, "end": 10, "probe_score": 0.1428, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "intervention generates citywide road safety improvements through the City's Traffic Management Center, traffic signals in selected corridors, traffic enforcement_**<br>**_equipment procured for Addis Ababa police commission, parking strategy, driver licensing and vehicle registration systems._**<br>**_Due to changes to the unit and scope of this indicator, the original baseline data is no longer relevant. This restructuring revised the baseline at 9.8._**|**_Rationale:_**<br>**_The indicator is revised from \"Pedestrian fatalities on prescribed corridors per 1,000 vehicles\" to \"Citywide pedestrian fatalities Per 10,000 Vehicle\".  TRANSIP_**<br>**_intervention generates citywide road safety improvements through the City's Traffic Management Center, traffic signals in selected corridors, traffic enforcement_**<br>**_equipment procured for Addis Ababa police commission, parking strategy, driver licensing and vehicle registration systems._**<br>**_Due to changes to the unit and scope of this indicator, the original baseline data is no longer relevant. This restructuring revised the baseline at 9.8._**|**_Rationale:_**<br>**_The indicator is revised from \"Pedestrian fatalities on prescribed corridors per 1,000 vehicles\" to \"Citywide pedestrian fatalities Per 10,000 Vehicle\".  TRANSIP_**<br>**_intervention generates citywide road safety improvements through the City's Traffic Management Center, traffic signals in selected corridors, traffic enforcement_**<br>**_equipment procured for Addis Ababa police commission, parking strategy, driver licensing and vehicle registration systems._**<br>**_Due to changes to the unit and scope of this indicator, the original baseline data is no longer", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010508", "page": 14, "chunk": 10, "title": "Disclosable Restructuring Paper - Ethiopia: Transport Systems Improvement Project (TRANSIP) - P151819", "pdf_url": "https://documents.worldbank.org/curated/en/271251615492977387/pdf/Disclosable-Restructuring-Paper-Ethiopia-Transport-Systems-Improvement-Project-TRANSIP-P151819.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "baseline data", "label": "VAGUE_DATA", "score": 0.5317444801330566, "start": 372, "end": 385, "probe_score": 0.9143, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 1\nPage 2 of 3\n\n\n**Project Development** **Outcome / Impact** **Project reports:** **(from Objective to Purpose'**\n**Objective:** **Indicators:**\nExpand access to basic Increased number of school Project Reports. It is assumed that\neducation. places. Government's current fiscal\nsituation will be resolved\n\n(salary payment to civil\nservants and teachers).\nEnrollment increases in MOE reports. Expansion of facilities and\nprimary schools from 35,000 quality will contribute to\nto 80,000 increased enrollment\nincluding among girls.\nIncreased availability of It is assumed that the\ntextbooks. Government maintains\ndouble-shifting.\n\n\nTrained primary school head Headteachers have autonomy\nteachers. and authority in managing the\nschools.\nBetter trained contractual Contractual teachers are\nteachers recruited early enough before\nthe school year to allow time\nfor training.\n\n\n**Output from each** **Output Indicators:** **Project reports:** **(from Outputs to Objective)**\n**Component:**\nIncreased number of school 226 classrooms will be built Monthly disbursement Availability of school places\nplaces. increasing capacity by over summary. will increase enrollment.\n20,000 based on double\nshifting.\nProvide textbooks. Numbers of textbooks per Semi-annual Provision of textbooks will\npupil increases. supervision reports. improve learning.\nTrained primary school head- Primary school head-teachers Annual audit reports; Better trained head-teachers\nteachers. trained and Guidebook for site visits. will improve school\nschool management prepared efficiency.\nand distributed.", "output": {"entities": {"named_data": ["MOE reports"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007916", "page": 30, "chunk": 0, "title": "Uganda - Financial Sector Adjustment Credit Project", "pdf_url": "https://documents.worldbank.org/curated/en/100881468117888632/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "MOE reports", "label": "NAMED_DATA", "score": 0.6933835744857788, "start": 385, "end": 396, "probe_score": 0.8075, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nDjibouti Integrated Slum Upgrading Project (P162901)\n\n\nof the population in Djibouti Ville and 75 percent of rural households to food insecurity. Djibouti’s natural\nhazard vulnerability is aggravated by limited water resource management, insufficient land-use planning,\nconstraining and nonsystematic building codes enforcement, and limited capacity to prevent and respond\neffectively to natural disasters. Today, it is estimated that about a quarter of one million people residing in\nDjibouti require direct assistance, including Djiboutian nationals living in extreme poverty, but also those that\nhave been forcibly displaced internally and from neighboring countries.\n\n\n4. **The refugee and displaced population has been growing at a steady pace due to the prolonged**\n**drought in the region and conflicts in neighboring countries.** Djibouti hosts a significant foreign population\n(apart from the expatriate population), though its number is unknown. A part of this population has come to\nDjibouti to join their family members (some of them being Djiboutian), others for economic opportunities or\nto flee difficult situation. In 2017, more than 27,000 refugees, mostly from Somali and Ethiopia as well as\nfrom Yemen, were registered in Djibouti, a number that has been growing (22,000 in 2015). In addition, it is\nestimated that about 94,000 people are also coming to Djibouti as a transit stop from the Horn of Africa\ntowards the Gulf countries. 30,000 Yemeni have also come to the country since the beginning of the conflict\nin 2015. A part of that foreign population has settled in the three refugee camps of the country (Holl Holl,\nd'Ali Addeh, and Markazi) and the larger part has settled in Djibouti cities. In a 2017 survey conducted in\nthree neighborhoods of Djibouti Ville, 10 to 12 percent of the population declared to be non-Djiboutian\nnationals, while an additional 20 percent could not prove their citizenship.\n\n\n**B. Sectoral", "output": {"entities": {"named_data": [], "descriptive_data": ["2017 survey conducted in\nthree neighborhoods of Djibouti Ville"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000015", "page": 12, "chunk": 0, "title": "Djibouti - Integrated Slum Upgrading Project", "pdf_url": "http://documents1.worldbank.org/curated/en/145511542078037348/pdf/project-appraisal-document-pad-P162901-20181017-10232018-636776568298453523.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2017 survey conducted in\nthree neighborhoods of Djibouti Ville", "label": "DESCRIPTIVE_DATA", "score": 0.7909865975379944, "start": 1743, "end": 1805, "probe_score": 0.9182, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " comparative data, the difference\nbetween the two years is only 2 percentage points.\n\n\n\n22 In 2023 there was data for only 7 out of the 10 countries we have\ndata for in 2024.\n23 There is very little correlation between these variables.\n24 See full data for a more detailed breakdown per type of\nenrolment.\n25 This means that 73 per cent of those not enrolled in host country\nschools are enrolled in online schooling.\n26 The _All-Ukrainian Online School_, _Всеукраїнська школа онлайн_,\nsee <u>[https://lms.e-school.net.ua/](https://lms.e-school.net.ua/)</u>\n27 _український компонент освітніх програм_, see <u>[https://](https://offlineschool.mon.gov.ua/)</u>\n<u>[offlineschool.mon.gov.ua/. The grade recognition system](https://offlineschool.mon.gov.ua/)</u>\nfacilitates reintegration into the Ukrainian education system of\nstudents who have studied abroad and who return to Ukraine. For\nexample, a student who passed mathematics in a given school\nyear in Poland will be able to present that grade to a Ukrainian\nschool upon return so the student does not have to redo the\nsubject.\n28 This usually means that children study 20-30 hours a week, as\nthey would if they were in school under normal circumstances.\n29 For example, participating in the National Multi-Subject Test to\nobtain a secondary education certificate that allows pupils to then\nenrol in higher education, see <u>[https://enic.in.ua/index.php/en/](https://enic.in.ua/index", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["comparative data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001564", "page": 18, "chunk": 9, "title": "Education of refugee children and youth from Ukraine: An analysis of major trends and challenges in education of refugees from Ukraine in Europe", "pdf_url": "https://reliefweb.int/attachments/f2e33cac-7266-570d-a29f-6f183b0e58bb/SEIS%20report%20education%202025%20-%20FINAL%2025042025.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "comparative data", "label": "VAGUE_DATA", "score": 0.6636338829994202, "start": 1, "end": 17, "probe_score": 0.3187, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Beach (1903) are reported for the other regressions. <sup>14</sup>\n\nThese two atlases are standard sources for georeferenced mission stations\nin Africa in the economic literature. However, Jedwab, Meier zu Selhausen,\nand Moradi (2018) have documented that both sources are subject to measurement error in the exact locations of missions due to geocoding mistakes.\nThey also showed that any issue of _classical_ measurement error can be substantially mitigated by using large enough cells. In particular, classical measurement error is almost completely eliminated when the cell size is increased\nto 0 _._ 3 <sup>_◦_</sup> _×_ 0 _._ 3 <sup>_◦_</sup> . Reassuringly, the present study uses even larger cells, with\na resolution of 0 _._ 5 <sup>_◦_</sup> _×_ 0 _._ 5 <sup>_◦_</sup> . Jedwab, Meier zu Selhausen, and Moradi (2018)\nalso collected more complete records of missions in Ghana from multiple\nsources. They were able to show that for Ghana, the correlation between\ntheir geocoded locations and those reported in Beach (1903) and Roome\n(1924) is very high only for those missions that were established early, but\nis lower for missions that were established later. <sup>15</sup> As early missions were\nlocated in better and more accessible areas, this might induce nonclassical\nmeasurement error, which tends to magnify the omitted variable bias induced\nby self-selection of missionaries. The next section explains how the analysis\ndeals with the selection issue.\n\n###### **2.3 Selection of Missions and Historical Controls**\n\n\nMissionary activity in Africa was not randomly assigned across the continent,\nas illustrated by the", "output": {"entities": {"named_data": [], "descriptive_data": ["records of missions in Ghana"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002281", "page": 12, "chunk": 0, "title": "the role of historical christian missions in the location of world bank aid in africa", "pdf_url": "https://local/prwp/the-role-of-historical-christian-missions-in-the-location-of-world-bank-aid-in-africa.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "records of missions in Ghana", "label": "DESCRIPTIVE_DATA", "score": 0.9098020792007446, "start": 855, "end": 883, "probe_score": 0.8099, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "#### **References**\n\nAguiar, M. and G. Gopinath (2007). Emerging market business cycles: The cycle is\n\nthe trend. _Journal_ _of_ _Political_ _Economy_ _115_, 69–102.\n\n\nBarro, R. and X. Sala-i Martin (2003). Economic growth. _MIT_ _Press_ .\n\n\nBenigno, P. (2007). Portfolio choices with near rational agents: A solution of some\n\ninternational-finance puzzles. _NBER_ _Working_ _Papers_ _No._ _13173_ .\n\n\nBertaut, C. C. and R. W. Tryon (2007). Monthly estimates of u.s. cross-border\n\nsecurities positions. _Board_ _of_ _Governors_ _of_ _the_ _Federal_ _Reserve_ _System_ _(U.S.)_\n\n_International_ _Finance_ _Discussion_ _Papers_ _No._ _910_ .\n\n\nBurnside, G. (1991). Real business cycle models: Linear approximation and gmm\n\nestimation. _mimeo,_ _The_ _World_ _Bank_ .\n\n\nCaballero, R. J., E. Farhi, and P.-O. Gourinchas (2006). An equilibrium model of\n\n”global imbalances” and low interest rates. _NBER_ _Working_ _Papers_ _No._ _11996_ .\n\n\nCoeurdacier, N., R. Kollmann, and P. Martin (2009). International portfolios, cap\nital accummulation and the dynamics of capital flows. _Journal_ _of_ _Interntional_\n\n_Economics_ _forthcoming_ .\n\n\nCurcuru, S. E., T. Dvorak, and F. Warnock (2008). Cross-border", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004366", "page": 19, "chunk": 0, "title": "wps5174", "pdf_url": "https://local/prwp/wps5174.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Disbursement forecast\n\n\n\nContract number\n*Contract subject\nAwardee\n*Launching date\n-Expected delivery date\n-Non objection date\n*Expected date of final delivery\n*Bidder nationality\n*Contract allocation (general account, budget, loan\ncategory, geographic area)\n*List of contracts\nManagement of financial -Standard financial statements (balance sheet;\naccounts statement of sources and uses of funds/income\nstatement, ...)\n*LACI reports for the project duration\nFixed Assets management -Inventory of Fixed Assets (type, quantity, valuation,\ndate of service, etc.)\n\n\n\nSupplier\nAccounting category ; budgetary and accounting\nallocation of fixed assets\n\n\n\nLocation\nDepreciation\n-Disposal of Fixed assets\n\n\n\n**Module** Functions\nSorting parameters Project ID and currency used\n\n                  - Fiscal years\nCurrency\nDecentralized data entry locations\n\n\n\nChart of accounts, managerial reports, geographic\nareas of intervention, etc.\n\n\n\n\n                - Books of accounts\nDonors\n\n                 - Contracts\nCategories of disbursement\nUser Management Data storage ; restitution ; correction; cleaning; etc.\n\n                - Import/export of data to other Tempro modules\n\n\n\nIt is expected that the application would be modified to differentiate the operations from the\nprojects, as well as funding sources to allow for reporting in financial and accounting terms of the\nproject objectives and activities. The concept should allow for proper monitoring of the project\nduring the life of the credit, namely: (i) chart of accounts; (ii) by category, component, and subcomponent; (iii) by geography (type of establishment, site and district); (iv) by category of\nexpenses; and (v) in local and foreign currency. Reporting of multi-level data is planned, which\n**wiU** bring about a more dynamic approach to the management of the project, and which should", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["multi-level data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000161", "page": 51, "chunk": 0, "title": "Cambodia - Social Fund II Project", "pdf_url": "http://documents1.worldbank.org/curated/en/932001468769834027/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "multi-level data", "label": "VAGUE_DATA", "score": 0.6651609539985657, "start": 1720, "end": 1736, "probe_score": 0.4661, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " This is particularly\nevident among women, who make up the\nmajority of refugees. The employment\nrate for women aged 20-64 has grown\nconsistently from 68.2% in Q2 2021 to\n70.2% in Q2 2022, 71.7% in Q2 2023, and\n72.2% in Q2 2024 (see Chart 26). The\nunemployment rate for women aged\n20-64 has consistently fallen, from 3.5% in\nQ2 2021 to 3.0% in Q2 2022, 2.6% in both\nQ2 2023 and Q2 2024.\n\n\n\nSecond, panel regression analysis shows\nthat a larger influx of Ukrainian refugees\nat the poviat level was accompanied by\na larger increase in employment rates\nfor Polish citizens along with a larger\ndecrease in registered unemployment\nrates. The data sample for all regressions\nencompassed quarterly data for all\n380 poviats from Q1 2022 to Q2 2024.\nThe Ukrainian refugee share variable was\nconstructed as the share of Ukrainian\nrefugees among all employed, temporarily\nemployed, and self-employed persons\ninsured with ZUS in a given poviat at the\nend of the quarter. The employment rate\nof Polish citizens was constructed as the\nshare of Polish citizens who are employed,\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\ntemporarily employed, and self-employed\nand who are insured with ZUS, divided by\nthe population from GUS in a given poviat\nin a given quarter (estimated based on halfyear population data). The unemployment\nrate is the registered unemployment\nrate series from GUS. Fixed effects panel\nregressions show that an increase in the\nemployment share of Ukrainian refugees\nby 1 percentage point correlates with an\nincrease in Polish citizens' employment\nrates by 0.5% and a decrease in the\nunemployment rate by 0.3%, in the\npreferred specification with dummy\nvariables for all quarters. All results are\nstatistically significant at a 0.01 level.\n\n\n\n**", "output": {"entities": {"named_data": [], "descriptive_data": ["quarterly data for all\n380 poviats", "halfyear population data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 19, "chunk": 1, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "quarterly data for all\n380 poviats", "label": "DESCRIPTIVE_DATA", "score": 0.7434679865837097, "start": 680, "end": 714, "probe_score": 0.8312, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "halfyear population data", "label": "DESCRIPTIVE_DATA", "score": 0.8687865734100342, "start": 1303, "end": 1327, "probe_score": 0.745, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " all refugee camps, with children under 5 years\nbeing particularly affected by malnutrition and micronutrient deficiencies. <sup>14</sup>\n\n6. **The devolution of health service delivery in 2013 has presented mixed results** . Decentralization of responsibility\nfor public sector health service delivery to the 47 county Governments has been accompanied by a 34.0 percent increase\nin the number of facilities, a 46.0 percent improvement in public health worker density between 2014 and 2020, and many\ncounties have equipped their health facilities to respond to the evolving health needs. County Governments are also\nexploring approaches to strengthen primary care service delivery through governance and financial management reforms,\nsuch as the Facility Improvement Fund. However, county Governments have faced significant challenges in management\nof human resources for health, ensuring availability of Health Products and Technologies (HPTs), improving quality of care,\n\n\n[10 World Bank Estimates: https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=KE](https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=KE)\n\n11 Kenya Demographic Health Survey, 2022. Key Indicators Report\n12 Ministry of Health Kenya (2020) Kenya Progress Report on Health and Health-Related SDGs.\n13 Kenya Demographic Health Survey, 2022\n14 UNHCR & WFP, Joint Assessment Mission Kenya-Refugee Operations (2022)\n\nPage 10 of 43", "output": {"entities": {"named_data": ["World Bank Estimates"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000000", "page": 15, "chunk": 2, "title": "Kenya - Building Resilient and Responsive Health Systems Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099022324094562763/pdf/BOSIB1554c314c0a2187c019d7e85bc2a91.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "World Bank Estimates", "label": "NAMED_DATA", "score": 0.5481935739517212, "start": 979, "end": 999, "probe_score": 0.0063, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nLebanon Health Resilience Project (P163476)\n\n\n|Indicator Name|Core|Unit of<br>Measure|Baseline|End Target|Frequency|Data Source/Methodology|Responsibility for<br>Data Collection|\n|---|---|---|---|---|---|---|---|\n|Description:Percent of female beneficiaries of the total number of beneficiaries who will have access to the essential healthcare services package.|Description:Percent of female beneficiaries of the total number of beneficiaries who will have access to the essential healthcare services package.|Description:Percent of female beneficiaries of the total number of beneficiaries who will have access to the essential healthcare services package.|Description:Percent of female beneficiaries of the total number of beneficiaries who will have access to the essential healthcare services package.|Description:Percent of female beneficiaries of the total number of beneficiaries who will have access to the essential healthcare services package.|Description:Percent of female beneficiaries of the total number of beneficiaries who will have access to the essential healthcare services package.|Description:Percent of female beneficiaries of the total number of beneficiaries who will have access to the essential healthcare services package.|Description:Percent of female beneficiaries of the total number of beneficiaries who will have access to the essential healthcare services package.|\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Name: Pregnant women<br>receiving at least four<br>antenatal care visits|Col3|Percentage|50.00|70.00|Annual|HIS|PMU|Col10|\n|---|---|---|---|---|---|---|---|---|---|\n||Description:Percent of pregnant women (from among the cumulative number of", "output": {"entities": {"named_data": ["Lebanon Health Resilience Project"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000108", "page": 43, "chunk": 0, "title": "Lebanon - Health Resilience Project", "pdf_url": "http://documents1.worldbank.org/curated/en/616901498701694043/pdf/Lebanon-Health-PAD-PAD2358-06152017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Lebanon Health Resilience Project", "label": "NAMED_DATA", "score": 0.7395796179771423, "start": 19, "end": 52, "probe_score": 0.947, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 1\nPage 2 of 3\n\n\n**Project Development** **Outcome / Impact** **Project reports:** **(from Objective to Purpose'**\n**Objective:** **Indicators:**\nExpand access to basic Increased number of school Project Reports. It is assumed that\neducation. places. Government's current fiscal\nsituation will be resolved\n\n(salary payment to civil\nservants and teachers).\nEnrollment increases in MOE reports. Expansion of facilities and\nprimary schools from 35,000 quality will contribute to\nto 80,000 increased enrollment\nincluding among girls.\nIncreased availability of It is assumed that the\ntextbooks. Government maintains\ndouble-shifting.\n\n\nTrained primary school head Headteachers have autonomy\nteachers. and authority in managing the\nschools.\nBetter trained contractual Contractual teachers are\nteachers recruited early enough before\nthe school year to allow time\nfor training.\n\n\n**Output from each** **Output Indicators:** **Project reports:** **(from Outputs to Objective)**\n**Component:**\nIncreased number of school 226 classrooms will be built Monthly disbursement Availability of school places\nplaces. increasing capacity by over summary. will increase enrollment.\n20,000 based on double\nshifting.\nProvide textbooks. Numbers of textbooks per Semi-annual Provision of textbooks will\npupil increases. supervision reports. improve learning.\nTrained primary school head- Primary school head-teachers Annual audit reports; Better trained head-teachers\nteachers. trained and Guidebook for site visits. will improve school\nschool management prepared efficiency.\nand distributed.", "output": {"entities": {"named_data": ["MOE reports"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020879", "page": 30, "chunk": 0, "title": "Kenya - Olkaria Geothermal Power Expansion Project", "pdf_url": "https://documents.worldbank.org/curated/en/968811468046806721/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "MOE reports", "label": "NAMED_DATA", "score": 0.6933835744857788, "start": 385, "end": 396, "probe_score": 0.8075, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "output": {"entities": {"named_data": [], "descriptive_data": ["random survey"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000041", "page": 16, "chunk": 0, "title": "Jordan - Community Infrastructure Project", "pdf_url": "http://documents1.worldbank.org/curated/en/294581468773394111/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7714613080024719, "start": 379, "end": 395, "probe_score": 0.582, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "random survey", "label": "DESCRIPTIVE_DATA", "score": 0.7173007130622864, "start": 1487, "end": 1500, "probe_score": 0.012, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_Environmental & Social Impact Assessment Project Report for the Construction of Kenol Hospital Road in_\n\n_<u>Murang’a County of the Nairobi Metropolitan Region</u>_\n\n\n**CHAPTER THREE: BASELINE INFORMATION OF THE STUDY AREA**\n\n\n**3.1** **Introduction**\n\n\nBaseline conditions cover all the biophysical and socio-economic conditions in the\nproject area. Gathering of baseline data is necessary to meet the following\nobjectives:\n\n`o` To _understand_ key biological, physical, ecological, social, cultural, economic,\n\nand political conditions in areas potentially affected by the proposed project;\n\n`o` To _understand_ the expectations and concerns of a range of stakeholders on the\n\nproposed development ;\n\n`o` To _inform_ the development of mitigation measures;\n\n`o` To _benchmark_ future socio-economic changes/ impacts and assess the\n\neffectiveness of mitigation measures.\n\n\n**3.2** **Project Location**\n\n\n**3.2** **Environmental Baseline Profile**\n\n\n**_3.2.1 Relief and physiography_**\n\n\nThe land of the project area has an altitude of about 1520 metres above sea level\nand rises to an altitude of 3,353m above sea level along the slopes of the Aberdares.\nThe highest areas to the West have deeply dissected topography and are well\n\n\n29", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013736", "page": 28, "chunk": 0, "title": "Kenya - Nairobi Metropolitan Services Improvement Project : Environmental Assessment (Vol. 10 of 41) : Environmental and Social Impact Assessment (ESIA) Project Report for the rehabilitation of Kenol Hospital Road in Murang'a county", "pdf_url": "https://documents.worldbank.org/curated/en/485971490937868218/pdf/SFG1405-V10-EA-P107314-Box402899B-PUBLIC-Disclosed-3-29-2017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "baseline data", "label": "VAGUE_DATA", "score": 0.6473055481910706, "start": 365, "end": 378, "probe_score": 0.0825, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 2015 World Bank Country Partnership Framework (CPF) also called for\napplication of a prioritization tool. These factors confirmed demand for\nprioritization of investments in infrastructure planning.\n\nThe IPF was applied to a selection of 35 proposed projects in water supply and\nsanitation and 19 in transport. These projects were identified in consultation\nwith the Ministry of Economics and Finance. The pilot offered a key opportunity\nto replicate and refine the existing framework, in that it entailed decision\nanalysis based on limited financial‐economic data, particularly for a portion of\nthe water projects. In this way, it replicated a common input problem for\ninfrastructure decision‐making, namely restrictions on data.\n\nPlanners from several agencies, in consultation with the Ministry of Economy\nand Finance and a team from the World Bank, agreed on a set of component SEI\nand FEI variables. The SEI variables initially selected included the number of\nbeneficiaries (BEN), direct jobs created during implementation (EMP), the\npopulation of poor serviced by the project (POOR), social and environmental\nrisks (SER), and the carbon footprint (CO2). The final analysis used only the first\nthree, due to data problems and lack of specificity in the risk variable. <sup>17</sup>\n\n\n17. See Marcelo, Mandri‐Perrott, & House, 2015 for a description of these challenges.\n\n\n20", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["financial‐economic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006701", "page": 21, "chunk": 1, "title": "wps7674", "pdf_url": "https://local/prwp/wps7674.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "financial‐economic data", "label": "VAGUE_DATA", "score": 0.6543342471122742, "start": 542, "end": 565, "probe_score": 0.2534, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nKenya Social and Economic Inclusion Project (P164654)\n\n\narrangements for monitoring progress and resolution of any difficulties; and (v) agreed arrangements for\nthe sharing of information on enrollment and usage of NHIF services, preferably automated.\n\n\n35. **Expansion of existing nutrition-sensitive safety net.** Under the proposed KSEIP, the SDSP would\nexpand NICHE to four additional counties (Kilifi, Marsabit, Turkana and West Pokot) and continue scale\nup in Kitui county, based on lessons during the pilot. This expansion will benefit approximately 138,600\nindividuals in 23,500 households. <sup>30</sup> [^30: Estimates based on current data from NICHE and the HSNP suggest that an average of 1.5 top-ups per household would be\npaid, amounting to around 38,000 cash top-ups in total.] Households in the four NSNP programs <sup>31</sup> [^31: OPCT beneficiaries over 70 years of age universally targeted at the individual level will not be included as NICHE beneficiaries,\nas NICHE aims to provide benefits to the poor and vulnerable.] would be targeted as in Kitui\ncounty. The provision of nutrition counselling would be financed through IPF to ensure quality and closer\nsupervision. For this intervention, the SDSP will directly associate UNICEF (under an agreement to be\nsigned between the SDSP and UNICEF) to provide technical assistance, including implementation support\nand rigorous evaluation, findings of which would be used to adjust the intervention design, as needed, to\nachieve the desired outcomes. Moreover, the partnership with UNICEF would clearly indicate a strategy\nfor capacity building and gradual hand over of key roles to relevant GoK functionaries to ensure\nsustainability of efforts. Support from UNICEF will be provided in a phased-out manner to ensure that by\nend of year 3, the GoK takes over NICHE implementation throughout and beyond the life of the project.\nDetails of the technical assistance will be spelled out in the agreement between the SDSP and UNICEF.\nThe requirements of UNICEF", "output": {"entities": {"named_data": [], "descriptive_data": ["current data from NICHE and the HSNP"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013099", "page": 22, "chunk": 0, "title": "Kenya - Social and Economic Inclusion Project", "pdf_url": "https://documents.worldbank.org/curated/en/442271543719657009/pdf/KENYA-SOCIAL-PAD-11062018-636792984505888118.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "current data from NICHE and the HSNP", "label": "DESCRIPTIVE_DATA", "score": 0.6383776068687439, "start": 657, "end": 693, "probe_score": 0.9525, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the productivity of the transport sector or the costs of\n\n\ntransportation, and examine the four dimensions of trade facilitation noted above. We use a\n\n\ngravity model of bilateral trade flows for our estimations, rather than a computable general\n\n\nequilibrium (CGE) approach. The scenarios examined here do not assume that all countries\n\n\nin our sample (those that have acceded to the European Union or candidate members)\n\n\nimprove capacity by the same amount. To keep our scenarios realistic, we assume that\n\n\ncountries improve their trade facilitation capacity half-way to the EU15 level– the countries\n\n\n4 The data on port efficiency, customs regimes, regulatory policy and information technology\ninfrastructures for Cyprus, Malta and Croatia are not available. Given the relatively small economic\nsize of Cyprus and Malta, we focus on the study of the other eight new member countries of EU. Data\nfor Croatia are not currently available.\n\n\n5", "output": {"entities": {"named_data": [], "descriptive_data": ["data on port efficiency"], "vague_data": ["Data\nfor Croatia"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003046", "page": 4, "chunk": 1, "title": "wps3832", "pdf_url": "https://local/prwp/wps3832.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on port efficiency", "label": "DESCRIPTIVE_DATA", "score": 0.5208157300949097, "start": 614, "end": 637, "probe_score": 0.4694, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Data\nfor Croatia", "label": "VAGUE_DATA", "score": 0.6310961246490479, "start": 897, "end": 913, "probe_score": 0.0299, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "16\n\n\naddressed the Donors Roundtable and committed to increase Government resources to education to\nover 25% of the budget and noted that the government viewed education as the main source of future\ngrowth in Djibouti.\n\n\n**5. Value added of Bank support in this project**\n\nIDA has been supporting the national consensus building process through the National Education\nForum. The proposed project will help demonstrate that a consensus building approach that involves\n\nall elements of civil society is effective and produces results. In addition the use of an APL\ndemonstrates the long-term commitment by IDA to assist the Government in its strategic goal of\nreaching full enrollment in basic education. It is also hoped that the use of the IDA credit will further\ndecrease the construction unit cost (as IDA is supporting the use of local construction materials which\nshould be cheaper), help develop more cost-effective classroom designs, and provide the environment\nwith a more efficient procurement process.\n\n\n**E. SUMMARY PROJECT ANALYSIS** (Detailed assessments are in the project file, see Annex 8)\n\n\n**1. Economic (see Annex 4)**\n\n\nOther (specify) NPV=US$ million; ERR = ** % (see Annex 4)\n\n\n_** ERR = Over 11% based on system efficiency gains alone without allowing for development_\n_benefits, public goods nature of education and poverty reduction benefits._\n\n\nDjibouti's main resource base is its population and in order to achieve sustained development, the\ncountry needs to improve the quality of its human resource base. Quality starts with improved basic\neducation and school enrollments. In addition, the issue of equity arises. According to the household\nexpenditure survey data, in urban areas, the net enrollment rate (NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey", "output": {"entities": {"named_data": [], "descriptive_data": ["household\nexpenditure survey data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000041", "page": 19, "chunk": 0, "title": "Jordan - Community Infrastructure Project", "pdf_url": "http://documents1.worldbank.org/curated/en/294581468773394111/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "household\nexpenditure survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8924797177314758, "start": 1661, "end": 1694, "probe_score": 0.9403, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_K_ **_ENYA_**\n\n\nSMALDIOIDER **TEA** **DEVELOMENT** **PROJECT**\n\n\nTABIE OF **CONTENTS**\n\n```\n                                        Page No.\n```\n\nSUMMARY **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** . . **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** i-ii\n### I. INTRODUCTION . . . . . . . . . . . . . . . . . 1 . .. . .\n\nII. **BACKGROUND** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** **.** 1\n\n\nIII. THE **PROJECT** **.** **.** **.** **", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010371", "page": 2, "chunk": 0, "title": "Kenya - Smallholder Tea Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/261831468088477754/pdf/Kenya-Smallholder-Tea-Development-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Annex 1: Results Framework and Monitoring**\n\n**Republic of Chad: Emergency Food and Livestock Crisis Response Project (P151215)**\n\n\n**Project Development Objective**\n\n\nThe project development objective is to improve the availability of and access to food and livestock productive capacity for targeted beneficiaries affected by the conflict in the\nCentral African Republic on the Recipient’s territory.\n\n\n**<mark>These results are at</mark>** Project Level\n\n\n**Project Development Objective Indicators**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Col2|Col3|Col4|Cumulative Target Values|Col6|Col7|Col8|Col9|Data source/|Responsibility for|\n|---|---|---|---|---|---|---|---|---|---|---|\n|**Indicator name**|**Core**|**Unit of**<br>**measure**|**Baseline**|**YR1**|**YR2**|**YR3**|<br>**End target**|**Frequency**|**methodology**|**data collection**|\n|Number of<br>agricultural input<br>packages distributed<br>to beneficiaries in the<br>target areas||Tons|0.00|5,000|<br>10,000<br>|15,000|<br>15,000|Quarterly|M&E and surveys|FAO, NGOs, MAE,<br>EAPSP|\n|Number of direct<br>beneficiaries of<br>vouchers or direct<br>food transfers||Number|0.", "output": {"entities": {"named_data": [], "descriptive_data": ["M&E and surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000007", "page": 31, "chunk": 0, "title": "Chad - Emergency Food and Livestock Crisis Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/179061468215115488/pdf/PAD11010PAD0P1010Box385329B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "M&E and surveys", "label": "DESCRIPTIVE_DATA", "score": 0.7728064060211182, "start": 1006, "end": 1021, "probe_score": 0.2647, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " through which resources will be pooled<br>• Coordinate donor and Government inputs into project documents and<br>monitoring reports<br>• Provide fiduciary, technical, and management oversight for health service<br>delivery financed by IDA and linked MDTF|\n|High Level<br>Steering<br>Committee|Donors, MoH, MoFP, WB,<br>SMoH, UNICEF|• Provide high level direction for the project<br>• Meet every six months<br>• Review project data, identify needed actions, and follow-up on actions during<br>meetings|\n|Operational<br>steering<br>committee|MoH, PMU, World Bank,<br>Donors, UNICEF|• Provide routine oversight and operational direction in line with overall<br>direction from the HSC<br>• Meet on a quarterly basis<br>• Identify and discuss needed actions<br>• Review project data, identify needed actions, and follow-up on actions during<br>meetings|\n|UNICEF|UNICEF contracted by the<br>PMU|• Sub-contract NGOs<br>• Supervise and support NGOs<br>• Sub-contract procurement and logistics agency<br>• Supervise and support logistics agency<br>• Develop capacity of CHDs|\n|Contracted<br>Service<br>Providers|NGOs sub-contracted by<br>UNICEF|• Deliver health services<br>• Engage with communities to support health service delivery|\n\n\n\nPage 58 of 68", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["project data", "project data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000006", "page": 61, "chunk": 1, "title": "South Sudan - Health Sector Transformation Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099121123152529349/pdf/BOSIB12886229a02a1bcdc12ee681b5fe59.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "project data", "label": "VAGUE_DATA", "score": 0.6361153721809387, "start": 419, "end": 431, "probe_score": 0.0004, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "project data", "label": "VAGUE_DATA", "score": 0.5519635081291199, "start": 766, "end": 778, "probe_score": 0.0002, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "the average size in our undistorted model economy to attain the average size\n\nof the benchmark economy, the US, when constrained to the same universe of\n\nfirms.\n\n###### **5.3 Cross-Country Distribution of Average Firm Size** **under Idiosyncratic Distortions Only**\n\n\nAs motivation for the importance of entry barriers, we begin characterizing\n\nthe model’s prediction for the cross-country distribution of average firm size\n\nunder the assumption that idiosyncratic distortions are the sole distortion in\n\nthe economy. As established in proposition 2, idiosyncratic distortions reduce\n\nthe average firm size in equilibrium, thus constituting a plausible driving force\n\nfor the cross-country distribution of average size in the data. However, our\n\ngoal here is to show that idiosyncratic distortions fail to account for such\n\ndistribution, thus reenacting the relevance of entry barriers.\n\n\nFormally, the experiment consists of feeding each country’s estimate of the\n\nproductivity elasticity of distortions ( _γi_ ) into the quantitative model previously\n\npresented, solving for the stationary equilibrium, and comparing the resulting\n\naverage size with the data. The results from this exercise are reported in Figure\n\n3. The left plot in the figure illustrates the average firm size from the model’s\n\ndistorted stationary equilibrium relative to the undistorted one, against the\n\naverage firm size ratio each country with respect to the US. Deviations from the\n\n45-degree line represent shortcomings in the idiosyncratic distortion economy\n\nto account for the data.\n\n\nFigure 3 illustrates the (in)ability of the economy with idiosyncratic dis\ntortions to replicate the average firm size distribution in the data. With few\n\nexceptions, we find that the predicted decline in firm size due to misallocation\n\nis notably larger in the model than in the data. For the majority of countries,\n\nthen, reconciling the equilibrium’s average firm size with the empirical one\n\nrequires a countervailing force on the firm size distribution. As an example,\n\nconsider the case of Chile. In", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000362", "page": 35, "chunk": 0, "title": "entry barriers idiosyncratic distortions and the firm size distribution", "pdf_url": "https://local/prwp/entry-barriers-idiosyncratic-distortions-and-the-firm-size-distribution.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "subprojects undertaken, the amount of solid waste collected or the number of household\nwastewater connections provided, the number of community activities supported, and so\nforth. This will be tracked by CDR with the help of the feedback from the community\nmonitoring subcommittees and a monitoring specialist hired under the Project who will\nsupport the PMU and the unions on project monitoring aspects. Half yearly progress\nreports prepared by CDR, and submitted to the Bank will report on key activities, outputs\nand results.\n\n47. The CDR and the Bank team will undertake ex-post evaluations of the Project. This will\ninvolve surveys of beneficiary households and other key stakeholders at key points during the\nlife of the Project. The evaluation design will employ appropriate evaluation techniques to\nestimate Project-specific benefits and impacts. In addition, the Project will also benefit from the\nknowledge being generated by other projects targeting refugee-hosting municipalities to gain a\nbetter understanding of the efficacy of various intervention modalities. Several other donors,\nincluding UNDP and the EU, are currently planning or implementing initiatives at the municipal\nlevel using other institutional arrangements, targeting methodologies or priority investments. The\nProject will collaborate closely with these and other projects as they may evolve in order to\ncreate cumulative and comparative indicators suitable to inform the global efforts currently\nunderway to assist host communities cope with the massive population inflows.\n\n\n**A.** **Sustainability**\n\n\n48. _Component 1._ Most activities proposed under the Project are within municipal\ncompetence and routinely delivered by municipalities and unions of municipalities. The\ninterventions under this component will be small in scale and of an emergency nature, and they\nare expected to be continued by the municipalities after Project closure. To facilitate\nsustainability, the component will scale up service delivery in areas for which there is basic\ncapacity at the local level. However, with limited annual budget transfers from the Government\nto municipalities, they may face challenges to sustain the level of services provided beyond the\nProject’s duration. To facilitate sustainability,", "output": {"entities": {"named_data": [], "descriptive_data": ["surveys of beneficiary households"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000003", "page": 24, "chunk": 0, "title": "Lebanon - Municipal Services Emergency Project", "pdf_url": "http://documents.worldbank.org/curated/en/119441469672145615/pdf/PAD10180PAD0P14972400PUBLIC00Box391431B.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "surveys of beneficiary households", "label": "DESCRIPTIVE_DATA", "score": 0.9055202007293701, "start": 629, "end": 662, "probe_score": 0.0532, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "’apprentissage <br>sont accessibles à<br>tous.|les éducateurs comprennent les difficultés d’apprentissage et les difficultés sociales<br>desélèves handicapés et qu’ils soient soutenus pour répondre à leurs besoins divers<br>grâce à des programmes d’études et des supports d’enseignement et d’apprentissage<br>flexibles et des procédures d’examen adaptées|\n|Les environnements<br>d’apprentissage <br>sont accessibles à<br>tous.|les élèves handicapés aient l’occasion de nouer des liens protecteurs avec<br>d’autres enfants et jeunes<br>|\n|Les environnements<br>d’apprentissage <br>sont accessibles à<br>tous.|les lieux d’apprentissage tirent parti des technologies numériques pour atteindre les élèves<br>qui étudient avec des programmes éducatifs mixtes (en présentiel et à distance), pour<br>promouvoir des expériences éducatives individualisées et répondre aux besoins des élèves|\n|Les environnements<br>d’apprentissage <br>sont accessibles à<br>tous.|les environnements éducatifs utilisent des pratiques et des plateformes<br>pédagogiques novatrices pour améliorer la qualité et l’accessibilité de l’enseignement<br>pour tous les élèves, notamment", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001028", "page": 25, "chunk": 1, "title": "Éducation des réfugiés 2030 : Une Stratégie pour l’Inclusion des Réfugiés", "pdf_url": "https://reliefweb.int/attachments/9c93d8ad-38fe-3734-8134-a91f2f9f7d97/5dfcd3aa4.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nRoads and Employment Project (P160223)\n\n\n54. **The project implementation entity is CDR that will coordinate with relevant government**\n**agencies.** This is a national project executed at the central level, and all technical, fiduciary, safeguards,\nand monitoring aspects will be executed directly by CDR, therefore avoiding the complication of multiple\nagencies’ implementation. CDR has a long and well established cooperation with the World Bank and\nother donors, and its performance at project implementation has been generally satisfactory. CDR will\nensure coordination with the relevant government agencies, particularly MPWT, regarding roads\npriorities, technical aspects, and project’s requirements. The selection of priority roads for the program\nwill be undertaken in consultation with the MPWT based on the results of the visual survey and the agreed\ncriteria. MPWT will also identify and submit its needs for emergency equipment and the desired technical\nspecifications to CDR that will undertake the procurement of such equipment. Meanwhile, the SNRSC will\nbe the technical lead agency on road safety aspects and the SNRSC will inform CDR about its capacity\nbuilding needs and will draft and review terms of reference for the required services, with Bank support,\nbefore CDR proceeds with the procurement of such services. The road asset management system and its\nsupporting consultancy services will be procured by CDR and will be installed within both CDR and MPWT.\nThe project will include capacity building of MPWT and CDR staff on the utilization of the new road asset\nmanagement system, therefore reinforcing project’s sustainability. CDR will therefore be the project\nimplementing agency, and will coordinate with MPWT and SNRSC on various technical aspects as required.\n\n\n**B. Results Monitoring and Evaluation**\n\n\n55. **Project monitoring and verification will be undertaken by the implementing agency to ensure**\n**the project is being implemented in line with the proposed objectives and is on track to achieve**\n**expected results.**", "output": {"entities": {"named_data": [], "descriptive_data": ["visual survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 32, "chunk": 0, "title": "Lebanon - Roads and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/210611486651815142/pdf/Lebanon-Roads-Employment-PAD-P160223-01262017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "visual survey", "label": "DESCRIPTIVE_DATA", "score": 0.9027206897735596, "start": 852, "end": 865, "probe_score": 0.271, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", of which the most recent one is the 2019/20 UNHS. In addition,\nthe Bureau initiated a multi-topic, four-year annual Uganda National Panel Survey (UNPS) program in 2009.\nThe 2009/10 UNPS was funded with support from the Kingdom of the Netherlands while the subsequent\nsurveys (2010/11, 2011/12 and 2013/14) were funded largely by the World Bank. The GoU contributed\ntowards the implementation of the UNPS rounds and provided resources that facilitated the UNPS program\nimplementation.\n\n\n3. The first phase of the UNPS ended in 2015. According to the plan, the UNPS was carried out annually\nover a 12-month period on a nationally representative sample with the aim to produce annual estimates of\noutcomes and outputs in the key policy areas and to provide a platform for the experimentation and\nassessment of national policies and programs. One of the primary uses of the UNPS was to inform policy in\nadvance of the Budget and to provide an analytical framework to inform National Budget preparations and\ngovernment annual reviews. The first phase of panel surveys ensured regular availability of data.\n\n\n4. The success achieved during the first phase of UNPS implementation asked for a second phase of\nimplementation with the goal of consolidating the capacity.\n\n\n5. The first motivation for the second phase of the UNPS 2016 – 2021 was to consolidate and enhance\nthe technical capacity already developed, the efficiency in data collection and processing to continue to\nproduce on an annual basis the key outcome indicators (poverty, service delivery, governance, employment\namong other indicators) to monitor the NDP. The second motivation was to continue supporting the program\nof annual national panel household surveys over the period of 2016-2020, and maintaining the links to at least\na sub-sample of households that have been surveyed in the period of 2009-2015. In such a way the second\nphase intended to facilitate analysis of long-term, slow-moving processes such as agricultural transformation", "output": {"entities": {"named_data": ["2019/20 UNHS", "Uganda National Panel Survey"], "descriptive_data": ["panel surveys", "annual national panel household surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005339", "page": 6, "chunk": 1, "title": "Implementation Completion and Results Report (ICR) Document - LSMS-ISA Uganda National Panel Survey - P163029", "pdf_url": "https://documents.worldbank.org/curated/en/099112923192057641/pdf/P1630290676b9d0608ac0009120a4899ad.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2019/20 UNHS", "label": "NAMED_DATA", "score": 0.6794834136962891, "start": 38, "end": 50, "probe_score": 0.978, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Uganda National Panel Survey", "label": "NAMED_DATA", "score": 0.8382548093795776, "start": 118, "end": 146, "probe_score": 0.7659, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "panel surveys", "label": "DESCRIPTIVE_DATA", "score": 0.7610795497894287, "start": 1051, "end": 1064, "probe_score": 0.7044, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "annual national panel household surveys", "label": "DESCRIPTIVE_DATA", "score": 0.7942556142807007, "start": 1684, "end": 1723, "probe_score": 0.1707, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nand accommodation type. All interviews were conducted face to face. As a probabilistic selection of\nrespondents could not be ensured, the primary goal was to collect a diverse sample that would reflect the\npopulation’s composition as closely as possible.\n\n\nFor the regional analysis, weights were applied based on the most up-to-date estimates of the number of\nrefugees staying in each country. This allowed calculated indicators to more accurately represent the broader\nrefugee population across the region.\n\n\nAppropriate measures were implemented to ensure the protection of personal data and to guarantee\nconfidentiality in all data collection and processing activities. Consent was requested and recorded for all\nselected participants, providing clear information on the purpose, and expected use of the data.\n\n\nWith the exception of Republic of Moldova, the poverty line for each country was defined as 50% of the median\n<u>[equivalized disposable income (after social transfers) as reported by](https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Glossary:Equivalised_disposable_income)</u> <u>[Eurostat for 2023. This figure was indexed](https://ec.europa.eu/eurostat)</u>\ntowards 2024 using national annual wage inflation data for the third quarter of 2024. As the Republic of\nMoldova does not currently run the SILC survey, the absolute poverty line as reported by the country’s National\nBureau of Statistics was used instead. Host poverty rates were based on the same poverty threshold. With the\nexcept of Republic of Moldova, these were equal to the at-risk-of-poverty (AROP) rate reported by Eurostat. On\n\n\n**14**", "output": {"entities": {"named_data": ["SILC survey"], "descriptive_data": ["national annual wage inflation data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 13, "chunk": 1, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "national annual wage inflation data", "label": "DESCRIPTIVE_DATA", "score": 0.8794733881950378, "start": 1215, "end": 1250, "probe_score": 0.9279, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "SILC survey", "label": "NAMED_DATA", "score": 0.793152391910553, "start": 1336, "end": 1347, "probe_score": 0.9283, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a v\nManufacturIng 5 7 3.7 4 7 5 0 / s \\\\t oo  Services 475 272 190 201\n\nPrfvate consumpffon 90 7 81 9 938 95 1 20\nGeneral govemment consumption 7 0 9 6 146 17.2 =c ~GDFDl\nImpons of goods and servrcea 39 7 23 6 33 4 373 -3GW_G_____\n\n\n_(average_ _annual growth)_ 1981-9 1991401 2000 2001 Growth ot exports and Imports (%)\n\nAgrutumre -0 6 -2 6 2 2 3 8 oo\nIndustry 0.1 -41 51 5 6 s0\nManUnacturIng 6.9 . .\nServices -5 7 -5.4 4 0 51 \nPrivate oonsumpffon -2 0 -19 10 4 100 -50\nGeneral govemment consumption -5.1 -0 2 41.3 27 9 -100\nGross domestic Investment -06 3 0 50 - EOpois -tr-ports\nImports of goods and services -2 2 -151 85 0 61 3\n\n\nNote 2001 data are pretirrinary eastliates\n'The diamonds show four Key Indicators in the country (in bold) conipared with itS income-group average It data are missing, the diantond wiUt be rrconrrlte\n\n\n-56", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["2001 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013370", "page": 60, "chunk": 2, "title": "Uganda - Second Economic Recovery Credit Project", "pdf_url": "https://documents.worldbank.org/curated/en/460751468117883369/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2001 data", "label": "VAGUE_DATA", "score": 0.7082152366638184, "start": 639, "end": 648, "probe_score": 0.0183, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad COVID-19 Strategic Preparedness and Response Project (P173894)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Number of communication campaigns<br>about COVID-19 broadcast to<br>communities|Number of awareness<br>communications<br>campaigns conducted|weekly|COVID-19<br>report|routine data|MOPH|\n|---|---|---|---|---|---|\n|<br>National COVID-19 risk communication<br>and community engagement strategy<br>established|<br>Establishment of a risk<br>communication and<br>engagement strategy in<br>Chad <br>|once<br>|<br>COVID-19<br>report<br>|routine data<br>|MOPH<br>|\n|Number of technical crisis coordination<br>meetings issuing an official report on<br>epidemic surveillance and response|<br>Number of meetings<br>conducted/official reports<br>issued by the emergency<br>crisis committee|weekly<br>|COVID-19<br>report<br> <br>|routine data<br>|MOPH<br>|\n|Number of treatment, isolation &<br>quarantine centers preparing daily report <br>|<br>Number of centers<br>preparing daily reports|weekly<br>|COVID-19<br>report<br> <br>|routine data<br>|MOPH<br>|\n|Number of centers assessed monthly<br>(using check list) treatment, isolation &<br>quarantine|Number of centers<br>assessed monthly|monthly<br>|<br>COVID-19<br>report<br> <", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["routine data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000124", "page": 38, "chunk": 0, "title": "Chad - COVID-19 Response Project", "pdf_url": "http://documents1.worldbank.org/curated/en/717781588366403375/pdf/Chad-COVID-19-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "routine data", "label": "VAGUE_DATA", "score": 0.5518015623092651, "start": 277, "end": 289, "probe_score": 0.4384, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 6\nPage 3 of 6\n\n\nLarge consultant contracts for amounts above US$200,000 will be advertised through the UN's\n_Development Business,_ for which expressions of interest will be requested. Following the short-listing\nprocess, Quality and Cost-Based Selection (QCBS) will be the preferred method of selection.\n\n\nImpact assessments and small-size sampling surveys will be carried out using Selection Based on\nConsultant's Qualifications (CQ) for contracts estimated to cost less than US$25,000, and Single-Source\n\nSelection (SS) for services not exceeding US$15,000.\n\n\n**Table A: Project Costs by Procurement Arrangements**\n\n(US$ million equivalent)\n\n\n**Expenditure Category** **Procurement** **Methodl**\n**ICB** **NCB** **Other** <sup>**2**</sup> **N.B.F.** **Total Cost**\n\n**1. Works** **0.00** 5.30 0.60 0.00 5.90\n(0.00) (4.90) (0.50) (0.00) (5.40)\n**2. Goods** 0.80 0.41 0.05 0.00 1.26\n(0.76) (0.30) (0.04) (0.00) **(1.10)**\n**3. Services** **0.00** **0.00** 3.41 0.05 3.46\n!:_________________ _ X **:(0.00)** **(0.00)** (3.30) (0.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000038", "page": 45, "chunk": 0, "title": "Africa - Multi - Country HIV/AIDS Program for the Africa Region (Ethiopia and Kenya)", "pdf_url": "http://documents1.worldbank.org/curated/en/287591468768313907/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nBuilding Resilient and Responsive Health Systems (P179698)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Data source|Project report|\n|---|---|\n|Methodology for Data<br>Collection <br>|Project monitoring|\n|Responsibility for Data<br>Collection <br>|MoH <br>|\n|**Health insurance benefits package developed (Yes/No)  ** <br> <br>|**Health insurance benefits package developed (Yes/No)  ** <br> <br>|\n|Description <br>|A health insurance benefits package is developed, rationalized, and disseminated. <br>|\n|Frequency <br>|Every six months <br>|\n|<br>Data source <br>|<br>Routine ERP data|\n|Methodology for Data<br>Collection <br>|ERP|\n|Responsibility for Data<br>Collection <br>|KEMSA, MoH <br>|\n|**Improving utilization of quality health services at primary care level** <br>|**Improving utilization of quality health services at primary care level** <br>|\n|**Proportion of functional community health units (CHUs) (Percentage)  **|**Proportion of functional community health units (CHUs) (Percentage)  **|\n|Description <br>|<br>Numerator: Number of CHUs scoring at least 80% on the CHU assessment. Denominator: Total number of existing CHUs.<br>Comment: At appraisal, the total number of functional CHUs was 7,780 and the total number of existing CHUs<br>(functional, non-functional, and semi-functional) was 10,382. <br>|\n|Frequency <br>|<br>Every six", "output": {"entities": {"named_data": [], "descriptive_data": ["Routine ERP data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000000", "page": 38, "chunk": 0, "title": "Kenya - Building Resilient and Responsive Health Systems Project", "pdf_url": "http://documents1.worldbank.org/curated/en/099022324094562763/pdf/BOSIB1554c314c0a2187c019d7e85bc2a91.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Routine ERP data", "label": "DESCRIPTIVE_DATA", "score": 0.7711866497993469, "start": 573, "end": 589, "probe_score": 0.2215, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2023 Post-Earthquake Population Movement Dynamics Analysis - Türkiye\n\n\nthe country, including in affected areas. <sup>14</sup> [^14: IFRC Turkiye Delegation: Secondary Data Review, Turkiye February 2023 Earthquake Bi-Weekly Highlights Vol. 20 - 01 June 2023:\n[https://reliefweb.int/report/turkiye/ifrc-turkiye-delegation-secondary-data-review-turkiye-february-2023-earthquake-bi-weekly-highlights-](https://reliefweb.int/report/turkiye/ifrc-turkiye-delegation-secondary-data-review-turkiye-february-2023-earthquake-bi-weekly-highlights-vol-20-01-june-2023)\n[vol-20-01-june-2023](https://reliefweb.int/report/turkiye/ifrc-turkiye-delegation-secondary-data-review-turkiye-february-2023-earthquake-bi-weekly-highlights-vol-20-01-june-2023)], making it harder for people, including\n\n\nrefugees to afford accommodation <sup>15</sup> [^15: Upon their return to Hatay, 60 per cent of displaced refugee-respondents were staying in spontaneous tented sites, 17 per cent in\nformal tented sites, 17 per cent in their former homes, and 6 per cent in newly rented accommodation.] . This is supported by secondary data suggesting\n\n\nhigh living costs in other provinces.\n\n\nAlmost all respondents (98.2 per cent) stated that since their return from other\n\n\nprovinces in Türkiye, they lived in their province of registration. Only 1.7 per cent said\n\n\nthat they lived in another province in the south-east.\n\n\nConcerning the **reasons for returning to earthquake provinces**, refugee\n\n\nrespondents frequently reported the lack of available accommodation/shelter in the\n\n\nprovince of temporary stay (22 per cent) – particularly attributed to increasing rent\n\n\nprices, both in other parts of the country and in Syria. <sup>16</sup> [^16: IFRC Secondary Data Review: https://reliefweb.int/report/turkiye/ifrc-turkiye-delegation-secondary-data-review-turkiye-february-2023-\n[earthquake-bi-weekly-highlights-vol-20-01-june-2023](https://reliefweb.int/report/turkiye/ifrc-turkiye-delegation-secondary-data-review-turkiye-february-2023-earthquake-bi-weekly-highlights-vol-20-01-june-2023)] Those returning to the south\n\neast after temporarily staying in other parts of Türkiye also referred to the uncertainty\n\n\nas to the possibility of extension of the travel permit’s validity (18 per cent) and other\n\n\nbureaucratic requirements (14 per cent) they were unable to", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["secondary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000759", "page": 18, "chunk": 0, "title": "2023 Post-Earthquake Population Dynamics Analysis - Türkiye", "pdf_url": "https://reliefweb.int/attachments/6ee003d6-58b7-4899-9a77-e1772778be15/UNHCR%20-%202023%20Population%20Dynamics%20post%20EQ.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "secondary data", "label": "VAGUE_DATA", "score": 0.7321003079414368, "start": 1089, "end": 1103, "probe_score": 0.9818, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " new\neducation law (approved in August 2000) sets in place the conditions for broadening participation in\nDjibouti's education system. It provides for setting up school management committees with parent\n\nand community involvement. The law also provides for the creation of conditions to increase private\nsector participation in education.\n\n\n_6.3 How does the project involve consultations or collaboration with NGOs or other civil society_\n_organizations?_\n\n\nThe National Educational Forum consulted all stakeholders including NGOs and civil society during\nthe initial preparation. In addition, the project foresees the increased involvement of parent\nassociations or community-based associations in the management of project activities on the ground\n(i.e., operations & maintenance).\n\n\n_6.4 What institutional arrangements have been provided to ensure the project achieves its social_\n_development outcomes?_\n\n\nThe DGEN will be responsible for monitoring the gender gap in enrollment issues, and the gap\nbetween the poorest and the richest quintiles, and related education services available to them. The\ndata collection on enrollment will be strengthened by the capacity building support provided to the\nMinistry of Education's planning unit - thus over time these issues can be effectively monitored.\nTriggers are included in the APL phasing to ensure that various social development goals are met e.g.\ndecreasing the enrollment gap between the rich and the poor, decreasing the gender gap and increasing\ncommunity participation in school management.\n\n\n_6.5 How will the project monitor performance in terms of social development outcomes?_\n\n\nThe MOE planning unit will monitor enrollment paying attention to gender gaps, socioeconomic gaps\n\nand performance of students by socioeconomic class through use of surveys of students.", "output": {"entities": {"named_data": [], "descriptive_data": ["surveys of students"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018857", "page": 24, "chunk": 1, "title": "Ethiopia - Ambibara Irrigation Project", "pdf_url": "https://documents.worldbank.org/curated/en/831001468250236544/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "surveys of students", "label": "DESCRIPTIVE_DATA", "score": 0.8922238349914551, "start": 1811, "end": 1830, "probe_score": 0.3477, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "/ny-gnp-pcap-cd/)</u>\nto <u>[Purchasing Power Parity (PPP), and](https://www.worldbank.org/en/programs/icp/brief/VC_Uses)</u> <u>[Human](https://hdr.undp.org/data-center/human-development-index#/indicies/HDI)</u>\n<u>[Development Index (HDI).](https://hdr.undp.org/data-center/human-development-index#/indicies/HDI)</u> <sup>53</sup>\n\n\nThe Gini coefficient is a statistical measure of how\nincome is divided among individuals in a society or\nspecific group. It is typically expressed as a number\nbetween 0 and 1, with 0 representing perfect\nequality (where everyone has the same income)\nand 1 representing complete inequality (where\none individual or household has all the income).\nFor this report, the Gini was conceptualized as\na measure of the disparities between countries\nhosting refugees and providing durable solutions.\nA value of 0 indicates a perfectly equal distribution\nof refugees worldwide, while a value of 1 signifies\ncomplete inequality, with only one country hosting all\nrefugees and providing durable solutions. The closer\n\n\n62 GLOBAL COMPACT ON REFUGEES INDICATOR REPORT\n\n\n\nthe Gini value is to 1, the greater the concentration\nof refugees in a small number of countries. A Gini\ncoefficient of 0.4 or higher indicates significant\ninequality, whereas lower values indicate a more\nequal distribution.\n\n\nThe estimate for the distribution of refugees in terms\nof the population size of the hosting communities\nis 0.81 and remains relatively stable over time. Data\nshows reductions in inequality when looking at\ncountries’ income (0.77) and human development\n(0.72", "output": {"entities": {"named_data": ["GLOBAL COMPACT ON REFUGEES INDICATOR REPORT"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000435", "page": 61, "chunk": 1, "title": "2023 Global Compact on Refugees Indicator Report", "pdf_url": "https://reliefweb.int/attachments/3d407ba2-2493-4519-a8d6-c8b8911d1346/2023-gcr-indicator-report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "GLOBAL COMPACT ON REFUGEES INDICATOR REPORT", "label": "NAMED_DATA", "score": 0.5588445663452148, "start": 1044, "end": 1087, "probe_score": 0.9998, "gold": "NON_MENTION", "gold_tier": "human-final"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Figure 2**\n**Yield to Maturity of U.S. Dollar Corporate Bonds Issued by Emerging Markets**\nThis figure shows the yield to maturity of international U.S. dollar-denominated bonds issued by firms in emerging\nmarkets during 2000-2016. The lines show the average yield to maturity of bonds issued with face values below\n$300 million (0:300), between $300 and $500 million [300:500), and equal to or above $500 million [500:1,000),\nrespectively.\n\n\n9\n\n\n8\n\n\n7\n\n\n6\n\n\n5\n\n\n4\n\n\n3", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002071", "page": 44, "chunk": 0, "title": "search for yield in large international corporate bonds investor behavior and firm responses", "pdf_url": "https://local/prwp/search-for-yield-in-large-international-corporate-bonds-investor-behavior-and-firm-responses.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " those of their\nnative counterparts. Tani (2020) found\nthat in Australia, licensing raised hourly\n\n\n\nvalue to the economy. This estimate may\nunderestimate the potential benefits,\nas the boost in productivity would most\nlikely rise not just employee wages, but\nemployer profits as well. Conversely, the\noverall impact on wages might be lower, if\nincreased worker competition reduced the\naverage individual premium.\n\n\nwages and reduced over-education for\nmigrants working in licensed jobs, while\nproducing worse labour market outcomes\nfor those who did not gain licensure.\nAccording to Peterson et al. (2014), over the\n1973–2010 period, U.S. states with more\nstringent occupational licensing for migrant\nphysicians received fewer new migrant\nphysicians and struggled more with staffing\nshortages in healthcare. Aleksynska and\nTritah (2013) quoted data that migrants\nin France were denied legal access to\napproximately 30% of jobs in the country.\n\n\n\nUkrainian refugees Polish citizens\n\n\nSource: Deloitte own elaboration based on mid-2024 SEIS UNHCR survey\n(Ukrainian refugees’ educational attainment), 2023 Eurostat Labour Force\nSurvey Eurostat (Polish citizens educational attainment), and mid-2024 ZUS\nadministrative data (occupational groups).\n\n\n\nSource: Deloitte own elaboration based on mid-2024 SEIS UNHCR survey\n(Ukrainian refugees’ educational attainment and median net wages),\n2023 Eurostat Labour Force Survey Eurostat (Polish citizens educational\nattainment), and mid-2024 ZUS administrative data (occupational groups).\n\n\n\n**Widespread occupational licensing**\n**is a serious obstacle to an efficient**\n**use of Ukrainian refugees’ human**\n**capital.** Poland has the third highest\nnumber of regulated professions among\nthe 28 European Union member states,\naccording to European Commission’s\nRegulated Professions Database. This can\nbe a problem, as occupational licensing is\ncited in the literature among the reasons\nfor occupational downgrading of migrants.\nCassidy and Dacass (2021) found that in the\nUnited States, immigrants were significantly\nless likely to", "output": {"entities": {"named_data": ["SEIS UNHCR survey", "2023 Eurostat Labour Force\nSurvey Eurostat", "ZUS\nadministrative data", "SEIS UNHCR survey", "Regulated Professions Database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 14, "chunk": 1, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SEIS UNHCR survey", "label": "NAMED_DATA", "score": 0.8007447123527527, "start": 1035, "end": 1052, "probe_score": 0.9974, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2023 Eurostat Labour Force\nSurvey Eurostat", "label": "NAMED_DATA", "score": 0.621566891670227, "start": 1099, "end": 1141, "probe_score": 0.999, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "ZUS\nadministrative data", "label": "NAMED_DATA", "score": 0.726600706577301, "start": 1197, "end": 1220, "probe_score": 0.9499, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "SEIS UNHCR survey", "label": "NAMED_DATA", "score": 0.5943534970283508, "start": 1298, "end": 1315, "probe_score": 0.9983, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Regulated Professions Database", "label": "NAMED_DATA", "score": 0.846522867679596, "start": 1800, "end": 1830, "probe_score": 0.8069, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " forced family separation,\ndestruction of property, forced evictions, lack of access to justice,\ndiscriminatory practices against persons with minority clan\naffiliations, and concerns regarding the protection of civilians.\n\n**<u>Methodology</u>**\n\nThis report was prepared through a desk review of various sources,\nmost notably, the protection monitoring systems in Somalia,\nincluding: the Somalia Protection Monitoring System (SPMS), the\nProtection and Return Monitoring Network (PRMN) and the\nEviction tracker.\n\n**<u>Limitations</u>**\n\nData available in Somalia is limited to areas that are accessible by\nhumanitarian actors. Those that are not accessible are under the\ncontrol of Al-Shabaab <sup>3</sup> [^3: “Al-Shabaab has engaged in acts that directly or indirectly threaten\nthe peace, security, or stability of Somalia, including but not limited to] . A limited data set is collected from\nindividuals that flee Al-Shabaab controlled territories by REACH,\ntitled ‘Hard-to-Reach’ data. The information in this report was\ncollected using existing reports and data collection methodologies.\n\n\nacts that threaten the Djibouti Agreement of August 18, 2008, or the political process; and\nacts that threaten the Transitional Federal Institutions (TFIs), the African Union Mission\nin Somalia (AMISOM), or other international peacekeeping operations related to Somalia.\nAl-Shabaab has also obstructed the delivery of humanitarian assistance to Somalia, or\naccess to, or distribution of, humanitarian assistance in Somalia.”\n[https://www.un.org/securitycouncil/sanctions/751/materials/summaries/entity/al-](https://www.un.org/securitycouncil/sanctions/751/materials/summaries/entity/al-shabaab)\n[shabaab](https://www.un.org/securitycouncil/sanctions/751/materials/summaries/entity/al-shabaab)", "output": {"entities": {"named_data": ["Somalia Protection Monitoring System", "Eviction tracker"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000833", "page": 2, "chunk": 1, "title": "Somalia: Protection Analysis Update (February 2022)", "pdf_url": "https://reliefweb.int/attachments/7b77ad31-d168-316e-86c9-18c5a6a777b8/SOM_PAU_Somalia-Protection-Analysis_Feb2022.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Somalia Protection Monitoring System", "label": "NAMED_DATA", "score": 0.6805587410926819, "start": 390, "end": 426, "probe_score": 0.0285, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Eviction tracker", "label": "NAMED_DATA", "score": 0.7727727293968201, "start": 495, "end": 511, "probe_score": 0.0654, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nBurundi Integrated Community Development Project (P169315)\n\n\nforced displacement and gender/GBV. The World Bank task team will also meet with the Consultative Committee to\nensure effective coordination as the project moves into the implementation phase.\n\n\n**F. Lessons Learned and Reflected in the Project Design**\n\n\n62. **Allocating development resources based on transparent, objective criteria builds government credibility** . The\ndesign will build on the World Bank’s extensive experience with community-driven development (CDD) and local\ndevelopment projects, which highlights the importance of fair and transparent methods for allocating resources,\nparticularly in countries where state-society relations have been affected by a legacy of mistrust borne of social conflict.\nBy targeting communes based on objective data on poverty, malnutrition and the impact of forced displacement and\nallocating funds on a per capita basis, the government will demonstrate commitment to transparency and equity.\n\n\n63. **Lessons from community-based operations highlight the need to simultaneously support communities and local**\n**governments.** Analyses of the impact of community-driven projects underscore the risk of creating parallel community\nstructures for planning at the expense of building sustainable capacity for local governance. In fragile contexts, Bank\nexperience suggests the need for a hybrid of community and local government institutions with adequate capacity,\nwhich are empowered to deliver effective and sustainable infrastructure and services. Turikumwe will support the\ncapacity of communes to effectively engage with communities, including marginalized groups. It will also build commune\ncapacity for planning, procurement and oversight of socio-economic infrastructure subprojects.\n\n64. **In contexts such as Burundi, community development projects need to take a gradual approach and be wary of**\n**elite capture.** The Burundi Community and Social Development Project (P095211 – PRADECS), which ran from 20072012 also supported the formulation of CDPs and funding of public and private goods through", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["objective data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000110", "page": 29, "chunk": 0, "title": "Burundi - Integrated Community Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/644221583204472551/pdf/Burundi-Integrated-Community-Development-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "objective data", "label": "VAGUE_DATA", "score": 0.7856014370918274, "start": 831, "end": 845, "probe_score": 0.6164, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the crop simulation\nstudies examine only exogenous measures arbitrarily added by the researcher that are not\nnecessarily efficient responses to climate change.\n\n\nThis paper relies on an entirely different approach to measure climate impacts. The study\nuses AgroEcological Zones (AEZs) as the cornerstone of the analysis. FAO established\nAEZs as a method of measuring crop productivity (FAO 1978). The zones were intended\nto capture the length of the growing season taking into account soil moisture. Although\nlonger growing seasons are not always better, the AEZ system does do a good job of\ndividing a heterogeneous landscape into a set of homogeneous zones. Other factors that\ndetermine productivity such as status of soils, drainage, and crop type are reflected in the\nAEZ classification. In this analysis, we rely on the FAO classification of every district in\nAfrica using this AEZ methodology <sup>3</sup> (FAO 2003). More recent work by FAO in this area\nincludes the Land Use Systems of the World <sup>4</sup> and Globcover <sup>5</sup> initiatives.\n\n\n3 FAO and IIASA applied the AEZ methodology for the whole world (Fischer et al. 2002), not only for\nAfrica.\n4 This data is developed in the framework of the LADA project (Land degradation Assessment in Drylands)\nby the Land Tenure and Management Unit of the Food and Agriculture Organization of the United Nations\nand is copyright of FAO/UNEP GEF.\n5 GlobCover is an European Space Agency led initiative in partnership with JRC, EEA, FAO, UNEP,\nGOFC-GOLD and IGBP. The GlobCover project has developed a service capable of delivering global", "output": {"entities": {"named_data": ["Land Use Systems of the World"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003921", "page": 3, "chunk": 1, "title": "wps4717", "pdf_url": "https://local/prwp/wps4717.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Land Use Systems of the World", "label": "NAMED_DATA", "score": 0.5568880438804626, "start": 975, "end": 1004, "probe_score": 0.0017, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and 56 per cent of the refugee population,\nrespectively. Among IDPs, 56 per cent of the\npopulation was covered by sex-disaggregated data,\nwhile only 26 per cent was covered by agedisaggregated data. For asylum-seekers, the coverage\nwas 58 per cent for sex-disaggregated data and 49 per\ncent for age. For the other types of population of\nconcern reported to UNHCR, the figures for sex and\nage disaggregation were as follows: returned IDPs (51\n\n\n\nper cent and 36 per cent, respectively), others of\nconcern (86 per cent and 73 per cent), returned\nrefugees (83 per cent and 79 per cent), and stateless\npeople (69 per cent and 1 per cent).\n\n\nBased on the available data, 49 per cent of refugees\nwere women in 2016 (Table 5). This was a small\nincrease over 2015 but consistent with trends in\nearlier years. As in 2014 and 2015, the proportion of\nchildren under the age of 18 among refugees\nremained at 51 per cent. In addition, there was a\nchange of only one percentage point in the working\nage (18-59) and older (60 plus) populations, which\nwere 45 per cent and 4 per cent of the total\npopulation, respectively. Many countries in subSaharan Africa hosted refugee populations with a\nhigher proportion of children, reflective of the\nyounger population structure in the region.\n\n\nCameroon, the Central African Republic, the\nDemocratic Republic of the Congo, Ethiopia, Niger, and\nSouth Sudan all hosted refugee populations with more\nthan 60 per cent children by end-2016, with clear\nimplications for the provision of protection and services.\n\n\n**LOCATION CHARACTERISTICS**\n\n\nKnowing where displaced people are and how they are\nliving is as important as knowing who they are when it\ncomes to delivering assistance and protection. UNHCR\nrequests geographically disaggregated data on\n\n\n**70** UNHCR’s population of concern includes refugees, IDPs,\nreturnees", "output": {"entities": {"named_data": [], "descriptive_data": ["sex-disaggregated data", "agedisaggregated data", "sex-disaggregated data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000712", "page": 53, "chunk": 1, "title": "Global Trends: Forced Displacement in 2016", "pdf_url": "https://reliefweb.int/attachments/68295936-5f9b-382c-8466-3e660ac587d3/5943e8a34.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "sex-disaggregated data", "label": "DESCRIPTIVE_DATA", "score": 0.7276695370674133, "start": 115, "end": 137, "probe_score": 0.8701, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "agedisaggregated data", "label": "DESCRIPTIVE_DATA", "score": 0.6923699975013733, "start": 177, "end": 198, "probe_score": 0.7592, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "sex-disaggregated data", "label": "DESCRIPTIVE_DATA", "score": 0.6150107979774475, "start": 253, "end": 275, "probe_score": 0.7967, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\n\n\n\n\n\n\n\n|Col1|working on LIPW under sub-<br>component 1.1 on behalf of<br>beneficiary HH, of which are<br>refugees and host<br>communities. Refugees are<br>defined as forcibly displaced<br>HHs originating from a<br>country other than South<br>Sudan and registered as<br>refugees in South Sudan by<br>the UNHCR. Host<br>communities are defined as<br>local population groups<br>living in counties with a high<br>concentration of refugees.|measured<br>at a<br>minimum<br>on a<br>quarterly<br>basis|SNSOP MIS|updated over the<br>course of the project.<br>Payment data will also<br>be periodically updated<br>in the MIS|Col6|\n|---|---|---|---|---|---|\n|Number of beneficiary households<br>receiving Direct Income Support who<br>have a female primary beneficiary<br>(Number)|Total number of beneficiary<br>households under<br>comopnent 1.2 that have a<br>primary beneficiary, as<br>registered in the SNSOP<br>MIS, who is a woman.|This<br>indicator<br>will be<br>measured<br>at least on<br>a quarterly<br>basis<br>|SNSOP MIS<br>|This data will be<br>collected through<br>registration and<br>payments<br>|Implementing Partner<br>|\n|Number of beneficiaries receiving<br", "output": {"entities": {"named_data": ["SNSOP MIS"], "descriptive_data": [], "vague_data": ["Payment data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 62, "chunk": 0, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "SNSOP MIS", "label": "NAMED_DATA", "score": 0.7858204245567322, "start": 587, "end": 596, "probe_score": 0.0293, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Payment data", "label": "VAGUE_DATA", "score": 0.6631499528884888, "start": 643, "end": 655, "probe_score": 0.6771, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " bills action plans to the Office of the Controller of Budget\n(OCOB), with implementation progress being reported through quarterly updates. 32 counties have published\ndetails of their pending bills on their official websites, while 15 counties were yet to disclose this information\nexternally. Reporting formats differ between counties; many use templates from the OCOB, while others utilize\nformats developed by pending bills verification committees or internal audit units. To ensure standardization,\nit was agreed that all counties should report the status, payments, and summary details of pending bills using\nthe OCOB’s prescribed reporting templates.\n\n- **DLI 5:** **_Counties that have integrated their HR records, authorized staff establishment and payroll, and_**\n**_uploaded cleaned payrolls in the HRIS-KE._** 32 counties have developed implementation plans for HR and\nPayroll Audit, and all staff including advisers, and casuals have been assigned unified payroll numbers\n(eliminating manual payment of salaries). 20 counties have uploaded the approved authorized staff\nestablishment in the HRIS-Ke. 26 counties are yet to upload the staff's establishment, citing among other things,\nthat the module in HRIS-KE is inactive and/or that they were yet to complete the review of the establishments\nand obtain approval prior to uploading into the system. 37 counties have an action plan for implementing\nrecommendations from the Salaries and Remuneration Commission (SRC) 2025 Monitoring and Evaluation\n(M&E) reports which enables compliance checks to SRC requirements on salaries and allowances aimed at\nwage bill control. It was also noted that 32% of the counties still use a combination of manual and automated\npayrolls.\n\n\n3\n\n\nOfficial Use Only", "output": {"entities": {"named_data": ["HRIS-KE"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001259", "page": 2, "chunk": 1, "title": "Kenya - Second Devolution Support Program Project : Technical Support Mission - October 13 to 21, 2025", "pdf_url": "https://documents.worldbank.org/curated/en/099030926103072760/pdf/P180935-194ec8c9-1cb3-4262-b85b-f23c6e9dc79c.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "HRIS-KE", "label": "NAMED_DATA", "score": 0.5826954245567322, "start": 810, "end": 817, "probe_score": 0.0001, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">\n\nThere is strong competition among a small number of AFPs in the accumulation market and\namong a larger number of insurance companies in the annuity market. <sup>11</sup> This has resulted in large\nmarketing costs, mostly taking the form of high commissions paid to agents and brokers.\nHowever, a growing consolidation of the two markets, which is much more pronounced among\npension administrators, the threat of regulation and the adoption of informal agreements among\ncompeting institutions in the two main segments of the market have recently resulted in a major\ncontainment of marketing costs.\n\nThe potential role that central agencies can play in collecting contributions, paying benefits and\nmaintaining accounts, all activities that are characterized by large economies of scale, has been\nconsidered but not adopted in Chile, but more intensive use of electronic payment systems is\nexpected in the future. <sup>12</sup> A competitive decentralized asset management structure would\nstimulate innovation and efficiency, which are essential for attaining high investment returns. On\nthe other hand, centralized administration lowers operating costs because of scale economies and\navoidance of high marketing costs, while the centralized offer of life annuities could benefit from\nusing a larger customer base and thus more efficient risk pooling.\n\nThe structure of the pension and life insurance sectors evolved very differently in the past 20\nyears. As shown in Figure 3, the pension sector became very concentrated during the 1990s,\nwith the number of AFPs declining from 20 to 8 between 1990 and 2000 and to only 6 more\n\n\n10 An example is the creation of SCOMP, which plays the role of information clearing housing collecting and\ncommunicating electronic quotations in the market for annuities.\n11 The PW market is handled in a passive way by AFPs.\n12 Hysteresis in the institutional framework has inhibited action in this area,\n\n\n6", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004515", "page": 11, "chunk": 1, "title": "wps5325", "pdf_url": "https://local/prwp/wps5325.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "World Bank Hazar Analysis programme\nor Process Hazards Assessments\nScreening Tools pr gramme to model risk\nof individual sites d processes\n**Water** - Industrial effluent may pollute - All industries pre-t eat effluent before it is\n**pollution** springs, streams and rivers sent to the treatment works\n\n           - Construction of pit-latrines may            - Industries adhere to Standards for\nreach the high water table and Discharge of Efflue nt or Wastewater 1999\ncontaminate the aquifer and Pollution Prev tion Abatement\n\n           - Potential for pollution of Handbook\ngroundwater from improper           - Follow recommen ations outlined in\nindustrial practice National Environm nt Regulations 2000\n\n           - Pollution in Inner Murchison Bay            - Stringent monitori g and enforcement of\nand Lake Victoria waste treatment an effluent standards\n\n                                     - Treated waste disc arged into waste\nstabilization ponds md sewage treatment\nworks\n\n                                     - Latrine constructio monitored by public\nhealth officials\n\n                                     - A specific monitor ng program\nimplemented by the UIA in conjunction\nwith NEMA and th DWD\n\n                                     - Regular water qual ty sampling from\nRiver Namanve at outlet into Lake\nVictoria, Namanve 'retland, and Inner\nMurchison Bay\n\n                                     - Regular testing at p oint of exit for each\nindustry, at influent and effluent points of\nsewage treatment w rks\n\n                                     - Install ground wate monitoring wells\n\n                                     - Water quality samp es collected quarterly\nfrom all boreholes within a 2 km radius of\nIndustrial Park which also forms baseline\ndata\n\n                                     - Restoration ecolog in area of sewage\ntreatment to upgrad the status of papyrus\nand other species\n\n                                     - Water from industri al sites should be\npassed through oil- rater separators to\nremove impurities b fore it reaches\nwetlands\n\n\n16", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["baseline\ndata"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009747", "page": 18, "chunk": 0, "title": "Uganda - Second Private Sector Export Competitiveness Project : environmental assessment", "pdf_url": "https://documents.worldbank.org/curated/en/220531468781777792/pdf/E936.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "baseline\ndata", "label": "VAGUE_DATA", "score": 0.5053020119667053, "start": 1761, "end": 1774, "probe_score": 0.7359, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "ك وت **ددد**\n\nباب الجي يأ لذي الت  د إلا األماكن انمنأ لا زالا وتدعو الااجأ الع مزيد من ا جراءا لمعالجأ األتد **دددد**\n\nومن الا  الدول مدعوة الع تعزيز الوصداذا ةدادل لارحث الا رة **دد** ا ا آمنأ وقا و اأ ةوصد **دد** ول الع ممد **دد**\n\nرمكن العمل ةذا بما تماشع ومبدأ تإلاتا األثباء والممؤولاا ا\n\n\n#### **نظم اللجوء باء-**\n\nعوبا عند التعامل من األعداع ال متزا دة من **دد** واجذت أ يمأ الاجوء الولناأ و بع البادال ص-15\n\nلابا الاجوءا وب نما عمات بع الدول عاع توتتقبال **ددد** ارا المتراكمأ وات **ددد** اع قد اتذا عاع معالجأ الإلن **ددد**\n\nماتممدل **د** ول الع اجراءا الاجوء أو تاوي **دددددد** ا ومنع الوصد **د** دوعف **د** ت عول ألر", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001493", "page": 3, "chunk": 5, "title": "Note on international protection - Note by the High Commissioner (A/AC.96/74/3) [EN/AR/RU/ZH]", "pdf_url": "https://reliefweb.int/attachments/e7efd806-10af-4664-82e9-e3d4ebfcefaa/G2314711.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the social and\neconomic impact of a refugee influx and to ensure that the refugees’ presence is taken into\naccount in the formulation of local, regional and national development plans. And the media\n(which, if not a part of the international refugee regime, is used by and exerts a considerable\ninfluence upon it) need statistics to provide their audience with information about the refugee\nmovements, mass displacements and asylum flows taking place throughout the world. The\nprecise nature of the statistics required by these different actors evidently varies. Journalists\nand advocacy groups, for example, are most likely to be concerned with easily-digested\n‘headline’ figures: the size of a refugee influx; the total number of refugees to be found on the\nterritory of a given state; or the relative number of asylum applications received and recognized\nby different governments in the same region.\n\n\nFor UNHCR and its operational partners, however, the level of statistical detail required is\nnormally much greater. To provide a refugee population with effective protection and\nassistance, it will normally be necessary to know something about the composition of that\ncommunity in terms of gender, age, ethnic origin and household structure. And in situations\nwhere an exiled population wishes to return to its homeland, statistical data on the refugees’\nplace of origin, educational background, skills and occupational status is an obvious\nprerequisite for effective repatriation and reintegration planning.\n\n\nDuring the past 10 to 15 years, the requirement for such statistical data has been strengthened\nby the recognition that refugee populations are not simply an undifferentiated mass of people\nwith identical needs and capacities. Rather, such populations consist of many different (and\noverlapping) social groups: males and females; elderly people, adults, adolescents and\nchildren; the able-bodied and the disabled; female-headed households and unaccompanied\nchildren. The collection of accurate data on these different social groups not only provides an\nimportant basis for effective programming, but also contributes to the all-important task of\nmobilizing financial resources. As UNHCR's registration", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["statistical data", "statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000558", "page": 2, "chunk": 1, "title": "\"Who has counted the Refugees?\" UNHCR and the Politics of Numbers", "pdf_url": "https://reliefweb.int/attachments/524235ad-ad20-3b57-8f5d-fb4ced1d78d8/ED9302CE174AB751C1256DAD0037FB44-hcr-count-jun99.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7048991322517395, "start": 1327, "end": 1343, "probe_score": 0.2287, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "statistical data", "label": "VAGUE_DATA", "score": 0.6213106513023376, "start": 1574, "end": 1590, "probe_score": 0.1018, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "rio de enumeración” <sup>36</sup> consistente\nen siete preguntas con filtros de aplicación\nque exploraban el historial migratorio del\nhogar. El objetivo del formulario fue clasificar\na la población entre hogares de estudio\n(hogares en los que al menos una persona\nreportara haber cambiado de residencia\nal interior de Honduras entre 2004 y 2014\npor causas relacionadas con violencia o\ninseguridad) y hogares de comparación. <sup>37</sup> [^37: Para el estudio, se entiende por hogar a una o varias\npersonas, unidas o no por vínculos familiares, que viven\njuntas para proveer y satisfacer sus necesidades alimenticias,\nque habitan una vivienda.]\n\n**Selección de hogares:** se determinó\nencuestar a todos los hogares de población\nde estudio encontrados en la enumeración\ny encuestar a uno de población de\ncomparación, seleccionado de forma\naleatoria, por cada tres hogares de estudio\nencontrados. En los casos en que se\nencontraron menos de tres hogares de\nestudio por segmento siempre se realizó una\nencuesta en los hogares de comparación.\n\n**Encuesta:** el instrumento de encuesta <sup>38</sup> [^38: Ver anexo II] se\ndiseñó para recopilar la siguiente información:\n\n- Datos de la vivienda: tipo, tenencia,\nservicios, etc.\n\n- Datos del hogar: activos, recursos,\nparticipación, redes sociales,\nintegración, etc.\n\n- Datos de las personas del hogar:\ncaracterísticas demográficas, migración,\nsalud, educación, empleo, etc.\n\n- Historial de migración y hechos\nvictimizantes\n\n- Intenciones futuras\n\n\n36 Ver anexo I\n37 Para el estudio, se entiende por hog", "output": {"entities": {"named_data": [], "descriptive_data": ["Datos de la vivienda", "Datos del hogar", "Datos de las personas del hogar"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001615", "page": 26, "chunk": 2, "title": "Caracterización del desplazamiento interno en Honduras", "pdf_url": "https://reliefweb.int/attachments/fa4ef533-fbec-3fd5-aa26-2f8613ff774b/Informe%20caracterizacion%20desplazamiento.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Datos de la vivienda", "label": "DESCRIPTIVE_DATA", "score": 0.8609604239463806, "start": 1169, "end": 1189, "probe_score": 0.046, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Datos del hogar", "label": "DESCRIPTIVE_DATA", "score": 0.8270536065101624, "start": 1226, "end": 1241, "probe_score": 0.2977, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Datos de las personas del hogar", "label": "DESCRIPTIVE_DATA", "score": 0.8567227125167847, "start": 1314, "end": 1345, "probe_score": 0.3922, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n\n**Refugee employment rates significantly improved in 2024, moving closer to national levels**\n\n\nUkrainian refugee employment rates <sup>14</sup> [^14: The employment rate is defined as the number of employed or self-employed individuals of working age (15-64) as a share of\nthe total number of people in this age group] have experienced a sizeable increase from 2023 in most countries,\nrising by 9 percentage points year-over-year at the regional level to 64%. This indicator now stands just 7\npercentage points below the equivalently weighted mean for the host population (71%).\n\n\nRefugee employment grew both owing to a decrease in unemployment, which declined to 9% from 13% last\nyear, as well as new individuals coming into the labor force <sup>15</sup> . In fact, the 2024 labor force participation rate\namounted to 70%, which stands almost in line with the equivalent host country indicator of 73%.\n\n\n**<u>EVOLUTION OF THE REFUGEE EMPLOYMENT RATE FROM 2023 TO 2024</u>**\n\n\n70%\n\n\n60%\n\n\n50%\n\n\n40%\n\n\n30%\n\n\n20%\n\n\n10%\n\n\n\n0%\n\n\n\nEmployment\n\nrate 2023\n\n\n\nEmployment\n\nrate 2024\n\n\n\nUnclear\nlabor force\n\nstatus\n\n\n\nDecrease in\nunemployment\n\n\n\nDecrease in\n\npotential\nlabor force\n\n\n\nExpansion of\n\n\n\nforce\n\n\n\nthe labor\n\n\n\nNote: Only includes data from the 7 countries surveyed in both rounds (Bulgaria, Czech Republic, Hungary, Republic of Moldova, Poland, Romania, and\nSlovakia)\n\n\nSource: Survey data, SAG estimates\n\n\n**<u>REFUGEE VS HOST EMPLOYMENT RATES BY COUNTRY</u>**\n\n\nRefugee (2023) Refugee (2024) Host (2023)\n\n\n\n76% 76%\n\n\n\n76%\n\n\n\n\n\n\n\n62%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nBulgaria Czechia Estonia Hungary Latvia Lithuania Moldova Poland Romania Slovakia Region\n\n\nNote: For comparability, employment rates for host countries have been recalculated assuming a similar gender distribution to that of refugees\n\n\nSource: ILO, survey data\n\n\n14. The employment rate is defined", "output": {"entities": {"named_data": ["SAG estimates"], "descriptive_data": ["Survey data", "survey data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 9, "chunk": 0, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Survey data", "label": "DESCRIPTIVE_DATA", "score": 0.6407687664031982, "start": 1489, "end": 1500, "probe_score": 0.9928, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "SAG estimates", "label": "NAMED_DATA", "score": 0.5963414907455444, "start": 1502, "end": 1515, "probe_score": 0.9921, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "DESCRIPTIVE_DATA", "score": 0.5708122849464417, "start": 1916, "end": 1927, "probe_score": 0.8192, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*equilibrium model** <sup>**18**</sup> **in a modelling**\n**scenario that includes a productivity**\n**shock to account for the positive**\n**productivity impacts of migrants.**\nIn the model a marginal productivity\nof labour shock of a 1.5-2% dependent\non the year is set, as to zero out the\nimpact of Ukrainian refugees on the\nunemployment rate in the economy. This\nis in line with the lack of negative impacts\nof Ukrainian refugees on the Polish labour\nmarket in our econometric modelling,\nand empirical literature on productivity\n\n\n\n17 For the literature review, underlying empirical evidence, and model calibration refer to the appendix on modelling strategy.\n\n18 Details on Deloitte D.Climate model calibration are outlined in the Appendix on modelling strategy, while further details on this CGE- class (Computable General\nEquilibrium) model are available in the Online Technical Appendix.\n\n\n22\n\n\n\n19 The complete rationale for the productivity shock is outlined in the Appendix on modelling strategy, while further detailed results of econometric models are\navailable in the Online Technical Appendix.\n\n20 As outlined in the Appendix on modelling strategy, the total number of refugees was set at 2.6% of the total population, while their share in total employment as\ngrowing from 1.5% in 2022 to 2.4% in 2024.\n\n21 Full results of a modelling scenario with no shock to productivity are available in the Online Technical Appendix.\n\n\n\n23", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 11, "chunk": 4, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "7 ENVIRONMENTAL AND SOCIAL MONITORING\n\n\nAppropriate environmental monitoring indicators should be selected for both the re\nconstruction and the road operation phases. It is envisaged that monitoring be undertaken by\nthe Environmental and Social Unit of the Ministry of Roads, Public Works and Housing.\n\nThe preceding sections outline the indicators for monitoring during construction and operation\n\nphases of the project road. The associated cost estimates for monitoring have also been\nincluded. In addition, the institutional responsibilities and capacity for monitoring and the\ntraining needs have been discussed.\n\n\n**7.1** **Indicators** **for monitoring during the** **construction phase**\n\n\nThe recommended indicators for monitoring during the construction phase include:\n\nA simple questionnaire to assess the awareness level of the Contractor's team on public\nhealth issues, such as HIV/AIDs and environmental issues (air, water and land pollution).\nThis could take the form of double checking whether they were provided with awareness\n\ntraining at the start of the Project as recommended in the mitigation measures. For\nenvironmental issues, simple questions could include _'what_ _do_ _you_ _do_ _with_ _your_ _waste_\n_products?';_\nThe effectiveness of rehabilitation of quarries and borrow pits by the Contractor      - the\nSupervising Engineer / Environmental Officer to locate the borrow pits one year after the\nlast contract payment of the Contractor or have the re-vegetation programmes improve\nthe area in comparison to its original condition;\nThe effectiveness of rehabilitation of construction camps, as above.\nThe efficiency of drainage structures;\nCompensation of Project Affected People;\nAn assessment of the amount of timber used for the Project. This should include\nquantification, the source and comments on proof of sustainability.\nAn estimate on the saving in material needs by recycling the bitumen.\n\nNoise, vibration and air emissions surveys of selected pieces of equipment used during\nconstruction.\n\n\n**7.2** **Indicators for monitoring** **", "output": {"entities": {"named_data": [], "descriptive_data": ["Noise, vibration and air emissions surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013130", "page": 44, "chunk": 0, "title": "Kenya - Northern Corridor Transport Improvement Project : environmental assessment (Vol. 8 of 9) : Feasibility and detailed design for rehabilitation of the Lanet - Nakuru - Mau Summit - Timboroa roads", "pdf_url": "https://documents.worldbank.org/curated/en/443781468774529912/pdf/E8430vol010801paper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Noise, vibration and air emissions surveys", "label": "DESCRIPTIVE_DATA", "score": 0.7939372658729553, "start": 1927, "end": 1969, "probe_score": 0.0033, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " (whose authorities have\nvolunteered to take part in this exercise), over\n2 million <sup>1</sup> people arrived via such routes from\n2010 to 2021, and positive reforms in different\ncountries have facilitated access to legal entry via\nregular migration channels for persons in need of\ninternational protection.\n\n\nTo meet the objective of the Global Compact on\nRefugees, though, there is still a long way to go.\nData included in this report can be used to identify\ngaps, evaluate impact and achievements, and\ninform new initiatives. Governments, academia,\nemployers and private sector, civil society and\ncommunities all have a role to play in creating\nmore opportunities for refugees to feel safe,\napply their talents and build a life in dignity for\nthemselves and their families through moving to\nother countries.\n\n\nThe Global Refugee Forum 2023 in December\nis the perfect moment for the international\ncommunity to step up their efforts and strengthen\ntheir commitment to reach the Roadmap’s\nobjective of 2.1 million refugees accessing\ncomplementary pathways between 2019 and\n2030.\n\n\n**<mark>Gillian Triggs</mark>**\n\nAssistant High Commissioner for\n\nProtection, **UNHCR**\n\n\n\n**1** Over 1.88 million permits to nationals from Afghanistan, Eritrea, Iran, Iraq, Somalia, Syria, Venezuela to OECD countries and Brazil for family, work and\nstudy purposes from 2010–2021 in addition to the 133,498 permits for sponsorship purposes.\n\n\n<u>5</u>", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Data included in this report"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001039", "page": 4, "chunk": 1, "title": "Safe Pathways for Refugees III: OECD-UNHCR study on pathways used by refugees linked to family reunification, study programmes and labour mobility between 2010 and 2021 [EN/AR]", "pdf_url": "https://reliefweb.int/attachments/9e4502d1-14dc-4ba0-bc12-a8a9b183bcfb/Safe%20Pathways%20for%20Refugees%20III.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data included in this report", "label": "VAGUE_DATA", "score": 0.6240541338920593, "start": 410, "end": 438, "probe_score": 0.0073, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " among\nproductive-age individuals, with women\n18-65 making up 40% and men only 18% of\nUkrainian refugee population. This is largely\ndue to the conscription of military aged\nmen in Ukraine.\n\n\n\n66+\n\n\n56-65\n\n\n46-55\n\n\n36-45\n\n\n26-35\n\n\n18-25\n\n\n<18\n\n\n\nsocial insurance. Second, the statistical\ndefinition of an employed person is wider\nthan just being registered with the Social\nInsurance Institution (Zakład Ubezpieczeń\nSpołecznych, ZUS) on a certain day <sup>3</sup> [^3: Employed person is a person, who during the reference week worked for at least 1 hour for pay or profit, including contributing family workers; had a certain job\nattachment; or produced agricultural goods for sale or barter. A definition according to the Labour Force Survey: <u>https://ec.europa.eu/eurostat/statistics-explained/</u>\n<u>index.php?title=Glossary:Employed_person_-_LFS</u>] . Third,\nsome Ukrainians work in the shadow\neconomy. The number of workers with\nUkrainian citizenship and social insurance\nincreased from only 33 thousand at\nthe end of 2013 to 627 thousand at the\nend of 2021 – just before the refugee\ninflux. Some of this increase reflects\nthe transitioning of Ukrainians to more\nregular work arrangements and securing\nwork permits. Following February 2022,\n\n\n\nthe numbers further increased with the\narrival of Ukrainian refugees. The data for\nmid-2024 shows 771 thousand workers\nwith Ukrainian citizenship registered for\nsocial insurance, including 247 thousand\nrefugees. Ukrainian refugees in Poland\nhave been given PESEL UKR numbers\n\n- a version of an ID number assigned to\nevery Polish national – which made high\nquality data on their demographics easily\navailable, though they may still be missing\nfrom most of the statistics compiled by the\nPolish statistical office.\n\n\n\n20% 19%\n\n\nMen Women\n\n\n\n1%\n\n\n1%\n\n\n2%\n\n\n\n3%\n\n\n4%\n\n\n\n7%\n\n\n8%\n\n\n\n4%\n\n\n4%\n\n\n\n9%\n\n\n\n12%\n\n\n\n7%\n\n\n#### **1.2 Households characteristics**\n\n\n\n**The structure of the Ukrainian**", "output": {"entities": {"named_data": ["Labour Force Survey"], "descriptive_data": [], "vague_data": ["data for\nmid-2024"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 4, "chunk": 1, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Labour Force Survey", "label": "NAMED_DATA", "score": 0.7920582294464111, "start": 722, "end": 741, "probe_score": 0.9286, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data for\nmid-2024", "label": "VAGUE_DATA", "score": 0.5688758492469788, "start": 1326, "end": 1343, "probe_score": 0.0039, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "education would retire at age 85 and a 45 year-old pursuing tertiary education\n\n\nwould retire at age 95.\n\n\n(iii) _The earnings function is separable in schooling and experience implying that_\n\n_the return to experience is independent from the level of education._ <sup>_16_</sup> [^16: An assumption derived from an assumption of identical post school investments across individuals and] The\n\n\nassumption implies that the log (real) wage experience profiles are parallel across\n\n\nschooling levels. Basically, this assumption implies that the value of one extra\n\n\nyear of job experience of a street vendor is equal to the value of one extra year of\n\n\njob experience for a surgeon. Given knowledge intensive jobs are expected to\n\n\ncarry a higher return to experience, it is plausible that additional education\n\n\nincreases the return to experience. Therefore, schooling and job-experience\n\n\nappear to be inseparable, contrary to the assumption. Heckman et al. (2003)\n\n\nstatistically test the assumption on US data. They find that the assumption might\n\n\nhave been valid for the available US-data at the time when the Mincer-regression\n\n\nmethodology was developed (1970s). However, the assumption is not valid for\n\n\nrecent data.\n\n\n(iv) _The only costs of schooling are foregone earnings._ In the case of Colombia, this\n\n\nassumption could distort the estimate significantly. For a large share of the\n\n\npopulation, the cost of education presents an obstacle for re-entering the\n\n\neducation system. Especially, tertiary education can be prohibitively expensive.\n\n\nYearly tuition amounts to the equivalent of 80 percent of GDP per capita, World\n\n\nBank (2003b).\n\n\n(v) _The age-earning-education profiles remain constant over the lifetime of an_\n\n\n_individual_ . This is contradictory to the empirical evidence. Various papers\n\n\ndocument a rise in the skill premium to tertiary education over the last two\n\n\ndecades, Card and Lemieux (2000) and Blom and Velez (2001). The assumption\n\n\ncorresponds to an implicit assumption of perfect certainty of future earnings.\n\n\n16 An assumption derived from an assumption", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["US data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003014", "page": 24, "chunk": 0, "title": "wps3800", "pdf_url": "https://local/prwp/wps3800.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "US data", "label": "VAGUE_DATA", "score": 0.7079127430915833, "start": 1003, "end": 1010, "probe_score": 0.9434, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "03-26|||||||2020-05-05|2020-04-09|2020-06-04|2020-06-09|\n|ET-AAWSA-166154-GO-RFQ /<br>Procurement of GS pipe(2 1/<br>2\"),63mm B class, length 2<br>700 M|IDA / 60070|Component 1: Sanitation an<br>d water supply services impr<br>ovements in Addis Ababa|Post|Request for Quota<br>tions|Limited|Single Stage - One E<br>nvelope||100,000.00|52,229.23|Completed|||||||2020-04-10|2020-03-30|||||||2020-05-08|2020-04-09|2020-06-07|2020-06-04|\n|ET-AAWSA-166158-GO-RFQ /<br>Procurement 2 Surface with c<br>ables and accessories|IDA / 60070|Component 1: Sanitation an<br>d water supply services impr<br>ovements in Addis Ababa|Post|Request for Quota<br>tions|Limited|Single Stage - One E<br>nvelope||95,000.00|30,558.95|Completed|||||||2020-04-06|2020-03-26|||||||2020-05-04|2020-04-09|2020-06-03|2020-06-05|\n|ET-AAWSA-169273-GO-RFQ /<br>Procurement of Standard 6m<br>length riser pipe (class \"C\" g<", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:006333", "page": 5, "chunk": 4, "title": "Ethiopia - EASTERN AND SOUTHERN AFRICA- P156433- Second Ethiopia Urban Water Supply and Sanitation Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099245010072213125/pdf/P156433018f9700630bf790507674069272.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a v\nManufacturIng 5 7 3.7 4 7 5 0 / s \\\\t oo  Services 475 272 190 201\n\nPrfvate consumpffon 90 7 81 9 938 95 1 20\nGeneral govemment consumption 7 0 9 6 146 17.2 =c ~GDFDl\nImpons of goods and servrcea 39 7 23 6 33 4 373 -3GW_G_____\n\n\n_(average_ _annual growth)_ 1981-9 1991401 2000 2001 Growth ot exports and Imports (%)\n\nAgrutumre -0 6 -2 6 2 2 3 8 oo\nIndustry 0.1 -41 51 5 6 s0\nManUnacturIng 6.9 . .\nServices -5 7 -5.4 4 0 51 \nPrivate oonsumpffon -2 0 -19 10 4 100 -50\nGeneral govemment consumption -5.1 -0 2 41.3 27 9 -100\nGross domestic Investment -06 3 0 50 - EOpois -tr-ports\nImports of goods and services -2 2 -151 85 0 61 3\n\n\nNote 2001 data are pretirrinary eastliates\n'The diamonds show four Key Indicators in the country (in bold) conipared with itS income-group average It data are missing, the diantond wiUt be rrconrrlte\n\n\n-56", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["2001 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020016", "page": 60, "chunk": 2, "title": "Ethiopia - Emergency Recovery and Rehabilitation Project : Environmental Assessment", "pdf_url": "https://documents.worldbank.org/curated/en/914431468749790993/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2001 data", "label": "VAGUE_DATA", "score": 0.7082152366638184, "start": 639, "end": 648, "probe_score": 0.0183, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "88 is not likely the same as\n\n\nthat which generated changes of inequality between 1987-88 and 2001-02. The panel data exercise is thus\n\n\nlikely doomed from the outset: It is predicated on variation in the explanatory variables being comparable\n\n\nbetween and within villages. Combined with results from Table 2 that showed that the effect of inequality\n\n\non growth was not constant in the first place, the village-panel probably cannot be used to address the\n\n\nquestion of whether the growth-inequality relationship is driven by fixed heterogeneity. However, the\n\n\nexercise is still revealing as to the limited nature by which increases in inequality potentially mattered\n\n\nover this time period: After its initial impact from 1987-88, there is no evidence of a link between\n\n\nsubsequent inequality and growth.\n\n##### 5.0 Conclusions and Interpretation\n\n\nIf in 1987 a compulsive gambler wagered that between two otherwise identical Chinese villages,\n\n\nthe low inequality village would be richer in 1997 than the high inequality village, he would likely win.\n\n\nOur estimates suggest that if the difference in the Mean Log Deviation was 0.09, i.e., the difference\n\n\nbetween the 10th and 90th percentiles of inequality in 1987, the average annual growth rate for\n\n\nhouseholds in the low inequality village would be 1.8 percentage points higher relative to a median\n\n\nhousehold annual growth rate of 3.4 percent. By this standard, high inequality was a robust and\n\n\n_Inequality and Growth in Rural China_, Page 21", "output": {"entities": {"named_data": [], "descriptive_data": ["panel data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004669", "page": 23, "chunk": 1, "title": "wps5483", "pdf_url": "https://local/prwp/wps5483.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "panel data", "label": "DESCRIPTIVE_DATA", "score": 0.6109747886657715, "start": 107, "end": 117, "probe_score": 0.9295, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " model will introduce and maintain a minimum standard of quality for a lower secondary education school\nand develop schools as safe learning spaces.\n\n\n33. **Approach to targeting sub-counties** :\n\n     - There are 135 districts in Uganda (as of 2016), including 13 refugee hosting districts (RHDs). The Project\nwill target sub-counties in 96 districts with low enrollment rates, high unsatisfied demand for lower\nsecondary education, and no public secondary school. All RHDs will be supported under the Project.\n\n     - The Project will also include 84 non-refugee hosting local governments (LG). The 84 LG were selected\nusing the following approach. First, only LGs which have sub-counties without a public secondary school\n(“underserved subcounty”) were considered as Uganda implements one-public-school-per-subcounty\npolicy. There are 90 such LGs. Second, the LGs which do not have enough primary feeder schools in\nunderserved sub-counties were removed. Based on the current primary to secondary transition patterns\nand experience from private sector constructing new secondary schools, a minimum of seven primary\nschools are required to provide sufficient number of graduates to feed in a new large (eight classrooms,\ntwo stream) lower secondary school. Thus, six LG were removed from the list brining the final number to\n84 LG.\n\n     - Unfortunately, enrollment data is not available on sub-county level. Thus, the demand assessment used\ndistrict/LG level information as a proxy. In 70 out of 84 selected LGs, the GER is below average for Uganda,\nand in 14 districts it exceeds the average. However, while the GER for the district as a whole is higher than\nexpected, there are sub-counties/areas in these districts which provide limited opportunities for\ncontinuing education in secondary schools and unsatisfied demand for lower secondary education is high.\nThe demand for each subcounty will be established and verified during the", "output": {"entities": {"named_data": [], "descriptive_data": ["district/LG level information"], "vague_data": ["enrollment data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 22, "chunk": 1, "title": "Uganda - Secondary Education Expansion Project", "pdf_url": "http://documents.worldbank.org/curated/en/406361595815248191/pdf/Uganda-Secondary-Education-Expansion-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "enrollment data", "label": "VAGUE_DATA", "score": 0.7374069690704346, "start": 1356, "end": 1371, "probe_score": 0.6073, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "district/LG level information", "label": "DESCRIPTIVE_DATA", "score": 0.7174698710441589, "start": 1443, "end": 1472, "probe_score": 0.0, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the situation that was agreed upon with\nthe Borrower.\n\nSigned by:\nFinancial Management v I _N_\n##### Specialist K {dO'.i1, O0\n\n(FMS-OPR) Rafika Chaouali, MNSHD Date\n\n\n**Part II:** **Procurement/Contract Management** System\n\nI have reviewed the procurement/contract management system relating to this project, including\nthe format and content of the section on Project Management Reports (PMRs) on procurement\n\nmonitoring. The objective of the review was to determine whether the procurement/contract\nmanagement system adopted by the project conforms to IDA's guidelines for procurement in\ninvestment projects. My review was based on the \"Assessment of Agency's Capacity to\nImplement Project Procurement, Setting of Prior Review Thresholds and Procurement\nSupervision Plan\" guidelines issued by IDA.\n\nI confirm that the project satisfies IDA's minimum procurement management requirements.\nHowever, in my opinion, the project does not have in place an adequate procurement/contract\nmanagement system that can provide the appropriate data on major procurement and contract\nmanagement (PMR - Section 3) as required by IDA.", "output": {"entities": {"named_data": [], "descriptive_data": ["data on major procurement and contract\nmanagement"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000022", "page": 54, "chunk": 1, "title": "Albania - Microcredit Project", "pdf_url": "http://documents1.worldbank.org/curated/en/192291468767658763/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data on major procurement and contract\nmanagement", "label": "DESCRIPTIVE_DATA", "score": 0.6258809566497803, "start": 1032, "end": 1081, "probe_score": 0.0015, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nState of Palestine\n\n\nEcuador\n\n\nBangladesh\n\n\nColombia\n\n\nUganda\n\n\nSyrian Arab Republic\n\n\nIraq\n\n\n\n\n\n3.0\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n**The number of donors increased, but about two-**\n**thirds of ODA came from the five largest providers.**\n\n\nTo enhance burden- and responsibility-sharing, the\nGCR calls for broadening the support base, including\nthe number and types of donors. Compared to the\n2018-2019 data, where 36 donors reported financing\nfor refugee situations, 48 donors reported in 20202021. This included 32 DAC countries (USD 19.9\nbillion in bilateral ODA), 11 non-DAC countries (USD\n\n\n\n293 million in bilateral ODA), and five development\nbanks (USD 3 billion in multilateral ODA). Another\nUSD 3.2 billion was channelled as core contributions\nto 11 refugee-mandated United Nations agencies\nand four other multilateral entities, such as UNHCR,\nUNRWA, UNOCHA, Global Fund, i.a. (Figure 9).\nDespite the generosity of a larger number of financial\nproviders, the responsibility of supporting refugee\nsituations lay squarely with the five largest providers.\nThe United States of America (USD 6.6 billion),\n\n\nGLOBAL COMPACT ON REFUGEES INDICATOR REPORT 29", "output": {"entities": {"named_data": ["GLOBAL COMPACT ON REFUGEES INDICATOR REPORT"], "descriptive_data": [], "vague_data": ["2018-2019 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000435", "page": 28, "chunk": 1, "title": "2023 Global Compact on Refugees Indicator Report", "pdf_url": "https://reliefweb.int/attachments/3d407ba2-2493-4519-a8d6-c8b8911d1346/2023-gcr-indicator-report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2018-2019 data", "label": "VAGUE_DATA", "score": 0.8117124438285828, "start": 378, "end": 392, "probe_score": 0.9218, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "GLOBAL COMPACT ON REFUGEES INDICATOR REPORT", "label": "NAMED_DATA", "score": 0.6239766478538513, "start": 1097, "end": 1140, "probe_score": 0.9859, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " frames and\ninformation regarding population distribution by\n\n\n18 With both adult males and females present\n\n19 Also defined here for the 15+ age group\n\n\n**10**\n\n\n\ngeographic area and accommodation type. The\nobjective was to ensure a diverse sample\nrepresentative of the population’s composition. A\ncombination of different sampling methods was\nused, typically incorporating multiple stages and\nblending convenience sampling, cluster random\nsampling, and simple random sampling (the latter\nbeing exclusive to Romania).\n\n\nFor the regional analysis, population weights were\napplied based on the most up-to-date figures\nregarding the number of individual refugees\nrecorded in each country. This ensured the analysis\nmore accurately represented the broader refugee\npopulation across the region.\n\n\nAppropriate measures were implemented to ensure\nthe protection of personal data and guarantee\nconfidentiality in all data collection and processing\nactivities. Consent was requested and recorded for\nall selected participants, providing clear information\non the purpose, and expected use of the data.\n\n\nThe poverty line for each country was defined as\n50% of the median <u>[equivalized disposable income](https://www.oecd.org/els/soc/OECD-Note-EquivalenceScales.pdf)</u>\nas reported by the <u>[OECD (new definition since](https://stats.oecd.org/)</u>\n2012) for 2021. This figure was indexed towards\n2023 using national consumer price indexes (CPI).\nOn the survey data side, only households that did\nnot have any missing information on income\n(respondents were asked to provide both sources\nand amounts) were included in the calculation\n(households that reported having no income also\ndid not pass the filter). In addition, for households\nthat reported total expenditure above total income,\nexpenditure data was used instead, as it was\ndeemed to be more reliable. Following the OECD\nmethodology for equivalization, the resulting\ndisposable income figure for each household was\ndivided by the", "output": {"entities": {"named_data": [], "descriptive_data": ["national consumer price indexes", "expenditure data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 9, "chunk": 1, "title": "3", "pdf_url": "https://local/jad_paddy_docs/3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "national consumer price indexes", "label": "DESCRIPTIVE_DATA", "score": 0.7653444409370422, "start": 1402, "end": 1433, "probe_score": 0.5394, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "expenditure data", "label": "DESCRIPTIVE_DATA", "score": 0.7153494358062744, "start": 1782, "end": 1798, "probe_score": 0.1167, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n# Recommendations\n\n\n\nHost countries and communities have made\ncommendable and continuous efforts to support\nrefugees in accessing essential health and MHPSS\nservices. While most respondents reported\nadequate access, barriers to services changed and\nincreased for some refugees. These changes do not\ntake the same form for all refugees, and\nintersectional factors related to gender, age,\ndisability, and chronic illness continue to impact the\nexperiences and needs of refugees from Ukraine in\nthis regard. The recommendations below highlight\nkey priorities and actions for governments and RRP\npartners to address these challenges and enhance\nrefugees’ access to care in host countries.\n\n\nThese actions aim to support governments and\nlocal communities in strengthening health and\nMHPSS systems in areas impacted by refugee\narrivals and advancing the integration of refugees\ninto national systems. Achieving these goals will\nrequire long-term planning and sustained funding\ncommitments.\n\n\n\n\n\n\n\n9. <u>[Integration of migrant and refugee data in health information systems in Europe: advancing evidence, policy and practice](https://doi.org/10.1016/j.lanepe.2023.100744)</u>\n\n\n**28**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["migrant and refugee data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000004", "page": 27, "chunk": 0, "title": "NAVIGATING HEALTH AND WELL BEING CHALLENGES FOR REFUGEES FROM UKRAINE   2nd Edition", "pdf_url": "https://local/jad_paddy_docs/navigating health and well-being challenges for refugees from ukraine - 2nd edition.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "migrant and refugee data", "label": "VAGUE_DATA", "score": 0.6438383460044861, "start": 1084, "end": 1108, "probe_score": 0.74, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "# **Forewords**\n\nToday, more people than ever are forcibly displaced due to\nconflict, violence, and environmental hazards. Fragility, conflict, and violence (FCV) has become a development barrier that predominantly affects the most vulnerable people,\nthreatening their livelihoods and economic growth opportunities. In fact, by 2030, at least half of the world’s poor will\nbe living in fragile and conflict-affected settings and most of\nthem in Africa. With violent conflicts rising at an unprecedented rate, the impact of violence and conflict has worsened, creating the largest forced displacement crisis since\nWorld War II. We need adequate data on displaced and host\ncommunities to better understand their characteristics and\ndynamics, which is fundamental to inform the design and\nimplementation of targeted interventions. However, notably\nin Sub-Saharan Africa, multidimensional data gaps prevent\nan assessment of socioeconomic conditions among the displaced and host populations.\n\n\nKenya is exemplary of the challenges and opportunities at\nthe heart of these dynamics. The current refugee and asylum seeker population in Kenya exceeds 490,000 people,\nengendering multilayered impacts on host communities. In\nTurkana, the poorest county in the country, the refugee population makes up a significant share of the local economy\nand the population (an estimated 40 percent). The Kalobeyei\nsettlement in Turkana West was established in 2015 as an\nalternative to a camp setting, based on principles of refugee\nself-reliance, integrated delivery of services, and greater support for livelihood opportunities through evidence-based\ninterventions.\n\n\nAligned with the Global Compact on Refugees, the Kalobeyei\nIntegrated Socioeconomic Development Plan (KISEDP) recognizes the need for collecting and using socioeconomic\n\n\nviii\n\n\n\ndata on refugees and hosts for targeted programming. The\nUNHCR-World Bank 2018 Kalobeyei Socioeconomic Survey (SES) addresses this need by introducing an innovative approach which allows generating welfare data that are\nrepresentative of the Kalobeyei settlement’s population and\ncomparable to the Turkana County and national residents.\n\n\nThis report", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["socioeconomic\n\n\nviii\n\n\n\ndata"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000641", "page": 8, "chunk": 0, "title": "Understanding the Socioeconomic Conditions of Refugees in Kenya | Volume A: Kalobeyei Settlement - Results from the 2018 Kalobeyei Socioeconomic Survey", "pdf_url": "https://reliefweb.int/attachments/5db37855-7edd-3a88-a03c-464668a5c042/6034c5124.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "socioeconomic\n\n\nviii\n\n\n\ndata", "label": "VAGUE_DATA", "score": 0.6297073364257812, "start": 1803, "end": 1831, "probe_score": 0.4134, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "br>Reports.<br>Third-Party<br>Monitoring<br>Agent<br>reports. Proj<br>ect<br>Management<br>Team<br>estimations.<br>|Number of owners will<br>be determined by<br>disaggregating the<br>beneficiary data of the<br>progress reports<br>|Project Management<br>Team/UN-Habitat<br>|\n|Tenants benefiting from resilient,<br>rehabilitated residential units|Number of tenants who<br>receive technical and|Annual<br>|Progress,<br>Monitoring|Number of tenants will<br>be determined by|Project Management|\n\n\nPage 34 of 66", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["beneficiary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 39, "chunk": 1, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "beneficiary data", "label": "VAGUE_DATA", "score": 0.5364707708358765, "start": 183, "end": 199, "probe_score": 0.2031, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "> Despite a number of donor activities in the education sector discussed in greater\ndetail in Annex II, the needs of the Syrian population are great, as are the strains that they are\nplacing on public provisions especially the public education system. For those students not\nenrolled, early marriage and child labor are significant concerns. Even for those enrolled,\ndropout is high and the social disruption to a generation of children is potentially catastrophic. <sup>4</sup>\nServing these students is a priority along with maintaining existing services to Lebanese\nstudents.\n\n\n7. This project is intended to provide emergency support to the Lebanese public education\nsystem and has two principal objectives: (i) to support schools to meet operational needs in order\nto provide education services to the Lebanese and Syrian school age population, and (ii) to help\nimprove the learning environment in Lebanese public schools in the face of an influx of refugee\nchildren, deteriorating physical and learning environments, and lack of both human and financial\nresources.\n\n\n**C.** **Sectoral and Institutional Context**\n\n\n8. **Prior to the Syrian Crisis, human capital development in Lebanon was already**\n**characterized by high inequality.** As revealed by the World Bank’s inequality-adjusted 2013\nHuman Development Index (HDI), while Lebanon performs relatively well in terms of human\n\n\n2 “Syrian Refugee Response: Lebanon Interagency Update” UNHCR, November 2014\n3 GER 2012 all secondary programs, Lebanon and Syria; World Bank EdStats accessed 10.7.14; current Syrian\nsecondary enrollment rate estimated Inter-Agency Multi-Sector Needs Assessment 2014 (Education Chapter).\n4 UNHCR 2013 (The Future of Syria: Refugee Children in Crisis).\n\n\n2", "output": {"entities": {"named_data": ["2013\nHuman Development Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000030", "page": 10, "chunk": 1, "title": "Lebanon - Emergency Education System Stabilization Project", "pdf_url": "http://documents.worldbank.org/curated/en/578481467991017996/pdf/PAD1190-PAD-P152848-PUBLIC-Box391435B-LB-EESSP-Final-PAD-for-printing.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "2013\nHuman Development Index", "label": "NAMED_DATA", "score": 0.5816147923469543, "start": 1295, "end": 1323, "probe_score": 0.9874, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " registration procedures, the\nmediation committee will be established, and mediation meetings will be organized with interested\nparties. Minutes of meetings will be recorded. The existence of this first instance mechanism will be\nwidely disseminated to the affected people as part of the consultation undertaken for the sub‐project\nin general. It is important that these mediation committees be set up as soon as RAP preparation\nstarts. Disputes documented for example, through socio‐economic surveys should be dealt with by\nappropriate mediation mechanisms which must be available to cater for claims, disputes and\ngrievances at this early stage. A template form for claims should be developed and these forms be\ncollated on a quarterly basis into a database held at project level.\n\n\n**VIII.** **Verification**\n\n\n11. The Mediation Meeting Minutes, including agreements of compensation and evidence of\ncompensation made shall be provided to the Municipality/district, to the supervising engineers, who\nwill maintain a record hereof, and to auditors and socio‐economic monitors when they undertake\nreviews and post‐project assessment. This process shall be specified in all relevant project documents,\nincluding details of the relevant authority for complaints at the municipal/district or implementing\nagency level.\n\n\nPage 80 of 90", "output": {"entities": {"named_data": [], "descriptive_data": ["socio‐economic surveys", "database held at project level"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 83, "chunk": 1, "title": "Lebanon - Roads and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/210611486651815142/pdf/Lebanon-Roads-Employment-PAD-P160223-01262017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "socio‐economic surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8739959597587585, "start": 478, "end": 500, "probe_score": 0.0022, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "database held at project level", "label": "DESCRIPTIVE_DATA", "score": 0.8643261790275574, "start": 751, "end": 781, "probe_score": 0.0019, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "data from 1997 to maintain consistency in the number of districts used in the analysis. <sup>1</sup> [^1: Three new districts were formed in the 1990s in Rajasthan, limiting us to using data since 1996.] We\nuse this data to construct an aggregate district-level measure for annual farm productivity.\nSpecifically, we define _FarmProd_ for district _d_ and year _t_ as:\n\n\n\n_FarmProddt_ =\n\n\n\n_n_\n\n\n\n_c_ =1\n\n\n\n_MSPct ∗_ <sup>_<u>Prodct</u>_</sup>\n\n_Areact_\n\n\n\n(1)\n\n\n\nIn (1), _c_ refers to the crop while _Prod_ denotes the output, measured in thousands of\ntons for each crop. _Area_ denotes the area alloted to the crop in the district for that year,\nmeasured in thousand of hectares. As we are aggregating across 14 crops, we use the federally\nadministered minimum support price (MSP) as the crop-specific weight to convert the cropspecific yields into an uniform monetary value (scaled by area). The MSP provides the\nminimum price for 22 major crops in India, including both food and non-food crops. The\nprices are set by the federal government each year prior to the cropping season, allowing\nproducers to know in advance the minimum price guaranteed by the government for their\noutput. As the MSP is binding across all states and districts in India, it provides a national\nmeasure of prices which we use to convert the crop-specific yield measure into an uniform\nmonetary value. As the MSP prices are measured as rupees per quintal, our productivity\nmeasure is scaled accordingly and measured as rupees per quintal.\n\nMonthly data on district rainfall is also provided by ICRISAT. We aggregate the monthly\ndata into annual data by summing monthly rainfall across all months. We use the two-decade\nlong rainfall data for each district to obtain district-specific rainfall distributions, which we\nsubsequently use to define positive and negative", "output": {"entities": {"named_data": [], "descriptive_data": ["Monthly data on district rainfall", "rainfall data"], "vague_data": ["data from 1997"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001631", "page": 6, "chunk": 0, "title": "idu1f810700010f571467d1a26d1b44b4902e8d5", "pdf_url": "https://local/prwp/idu1f810700010f571467d1a26d1b44b4902e8d5.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from 1997", "label": "VAGUE_DATA", "score": 0.723152756690979, "start": 0, "end": 14, "probe_score": 0.9845, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Monthly data on district rainfall", "label": "DESCRIPTIVE_DATA", "score": 0.9038915634155273, "start": 1518, "end": 1551, "probe_score": 0.866, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "rainfall data", "label": "DESCRIPTIVE_DATA", "score": 0.6388612389564514, "start": 1702, "end": 1715, "probe_score": 0.4982, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000097", "page": 19, "chunk": 1, "title": "West Bank and Gaza - Second Community Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/573471468763473544/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7292463183403015, "start": 272, "end": 283, "probe_score": 0.8771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "beneficiaries; (iii) applying a proxy means test (PMT) <sup>15</sup> [^15: Prior to 2009 this ranking was purely done on the basis of the age of the caregiver (from the youngest to oldest if the\ncaregiver was younger than 18 and from oldest to youngest if the caregiver was aged over 18).] to create a priority list of eligible households;\nand (iv) validation of this priority list of beneficiaries by the community. The assessment team found\nthat this process was followed in most of the areas visited. However, there were places where favors\nwere sought from would-be beneficiaries, mainly in moneta1y tenns.\n\n32. _The HSNP:_ The program piloted the use of three forms of targeting: (i) community-based\ntargeting (CBT) in which communities both identify appropriate targeting criteria and identify needy\nhouseholds up to the specified quotas; (ii) a universal social pension (SP) that benefits those over the\nage of _55_ years old who can prove their age with a national ID card or bi1th cettificate and those over\n60 years for those who have to prove their age using a historical calendar implemented by a vetting\ncommittee; and (iii) a dependency ratio approach that benefits households with a high number of\ndependents. These approaches have relied on 'on-demand' methodology, which requires households\nto request for inclusion in the program rather than relying on community leaders to identify eligible\nhouseholds. Monitoring information indicates that the procedures were generally followed and that\ntargeting procedures were more or less seen as fair (96% of the HSNP beneficiaries thought the\ntargeting process was fair compared to 50% of non-beneficiaries). <sup>16</sup> [^16: 0PM (2012) _Consolidated Operational Monitoring Report._ Kenya Hunger Safely Net Programme: Monitoring and\nEvaluation Component.\n17Infom1ation derived from OPM and IDS (2011) and OPM (2012a).] Key constraints in the\nimplementation of the system include: <sup>17</sup>", "output": {"entities": {"named_data": ["OPM and IDS"], "descriptive_data": [], "vague_data": ["Monitoring information"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014802", "page": 16, "chunk": 0, "title": "Kenya - National Safety Net Program for Results : additional financing : Environmental and social systems assessment", "pdf_url": "https://documents.worldbank.org/curated/en/561151484233714724/pdf/111962-EA-P161179-P131305-NSNP-ESSA-PUBLIC-Disclosed-1-12-2016-II.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Monitoring information", "label": "VAGUE_DATA", "score": 0.6286736130714417, "start": 1422, "end": 1444, "probe_score": 0.9737, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "OPM and IDS", "label": "NAMED_DATA", "score": 0.514438807964325, "start": 1845, "end": 1856, "probe_score": 0.5314, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Disbursement forecast\n\n\n\nContract number\n*Contract subject\nAwardee\n*Launching date\n-Expected delivery date\n-Non objection date\n*Expected date of final delivery\n*Bidder nationality\n*Contract allocation (general account, budget, loan\ncategory, geographic area)\n*List of contracts\nManagement of financial -Standard financial statements (balance sheet;\naccounts statement of sources and uses of funds/income\nstatement, ...)\n*LACI reports for the project duration\nFixed Assets management -Inventory of Fixed Assets (type, quantity, valuation,\ndate of service, etc.)\n\n\n\nSupplier\nAccounting category ; budgetary and accounting\nallocation of fixed assets\n\n\n\nLocation\nDepreciation\n-Disposal of Fixed assets\n\n\n\n**Module** Functions\nSorting parameters Project ID and currency used\n\n                  - Fiscal years\nCurrency\nDecentralized data entry locations\n\n\n\nChart of accounts, managerial reports, geographic\nareas of intervention, etc.\n\n\n\n\n                - Books of accounts\nDonors\n\n                 - Contracts\nCategories of disbursement\nUser Management Data storage ; restitution ; correction; cleaning; etc.\n\n                - Import/export of data to other Tempro modules\n\n\n\nIt is expected that the application would be modified to differentiate the operations from the\nprojects, as well as funding sources to allow for reporting in financial and accounting terms of the\nproject objectives and activities. The concept should allow for proper monitoring of the project\nduring the life of the credit, namely: (i) chart of accounts; (ii) by category, component, and subcomponent; (iii) by geography (type of establishment, site and district); (iv) by category of\nexpenses; and (v) in local and foreign currency. Reporting of multi-level data is planned, which\n**wiU** bring about a more dynamic approach to the management of the project, and which should", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["multi-level data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000093", "page": 51, "chunk": 0, "title": "Tajikistan - Education Reform Project (LIL)", "pdf_url": "http://documents1.worldbank.org/curated/en/555901468777299385/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "multi-level data", "label": "VAGUE_DATA", "score": 0.6651609539985657, "start": 1720, "end": 1736, "probe_score": 0.4661, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Project Coordination and<br>Management|Post|Direct Selection|Direct<br>||39,325.00|28,524.00|Signed|2018-11-09|2018-07-05|2018-11-19|2018-08-02|||2019-01-23|2020-01-21|2019-03-24||\n|KE-MOALF-85420-CS-INDV<br>/ Consultancy on<br>Development of web based<br>Grievance Redress Mechanism<br>(GRM)<br>|IDA / 59000|Project Coordination and<br>Management|Post|Individual<br>Consultant<br>Selection|Limited<br>||70,000.00|70,143.92|Completed|2018-11-16|2019-04-04|2018-11-21|2019-11-14|2018-12-12|2020-02-07|2019-01-16|2020-03-06|2019-03-17|2020-11-30|\n|KE-MOALF-200171-CS-INDV<br>/ Consultancy to undertake<br>feasibility study on milk<br>processing plant for Dairy<br>Farmers of Cherangany (DFC)<br>and Cherangany Dairy Group<br>(CDG)<br>|IDA / 59000|Strengthening Producer<br>Organizations and Value<br>Chain Development|Post|Individual<br>Consultant<br>Selection|Limited<br>||20,000.00|0.00|Canceled|2020-10-22||2020-11-05||2020-11-19||2020-11-24", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019530", "page": 7, "chunk": 3, "title": "Kenya - AFRICA EAST- P153349- National Agricultural and Rural Inclusive Growth Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/882191637170263278/pdf/Kenya-AFRICA-EAST-P153349-National-Agricultural-and-Rural-Inclusive-Growth-Project-Procurement-Plan.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Financial Contributions: agencies are very grateful for the financial support provided\nby donors who have contributed to the 3RP activities with unearmarked and broadly earmarked\nfunds as well as for those who have contributed directly to the operation.\n\n\nand private donors.\n\n\nHosting: The agencies are also very grateful for the generosity of Kurdistan Regional\nGovernment of Iraq (KRG) for hosting 238,061 (97%) of Syrian refugees and about 1.2m IDPs.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000817", "page": 49, "chunk": 0, "title": "Information Kit No. 15: Syrian Refugees - Iraq: Humanitarian Inter-Agency Interventions - First fourth-monthly report: 2016 January, February, March and April (Published: May 2016)", "pdf_url": "https://reliefweb.int/attachments/78aa2f49-ef9d-3b06-b9ca-ef840bc8ec99/InformationKit3RPMay2016Inter-AgencyInterventionsforSyrianRefugees-Iraq.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and the rest mostly from\ncorn and sugar beets. While ethanol represents the largest share of total biofuel production (around 80%),\nbiodiesel production has grown faster in recent years.\n\n\nAutomotive fuels are directly consumed by households or businesses that own vehicles, nevertheless to\na lesser degree they might affect the broader population through public/shared transportation. The\ncountry’s more than 115 million vehicles are shared among the total population of more than 213 million\nand total households of more than 75 million, or around 0.54 per capita and 1.5 per household\nrespectively, according to data from IBGE for recent years. The country has a young population on average,\nand slightly over 37% of the country’s population is below the age of 18 (the minimum legal age for\nobtaining a driver license) and would not own a vehicle. The regional distribution of vehicles is also uneven,\nwith almost half\n\n\n6", "output": {"entities": {"named_data": ["data from IBGE"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001581", "page": 7, "chunk": 1, "title": "idu1dd6794ee14daf14bb21a1c810ba10751f08a", "pdf_url": "https://local/prwp/idu1dd6794ee14daf14bb21a1c810ba10751f08a.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from IBGE", "label": "NAMED_DATA", "score": 0.8165425658226013, "start": 616, "end": 630, "probe_score": 0.159, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\npensions)\n\n\n\nHumanitarian\n\ncash\n\n\n\nEquivalized\n\n\n\nEmployment\n\nincome\n\n\n\nOther Equivalized\n\n\n\nincome\n\n\n\n2024\n\n\n\nincome\n\n\n\n2023\n\n\n\nNote: Only includes data from the 7 countries surveyed in both rounds (Bulgaria, Czech Republic, Hungary, Republic of Moldova, Poland, Romania, and\nSlovakia)\n\n\nSource: Survey data, SAG estimates\n\n\n12. Household disposable income adjusted for size, as per Eurostat’s methodology\n13. The 2024 survey probed for income from family in Ukraine more explicitly\n\n\n**9**", "output": {"entities": {"named_data": [], "descriptive_data": ["Survey data", "2024 survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000010", "page": 8, "chunk": 1, "title": "socio economic researchpaper", "pdf_url": "https://local/jad_paddy_docs/socio-economic_researchpaper.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Survey data", "label": "DESCRIPTIVE_DATA", "score": 0.6273173689842224, "start": 298, "end": 309, "probe_score": 0.9985, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2024 survey", "label": "DESCRIPTIVE_DATA", "score": 0.6902467012405396, "start": 416, "end": 427, "probe_score": 0.9861, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "A bridge to life in the UK\n\n\nMany RCOs felt that supplementary schools helped to\naddress inter-generational tensions between parents who\ncame to the UK with a clear sense of identity from their\nhome country, and children who were born in Britain or\narrived at a young age and were immersed in British\nsociety through the educational system. For the second\ngeneration, competence in the community language\nenabled communication with parents who might have\nlimited English, especially with single-parents who faced\nadditional pressures and may have had fewer opportunities\nto learn English. Supplementary schools also provided a\nvenue for exploring issues of identity and values. Some\nRCOs felt that supplementary education helped young\npeople to arrive at an identity that was British but also\nincluded and valued the culture of their parents.\nFostering an identity that embraced both cultures\nwas seen to help young people engage positively\nand confidently with the educational system and the\nwider community.\n\n\nMany RCOs providing supplementary education were\nconscious of outcomes and aimed to improve competence\nin community languages and educational attainment\nthrough supplementary schools. Several RCOs in the\nsample had been awarded the National Resource Centre\nfor Supplementary Education (NRCSE) Gold Quality Mark,\nwhich assesses monitoring. One RCO set its own targets\nfor pupils, consulting national statistics and meeting with\nparents to set targets more ambitious than those set by\nschools. The RCO then set a scheme of work for pupils\nand parents, recording parents’ involvement. Some RCO\nschools reported as outcomes the numbers of pupils\nsitting GCSEs in community languages and their results.\nSeveral felt that supplementary schools improved\nmotivation and engagement with education, including\nhigher education, but evidence for this was anecdotal.\n\n\nSome RCOs recognised the need for better documentation\nand expressed the intention to improve. Time and capacity\nwere common barriers to documentation. One RCO\nobserved that the new pupil assessment system made it\nmore difficult to monitor progress in primary school.\nIt should be noted that in general, the outcomes of\nsupplementary education are well-documented <", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["national statistics"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001328", "page": 19, "chunk": 0, "title": "A bridge to life in the UK: Refugee-led community organisations and their role in integration (October 2018)", "pdf_url": "https://reliefweb.int/attachments/cc625cfb-c5d9-3500-a07e-3f8eca765f83/A_bridge_to_life_in_the_UK_Oct_2018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "national statistics", "label": "VAGUE_DATA", "score": 0.6680818796157837, "start": 1402, "end": 1421, "probe_score": 0.9609, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Value<br>Ongoing bulk training in all<br>programs<br>Date<br>23-Nov-2004<br>Comment|Value<br>Continuous targeted training in key<br>areas such as ICT, exp mgt,<br>ROPE, VAT/withhold, governance<br>package in regions and local<br>governments<br>Date<br>29-Nov-2010<br>Comment|Value<br>Date<br>Comment|\n\n\n**<u>Data on Financial Performance (as of 06-Dec-2010)</u>**\n\n\n\n\n\n\n\n\n\n\n|nt(s) Key Dates|Col2|Col3|Col4|Col5|\n|---|---|---|---|---|\n|Loan No.|Status|Approval Date|Signing Date|Effectiveness Date|\n|IDA-38990|Effective|11-May-2004|23-Aug-2004|22-Nov-2004|\n\n\n\nPage 13 of 14", "output": {"entities": {"named_data": ["Data on Financial Performance"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020384", "page": 12, "chunk": 1, "title": "Ethiopia - Public Sector Capacity Building Program Support Project : P074020 - Implementation Status Results Report : Sequence 10", "pdf_url": "https://documents.worldbank.org/curated/en/937991468744278759/pdf/P0740200ISR0Di020420111296826783627.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data on Financial Performance", "label": "NAMED_DATA", "score": 0.7273550033569336, "start": 308, "end": 337, "probe_score": 0.3471, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "more effect in some cases than others, and the controls do change the regression function on\n\n\nexpenditure; in a number of cases, the controls attenuate the gains at high expenditure levels,\n\n\neven producing an inverted-U relationship.\n\n\nHow well does _SAH_ reflect objective health circumstances? We give in Table 3 the\n\n\ncross-sectional OP for 2002 in which we regress _SAH_ on all measures of specific abilities and\n\n\nailments reported in the survey. We included all the variables in the RLMS 2002 round that we\n\n\nfelt could reasonably be treated as exogeneous to overall health status. These assumptions can\n\n\nalways be questioned, and we cannot rule out the possibility that errors in the self-reporting of\n\n\neven truly exogeneous predictor can introduce a correlation with the error term. We decided not\n\n\nto include two variables that are likely to be correlated with _SAH_, namely whether the respondent\n\n\nis a smoker and alcohol consumption, on the grounds that the concern about endogeneity was too\n\n\nsevere in these cases.\n\n\nFor both men and women, roughly half the variance in _SAH_ is explicable in terms of age\n\n\nand the specific health attributes identified in the data set; for women a slightly higher share of\n\n\nthe variance is explained by these variables. The signs are generally what one would expect.\n\n\n_SAH_ tends to fall for both men and women over the bulk of the data. <sup>15</sup> [^15: The turning point for men is at age 50, while for women it is over 100 years. The relatively low\nturning point for men (implying that men over 50 start to perceive that their health as improving with age)\ncould well stem from selective mortality (recalling that male life expectancy is about 60, more than 10\nyears lower than for women). Adaptive behavior amongst older men may also be playing a role, along the\nlines of Groot (2000).] Amongst the physical\n\n\nactivity variables, the strongest predictors of _SAH_ are ability to run, climb stairs, crouch and eat.\n\n\nThe effects of the physical activity variables are similar for men and-mass", "output": {"entities": {"named_data": ["RLMS 2002 round"], "descriptive_data": [], "vague_data": ["data set"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002912", "page": 15, "chunk": 0, "title": "wps3698", "pdf_url": "https://local/prwp/wps3698.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "RLMS 2002 round", "label": "NAMED_DATA", "score": 0.5244362950325012, "start": 491, "end": 506, "probe_score": 0.7376, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data set", "label": "VAGUE_DATA", "score": 0.5690816044807434, "start": 1180, "end": 1188, "probe_score": 0.9543, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nStrengthening Public Sector Efficiency and Statistical Capacity Project (P151155)\n\n\nthe closing date of the project.\n\n\n32. **Procurement prior review. The procurement risk is rated Substantial.** Table 2.3 summarizes the\nprocurement prior review for ‘Substantial risk’. These prior review thresholds can evolve according to\nthe variation of procurement risk during the life of the project.\n\n|Table 2.3. Procurement Prior Review Thresholds (US$, millions)|Col2|\n|---|---|\n|**Type of Procurement**|**Thresholds**|\n|Goods, Information technology and non - consulting services|2|\n|Consulting firms|1|\n|Individual Consultants|0.3|\n\n\n\n**Environmental and Social (including safeguards)**\n\n\n33. The activities supported by the proposed project are likely to have no adverse environmental\nimpacts. The project is therefore classified as Environmental Category C. No specific environmental\nsafeguard instrument will be required. Consequently, the World Bank’s policies in this area are not\ntriggered.\n\n\n34. The proposed project is limited to the provision of training and TA and is not expected to result\nin any direct negative social impacts. The project will assist the Government in improving PFM,\nespecially public investment management, and enhancing the quality of the statistics system, especially\npoverty statistics. It is hence expected to contribute to improved delivery of basic social services and\nreduced poverty.\n\n\n35. **Citizens’ engagement** . The project will contribute to increased citizens’ engagement not only\nthrough increased transparency and access to information on policy impact (statistics) and public\nfinance data but also by stimulating direct participation in PIB monitoring. First, the project will support\nthe publication of public budget and spending in a user-friendly and reusable format through online\nBOOST and ensure the publication of key financial and performance data of SOEs. Second", "output": {"entities": {"named_data": [], "descriptive_data": ["public\nfinance data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000044", "page": 72, "chunk": 0, "title": "Cameroon - Strengthening Public Sector Effectiveness and Statistical Capacity Project", "pdf_url": "http://documents1.worldbank.org/curated/en/305621511406035802/pdf/CAMEROON-PAD2-11012017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "public\nfinance data", "label": "DESCRIPTIVE_DATA", "score": 0.5417618751525879, "start": 1631, "end": 1650, "probe_score": 0.0709, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "satisfied two or more rainy seasons; - Progress reports submitted\n2b.3 100% of houses benefit by implementing partners;\nmarginalized population                 - Beneficiary assessments\ngroups (female headed                 - NaCSA M&E data\nhouseholds, disabled and their\nfamilies); and\n2b.4 100% of beneficiaries\nwere selected by beneficiary\ncommunities.\n\n\n**3.** Proiect Management and\nInnovative Activities - NaCSA administrative data - Qualified implementing\n\n                                  - Capacity building event partners available to provide\n**3(a)** **Capacities of** assessments; capacity building and IEC\n**communities,** **chiefdomns,** **and** 3a.1 At least 5 successful - Participatory project activities at all levels;\n**district authorities to select,** capacity building events completion reviews; - A qualified full-time M&E\n**implement and maintain** carried out each year; - IDA supervision missions specialist is provided to\n**projects established** **and** NaCSA by another donor\n**strengthened** agency\n\n**3(b)** **Information, Education** 3b. 1 At least 40% of HHs are - Beneficiary assessments; - Non-NSAP activities\n**and Communication** aware of program; - NaCSA adrninistrative data; undertaken by NaCSA do not\n3b.2 At least 60%of chlefdom                  - IDA aide-memoires and detract from NaCSA ability to\nand district governments project status reports; and implement project.\naware of NSAP coverage,\ntargeting, methodology, and\nresults; and\n3b.3 At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA", "output": {"entities": {"named_data": ["NaCSA M&E data", "NaCSA administrative data", "NaCSA adrninistrative data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000121", "page": 31, "chunk": 0, "title": "Sierra Leone - HIV/AIDS Response Project", "pdf_url": "http://documents1.worldbank.org/curated/en/710911468776784140/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NaCSA M&E data", "label": "NAMED_DATA", "score": 0.8557507395744324, "start": 226, "end": 240, "probe_score": 0.0002, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "NaCSA administrative data", "label": "NAMED_DATA", "score": 0.7650092840194702, "start": 412, "end": 437, "probe_score": 0.0006, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "NaCSA adrninistrative data", "label": "NAMED_DATA", "score": 0.6916330456733704, "start": 1188, "end": 1214, "probe_score": 0.4531, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Makhtar Diop|\n|. <br>Borrower: Islamic Republic of Mauritania|. <br>Borrower: Islamic Republic of Mauritania|. <br>Borrower: Islamic Republic of Mauritania|. <br>Borrower: Islamic Republic of Mauritania|. <br>Borrower: Islamic Republic of Mauritania|. <br>Borrower: Islamic Republic of Mauritania|. <br>Borrower: Islamic Republic of Mauritania|. <br>Borrower: Islamic Republic of Mauritania|. <br>Borrower: Islamic Republic of Mauritania|\n|Responsible Agency: Ministry of Economic Affairs and Development|Responsible Agency: Ministry of Economic Affairs and Development|Responsible Agency: Ministry of Economic Affairs and Development|Responsible Agency: Ministry of Economic Affairs and Development|Responsible Agency: Ministry of Economic Affairs and Development|Responsible Agency: Ministry of Economic Affairs and Development|Responsible Agency: Ministry of Economic Affairs and Development|Responsible Agency: Ministry of Economic Affairs and Development|Responsible Agency: Ministry of Economic Affairs and Development|\n|Contact:<br>|Contact:<br>|Mr. Mohamed Ould Babetta|Mr. Mohamed Ould Babetta|Mr. Mohamed Ould Babetta|Title:|Title:|Project Coordinator|Project Coordinator|\n|Tel. No.:<br>|Tel. No.:<br>|22245290601|22245290601|22245290601|Email:|Email:|Babetta@pdu.mr|Babetta@pdu.mr|\n|. <br>**Project Financing Data (in US$ million)**|. <br>**Project Financing Data (in US$ million)", "output": {"entities": {"named_data": [], "descriptive_data": ["Project Financing Data", "Project Financing Data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000166", "page": 6, "chunk": 3, "title": "Mauritania - Local Government Development Program Project", "pdf_url": "http://documents1.worldbank.org/curated/en/943421468056371471/pdf/760530PAD0P127010Box377322B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Project Financing Data", "label": "DESCRIPTIVE_DATA", "score": 0.5612092018127441, "start": 1303, "end": 1325, "probe_score": 0.9653, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Project Financing Data", "label": "DESCRIPTIVE_DATA", "score": 0.5137293934822083, "start": 1353, "end": 1375, "probe_score": 0.3695, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_3.4 Limitations of the study_\n\n\nThis assessment of the impact of the JCLIS relies on simple comparisons of the average outcomes\n\n\nof interest between participants of the lift irrigation system and their neighbors in the same village\n\n\nor in a neighboring village who do not participate. We use self-reported recall data collected from\n\n\nfarmers through in-person interviews with them. JCLIS sites and their beneficiaries were not\n\n\nselected randomly. Site selection was guided by hydrological and topological characteristics.\n\n\nFarmers with land closer to favorable sites may differ from their neighbors in skills, motivation,\n\n\nsocial capital, and other qualities, any of which can also affect agricultural outcomes. Farmers\n\n\nwere moreover required to pay a small one-time Rs. 1,100 fee and join the local water user group\n\n\nto irrigate their land from the JCLIS, and their decision to do so may also differentiate them from\n\n\nothers who chose to stay out or wait longer before joining the group. The comparisons made are\n\n\ntherefore qualified as suffering from omitted variables bias. Nor did the study benefit from baseline\n\n\ndata on variables of interest prior to the intervention. Attempts to collect recall data from farmers\n\n\nwith questions about cropping areas, patterns, and yields before the JOHAR irrigation systems\n\n\nwere introduced led to unreliable data, particularly for earlier years, and were discontinued. We\n\n\nalso considered revisiting farmers who were interviewed in the baseline survey carried out by\n\n\nOxford Policy Management (OPM), but at the time of our survey (August-September 2021), very\n\n\nfew villages in the baseline survey had a functioning JCLIS. We compare beneficiary and non\n\nbeneficiary farmers across economic variables that presumably do not change over time or as a\n\n\nresult of the JCLIS irrigation. These include average land holding size and asset holdings. We find\n\n\nthat the two are not significantly different across the two groups, providing some evidence of\n\n\nbaseline comparability. In an alternate specification, we drop the control farmers from the\n\n\nneighboring villages and compare JCLIS beneficiaries only with their geographical neighbors\n\n\nwhile", "output": {"entities": {"named_data": [], "descriptive_data": ["self-reported recall data", "baseline survey", "baseline survey"], "vague_data": ["baseline\n\n\ndata", "recall data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001011", "page": 8, "chunk": 0, "title": "idu0be619ce802229044310b97c088a139ef33c1", "pdf_url": "https://local/prwp/idu0be619ce802229044310b97c088a139ef33c1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "self-reported recall data", "label": "DESCRIPTIVE_DATA", "score": 0.8533651232719421, "start": 295, "end": 320, "probe_score": 0.6422, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "baseline\n\n\ndata", "label": "VAGUE_DATA", "score": 0.7063799500465393, "start": 1120, "end": 1135, "probe_score": 0.6875, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "recall data", "label": "VAGUE_DATA", "score": 0.557592511177063, "start": 1208, "end": 1219, "probe_score": 0.376, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "baseline survey", "label": "DESCRIPTIVE_DATA", "score": 0.5479962825775146, "start": 1494, "end": 1509, "probe_score": 0.7531, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "baseline survey", "label": "DESCRIPTIVE_DATA", "score": 0.5720911622047424, "start": 1641, "end": 1656, "probe_score": 0.8726, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "#### **CHAPTER 3: ENVIRONMENTAL CONSIDERATIONS**\n\n**3.1.0 Environmental Profiles**\nClimatic conditions are rather harsh and vegetation (as described above) is\nadapted to such a situation. The watershed function is therefore attributed to\nNakasongola, which contribute to the water flow system. Lugogo River and\nNamwanga swamp are water reserves within Katugo and Kasagala forest\nreserves respectively.\nEnvironmental degradation is a serious issue due to: \n1. Excessive tree cutting, say ‘deforestation’ is now a serious problem,\nresulting from charcoal production.\n_2._ Cattle grazing because the level of cattle keeping is quite high in all areas.\nAs there is inadequate pasture for grazing, cattle owners deliberately set\nfires in anticipation of fresh grass, particularly during dry seasons.\n_3._ Many cattle keepers are landless thus grazing in the forest reserves.\nCattle movement hardens the ground, which in combination with\ndeforestation exposes the soil to surface water runoff and soil erosion.\n\n**3.1.1 Biodiversity Status and Function**\nOnly Kasagala CFR was identified and included in the Uganda Forestry Nature\nConservation Master Plan (FNCMP) because it supports:\n\n  - At least one unique tree species of conservation importance on (Albertine\nrift endemic);\n\n  - Vegetation types W2 ( _Sorghastrum_ Grassland) not otherwise represented\nin the protected area system of Uganda-including Uganda National Parks.\nKasagala falls under category: SECONDARY conservation forest in the\nFNCMP classification. Table 19 summarises the biodiversity values based on\nthe inventory indicators taxa.\n\nAlthough Kasagala has limited biodiversity richness, those existing play\nsignificant functions.\n\nAnimals and insects are agents for seed dispersal.\n\n       - Trees, shrubs and grasses are important sources of medicinal\nherbs, which rural communities constantly use.\n\n       - Katugo MPA and the district as a whole are generally a dry area\nwhere trees/shrubs are important in climate mitigation.\n\n       -", "output": {"entities": {"named_data": [], "descriptive_data": ["inventory indicators taxa"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015910", "page": 30, "chunk": 0, "title": "Uganda - Second Environmental Management and Capacity Building Project : environmental assessment (Vol. 2 of 20) : Forest management plan for Katugo management plan area (Katugo and Kasagala central forest reserves)", "pdf_url": "https://documents.worldbank.org/curated/en/635381468174902726/pdf/E28840v20EA0P0071B0AFR0EA0P073089v2.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "inventory indicators taxa", "label": "DESCRIPTIVE_DATA", "score": 0.6805762052536011, "start": 1570, "end": 1595, "probe_score": 0.9447, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the Deloitte D.Climate model, economic\nimpact of Ukrainian refugees amounted\nto a higher real GDP by 1.5% in 2022, as\nthey initially entered the labour market.\nWith more refugees finding employment,\ntheir impact grew to 2.3% GDP in 2023,\nand further to 2.7% GDP in 2024. This\ncorresponds to GDP being higher by\nPLN 98.7 billion in 2024. In the long term, as\nthe refugees acquire more country-specific\nskills and firms invest to restore their\ncapital-to-labour ratio, the impact will grow\nto 3.2% GDP by 2030. Refugees contribute\nto the economy by increasing the labour\nsupply as both workers and entrepreneurs,\nand by boosting demand as consumers.\nThe increase in GDP is not directly\n\n\n\nproportional to the increase in population\nor employment. <sup>20</sup> [^20: As outlined in the Appendix on modelling strategy, the total number of refugees was set at 2.6% of the total population, while their share in total employment as\ngrowing from 1.5% in 2022 to 2.4% in 2024.] On the one hand,\nincrease in productivity further boosts\nthe economy, on the other net benefits\nare lowered both due to a decrease in\nthe capital-to-labour ratio, as well as an\nincrease in competition in the labour\nmarket. Moreover, the increase in demand\nin tight labour market conditions work in\nthe direction of higher inflation and lower\nprice competitiveness of Polish products\nwhich decrease its overall positive impact.\n\n\n**The results are in line with the**\n**optimistic scenario from the**\n**previous Deloitte (2024) report.** The\ncurrent report is different from the one\nfrom 2024 in that we account for the\npositive productivity shock reflected in\nthe labour market data, which further\n\n\n\n**The impact of Ukrainian refugees**\n**on the Polish economy is estimated**\n**with the Deloitte D.Climate general**\n**equilibrium model** <sup>", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["labour market data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 11, "chunk": 3, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "labour market data", "label": "VAGUE_DATA", "score": 0.6833744049072266, "start": 1635, "end": 1653, "probe_score": 0.0971, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Regular Surveys on Social Tensions throughout Lebanon: Wave IV September 2018\n\n\ncoincided with the Wave III survey, and this most likely provoked a ‘spike’\n\n\nin public confidence. The 34.3% who said the Cabinet ‘improved life a little’\n\nand the 4.4% who said the Cabinet ‘improved life a lot’ represented about\n\n\na ten-percentage point drop in confidence, but the level of confidence in\n\nthis institution, even with the new Cabinet’s formation still pending,\n\n\nnevertheless exceeded the baseline levels of _distrust_ observed in the initial\n\nWave I and Wave II surveys. While public support for the Lebanese Armed\n\n\nForces (LAF) remained near-unanimous, increasing support both for the\n\nInternal Security Forces (ISF) and General Security (GS) brought public\n\n\nsupport the two other major Lebanese security agencies closer in line with\n\npublic support for the LAF.\n\n\n**Figure 8:** _Lesser_ trust in government institutions, by governorate and wave, as a per cent\nof scale maximum.\n\n\nARK DMCC | 27", "output": {"entities": {"named_data": ["Regular Surveys on Social Tensions throughout Lebanon"], "descriptive_data": ["Wave III survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000696", "page": 27, "chunk": 0, "title": "Social Stability - Regular Surveys on Social Tensions throughout Lebanon - Wave IV, September 2018", "pdf_url": "https://reliefweb.int/attachments/661ebcaf-9c3c-36ed-b917-ef8a3906a3ea/67048.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Regular Surveys on Social Tensions throughout Lebanon", "label": "NAMED_DATA", "score": 0.6869507431983948, "start": 0, "end": 53, "probe_score": 0.9977, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Wave III survey", "label": "DESCRIPTIVE_DATA", "score": 0.5741577744483948, "start": 99, "end": 114, "probe_score": 0.9006, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "000 in Turkey, 170,000 in Iraq and 83,000 in Egypt. As of today, Lebanon hosts 963,000 refugees\ncompared to 585,000, 643,000, 227,000, and 135,000 in Jordan, Turkey, Iraq, Egypt respectively (UNHCR data).\n\n\n1", "output": {"entities": {"named_data": ["UNHCR data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000047", "page": 11, "chunk": 2, "title": "Lebanon - Emergency National Poverty Targeting Program Project", "pdf_url": "http://documents.worldbank.org/curated/en/810511467987899324/pdf/PAD1030-ENGLISH-P149242-PUBLIC-FINAL-LEB-ENPTP-English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "UNHCR data", "label": "NAMED_DATA", "score": 0.747323751449585, "start": 192, "end": 202, "probe_score": 0.9102, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Appendix 6** **Map of Affected Land**\n\n\n**Downstream Wellfield**\n\n\n**Upstream well Field**\n\n\n59", "output": {"entities": {"named_data": [], "descriptive_data": ["Map of Affected Land"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007777", "page": 74, "chunk": 0, "title": "Kenya - Water and Sanitation Development Project : Resettlement Plan (Vol. 5 of 3) : Abbreviated Resettlement Action Plan for Baricho Wellfields Protection Works", "pdf_url": "https://documents.worldbank.org/curated/en/099925001262229086/pdf/P1566340b03a5003d092b602ca0529b9ddb.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Map of Affected Land", "label": "DESCRIPTIVE_DATA", "score": 0.7068626880645752, "start": 17, "end": 37, "probe_score": 0.0049, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " sector have low levels\n\nof schooling (which would explain our empirical results on schooling).\n\nIf the cost of mandated benefits to the firm is below the value they have to workers (e.g.,\n\ntax-free job severance payments, health and safety on the job), then an increase in mandated\n\nbenefits could explain a rise in formal sector employment, if wages are fully flexible. Labor\n\nsupply to the formal sector would increase since this sector becomes more attractive, and labor\n\ndemand would also increase if there were a large enough decline in wages. The contraction in the\n\nsupply of self-employed workers causes an increase in their wages. Formal sector employment\n\ncould also increase due to worker registration (through direct action of labor inspectors, or\n\nindirectly through a deterrent effect).\n\n\n32 Using data from IPEA, we can compute the number of people searching for a job in each city, by subtracting the\nnumber of employed from the number of active individuals. The problem with this measure is that we cannot\ndistinguish search in the formal and in the informal sector. If we regress the (log) number of individuals searching\non enforcement (instrumented) we estimate that a one standard deviation increase in enforcement increases total\nsearch by 1/3 of a standard deviation.\n\n\n26", "output": {"entities": {"named_data": ["data from IPEA"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004312", "page": 28, "chunk": 1, "title": "wps5119", "pdf_url": "https://local/prwp/wps5119.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data from IPEA", "label": "NAMED_DATA", "score": 0.8650760054588318, "start": 813, "end": 827, "probe_score": 0.9156, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " ente los refugiados\nacogidos. Entre los países que reportaron datos\ndesglosados por sexo en 2018 para más de\n1,000 refugiados, Serbia y Kosovo (S/RES/1244\n(1999)) y Bosnia y Herzegovina tuvieron la mayor\nproporción femenina con un 58%, seguido de\nTogo, con 56%, y Nigeria y Chad con el 55%. La\nmenor proporción fue reportada por Ecuador, un\n24%, seguido de Malta (27%), Indonesia (28%) y la\nRepública de Corea (29%).\n\n\nLa proporción de menores entre la población\nrefugiada también varió ampliamente en 2018.\nEntre los países que reportan datos desglosados\npor edad para más de 1.000 refugiados, la RDC\nreportó la mayor proporción de menores de 18\naños con un 63%, seguida de Sudán del Sur\n(62%) y Uganda (62%), lo que refleja la joven\nestructura de edad de la población de muchos\npaíses de la región. La menor proporción fue\nreportada en 2018 por Serbia y Kosovo (S/\nRES/1244 (1999)), con sólo alrededor del 1 por\nciento de la población, seguidos de Bosnia y\nHerzegovina (6%) y Argentina (9%).\n\n\nEstas diferencias también se aprecian a nivel regional\n\n[gráfico 22]. La proporción más baja de menores y\nmujeres se vio entre la población de refugiados\nen Europa, donde solo el 44% de la población\n\n\n\n60 ACNUR > **TENDENCIAS GLOBALES 2018** ACN", "output": {"entities": {"named_data": [], "descriptive_data": ["datos\ndesglosados por sexo", "datos desglosados\npor edad"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000519", "page": 30, "chunk": 4, "title": "Tendencias global desplazados forzosos en 2018", "pdf_url": "https://reliefweb.int/attachments/4a4b8fc2-fcc6-390b-b9e3-d1f08bbef1ad/5d09c37c4.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "datos\ndesglosados por sexo", "label": "DESCRIPTIVE_DATA", "score": 0.6135600805282593, "start": 63, "end": 89, "probe_score": 0.4462, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "datos desglosados\npor edad", "label": "DESCRIPTIVE_DATA", "score": 0.6588620543479919, "start": 539, "end": 565, "probe_score": 0.0411, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank** Implementation Status & Results Report\nEA Regional Transport, Trade and Development Facilitation Project (Second Phase of Program) (P148853)\n\n\n<u>Baseline</u> <u>Actual (Previous)</u> <u>Actual (Current)</u> <u>End Target</u>\n\n\nValue 0.00 0.00 0.00 20.00\n\n\nDate 12-Jun-2015 15-Dec-2020 30-Jul-2021 30-Jun-2021\n\n\nThis indicator will be revised during restructuring to reflect the cancellation of the South Sudan Phase 1 of the progra\ndepends on many factors that may not all be related to the project.\n\nComments **:**\n\n\n\n\n\n\n\n\n\n\n\n**Performance-Based Conditions**\n\n\n**Data on Financial Performance**\n\n\n**Disbursements (by loan)**\n\n\n\n\n\nProject Loan/Credit/TF Status Currency Original Revised Cancelled Disbursed Undisbursed % Disbursed\n\n\nP148853 IDA-56380 Effective USD 500.00 500.00 0.00 283.75 224.81 56%\n\n\n**Key Dates (by loan)**\n\n\nProject Loan/Credit/TF Status Approval Date Signing Date Effectiveness Date Orig. Closing Date Rev. Closing Date\n\n\nP148853 IDA-56380 Effective 11-Jun-2015 20-Jul-2015 16-Nov-2015 31-Dec-2021 31-Dec-2021\n\n\n**Cumulative Disbursements**\n\n\n8/23/2021 Page 5 of 6", "output": {"entities": {"named_data": [], "descriptive_data": ["Data on Financial Performance"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011563", "page": 4, "chunk": 0, "title": "Disclosable Version of the ISR - EA Regional Transport , Trade and Development Facilitation Project (Second Phase of Program) - P148853 - Sequence No : 12", "pdf_url": "https://documents.worldbank.org/curated/en/343971629736089055/pdf/Disclosable-Version-of-the-ISR-EA-Regional-Transport-Trade-and-Development-Facilitation-Project-Second-Phase-of-Program-P148853-Sequence-No-12.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data on Financial Performance", "label": "DESCRIPTIVE_DATA", "score": 0.5669000148773193, "start": 584, "end": 613, "probe_score": 0.0017, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Economic Survey of Syrian Refugees in the Kurdistan Region of Iraq, April 2014**\n\n## **FINDINGS**\n\n\nThis section outlines the main findings from the livelihoods assessment. Unless otherwise specified, these are\nrepresentative for population of all the camps across KRI. Where findings are not disaggregated by camp, this results\nfrom the lack of significant variation amongst the camps.\n\n\n**Household Income Levels and Sufficiency**\n\n\nAcross the KRI camps, **47% of respondents reported no source of cash/income for their household** in the 30\ndays preceding the assessment. At camp-level, some significant variations can be noted: on the one hand, camps like\nBasirma, Darashakran and Gawilan exhibit very low percentages of households with income (28%, 35% and 36%\nrespectively) whereas others show **much higher percentages, especially Domiz (75%) and Kawergosk (69%)** .\n\n\n\n\n\n\n\n\n\nSeveral factors can explain the variation in household income levels between refugee camps, including:\n\n\n- The **correlation between geographical location and access to labour markets** . Camps located closer to urban\nareas have easier access to local labour markets. Camps located closer to urban areas have easier access to\nlocal labour markets, notably Domiz (near Duhok), Kawergosk and Qushtapa (Erbil), Arbat (Sulaymaniyah), and\nAkre, which is located inside the town of Akre. The camps of Gawilan, Darashakran and Basirma, which are located\nthe farthest away from any major urban area, consequently have the lowest proportion of the population reporting\nan income.\n\n\n- In the specific cases of Domiz and Kawergosk, the **high number of humanitarian actors inside the camps**\nimpacts inevitably on the employment structure within the camps as well as it increases income-generating\nopportunities through CFW", "output": {"entities": {"named_data": ["Economic Survey of Syrian Refugees"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000688", "page": 11, "chunk": 0, "title": "Economic Survey of Syrian Refugees in the Kurdistan Region of Iraq, April 2014", "pdf_url": "https://reliefweb.int/attachments/65990d0d-ded7-3935-8405-bcfdd2df666c/REACHInitiative_KRISyrianRefugeesEconomicSurvey_validated.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Economic Survey of Syrian Refugees", "label": "NAMED_DATA", "score": 0.8826833963394165, "start": 2, "end": 36, "probe_score": 0.9136, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**24 /** Synthesis of key findings from Inter-Agency Humanitarian Evaluations (IAHEs) of the international responses to crises in\nthe Philippines (Typhoon Haiyan), South Sudan and the Central African Republic\n\n\nin Bangui and coverage gaps at the sub-national level. Overall, HCT-led coordination activities in\nBangui absorbed much capacity and left considerable room for improvement, but coordination\nremained an important factor in the effectiveness of the international response.\n\n\n73. On the relationship and accountabilities among the HCT, ICWG and clusters, the South Sudan\nreport found that there was too much overlap between the functioning of the ICWG and the\nHCT and that “leadership responsibilities became diluted between the various coordination\nbodies”. Greater focus was needed on mandates and accountability. In CAR, respondents\nhighlighted weaknesses in inter-cluster coordination, which “did not support HCT with strategic\nguidance or allow for integrated approaches across clusters”. The OPR had observed that\nweaknesses in inter-cluster coordination led to a proliferation of bilateral operational meetings,\nand had suggested streamlining meetings by appointing executive committees, but the\nevaluation found no evidence that this had happened. Evidently the balance and relationships\namong the HCT, inter-cluster mechanisms and clusters need careful attention, not only to avoid\nduplication and proliferation of meetings, but also to ensure mutual accountability.\n\n\n74. The CAR report notes that some international NGOs challenged the overall HCT-led coordinated\nresponse model, saying that it was “poorly defined”, a “United Nations control mechanism”,\nand an “empty concept”. They judged OCHA’s capacity to be “excessive”, with too many\n“coordinators and talkers”, a duplication of meetings and information, but too few “technicallyinclined implementers”. This is a common enough perception that it needs to be taken seriously,\nand it echoes the analysis above concerning the lack of focus on practical cooperation. On\nthe other hand, at least one United", "output": {"entities": {"named_data": ["Inter-Agency Humanitarian Evaluations"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000991", "page": 25, "chunk": 0, "title": "Synthesis of key findings from Inter-Agency Humanitarian Evaluations (IAHEs) of the international responses to crises in the Philippines (Typhoon Haiyan), South Sudan and the Central African Republic", "pdf_url": "https://reliefweb.int/attachments/94a44662-e79e-32be-ad59-93a5445f6d9d/web_interactive_0.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Inter-Agency Humanitarian Evaluations", "label": "NAMED_DATA", "score": 0.6232900023460388, "start": 40, "end": 77, "probe_score": 0.9417, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "ographic data will<br>be monitored in<br>through the progress<br>reports<br>|Project Management<br>Team/UN-Habitat<br>|\n|Rental contracts signed for rehabilitated<br>units|Number of rental contracts<br>signed for units that have<br>been rehabilitated under<br>subcomponent 1.1. for<br>socio-economic vulnerable<br>renters|Annual<br>|Progress<br>Reports. Mon<br>itoring and<br>Evaluation<br>Reports.<br>|The progress report will <br>monitor the number of<br>rehabilitated apartment<br>units with preferable<br>rental contracts for<br>tenants of buildings<br>rehabilitated under<br>component 1.1.<br>|Project Management<br>Team/UN-Habitat<br>|\n|Of which, are signed with renters|Number of rental contracts|Annual|Progress|The progress report will|Project Management|\n\n\nPage 37 of 66", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["ographic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 42, "chunk": 1, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "ographic data", "label": "VAGUE_DATA", "score": 0.6607747673988342, "start": 0, "end": 13, "probe_score": 0.033, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "completed sub-projects local authorities provide\nconform to ministry standards, resources and staff to operate\ndesigns and norms. and maintain facilities (e.g.\nprovision of teachers and\n\ntextbooks in the case of\nprimary schools);\n\n\nl(b) Targeted communities are lb. 1 At <sup>least 90%</sup> <sup>of</sup> - Beneficiary/ impact - Sub-projects reflect\nempowered to carry out projects are assessed as assessments and other beneficiary needs and\npriority investments. successful by communities evaluation reports improved access to social and\n(achieve rmnimum expected economic services;\noutputs and\noutcomes/imnpacts).\n\n                                     - Supervision missions                                     - PPA methodology is\nlb.2 All supported                  - Beneficiary Assessments internalized by NaCSA and\ncommunities have conducted                - NSAP quarterly progress partners;\nparticipatory needs reports\nassessments and project                 - Participatory M&E results\nidentification using PPA\napproach.                 - Continuous social                 - Capacity building efforts\nI assessment process provided and/or coordinated\nlb.3 100% of communities                  - Participatory M&E results by NaCSA are appropriate and\nhave project management effective;\nstructures in place and trained\ncommunity members.\n\n**2.** Pilot and Special 2a.1 100 km. of feeder roads - Supervision <sup>missions;</sup> - NaCSA's commitment to\n\n**Programs in** Newly rehabilitated. - NSAP quarterly reports; pilot both programs remains\n**Accessible** **Areas** - Annual technical audits; strong\n2a.2 800,000 person days of                  - NaCSA M&E data\n**2(a)** **Rural Public Works** temporary employment\n**Program:** created.\n\nInfrastructure constructed 2a.3 250,000 \"woman days\" of\nand/or upgraded using labor temporary employment\nintensive techniques. created.\n\n\n2a.4 At mid-term review the\ncost per day", "output": {"entities": {"named_data": ["NaCSA M&E data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011239", "page": 30, "chunk": 0, "title": "Ethiopia - Ethiopian Electric Light and Power Authority Project", "pdf_url": "https://documents.worldbank.org/curated/en/321691468034740109/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NaCSA M&E data", "label": "NAMED_DATA", "score": 0.9113216400146484, "start": 1658, "end": 1672, "probe_score": 0.7359, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">21</sup>\n\n\n**Case study: Pakistan**\n\nDuring the 2010 monsoon, Pakistan experienced the\nworst floods in its history. Flooding hit 84 of 121 districts\nand displaced over 20 million people. More than 1,700\nmen, women and children lost their lives, and nearly 2\nmillion had their homes damaged or destroyed. <sup>22</sup>\nOver a million of the affected people were aged 60+.\n\nA vast number of humanitarian stakeholders were\ninvolved in the Pakistan response, and this created\ndifficulties in integrating age-friendly responses by\nclusters. Identifying key UN, NGO and government\ndecision makers was a challenge, both at national and\nregional levels. Even with specific cluster commitment\nto address core concerns such as age and disability,\nthe lack of field data on older people reduced the\nefficacy (and legitimacy) of advocacy messages, and\nmade claims of exclusion of older people from service\nprovision hard to prove.\n\n\n\nTo highlight the needs of older and disabled people,\nUNHCR brought an Age and Disability Task Force into\nthe Protection Cluster. Drawing on its age and disability\nexpertise and human resources, the task force\ninfluenced humanitarian agencies to mainstream age\nand disability across protection and other clusters.\nThrough consultation and assessment, individual\nmembers identified key issues for older and disabled\npeople who had been affected by the flooding.\nTask force members were then assigned to specific\nclusters to advocate for age-friendly and disabilityfriendly responses to be part of emergency and early\nrecovery initiatives. The task force was also given\na space on the Protection Cluster meeting agendas.\n\nTask force outputs focused on older and disabled people\nbeing included in three key areas:\n\n**•** <sup>needs assessments, implementation and monitoring</sup>\n\n**•** <sup>developing technical guidance</sup>\n\n**•** <sup>promoting inclusive reconstruction through</sup>\nhumanitarian and government partners.\n\n\n**The task force approach", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["field data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001104", "page": 6, "chunk": 1, "title": "Protecting older people in emergencies: good practice guide", "pdf_url": "https://reliefweb.int/attachments/a7217620-a83f-3548-835e-45a82ee07e37/6-5-protecting-older-people-in-emergencies-helpage-2013.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "field data", "label": "VAGUE_DATA", "score": 0.7183758616447449, "start": 750, "end": 760, "probe_score": 0.3426, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "للمبردئ . يتم صرف عرئدات المنحة وفقر **ي ردنمصروفات البنك المركزي األ** -11\n\nالتوجيهيةللمبردئ التوجيهية للبنك الدولي كمر هو مشر إليه في خطرب الصرف ووفقر\nللبنك الدولي الخرصة برلصرف للمشروعرت. وسوف يستخدم نظرم الصرف وفقر\nللمعرملة في هذا المشروع. وبنرء عليه، يتم عمل اطلبرت السداد من المنحة من خالل\nاستخدام اطلبرت سحب سواء للمدفوعرت المبرشرة أو المبرلغ المستردة أو إعردة ضخ\n\nاألموال في الحسرب المخصص. وست تضمن كل اطلبرت السحب كرفة المستندات الداعمة\nالمنرسبة، بمر في ذلك بير مفصل برإلنفرق لعمليرت الصرف وإعردة ضخ األموال في\nالحسرب المخصص. إ فئة النفقرت المؤهلة والتي يمكن تمويلهر من عرئدات المنحة\n\nالمنحة. وسيتم منحقية اتفر ونسبة النفقرت التي يتم تمويلهر كنفقرت مؤهلة سيتم تحديدهر في\nفترة س", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000095", "page": 47, "chunk": 0, "title": "Jordan - Enhancing Governance and Strengthening the Regulatory and Institutional Framework for Micro, Small, and Medium Enterprise (MSME) Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/568071468273354492/pdf/PAD7340ARABIC00n0220020140Arabic01.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nGenerating Growth Opportunities and Productivity for Women Enterprises Uganda Project (P176747)\n\n\nlearning agenda. For further details see Annex 4. The Results Framework also includes an indicator relating to the\nadoption of energy efficient and climate resilience infrastructure under Component 3.\n\n64. **Citizen engagement.** The project will work on strengthening citizen engagement, and all beneficiaries, including\nrefugees are key partners in its implementation. Specifically, the project will utilize the following citizen engagement\nmechanisms: (a) participatory decision-making and mobilization of women entrepreneurs through support to existing\nand new women platforms at the village, district, and refugee settlement levels; (b) participatory planning in the design\nof infrastructure for women; and (c) implementation of a grievance redress mechanism (GRM). The GRM will ensure that\nqueries or clarifications about the project are responded to in a timely manner, and that grievances are addressed\nefficiently and effectively. The proposed project will further solicit periodic feedback from beneficiaries through\nbeneficiary satisfaction surveys as well as spot checks and includes a results indicator on the percentage of the project’s\ngrievance redress systems that are addressed.\n\n**C. Project Costs and Financing**\n\n65. **The total project costs are US$217 million, which is to be financed through an IDA grant including US$36 million**\n**from the IDA19 WHR** **for host communities and refugees matched with $4 million from Uganda’s PBA.** See Table 4 for\ndetails.\n\n\n**Table 4: Project Costs by Component**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Project Component|Cost (US$<br>millions)|Of which WHR<br>(US$ millions)|\n|---|---|---|\n|1. Support for Women Empowerment and Enterprise Development<br>Services, including in host and refugee communities<br>|<br>42.0<", "output": {"entities": {"named_data": [], "descriptive_data": ["beneficiary satisfaction surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014321", "page": 31, "chunk": 0, "title": "Uganda - Generating Growth Opportunities and Productivity for Women Enterprises Uganda Project", "pdf_url": "https://documents.worldbank.org/curated/en/527091655323259747/pdf/Uganda-Generating-Growth-Opportunities-and-Productivity-for-Women-Enterprises-Uganda-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "beneficiary satisfaction surveys", "label": "DESCRIPTIVE_DATA", "score": 0.9267861843109131, "start": 1144, "end": 1176, "probe_score": 0.0526, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "CORD), _Libya, Year 2017: Update_\n_on Incidents According to the Armed Conflict Location & Event Data Project (ACLED)_ [, 18 June 2018, https://bit.ly/2ttcMvB.](https://bit.ly/2ttcMvB)\n4 See below “ _Internal and External Displacement_ ”.\n5 See below “ _Humanitarian Situation”_ .\n\n1", "output": {"entities": {"named_data": ["Armed Conflict Location & Event Data Project"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001305", "page": 0, "chunk": 6, "title": "UNHCR position on returns to Libya (Update II) - September 2018", "pdf_url": "https://reliefweb.int/attachments/c94c1114-f697-3c6f-95c7-860d0cd06013/5b8d02314.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Armed Conflict Location & Event Data Project", "label": "NAMED_DATA", "score": 0.7317842245101929, "start": 65, "end": 109, "probe_score": 0.9933, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nframework advance the integration of refugees and foster an enabling environment for them to live in safety and\nwith dignity. Uganda is also implementing the Comprehensive Refugee Response Framework (CRRF) in accordance\nwith the New York Declaration for Refugees and Migrants that is guiding and framing all refugee-related activities.\nThese, combine with the aim to ensure that the refugee response provides support to both refugees and RHDs,\nputting them on a path to self-reliance and by bridging humanitarian and development ways of working. Uganda\nhas reiterated its ongoing commitments to refugee protection in the context of COVID-19 in Uganda’s Strategy\nNote on Support to Refugees and RHDs. Since initial eligibility for WHR resources, Uganda has been implementing\nRefugee and Host Community Sector Response Plans for: education; health; water and environment; and jobs and\n\n\n36 Based on the Uganda Refugee Protection Assessment Update August 2-18, 2021.\n\n\nPage 18 of 92", "output": {"entities": {"named_data": ["Uganda Refugee Protection Assessment Update"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000021", "page": 23, "chunk": 1, "title": "Uganda - Investment for Industrial Transformation and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/469061641926083502/pdf/Uganda-Investment-for-Industrial-Transformation-and-Employment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Uganda Refugee Protection Assessment Update", "label": "NAMED_DATA", "score": 0.8899557590484619, "start": 902, "end": 945, "probe_score": 0.9939, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "analog mechanisms for citizen feedback and grievance redress (mystery shoppers and outreach campaigns on anticorruption and the establishment of Government Service Centers (GSCs)). However, many of these reforms are still works\nin progress and have yet to make a significant difference in the interaction between the government and its citizens. In its\n2021 _State of the Country Report_, the Economic and Social Council of Jordan (ESCJ), an advisory body to the GOJ, has\nstressed that so far, public sector reforms have not met expectations and that digital transformation calls for further\nprogress in the availability, management, and use of data to inform policy making and the implementation of government\nactivities. <sup>4</sup> [^4: See the _<u>State of the Country</u>_ _<u>Reports</u>_ <u>on the ESCJ website at https://www.esc.jo/Reportsen.aspx.</u>]\n\n\n**7.** **The National Digital Transformation Strategy and Implementation Plan for 2021-2025 also drives the digitalization of**\n**government.** It aims to develop digital public infrastructure (DPI), <sup>5</sup> [^5: DPI refers to digital ID, payment, and data exchange capabilities that are fundamental to enabling service delivery at scale and\nsupporting innovation in the digital economy. DPI provides reusable and foundational digital platforms that allow public- and privatesector service providers to build and innovate their products and services.] such as digital identity (ID) and e-payments, to\nstrengthen open government data and the management of government resources, expand government digital services\n(with the objective of automating them fully by 2025), institutionalize e-participation, and promote change management.\nThe GOJ is also adopting a legal and regulatory institutional framework for the protection of personal data (with a\nCybersecurity Strategy adopted in 2018 and a Personal Data Protection Law enacted in 2023, both critical safeguards for\ndigitalization", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["open government data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000181", "page": 12, "chunk": 0, "title": "Jordan - People-Centric Digital Government Program for Results", "pdf_url": "https://documents1.worldbank.org/curated/en/099030724150040202/pdf/BOSIB-70f97ae8-b741-401c-82cc-e87615cc5487.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "open government data", "label": "VAGUE_DATA", "score": 0.530120849609375, "start": 1481, "end": 1501, "probe_score": 0.1114, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**PAD DATA SHEET**\n\n_Lebanon_\n\n_Lake Qaraoun Pollution Prevention Project (P147854)_\n\n**PROJECT APPRAISAL DOCUMENT**\n\n\n_MIDDLE EAST AND NORTH AFRICA_\n\n_GENDR_\n\nReport No.: PAD860\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Col2|Col3|Col4|Col5|Col6|Col7|\n|---|---|---|---|---|---|---|\n|**Basic Information**|**Basic Information**|**Basic Information**|**Basic Information**|**Basic Information**|**Basic Information**|**Basic Information**|\n|Project ID|Project ID|Project ID|EA Category|EA Category|Team Leader(s)|Team Leader(s)|\n|P147854|P147854|P147854|B - Partial Assessment|B - Partial Assessment|Maria Sarraf|Maria Sarraf|\n|Lending Instrument|Lending Instrument|Lending Instrument|Fragile and/or Capacity Constraints [  ]|Fragile and/or Capacity Constraints [  ]|Fragile and/or Capacity Constraints [  ]|Fragile and/or Capacity Constraints [  ]|\n|Investment Project Financing|Investment Project Financing|Investment Project Financing|Financial Intermediaries [  ]|Financial Intermediaries [  ]|Financial Intermediaries [  ]|Financial Intermediaries [  ]|\n||||Series of Projects [  ]|Series of Projects [  ]|Series of Projects [  ]|Series of Projects [  ]|\n|Project Implementation Start<br>Date|Project Implementation Start<br>Date|Project Implementation Start<br>Date|Project Implementation End Date|Project Implementation End Date|Project Implementation End Date|Project Implementation End Date|\n|14-", "output": {"entities": {"named_data": ["PAD DATA SHEET"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000036", "page": 4, "chunk": 0, "title": "Lebanon - Lake Qaraoun Pollution Prevention Project", "pdf_url": "http://documents1.worldbank.org/curated/en/279341468589482380/pdf/PAD860-PAD-P147854-R2016-0133-1-Box396255B-OUO-9.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "PAD DATA SHEET", "label": "NAMED_DATA", "score": 0.5223484039306641, "start": 2, "end": 16, "probe_score": 0.0838, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " nondiscrimination to\nensure the risk to survivors of raising grievances (for example, retaliation, further violence, and even\ndeath) is minimized. GBV service mapping and linking to referrals for GBV and child protection services in\nproject locations will be conducted. Referral pathway training and skills building on how to support a\nsurvivor of GBV using psychological first aid will be provided to all project personnel, thereby ensuring\naccess to referral services in all project areas. To monitor and track GBV risks, recurring gender/GBV audits\nof identified risks will be conducted to identify trends to inform action. The project will engage a gender\nand GBV specialist(s)/specialized agency to train and provide technical assistance. A GBV Action Plan and\na Gender Action Plan have been developed for the scope of the project (see annex 6 for details).\n\n\n116. Security risks are also ‘High’. Decades of war has torn apart the social fabric and has engendered\na culture of mistrust, revenge killings, and competition over resources. Insecurity can constrain\nmovements of the indigenous peoples and stall subproject implementation through delaying the\ntransportation of construction materials. The project has developed a strategy for implementation in\ninsecure areas which defines objective criteria for classifying levels of insecurity and provides options to\nguide implementation in the light of the fluid security context. If IPs cannot access an area, project\nactivities will be temporarily suspended in that location. If the security situation deteriorates significantly,\noptions for restructuring will be considered. Minimum requirements on security risk assessments and\nreporting of incidents are integrated into the ESMF as well as into the more detailed Security Management\nPlan, including (a) documented, regular security meetings, at least weekly; (b) ) tracking of the security\nalert status in project areas and awareness of accompanying procedures for each level; (c) site-specific,\ndocumented emergency response protocols and support lines; and (d) reporting of requirements for\nincidents. UNOPS and IOM are integrated into", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 54, "chunk": 1, "title": "South Sudan - Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/824121596765983121/pdf/South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 1\nPage 2 of 3\n\n\n**Project Development** **Outcome / Impact** **Project reports:** **(from Objective to Purpose'**\n**Objective:** **Indicators:**\nExpand access to basic Increased number of school Project Reports. It is assumed that\neducation. places. Government's current fiscal\nsituation will be resolved\n\n(salary payment to civil\nservants and teachers).\nEnrollment increases in MOE reports. Expansion of facilities and\nprimary schools from 35,000 quality will contribute to\nto 80,000 increased enrollment\nincluding among girls.\nIncreased availability of It is assumed that the\ntextbooks. Government maintains\ndouble-shifting.\n\n\nTrained primary school head Headteachers have autonomy\nteachers. and authority in managing the\nschools.\nBetter trained contractual Contractual teachers are\nteachers recruited early enough before\nthe school year to allow time\nfor training.\n\n\n**Output from each** **Output Indicators:** **Project reports:** **(from Outputs to Objective)**\n**Component:**\nIncreased number of school 226 classrooms will be built Monthly disbursement Availability of school places\nplaces. increasing capacity by over summary. will increase enrollment.\n20,000 based on double\nshifting.\nProvide textbooks. Numbers of textbooks per Semi-annual Provision of textbooks will\npupil increases. supervision reports. improve learning.\nTrained primary school head- Primary school head-teachers Annual audit reports; Better trained head-teachers\nteachers. trained and Guidebook for site visits. will improve school\nschool management prepared efficiency.\nand distributed.", "output": {"entities": {"named_data": ["MOE reports"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000072", "page": 30, "chunk": 0, "title": "Jordan - Health Sector Reform Project", "pdf_url": "http://documents1.worldbank.org/curated/en/466121468773744158/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "MOE reports", "label": "NAMED_DATA", "score": 0.6933835744857788, "start": 385, "end": 396, "probe_score": 0.8075, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "satisfied two or more rainy seasons; - Progress reports submitted\n2b.3 100% of houses benefit by implementing partners;\nmarginalized population                 - Beneficiary assessments\ngroups (female headed                 - NaCSA M&E data\nhouseholds, disabled and their\nfamilies); and\n2b.4 100% of beneficiaries\nwere selected by beneficiary\ncommunities.\n\n\n**3.** Proiect Management and\nInnovative Activities - NaCSA administrative data - Qualified implementing\n\n                                  - Capacity building event partners available to provide\n**3(a)** **Capacities of** assessments; capacity building and IEC\n**communities,** **chiefdomns,** **and** 3a.1 At least 5 successful - Participatory project activities at all levels;\n**district authorities to select,** capacity building events completion reviews; - A qualified full-time M&E\n**implement and maintain** carried out each year; - IDA supervision missions specialist is provided to\n**projects established** **and** NaCSA by another donor\n**strengthened** agency\n\n**3(b)** **Information, Education** 3b. 1 At least 40% of HHs are - Beneficiary assessments; - Non-NSAP activities\n**and Communication** aware of program; - NaCSA adrninistrative data; undertaken by NaCSA do not\n3b.2 At least 60%of chlefdom                  - IDA aide-memoires and detract from NaCSA ability to\nand district governments project status reports; and implement project.\naware of NSAP coverage,\ntargeting, methodology, and\nresults; and\n3b.3 At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA", "output": {"entities": {"named_data": ["NaCSA M&E data", "NaCSA administrative data", "NaCSA adrninistrative data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000052", "page": 31, "chunk": 0, "title": "Croatia - Municipal Environmental Infrastructure Project", "pdf_url": "http://documents1.worldbank.org/curated/en/367181468770702078/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NaCSA M&E data", "label": "NAMED_DATA", "score": 0.8557507395744324, "start": 226, "end": 240, "probe_score": 0.0002, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "NaCSA administrative data", "label": "NAMED_DATA", "score": 0.7650092840194702, "start": 412, "end": 437, "probe_score": 0.0006, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "NaCSA adrninistrative data", "label": "NAMED_DATA", "score": 0.6916330456733704, "start": 1188, "end": 1214, "probe_score": 0.4531, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nNortheastern Road-corridor Asset Management Project 2 (P514937)\n\n\nmanaging ramp meters, and controlling reversible lanes to optimize flow; (iii) Incident Management: Coordinating with\nlaw enforcement and emergency services to detect crashes, manage traffic scenes, and clear incidents to restore\ncapacity; (iv) Demand & Flow Management: Implementing dynamic lane use control, variable speed limits, and\nmanaging queues to prevent bottlenecks; (v) Information Dissemination: Providing real-time updates to travelers\nregarding congestion, weather conditions, and travel times; (vi) Data Analysis & Planning: Analyzing historical and realtime data to improve future traffic strategies. The NERAMP parent project prioritized road safety interventions like\ndriver/school sensitization, signage, and enforcement along the Tororo-Kamdini corridor, aiming to reduce accidents,\nthough implementation faced challenges requiring corrective actions and focus on proper road guidance (signage,\nenforcement) for drivers. This project will enhance road safety by implementing a Safe Systems Approach, which\nintegrates improved infrastructure elements such as walkways, lighting, and bridges, alongside strengthened\nmanagement of the road network. The Safe System Approach is designed to account for human error and lessen crash\nseverity, with the goal of achieving zero fatalities. Key initiatives include upgrading roundabouts at intersections,\nconstructing separated pedestrian walkways in peri-urban areas, reducing speed limits through the installation of speed\nhumps, and improving intersections with curb extensions to protect vulnerable road users. These activities collectively\naim to reduce road traffic injuries and fatalities by building robust road safety management capacity. (c) Subcomponent\n1.3: Institutional support through a capacity building program (US$3.5 million). This subcomponent will finance (i)\nTechnical Assistance (TA) to strengthen MoWT’s capacity for Design, Procurement, Management and Supervision of\ncontracts including not limited to HDM licensing and training (US$ 1.5 million), (ii) A capacity building program on", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["historical and realtime data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001798", "page": 3, "chunk": 0, "title": "Appraisal Environmental and Social Review Summary (ESRS) - NORTHEASTERN ROAD-CORRIDOR ASSET MANAGEMENT PROJECT 2 - P514937", "pdf_url": "https://documents.worldbank.org/curated/en/099041326071027889/pdf/P514937-d4db9788-0ada-4767-9418-44aa680551ad.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "historical and realtime data", "label": "VAGUE_DATA", "score": 0.6479401588439941, "start": 635, "end": 663, "probe_score": 0.7844, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad COVID-19 Strategic Preparedness and Response Project (P173894)\n\n\n\n\n\n|Monitoring & Evaluation Plan: Intermediate Results Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **|**Definition/Description **<br>|**Frequency **|**Datasource **<br>|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|1.1. Update of National COVID-19<br>Response Action Plan|Updating of national action<br>plan to respond to COVID-<br>19 <br>|once<br>|COVID-19<br>report<br>|<br>routine data<br>|<br>MOPH<br>|\n|1.2 Percentage of healthcare workers<br>trained in surveillance and investigation <br>|<br>Number of trained<br>healthcare workers as a<br>percentage of all the health<br>care workers that could be<br>trained|<br>weekly<br>|<br>COVID-19<br>report<br> <br>|routine data<br>|MOPH<br>|\n|1.2 Number of health workers trained on<br>case definition, management, infection<br>prevention and control for COVID-19|<br>Number of trained<br>healthcare workers <br>|weekly<br>|COVID-19<br>report<br>|routine data<br>|MO", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["routine data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000039", "page": 37, "chunk": 0, "title": "Chad - COVID-19 Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/717781588366403375/pdf/Chad-COVID-19-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "routine data", "label": "VAGUE_DATA", "score": 0.5242028832435608, "start": 549, "end": 561, "probe_score": 0.6146, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ",\npharmacists (0.01%), and psychologists\n(0.09%), compared to the following shares\nfor Polish citizens: 0.26%, 0.19%, and 0.18%,\nrespectively.\n\n\n\n**One of the most effective forms**\n**of support offered to refugees**\n**and other immigrants in terms of**\n**employment and earnings to be found**\n**in the literature is language training.**\nFoged et al. (2024) analysed labour market\noutcomes of language training, placement\nin strong labour markets, active labour\nmarket policies, cutting welfare benefits,\nand placement in co-ethnic networks that\nwere directed at refugees in Denmark.\nThanks to unusually detailed Danish data,\nthey could follow individual refugees who\narrived in Denmark between 1987 and\n2008, for at least 10 years, and in most\ncases for 15 years. They found intensive\nlanguage training introduced in 1999 to be\nthe most effective of all policies, accounting\nfor a 5-6 pp. increase in the probability of\nemployment and a USD 3,000 increase\nin annual earnings (2015 figures). While\nlocating refugees in strong labour markets\nalso had considerable positive effects,\nthe report found only some evidence that\nActive Labour Market Policies (ALMPs)\nfocused on matching refugees with deficit\noccupations improved their employment\nprospects and no evidence of positive\neffects of cutting benefits or placing\nrefugees in co-ethnic networks. Heller\nand Mumma (2023) exploited randomized\nenrolment lotteries for a publicly-funded", "output": {"entities": {"named_data": [], "descriptive_data": ["Danish data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 15, "chunk": 4, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Danish data", "label": "DESCRIPTIVE_DATA", "score": 0.6691853404045105, "start": 613, "end": 624, "probe_score": 0.9788, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " in grades 1–\n4 is one of the causes of school dropouts in Cambodia. According to IHSES 2006-2007, the\naverage percentage of completing primary education or above for cohorts of 1963-1969, who\nfinished primary school during the Islamic Republic of Iran–Iraq war, was 88%. In contrast,\n\n\n4", "output": {"entities": {"named_data": ["IHSES"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001633", "page": 5, "chunk": 2, "title": "idu1f87e964d10cb614d3219bdd1759b52b0527b", "pdf_url": "https://local/prwp/idu1f87e964d10cb614d3219bdd1759b52b0527b.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "IHSES", "label": "NAMED_DATA", "score": 0.6084235906600952, "start": 82, "end": 87, "probe_score": 0.996, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nfell into the last two categories (GUS,\n2024). However, to become promoted\nto an appointed or chartered teacher, a\nforeigner must possess Polish, EU, Swiss,\nor other EEA citizenship (Babakova et al.,\n2024). In effect, only 0.4% of Ukrainian\nrefugees were teachers (ZUS-registered\nin mid-2024) compared to 2.2% of Polish\ncitizens. There were more teachers’\nassistants, who are not regulated, than\n\n\n\nactual teachers. Furthermore, the data\npresented in chapter 2 shows that the\nmedian net wages of Ukrainian refugees\nin the teaching profession are just\nPLN 3,500, constituting 66% of what the\nhost population earns, the lowest earnings\nof all sectors.\n\n\n**Occupational licensing rules regarding**\n**citizenship have been relaxed for**\n**medical professions in the wake of**\n**the COVID-19 pandemic in 2020 and in**\n**February 2022, but those were often**\n**makeshift arrangements.** According to\nthe Babakova et al. (2024) report, during\nthe COVID-19 pandemic, practicing medical\nprofessionals from Ukraine were allowed\n\n\n#### **4.3 Language wage premium**\n\n\n\nEnglish for Speakers of Other Languages\nprogramme in Massachusetts. The policy\ntargeted all immigrants, including those\nwho had lived in Massachusetts for\nseveral years, with data for 2008–2016 and\n4,700 individual lottery applicants. Authors\nfound a causal effect, with annual earnings\nincreasing by USD 2,400. These earnings\ngains generated additional tax revenue\nthat produced a 6% return for taxpayers.\nSchmid (2023) studied African refugees\nwho applied for asylum in Switzerland\nbetween 2008 and 2017. He exploited the\nrandom assignment of refugees to French,\nGerman, and Italian cantons, as well as\ntheir prior language knowledge (e.g. French\nspeakers placed in French or German\nspeaking cantons). The results showed that", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data\npresented in chapter 2", "data for 2008–2016"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000001", "page": 15, "chunk": 1, "title": "Analysis of the impact of refugees from Ukraine on the economy of Poland", "pdf_url": "https://local/jad_paddy_docs/analysis of the impact of refugees from ukraine on the economy of poland.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "data\npresented in chapter 2", "label": "VAGUE_DATA", "score": 0.6886163353919983, "start": 434, "end": 461, "probe_score": 0.9968, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data for 2008–2016", "label": "VAGUE_DATA", "score": 0.7513561844825745, "start": 1234, "end": 1252, "probe_score": 0.9905, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Intermediate Results Indicators|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|Col10|\n|---|---|---|---|---|---|---|---|---|---|\n|||||Cumulative Target Values|Cumulative Target Values|Cumulative Target Values|Frequency|Data<br>Source/Methodology|Responsibility for Data<br>Collection|\n|Indicator Name|Core|Unit of<br>Measure|Baseline<br>2013|2014-15<br>(Year 1)|2015-16<br>(Year 2)|2016-17<br>(Year 3)||||\n|Number of NPTP Applicants||Number|480,000|550,000|700,000|800,000|Quarterly|- NPTP database|NPTP Program|\n|Time lapse between application<br>and eligibility notification||Months|3|1|1|1|Quarterly|- NPTP database|NPTP Program|\n|Household awareness of NPTP||Percentage|40|60|80|90|Two time during the life<br>of the program|- Opinion Poll surveys<br>(Y2, Y3)|NPTP Program|\n|Proportion of assisted people<br>informed about the e-card food<br>program||Percentage|0||100||Once after the first year<br>of the program|- NPTP database|NPTP Program<br>|\n\n\n23", "output": {"entities": {"named_data": ["NPTP database"], "descriptive_data": ["Opinion Poll surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000047", "page": 33, "chunk": 0, "title": "Lebanon - Emergency National Poverty Targeting Program Project", "pdf_url": "http://documents.worldbank.org/curated/en/810511467987899324/pdf/PAD1030-ENGLISH-P149242-PUBLIC-FINAL-LEB-ENPTP-English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "NPTP database", "label": "NAMED_DATA", "score": 0.5796927809715271, "start": 478, "end": 491, "probe_score": 0.8819, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Opinion Poll surveys", "label": "DESCRIPTIVE_DATA", "score": 0.7920738458633423, "start": 724, "end": 744, "probe_score": 0.9834, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nDjibouti Integrated Slum Upgrading Project (P162901)\n\n\nof financial position; (c) a statement of ongoing commitments; (d) an analysis of payments and withdrawals\nfrom the project’s account; (e) a statement of cash receipts and payments by category and component; (f)\nreconciliation statement for the balance of the project’s Designated Accounts; (g) statement of cash\npayments made using SOE basis; and (h) the yearly inventory of fixed assets acquired under the project.\n\n\n24. _Flow of funds_ : Payment will be authorized by three signatures: by the Director of ARULOS, the Director\nof the External Financing Department at the Ministry of Finance, and the Director of the Debt Department at\nthe Ministry of Budget. Funds will be transferred based on Withdrawal Applications submitted by ARULOS.\nThe funds will be channeled from the IDA through one segregated Designated Account (DA) in US dollars\nopened at a commercial bank in Djibouti acceptable for the IDA. Advances from the IDA account will be\ndisbursed to the Designated Accounts to be used for the project expenditures.\n\n\n_Additional Control Arrangements_\n\n25. The project will be financing works, goods, consultants’ services, non-consultants’ services,\ncommunity development sub-grants and operational costs.\n\n\n26. For the category of works and to ensure proper quality in execution, the scope of the external\nauditor’s terms of references will be expanded to include qualitative on-site checks of the works done in\ninfrastructure under Component 2 in the zone of Balbala. The auditor will provide a special purpose report\non the progress and quality of the works done. The special purpose audit report will be submitted with the\naudit report on the financial statements.\n\n\n27. For the community development sub-grants, the project will be providing small grants to community\nassociations. The following control arrangements will be applied under this category:\n\n\n   - ARULOS will prepare a specific small grants", "output": {"entities": {"named_data": [], "descriptive_data": ["yearly inventory of fixed assets"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000015", "page": 57, "chunk": 0, "title": "Djibouti - Integrated Slum Upgrading Project", "pdf_url": "http://documents1.worldbank.org/curated/en/145511542078037348/pdf/project-appraisal-document-pad-P162901-20181017-10232018-636776568298453523.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "yearly inventory of fixed assets", "label": "DESCRIPTIVE_DATA", "score": 0.7324469685554504, "start": 430, "end": 462, "probe_score": 0.0536, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "The World Bank\n\n\nPreparation of city-specific housing strategies\nand action plans.\n\n\nNew Sewer connections constructed under the\nproject\n\n\n\n\n\nReport No: ISR15848\n\n\n\n<u>30-Jun-2016</u>\n\n\n\n\n\n\n\n\n\n<u>30-Jun-2016</u>\n\n\n\n\n|Col1|Number|Value|0.00|0.00|\n|---|---|---|---|---|\n||Number|Date|25-Oct-2010|30-Jun-2014|\n||Number|Comments||To be dropped.|\n||Number|Value|0.00|0.00|\n||Number|Date|25-Oct-2010|30-Jun-2014|\n||Number|Comments||Sewerage works in Kayole<br>Soweto commenced in Feb/<br>March 2014 and expected to<br>be completed in 18 months|\n\n\n\n**<u>Data on Financial Performance (as of 22-Aug-2014)</u>**\n\n|nt(s) Key Dates|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|Ln/Cr/Tf|Status|Approval Date|Signing Date|Effectiveness Date|Original Closing Date|\n|IDA-48730|Effective|24-Mar-2011|23-May-2011|30-Jun-2011|30-Jun-2016|\n\n\n|Millions)|Col2|Col3|Col4|Col5|Col6|Col7|Col8|\n|---|---|---|---|---|---|---|---|\n|", "output": {"entities": {"named_data": ["Data on Financial Performance"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011279", "page": 4, "chunk": 0, "title": "Kenya - Kenya Informal Settlements Improvement Project (KISIP) : P113542 - Implementation Status Results Report : Sequence 07", "pdf_url": "https://documents.worldbank.org/curated/en/324791468278707402/pdf/ISR-Disclosable-P113542-11-11-2014-1415751710504.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "Data on Financial Performance", "label": "NAMED_DATA", "score": 0.678961455821991, "start": 547, "end": 576, "probe_score": 0.4297, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " assure adherence to policies and procedures; (iii) safeguard, manage and control the assets of the\nproject; (iv) ensure completeness and accuracy of the financial transaction/information; (v) ensure proper\nsegregation of FM-related functions; (vi) ensure proper flow of funds; and (vii) ensure adequacy and accuracy and\nrecording of FM data. The details of these procedures will be documented in the Project FM Manual to be prepared.\nThe Internal Audit Chamber will assign a staff to carry out internal audit reviews on the project on a regular basis.\nThe reports of the internal audit will be shared during supervision missions. The project management will ensure\nthat audit findings are timely resolved.\n\n61. **Disbursement Arrangement:** The following disbursement methods may be used under the project:\nreimbursement, advance, direct payment, and special commitment as will be specified in the Disbursement Letter\nand in accordance with the World Bank Disbursement Guidelines for Projects, dated February 1, 2017.\nDisbursements will be transactions-based whereby withdrawal applications will be supported with Statement of\nExpenditures (SOE). Documentation will be retained at the project for review by World Bank staff and external\nauditors. The Disbursement Letter will provide details of the disbursement methods, required documentation,\ndesignated account (DA) ceiling, and minimum application size. No withdrawal shall be made for payments made\nprior to the Signature Date of the Grant Agreement, except that withdrawals up to an aggregate amount not to\nexceed US$2,315,000 may be made for payments made prior to this date but on or after May 1, 2020, for Eligible\nExpenditures. The Closing Date is February 28, 2021. A period of four months (grace period) after the closing date\nwill be allowed to complete processing of disbursement for eligible expenditures incurred up to and until the closing\ndate of the grant.\n\n62. **Banking Arrangements** :", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["FM data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000024", "page": 25, "chunk": 1, "title": "Sudan - Basic Education Emergency Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/208261588781212409/pdf/Sudan-Basic-Education-Emergency-Support-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "FM data", "label": "VAGUE_DATA", "score": 0.5702047348022461, "start": 334, "end": 341, "probe_score": 0.0378, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 2005. Passenger traffic stopped in\n2007.\n\n\nOCBN also needs to enhance its productivity, which lags most railways in West Africa. At 40,000\ntraffic units per employee, OCBN’s labor productivity is comparable with NRC’s but behind the labor\nproductivity of SITARAIL and GRC, with 481,000 and 84,000 traffic units per employee, respectively.\nOn average, OCBN locomotives transported 3 million traffic units, the lowest figure of concessions in the\nregion. Similarly, wagon productivity, at 74 thousand net ton-km per wagon, was just a fraction of the\nfigures for SITARAIL, GRC and TRANSRAIL. Only carriage productivity, at 900,000 km per carriage,\nwas comparatively high (table 6).\n\n\nOCBN’s freight tariffs are the highest in the region, with an average of $ 5.8 cents/ton-km. Only\nSITARAIL has freight tariffs comparable with OCBN’s. However, the passenger tariffs, at $2\ncents/passenger-km, were the lowest—until passenger traffic was halted in 2007.\n\n\n17", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004867", "page": 22, "chunk": 1, "title": "wps5689", "pdf_url": "https://local/prwp/wps5689.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "train", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "the issuance of work permits for refugees. Specific agreed upon measures will be detailed in the Operations\nManual. To achieve DLI#1 prior result, 20,000 work permits are to be issued between April 8 and October\n31, 2016 to Syrian refugees.\n\n\n**Table 1.2. DLI#1: The Number of Work Permits Issued to Syrian Refugees**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n8. _Suggested steps to Be Taken to Achieve the Results_ . Over the medium term, a significant number\nof new jobs are expected to be created for Jordanians and Syrian refugees through investment associated\nwith improvements in access to the EU market and in the business climate. More immediately, the goal of\n130,000 job opportunities can be reached by legalizing work for Syrian refugees and by increasing the\nincentives for employers to hire Jordanians and Syrian refugees.\n\n\n9. Other measures should contribute to reaching the target of 130,000 work permits:\n\n\n(a) Extend the period of free work permits and relaxed inspections for the first two years if\n\nimplementation (target date: September 2016)\n\n\n(b) Disseminate information regarding eligibility, administrative process, and service standards\n\nfor obtaining the Ministry of Interior ID cards, work permits, and (work-related) camp leave\npermits (target date: biannually, starting September 2016)\n\n\n**DLI #2: Annual public disclosure by “Better Work Jordan” of a report on factory-level compliance**\n**with a list of at least 29 social and environmental-related items**\n\n\n_Context_\n\n\n10. Lessons learned based on an evaluation of five SEZs conducted by USAID and recent compliance\nsynthesis reports prepared by Better Work Jordan have provided a sound basis of understanding of the risks\nand opportunities for actions that strengthen labor standards. Compliance with ILO and Jordanian labor and\nenvironmental standards varies across sectors, companies, and SEZs.\n\n\n11. Transparent reporting will be achieved through the publication of factory-level compliance\ninformation on selected issues assessed by", "output": {"entities": {"named_data": [], "descriptive_data": ["evaluation of five SEZs"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000045", "page": 34, "chunk": 0, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "evaluation of five SEZs", "label": "DESCRIPTIVE_DATA", "score": 0.7726700305938721, "start": 1522, "end": 1545, "probe_score": 0.2734, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:021057", "page": 19, "chunk": 1, "title": "Kenya - Second Education Project", "pdf_url": "https://documents.worldbank.org/curated/en/980201468285578528/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "train", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7292463183403015, "start": 272, "end": 283, "probe_score": 0.8771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "- In **Chad**, following a general effort to increase access to rehabilitation services for survivors living in\nremote areas, ICRC conducted an information campaign to raise awareness about accessing services,\ngiving priority to those in most need, especially women and children.\n\n  - In **Iraq’s Kurdistan region**, healthcare facilities were overwhelmed by the number of refugees in need\nentering from Syria during 2014, especially when combined with the increase in internal\ndisplacement. UNICEF and UNHCR monitored a border crossing between Syria and Iraq to identify\nfamilies with vulnerable or disabled children for referral to specific services.\n\n  - In **Somalia**, the Institute for Education for Disabled People provided inclusive education opportunities\nfor children with disabilities, but less than 1% of children with disabilities attend school of any kind.\n\n  - In **Afghanistan** a government-run inclusive education program has been operating since 2008, which\nhas increased the enrolment of children with disabilities. Inclusive education training for teachers,\nchildren with disabilities and their parents support attendance, and an inclusive Child Friendly\nEducation Coordination Working Group now discusses activities, challenges, and the way ahead. <sup>241</sup> [^241: Landmine and Cluster Munition Monitor (2015) The Impact of Mines/ERW on Children, November 2015; M Seedat, A v Niekerk, A\nSukhai (2013). University of South Africa Institute for Social and Health Sciences and MRC-UNISA: Safety and Peace Promotion Research\nUnit. The Eritrean National Injury Prevention and Safety Promotion Response: Strengths, Gaps and Recommendations. Draft November\n19th 2013]\n\n##### First Aid\n\nFirst aid is help that is immediately given to a sick or injured person until full medical treatment is available.\nUsing appropriate techniques to take immediate action, while waiting for professional help can considerably\nreduce deaths and injuries and the impact of disasters. It is a vital step to reducing serious injuries and\nimproving the chances of survival. For those living in conflict or disaster affected areas, not only is", "output": {"entities": {"named_data": ["Landmine and Cluster Munition Monitor"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000475", "page": 64, "chunk": 0, "title": "Child Protection in Humanitarian Action Review: Dangers and Injuries", "pdf_url": "https://reliefweb.int/attachments/4436d98a-06f0-3568-abdf-1b58c50242ca/DI__full_FINAL_4916.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Landmine and Cluster Munition Monitor", "label": "NAMED_DATA", "score": 0.6736590266227722, "start": 1292, "end": 1329, "probe_score": 0.5498, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_Recommendation: Livelihoods Trainings_\n\n\nThere are several avenues to pursue when taking steps to help livelihoods trainings lead more directly\nto refugee employment. One way to make livelihoods trainings more effective is for organisations to\noffer trainings based on a fully investigated market demand (expanded on below). This coincides with\nReHoPE’s focus on fostering local economic development as opposed to solely supporting\npopulations such as refugees. Instead of one-off, limited scale activities to specific households and\ngroups, ReHoPE will strive to stimulate local development through an area-based approach. Such\nwork is important, and, when combined with market research, can lead to the creation of targeted\nbusiness development services in particular regions and sectors.\n\n\nLivelihoods trainings should also be concretely ‘linked’ to job opportunities. This could include shortterm ‘internships’ such as those organised at local salons by the JRS hairdressing trainer, or\nagreements with business owners open to expanding their businesses through hiring refugees. Given\nthe prevalence of xenophobia, as well as practical barriers such as language, contacting successful\nrefugee business owners as well as local Ugandans to further explore this possibility would be\nprudent.\n\n\nCorresponding to this, refugees should be followed after trainings in order to elucidate their\n(un)employment experiences and the value that trainings offer. Almost no comprehensive data in this\narea exists, which greatly constrains the ability of organisations to prove ‘impact’ as well as make\nchanges to training programmes or foci. Similarly, without this data, possibilities to connect skilled\nrefugees to expand or create businesses are reduced.\n\n\n_Access to Markets_\n\n\nEach organisation interviewed had conducted needs assessments of refugees that reflected refugees’\ndesire for skills training and micro-finance loans. These findings led to the specific livelihoods training\nand small-scale loan programmes detailed above. However, it is clear that the trainings refugees\nadvocated do not always reflect a market demand. Indeed, neither the Government of Uganda", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001074", "page": 20, "chunk": 0, "title": "New issues in Refugee Research - Research Paper No. 277 - Refugees asked to fish for themselves: The Role of Livelihoods Trainings for Kampala’s Urban Refugees", "pdf_url": "https://reliefweb.int/attachments/a23e063d-0c7b-3098-ab0f-bf456a00320f/56bd9ed89.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " an individual-level panel data set of exposure to violent conflict events and labor allocation.\n\n\nSecond, we discuss some descriptive statistics which characterize our study sample. Third, we specify our\n\n\ncore identification strategy and discuss the interpretation of our preferred estimates. Finally, we discuss\n\n\nthe potential consequences of sample attrition and discuss how we address these concerns.\n\n\n**3.1** **Data**\n\n\nWe combine two detailed panel datasets. The first set of data is from the Nigeria General Household\n\n\nSurvey (GHS), which is a product of the Nigeria Bureau of Statistics and the World Bank’s Living Stan\n\ndard Measurement Study (LSMS). <sup>23</sup> The GHS was conducted over four rounds in 2010–2011, 2012–2013,\n\n\n2015–2016, and 2018–2019, and each survey round includes two data points for each household: one\n\n\nin the post-planting (rainy season) period and one in the post-harvest (dry season) period, regardless\n\n\nof whether the household engages in agricultural activities. Data collection in the post-planting period\n\n\ngenerally occurs in the later fall months, while fieldwork in the post-harvest season occurs within the first\n\n\nfew months of the next year. Figure 2 illustrates the timing of GHS survey rounds and shows how these\n\n\ndata collection periods correspond with the trend in herder-related violence in Nigeria.\n\n\nThe GHS is designed to include a nationally (and zonally) representative set of enumeration areas,\n\n\n23These data (and all documentation) were accessed via the World Bank’s microdata catalog. Data were downloaded on\nNovember 8, 2019.\n\n\n8", "output": {"entities": {"named_data": ["Nigeria General Household\n\n\nSurvey", "Living Stan\n\ndard Measurement Study"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000572", "page": 10, "chunk": 1, "title": "idu0087febc70d8df04ff50a05a0a34a221591c0", "pdf_url": "https://local/prwp/idu0087febc70d8df04ff50a05a0a34a221591c0.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Nigeria General Household\n\n\nSurvey", "label": "NAMED_DATA", "score": 0.9185903072357178, "start": 502, "end": 536, "probe_score": 0.9889, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Living Stan\n\ndard Measurement Study", "label": "NAMED_DATA", "score": 0.8313765525817871, "start": 620, "end": 655, "probe_score": 0.3229, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Integrated Information\nSystem that includes M&E\nbased on a suitable software\ncustomized to suit needs o f\nGLIA as a body corporate\nand installed and test run\nwith dummy data. GLIA\nSecretariat i s responsible for\nthe task.\n\n\n1-2 days Financial\nMonitoring Reports training\nfor the FMA and core\nfiduciary professional staff\nundertaken by IDA\n\n\nInternal Auditor to be\nappointed. Action by GLIA\nsecretariat\n\n\nTOR for External Auditor\nacceptable to IDA to be\nfinalized. Action by GLIA\nSecretariat\n\n\n\ncompetent and\nqualified experienced\nStaff to manage the\nsystem to be agreed\nand core professional\nfiduciary staff hired\n(Phase 11).\n\n**_0_** Comprehensive\ncontract o f\nengagement with\nFMA formally\nsigned.\n\n\nConsultant TOR for the task\nagreed and assignment to be\nfully undertaken during\nPhase I (PPF financed). Core\nfiduciary staff hired and in\nplace to supervise and\noversee the consultant\n\n\nTask team leader to mobilize\nIDA staff as appropriate for\ndelivery o f the training\n\n\nTOR to be agreed and\nappointment concluded in\nconsultation with IDA\n\n\nGLIA Secretariat to prepare\nthe TOR during the PPF\nphase while competitive\n\nselection process following\nIDA guidelines for selection\n\n- f consultants to be pursued\nsoon after effectiveness\n\n\n51\n\n\n\n**_0_** FMAcontract\nconcluded and '\nformally signed not\nlater than January 3 1,\n200\n\n\nAssignment to be completed\nby Effectiveness date slated\nfor April 01,2005\n\n\nSeminar to be delivered not\nlater than March 15, 2005 or\nas soon as the FMA and core\nfiduciary staff are in place\nand ready\n\n\nNot later than April 30,2005\n\n\nN o t later than Effectiveness\n\ndate slated for April 0 1, 2005", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["dummy data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000021", "page": 54, "chunk": 0, "title": "Africa Region - Great Lakes Initiative on HIV/AIDS (GLIA) Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/188651468741666540/pdf/30267.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "dummy data", "label": "VAGUE_DATA", "score": 0.5938060879707336, "start": 163, "end": 173, "probe_score": 0.2479, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "project. Major funding requirements<br>(USD 30 per beneficiary per month) need<br>to be met in order to keep delivering this<br>benefit for two additional years.|||||||\n|1. Weak capacity of the implementing<br>agencies in monitoring and evaluation.<br>2. Sustainability of the e-card food<br>voucher component is a major risk in this<br>project. Major funding requirements<br>(USD 30 per beneficiary per month) need<br>to be met in order to keep delivering this<br>benefit for two additional years.|The Bank and the MOSA NPTP team will continue the dialogue with donors in order to secure the funding<br>throughout the lifetime of the project for the e-card food voucher component. Moreover, the e-card food<br>voucher card will be identified as temporary to all beneficiaries.|The Bank and the MOSA NPTP team will continue the dialogue with donors in order to secure the funding<br>throughout the lifetime of the project for the e-card food voucher component. Moreover, the e-card food<br>voucher card will be identified as temporary to all beneficiaries.|The Bank and the MOSA NPTP team will continue the dialogue with donors in order to secure the funding<br>throughout the lifetime of the project for the e-card food voucher component. Moreover, the e-card food<br>voucher card will be identified as temporary to all beneficiaries.|The Bank and the MOSA NPTP team will continue the dialogue with donors in order to secure the funding<br>throughout the lifetime of the project for the e-card food voucher component. Moreover, the e-card food<br>voucher card will be identified as temporary to all beneficiaries.|The Bank and the MOSA NPTP", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000139", "page": 58, "chunk": 4, "title": "Lebanon - Emergency National Poverty Targeting Program Project", "pdf_url": "http://documents1.worldbank.org/curated/en/810511467987899324/pdf/PAD1030-ENGLISH-P149242-PUBLIC-FINAL-LEB-ENPTP-English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "- **_The procurement is open to eligible firms from any country;_**\n\n\n  - **_The request for bids/Proposal documents shall require that_**\n\n\n**_bidders/proposers submitting Bids/Proposal present a signed_**\n\n\n**_acceptance at the time of bidding, to be incorporated in any_**\n\n\n**_resulting contracts, confirming application of and compliance_**\n\n\n**_with the Bank’s Anti-Corruption Guidelines, including without_**\n\n\n**_limitation the bank’s right to sanction and the Bank’s inspection_**\n\n\n**_and audit right;_**\n\n\n  - **_Contracts with an appropriate allocation of responsibilities, risks_**\n\n\n**_and liabilities;_**\n\n\n  - **_Application of Standstill period and Publication of contract award_**\n\n\n**_information;_**\n\n\n  - **_Maintenance of records of the procurement process; and_**\n\n\n  - **_The Bank has the right to review procurement documentation_**\n\n\n**_and activities._**\n\n\nWhen other national procurement arrangements other than national open\ncompetitive procurement arrangements are applied by the Borrower, such\narrangements shall be subject to paragraph 5.5 of the Procurement\nRegulations.\n\n\n**_Leased Assets as specified under paragraph 5.10_** of the Procurement\nRegulations: Leasing may be used for those contracts identified in the\nProcurement Plan tables. **_“Not Applicable”_**\n\n\n**_Procurement of Second-Hand Goods_** **_as specified under paragraph_**\n**_5.11_** of the Procurement Regulations – is allowed for those contracts identified\nin the Procurement Plan tables _“_ **_Not Applicable”_**\n\n\n**_Domestic preference as specified under paragraph 5.51_*", "output": {"entities": {"named_data": [], "descriptive_data": ["Procurement Plan tables"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000108", "page": 1, "chunk": 0, "title": "Ethiopia - EASTERN AND SOUTHERN AFRICA- P169943- Urban Productive Safety Net and Jobs Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099010924044011392/pdf/P1699431339b5d02c1a63119456cc286be3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Procurement Plan tables", "label": "DESCRIPTIVE_DATA", "score": 0.5487840175628662, "start": 1250, "end": 1273, "probe_score": 0.0031, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|GEORGIA|Col2|\n|---|---|\n|**_General context on_**<br>**_Housing Solutions and_**<br>**_Compensation for_**<br>**_Destroyed/Damaged_**<br>**_Housing  for IDPs in the_**<br>**_country_**|The total number of registered IDPs is 259,247 or 86,283 families (according to MRA statistics as of 17.09.2014, latest available on the official website). IDPs represent about<br>6% of Georgia’s population, giving it one of the world’s highest incidences of internal displacement relative to its overall population. People lost their family homes and were<br>forcibly displaced as a result of wars in 1990s (233,000 persons) and 2008 (initially - 192,000 persons, most of whom were able to return but over 26,000 are still displaced).<br>Thus, IDPs in Georgia are always referred to as representing 2 separate case loads. 44% of IDPs are living in Tbilisi and about 26.4 % - in Samegrelo-Zemo Svaneti region,<br>neighboring to AAR. In total 75% of IDPs live in urban areas. The issue of housing is particularly prominent for old case load IDPs, many of whom still reside in collective centers.<br>Return has largely not been possible for IDPs displaced to undisputed areas of Georgia.|\n|**_Restitution mechanisms_**<br>|1. Law of Georgia on Internally Displaced Persons – Persecuted from the Occupied Territories of Georgia<br>2. Law of Georgia on Property Restitution and Compensation on the Territory of Georgia for the Victims", "output": {"entities": {"named_data": ["MRA statistics"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000947", "page": 11, "chunk": 0, "title": "Foreign Experience of Housing Solutions and Compensation for Destroyed/Damaged Housing for IDPs [EN/UK]", "pdf_url": "https://reliefweb.int/attachments/8d11082d-d7de-3068-8431-b4df649f866b/foreignexperiencehousingforidps-integrated_eng.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "MRA statistics", "label": "NAMED_DATA", "score": 0.9129279255867004, "start": 266, "end": 280, "probe_score": 0.9931, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "24\n\n\n**During negotiations the following assurances were received:**\n\n\n1. Agreement on triggers for subsequent phases\n2. Agreement on monitoring and impact assessment studies\n3. Agreement on project monitoring indicators\n4. Agreement on finalized bidding documents for the first batch of schools\n\n\n**Actions to be included in Development Credit Agreement:**\n\n\n_Financial_\n\n\n1. Audits and Project Management Reports.\n2. Dated covenant on the selection of the auditor before March 31, 2001.\n\n\n_Management_\n\n\n1. Daied covenant on a baseline survey to establish gender and social class distribution of students\nbefore December 31, 2001.\n2. Provide regular reports on monitoring indicators and prepare a draft midterm report for review\nwith IDA before September 15, 2002.\n\n\n**In addition the following Management conditions are included in supplemental letters attached**\n**to the Developinent Credit Agreement:**\n\n\n1. Triggers from Phase I to Phase II in APL\n2. Triggers from Phase II to Phase III in APL\n\n\nH. READINESS **FOR IMPLEMENTATION**\n\n\nL. a) The engineering design documents for the first year's activities are complete and ready for the\n\nstart of project implementation.\nD b) Not applicable.\n\n3 2. The procurement documents for the first year's activities are complete and ready for the start of\nproject implementation.\n\n\nK/ 3. The Project Implementation Plan has been appraised and found to be realistic and of satisfactory\n\nquality.\n##### D 4. \"he following 7tems are lacking and are discussed under loan conditions (Section G):", "output": {"entities": {"named_data": [], "descriptive_data": ["baseline survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016067", "page": 27, "chunk": 0, "title": "Ethiopia - Fourth Livestock Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/645141468256732906/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "baseline survey", "label": "DESCRIPTIVE_DATA", "score": 0.810932993888855, "start": 529, "end": 544, "probe_score": 0.1317, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "’asile, le taux d’octroi de protection aux ressortissants afghans lors des trois premiers trimestres de 2018 au sein\nde pays qui avaient traité plus de 100 demandes a fortement varié : de 86 % en Italie et 75 % en Grèce à 11 % en Bulgarie et 14 % au\n\n\n34 **VOYAGES DU DÉSESPOIR**", "output": {"entities": {"named_data": ["VOYAGES DU DÉSESPOIR"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000566", "page": 33, "chunk": 15, "title": "Voyages du désespoir : Réfugiés et migrants qui arrivent en Europe et aux frontières, janvier – décembre 2018", "pdf_url": "https://reliefweb.int/attachments/53bfdff3-873a-3a7b-97ea-f3ba9660e634/67714.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "VOYAGES DU DÉSESPOIR", "label": "NAMED_DATA", "score": 0.5632166266441345, "start": 257, "end": 277, "probe_score": 0.6064, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**A Review of Cooking Systems for Humanitarian Settings**\n\n\n**•** Clean Cookstoves Association of Kenya\n\n\n**•** Ghana Alliance for Clean Cookstoves <sup>48</sup>\n\n\n**•** Nepal Alliance for Clean Cookstoves/Nepal Biogas Promotion Association\n\n\n**•** Nigerian Alliance for Clean Cookstoves\n\n\n**•** West Africa Alliance for Clean Cooking (WACCA)\n\n\n**•** Vietnam Biogas Association\n\n\n[48 http://www.cleancookstovesghana.org/.](http://www.cleancookstovesghana.org/)\n\n\n38 | Chatham House", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000760", "page": 38, "chunk": 0, "title": "A Review of Cooking Systems for Humanitarian Settings (May 2016)", "pdf_url": "https://reliefweb.int/attachments/6f0728a6-7fd2-5af4-9b73-b0d87e11fec1/Resource-1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**II. \u0007CASE STUDIES:**\n\n**DISPLACEMENT-RELATED SEXUAL AND GENDER-BASED**\n**VIOLENCE AND SAFE SHELTER CONTEXTS**\n\n\n**Colombia**\n\n\nThe armed conflict that has raged among Colombian security forces, guerrilla groups, paramilitaries,\nand narcotics traffickers for more than forty-five years has cost the lives of an estimated 50,000 to\n200,000 people and has displaced millions of others. According to the UNHCR, out of a population of\n45 million, there are currently more than 3.8 million officially registered internally displaced persons\ninside Colombia, <sup>15</sup> while another 500,000 Colombians are seeking refuge in neighboring countries. <sup>16</sup>\nHowever, these figures are likely only a fraction of the true displaced population due to restrictions on\neligibility to register, a lack of information, and several other barriers to registration. Estimates by local\nNGOs suggest that the number could be as high as 5.4 million. <sup>17</sup> By any measure, this is the largest\ndisplacement crisis in the Western Hemisphere.\nThe main pattern of displacement in Colombia is from rural to urban areas, since the countryside continues to be most affected by conflict-related violence. Data from the National Department of\nPlanning indicate that from 1998 to 2008, 92 percent of the displaced population migrated away from\nrural areas, predominantly from the north and west of the country. <sup>18</sup> Most fled to urban centers, where\nthey reside in informal slums.\nDisplacement and conflict-related sexual violence is widespread in Colombia. Rape and other\nforms of sexual violence are used as tactics of war by all of Colombia’s armed actors. Women who are\nassumed to be allied with one of the warring parties are often targeted by another party as a way to\nsend a", "output": {"entities": {"named_data": [], "descriptive_data": ["Data from the National Department of\nPlanning"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001484", "page": 20, "chunk": 0, "title": "Safe Haven: Sheltering Displaced Persons from Sexual and Gender-Based Violence", "pdf_url": "https://reliefweb.int/attachments/e7014c51-2f67-396e-9a45-90808af5311b/51b6e27b9.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Data from the National Department of\nPlanning", "label": "DESCRIPTIVE_DATA", "score": 0.7498136162757874, "start": 1193, "end": 1238, "probe_score": 0.994, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Sr.<br>No|Contract<br>Description|Estimat<br>ed Cost<br>(US$)|Revi<br>ew<br>by<br>Ban<br>k<br>(Pri<br>or/<br>Post<br>)|Market<br>Approa<br>ch<br>(Open-<br>Nation<br>al/<br>Limited<br>etc.)|Selectio<br>n<br>Method<br>(RFP,<br>RFB,<br>RFQ, DS<br>etc.)|Evaluation<br>Options<br>(Most<br>Advantage<br>ous Bid,<br>BAFO,<br>Rated<br>Criteria<br>etc.)|Procurem<br>ent<br>Process<br>(Single<br>stage-<br>single<br>envelope<br>etc.)|Prequal<br>ificatio<br>n<br>(Yes/<br>No)|Domesti<br>c<br>Prefere<br>nce<br>(Yes/No<br>)|Expect<br>ed date<br>of bid/<br>propos<br>al<br>openin<br>g|Expect<br>ed date<br>of<br>Contra<br>ct<br>Signat<br>ure|\n|---|---|---|---|---|---|---|---|---|---|---|---|\n||Training Centre for<br", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002309", "page": 6, "chunk": 0, "title": "Uganda - EASTERN AND SOUTHERN AFRICA- P176747- Generating Growth Opportunities and Productivity for Women Enterprises Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099050823031036252/pdf/P17674708448ac06b0a1fc0a0bf2cf6011d.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " stand-alone solar, productive uses technologies such as solar water pumps, solar refrigeration, milling\nunits, efficient appliances units, clean cooking, and internal wiring. Lines of credit will be channeled through\nparticipating Commercial Financial Institutions (CFIs). In addition, UECCC would also provide direct financing to\nseveral project beneficiaries to start up the market and provide demonstration impact to build market confidence\nof CFIs. A Project Operations Manual (POM) will detail the eligibility of the entrepreneurs and line of credit terms\nand conditions.\n\n\n29. **Sub-component 2-1: Financial Intermediation through participating Commercial Financial Institutions.**\nUECCC will extend line of credit to participating CFIs including commercial banks, micro finance institutions (MFIs),\nleasing companies, and funds. Private companies will borrow at favorable market terms to finance their working\n\n\nFebruary 5, 2021 Page 11 of 17", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017235", "page": 10, "chunk": 2, "title": "Project Information Document - Uganda Electricity Access Scale-up Project (EASP) - P166685", "pdf_url": "https://documents.worldbank.org/curated/en/722961612536168002/pdf/Project-Information-Document-Uganda-Electricity-Access-Scale-up-Project-EASP-P166685.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nDecent Employment Creation for Vulnerable Lebanese Citizens and Syrian Refugees in Livestock Value Chains\n\n\nmerchandise exports from 1998–2017 (World Bank, 2021). The production of animal products, such\nas cow’s milk, poultry, sheep and goats and eggs, is one of the main activities in rural Lebanon,\nparticularly in the northern areas. In these areas, the poorest in the country, the majority of farmers\ndepend on dairy products as their primary means of subsistence (Abdallah _et al_ ., 2018). The 2016\nproduction survey indicated that the number of cattle heads reached 86 265, of which 62 percent\nwere dairy cows, accounting for 82 percent of the total value of milk production (FAO, 2021).\n5. **In smallholder and family farming households, women play a prominent role in animal production,**\n**but major constraints impede female work in the livestock value chain.** According to an FAO review\n(2021), in homesteads, women take care of poultry (with an average of 10–50 backyard chicken),\nsheep, goats and cattle. They are responsible for all aspects of animal husbandry, especially on farms\nwith less than 3 cows. The tasks include milking, feeding, providing water, fodder collection,\npreparing feed rations, and feed and care for the animals, particularly small ruminants, rabbits and\npoultry. Women also clean stables and poultry houses, as well as ensure egg collection and processing\nof milk into butter, cheese, yogurt, labneh, and other dairy products (in many cases, the processing\nand marketing activities are done through cooperatives). Marketing tasks performed by women\ninclude selling fresh milk, eggs and processed dairy products to people coming to their doorsteps\nfrom within their same villages or nearby villages or to middlemen coming to their doors. Female\ntraining needs in animal production include capacity building in the areas of animal nutrition and feed\nration mix, disease diagnosis and treatment", "output": {"entities": {"named_data": [], "descriptive_data": ["2016\nproduction survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000036", "page": 3, "chunk": 0, "title": "Project Information Document (PID) - Decent Employment Creation for Vulnerable Lebanese Citizens and Syrian Refugees in Livestock Value Chains - P176547", "pdf_url": "http://documents.worldbank.org/curated/en/665221630592327291/pdf/Project-Information-Document-PID-Decent-Employment-Creation-for-Vulnerable-Lebanese-Citizens-and-Syrian-Refugees-in-Livestock-Value-Chains-P176547.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "2016\nproduction survey", "label": "DESCRIPTIVE_DATA", "score": 0.818434476852417, "start": 519, "end": 541, "probe_score": 0.9275, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*<br>**20**<br>**Regional**<br>**Overview**<br>registered Syrian refugees<br>**506,000**<br>**129,210**<br>directly targeted members<br>of impacted communities<br>in 2019<br>**EGYPT**<br>registered Syrian refugees<br>**520,000**<br>**654,692**<br>directly targeted members<br>of impacted communities<br>in 2019<br>**JORDAN**<br>registered Syrian refugees<br>**158,110**<br>**245,810**<br>directly targeted members<br>of impacted communities<br>in 2019<br>**IRAQ**<br>registered Syrian refugees<br>**1,005,000**<br>**914,648**<br>directly targeted members<br>of impacted communities<br>in 2019<br>**LEBANON**<br>registered Syrian refugees<br>**1,800,000**<br>**3,576,369**<br>directly targeted members<br>of impacted communities<br>in 2019<br>**TURKEY**<br>**REGIONAL TOTAL**<br>**5,520,729**<br>registered refugee population<br>as of 31 December 2019<br>**Voluntary Syrian Refugee Returns**<br>**Syrian Refugee Resettlement Targets**<br>**and Submissions**<br>Population in Need<br>Achievements<br>Syrian refugees who have been", "output": {"entities": {"named_data": [], "descriptive_data": ["registered refugee population"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000166", "page": 1, "chunk": 24, "title": "3RP Regional Refugee and Resilience Plan in response to the Syria Crisis | 2019 Annual Report", "pdf_url": "https://reliefweb.int/attachments/0d34cd24-6e01-3f5c-8c00-0f3d92eaea8d/76670.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "registered refugee population", "label": "DESCRIPTIVE_DATA", "score": 0.526326060295105, "start": 795, "end": 824, "probe_score": 0.0649, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "## **Puntos de acción**\n\nde ACNUR en Apartado, Antioquia. Profamilia, 2021.\n\n\n\nopción.\n\n\n\nfortalecer la difusión sobre estos\n\n\n\nservicios para la población que no\ntiene la elegibilidad para ser\nafiliada. Y asi mismo priorizar\nestos departamentos por parte de\nla cooperación para el apoyo con\nservicios de atención primaria.\n\n\n- A futuro es importante que el\nmonitoreo de protección pueda\nposibilitar hacer seguimiento al\nacceso y barreras presentadas\nsegún tipo de servicio o\nnecesidad de salud presentada\npara identificar con mayor\nprecisión los cuellos de botella,\nespecialmente de posibles\nvulneraciones al derecho a la\nsalud como la negación de la\natención.\n\n\n\n**FUENTES DE INFORMACIÓN**\n1.Ministerio de Salud y Protección Social. Cubos SISPRO Base de Datos única de afiliados (BDUA) y Población venezolana elegible afiliación en SAT Corte a Junio 2024\nCantidad de venezolanos por grupo etáreo inscritos en EPTV en Migración Colombia. Informe especial de la situación de salud de la población migrante venezolana a partir de la encuesta de\ncaracterización del EPTV. 2024\n\n\n2. Este análisis se basa en las encuesta de monitoreo de protección en migrantes con vocación de permanencia realizadas por ACNUR cada trimestre con la población que busca sus diferentes\nservicios así como en puntos estratégicos. La encuesta en 2022 y 2023 fue realizada a 5409 y 5865 personas respectivamente en", "output": {"entities": {"named_data": ["Base de Datos única de afiliados"], "descriptive_data": ["encuesta de\ncaracterización del EPTV", "encuesta de monitoreo de protección"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001439", "page": 17, "chunk": 0, "title": "Boletín de aseguramiento y acceso a la atención en salud de población refugiada y migrante venezolana en Colombia Primer semestre 2024", "pdf_url": "https://reliefweb.int/attachments/df387e7d-5660-4050-b451-5f87102c9180/Boletinaseguramiento-I2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Base de Datos única de afiliados", "label": "NAMED_DATA", "score": 0.6501675248146057, "start": 748, "end": 780, "probe_score": 0.8282, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "encuesta de\ncaracterización del EPTV", "label": "DESCRIPTIVE_DATA", "score": 0.7374354004859924, "start": 1032, "end": 1068, "probe_score": 0.8607, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "encuesta de monitoreo de protección", "label": "DESCRIPTIVE_DATA", "score": 0.6727712154388428, "start": 1109, "end": 1144, "probe_score": 0.9277, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "сті осіб, які виконують сімейні обов’язки\n(із 7% до 13%), і пов’язана здебільшого з труднощами знайти роботу, а рівень\nбезробіття зріс із 4% до переміщення до 27% у Польщі після переміщення.\n\n\nОбмежений доступ до можливостей працевлаштування, які достатньо\nвідповідали б кваліфікаціям і сподіванням, а також мовні бар’єри були названі\nнайпоширенішими перешкодами в пошуку роботи безробітними незалежно від\nїхнього рівня освіти. Що стосується ризиків захисту, слід ретельніше\nконтролювати перепрацювання з низькою заробітною платою, а іноді й у\nневідповідних умовах.\n\n\nВ опитуванні біженців з України в ЄС, проведеному FRA (Агентством\nЄвропейського Союзу з фундаментальних прав людини), 16% респондентів\nзазначили, ", "output": {"entities": {"named_data": [], "descriptive_data": ["опитуванні біженців"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000349", "page": 16, "chunk": 1, "title": "Regional Refugee Response for the Ukraine Situation: Poland - Joint Protection Analysis (October 2023) [EN/PL/UK]", "pdf_url": "https://reliefweb.int/attachments/2c4b2a73-599c-4d47-80fb-4d2213f5ac6b/Poland%20October%202023%20-%20Joint%20Protection%20Analysis%20Report_UA.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "опитуванні біженців", "label": "DESCRIPTIVE_DATA", "score": 0.6189923882484436, "start": 570, "end": 589, "probe_score": 0.9306, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012356", "page": 19, "chunk": 1, "title": "Uganda - Road Development Program Project : environmental impact assessment (Vol. 3 of 3)", "pdf_url": "https://documents.worldbank.org/curated/en/396981468779155592/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7292463183403015, "start": 272, "end": 283, "probe_score": 0.8771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ",000 houses were destroyed dunng the war and only 10,000 have been\nrebuilt so far. Government is particularly concerned with the shelter needs of returnees, IDPs <sup>and</sup>\n\n\n\ngovernment employees such as health workers and teachers. The state of shelter in many <sup>areas is one</sup> <sup>of</sup>\nthe factors constraining the return of government employees and the revitalization of district and local\neconomic activity. The agricultural sector is particularly important because it currently <sup>employs 75%</sup> <sup>of</sup>\nthe country's labor force. The 2000 Baseline Service Delivery Survey reported that between <sup>65%</sup> <sup>and</sup>\n85% of the population do not have access to safe drinking water and sanitation facilities. Recent\nestimates in the most neglected communities of the \"newly accessible areas\", such as Bombali, <sup>suggest</sup>\nthat access to potable water and adequate sanitation are as low as 5% and 3%, respectively.\n\n\n\nWidespread human rights abuses during the civil war included the forced recruitment of children\nas combatants, porters and sex slaves. In addition, tens of thousands of people continue to suffer <sup>from</sup>\nthe traumatic effects of amputation and other injuries, sexual violence, loss of parents, and the general\nstress of living through a civil war. This has greatly increased the need for a kind of <sup>social service</sup>\nsupport that was not as widely needed before the war, integrating traditional health services <sup>with</sup>\npsycho-social care, counselling, foster homes and disability programs. The challenges ahead <sup>will include</sup>\n\nthe provision of community-", "output": {"entities": {"named_data": ["2000 Baseline Service Delivery Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009504", "page": 9, "chunk": 1, "title": "Uganda - Second Poverty Reduction Support Credit Project (PRSC2)", "pdf_url": "https://documents.worldbank.org/curated/en/205881468765563829/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "2000 Baseline Service Delivery Survey", "label": "NAMED_DATA", "score": 0.8882462978363037, "start": 568, "end": 605, "probe_score": 0.97, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 0.1 percentage points.\n\n\n\nWe perform distributional analysis within CPAT for five South Asian economies (Bangladesh, India,\nNepal, Pakistan, and Sri Lanka) using data on household budget shares obtained from the following\nHousehold Budget Surveys (HBSs): i) 2016-2017 Household Income and Expenditure Survey (HIES)\n\n\n[12 See, for example: https://www.imf.org/en/Topics/climate-change/energy-subsidies.](https://www.imf.org/en/Topics/climate-change/energy-subsidies)\n13 [Detailed documentation on the CPAT methodology is available here: https://cpmodel.github.io/cpat_public/](https://cpmodel.github.io/cpat_public/)\n\n14 Though parameterization is broadly consistent with the modeling literature, which (to varying degrees) incorporates\nthese factors. See further discussion of these issues in IMF (2019b), Parry, Mylonas, and Vernon (2021) as well as Black\net al. (forthcoming).\n\n\n10", "output": {"entities": {"named_data": ["2016-2017 Household Income and Expenditure Survey"], "descriptive_data": ["data on household budget shares", "Household Budget Surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000757", "page": 12, "chunk": 2, "title": "idu0502ccf8e0286b046b90920302a451b6e0b6e", "pdf_url": "https://local/prwp/idu0502ccf8e0286b046b90920302a451b6e0b6e.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "data on household budget shares", "label": "DESCRIPTIVE_DATA", "score": 0.8270265460014343, "start": 163, "end": 194, "probe_score": 0.1532, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Household Budget Surveys", "label": "DESCRIPTIVE_DATA", "score": 0.7788713574409485, "start": 223, "end": 247, "probe_score": 0.6613, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2016-2017 Household Income and Expenditure Survey", "label": "NAMED_DATA", "score": 0.7055688500404358, "start": 259, "end": 308, "probe_score": 0.9314, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", and greater alignment with international trade standards.\n**51.** **Finally, a notable behavioral shift was observed in the sourcing of QA services.** By project close, outsourcing of\nconformity assessment services declined by 28% compared to 2021 due to new equipment utilization (source: GoE’s ICR),\nindicating that domestic institutions like ECAE were increasingly capable of meeting industry needs. While sector-specific\ndata is unavailable, it is likely that the decline in outsourcing was even greater in the targeted value chains, given the\nproject's concentrated investments and support. This points to improved trust and capacity in Ethiopia's NQI system.\n**52.** **As a proxy for counterfactual analysis, the evolution of two demand-driven indicators—volume of QA services**\n**delivered and number of enterprises using NQI services in targeted sectors—was assessed for the first vs the second**\n**half of the project** . These indicators are based on voluntary firm uptake and not solely attributable to project-funded\noutputs, making them useful proxies for estimating the project's added value. At baseline in July 2017, QA service volume\nstood at 1,959, with modest growth through July 2021, averaging just 650 services annually and totaling around 4,600.\nEnterprise uptake followed a similar trend, rising from 67 to about 400 firms by mid-2021, or roughly 85 new users per\nyear. This period coincided with early implementation and low disbursement (<40%). In contrast, from late 2021 through\nproject close in 2025, QA services surged to an average of 1,785 per year, reaching 11,742 total, while enterprise use\njumped to 1,855, averaging 350 firms annually. This inflection aligns with the scaling-up of project support and suggests\nthat NQIDP helped build institutional readiness and private sector confidence in quality infrastructure. Without these\ninterventions, demand for QA services", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["sector-specific\ndata"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001487", "page": 15, "chunk": 2, "title": "Ethiopia - National Quality Infrastructure Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/099032526102032966/pdf/BOSIB-eb610218-fdec-49ed-b9c7-c1539f37b0a1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "sector-specific\ndata", "label": "VAGUE_DATA", "score": 0.6267600655555725, "start": 411, "end": 431, "probe_score": 0.6117, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "output": {"entities": {"named_data": [], "descriptive_data": ["household expenditure survey data", "data from the Household Survey"], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015246", "page": 38, "chunk": 1, "title": "Ethiopia - Drought Recovery Project", "pdf_url": "https://documents.worldbank.org/curated/en/590541468243870354/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "household expenditure survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8699104189872742, "start": 565, "end": 598, "probe_score": 0.7323, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.5808603167533875, "start": 870, "end": 881, "probe_score": 0.1461, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from the Household Survey", "label": "DESCRIPTIVE_DATA", "score": 0.5346028804779053, "start": 1978, "end": 2008, "probe_score": 0.1121, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "##### **2 Data**\n\nOur sample covers 6 low- and middle-income countries in Africa and Eastern Europe:\n\n\nKenya, Madagascar, Nigeria, Rwanda, Tanzania and Georgia. In order to apply the\n\n\nmethodology developed by Atkin and Donaldson (2015), we require two sets of data for\n\n\neach country. First, we need price data on narrowly-defined product varieties, with ob\n\nservations spanning multiple locations within each country at a monthly frequency over\n\n\nseveral years. Second, we need the locations in which product varieties were produced or\n\n\nfrom which they were imported. The latter allows for the identification of trading pairs\n\n\nand the corresponding direction of trade from origin to destination locations. In this sec\n\ntion, we briefly describe how we construct these data. Appendix A includes additional\n\n\ndetails about the data preparation process.\n\n\n**2.1** **Price** **data**\n\n\nOur price data come from CPI microdata provided to us by NSOs in each country in\n\n\nour sample. NSOs collect price data from a predefined list of product varieties (including\n\n\ngoods and services), designed to capture the consumption basket of a typical household, at\n\n\nspecified locations. Apart from the monthly price quote, the information provided to us by\n\n\nNSOs includes a product description, in some cases including the brand and presentation\n\n\n(e.g., “Coca-Cola, canned, 500ml” or “Body lotion, Nivea, 200ml”), the name of the\n\n\nlocation where the price was collected, and, occasionally, the name of a producer or the\n\n\ncountry from where the product was imported.\n\n\nWe restrict the choice of products to narrowly defined varieties, i.e., those for which\n\n\nwe can observe a detailed product description and a brand. For most countries in our\n\n\nsample, prices are at the town or city level, with the exception of Rwanda, where prices\n\n\nare collected at the (more", "output": {"entities": {"named_data": ["CPI microdata"], "descriptive_data": [], "vague_data": ["price data", "price data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001350", "page": 5, "chunk": 0, "title": "idu167abbddb15f9714c941870b1a84d441e8e50", "pdf_url": "https://local/prwp/idu167abbddb15f9714c941870b1a84d441e8e50.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "price data", "label": "VAGUE_DATA", "score": 0.7147720456123352, "start": 301, "end": 311, "probe_score": 0.5362, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "price data", "label": "VAGUE_DATA", "score": 0.5825955271720886, "start": 890, "end": 900, "probe_score": 0.7164, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "CPI microdata", "label": "NAMED_DATA", "score": 0.8452364802360535, "start": 911, "end": 924, "probe_score": 0.7689, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2 REGULATORY ENVIRONMENT AND GOVERNANCE\n\n\nThe Refugee Act 2012 also mandated CRA to coordinate inter-ministerial and non-governmental activities\nand programmes relating to refugees. CRA’s limited institutional and organizational capacity is an obstacle\nto it fully assuming its coordination roles and responsibilities at inter-ministerial national and subnational\nlevels. CRA’s reporting expertise also requires further enhancement and support.\n\n\nRefugees have so far not been included in the national population census, although refugees and asylumseekers have always been registered by the CRA. UNHCR manages and updates the refugee database on\na regular basis and uses such figures for planning and advocacy for inclusion in national planning. While\nUNHCR supports the provision of basic health services, the mandatory national services such as tuberculosis\ntreatment, HIV programming, vaccination antigens, are meant to include refugees in the national planning\nprocess for quantifying medicines and commodities. The inclusion of refugee data in the national statistics\nplans would improve the quality of the health service delivery at primary and referral levels available to\nthem. Similarly, refugee data inclusion would be impactful in influencing the national sector development\nplans and related budgets and in facilitating the implementation of Government pledges. Refugee education\nneeds and data have been captured in the national Education Plan (ESO) by the Ministry of Education but\nhave not been translated into budgetary provisions.\n\n\n**2.4** **Access to civil registration and documentation**\n\n\nChapter V of the Refugee Act provides that refugees are issued with an identity document and shall be\nentitled to a travel document. Chapter IV states that asylum-seekers, further to their asylum application, shall\nbe issued with a temporary document valid for not less than 90 days. In effect, the asylum-seeker certificate\nis valid for one year. The Eligibility Regulations 2017 stipulate that CRA shall issue to every person granted\nrefugee status, and every member of his or her family aged sixteen and above, an individual identification\ndocument in the form of a refugee identity card. This card is valid for", "output": {"entities": {"named_data": [], "descriptive_data": ["national population census", "refugee database"], "vague_data": ["refugee data", "refugee data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000572", "page": 7, "chunk": 0, "title": "South Sudan: Refugee Policy Review Framework Country Summary as at 31 December 2021", "pdf_url": "https://reliefweb.int/attachments/54b8aca2-8218-4e6a-a493-afcdbdd35766/FNAL%20RPRF%20South%20Sudan%20.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "national population census", "label": "DESCRIPTIVE_DATA", "score": 0.8822579979896545, "start": 493, "end": 519, "probe_score": 0.3206, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "refugee database", "label": "DESCRIPTIVE_DATA", "score": 0.8171594738960266, "start": 627, "end": 643, "probe_score": 0.3753, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "refugee data", "label": "VAGUE_DATA", "score": 0.6549417972564697, "start": 1034, "end": 1046, "probe_score": 0.472, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "refugee data", "label": "VAGUE_DATA", "score": 0.6063302159309387, "start": 1198, "end": 1210, "probe_score": 0.2519, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "decentralized \"partnership\" approach to governance that involves line ministnes, NGOs, CBOs, <sup>and</sup> <sup>civil</sup>\nsociety. NCRRR/NaCSA has been supported by the African Development Bank, UNDP, DflD, and IDA.\nIt has provided assistance for more than 500,000 displaced persons, shelter rehabilitation, vocational\ntraining, trauma healing, and micro-finance programs. It has financed 275 community-based sub-projects\nin the areas of health, education, water and sanitation, agriculture and capacity building. These <sup>tasks</sup>\nhave been carried out with considerable support from the 260 NGOs registered in Sierra Leone, of which\n68 are international. These NGOs have been instrumental in ensuring service delivery to remote <sup>areas</sup>\nwhere public services were absent.\n\n\n**3.** **Sector** **issues** **to be** **addressed** **by the** **project and strategic choices:**\n\n**Poverty in a Post-Conflict** **Environment.** Section 2 above outlines the principal characteristics\nof poverty in Sierra Leone and the condition of the country at the close of the civil war. <sup>Access</sup> <sup>of the</sup>\npoor majority to food, shelter, employment opportunities and social services are among the <sup>principal</sup>\n\n\n\nconstraints to post-conflict reconstruction, economic recovery and poverty reduction. District recovery\nassessments reveal that over 340,000 houses were destroyed dunng the war and only 10,000 have been\nrebuilt so far. Government is particularly concerned with the shelter needs of returnees, IDPs <sup>and</sup>\n\n\n\ngovernment employees such as health workers and", "output": {"entities": {"named_data": [], "descriptive_data": ["District recovery\nassessments"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:021302", "page": 9, "chunk": 0, "title": "Uganda - Road Development Program Project (Phase 1) (RDPP1)", "pdf_url": "https://documents.worldbank.org/curated/en/996931468760805645/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "District recovery\nassessments", "label": "DESCRIPTIVE_DATA", "score": 0.861286461353302, "start": 1323, "end": 1352, "probe_score": 0.8419, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "##### Safe & Sustainable Existences\n\n###### Objective 8: Promoting livelihoods and self-reliance\n\nMany would argue that the key factor in establishing well-being or even just survival for urban\nrefugees is their access to viable livelihoods. Often this debate focuses on whether or not the\nhost government provides refugees with the legal right to work. However, the survey responses\nindicate that access to fi nancial capital is perceived as the most salient factor. UNHCR offi ces\nalso emphasize consideration of the socio-economic conditions in these urban areas—areas with\nextensive and extreme urban poverty may offer only very limited opportunities for refugees even\nif they have a legal right to work. Several respondents note that many refugees from rural agrarian\nregions arrive in these cities without skills relevant for the urban economies, which makes it diffi cult\nfor them to fi nd formal or formal work. Survey responses suggest that access to banking services,\nincluding credit; contextually specifi c training, including language training; refugees’ ability to\nregularize their status and obtain documentation and their links with civil society may be more useful\nthan the legal right to work per se.\n\n\n**Barriers to sustainable livelihoods for urban refugees**\n\n\n**<mark>Graph 12:</mark>** <mark>Most signif cant barriers for urban refugees to sustain livelihoods</mark> i\n\n\nLinguistic\n\n\nSocio-cultural\n\n\nFinancial\n\n\nLegal\n\n\n\nNumber of UNHCR offi ces\n\n\n\n0 5 10 15 20 25\n\n\n\n**Almost all offi ces (23) cite fi nancial barriers as signifi cant in inhibiting refugees in their efforts**\n**to establish sustainable livelihoods.** Two-thirds or more of the offi ces cite legal barriers (19);\nsocio-cultural barriers (17); and linguistic barriers (16). The risk of arrest and detention also deters\nrefugees from livelihood activities in countries such as Thailand, where they have no legal status,", "output": {"entities": {"named_data": [], "descriptive_data": ["survey responses"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000907", "page": 31, "chunk": 0, "title": "The Implementation of UNHCR’s Policy on Refugee Protection and Solutions in Urban Areas - Global Survey – 2012", "pdf_url": "https://reliefweb.int/attachments/85f901a8-f804-3ef5-9421-00ded165230d/UNHCRs%20Policy%20on%20Refugee%20Protection%20and%20Solutions%20in%20Urban%20Areas.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "survey responses", "label": "DESCRIPTIVE_DATA", "score": 0.6357653141021729, "start": 367, "end": 383, "probe_score": 0.9061, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "a plot is a part or whole of a field on which a specific crop or crop mixture is cultivated, or which\n\nis fallow or waiting to be planted” (FAO 2015). However, when designing and implementing an\n\nagricultural survey, practitioners should confirm the tiers and definitions used by the national\n\nstatistical office, as these may not always coincide with the FAO definitions. As suggested above,\n\ntracking parcels may be a more practical option for longitudinal studies, given the changing size\n\nof plots across seasons.\n\n\nRecording agricultural information at the household level inherently aggregates individual\n\nproduction and imposes a linearity assumption across plots for input utilization and asset use. The\n\nmain trade-off in recording agricultural information at the plot level is that farmers must recall\n\ninput allocation at the plot level, which requires more cognitive effort and response time. These\n\nrecall biases may be compounded by proxy response bias, as plot-level self-reporting is time\nconsuming in the field and may be not feasible for all survey responses. Proxy respondents may\n\nhave incomplete information on plots managed by other household members. For farmers who\n\npurchase inputs collectively with their family for multiple plots, it may be difficult to accurately\n\nassess how much fertilizer, seed, or other input was applied to a particular plot. Consistent with\n\ntime use data, it may also be difficult for a farmer to recall individual household labor allocations\n\nto particular plots over an agricultural season or with respect to particular agricultural tasks. While\n\nmore research is needed to understand the measurement implications of the disaggregation of input\n\nand production data to the plot level from the household level, the known analytical advantages of\n\ndoing so – such as analysis of male-managed plots vis-à-vis female-managed plots – outweigh the\n\nunknown risk of aggregation in many surveys, including LSMS-ISA surveys.\n\n\nDue to variation in land tenure status and land use rights, it is also important to account for\n\nseasonality in production on plots and changes in plot management when considering the unit of\n\nanalysis. Depending on the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["time use data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000049", "page": 30, "chunk": 0, "title": "agricultural data collection to minimize measurement error and maximize coverage", "pdf_url": "https://local/prwp/agricultural-data-collection-to-minimize-measurement-error-and-maximize-coverage.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "time use data", "label": "VAGUE_DATA", "score": 0.704076886177063, "start": 1393, "end": 1406, "probe_score": 0.3158, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " The country’s population has been growing by more than 3 percent per annum\nover the last three decades and it was 42.7 million in 2018 <sup>2</sup> . More than 47 percent of the population are\nunder the age of 15 and nearly 80 percent under the age of 30. About 77 percent of the total population\nlive in rural areas and work in the agricultural sector, which accounts for 71 percent of total employment\nand around a quarter of the country’s GDP <sup>3</sup> .\n\n3. **The macroeconomic impact of COVID-19 and Locusts on the Ugandan economy will be significant,**\n**creating both economic disruptions and financing imbalances that will need to be addressed urgently** .\n\n\n[1 https://data.worldbank.org/country/uganda.](https://data.worldbank.org/country/uganda)\n[2 https://data.worldbank.org/country/uganda.](https://data.worldbank.org/country/uganda)\n3 World Bank World Development Indicators (2017).\n\n\nApr 07, 2020 Page 3 of 16", "output": {"entities": {"named_data": ["World Bank World Development Indicators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000001", "page": 2, "chunk": 1, "title": "Project Information Document - Uganda: Roads and Bridges in the Refugee Hosting Districts Project - P171339", "pdf_url": "http://documents.worldbank.org/curated/en/109301595258535610/pdf/Project-Information-Document-Uganda-Roads-and-Bridges-in-the-Refugee-Hosting-Districts-Project-P171339.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "World Bank World Development Indicators", "label": "NAMED_DATA", "score": 0.7097330689430237, "start": 853, "end": 892, "probe_score": 0.9994, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " non-DAC\n\ndonors. Use of country systems is expected to be higher for DAC donors, because of the DAC’s\n\nleading role in donor harmonization initiatives, and peer reviews of members’ aid programs that\n\nnow include assessments of their consistency with Paris Declaration principals and objectives.\n\nThe DAC donors can be divided further, between the “Nordic Plus” group and others.\n\nNordic Plus donors include Denmark, Finland, Norway, Sweden, Ireland, the Netherlands, and\n\nthe United Kingdom. The group’s purpose is to improve complementarities among its members,\n\nthrough division of labor based on comparative advantages (NORAD, 2006; de Renzio, 2005).\n\nBy reducing the number of sectors and countries each donor operates in, transactions costs for\n\nrecipients can be reduced, at the price of reduced visibility for the donors. We take membership\n\nin the Nordic Plus group as a proxy for low “skepticism” of aid effectiveness among the\n\ndomestic constituencies of these bilateral donors. Empirical support for this hypothesis could be\n\ninterpreted as merely indicating that donors committed to certain parts of the Paris Declaration\n\nagenda tend to be committed to other parts of it. At a minimum, however, tests of the Nordic\n\n\n20 The OECD-DAC is itself a multilateral agency, representing most of the OECD’s bilateral donor countries. The\nOECD-DAC is not a donor agency, but conducts peer reviews of its members’ aid programs, maintains aid\ndatabases, and pursues research and advocacy work on improving aid effectiveness.\n21 However, “ownership” is sometimes criticized as a euphemism for developing countries’ adoption of policies\nadvocated by the Bank and other donors (OECD, 2008b).\n\n17", "output": {"entities": {"named_data": [], "descriptive_data": ["aid\ndatabases"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004198", "page": 18, "chunk": 1, "title": "wps5005", "pdf_url": "https://local/prwp/wps5005.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "aid\ndatabases", "label": "DESCRIPTIVE_DATA", "score": 0.7555899620056152, "start": 1441, "end": 1454, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA M&E data - NaCSA maintains lean and\n**community** **sub-projects and** decision-making by NaCSA; efficient organizational\n**NSAP** **partners monitored** structure\n**and evaluated** **in order to**\n**improve** **program**\n**effectiveness.**\n\n\n**3(d)** **Technical** **Assistance** 3d. 1 NaCSA staff indicate - IDA aide-memoires and\n**services** **effectively** **provided** satisfaction with technical project status reports\n**to support program** assistance, including skill\n**implementation** transfer activities\n\n\n**3(e)** NaCSA **management** 3e. 1 Project management - IDA Project Status reports\n**systems** **functioning** costs (NaCSA staff salaries at (including disbursement\n**effectively** **to ensure** all levels as well as operating reports);\n**program success** expenditures) are 13.5% or - NaCSA proposed annual\nless than total budgeted annual work program and budget\nexpenditures;                 - Annual audit reports;\n3e.2 NaCSA staff and                  - GOSL semi-annual PETS\npartners indicate satisfaction reports\nwith the performance of\nNaCSA's management;\n3e.3 NaCSA performance in\n\n\n                                  - 27", "output": {"entities": {"named_data": ["NaCSA M&E data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000104", "page": 31, "chunk": 1, "title": "East Timor - Fundamental School Quality Project", "pdf_url": "http://documents1.worldbank.org/curated/en/597541468309559446/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "NaCSA M&E data", "label": "NAMED_DATA", "score": 0.6971123814582825, "start": 170, "end": 184, "probe_score": 0.0004, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nMauritania Social Safety Net System Project II (P171125)\n\n\nimplementation.\n\n\n72. **Building capacity to implement social protection interventions requires institutional strengthening** .\nThe project aims to support government SP policies and programs. Since the GoM’s technical and financial\ncapacity for the implementation of these policies and programs is still limited, the proposed project will\nprovide institutional and financial support to _Taazour_ and the CSA to increase their technical capacity at the\ncentral and decentralized levels.\n\n\n73. **A sustainable climate shock response strategy is key to maintaining recent poverty reduction gains** .\nThe ability to rapidly scale up cash transfers is essential to effectively prevent negative outcomes on household\nconsumption in the event of a disaster and to protect livelihoods and assets. The ongoing project laid the\ngroundwork for using existing safety net programs, mechanisms, and procedures to provide emergency cash\ntransfers in the event of a shock. The implementation of _Elmaouna_ provided a lot of lessons on how to identify,\nregister, and transfer money to vulnerable households affected by a shock.\n\n\n74. **Existing gender imbalances in Mauritania should be considered when targeting social services,**\n**productive and human capital development activities.** Socio-economic data show that women are\nsignificantly disadvantaged in Mauritania <sup>18</sup> [^18: See annex 3.] . To address this gap, the project delivers cash transfers to the main\nchildren caregivers (mostly women), which potentially provides them with more agency to decide on\nhousehold expenses and alleviate their household’s poverty and more social standing within their households\nand communities, and releases some of the stress linked to poverty. A 2018 evaluation of the _Elmaouna_\nprogram shows that more than 90 percent of the cash transfers managed by women go to expenses for\nimproved meals and children's health and education. Specific local gender gaps in access to health and\neducation, jobs and assets, and voice will inform", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Socio-economic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000045", "page": 29, "chunk": 0, "title": "Mauritania - Second Social Safety Net System Project", "pdf_url": "http://documents1.worldbank.org/curated/en/323551584151262464/pdf/Mauritania-Second-Social-Safety-Net-System-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Socio-economic data", "label": "VAGUE_DATA", "score": 0.7439492344856262, "start": 1351, "end": 1370, "probe_score": 0.9201, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Saint Vincent<br>& Grenadines|27.1|32.3|19.3|19.2|22.9|19.4|1.9|2.3|19.9|0.6|0.8|20.6|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|\n|<br>**Jersey (U.K.)** <br>|18.7|30.4|62.0|15.6|25.8|65.7|1.6|2.0|30.8|1.0|1.4|37.3|\n|**Solomon**<br>**Islands**|25.4|28.3|11.5|19.2|20.9|8.7|2.3|2.7|18.2|1.2|1.4|18.1|\n|<br>**Grenada**|19.8|26.5|33.9|16.9|22.5|33.0|0.7|1.0|38.5|0.2|0.3|41.2|\n|**Maldives** <br>|25.0|25.7|2.8|23.5|24.1|2.5|0.1|0.1|0.0|0.0|0.0|0.0|\n|**Antigua and**<br>**Barbuda**|19.6|25", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001123", "page": 29, "chunk": 0, "title": "idu0ef8bc63a022b304b7c08e7c04aac815d4d98", "pdf_url": "https://local/prwp/idu0ef8bc63a022b304b7c08e7c04aac815d4d98.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda: Investment for Industrial Transformation and Employment (P171607)\n\n\n**Component 4: Implementation Support and Monitoring & Evaluation.** The objective of this component is to assist in\nthe development and implementation of the different facilities, and to provide guidance and support in the setting up and\noperation of the Project Management Unit. M&E activities undertaken as part of this component will focus on developing\nan indicator framework with baseline measurements and annual targets, monitoring the economic impact of program\nactivities through data collection and survey implementation, and evaluating the economic impact of the program through\na structured impact evaluation at the conclusion of the project.\n.\n\n\n\n\n\n**E. Environmental and Social Risk Classification (ESRC) -** Substantial\n\n**Environmental Risk Rating -** Substantial\n\nEnvironmental risk is rated substantial. Environmental impacts are expected under Components 1, 2 and 3. Component\n1 will support existing MSMEs and there is a likelihood that these MSMEs will have pre-existing / ongoing environment,\nhealth and safety (EHS) issues/risks (use of solvents or toxic substances, industrial accidents, etc.). The extent of the risks\nposed by beneficiary MSMEs and small corporates will depend on the sectors in which they operate and on the specific\nnature and scale of their operations, which is yet to be defined during project implementation. Medium and long-term\ninterventions under component 2, particularly those involving enterprises and projects benefiting from liquidity\nenhancement facilities to finance more productive investments might involve activities such as construction of new\nfactories/ facilities and other infrastructure, are likely to have comparatively more significant environmental impacts such\nas increased waste generation, air/noise pollution, health and safety risks for workers and communities, etc. The potential\nenvironmental impacts are expected to be site specific, local, reversible and temporary and can be mitigated through\nappropriate mitigation measures. Similarly, activities under component 3 are likely to have moderate environmental\nimpacts related to operations of the MSME", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000043", "page": 6, "chunk": 0, "title": "Project Information Document - Uganda: Investment for Industrial Transformation and Employment - P171607", "pdf_url": "http://documents.worldbank.org/curated/en/790161604416004965/pdf/Project-Information-Document-Uganda-Investment-for-Industrial-Transformation-and-Employment-P171607.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA M&E data - NaCSA maintains lean and\n**community** **sub-projects and** decision-making by NaCSA; efficient organizational\n**NSAP** **partners monitored** structure\n**and evaluated** **in order to**\n**improve** **program**\n**effectiveness.**\n\n\n**3(d)** **Technical** **Assistance** 3d. 1 NaCSA staff indicate - IDA aide-memoires and\n**services** **effectively** **provided** satisfaction with technical project status reports\n**to support program** assistance, including skill\n**implementation** transfer activities\n\n\n**3(e)** NaCSA **management** 3e. 1 Project management - IDA Project Status reports\n**systems** **functioning** costs (NaCSA staff salaries at (including disbursement\n**effectively** **to ensure** all levels as well as operating reports);\n**program success** expenditures) are 13.5% or - NaCSA proposed annual\nless than total budgeted annual work program and budget\nexpenditures;                 - Annual audit reports;\n3e.2 NaCSA staff and                  - GOSL semi-annual PETS\npartners indicate satisfaction reports\nwith the performance of\nNaCSA's management;\n3e.3 NaCSA performance in\n\n\n                                  - 27", "output": {"entities": {"named_data": ["NaCSA M&E data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010449", "page": 31, "chunk": 1, "title": "Uganda - Capacity and Performance Enhancement Program (CAPEP) Project", "pdf_url": "https://documents.worldbank.org/curated/en/267541468760510994/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "NaCSA M&E data", "label": "NAMED_DATA", "score": 0.6971123814582825, "start": 170, "end": 184, "probe_score": 0.0004, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_Empowerment Case Studies: Uganda PRSC_\n\n\n**V.** **Issues and Lessons**\n\n\n**_Critical Issues_**\n\n\nDespite the efforts taken by the GOU to improve access to health services, the health\nstatus of the Ugandan population continues to be poor. The Demographic Survey\n(HDS) 2000–2001 indicated high infant and maternal mortality rates. An increase in\ncontraceptive prevalence has not abated the fertility rates. As a result, population\ngrowth remains high, as much as 2.5 percent per annum, posing a potential threat to\npoverty reduction efforts. In addition, almost 51 percent of the population lives more\nthan 5 kilometers away from a health facility that provides basic curative and\npreventive services. Most of the facilities remain understaffed due to a shortage of\ntrained health workers, meager salaries, a lack of financial management, and the\nabsence of well-coordinated procurement and support systems. Furthermore, the\nhealth facilities often run out of drugs and supplies, thus creating a negative public\nimage. According to NSDS 2000, only 56 percent of households are satisfied with the\nquality of health services.\n\n\nReducing absenteeism and dropout rates in primary schools remains an important\nissue to be tackled as a part of the education sector reforms. Some of the reasons cited\nfor increased absenteeism at the primary level were poor health (64 percent), inability\nto pay extra school charges (52 percent), and lack of school uniforms (42 percent). <sup>7</sup> [^7: Source: “Summary of Background to the Budget 2001/2002,” _Uganda Poverty Reduction Support Paper,_\n_Progress Report 2002._ URL: http://poverty.worldbank.org/files/Uganda_PRSP_APR.pdf.] In\naddition, lacking and improper hygienic facilities also resulted in absenteeism and\ndropouts, especially among girl students.\n\n\nAlthough efforts are underway to publicize and disseminate information of policy\nissues and budget processes by sectors and ministries, these efforts are mostly\nuncoordinated, resulting in duplication and low level of efficiency", "output": {"entities": {"named_data": ["Demographic Survey", "NSDS 2000"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008116", "page": 7, "chunk": 0, "title": "Uganda - Poverty Reduction Support Credit (PRSC)", "pdf_url": "https://documents.worldbank.org/curated/en/115011468318293125/pdf/514350WP0UG00P10Box342028B01PUBLIC1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Demographic Survey", "label": "NAMED_DATA", "score": 0.7021002769470215, "start": 243, "end": 261, "probe_score": 0.9942, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "NSDS 2000", "label": "NAMED_DATA", "score": 0.671424388885498, "start": 1031, "end": 1040, "probe_score": 0.9968, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_4.3._ _Number of items_\n\n\nIn the absence of diary fatigue, the number of items and total expenditure should be relatively consistent\n\n\nacross diary days, allowing for some variation due to weekly shopping patterns. To prevent bias from these patterns,\n\n\nthe first day was staggered over days of the week. The two PAPI diaries, however, show considerable diary fatigue.\n\n\nIn the highly monitored diaries, the number of transactions listed in the diary declines from 8.3 on day 1 to 4.5 on\n\n\nday 14, with small jumps on the last day of each diary-keeping week (Figure 4). With the low monitored diary, the\n\n\ndecline in the number of transactions was from 6.2 on day 1 to 3.0 on day 14. This finding was robust to controlling\n\n\nfor day of the week and for location using econometric analysis (Figure 5). Combining the data from the highly\n\n\nmonitored and low monitored diaries, the rate of decline was 3.4 percent fewer transactions recorded per day, the\n\n\nsame rate of diary fatigue seen in the 2009/10 PNG HIES (Figure 1), resulting in 35 percent fewer transactions\n\n\nrecorded, on average, in the low monitored diaries.\n\n\nWhile the diary fatigue reduces measured household food acquisition, an off-setting error that raises apparent\n\n\nfood consumption comes from stock measurement. Of 270 diary-keeping households with analyzable results, 236\n\n\nreported starting food stocks but only 211 reported ending food stocks. Moreover, of those reporting food stocks at\n\n\nboth the start and end, twice as many reported larger starting food stocks than ending food stocks. The combination\n\n\nof these two patterns sees apparent destocking of food being equivalent to about 4 percent of total expenditure (Figure\n\n\n6). For the low monitored diary, apparent destocking contributes almost 400 calories per person per day, while it\n\n\ncontributes about 200 calories per person per day for the highly monitored diary (and about 130 calories per person\n\n\nper day for", "output": {"entities": {"named_data": ["PNG HIES"], "descriptive_data": ["PAPI diaries"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000607", "page": 15, "chunk": 0, "title": "idu014657f420d00e042a30a68903563423f5b37", "pdf_url": "https://local/prwp/idu014657f420d00e042a30a68903563423f5b37.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "PAPI diaries", "label": "DESCRIPTIVE_DATA", "score": 0.5008732080459595, "start": 314, "end": 326, "probe_score": 0.8438, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PNG HIES", "label": "NAMED_DATA", "score": 0.8751328587532043, "start": 1002, "end": 1010, "probe_score": 0.9875, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**REPORT ON THE ERPSNP RESULTS FRAMEWORK INDICATORS (FROM GOE REPORT)**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|S. N.|RPSNP|Col3|To be reported by May 2018|Col5|Col6|Col7|\n|---|---|---|---|---|---|---|\n|**S. N.**|<br> <br>**Indicators**||**30-Jun-18**|**30-Jun-18**|**30-Jun-18**|**30-Jun-18**|\n|**S. N.**|<br> <br>**Indicators**||**Performance**|**Target**|**Percentage**|**Absolute Value (Y/N, absolute**<br>**number, days, etc)**|\n|1|**PERCENT OF CORE SAFETY NET TRANSFERS**<br>**PAID ON TIME **|**PERCENT OF CORE SAFETY NET TRANSFERS**<br>**PAID ON TIME **|28.5|60|28.5||\n||**CASH **||40||40||\n||RAW DATA<br>SOURCES||||||\n||Comments<br>||||40% for the nine<br>months (July to<br>March) 2018||\n||**FOOD **||17|60|17||\n||RAW DATA<br>SOURCES||||FIC report||\n||Comments||||For food 17 % is", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["RAW DATA"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017191", "page": 57, "chunk": 0, "title": "Ethiopia - Phase Four of the Rural Productive Safety Net Project : Joint Review and Implementation Support Mission - June 4-14, 2018", "pdf_url": "https://documents.worldbank.org/curated/en/720621541065692801/pdf/Aide-Memoire-Ethiopia-Rural-Productive-Safety-Net-Project-P163438.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "RAW DATA", "label": "VAGUE_DATA", "score": 0.5436584949493408, "start": 581, "end": 589, "probe_score": 0.0061, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "child height on these more precise measures of exposure to density of open defecation using\n\n\ndistrict and survey round fixed effects. As in Sastry and Hussey (2003), we use geographic\n\n\nfixed effects because they control for time-invariant properties of place at the level of the\n\n\nfixed effect, in this case the district. <sup>1</sup> The magnitude of the interaction that we identify in\n\n\nthe Bangladesh dataset is quantitatively similar to what is predicted for Bangladesh by a\n\n\nsemi-parametric model fit to the international data.\n\n\nThis paper proceeds in three sections. First, section 2 presents background on global\n\n\nsanitation and summarizes evidence from the literature about why poor sanitation would\n\n\nbe expected to have a larger effect on infant mortality and child height where population\n\n\ndensity is higher. Section 3 describes the analysis and presents results from the international\n\n\ndataset. Section 4 describes the analysis and presents results from the Bangladesh dataset.\n\n\nSection 5 discusses the findings. We point out that although, taken at face value, our results\n\n\nmight seem to recommend concentrating policy efforts on improving sanitation in urban\n\n\nareas, the distributions of sanitation coverage and population density in the world today\n\n\nshow that many of the places on earth where open defecation is most densely practiced are\n\n\nactually classified as rural. Indeed, our findings, combined with these empirical distributions,\n\n\nhighlight the threats to child health posed by the enduring density of open defecation in _rural_\n\n\nSouth Asia.\n\n#### **2 Background: Population density, sanitation and** **disease externalities**\n\n\nRural places have lower population density than urban places on average, but also have\n\n\nmore open defecation than urban places and lower quality sanitation, on average. Although\n\n\n1We do not present multi-level models because, as explained by Sastry and Hussey (2003), these models\nrequire the assumption that the random effects that are used in the models be independent of measured\ncovariates. This independence criterion is not met in this case; for example, more", "output": {"entities": {"named_data": ["Bangladesh dataset"], "descriptive_data": ["international\n\n\ndataset"], "vague_data": ["international data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006203", "page": 6, "chunk": 0, "title": "wps7124", "pdf_url": "https://local/prwp/wps7124.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Bangladesh dataset", "label": "NAMED_DATA", "score": 0.6655413508415222, "start": 396, "end": 414, "probe_score": 0.931, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "international data", "label": "VAGUE_DATA", "score": 0.7047409415245056, "start": 517, "end": 535, "probe_score": 0.9527, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "international\n\n\ndataset", "label": "DESCRIPTIVE_DATA", "score": 0.6114823222160339, "start": 890, "end": 913, "probe_score": 0.9873, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">sources to support the vaccination sites.<br> <br>Additional mobile vaccination units need<br>to be deployed to vaccinate hard-to-<br>reach populations.<br> <br>Given the success of the large-scale<br>marathons being conducted by the<br>MoPH, additional marathons should be<br>conducted to improve vaccine uptake.<br> <br>|\n|Training and<br>supervision<br>| <br>Vaccination teams were trained on the<br>vaccination process.<br> <br>|<br> <br>With the opening of new vaccination<br>sites with new vaccination teams,<br>reminder trainings may be required. In<br>preparation for vaccination in schools,<br>vaccination teams should also be trained<br>on vaccination in children/ adolescents.<br> <br>|\n|Monitoring and<br>evaluation<br>| <br>Multiple channels for grievance reporting<br>exist (hotline, and the MOPH website) for<br>vaccination.<br> <br>IMPACT platform is used to monitor<br>vaccination data<br> <br>|<br> <br>A Third-Party Monitoring Agency (TPMA)<br>was contracted to verify theGoL’s<br>compliance of the vaccination<br>deployment with the NDVP, WHO<br>standards and WB requirements<br>reflected in the legal agreements,<br>Environmental and Social safeguards and<br>POM.<br> <br>A technical auditor will be hired to<br>monitor the deployment of World Bank-<br>financed vaccines under the proposed<br>operation.<br> <br>|", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["vaccination data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000000", "page": 19, "chunk": 1, "title": "Lebanon - Strengthening Lebanon's COVID-19 Response under the COVID-19 Strategic Preparedness and Response Program (SPRP)", "pdf_url": "http://documents.worldbank.org/curated/en/099410007282239961/pdf/BOSIB09c1bfedd05c098380dc89cfe988b8.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "vaccination data", "label": "VAGUE_DATA", "score": 0.6836509704589844, "start": 893, "end": 909, "probe_score": 0.008, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "technological tools and exporting behavior, given the firm’s characteristics and\n\n\nproductivity. As mentioned above, I estimate a binomial probit model and a tobit model.\n\n\nTable 6 shows the results from the probit model defined in equation (7). The\n\n\ndependent variable _Exporter_ equals zero if the firm exclusively supplies the local market,\n\n\nand it equals one otherwise. There are five different specifications, all of which include\n\n\nsector, country, and year effects. Each column controls for an additional set of\n\n\nexplanatory variables. Consistent with the existing literature, productivity, size, and type\n\n\nof ownership are significant in every specification. As expected the productivity and size\n\n\nof the firm are clear determinants for whether a firm exports or not. A 10% increase in\n\n\nproductivity results in a 0.4% increase in the likelihood that the firm exports. The size of\n\n\nthe firm has an even greater effect on its probability to export; a 10% increase in size\n\n\nresults in 1.3% increase in the likelihood the firm exports. It is not surprising to find that\n\n\nthe size of the firm has a greater impact in the likelihood that a firm exports considering\n\n\nthat all firms in the sample are located in developing countries where economic activity is\n\n\ndominated by a mass of small and inefficient businesses, and perhaps as much as half the\n\n\npopulation works in the informal economy. In this scenario big firms are clearly more\n\n\nlikely to export.\n\n\nThe type of ownership is also an important factor that determines the exporting\n\n\nbehavior of a firm. Firms that are owned in their majority by a foreign entity are 13%\n\n\nmore likely to export than national-private owned firms; whereas firms owned by a\n\n\npublic entity are 16% less likely to export than national-private owned firms. The positive\n\n\neffect of foreign-ownership can be due to three main reasons: 1) network effects—foreign\n\n\nowners have connections in foreign countries; 2) supply chains—if the firm is a\n\n\n20", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004733", "page": 21, "chunk": 0, "title": "wps5547", "pdf_url": "https://local/prwp/wps5547.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Policy Research Working Paper 10703\n\n### **Abstract**\n\nThis paper describes the state of informal sector work in\n\nurban Sub-Saharan Africa, using household surveys from\n26 countries representing 61 percent of the population of\nSub-Saharan Africa and firm surveys from three countries.\nFive main conclusions emerge. First, the urban informal\n\nsector is large and persistent in Sub-Saharan Africa. Approximately 56 to 65 percent of urban workers are informal, half\nof whom are self-employed. Data from five countries suggest\nlittle systematic reduction in the prevalence of informality\nduring the 2010s. Second, heterogeneity in the African\ninformal sector cuts along demographic lines. Women are\noverrepresented in informal self-employment, men in informal wage work, and youth in unpaid employment. Third,\nwhile the urban informal workers are, on average, poorer\n\n\n\nand in less-skilled occupations than formal sector workers,\nthe majority are not extremely poor and are in mid-skilled\noccupations. Fourth, informal enterprises are small and are\nchallenged to survive and grow into job-creating firms. Few\nfind much benefit from registration given the costs, both\nmonetary (taxes) and transactional (information about the\nregistration process). Fifth, access to urban public services\n(utilities) is weakly associated with the probability of work\ning in an informal job, although access to mobile phones\nis high across all job types. If thriving urban jobs are to\ncontribute to economic and social development in Africa,\nit will be crucial for policies and programs to take into consideration the heterogeneity in jobs, the profile of workers,\nand the urban context.\n\n\n\nThis paper is a product of the Social Protection and Jobs Global Practice and the Poverty and Equity Global Practice. It is part\n\nof a larger effort by the World Bank to provide open access to its research and make a contribution to development policy\ndiscussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/pr", "output": {"entities": {"named_data": [], "descriptive_data": ["household surveys from\n26 countries", "firm surveys from three countries"], "vague_data": ["Data from five countries"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001610", "page": 1, "chunk": 0, "title": "idu1e9d2d68a110ad14aaa1af9a110e90bd603f1", "pdf_url": "https://local/prwp/idu1e9d2d68a110ad14aaa1af9a110e90bd603f1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "household surveys from\n26 countries", "label": "DESCRIPTIVE_DATA", "score": 0.8731361031532288, "start": 146, "end": 181, "probe_score": 0.9739, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "firm surveys from three countries", "label": "DESCRIPTIVE_DATA", "score": 0.8298051953315735, "start": 250, "end": 283, "probe_score": 0.9724, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Data from five countries", "label": "VAGUE_DATA", "score": 0.7356199622154236, "start": 490, "end": 514, "probe_score": 0.9736, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " rate of only 29 percent (15 percent among young women).\n\n\n1 Marquez, PV. 2020. “Does Tobacco Smoking Increases the Risk of Coronavirus Disease (Covid-19) Severity? The Case of China.”\n_[http://www.pvmarquez.com/Covid-19](http://www.pvmarquez.com/Covid-19)_\n2 Fauci, AS, Lane, C, and Redfield, RR. 2020. “Covid-19 — Navigating the Uncharted.” New Eng J of Medicine, DOI: 10.1056/NEJMe2002387\n3 Del Rio, C. and Malani, PN. 2020. “COVID-19—New Insights on a Rapidly Changing Epidemic.” JAMA, doi:10.1001/jama.2020.3072\n\n4 World Bank Development Indicators (2017).\n\n\nPage 8 of 34", "output": {"entities": {"named_data": ["World Bank Development Indicators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000152", "page": 12, "chunk": 2, "title": "Niger - COVID-19 Emergency Response Project", "pdf_url": "http://documents1.worldbank.org/curated/en/876471587417866707/pdf/Niger-COVID-19-Emergency-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "World Bank Development Indicators", "label": "NAMED_DATA", "score": 0.779369592666626, "start": 520, "end": 553, "probe_score": 0.0064, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017044", "page": 19, "chunk": 1, "title": "Kenya - Financial Sector Adjustment Credit Project", "pdf_url": "https://documents.worldbank.org/curated/en/709771468773423166/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7292463183403015, "start": 272, "end": 283, "probe_score": 0.8771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "DISPLACEMENT PATTERNS, PROTECTION RISKS AND NEEDS OF REFUGEES FROM UKRAINE\n\n# The protection situation of persons with specific needs\n\n\n\n22% of assessed households reported at least one\nfamily member with specific needs, such as\ndisabilities and serious medical conditions, with a\nhigher percentage in Hungary. Previous <u>[research](https://data.unhcr.org/en/documents/details/96266)</u> by\nUNHCR demonstrated that persons with specific\nneeds face increased obstacles to accessing their\nrights under the TPD, partly due to a lack of\nsystematic identification procedures in host\n\n\n\ncountries. Protection monitoring data also indicates\nthat households with members with specific needs\nexperience greater challenges and vulnerability in\nmeeting their socio-economic needs. As the\ndisplacement period extends, the vulnerability of\nthese households may increase, impacting\ndecisions to return to Ukraine even in sub-optimal\nconditions.\n\n\n##### **Persons with disabilities**\n\n\n\n12% of respondents reported at least one household\nmember with a disability. A higher proportion of\nhouseholds with a person with a disability (PWD)\nreported difficulties accessing healthcare (39%) as\ncompared to other households (23%), predominantly\ndue to long waiting times. Moreover, in contrast to\nother households surveyed, a higher portion of\nhouseholds with a PWD are missing their biometric\npassport (27%). Persons with disabilities may face\nincreased challenges to replace missing\ndocumentation due difficulties reaching locations\nwhere these services are offered, among other\nfactors.\n\n\n\nProtection monitoring data indicates that, as\ncompared to other households surveyed,\nhouseholds with a PWD are likely to reside in\ncollective sites (24%), with relatives (13%) and\nhostels by provided government (12%) rather than in\nrented accommodation, indicating more limited\naccess to financial resources. Prejudice against\npersons with cognitive disabilities is additionally\ncited as a barrier for families searching for housing. <sup>8</sup>\n\n\n\n8. UNHCR (2023", "output": {"entities": {"named_data": [], "descriptive_data": ["Protection monitoring data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001343", "page": 12, "chunk": 0, "title": "Displacement Patterns, Protection Risks and Needs of Refugees from Ukraine - Regional Protection Analysis # 2", "pdf_url": "https://reliefweb.int/attachments/cf0b3f3f-9740-40f9-b43e-118ce097f367/Protection%20monitoring%20regional%20analysis%202__April%202023.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Protection monitoring data", "label": "DESCRIPTIVE_DATA", "score": 0.7294100522994995, "start": 593, "end": 619, "probe_score": 0.9072, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">)</sup>\n\n_∂ws_\n\n\n\n_≤_ 0 (A28)\n\n\n_≤_ 0 (A29)\n\n\n\nTo summarize, (A26)-(A29) indicate that an increase in the wage level in North (which can be\ninterpreted as a real-exchange-rate appreciation in North) all else equal will lead to an increase\nin firm-average output and input prices among Home firms, and an increase in the wage level in\nSouth will lead to a decrease in both firm-average output and input prices. These are the testable\nimplications that we take to the data in the main text.\n\n#### **References**\n\n\nArkolakis, C., S. Demidova, P. J. Klenow, and A. Rodriguez-Clare (2008): “Endogenous Variety\n\nand the Gains from Trade,” _American_ _Economic_ _Review_, 98(2), 444  - 450.\nBaldwin, R., and J. Harrigan (2011): “Zeros, Quality and Space: Trade Theory and Trade Evidence,”\n\n_American_ _Economic_ _Journal:_ _Microeconomics_, 3(2), 60–88.\nChaney, T. (2008): “Distorted Gravity: The Intensive and Extensive Margins of International Trade,”\n\n_American_ _Economic_ _Review_, 98(4), 1707  - 1721.\nCrozet, M., K. Head, and T. Mayer (2012): “Quality Sorting and Trade: Firm-Level Evidence for\n\nFrench Wine,” _Review_ _of_ _Economic_ _Studies_, 79, 609–644.\nEckel, C., L. Iacovone, B. Javorcik, and J. P. Neary (2011): “Multi-Product Firms at Home", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data in the main text"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006023", "page": 36, "chunk": 1, "title": "wps6914", "pdf_url": "https://local/prwp/wps6914.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "data in the main text", "label": "VAGUE_DATA", "score": 0.5281065702438354, "start": 467, "end": 488, "probe_score": 0.9981, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nNational Youth Opportunities Towards Advancement Project (P179414)\n\n\n\n|Col1|beneficiaries who are living<br>with any kind of disability<br>that allows beneficiaries to<br>participate fully in the<br>program.|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|Youth beneficiaries in wage or self-<br>employment at least 6 months after<br>completing the package of project<br>interventions|This indicator measures<br>youth under components 1<br>and 2 who are employed<br>(wage or self-employment)<br>at least 6 months from date<br>of completion of package of<br>interventions|Annual<br>|Surveys,<br>Project MIS<br>data<br>|Tracer study survey on<br>youth employment<br>status and other<br>activities conducted at<br>least six months after a<br>cycle of training is<br>completed.<br> <br> <br>|MYAAS with survey<br>firm<br>|\n|Female beneficiaries in wage or self-<br>employment at least 6 months after<br>completing the package of project<br>interventions|This indicator measures<br>female beneficiaries under<br>components 1 and 2 who<br>are employed (wage or self-<br>employment) at least 6<br>months from date of<br>completion of package of<br>interventions|Annual<br>|Surveys<br>|Tracer Studies, Project<br>MIS data<br>|MYAAS with survey<br>", "output": {"entities": {"named_data": ["MYAAS with survey", "MYAAS with survey"], "descriptive_data": ["Tracer study survey"], "vague_data": ["MIS data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002639", "page": 55, "chunk": 0, "title": "Kenya - National Youth Opportunities Towards Advancement Project", "pdf_url": "https://documents.worldbank.org/curated/en/099052623140041067/pdf/BOSIB-29fbdabe-b613-44f4-aa80-5ca7c6b046bf.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Tracer study survey", "label": "DESCRIPTIVE_DATA", "score": 0.6589129567146301, "start": 637, "end": 656, "probe_score": 0.948, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "MYAAS with survey", "label": "NAMED_DATA", "score": 0.5390350222587585, "start": 807, "end": 824, "probe_score": 0.1218, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "MIS data", "label": "VAGUE_DATA", "score": 0.544748067855835, "start": 1224, "end": 1232, "probe_score": 0.9335, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "MYAAS with survey", "label": "NAMED_DATA", "score": 0.5555098652839661, "start": 1237, "end": 1254, "probe_score": 0.895, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEthiopia: National Quality Infrastructure Development Project (P160279) ICR DOCUMENT\n\n\n**86.** **However, important weaknesses in the RF and implementation planning limited early effectiveness.** Several\nindicators were based on limited baseline data and proved overly optimistic, particularly regarding enterprise uptake and\nservice volumes. Key activities such as TOTs and regulatory reforms were not well integrated into the RF, and assumptions\naround the pace of private sector engagement proved optimistic. While implementation risks were identified, challenges\nrelated to institutional coordination —particularly across shifting ministerial structures—may have been underestimated.\nThese shortcomings were partially corrected in the 2022 restructuring.\n\n**Quality of Supervision**\n**87.** **WB supervision was proactive and responsive, underpinned by strong day-to-day collaboration with MoTRI and**\n**the PIU.** The team maintained regular engagement through in-person and virtual missions, including during disruptions\nrelated to COVID-19, inflationary pressures, and the internal conflict in Northern Ethiopia. The WB played a key role in\nfacilitating the 2022 restructuring, including revising the RF, recalibrating targets, and extending the project timeline.\nCoordination with the PIU remained strong throughout, with timely support on procurement, safeguards, and financial\nmanagement—enabled by responsive focal persons within the PIU and MoTRI who maintained close communication and\ndiligent follow-up on mission recommendations. This collaboration supported joint problem-solving, timely course\ncorrection, and more effective supervision. This joint problem-solving approach was particularly important in an FCV\ncontext, where mobility constraints and intermittent states of emergency required adaptive mission planning and flexible\nsupport modalities.\n\n**88.** **The WB consistent technical support contributed to implementation quality** . Specialists offered guidance on\ninstitutional capacity, calibration equipment, and service delivery metrics, and worked closely with implementing agencies\nto improve indicator definitions and reporting systems. The Bank", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["limited baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001487", "page": 22, "chunk": 0, "title": "Ethiopia - National Quality Infrastructure Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/099032526102032966/pdf/BOSIB-eb610218-fdec-49ed-b9c7-c1539f37b0a1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "limited baseline data", "label": "VAGUE_DATA", "score": 0.6670382022857666, "start": 248, "end": 269, "probe_score": 0.3733, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "’s life cycle from from\npreconstruction to construction, and post construction phases. It adopts an inclusive approach\nthat takes care of the specific needs and expectations of stakeholders at regional, national, and\nlocal level. Since the project was conceived with the view of improving access to refugee\nsettlements and host communities, the needs and priorities of the existing refugee groups, both\nregistered and unregistered (self-settled) must be must be integrated in an all-inclusive and\nelaborate stakeholder engagement plan. It also accounts for the needs of the different tribes that\nexist in the host communities. The SEP also details engagements undertaken as part of ESIA and\nRAP preparations and serves as a guide for engagement during implementation, construction,\npost construction/operation activities. This SEP is a living document and will have to be revised\nregularly to inform ongoing stakeholder engagement through the various stages of project\ndevelopment, in line with legal and policy frameworks including the UNRA Environment and Social\nManagement System (2019) guidelines on stakeholder engagements.\n\n\nStakeholder engagement is an interactive process that aims to build and maintain an open and\nconstructive relationship with stakeholders and thereby facilitate and enhance project\nmanagement of its activities and operations, including its environmental and social effects and\nrisks. It is a more inclusive and continuous process between a project (and or developer) and those\npotentially affected by or have an interest in the project.\n\n\nIn the context of this SEP, a stakeholder refers to individuals or groups who: (a) are affected or\nlikely to be affected by the project (project-affected parties); and (b) may have an interest in the\nproject (other interested parties). They may include local communities, national and local\nauthorities, neighboring projects, and non-governmental organizations (WB-ESS10).\n\n\n6", "output": {"entities": {"named_data": ["WB-ESS10"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:006707", "page": 17, "chunk": 1, "title": "Uganda - Roads and Bridges in the Refugee Hosting Districts-Koboko-Yumbe-Moyo (KYM) Road Corridor Project : Stakeholder Engagement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099419407242442502/pdf/IDU-e4811189-3ab5-4069-928c-d9b7fd13163e.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "WB-ESS10", "label": "NAMED_DATA", "score": 0.6371264457702637, "start": 1931, "end": 1939, "probe_score": 0.0041, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "taxpayer registry in 1993, which is indeed impressive. At the same time only 35% of\n\n\ntaxpayers have filed on average over the period, and SUNAT has not been able to\n\n\nincrease the relative amount filing (as a percentage of those registered).\n\n\nA more detailed analysis shows that SUNAT has been using its limited resources\n\n\njudiciously. Data from 1997 show that SUNAT has focused its efforts on large and\n\n\nmedium taxpayers, and has been extremely successful in the process. The 33,300 large\n\n\nand medium taxpayers are well-controlled by SUNAT: the ratios of those declaring and\n\n\npaying are 100%. The same ratios for the general and other simplified regimes, however,\n\n\nwere quite low.\n\n\nThe data available for Venezuela allow for a limited comparison, revealing that\n\n\nSENIAT’s control over its large taxpayers was weaker when compared with SUNAT’s.\n\n\nThe absolute number of non-filers in SENIAT’s large taxpayers unit increased steadily\n\n\nsince 1995, nearly tripling by 1998. The average percentage of non-filers to the number\n\n\nof large taxpayers registered was 32% over the period, suggesting a large hole in the\n\n\nadministration’s effort to increase compliance.\n\n\nAnother useful indicator of administrative performance is late payments by\n\n\ntaxpayers (total late payments by taxpayers during the year). Data also showed that the\n\n\nnumber of large taxpayers in Venezuela making late payments increased since 1995,\n\n\nmore than tripling by 1998, though the amount of taxes paid late as a percentage of total\n\n\ncollections was quite small (about 1%).\n\n\nIn South Africa SARS steadily broadened the tax net with impressive year on year\n\n\ngrowth. From March 1996 to March 2001 the number of taxpayers with active status\n\n\ngrew from 518,649 to 976,720 for corporate income taxpayers; 1,929,274 to 3,187,072\n\n\nfor individual income taxpayers; 388,454 to 450,630 for VAT taxpayers; and 188,841 to\n\n\n211,425 for PAYE taxpayers. From 2000", "output": {"entities": {"named_data": [], "descriptive_data": ["taxpayer registry"], "vague_data": ["Data from 1997", "data available for Venezuela"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002681", "page": 30, "chunk": 0, "title": "wps3423", "pdf_url": "https://local/prwp/wps3423.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "taxpayer registry", "label": "DESCRIPTIVE_DATA", "score": 0.7125438451766968, "start": 0, "end": 17, "probe_score": 0.4083, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Data from 1997", "label": "VAGUE_DATA", "score": 0.700668454170227, "start": 339, "end": 353, "probe_score": 0.9025, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "data available for Venezuela", "label": "VAGUE_DATA", "score": 0.6746082305908203, "start": 695, "end": 723, "probe_score": 0.956, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " deux\n\n\ntypes de déclarations :les déclarations relatives aux comportements à risques réels relatifs au VIH et les déclarations\n\n\nconcernant les croyances et les idées. Les informations recueillies représentent toujours un mélange de ces deux\n\n\ncaractéristiques. Les deux sont importantes, mais doivent néanmoins être clairement différenciées. La triangulation\n\n\n- c’est-à-dire la comparaison des données en provenance d’une source et d’une autre, ou la comparaison des\n\n\ndonnées obtenues à l'aide d'un outil avec des données obtenues avec un autre outil - est un processus important\n\n\npermettant de minimiser le potentiel d’un biais lors de l’affectation d’une valeur aux opinions exprimées et aux\n\n\nattitudes. La triangulation a également pour objectif de renforcer la crédibilité et la validité des résultats.\n\n\nL’interprétation des données majoritairement qualitatives recueillies dans le cadre d'une évaluation rapide est\n\n\ndifficile.Si l’analyse et l’interprétation des données ne sont pas effectuées soigneusement,les équipes risquent tout\n\n\nsimplement de renforcer les idées préconçues. Les jugements subjectifs et les généralisations sont courants. Des\n\n\nlistes de besoins ont pu être pré-établies mais ils ne sont pas classés par ordre de priorité en fonction de la situation\n\n\nlocale.Il se peut que la variabilité et les mécanismes adaptatifs et opératoires ne soient pas identifiés.Une hypothèse\n\n\n22", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["données majoritairement qualitatives"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001477", "page": 23, "chunk": 3, "title": "Besoins Relatifs au VIH Chez les Personnes Déplacées à l'Interieur de Leur Propre Pays et les Populations Affectées pas les Conflits: Outil d'Evaluation Rapide de la Situation", "pdf_url": "https://reliefweb.int/attachments/e5e599e2-c45c-3968-8168-f74321e0c5f4/9E7A791A8B8004D6C1257501003B8BF4-unhcr_2007.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "données majoritairement qualitatives", "label": "VAGUE_DATA", "score": 0.5949394106864929, "start": 836, "end": 872, "probe_score": 0.0, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<br>project<br>midterm and<br>end of<br>project.<br>|<br>EMIS<br>|Headcount<br>|MoES<br>|\n|Enrolment at public lower secondary<br>schools in targeted districts, boys|The indicator will measure<br>the number of male<br>students who will enroll<br>annually in public school in<br>the targeted districts (2017<br>is the baseline year).|<br>Midterm and<br>end year<br>|EMIS<br>|Head count<br>|MoES<br>|\n\n\nPage 51 of 96", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 56, "chunk": 1, "title": "Uganda - Secondary Education Expansion Project", "pdf_url": "http://documents.worldbank.org/curated/en/406361595815248191/pdf/Uganda-Secondary-Education-Expansion-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "* ة المعت **ـ** لجتماعي **ا** ى <sup>ن</sup> **ـ** ار الب **ـ** ف، تنه **ـ** رراع العني **ـ** اال ال **ـ** وخ\nف **ـ** �ي وص **ـ** ا ي **ـ** ي مة. � <sup>ف</sup> **ـ** اً للغاي **ـ** اً صعب **ـ** ى، تحدي **ـ** ي المنفنّ � <sup>ف</sup> **ـ** ن بمفردهنّ ال <sup>آ</sup> **ـ** ى رأس أرسه **ـ** ررن ع **ـ** ي يوا� <sup>ت</sup> **ـ** اء الل **ـ** ه النس **ـ** ة. وتواج **ـ** مألوف\n- 2014 الجئ�ي **ـ** ؤون الالجئ **ـ** امية لش **ـ** دة الس **ـ** م المتّح **ـ** مة ال <sup>أ</sup> **ـ** ر مفوضي **ـ** ي تقرينّ، � <sup>ف</sup> **ـ** ن أرسه **ـ** ي ", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001417", "page": 3, "chunk": 6, "title": "Sexual and Gender-Based Violence Prevention and Response in Refugee Situations in the Middle East and North Africa [EN/AR/TR]", "pdf_url": "https://reliefweb.int/attachments/dbaca2ef-5219-36a0-80bb-399c412d2ffa/SGBVPreventionandResponseOverviewinMENAArabic.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " characteristics of youth who choose male\n\n\nversus female contacts, rather than solely to the gender of the contact itself.\n\n#### **4 Discussion**\n\n\nLow take-up is a major barrier to the effectiveness of a large number of development programs\n\n\nand social policies. In some cases, that low take-up may reflect insufficient information\n\n\nregarding the program. This study sought to boost the uptake of a youth employment\n\n\n6", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001535", "page": 8, "chunk": 1, "title": "idu1bf667d10138031441e1afc61494656110d50", "pdf_url": "https://local/prwp/idu1bf667d10138031441e1afc61494656110d50.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " gaps and weaknesses are addressed.\n\nSome o f the main issues identified in the 2002 Country Status Report on Health are as follows:\n\n\n**a) Relatively poor** **health outcomes:** Although indicators are improving they are still below what they\nshould be compared to other African countries. Contraceptive prevalence in Guinea i s about 5%, maternal\nmortality i s high, and neonatal mortality accounts for 50% o f the deaths during the first year o f life.\n\n\n**b) Inequity:** Over the last decade, public expenditures focused primarily on services in urban areas with\nemphasis on Conakry, and overall benefited the wealthier income groups. More than 60% o f health\npersonnel i s in Conakry serving only 20% o f the country’s total population. Health indicators vary widely\n\n\n1", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Health indicators"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000092", "page": 6, "chunk": 2, "title": "Guinea - Health Sector Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/551731468037482453/pdf/28046.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Health indicators", "label": "VAGUE_DATA", "score": 0.6159379482269287, "start": 742, "end": 759, "probe_score": 0.002, "gold": "NON_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**ANNEX 9: CONSOLIDATED APPROACH FOR REPORTING INDICATORS OF**\n**FOOD SECURITY (CARI)**\n\n\n\nThe economic capacity of a household can be\ndemonstrated by either ECMEN or FES indicators, both\nof which utilize expenditure data and are measured on\na per capita basis within the household.\n\nThe ECMEN indicator provides a more accurate\nassessment of a household's economic capacity by\nexcluding the consumption of assistance. It uses the\nMinimum Expenditure Basket (MEB) to calculate the\nmonetary thresholds required to measure the\nhousehold's economic capacity. The MEB was\ndetermined using the expenditure-based approach. The\nreference group used for the MEB was all households\nthat had acceptable food consumption and did not rely\non emergency or crisis coping mechanisms. The WFP\nCARI guideline recommends using the ECMEN as the\nmost suitable indicator for assessing a household's\neconomic capacity. However, in cases where data for\nthe MEB is not available, the FES can be utilized instead.\n\n\n\nThe FES indicator is calculated by dividing total food\nexpenditures by total household expenditures. It is\nimportant to note that both the numerator and\ndenominator should include the value of nonpurchased consumed foods, such as those produced\nwithin the household or received as assistance during\nthe recall period. By considering both purchased and\nnon-purchased foods in the FES estimate, the indicator\ntakes into account households with different food\naccess situations. However, the FES may not be suitable\nfor use in refugee contexts or urban settings where\ncommunities receive commodities like shelter and\nconstruction material for free. Therefore, caution\nshould be exercised when applying the FES in these\ncontexts.\n\nConsidering the limitations and recommendations, the\nnew CARI (Comprehensive Food Security and\nVulnerability Analysis) incorporates the use of the\nECMEN indicator instead of the FES to assess the\neconomic capacity of households.\n\n\n\nSeptember 2023| UNHCR & WFP Joint Post Distribution Monitoring: South Sudan 49", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["expenditure data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001526", "page": 48, "chunk": 0, "title": "UNHCR/WFP Joint Post Distribution Monitoring: Profiling analysis to inform targeting and prioritization of assistance to refugees in South Sudan - September 2023", "pdf_url": "https://reliefweb.int/attachments/ec7d043d-dbe7-4bc2-a97d-cf079683e5fa/WFP-0000152712.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "expenditure data", "label": "VAGUE_DATA", "score": 0.6922474503517151, "start": 205, "end": 221, "probe_score": 0.8674, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "students’ competencies in literacy and numeracy; and (ii) an evaluation test which maps students’ more\n\n\nspecific abilities along the literacy and numeracy learning continuum.\n\n\nSeparate test booklets were developed for each elementary grade level with multiple-choice items\n\n\nconsisting of 15 percent grade-level, 65 percent one-grade-below, and 20 percent two-grade-below. Over\n\nlapping items across grades made it possible to vertically link scores across grades and thus assess these\n\n\ntests using item response theory (IRT). For the baseline survey, the evaluation test was administered for\n\n\nall students in grades 1 to 5 in participating schools, on a one-on-one basis for grades 1 and 2, and on a\n\n\ngroup basis for grades 3 to 5. At the endline, another evaluation test was administered to the same set\n\n\nof students, the majority of whom were in grades 2 to 6, as well newly enrolled grade 1 to 6 students\n\n\nwho did not participate in the baseline survey. Due to budgetary constraints, the follow-up survey was\n\nadministered to all students for grades 3 to 6 only. <sup>19</sup>\n\n\n**Teacher** **Absence** **Survey** **(TAS).** The instrument originated from the World Bank’s multi-country\n\n\nteacher absence survey (Chaudhury et al., 2006), which calls for an unannounced visit to schools during\n\n\nnormal school hours to obtain a representative estimate of teacher absence from school. The instru\n\nment has since been adapted for various TAS implementations in Indonesia. We adapted the design and\n\n\nmethodology of the TAS were from the Analytical and Capacity Development Partnership (2014) study\n\n\nin Indonesia, with additional inputs from the instruments used in UNICEF (2012) study in Papua and\n\n\nWest Papua. In its implementation, the enumerators implemented the TAS on the day of arrival which\n\n\nwere unannounced.\n\n\n**Survey** **Instrument", "output": {"entities": {"named_data": [], "descriptive_data": ["multi-country\n\n\nteacher absence survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002070", "page": 16, "chunk": 0, "title": "scores camera action social accountability and teacher incentives in remote areas", "pdf_url": "https://local/prwp/scores-camera-action-social-accountability-and-teacher-incentives-in-remote-areas.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "multi-country\n\n\nteacher absence survey", "label": "DESCRIPTIVE_DATA", "score": 0.6634838581085205, "start": 1184, "end": 1222, "probe_score": 0.97, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "........ 44**\n\n\n**ANNEX 2: Map of the First Phase of Civil Works and Remainder of Potential Candidates Pre-**\n**Identified ............................................................................................................................ 54**\n\n\n**ANNEX 3: Climate Change Impact Study ............................................................................... 55**\n\n\n**ANNEX 4: Climate Risk Assessment ...................................................................................... 60**\n\n\n**ANNEX 5: Mitigating and Responding to GBV, including SEA ..........", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000048", "page": 3, "chunk": 7, "title": "Chad - Rural Mobility and Connectivity Project", "pdf_url": "http://documents.worldbank.org/curated/en/815491545534039786/pdf/Chad-PAD-11302018-636811128215032206.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nCHAD Improving Learning Outcomes Project (P175803)\n\n\nof parents of children aged 7-14 years report that the school management committee includes parent members; and\nonly one fifth report participating in meetings of the committee. The majority (62 percent) receive report cards, but only\n26 percent report discussing their child’s progress with a teacher. <sup>27</sup> [^27: Data for this and the following two paragraphs are taken from MICS 2019.]\n\n\n18. **Children enter school poorly prepared for learning** **and are taught in a language** **they do not speak.** Many\nchildren start Grade One after years of debilitating health episodes and inadequate cognitive stimulation. Roughly 40\npercent of children under five years old are either moderately or severely stunted. Only one percent of children aged\n36-59 months attend a pre-school program, while only 2 percent of Grade One students have attended a pre-school in\nthe previous year. Also, the existing preschool program dates from 1994 and is no longer relevant, and there are no\nstandards regulating this sub-sector. Further, almost all children are taught in a language they cannot speak.\n\n\n19. **Education budgets are inadequate, and financial mechanisms can be strengthened** . Public spending on\neducation was the equivalent of 2 percent of GDP and education expenditures constituted only 11 percent of total\ngovernment expenditures in 2018, <sup>28</sup> [^28: Chad Public Expenditure Analysis 2019: Fiscal Space for Productive Social Sectors Expenditure, June 2019, pp. 55 ff.] well below those recommended by the Global Partnership for Education, 5 percent\nand 20 percent respectively. They are also low by regional standards. Over the past fifteen years, Chad’s public\nexpenditures on education as a percentage of GDP have on average been 0.8 percentage points lower than the Sahelian\naverage. <sup>29</sup> Education expenditures are fragile and susceptible to shocks. In", "output": {"entities": {"named_data": ["MICS 2019"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000009", "page": 12, "chunk": 0, "title": "Concept Project Information Document (PID) - CHAD Improving Learning Outcomes Project - P175803", "pdf_url": "http://documents.worldbank.org/curated/en/234501637169242309/pdf/Concept-Project-Information-Document-PID-CHAD-Improving-Learning-Outcomes-Project-P175803.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "MICS 2019", "label": "NAMED_DATA", "score": 0.8523844480514526, "start": 457, "end": 466, "probe_score": 0.9788, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "output": {"entities": {"named_data": [], "descriptive_data": ["random survey"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012549", "page": 16, "chunk": 0, "title": "Kenya - Integrated Agricultural Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/408861468914157567/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7714613080024719, "start": 379, "end": 395, "probe_score": 0.582, "gold": "NON_MENTION", "gold_tier": "flip"}, {"text": "random survey", "label": "DESCRIPTIVE_DATA", "score": 0.7173007130622864, "start": 1487, "end": 1500, "probe_score": 0.012, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nMauritania Social Safety Net System Project II (P171125)\n\n\n|Indicator Name|DLI|Baseline|Intermediate Targets|Col5|Col6|Col7|End Target|\n|---|---|---|---|---|---|---|---|\n||||**1 **|**2 **|**3 **|**4 **||\n|(Yes/No)||||||||\n|The common financial vehicle<br>has been established (Yes/No)<br>||No|No|Yes|Yes<br>|Yes|Yes|\n\n\n\n\n\n\n\n\n\n|Monitoring & Evaluation Plan: PDO Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **|**Definition/Description **|**Frequency **|**Datasource **|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|Programs using the Social Registry to<br>select their beneficiaries|Number of user agreements<br>signed by the Social Registry|Semester<br>|Project<br>Semester<br>report<br>|Supervision<br>|Social Registry<br>Directorate<br>|\n|SSN programs' beneficiary households<br>avoiding negative coping strategies<br>(national/refugees)|This indicators tracks the<br>percentage of households<br>benefiting from the shock-", "output": {"entities": {"named_data": ["Social Registry"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000045", "page": 42, "chunk": 0, "title": "Mauritania - Second Social Safety Net System Project", "pdf_url": "http://documents1.worldbank.org/curated/en/323551584151262464/pdf/Mauritania-Second-Social-Safety-Net-System-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Social Registry", "label": "NAMED_DATA", "score": 0.522925615310669, "start": 635, "end": 650, "probe_score": 0.6122, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "##### **From Farms to Factories and Firms** **–** **Structural Transformation and Labor Productivity Growth in Malaysia** **1. Introduction**\n\nSince independence in 1957, Malaysia has undergone a profound development process that has radically\nimproved nutrition, health care, and social service provision. During the last decades, Malaysia has also achieved\nan increasingly low mortality rate, a decline in fertility rates, and increases in life expectancy. As a result of\ngenerally favorable economic and demographic developments and in spite of more recent challenges like the\nCOVID-19 crisis, Malaysia has also seen relatively high levels of economic growth. Among the 88 countries\nfor which comparable data on GDP per capita in both 1960 and 2019 are available in the World Bank’s World\nDevelopment Indicators, Malaysia recorded the seventh highest growth rate in the intervening years (in local\ncurrency units). These relatively high levels of economic growth have propelled it to becoming the uppermiddle income country at the cusp of high-income status that it is today (World Bank forthcoming).\n\nDuring the last decades, Malaysia has also gone through a rapid and sustained structural transformation, defined\nby the reallocation of economic activity across sectors such as agriculture, manufacturing, and services. Within\nonly two generations, the South-East Asian country moved from an agriculture-centric economy to one with\nan important manufacturing base and then one dominated by services firms. In 1957, agriculture accounted for\n58 percent of employment (World Bank 2019a). Since then, its share of employment has declined to 10.6\npercent in 2018, releasing labor first to the manufacturing sector and then increasingly to the services sector.\nSimilarly, the share of agriculture in value-added was 32.6 percent in 1970 and has since declined to 7.4 percent\nin 2018. As Malaysia pursues further development toward becoming a high-income and developed nation but\nfaces a slowdown in both structural change and productivity growth, questions have", "output": {"entities": {"named_data": ["World\nDevelopment Indicators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000455", "page": 3, "chunk": 0, "title": "from farms to factories and firms structural transformation and labor productivity growth in malaysia", "pdf_url": "https://local/prwp/from-farms-to-factories-and-firms-structural-transformation-and-labor-productivity-growth-in-malaysia.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "World\nDevelopment Indicators", "label": "NAMED_DATA", "score": 0.8894138336181641, "start": 786, "end": 814, "probe_score": 0.959, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "- Lack of a unifi ed data management system\nimpedes registration.\n\n\n- UNHCR has limited access to the government\ndatabase and the government has limited\nresources to update the database.\n\n\n- The government is responsible for registration,\nbut does not recognize most of the registration\ncarried out by UNHCR and does not share\nregistration information with UNHCR.\n\n\n**Table 2:** The Sample countries with the largest\n\npopulations of registered asylum\n<u>seekers and refugees</u>\n\n|Countries|Number of Registered<br>Asylum Seekers|\n|---|---|\n|South Africa|219,368|\n|Kenya|35,271|\n|Uganda|23,453|\n|Ecuador|21,558|\n|Egypt|18,938|\n|Thailand|13,357|\n|Turkey|10,964|\n|Malaysia|10,937|\n|Sudan|6,912|\n|**Countries**<br>Yemen|Number of Registered<br>Refugees<br>5,878|\n|Iran|886,468|\n|Syrian Arab Republic|755,445|\n|Kenya|566,487|\n|Jordan|451,009|\n|Ethiopia|288,844|\n|Yemen|214,740|\n|India|185,118|\n|Uganda|139,448|\n|Sudan|139,415|\n|Ecuador|123,436|\n\n\n\n*Includes Sri Lankan and Tibetan refugees\nsupported directly by the Government of India.\n\n\n#### **REGISTRATION:** **WHAT WORKS WELL?**\n\nA well-structured process, including the\nsystematic use of mobile teams, careful\nscheduling and prioritization facilitates UNHCR\nregistration for urban refugees.\n\n\n**• India:** Schedules registration according to\ncountry of origin, and analyzes arrival trends\non a weekly basis to enable adjustments.\n\n\n**• Indonesia:**", "output": {"entities": {"named_data": [], "descriptive_data": ["government\ndatabase"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000907", "page": 17, "chunk": 0, "title": "The Implementation of UNHCR’s Policy on Refugee Protection and Solutions in Urban Areas - Global Survey – 2012", "pdf_url": "https://reliefweb.int/attachments/85f901a8-f804-3ef5-9421-00ded165230d/UNHCRs%20Policy%20on%20Refugee%20Protection%20and%20Solutions%20in%20Urban%20Areas.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "government\ndatabase", "label": "DESCRIPTIVE_DATA", "score": 0.8639174103736877, "start": 102, "end": 121, "probe_score": 0.8279, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Kydd J., Christiansen, R., “Structural change in Malawi since independence:\n\nconsequences of a development strategy based on large scale agriculture”, World\nDevelopment, Elsevier, 1982.\n\nIMF, “Malawi - IMF Country Report No. 08/3”, IMF, January 2008\n\nIMF, World Bank, “Financial Sector Assessment Program Malawi. Banking Sector: The\n\npath to a deeper and more inclusive system”, IMF, November 2007\n\nMinistry of Economic Planning and Development, “Annual Economic Report 2008”,\n\nGovernment of Malawi, 2008\n\nMillennium Challenge Account - Malawi, “Analysis of Constraints to Growth – Republic\n\nof Malawi”, Presentation, November 2008.\n\nMathisen, J., “Estimation of the equilibrium real exchange rate for Malawi”, IMF\n\nWorking Paper, WP/03/104, May 2003.\n\nNational Statistical Office, “Integrated Household Survey”, Malawi, 2005\n\nRajan, R. & Subramanian A., “What Undermines Aid’s Impact on Growth?” IMF\n\nWorking Paper No. 05/26, International Monetary Fund, Washington, June 2005.\n\nWhitworth, A., “Malawi’s recent fiscal performance and prospects”, DFID Malawi, 2005.\n\nWorld Bank, “Malawi Investment Climate Assessment”, Etude Economique Conseil,\n\nCanada Inc, June 2006\n\nWorld Bank, “Malawi Poverty and Vulnerability Assessment, Investing in Our Future.\n\nVolume II: Detailed Background Papers”, June 2006.\n\n\n                                 - 45", "output": {"entities": {"named_data": ["Integrated Household Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004290", "page": 46, "chunk": 0, "title": "wps5097", "pdf_url": "https://local/prwp/wps5097.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Integrated Household Survey", "label": "NAMED_DATA", "score": 0.7826629281044006, "start": 783, "end": 810, "probe_score": 0.0455, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a share of GDP. This measures trading relative to\nthe size of the economy. The next two measures of liquidity measure trading relative to stock price movements: (1)\nthe value traded ratio divided by stock return volatility, and (2) the turnover ratio divided by stock return volatility.\nThey also examine a measure of stock market integration. While a vast literature examines the pricing of risk, there\nexists very little empirical evidence that directly links risk diversification services with long-run economic growth.\nLZ do not find a strong link between economic growth and the ability of investors to diversify risk internationally.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003676", "page": 20, "chunk": 1, "title": "wps4469", "pdf_url": "https://local/prwp/wps4469.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*Gross (a)**\n\n\n\n**Unitary (b)**\n\n\n\n30\n\n\n25\n\n\n20\n\n\n15\n\n\n10\n\n\n5\n\n\n \n\n(5)\n\n\n\n160\n140\n120\n100\n80\n60\n40\n20\n\n  \n(20)\n(40)\n\n\n\n\n\n\n\n\n\n\n\n\n|95<br>79|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|Col10|\n|---|---|---|---|---|---|---|---|---|---|\n|||||||||||\n|||||||||||\n|||||||||||\n||78||94||108||104||127|\n|||||||||||\n\n\n|15|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|Col10|\n|---|---|---|---|---|---|---|---|---|---|\n|||||||||||\n|||||||||||\n||15||22||26||23||20|\n||15||22||26||23|||\n\n\n\nQ2 Q3 Q4 Q5\n(Richest 20%)\n\n\n\nQ1\n(Poorest 20%)\n\n\n\nQ2 Q3 Q4 Q5\n(Richest 20%)\n\n\n\nQ1\n(Poorest 20%)\n\n\n\n\n\nPrivate (negative) Public Net\n\n\n\n_Source: LCMS VI_\n\n\nUnlike education, healthcare results are sensitive to the assumptions made on the periodicity of health\n\nrelated episodes. Interestingly, the results of the second method—which", "output": {"entities": {"named_data": ["LCMS VI_"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005225", "page": 32, "chunk": 1, "title": "wps6052", "pdf_url": "https://local/prwp/wps6052.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "LCMS VI_", "label": "NAMED_DATA", "score": 0.5452421307563782, "start": 606, "end": 614, "probe_score": 0.7048, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the NRs and the respective\ndistrict, municipal and local authorities manage the secondary network.\n\n15. **Only 3.3 percent of the road network is paved; 52 percent are gravel roads and another about 45**\n**percent are earthen roads, which do not provide all-weather connectivity and are difficult to maintain.**\nOnly about 100-400 km of gravel NRs are being upgraded every year to paved roads. Some of the river\ncrossings on NRs do not have bridges and traffic movement on these highways is dependent on the ferry\ncrossings, which operate for only few hours in a day.\n\n\n16. **The road network is prone to disruption by floods, is not resilient, and has only few redundancies** <sup>**26**</sup> [^26: Redundancies are alternate routes] **but**\n**uncertainty about the future and limited resources make it difficult to plan robust mitigating measures.**\nUganda is exposed to a variety of natural hazards (droughts, flooding, landslides, heat waves). Each year,\nfloods impact nearly 50,000 people and over US$62 million in GDP. Uganda experiences both flash floods\nand slow-onset floods. Areas most prone to floods are the capital city, Kampala, and the northern and\neastern areas of the country.\n\n\n17. **According to UDHS, distance to health facilities in Uganda was reported as a serious problem to access**\n**health facilities and this is more acute in refugee-hosting districts in West Nile sub-region.** Mortality\nrate is still an issue in Uganda. Fertility and mortality rates, from the 2016 UDHS, forecasted that 2\npercent of women un Uganda would die from maternal causes at existing rates. Moreover, it is\ndocumented that health care services during pregnancy and childbirth and after delivery are important\nfor the survival and well-being of both the mother and infant. This situation worsens when roads are", "output": {"entities": {"named_data": ["UDHS", "2016 UDHS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000001", "page": 7, "chunk": 1, "title": "Project Information Document - Uganda: Roads and Bridges in the Refugee Hosting Districts Project - P171339", "pdf_url": "http://documents.worldbank.org/curated/en/109301595258535610/pdf/Project-Information-Document-Uganda-Roads-and-Bridges-in-the-Refugee-Hosting-Districts-Project-P171339.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "UDHS", "label": "NAMED_DATA", "score": 0.5625322461128235, "start": 1217, "end": 1221, "probe_score": 0.0457, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2016 UDHS", "label": "NAMED_DATA", "score": 0.7174077033996582, "start": 1492, "end": 1501, "probe_score": 0.9013, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " for COVID19 hospital claims and confirm that these expenditures are eligible as per the legal agreement and POM. In\naddition, and for better control over the vaccine stock, this technical audit will be conducting independent physical\nstock count of the COVID-19 vaccine doses at the vaccination sites and storage sites and reconciling the physical\nstock count with the MoPH stock reports. The PMU, from its end, will finalize the recruitment of a stock\nmanagement officer to monitor and validate the inventory of the vaccine stock which will help to align the stock\ncount between MoPH and the technical audit. In addition, the PMU will complete the procurement and\ninstallation of an accounting software to record transactions under the project and produce financial reports.\n\nh. _Budgeting:_ The WB funds will be channeled through the MoF Treasury Account and will be transferred to the\n\nproject accounts. A procurement plan and a disbursement plan for World Bank financing will be used to compare\nplanned expenditures with actual ones and monitor any variances. PMU will be preparing a separate annual\nbudget and a disbursement plan. The budget will be prepared on an annual basis and submitted to the World\nBank in November/December of each year covering the subsequent year. The PMU will monitor the variances in\nthe disbursement plan and will provide justification on any major divergence.\n\ni. _Project accounting system:_ The PMU does not have an accounting software to record transactions and produce\nfinancial reports. The same accounting software that is currently being procured under LHRP will be used under\nthe proposed project to record daily transactions and produce the required financial reports. The project Financial\nOfficer and Financial Assistant will be responsible for preparing the IFRs before their transmission to the Project\nDirector for approval. Project accounting will cover all sources and uses of project funds, including payments made\nand expenses incurred. All transactions related to the project will be recorded using the cash basis of accounting.\n\nj. _Project reporting:_ The project financial reporting includes", "output": {"entities": {"named_data": ["MoPH stock reports"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000000", "page": 54, "chunk": 1, "title": "Lebanon - Strengthening Lebanon's COVID-19 Response under the COVID-19 Strategic Preparedness and Response Program (SPRP)", "pdf_url": "http://documents.worldbank.org/curated/en/099410007282239961/pdf/BOSIB09c1bfedd05c098380dc89cfe988b8.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "MoPH stock reports", "label": "NAMED_DATA", "score": 0.5941552519798279, "start": 370, "end": 388, "probe_score": 0.0177, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013771", "page": 19, "chunk": 1, "title": "Kenya - Second Nairobi Water Supply Project and Third Nairobi Water Supply Engineering Project", "pdf_url": "https://documents.worldbank.org/curated/en/488551493241840396/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7292463183403015, "start": 272, "end": 283, "probe_score": 0.8771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the updated KNES. The\nconnection procedure will also incorporate the steps needed for mainstreaming PUE.\nKPLC agreed to submit to the Bank; (i) revised connection procedure incorporating the\nabove; and (ii) details on the connections made in FY24 (type of connection (paid-up vs.\nRES) and geographical area etc). It was agreed that KPLC will begin promoting PUE in\nconjunction with Last-Mile connectivity projects starting with a pilot. The mission\nprovided feedback on an initial outline of the pilot drafted by KPLC. It was agreed that\nKPLC will flesh out the details of the pilot and the Bank will make available to KPLC a\nconsultant to help KPLC finalize the design and support in implementation of the pilot.\n\nB. **Transfer of remaining disbursement and future disbursements to KPLC** : The mission\nnoted delays in the transfer of KSh 11 billion disbursed from IDA for achievement of results. The\n\n\n3", "output": {"entities": {"named_data": ["KNES"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005276", "page": 2, "chunk": 2, "title": "Kenya - Second Phase of Green and Resilient Expansion of Energy (GREEN) Program Project : Implementation Support Mission - 1-11 October, 2024", "pdf_url": "https://documents.worldbank.org/curated/en/099112624145015419/pdf/P180465-b8915643-cb60-4b03-b6d8-b1fd140588e3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "KNES", "label": "NAMED_DATA", "score": 0.7376726865768433, "start": 13, "end": 17, "probe_score": 0.0003, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " etc. in line\nwith ASI coverage; (iii) units covered under ASI; and (iv) public sector units. The sample design for the unorganized\nsector is a stratified multi-stage design. The first stage units (FSU) are the census villages in the rural sector and Urban\nFrame Survey (UFS) blocks in the urban sector. The ultimate stage units are enterprises in both sectors. In the case of\nlarge FSUs, one intermediate stage of sampling is the selection of three hamlet-groups/sub-blocks from each large\n\n\n12", "output": {"entities": {"named_data": ["Urban\nFrame Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006824", "page": 13, "chunk": 2, "title": "wps7814", "pdf_url": "https://local/prwp/wps7814.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Urban\nFrame Survey", "label": "NAMED_DATA", "score": 0.7737942337989807, "start": 251, "end": 269, "probe_score": 0.7072, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "agreement. Key legislations<br>on<br>public<br>procurement,<br>internal audit and national<br>audit chamber have not been<br>passed. Weaknesses in the<br>country’s overall governance<br>environment, involving lack<br>of<br>transparency<br>and<br>accountability over use of<br>public<br>funds<br>and<br>weak<br>oversight. Weak PFM systems<br>including<br>weaknesses<br>in<br>planning<br>and<br>budgeting<br>especially  budget  execution,<br>internal<br>controls<br>and<br>accounting<br>systems<br>and<br>capacity.  Also  poor  linkages<br>between strategic planning<br>and  long  term  budgeting  at<br>the sector levels.|Legislative framework in place<br>through PFMA Act 2011, draft PFM<br>regulations, public procurement<br>guidelines, ongoing implementation<br>of IFMIS in MoFP, ongoing Bank<br>support towards PFM reforms,<br>strengthening<br>capacity<br>and<br>oversight functions including SAI.<br>Project will support the contracting<br>of an External Audit Agent to<br>support SAI.<br>|No|H|\n|Entity<br>Level|H|MAFS<br>is<br>currently<br>implementing  3  other  Bank<br>projects and therefore has<br>experience<br>but<br>lacks<br>adequate capacity.|Project", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000038", "page": 53, "chunk": 1, "title": "South Sudan - Emergency Food and Nutrition Project", "pdf_url": "http://documents.worldbank.org/curated/en/713081494122547885/pdf/South-Sudan-PAD-04282017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda Electricity Access Scale-up Project (EASP) (P166685)\n\n\nthe total population live in rural areas and work in the agricultural sector, which accounts for 71 percent of the\ntotal employment and around a quarter of the country’s gross domestic product (GDP) <sup>1</sup> [^1: World Bank World Development Indicators (2017).] .\n\n2. **The topical issues of gender inequalities and climate impacts also persist in Uganda.** The people,\nenvironment and economy are highly dependent on natural resources and the country is experiencing impacts of\nclimate change. Along with poverty, land degradation, and rapid and unplanned urbanization and with the\nincrease in the spread of vector-borne diseases, these climate risks affect the people and major productive sectors\nin the country, which lack sufficient institutional and community capacities to adapt to climate change impacts.\nGender inequalities are stark with Uganda ranking 131 out of 161 countries in the 2019 Gender Inequality Index <sup>2</sup> [^2: http://hdr.undp.org/en/content/gender-inequality-index-gii.] .\nPrevalence rates of gender-based violence (GBV) in Uganda are high compared to both global and regional\naverages <sup>3</sup> [^3: It is estimated that 51 percent of women in Uganda will experience violence in their lifetime. By comparison, the global average\nprevalence rates for violence against women (physical or sexual) ages 15–49 is estimated by the World Health Organization at\n35.6 percent and the regional (Africa) average is 37.7 _percent._ <u>[http://www.noneinthree.org/uganda/policy-hub/](http://www.noneinthree.org/uganda/policy-hub/)</u> _<u>.</u>_ Accessed on\nJanuary 20, 2020.] . The Government of Uganda recognizes GBV as a serious problem and", "output": {"entities": {"named_data": ["World Bank World Development Indicators", "2019 Gender Inequality Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000040", "page": 3, "chunk": 0, "title": "Project Information Document - Uganda Electricity Access Scale-up Project (EASP) - P166685", "pdf_url": "http://documents.worldbank.org/curated/en/722961612536168002/pdf/Project-Information-Document-Uganda-Electricity-Access-Scale-up-Project-EASP-P166685.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "World Bank World Development Indicators", "label": "NAMED_DATA", "score": 0.730004608631134, "start": 298, "end": 337, "probe_score": 0.9987, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2019 Gender Inequality Index", "label": "NAMED_DATA", "score": 0.83408522605896, "start": 979, "end": 1007, "probe_score": 0.9986, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " training will address<br>the dimensions of :<br>identification of GBV<br>victims, simple counselling<br>and support mechanisms<br>and possible referral<br>pathways for further|6 months<br>|MOPH<br>|Administrative data<br>|PMU/MOPH<br>|\n\n\nPage 44 of 54", "output": {"entities": {"named_data": [], "descriptive_data": ["Administrative data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000000", "page": 48, "chunk": 1, "title": "Lebanon - Strengthening Lebanon's COVID-19 Response under the COVID-19 Strategic Preparedness and Response Program (SPRP)", "pdf_url": "http://documents.worldbank.org/curated/en/099410007282239961/pdf/BOSIB09c1bfedd05c098380dc89cfe988b8.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Administrative data", "label": "DESCRIPTIVE_DATA", "score": 0.8404330611228943, "start": 199, "end": 218, "probe_score": 0.0001, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "• <br>Process review on participatory<br>development planning process<br>• <br>Support for integration of refugees<br>into project-related programs<br>• <br>Undertake MTR|Procurement|3|3|\n|12-48<br>months|• <br>Joint ISMs with government and<br>UNHCR to monitor implementation<br>performance<br>• <br>Review of annual work/financial plans<br>• <br>Review of quarterly/annual reports<br>• <br>Review of audits/IFRs<br>• <br>Review subproject selection processes<br>• <br>Process review on participatory<br>development planning process<br>• <br>Support for integration of refugees<br>into project-related programs<br>• <br>Undertake MTR|ESS|4|4|\n|12-48<br>months|• <br>Joint ISMs with government and<br>UNHCR to monitor implementation<br>performance<br>• <br>Review of annual work/financial plans<br>• <br>Review of quarterly/annual reports<br>• <br>Review of audits/IFRs<br>• <br>Review subproject selection processes<br>• <br>Process review on participatory<br>development planning process<br>• <br>Support for integration of refugees<br>into project-related programs<br>• <br>Undertake MTR|Health|1|1|\n|12-48<br>months|• <br>Joint ISMs with government and<br>UNHCR to monitor implementation<br>performance<br>• <br>Review of annual work/financial plans<br>• <br>", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000110", "page": 60, "chunk": 6, "title": "Burundi - Integrated Community Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/644221583204472551/pdf/Burundi-Integrated-Community-Development-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Resettlement Policy Framework MWUD Draft 7B\n\n\n### **Annex A: ULGDP ESMF and RPF Screening Form**\n\n<u>ULGDP investment project name:</u>\nLocation (include map/sketch): _(e.g. region, district, etc)_\nType of activity : _(e.g. new construction, rehabilitation, periodic_\n_maintenance)_\nEstimated Cost: (Birr)\nProposed Date of Works Commencement\nTechnical Drawing and Specifications (circle Yes No\n\n\n\nYes No\n\n\n\n\n\n(circle\n\n\n\n|Reviewed : an This report is to be kept short and concise. 1. Site Selection:|nswer):|\n|---|---|\n|<br> <br>**Physical data:**|_Yes/No answers and bullet lists preferred except_<br>_where descriptive detail is essential._|\n|Site area in ha||\n|Extension of or changes to existing alignment||\n|Any existing property to transfer to project||\n|Any plans for new construction<br>|<br>|\n\n\n**2.** **Impact identification and classification:**\n_When considering the location of a ULG investment project, rate the sensitivity of the_\n_proposed site in the following table according to the given criteria. Higher ratings do not_\n_necessarily mean that a site is unsuitable – it indicates a real risk of causing adverse impacts_\n_involving resettlement and compensation. The following table should be used as a reference_ .\n\n\n**Table 6** **Impact Identification and Classification**\n\n\n\n\n\n\n\n\n\n\n|Issues|Site Sensitivity|Col3|Col4|\n|---|---|---|---|\n|**Issues**|**Low**|**Medium**|**High**|\n|Involuntary<br>re", "output": {"entities": {"named_data": [], "descriptive_data": ["Physical data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018069", "page": 32, "chunk": 0, "title": "Ethiopia - Urban Local Government Development Project : resettlement plan : Resettlement policy framework", "pdf_url": "https://documents.worldbank.org/curated/en/779931468257674845/pdf/RP11290P125316101public10BOX358335B.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Physical data", "label": "DESCRIPTIVE_DATA", "score": 0.5042476654052734, "start": 530, "end": 543, "probe_score": 0.0117, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">6 months<br>|MOPH<br>reports/ site<br>visit reports<br>|Administrative data<br>|PMU and MOPH<br>|\n|Number of communication initiatives<br>supported by the project to address<br>vaccine hesitancy <br>|<br>This indicator will track the <br>number of communication<br>initiatives that are either<br>conducted or/and<br>substantially supported by<br>MOPH for the public to<br>address the issue of<br>vaccine hesitancy. <br>|6 months<br> <br>|MOPH and<br>TPM reports<br> <br>|Administrative data<br> <br>|PMU/MOPH<br> <br>|\n|Percentage of vaccination sites visited by<br>the technical auditor in the last quarter|<br>This indicator will monitor<br>the percentage of project|3 months<br>|MOPH and<br>TPM reports|TPM reports<br>|PMU and TPM<br>|\n\n\nPage 46 of 54", "output": {"entities": {"named_data": [], "descriptive_data": ["Administrative data", "Administrative data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000000", "page": 50, "chunk": 1, "title": "Lebanon - Strengthening Lebanon's COVID-19 Response under the COVID-19 Strategic Preparedness and Response Program (SPRP)", "pdf_url": "http://documents.worldbank.org/curated/en/099410007282239961/pdf/BOSIB09c1bfedd05c098380dc89cfe988b8.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Administrative data", "label": "DESCRIPTIVE_DATA", "score": 0.6995431184768677, "start": 57, "end": 76, "probe_score": 0.7699, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Administrative data", "label": "DESCRIPTIVE_DATA", "score": 0.6343910694122314, "start": 472, "end": 491, "probe_score": 0.0084, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### **Key Findings**\n\nWherever feasible, the key findings have been framed\nusing the sectoral and functional distinctions commonly\nused in the MENA humanitarian and development sector\nresponses.\n\n### **Population Data and** **Information Management**\n\n\n**UNCRPD Article 31 – Statistics and data collection**\n1. States Parties undertake to collect appropriate\ninformation, including statistical and research data,\nto enable them to formulate and implement policies\nto give effect to the present Convention.\n2. The information collected in accordance with this\narticle shall be disaggregated.\n\n### **Data and Trends**\n\n\nDue to the broad definition, the number of individuals\nwho meet the definition of “persons with disabilities” is\nlarge. A 2011 joint report <sup>42</sup> by the WHO and the World\nBank estimates that there are one billion people, i.e. one\nout of every seven people, with a disability across the\nglobe. Most of this group has non-visible impairments,\nthat is, the person’s disability is not necessarily obvious\nto other people. The World Report on Disability\nestimates that 15 per cent of the world’s population has\na moderate or severe disability and that this proportion\nis likely to increase to 18-20 per cent in conflict-affected\npopulations. Conversely, the inclusion of disability in\ncollecting data in emergency and humanitarian contexts\nis very scarce, and publications <sup>43</sup> have referred to the\n‘invisibility’ of persons with disabilities in crisis contexts.\n\n\nUNHCR uses a statistical online population database\n(proGres) to register persons of concern and uses codes <sup>44</sup>\nto collect and flag specific needs and circumstances in\nbiodata. Some of the codes which are relevant to this\nsurvey include those classified as Disability (DS) and as\nSerious Medical (SM). UNHCR is currently in the process\nof revising all special", "output": {"entities": {"named_data": ["proGres"], "descriptive_data": ["statistical and research data", "statistical online population database"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001114", "page": 14, "chunk": 0, "title": "The power of inclusion- Mapping the Protection Responses for Persons with Disabilities Among Refugees in the Middle East and North Africa Region", "pdf_url": "https://reliefweb.int/attachments/a9759a2c-c79d-3881-bf7e-632f1a6e0bf3/74147.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "statistical and research data", "label": "DESCRIPTIVE_DATA", "score": 0.5510963797569275, "start": 382, "end": 411, "probe_score": 0.2914, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "statistical online population database", "label": "DESCRIPTIVE_DATA", "score": 0.7804253101348877, "start": 1508, "end": 1546, "probe_score": 0.7903, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "proGres", "label": "NAMED_DATA", "score": 0.7528015971183777, "start": 1548, "end": 1555, "probe_score": 0.6488, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", Togo, Uganda, and Zambia\n\n\n14 The new life-saving criteria can be found on the CERF website at <u>[https://cerf.un.org/sites/default/files/resources/CERF%20Life-](https://cerf.un.org/sites/default/files/resources/CERF%20Life-Saving%20Criteria%202020.pdf)</u>\n<u>[Saving%20Criteria%202020.pdf](https://cerf.un.org/sites/default/files/resources/CERF%20Life-Saving%20Criteria%202020.pdf)</u>\n\n\n15 While CERF is a funding mechanism only open for UN agencies, in June 2020, the ERC allocated $25m from CERF to NGOs (via IOM)\nfor Covid-19 programming.\n\n\n[16 The organisation ‘Humanitarian Outcomes’ (https://www.humanitarianoutcomes.org) has been commissioned to track the dispersal](https://www.humanitarianoutcomes.org)\nof funding following the conference. See Oslo Commitments on Ending Sexual and Gender-based Violence in Humanitarian Crises\nSummary of 2020 Collective Progress Report\n\n\n17 ECHO is one of the few donors that tracks funding to sectors. It provided this data as part of the consultation for the report on its funding\nto the protection sector.\n\n\n18 See for example ‘Still Unprotected’ report of SCI et al, October 2020\n\n\n19 International funding was distributed among the following sectors: clearance and risk education (56 per cent of all funding), victim\nassistance (eight per cent), capacity-building (one per cent), and advocacy (one per cent)\n\n\n20 See “Human rights situation in the Central African Republic”, Report of the Independent Expert on the situation of human", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000615", "page": 45, "chunk": 3, "title": "Breaking the glass ceiling: A smarter approach to protection financing", "pdf_url": "https://reliefweb.int/attachments/5a61e891-d2cf-3dc2-8aad-f36756a31e02/breaking-the-glass-ceiling---a-smarter-approach-to-protection-financing-report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " system productivity or degradation, and the extent to which the natural resource<br>is being managed sustainably and can recover to shocks such as drought. The method used is<br>the ExAct carbon balance estimation tool, which calculates carbon accumulation and<br>emissions based on project biophysical output data. The sub-indicator measures the<br>cumulative net change in carbon emissions (tCO2eq) during the implementation phase of<br>the project.|Measures the annual net change in CO2 emissions due to the project's wide range of on-<br>ground land management and use interventions. Changes in the amount of carbon present<br>in soil, crop, rangeland and forest/trees or mixed or mosaic systems can indicate overall<br>changes in system productivity or degradation, and the extent to which the natural resource<br>is being managed sustainably and can recover to shocks such as drought. The method used is<br>the ExAct carbon balance estimation tool, which calculates carbon accumulation and<br>emissions based on project biophysical output data. The sub-indicator measures the<br>cumulative net change in carbon emissions (tCO2eq) during the implementation phase of<br>the project.|\n|Area of Program watersheds<br>with Watershed User<br>Association (WsUA)<br>registered, with approved<br>Watershed Management<br>Plan (WMP) prepared in a<br>participatory manner<br>(Hectare(Ha))|0.00|Mar/2019|2,608,282.00|13-Dec-2024|3,496,482.70|02-Feb-2026|3,100,000.00|Sep/2025|\n|Area of Program watersheds<br>with Watershed User<br>Association (Ws", "output": {"entities": {"named_data": [], "descriptive_data": ["project biophysical output data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000749", "page": 11, "chunk": 3, "title": "Disclosable Version of the ISR - ETHIOPIA CLIMATE ACTION THROUGH LANDSCAPE MANAGEMENT PROGRAM FOR RESULTS - P170384 - Sequence No : 13", "pdf_url": "https://documents.worldbank.org/curated/en/099021526075518669/pdf/P170384-10aa50b3-8c5f-4a7c-977d-89cd51a998cb.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "project biophysical output data", "label": "DESCRIPTIVE_DATA", "score": 0.8005551099777222, "start": 284, "end": 315, "probe_score": 0.7827, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nCHAD Improving Learning Outcomes Project (P175803)\n\n\n  - **Interruptions in learning are common** . A 2019 survey indicated that 70 percent of school children aged 7-14 years\nexperienced classroom stoppages during the school year due to teacher absence; the other most common reasons\ngiven were strikes (66 percent) and natural catastrophe (20 percent). In the 2015-16 school year, the fall in oil\nprices led to a sharp reduction in salary payments, resulting in the closure of one quarter of primary schools.\n\n\n_Figure 1: Pupil-teacher ratio by province_\n\n\nSource: Education Statistics Yearbook, 2018-2019\n\n\n  - **The quality of teaching can be improved** . Aside from the difficulties of teaching effectively to overcrowded\nclassrooms, teachers have weak pedagogical skills and often do not master course content themselves. In a 2019\ncompetency test, primary teachers had the second lowest score (421) in reading comprehension among 14\nparticipating countries, and 38 percent were at Level 1 or below (vs. 17 percent for all countries). In terms of the\npedagogy of reading comprehension, Chad’s score was again the second lowest. With respect to mathematical\ncompetencies, primary teachers had the lowest score (419), with 69 percent of teachers operating at Level 1 or\nbelow (vs 35 percent for all countries). Pedagogical competencies in mathematics were third lowest. There was\nlittle or no difference in performance between teachers based on their years of work experience, while teachers\nwith a university degree performed markedly better than those with a secondary diploma. <sup>13</sup> [^13: PASEC 2019]\n\n  - **Remedial programs for children returning to school are not fully functional** . The Education Act No. 16 of March\n2006 introduced two types of education as part of the education system to help absorb out-of-school children: a\n4-year non-formal basic education program which targets children aged 9-", "output": {"entities": {"named_data": ["Education Statistics Yearbook"], "descriptive_data": ["2019 survey", "2019\ncompetency test"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000009", "page": 7, "chunk": 0, "title": "Concept Project Information Document (PID) - CHAD Improving Learning Outcomes Project - P175803", "pdf_url": "http://documents.worldbank.org/curated/en/234501637169242309/pdf/Concept-Project-Information-Document-PID-CHAD-Improving-Learning-Outcomes-Project-P175803.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "2019 survey", "label": "DESCRIPTIVE_DATA", "score": 0.8109083771705627, "start": 121, "end": 132, "probe_score": 0.55, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Education Statistics Yearbook", "label": "NAMED_DATA", "score": 0.8407483696937561, "start": 585, "end": 614, "probe_score": 0.9959, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2019\ncompetency test", "label": "DESCRIPTIVE_DATA", "score": 0.6511232852935791, "start": 851, "end": 871, "probe_score": 0.5194, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda: Investment for Industrial Transformation and Employment (P171607)\n\n\nenvironments, distribution systems, and customer engagement methodologies. Also, start-ups and scale-ups that\nhad forecasted high growth and future revenue but have high fixed costs and unproven unit economics will be\naffected. <sup>43</sup> [^43: See: Baker McKenzie. 2020. “The Impact of COVID-19 on Key African Sectors.” Quartz Africa. 2020. “African Startup Funding is Set to\nDrop by Nearly half in 2020.”]\n\n\n63. The Independent Evaluation Group (IEG) recommendations on implementing lines of credit which have\nbeen incorporated for the use of such funding by MFDs, MFIs, and SACCOs in Tiers 3 and 4 also focused on districts\nand regions with refugees and their host communities. The lines of credit will be applied only to those Tier 3 and\n4 institutions which have been assessed and are deemed qualified according to a set of key indicators, including a\nmeasure of the quality of the loan portfolio, capital adequacy, and governance; are compliant with the established\nprudential norms; and have adopted social and environmental frameworks or check lists. The sizing of the lines of\ncredit is envisaged to be a modest fraction of overall demand in the market segment, thus reducing the probability\nof poor disbursements and the need for large cancellations. <sup>44</sup> [^44: World Bank IEG. 2006. “Lines of Credit.”]\n\n\n64. An assessment of CGFs <sup>45</sup> [^45: A2F Consulting LLC. 2020. “Feasibility Study into the Establishment of a Credit Guarantee Fund in Kenya.”] noted the important role that these can play in countries with weak institutional\nenvironments. In addition to increasing the risk appetite of banks and providing a substitute for collateral that\nSMEs may well not be able to provide, credit guarantee schemes (CGSs) can play an important role in encouraging\nthe improvement of information available on borrowers in", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000021", "page": 33, "chunk": 0, "title": "Uganda - Investment for Industrial Transformation and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/469061641926083502/pdf/Uganda-Investment-for-Industrial-Transformation-and-Employment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "aires doivent\nimmédiatement négocier la réouverture des écoles fermées\npar le biais d'approches de médiation et de négociation basées\ndans la communauté.\n\n\n**3- Élaborer et mettre en œuvre des plans d'intervention**\n**fondés sur des données quantitatives et qualitatives, en**\n**accordant la priorité aux personnes les plus exposées**\n\n-  Les gouvernements, les organisations internationales\nhumanitaires et de développement et la société civile\ndevraient mettre en œuvre la boîte à outils pour la collecte et\nl'analyse de données sur les attaques contre l'éducation de la\n\n\n**4** [Global Partnership and Fund to End Violence Against Children (2016). Safe to Learn](https://www.end-violence.org/safe-to-learn#:~:text=THE%202021%2D2024%20SAFE%20TO%20LEARN%20STRATEGY&text=Safe%20to%20Learn%20is%20a%20coalition%20of%2014%20powerful%20partners,access%20to%20safe%20learning%20environments.)\n\n<u>[initiative.](https://www.end-violence.org/safe-to-learn#:~:text=THE%202021%2D2024%20SAFE%20TO%20LEARN%20STRATEGY&text=Safe%20to%20Learn%20is%20a%20coalition%20of%2014%20powerful%20partners,access%20to%20safe%20learning%20environments", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["données quantitatives et qualitatives"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000605", "page": 4, "chunk": 2, "title": "Attaques sur l'éducation en Afrique de l'Ouest et du centre - Mise à jour 2023", "pdf_url": "https://reliefweb.int/attachments/58f5ee5c-7368-4a8e-8700-84c2d635dbe5/Education_Update_Note_InDesign_August_23_FR%20V2.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "données quantitatives et qualitatives", "label": "VAGUE_DATA", "score": 0.7166732549667358, "start": 233, "end": 270, "probe_score": 0.0195, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " able and capable of negotiating a temporary\nrelief in the current economic crisis, while creating the foundation for rapid recovery and support continued economic\ntransformation.\n\n\nCountry Context\n\n**The Covid-19 pandemic is putting Uganda’s growth trajectory at risk and exacerbating structural constraints and**\n**increasing pressure on the poor and vulnerable. particularly those in refugee and host communities.** Uganda’s real\n\n\nJun 09, 2020 Page 3 of 9", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000043", "page": 2, "chunk": 1, "title": "Project Information Document - Uganda: Investment for Industrial Transformation and Employment - P171607", "pdf_url": "http://documents.worldbank.org/curated/en/790161604416004965/pdf/Project-Information-Document-Uganda-Investment-for-Industrial-Transformation-and-Employment-P171607.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_Syrian Refugees in Jordan_ <sup>_36_</sup> [^36: Throughout this document, we use the term ‘refugees’ as shorthand for both asylum seekers and refugees.]\n\n\n51. According to the recent Government census, there are approximately 1.3 million Syrian\nrefugees currently in Jordan. Approximately 655 thousands Syrian refugees—likely among the most\nvulnerable—have registered with the UNHCR. As refugees’ savings are depleted and humanitarian aid\nbecomes increasingly uncertain, many are turning to negative coping strategies including child labor.\n\n\n52. In many ways, the labor market characteristics of Syrian refugees in Jordan are complementary\nto those of Jordanians. According to a recent ILO survey, 23 percent of Syrian refugees have work\nexperience in construction, versus 7 percent among Jordanians; 9 percent of Syrian refugees have\nexperience in agriculture, versus 2 percent of Jordanians; and 16 percent of Syrian refugees have\nexperience in manufacturing versus 11 percent of Jordanians. Although, overall, Jordanians are much\nbetter educated than Syrian refugees and 60 percent of Syrian refugees have not completed basic\neducation, about 6 percent of Syrians refugees have attended university. <sup>37</sup> [^37: Op cit ILO/FAFO study.]\n\n\n53. Before 2016, the vast majority of Syrian refugees were prohibited from working legally in\nJordan. Although there was no law against Syrian refugees working, very few met the requirements of\nthe existing work permit regulations because they lacked a valid passport. As of the end of 2015, only\n5,300 Syrian refugees were working legally in Jordan.\n\n\n54. Recognizing the risk that Syrian refugees could remain in Jordan for an extended period and\nwould be dependent on others if they were unable to earn an income, the GoJ proposed the Jordan\nCompact. Under the Compact, the GoJ has committed to allow job opportunities for 50,000 Syrian\nrefugees during the first year of implementation of the Compact, rising to 200,000 in the coming years.\nMoreover, under the Compact, the international community", "output": {"entities": {"named_data": ["ILO survey"], "descriptive_data": ["Government census"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000137", "page": 69, "chunk": 0, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents1.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Government census", "label": "DESCRIPTIVE_DATA", "score": 0.7763534784317017, "start": 185, "end": 202, "probe_score": 0.9572, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "ILO survey", "label": "NAMED_DATA", "score": 0.7426784038543701, "start": 689, "end": 699, "probe_score": 0.9919, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " year\nbefore. This is the highest number since the early 70,000\n\n60,000\n\n1990s. By nationality, the main beneficiaries of the 50,000\nUNHCR-facilitated resettlement programmes in 2008 40,000\nwere refugees from Myanmar (23,200), Iraq (17,800), 30,000\nBhutan (8,100), Somalia (3,500), Burundi (3,100), and 20,000\n\n10,000\n\nthe Democratic Republic of the Congo (1,800). 0\n\n'92 '94 '96 '98 '00 '02 '04 '06 '08\n\nSome 85 UNHCR country offices were engaged in\nfacilitating resettlement during 2008. The largest number of refugees who were resettled with\nUNHCR assistance departed from Thailand (16,800), Nepal (8,200), the Syrian Arab Republic\n(7,300), Jordan (6,700), and Malaysia (5,900). These five UNHCR offices together accounted for\n7 out of every 10 resettlement departure assisted by the organization in 2008.\n\n<u>Local integration</u>\n\nThe degree and nature of local integration are difficult to measure in quantitative terms, though\nthis is the final and crucial step towards obtaining the full protection of the asylum country. In\nthose cases where refugees acquire the citizenship through naturalization, statistical data is often\nvery limited, as the countries concerned generally do not distinguish between refugees and others\nwho have been naturalized. Moreover, national laws in many countries do not permit refugees to\nbe naturalized. Therefore, the naturalization of refugees is both restricted and under-reported.\n\nThe limited data on naturalization of refugees available to UNHCR show that during the past\ndecade more than 1.1 million refugees were granted citizenship by their asylum country. The\nUnited States of America alone accounted for two thirds of them, even though their 2008\nnumbers are not yet available. Azerbaijan and Armenia also granted citizenship to a significant\nnumber of refugees during the same period", "output": {"entities": {"named_data": [], "descriptive_data": ["data on naturalization of refugees"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000784", "page": 11, "chunk": 1, "title": "2008 Global Trends: Refugees, Asylum-Seekers, Returnees, Internally Displaced and Stateless Persons", "pdf_url": "https://reliefweb.int/attachments/73888fea-5868-3760-9f0f-c4b9b6988ba9/D55D38D885CE853BC12575D70048C172-UNHCR_Jun2009.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7020359039306641, "start": 1108, "end": 1124, "probe_score": 0.0411, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "data on naturalization of refugees", "label": "DESCRIPTIVE_DATA", "score": 0.8640839457511902, "start": 1437, "end": 1471, "probe_score": 0.1559, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "never married (men more frequently than women, of which one third are living in India), those who are\ndivorced or separated (women representing the majority of the poor in that group, a quarter of them being\nin Latin America and the Caribbean), and those who are widowed (women more frequently than men).\n\n\n_Figure 5. Distribution of the poor by sex and marital status (ages 15+)_\n\n\n\n100\n\n\n90\n\n\n80\n\n\n70\n\n\n60\n\n\n50\n\n\n40\n\n\n30\n\n\n20\n\n\n10\n\n\n0\n\n\n\n**Women** **Men**\n\n\n\nMarried Living together Never married Divorced/ separated Widowed\n\n\nNote: Total sample 89 countries\nSource: WB Staff’s calculations based on GMD.\n\n\nA focus on gender differences in poverty through the lifecycle, as captured by age transitions\n(childhood to adolescence, to adulthood, to elder years) and the related changes in own household\nformation (marital status and living arrangements, and presence of children), reveals meaningful gender\ndifferences in poverty rates.\n\n\nEarly marriage is correlated with higher poverty for girls and boys, and marital shocks at that age\nmake girls extremely vulnerable to poverty. Girls who are married or widowed in the 15‐17 age group (only\none percent of all poor girls) are 11.2 and 30.6 percentage points more likely to live in poor households\ncompared to the average young women of that same age, among whom the most frequent marital status\nis single or never married <sup>24</sup> [^24: Marital status is only available for individuals 15 years old and above in the GMD. The data refers to marital status at the time of\nthe survey.] . Married young males have poverty rates 17 percentage points higher than the\naverage men of that same age group. But, contrary to what we observe with girls, poverty rates are lower\nfor the less than one percent of boys (0.13 percent) who report being divorced or widowers.\n\n\nFigure 6 shows the impact of changes in marital status on other age groups", "output": {"entities": {"named_data": ["GMD", "GMD"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007308", "page": 15, "chunk": 0, "title": "wps8360", "pdf_url": "https://local/prwp/wps8360.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "GMD", "label": "NAMED_DATA", "score": 0.8290071487426758, "start": 602, "end": 605, "probe_score": 0.9917, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "GMD", "label": "NAMED_DATA", "score": 0.6648509502410889, "start": 1474, "end": 1477, "probe_score": 0.9934, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. HUMAN MOBILITY IN NATIONAL DISASTER\n\n\n\nIt is noted that in the context of climate change\nand disaster risk in the Oceania/Pacific region,\nsome countries are putting plans in place\nfor access to labour markets and citizenship\nin other countries, highlighting the need for\ndurable solutions planning, <sup>28</sup> [^28: International Organization for Migration and International Labour Organization, Pacific Climate Change Migration and\nHuman Security: Climate Change and Labour Mobility in Pacific Island Countries Policy Brief, 2022. Available at: <u>[https://](https://environmentalmigration.iom.int/sites/g/files/tmzbdl1411/files/documents/wcms_856083.pdf)</u>\n<u>[environmentalmigration.iom.int/sites/g/files/tmzbdl1411/files/documents/wcms_856083.pdf.](https://environmentalmigration.iom.int/sites/g/files/tmzbdl1411/files/documents/wcms_856083.pdf)</u>] for example:\n\n\n- Tuvalu’s National Climate Change\nPolicy 2021-2030 highlights the need\nfor a national plan that provides durable\nsolutions and considers labour migration\nschemes and permanent resettlement.\n\n- Micronesia’s Nationwide Integrated\nDisaster Risk Management and Climate\nChange Policy specifically uses the\nterm ‘environmental migration’. It seeks\nadaptation strategies “while addressing\nhuman mobility associated with natural\ndisasters and climate change through\ndurable solutions” and also discusses\nlabour migration within the context of\neventual resolution strategies.\n\n\nThe 2018 Baseline Mapping considered\nthe topic of “post-disaster relocations of\nhouseholds or communities already displaced\nfrom their homes by disaster and unable to\nreturn” (p.35) under the broader heading\nof “relocation (or internal resettlement) as\na DRR measure” (p. 34). The 2023 Mapping\nconsidered this same topic as ‘resettlement\nor relocation’ following a displacement\nsituation.\n\n\nOf the 112 national DRR strategies and related\ninstruments reviewed in the 2023 Mapping,\n23 included references to resettlement or\nrelocation. The highest number", "output": {"entities": {"named_data": ["2018 Baseline Mapping", "2023 Mapping", "2023 Mapping"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001173", "page": 24, "chunk": 0, "title": "Mapping human mobility in national and regional disaster risk reduction strategies and related instruments", "pdf_url": "https://reliefweb.int/attachments/b375d337-f12f-45bb-8865-f72aaeb25d84/unhcr-mapping-report-on-human-mobility-on-drr-strategies-high-quality-version.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "2018 Baseline Mapping", "label": "NAMED_DATA", "score": 0.7345542311668396, "start": 1452, "end": 1473, "probe_score": 0.9925, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2023 Mapping", "label": "NAMED_DATA", "score": 0.5040242671966553, "start": 1729, "end": 1741, "probe_score": 0.4935, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2023 Mapping", "label": "NAMED_DATA", "score": 0.5168425440788269, "start": 1914, "end": 1926, "probe_score": 0.5298, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "u>(0.033)</u>\nThreshold 1 -2.045 <sup>***</sup>\n(0.304)\nThreshold 2 -1.171 <sup>***</sup>\n<u>(0.296)</u>\nObservations 6005 6005 6005 6005\n<u>PseudoR^2</u> <u>0.33878</u>\nStandard errors in parentheses. SE clustered at the individual level. <sup>*</sup> _p_ < 0.10, <sup>**</sup> _p_ < 0.05, <sup>***</sup> _p_ < 0.01. Asset index above median is\ncomputed using information about asset ownership in August 2014. Column (1) regression includes time dummies.\nSource: LDPS 2014-15\n\n20", "output": {"entities": {"named_data": ["LDPS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007004", "page": 21, "chunk": 4, "title": "wps8012", "pdf_url": "https://local/prwp/wps8012.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "LDPS", "label": "NAMED_DATA", "score": 0.7841719388961792, "start": 464, "end": 468, "probe_score": 0.9906, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "25**</sup> In response, UNHCR has worked to ensure\n\n\n\nChapter 2\n\n\nthat families have access to these programmes,\nsupporting more than 744,000 children and youth\nwith distance/home-based learning.\n\n\nEven before the pandemic, refugee children were\nat a grave disadvantage in terms of access to\neducation. COVID-19 has worsened the situation,\nwith a refugee child being twice as likely to be\nout of school as a non-refugee child. <sup>**26**</sup> UNHCR\nremains deeply concerned by the lasting effect of\nthe pandemic on education - as many as half of all\nrefugee girls in secondary school may not return\nto class without greater socio-economic support\nto their families, water, sanitation and hygiene\nmeasures in schools, as well as catch-up learning\nopportunities.\n\n\n**THE NEED FOR TIMELY AND**\n**ACCURATE DATA**\n\n\nThe availability of adequate and timely\ninformation has become more important than\never in order to assess the pandemic’s\nimpact on forcibly displaced populations. To\nmitigate these data gaps, humanitarian and\ndevelopment organizations have been\ncollecting data remotely, such as through\ntelephone surveys, self-directed surveys and\nremote key informant interviews. <sup>**27**</sup> Datasets\ndetailing the impact of COVID-19 on forcibly\ndisplaced populations in Lebanon, Kenya,\nMauritania and Zambia are already available\nin UNHCR’s Microdata Library, with more\ndatasets being curated. <sup>**28**</sup>\n\n\n\n**21** [See www.unhcr.org/news/briefing/2020/5/5eccbfec4/urban-refugees-struggling-survive-economic-impact-covid-19-worsens-east.html](https://www.unhcr.org/news/briefing/", "output": {"entities": {"named_data": [], "descriptive_data": ["Datasets\ndetailing the impact of COVID-19"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000911", "page": 8, "chunk": 1, "title": "UNHCR Mid-Year Trends 2020", "pdf_url": "https://reliefweb.int/attachments/86cd18c6-c5c8-3f2a-8618-f2999300f368/5fc504d44.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Datasets\ndetailing the impact of COVID-19", "label": "DESCRIPTIVE_DATA", "score": 0.7767961621284485, "start": 1197, "end": 1238, "probe_score": 0.7883, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "fixed effects). The coefficient for _Hindu_ _Non-Dalit_ was negative and significant in the case\n\n\nwithout control variables (columns 1 and 2) but the variable lost significance once other\n\n\ncontrols and fixed effects were included, indicating that they were statistically speaking no\n\n\ndifferent from their Dalit counterparts once we include measures of socio-economic status.\n\n\nThe Muslim effect however was robust and significant, suggesting that the effect may not\n\n\nbe driven by socio-economic status, at least to the same extent as the Dalits.\n\n\nAs an additional robustness check, we perform a similar analysis using village-level\n\ndata. <sup>18</sup> Our sample now consists of the 3644 villages in the NFHS-3, and our left-hand\n\n\nside variable of interest will be average fertility of women in a village (defined as the total\n\n\nnumber of children divided by the number of women who were interviewed in a village).\n\n\nThe dependent variables are as follows: the fraction of ever-born boys who had died before\n\n\nthe age of 5 and the fraction of ever-born girls who had died before the age of 5. The\n\n\nset of our control variables is similar to that in the previous section, except that they are\n\n\nconstructed as village-level averages. We control for the fraction of a village’s population\n\n\nthat is Muslim, as well as upper-caste Hindus. We also control for the average female\n\n\nage, age at marriage, primary school completion and the fraction of the population that\n\n\nhas never attended school. Similar variables for men - average age, fraction of men who\n\n\ncompleted primary school and fraction of men who never attended school – are also included\n\n\nas controls. We also include a set of control variables that focus on wealth. Measures of\n\n\naverage landholdings, the average household wealth index and the fraction of households\n\n\nthat are rural, are included in this group of control variables. Finally, we also include a\n\n\nset of community level", "output": {"entities": {"named_data": ["NFHS-3"], "descriptive_data": ["village-level\n\ndata"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004289", "page": 14, "chunk": 0, "title": "wps5096", "pdf_url": "https://local/prwp/wps5096.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "village-level\n\ndata", "label": "DESCRIPTIVE_DATA", "score": 0.7995654940605164, "start": 623, "end": 642, "probe_score": 0.9095, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "NFHS-3", "label": "NAMED_DATA", "score": 0.8819373250007629, "start": 710, "end": 716, "probe_score": 0.9708, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "OCHA Office of Commission for Humanitarian <sup>Assistance</sup>\nPAMC Project Approval and Monitoring Committee\nPETS Public Expenditure Tracking Survey\nPOM Project Operational Manual\nPPA Participatory Poverty Assessment\nQER Quality Enhancement Review\nRUF Revolutionary United Front\nSAPA Social Action and Poverty Alleviation <sup>Program</sup>\nSHARP Sierra Leone HIV/AIDS Response Project\nSLRA Sierra Leone Roads Authority\nSOCAT Social Capital Assessment Tool\nSPP Strategic Planning and Action Process\nTEP Training and Employment Program\nTSS Transitional Support Strategy\nUNAMSIL United Nations Mission for Sierra <sup>Leone</sup>\nUNHCR United Nations High Commission for <sup>Refugees</sup>\nUNICEF United Nations Children's Fund\nUNOPS United National Operations Support\n\n\nVice President: Mr. Callisto Madavo\nCountry Director: Mr. Mats Karlsson\nSector Manager: Mr. Alexandre Abrantes\nTask Team Leader/Task Manager: Ms. Eileen Murray", "output": {"entities": {"named_data": ["PETS Public Expenditure Tracking Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013711", "page": 2, "chunk": 0, "title": "Ethiopia - Finchaa Hydroelectric (Second Power) Project", "pdf_url": "https://documents.worldbank.org/curated/en/484701468038030177/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "PETS Public Expenditure Tracking Survey", "label": "NAMED_DATA", "score": 0.6079578399658203, "start": 112, "end": 151, "probe_score": 0.0351, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a legal status in Bangladesh.\n\n\n**3.4** **Financial and administrative services**\n\n\nRohingya refugees cannot open an account with either a regulated bank or a mobile financial service,\nabsent a legally-accepted proof of identity document. The biometric ID card provided by means of the\njoint UNHCR-Government of Bangladesh registration and verification exercise is not accepted for this\npurpose.\n\n\nBoth public and private banks adhere to the rules and regulations set by the Central Bank of Bangladesh\n(Bangladesh Bank) as well as the Know Your Customer (KYC) principles adopted by the Bangladeshi\nFinancial Authority. The Bangladesh Bank has allowed an electronic-KYC (e-KYC) process for some banks\nbased on a <u>[guideline from December 2019. The guidelines for e-KYC explicitly state that the “e-KYC shall](https://www.bb.org.bd/mediaroom/circulars/aml/jan082020bfiu25.pdf)</u>\nonly be applicable for natural persons who have a valid NID [national identity] document.” <u>In order to open</u>\nmobile banking accounts, one must furnish the national ID reference and have a registered mobile number.\nA <u>[Directive on Biometric Verification Systems (2015)](http://www.btrc.gov.bd/sites/default/files/Directives%20on%20Biometric%20Verification%20System.pdf)</u> <u>from the Bangladesh Telecommunication Regulatory</u>\n<u>Commission requires all SIM card registration data to be validated biometrically against the government’s</u>\nnational ID database. As Rohingya refugees are not part of that database, they are not able to purchase\nSIM cards.\n\n\n6 R E F U G E E P O L I C Y R E V I", "output": {"entities": {"named_data": [], "descriptive_data": ["SIM card registration data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000930", "page": 5, "chunk": 2, "title": "Bangladesh: Refugee Policy Review Framework Country Summary as at 30 June 2020 (March 2022)", "pdf_url": "https://reliefweb.int/attachments/8a182202-6247-3a13-bac6-ca2f705f2f61/Bangladesh%20-%20Refugee%20Policy%20Review.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "SIM card registration data", "label": "DESCRIPTIVE_DATA", "score": 0.8025466203689575, "start": 1347, "end": 1373, "probe_score": 0.0737, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nthey meet the criteria of the refugee definition in that instrument,\nwhether they are formally recognized as a refugee or not (UNHCR\nNote on Determination of Refugee Status under International\nInstruments). <u>[[source]](https://www.unhcr.org/excom/scip/3ae68cc04/note-determination-refugee-status-under-international-instruments)</u>\n\n\nA \" **migrant** \" refers to any person who is moving or has moved\nacross an international border or within a State away from their\nhabitual place of residence, regardless of (1) the person’s legal\nstatus; (2) whether the movement is voluntary or involuntary; (3)\nwhat the causes for the movement are; or (4) what the length of\nthe stay is. <u>[[source]](https://www.iom.int/who-is-a-migrant)</u>\n\n#### Limitation of available data on Children and UASC\n\nThere is no comprehensive data on arrivals (both adults\nand children) in Europe, especially by land and air, as such\nmovements are largely irregular and involve smuggling\nnetworks, which are difficult to track. If collected, data is rarely\ndisaggregated by nationality, risk category, gender or age.\nReliable data on the number of UASC either arriving or currently\nresiding in different European countries is often unavailable.\nThe number of asylum applications filed by UASC is used\nto provide an indication of trends but does not necessarily\nprovide an accurate picture of the caseload due to backlogs\nin national asylum systems, onward irregular movements\nor children not applying for asylum at all. In addition, due to\ndifferent definitions and national procedures and practices,\ncollecting accurate data on separated children specifically\nis very challenging (e.g. separated children being registered\nas either accompanied or unaccompanied). It should also be\nnoted", "output": {"entities": {"named_data": [], "descriptive_data": ["data on arrivals"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000909", "page": 6, "chunk": 1, "title": "Refugee and Migrant Children in Europe: Accompanied, Unaccompanied and Separated: Overview of Trends (January - December 2021)", "pdf_url": "https://reliefweb.int/attachments/86793319-617f-49c6-8957-11fc996732a3/Refugee%20and%20Migrant%20Children%20in%20Europe%202021-FINAL.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "data on arrivals", "label": "DESCRIPTIVE_DATA", "score": 0.5165290236473083, "start": 817, "end": 833, "probe_score": 0.3427, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|**Enhanced use of water resource management information system and data**|**Enhanced use of water resource management information system and data**|**Enhanced use of water resource management information system and data**|\n|Indicator Name|Baseline|Baseline|Actual (Previous)|Actual (Previous)|Actual (Current)|Actual (Current)|Closing Period|Closing Period|\n|Indicator Name|Value|Month/Year|Value|Date|Value|Date|Value|Month/Year|\n|Proportion of rural and urban<br>water supply scheme designs<br>using data from the water<br>resources management<br>information system<br>(Percentage)|0.00|Dec/2018|0.00|28-Feb-2024|67.00|18-Oct-2024|75.00|Jun/2024|\n|Proportion of rural and urban<br>water supply scheme designs<br>using data from the water<br>resources management<br>information system<br>(Percentage)|Comments on<br>achieving  targets|Comments on<br>achieving  targets|The indicator measures accessibility and use of the water resources monitoring system. It<br>measures the use of the water resource data (meteorology, hydrology and groundwater) to<br>inform design and management of water supply systems delivered under the Project.|The indicator measures accessibility and use of the water resources monitoring system. It<br>measures the use of the water resource data (meteorology, hydrology and groundwater) to<br>inform design and management of water supply systems delivered under the Project.|The indicator measures accessibility and use of the water resources monitoring system. It<br>measures the use of the water resource data (meteorology, hydrology and groundwater) to<br>inform design and management of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["water resource data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:004975", "page": 6, "chunk": 4, "title": "Disclosable Version of the ISR - One WASH-Consolidated Water Supply Sanitation and Hygiene Account Project (One WASH-CWA) - P167794 - Sequence No : 10", "pdf_url": "https://documents.worldbank.org/curated/en/099110324212016436/pdf/P167794-2c04414a-b6b0-4459-b52f-f7b5c5e6059b.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "water resource data", "label": "VAGUE_DATA", "score": 0.5389188528060913, "start": 988, "end": 1007, "probe_score": 0.898, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda Digital Acceleration Project - GovNet (P171305)\n\n\n\n|Col1|hosted at the new Data<br>Center that will be<br>established|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|E-waste centers established|<br>Number of new E-Waste<br>centers established by the<br>project in the refugee host<br>communities (2) and<br>nationally (2).|Annually<br>|Project<br>completion<br>reports<br>|The progress of the<br>implementation will be<br>monitored annually<br>based on activity<br>completion reports<br> <br>|NITA-U, NEMA, UBOS<br>|\n|People able to prove their identity<br>digitally|Percentage of people who<br>are 16 or older able to prove<br>their identity digitally<br>through a variety of digital<br>authentication modalities<br>offered by either<br>government or private<br>sector<br>|<br>Annually<br>|The data will<br>be sourced<br>from the<br>ID4D dataset<br>and GoU<br> <br>|<br>The data sourced from<br>ID4D dataset and GoU,<br>will be analyzed to<br>measure how many<br>people above 16 were<br>able to prove their<br>identity digitally while<br>receiving e-Services<br>|NITA-U<br>|\n|User satisfaction with effectiveness of<br>digital public", "output": {"entities": {"named_data": ["ID4D dataset", "GoU"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000075", "page": 55, "chunk": 0, "title": "Uganda - Digital Acceleration Project", "pdf_url": "http://documents1.worldbank.org/curated/en/473041622944887337/pdf/Uganda-Digital-Acceleration-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "ID4D dataset", "label": "NAMED_DATA", "score": 0.742062509059906, "start": 860, "end": 872, "probe_score": 0.7838, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "GoU", "label": "NAMED_DATA", "score": 0.5865985751152039, "start": 880, "end": 883, "probe_score": 0.9903, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nGovernance Modernization to Enable Efficient Service Delivery Project (P178808)\n\n|Col1|motivations, incentives, and access to and quality of training. The baseline indicator was created using 19 indicators<br>on recruitment, 39 on performance management, and 54 on training. Weightages were provided to each of the 3<br>categories with 40% on recruitment, 20% on performance management, and 40% on training to create the index.|\n|---|---|\n|Responsibility for Data<br>Collection|PMCSO (CSC)|\n\n\n\n**Monitoring & Evaluation Plan: Intermediate Results Indicators by Components**\n\n**<u>Improved Human Resource Management Capabilities</u>**\n\n|Complete HR records of federal civil servants in new IHRPS|Col2|\n|---|---|\n|**(Percentage)**|**(Percentage)**|\n|Description|Measures the coverage of the IHRPS, in terms of number of civil servants captured in the system, disaggregated by<br>gender, grade, and federal public body.|\n|Frequency|Annually|\n|Data source|IHRPS Generated Reports|\n|Methodology for Data<br>Collection|Summation of the total number of complete civil servant records in the IHRPS, disaggregated by gender, grade, and<br>sector/ministry (public body).|\n|Responsibility for Data<br>Collection|PMCSO (CSC)|\n\n\n|Federal Public Bodies with approved competency frameworks, including gender, climate, and digital competencies|Col2|\n|---|---|\n|**(Number)**|**(Number)**|\n|Description|Measures the extent to which Federal Public Bodies supported by the Project", "output": {"entities": {"named_data": ["IHRPS Generated Reports"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:004104", "page": 41, "chunk": 0, "title": "Ethiopia - Governance Modernization to Enable Efficient Service Delivery Project", "pdf_url": "https://documents.worldbank.org/curated/en/099082124120033234/pdf/BOSIB-8a85947f-785c-45db-a183-95ed26b4df7a.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "IHRPS Generated Reports", "label": "NAMED_DATA", "score": 0.7858819365501404, "start": 971, "end": 994, "probe_score": 0.6892, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "up survey had 2.5 kids in the appropriate\n\n\nage range to enroll in the lottery, but only enrolled 1.3 children. This decision already seems to\n\n\nreflect the allocation of activities within the household. In families that received no subsidies, 93\n\n\npercent of registered children reportedly attend school while only 75 percent of unregistered\n\n\nchildren attend. Similarly, registered children work 3.1 hours less a week (1.4 hours versus 4.6\n\n\nhours in the last week worked) than non-registered children.\n\n\nThe most direct test allowed by our research design is to directly compare families who\n\n\nregistered more than one child in the lottery. Unfortunately, most families (5,132) only\n\n\n                          - 30", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["up survey"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003787", "page": 31, "chunk": 1, "title": "wps4580", "pdf_url": "https://local/prwp/wps4580.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "up survey", "label": "VAGUE_DATA", "score": 0.578987717628479, "start": 0, "end": 9, "probe_score": 0.9467, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "engagement in the global economy. <sup>10</sup> Our results speak to both bodies of work by showing\n\n\nthat China’s rising DVAR is due to the substitution of domestic for imported materials.\n\n\nSuch substitution indicates that the country is relying less on imports and becoming more\n\n\ncompetitive in intermediate input sectors. This suggests that China has been moving up\n\n\nthe value chains, and thus may have signi…cant implications for world trade and the global\n\n\neconomy, given its sheer size. <sup>11</sup>\n\n\nThe paper proceeds as follows. Section 2 de…nes our measures of …rm DVAR. Section\n\n\n3 shows how we use …rms’DVAR to compute industry and aggregate DVARs, and analyze\n\n\ntheir patterns. We also discuss the associated aggregation biases in the standard IO table\n\nbased approach, extend our methodology to include the non-processing sector, and calculate\n\n\nthe DVAR of China’s aggregate exports in this section. Section 4 presents the pattern of\n\n\n…rm DVAR. Section 5 develops a simple model to theoretically and quantitatively study the\n\n\ndeterminants of …rm DVAR. Section 6 concludes. In the Appendix, we describe our data sets\n\n\nand the construction of the main variables, such as the number of upstream varieties, import\n\n\nvarieties, and industry exchange rates. A theoretical model that features a Cobb-Douglas\n\n\nproduction function is also presented there.\n\n\nliterature on global value chains.\n\n10Johnson and Noguera (2012) show that the US-China trade imbalance in 2004 is 30-40 percent smaller\nwhen trade is measured in value added. Autor, Dorn, and Hanson (2013) show that increasing Chinese\nimports cause signi…cantly suppressed job creation, lower wages, lower labor market participation, and\nhigher unemployment in the U.S. Pierce and Schott (2015) …nd that U.S. industries with the larger decline\nin tari¤", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data sets"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006537", "page": 7, "chunk": 0, "title": "wps7491", "pdf_url": "https://local/prwp/wps7491.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "data sets", "label": "VAGUE_DATA", "score": 0.5839366316795349, "start": 1129, "end": 1138, "probe_score": 0.7402, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Section 3.6, we estimate the grid-level correlation between projected urban expansion (in 2040\nand 2100) and baseline crop and livestock production (in 2010).\n\nClimate change projections and their impact on land use are inherently uncertain and subject to a\nrange of assumptions and modeling choices. While we have used the SSPs as a framework for our\nurban expansion projections, it is important to note that these scenarios are not predictions, but\nrather represent a range of plausible futures. As noted by Chen et al. (2020), the use of SSPs in\nland-use projections comes with limitations and uncertainties, including the reliance on imperfect\nclimate models and the inability to capture all relevant factors that may impact land use. Therefore,\nit is important to recognize the limitations and model uncertainty in our results and to exercise\ncaution when interpreting precise quantitative estimates.\n\n**3.1** **Projected urban overlap with global crop production**\n\n\n_Figure 3: Projected impact of urban expansion on crop production by SSP scenarios, 2040, 2100 (in_\n_percent change relative to baseline)_\n\n\nNote: SSP = Shared Socioeconomic Pathways.\nSince urban expansion data use 2015 as the starting year, any crop or livestock that overlap with the 2015 urban\nextent are not counted toward the initial agricultural production.\n\n\nThe projected overlap of urban expansion in 2040 is largest for vegetables, followed by fruits,\nroots, and sugar and cereals (see Figure 3). The overlap is smallest for oils and for pulses. For\nvegetables (and for most other crops), the projected urban overlap is largest under SSP5 (fossilfueled development), and also under SSP1 (sustainability). It is under these two scenarios that\nurban expansion is projected to be highest. For example, in 2040, the projected overlap of urban\nexpansion and vegetable production is around 2 percent under SSP5. In contrast, the projected\nurban overlap for vegetables is smallest under SSP3 (regional rivalry", "output": {"entities": {"named_data": [], "descriptive_data": ["urban expansion data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000746", "page": 13, "chunk": 0, "title": "idu04cee93890b4640460f08efa003d2e7d26ded", "pdf_url": "https://local/prwp/idu04cee93890b4640460f08efa003d2e7d26ded.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "urban expansion data", "label": "DESCRIPTIVE_DATA", "score": 0.8228055834770203, "start": 1163, "end": 1183, "probe_score": 0.9888, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " sought alternative arrangements for accommodation in unused facilities, hotels and camping sites. As the need for additional reception places\nincreased, a more collective reception approach was used, departing from Sweden’s practice of housing asylum-seekers in flats in small cities around the country.\nFrance’s strained reception capacity, particularly in Paris and other big cities, was\nillustrated in an incident earlier this year in Saint-Ouen, a working class suburb just\nnorth of the French capital. A group of 200 Syrians camped for several days in a park,\nat night sleeping in hostels paid for by local charities, in old cars or on the street. <sup>24</sup>\nThe authorities prioritized housing for Syrians despite the general shortage, and in an\n\n\n24 UNHCR, _A learning experience for UNHCR as Syrian refugees arrive in the outskirts of Paris,_ 29 April 2014,\n<u>http://www.unhcr.org/535f68526.html</u>\n\n\n\n18", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001133", "page": 17, "chunk": 1, "title": "Syrian Refugees in Europe: What Europe can do to Ensure Protection and Solidarity", "pdf_url": "https://reliefweb.int/attachments/abdae57a-2102-3b7d-8333-a54898b6800d/53b69f574.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "First, more understanding is needed of how statistical data are used. Some promising work has\n\n\nbeen done by PARIS21 on data use by the Executive Branch of Government and on data use by\n\n\ncitizens but there is an important research agenda to be pursued. This research can lead to fruitful\n\n\npolicy advice. For example, there is evidence that using volunteer data collected by citizens can\n\n\nencourage the public to participate more in environmental protection and enhance government\n\n\nability to monitor and manage natural resources (Conrad and Hilchey, 2011). Statistics have no\n\n\nvalue unless they are used and it is only through an understanding of how they are used, the extent\n\n\nof that use and drivers for better use that statistical systems can be designed in a user-centered\n\n\nway. In this regard, we acknowledge that conceptually, while the new SPI is intended to provide\n\n\nthe world with a new forward looking framework of how NSSs need to further evolve, the SPI\n\n\nscores are empirically based on the data currently available. As such, it must be further refined,\n\n\nbased on collective investment in developing more relevant measurements and data sources.\n\n\nSecond, the United Nations Statistics Division global database for SDG indicators is not well\n\n\npopulated, particularly for many high income countries. <sup>17</sup> [^17: Notably, high-income countries do not often collect data on certain indicators that are more relevant for poorer\ncountries such as child stunting, so they do not report on these indicators to the SDGs.] A recent study suggests that data are\n\n\navailable for just over half of all indicators and for just 19 percent of what is needed to\n\n\ncomprehensively track progress across countries and over time (Dang and Serajuddin, 2020). In\n\n\nsome cases it is likely that the data exists but has not found its way on to the database. This is a\n\n\nmajor problem for users and for those seeking to identify best country practice as a guide for their\n\n\nown statistical development. This issue is related to serious gaps in the data available on data\n\n\nsources. It would be", "output": {"entities": {"named_data": ["global database for SDG indicators"], "descriptive_data": [], "vague_data": ["statistical data", "volunteer data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002116", "page": 18, "chunk": 0, "title": "statistical performance indicators and index a new tool to measure country statistical capacity", "pdf_url": "https://local/prwp/statistical-performance-indicators-and-index-a-new-tool-to-measure-country-statistical-capacity.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7055602669715881, "start": 43, "end": 59, "probe_score": 0.4858, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "volunteer data", "label": "VAGUE_DATA", "score": 0.5734683871269226, "start": 348, "end": 362, "probe_score": 0.2064, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "global database for SDG indicators", "label": "NAMED_DATA", "score": 0.6577677130699158, "start": 1216, "end": 1250, "probe_score": 0.8877, "gold": "DATA_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Розлучення сімей стає все більш тривожним ризиком для дітей в Україні з моменту загострення війни, і з лютого**\n**2022 р. Всеукраїнська громадська організація \"Магнолія\" отримала понад 2,500 запитів про пошук дітей, які зникли**\n**безвісти** <sup>**45**</sup> [^45: <u>[«Магнолія» центр - зниклі діти в Україні - 2023 рік](http://help.missingchildren.org.ua/)</u>] **.** Оцінка захисту дітей Ініціативою REACH у 2024 р. показала, що 36% сімей вважають розлучення з сім'єю\nзначним ризиком. Міжсекторальна оцінка потреб 2023 р. виявила, що 2% усіх сімей в Україні повідомили принаймні\nпро одну дитину віком до 18 років, яка проживає окремо від них, з більшим відсотком у східних областях (7% у\nДонецькій, 5% у Херсонській та по 4% у Запорізькій та Харківській областях). Про розлучення сім’ї у п'ять раз", "output": {"entities": {"named_data": [], "descriptive_data": ["Оцінка захисту дітей"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000162", "page": 10, "chunk": 0, "title": "Ukraine: Protection Analysis Update - The Critical Need for Protection amongst Armed Conflict and Violence (July 2024) [EN/UK]", "pdf_url": "https://reliefweb.int/attachments/0cf1522f-0452-4727-8dc5-261a6a547d73/Protection%20Analysis%20Update_UKR.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Оцінка захисту дітей", "label": "DESCRIPTIVE_DATA", "score": 0.6244072318077087, "start": 373, "end": 393, "probe_score": 0.9665, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "........................................... 39\n\n**V.** **KEY RISKS ..................................................................................................................... 40**\n\n**VI.** **RESULTS FRAMEWORK AND MONITORING ................................................................... 48**\n\n**ANNEX 1: IMPLEMENTATION ARRANGEMENS AND IMPLEMENTATION SUPPORT PLAN . 60**\n\n**ANNEX 2: DETAILED COMPONENT DESCRIPTION ........................................................... 68**\n\n**ANNEX 3: PROCUREMENT ...............", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 5, "chunk": 7, "title": "Uganda - Secondary Education Expansion Project", "pdf_url": "http://documents.worldbank.org/curated/en/406361595815248191/pdf/Uganda-Secondary-Education-Expansion-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "output": {"entities": {"named_data": [], "descriptive_data": ["random survey"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000100", "page": 16, "chunk": 0, "title": "Bosnia and Herzegovina - Second Electric Power Reconstruction Project", "pdf_url": "http://documents1.worldbank.org/curated/en/583901468768013967/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7714613080024719, "start": 379, "end": 395, "probe_score": 0.582, "gold": "NON_MENTION", "gold_tier": "human-final"}, {"text": "random survey", "label": "DESCRIPTIVE_DATA", "score": 0.7173007130622864, "start": 1487, "end": 1500, "probe_score": 0.012, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Au moins 15 civils auraient été tués et une dizaine d’autres\nagriculteurs auraient été enlevés. Consécutivement à ces attaques, 331\nménages de 1,655 personnes en provenance des villages précités et le\nvillage Mamove se sont déplacés vers des familles d’accueil à la\ncommune rurale d’Oïcha.\n\n- En fin janvier, des éléments armés ont tué 11 civils et enlevé plusieurs\nautres lors de deux attaques contre les populations des localités de\nBayeti et de Kaza Roho (zone de santé d'Oicha), selon la société civile\nlocale. Plus de 2 000 personnes ont été contraintes de fuir vers des\nvillages voisins.\n\n\n2 <u>Rapports hebdomadaires du Monitoring de Protection_janvier 2024_INTERSOS et</u>\n<u>UNHCR ; les données statistiques n’ont pas été collectées pour janvier 2024.</u>\n\n\n\n\n- Du 5 au 8 janvier, 13 agriculteurs ont été tués dans leurs champs aux\nenvirons du village Molisho. Des éléments ADF étaient de passage dans\nla zone.\n\n- Le 23 janvier, dans le village Ngite-Mavivi (zone de santé d'Oicha), au\nmoins neuf personnes ont été tuées, cinq autres enlevées et 1 500\npersonnes ont été contraintes au déplacement vers Mbau et la ville de\nBeni.\n\n- Selon les acteurs de protection, au moins 57 civils ont été tués au cours\ndes attaques armées dans plusieurs villages du territoire de Beni.\n\n\n**<mark>LU", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["données statistiques"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001502", "page": 2, "chunk": 1, "title": "République démocratique du Congo | Points Saillants de Protection | janvier 2024", "pdf_url": "https://reliefweb.int/attachments/e8e54483-9f00-4026-bda9-953ed2a3b684/points_saillants_situation_de_protection_en_rdc_janvier_2024_vf.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "données statistiques", "label": "VAGUE_DATA", "score": 0.5816531181335449, "start": 697, "end": 717, "probe_score": 0.0021, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Second, data from the EBRD also suggests that while the large-scale privatization\nprogram has effectively stalled, the private sector share of output has nonetheless grown\nsteadily. While this observation is consistent with, say, the growing efficiency of existing\nprivate sector firms in producing output, it is also fully consistent with growing factor\ninputs (labor) among private firms, including the informal sector, and falling employment\nin state enterprises.\n\n\nThird, there are some data on sector-by-sector employment in the RS,\ndisaggregated by enterprise ownership. Unfortunately, the forms of ownership reported\ninclude those of mixed private and public ownership. Depending on whether or not mixed\nforms of ownership are included, SOE employment in RS accounted for about 15 to 40\npercent of total (formal sector) employment in late-2003. According to the LSMS, SOE\nemployment currently accounts for 30 percent of formal sector employment. Regardless\nof how SOE employment is calculated, averages drawn from semi-annual data available\nsuggest that SOE employment in the RS has steadily fallen in recent years as private\nsector employment has grown. <sup>14</sup> [^14: See RS Institute of Statistics (various issues).]\n\n\nFourth, summary data from the South-Eastern Europe Barometer (SEB) suggest\nthat employment in state enterprises ranges from 16 to 24 percent, based on survey data\ncollected in 2004. Available summary data do not allow us to calculate the weighted\naverage of SOE employment for BH as a whole but the average drawn from the LSMS\nfalls within the SEB estimates.\n\n\nThese three data sources do not—separately, on their own—provide conclusive\nevidence that SOE employment has indeed fallen as a share of total employment but they\ndo provide strong evidence that is broadly consistent with the LSMS findings.\n\n_SOE Evolution and Poverty Outcomes_\n\n\nWhat are the poverty and welfare outcomes for those who left the SOE sector and\nthose who stayed? <sup>15</sup> On the one hand, those who left were likely to experience more\nsevere wage", "output": {"entities": {"named_data": ["data from the EBRD", "South-Eastern Europe Barometer", "LSMS"], "descriptive_data": ["data on sector-by-sector employment"], "vague_data": ["semi-annual data", "survey data", "summary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003686", "page": 21, "chunk": 0, "title": "wps4479", "pdf_url": "https://local/prwp/wps4479.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "data from the EBRD", "label": "NAMED_DATA", "score": 0.7456359267234802, "start": 8, "end": 26, "probe_score": 0.9655, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data on sector-by-sector employment", "label": "DESCRIPTIVE_DATA", "score": 0.5345635414123535, "start": 491, "end": 526, "probe_score": 0.9574, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "semi-annual data", "label": "VAGUE_DATA", "score": 0.7631605863571167, "start": 1021, "end": 1037, "probe_score": 0.8343, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "South-Eastern Europe Barometer", "label": "NAMED_DATA", "score": 0.8336473107337952, "start": 1264, "end": 1294, "probe_score": 0.9967, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.6623910665512085, "start": 1385, "end": 1396, "probe_score": 0.8004, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "summary data", "label": "VAGUE_DATA", "score": 0.5700147747993469, "start": 1426, "end": 1438, "probe_score": 0.781, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "LSMS", "label": "NAMED_DATA", "score": 0.6135597229003906, "start": 1556, "end": 1560, "probe_score": 0.9914, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " National Accounts. Consumption data is used to derive potential VAT, and<br>Government revenue collection data is used to ascertain actual VAT collections. The difference is the total VAT Gap,<br>from which the policy gap will be subtracted to arrive at the VAT compliance gap.|\n|Responsibility for Data<br>Collection|PMCSO (MoR)|\n\n\n|Improved Public Financial Management Capabilities|Col2|\n|---|---|\n|**Public availability of annual recurrent and capital budget execution reports and contract award information (Text)**|**Public availability of annual recurrent and capital budget execution reports and contract award information (Text)**|\n|Description|Measures the extent to which budgetary, fiscal, and procurement information is publicly disclosed in a timely manner.|\n|Frequency|Annually|\n|Data source|Ministry of Finance Website and Federal Procurement and Property Administration Agency Website|\n|Methodology for Data<br>Collection|The Federal Government consistently makes available to the public: a) the annual recurrent and capital budget<br>execution reports, and b) contract awards information, through the MoF website and e-GP website respectively,<br>starting from EFY 2018 (FY2025/26). The quality and timeliness of budgetary and fiscal information will be assessed<br>using PEFA PI-5 (Budget Documentation) and PEFA PI-9 (Public Access to Fiscal Information). The quality of<br>procurement information will be assessed using the Open Contracting Data Standard (OCDS).|\n|Responsibility for Data<br>Collection|PMCSO (MoF)|\n\n\n\n\n\n|Beneficiary Citizen Feedback|Col2|\n|---|---|\n|**Increase in civil servant beneficiaries’ experience with the quality of HRM practices (Percentage) **|**", "output": {"entities": {"named_data": [], "descriptive_data": ["Government revenue collection data"], "vague_data": ["Consumption data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:004104", "page": 40, "chunk": 1, "title": "Ethiopia - Governance Modernization to Enable Efficient Service Delivery Project", "pdf_url": "https://documents.worldbank.org/curated/en/099082124120033234/pdf/BOSIB-8a85947f-785c-45db-a183-95ed26b4df7a.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Consumption data", "label": "VAGUE_DATA", "score": 0.5950062274932861, "start": 20, "end": 36, "probe_score": 0.0166, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Government revenue collection data", "label": "DESCRIPTIVE_DATA", "score": 0.8828353881835938, "start": 77, "end": 111, "probe_score": 0.0742, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nMauritania Social Safety Net System Project II (P171125)\n\n\n\n\n\n\n\n\n\n|Households with complete<br>information in the Social Registry -<br>Refugee|Number of refugee<br>households registred within<br>the Social Registry database<br>and for which the socio-<br>economic data has been<br>collected and recorded.|Semester|Social<br>Registry MIS|Specific request on the<br>Social Registry database|Social Registry<br>Directorate|\n|---|---|---|---|---|---|\n|Households with updated information<br>in the Social registry (less than 3<br>years)|<br>Percentage of households<br>included in the Social<br>Register database for which<br>socio-economic data was<br>collected within the<br>previous three years.|Semester<br>|Social<br>Registry MIS<br>|Request on the Social<br>Registry database<br>|Social Registry<br>Directorate<br>|\n|Cases from the Social Registry grievance<br>redress mechanism resolved in a timely<br>manner|Percentage of complaints or<br>requests for information<br>received by the Social<br>Registry that have been<br>resolved within 60 days.|Semester<br>|Social<br>Registry MIS<br>|MIS extraction<br>|Social Registry<br>Directorate<br>|\n|Spot-check surveys carried-out and<br>disclosed by the Social Registry|Number of spot checks on<br>the Social Registry carried<br>out by an external firm<br>and/or the Social Registry", "output": {"entities": {"named_data": ["Social Registry database"], "descriptive_data": [], "vague_data": ["socio-economic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000045", "page": 44, "chunk": 0, "title": "Mauritania - Second Social Safety Net System Project", "pdf_url": "http://documents1.worldbank.org/curated/en/323551584151262464/pdf/Mauritania-Second-Social-Safety-Net-System-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Social Registry database", "label": "NAMED_DATA", "score": 0.5217124819755554, "start": 218, "end": 242, "probe_score": 0.7287, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "socio-economic data", "label": "VAGUE_DATA", "score": 0.6352821588516235, "start": 641, "end": 660, "probe_score": 0.198, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " evaluation will be to: (i) verify project’s progress towards\nachievement of the development objective; (ii) ensure the correct use of funds on a six monthly\nbasis; (iii) verify the services received by project beneficiaries through independently checking a\nsample of health facilities for enrollment registers, volume, quality of services, reporting and\npayments, and sample of beneficiary households for verification of enrollment, receipt of\nservices and satisfaction; and (iv) look at different levels of monitoring as undertaken by MoPH\nto ensure that payments are being verified adequately against claims and services are actually\nprovided. Evaluation report will be submitted once per year and will include recommendations\non how to further improve project implementation and prevent fraudulent behavior or abuse.\n**_Beneficiary Assessment._** A beneficiary assessment will be carried out to determine the impact\nof the project on the household service utilization, the cost of the services used, and the capacity\nof PHCCs to deliver services in effective and cost efficient manner. **_Evaluation by the Bank._**\nAs part of regular supervision, the Bank will conduct an evaluation at the mid-year to (i)\nundertake its own assessment of the project achievements and progress towards development\nobjective; (ii) review the results of both the independent evaluation and beneficiary assessment\nreports, and reconcile the results with its own assessment; and (iii) suggest any changes to be\nmade to the evaluation methods, scope and frequency as needed.\n\n51. **Steps for Evaluation:** In order to meet the assessment requirements, the following steps\nshould be taken to prepare for evaluation: (i) data collection and analysis process, formally\ninstitutionalized; (ii) baseline data established per targeted indicator; (iii) clarity regarding the\ndefinition and collection of each indicator; (iv) defining indicators must be a participatory effort\n\n\n55", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000020", "page": 54, "chunk": 1, "title": "Lebanon - Emergency Primary Healthcare Restoration Project", "pdf_url": "http://documents1.worldbank.org/curated/en/185271468266958778/pdf/PAD12050PAD0P15264600PUBLIC00Box391428B.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "baseline data", "label": "VAGUE_DATA", "score": 0.6572362184524536, "start": 1772, "end": 1785, "probe_score": 0.0002, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Col1|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|Col10|Planned|Actual|Planned|Actual|Planned|Actual|Planned|Actual|Planned|Actual|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n|||||||||||||||||||||\n\n\nPage 4", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:006863", "page": 8, "chunk": 0, "title": "Kenya - Eastern and Southern Africa- P152394- Transforming Health Systems for Universal Care - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099505006032210553/pdf/P15239404610c902c09ecd0a3d131e6e5f2.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Test\n<mark>PNDS</mark> <mark>National Health Development Plan</mark> _<mark>(Plan National de Développement Sanitaire)</mark>_\n<mark>PP</mark> <mark>Procurement Plan</mark>\n<mark>PPSD</mark> <mark>Project Procurement Strategy for Development</mark>\nPRAPS Regional Sahelian Pastoralism Support Project ( _Projet Régional d'Appui au_\n_Pastoralisme au Sahel_ )\n<mark>QBS</mark> <mark>Quality Based Selection</mark>\n<mark>QCBS</mark> <mark>Quality Cost-Based Selection</mark>\n<mark>RFP</mark> <mark>Request for Proposal</mark>\nRGPH National Population Census ( _Recensement Général de la Population et de_\n_l’Habitat_ )", "output": {"entities": {"named_data": ["RGPH National Population Census"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000045", "page": 3, "chunk": 1, "title": "Mauritania - Second Social Safety Net System Project", "pdf_url": "http://documents1.worldbank.org/curated/en/323551584151262464/pdf/Mauritania-Second-Social-Safety-Net-System-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "RGPH National Population Census", "label": "NAMED_DATA", "score": 0.9069064259529114, "start": 524, "end": 555, "probe_score": 0.0013, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "average annual change in inequality between the CONAFE and non-CONAFE groups is the\n\n\nminimum positive effect attributable to CONAFE.\n\n\nRepetition rates of CONAFE students were, as expected, significantly higher than\n\n\nrepetition rates of non-CONAFE students in every grade, year, and disadvantage group.\n\n\nRepetition rates dropped by between 0.42 and 0.66 percentage points per year among CONAFE\n\n\nstudents (Table 9). Of course, because our analysis compares different grades in different years,\n\n\nit is likely that the lowest achieving students leave school each year, and that a decrease in\n\n\nrepetition rates is partly attributable to difference in the students that attend each grade.\n\n\nBut it appears that CONAFE caused part of this decrease in repetition rates. In the\n\n\ndisadvantaged group, CONAFE students had an annual average increase of 0.08 percentage\n\n\npoints in repetition rates above their non-CONAFE peers. But in both the mid-range and non\n\ndisadvantaged groups, CONAFE students had an annual average decrease of 0.35 and 0.13\n\n\npercentage points, respectively, against their non-CONAFE peers. Those decreases represent the\n\n\nlower level of repetition that CONAFE causes among its supported students. On balance, it\n\n\nappears that CONAFE decreases repetition rates by about 0.13 percent (0.0013 points) per year,\n\n\nbut that effect varies between disadvantage groups. While this affect may appear to be small, it\n\n\nsuggests that CONAFE annually eliminates 6 percent of inequality in repetition rates between\n\n\ncomparable CONAFE and non-CONAFE students (Table 9).\n\n\nData on failure rates suggest less conclusive results. CONAFE students fail at a much\n\n\nhigher rate than do comparable non-CONAFE students: among the grades and disadvantage\n\n\ngroups analyzed, an average of 5.04 percent of non-CONAFE students failed a class subject in a\n\n\ngiven year, whereas an average of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Data on failure rates"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002616", "page": 33, "chunk": 0, "title": "wps3334", "pdf_url": "https://local/prwp/wps3334.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Data on failure rates", "label": "VAGUE_DATA", "score": 0.6454369425773621, "start": 1582, "end": 1603, "probe_score": 0.5799, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**BOX** **4:** **Adoption** **of** **Tax** **E-services** **in** **Africa**\n\n\n**Problem:** Traditional tax processes involve paper-based filing and extensive in-person interactions between taxpayers and tax officials. This system creates several challenges such as\nlarge compliance costs, collusion with tax officials or extortion by them, and poor tax records\nthat limit the potential of tax agencies to conduct analyses for compliance monitoring and\nforecasting. Whereas new technology to digitize taxpayer services may hold a lot of promise,\nimportant barriers to adoption of these technologies may severely curb the potential for revenue mobilization.\n\n\n**Technology** **intervention:** Many African governments have been heavily investing in eservices as a way to move from paper-based systems to fully digital platforms. As an example\nof such e-services, e-filing and e-payment facilities enable digital filing of returns and digital\npayment of tax liabilities. These e-services often live within integrated and automated tax\nadministration systems. The associated web portals also provide a range of benefits in terms\nof clear information on deadlines, access to assistance, and better record-keeping.\n\n\n**Research** **design:** A number of studies from Africa attempt to understand the barriers to\naccess of such e-services. These studies are typically based on surveys of representative samples\nof taxpayers, collecting detailed information around taxpayer experiences with e-services. In\nthe case of Rwanda, Santoro et al. (2022) originally link survey data with tax administration\ndata, in order to gain more information around taxpayers and their filing behavior.\n\n\n**Results:** Lack of awareness and lack of training are key factors that have been identified in\nboth Nigeria (Mas’ud, 2019) and Zimbabwe (Obert et al., 2018) as barriers to adoption of eservices", "output": {"entities": {"named_data": [], "descriptive_data": ["surveys of representative samples\nof taxpayers", "tax administration\ndata"], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000739", "page": 23, "chunk": 0, "title": "idu049a724c20d3de042180b32f01e8d3a7bd276", "pdf_url": "https://local/prwp/idu049a724c20d3de042180b32f01e8d3a7bd276.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "surveys of representative samples\nof taxpayers", "label": "DESCRIPTIVE_DATA", "score": 0.8791261911392212, "start": 1370, "end": 1416, "probe_score": 0.4455, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.6475937366485596, "start": 1556, "end": 1567, "probe_score": 0.4004, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "tax administration\ndata", "label": "DESCRIPTIVE_DATA", "score": 0.8319250345230103, "start": 1573, "end": 1596, "probe_score": 0.7392, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " out of 40 Districts in the<br>North met the minimum<br>conditions and accessed the<br>LDG.||\n|% of LGs which have computerized financial<br>management system complete the final<br>accounts within three months after the end of<br>the fiscal year||Text|Value|57 %(8 out of 14 HLGs)|100% (14 out of 14 HLGs)|80%|\n|% of LGs which have computerized financial<br>management system complete the final<br>accounts within three months after the end of<br>the fiscal year||Text|Date|12-Oct-2007|02-Dec-2011|31-Dec-2012|\n|% of LGs which have computerized financial<br>management system complete the final<br>accounts within three months after the end of<br>the fiscal year||Text|Comments|Due to delay in Effectiveness,<br>baseline information has been<br>updated from 2005/06 to<br>2007/08.|Although KCCA with its 5<br>divisions became an Authority<br>on March 1, 2012 and<br>therefore ceased to be a LG,<br>the number of \"HLGs\" for this<br>indicator has been maintained<br>to 14 since KCCA and its<br>divisions are still benefiting<br>from the IFMS support under<br>the project. KCCA, its<br>Divisions and all the<br>remaining 8 LGs are<br>completing final account<br>within three months of the end<br>of the FY.||\n\n\n\nPage 3 of 6", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["baseline information"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018819", "page": 2, "chunk": 1, "title": "Uganda - Local Government Management and Services Delivery Project : P090867 - Implementation Status Results Report : Sequence 09", "pdf_url": "https://documents.worldbank.org/curated/en/828791468759599479/pdf/P0908670ISR0Di030201201327963194393.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "baseline information", "label": "VAGUE_DATA", "score": 0.5460860729217529, "start": 712, "end": 732, "probe_score": 0.0002, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "(ACD) of the high court. Further, investigation on funds mismanagement and abuse of offices\narising out of the OAG reports are discussed by the public accounts committee of Parliament\n(PAC) and the LG PAC (Local Governments), and the Committee on commissions, statutory\nauthorities and state enterprises (COSASE). The IGG, DPP, PPDA, CIID and ACD all have\nregional offices that have enabled the Government take the fight against corruption closer to the\ncitizens.\n\n\n69. The ACD operates as the arm of the judiciary with regional branches. The cases handled\ninclude corruptly soliciting gratification; neglect of duty; causing financial loss; embezzlement;\nabuse of office; corruption. The High Court Data Centre shows in table below growing case\nmanagement during 2014 and 2015 National Anti-Corruption Strategy 2014-2019 came onto the\nscene.\n\n\n**Table 4. Anti-corruption Division of the High Court case management during 2014-2015**\n\n|Case File category|2014|2015|\n|---|---|---|\n|Cases brought forward|166,000|168,000|\n|Cases registered|158,000|155,000|\n|Cases concluded|153,000|152,000|\n|Cases pending|172,000|173,000|\n\n\n\n_Source:_ High Court Data Centre.\n\n\n70. **Alignment with ACG for PforR Operation -** To address the F&C associated with\nfiduciary risk the Program for Results implementation will be aligned to the Anti-Corruption\nGuidelines (ACG) applicable to PforR **Operations** - Guidelines on Preventing and Combating\nFraud and Corruption in Program-for-Results financing”, dated February 1, 2012. The measures\nthat will be instituted under the Program in line with the ACGH guidelines include the following:\n\n\n(a) Sharing of information on F&C allegations – in line with", "output": {"entities": {"named_data": ["High Court Data Centre"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010877", "page": 14, "chunk": 0, "title": "Uganda - Intergovernmental Fiscal Transfers Program for Results : Integrated fiduciary systems assessment", "pdf_url": "https://documents.worldbank.org/curated/en/297081498833236937/pdf/UgIFT-PforR-FSA-Final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "High Court Data Centre", "label": "NAMED_DATA", "score": 0.5468334555625916, "start": 689, "end": 711, "probe_score": 0.3571, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "06-20||2021-07-11||2021-08-15||2024-12-27||\n|ET-SIDAMA WIDB-227485-CS<br>-INDV / Selection and employ<br>ment of Electromechnical En<br>gineer for Sidama Regional S<br>tate Water and Irrigation Bur<br>eau PMU by SRIWDB|IDA / 64450|Institutional Strengthening a<br>nd Project Management|Post|Individual Consult<br>ant Selection|Open||21,000.00|0.00|Canceled|2021-04-05||2021-05-24||2021-06-14||2021-07-19||2025-01-04||\n|ET-SIDAMA WIDB-427119-CS<br>-INDV / Procurement of Indivi<br>dual Consultant (Procuremen<br>t Specialist) for Sidama Natio<br>nal Regional Water Mines an<br>d Energy Bureau|IDA / 64450|Institutional Strengthening a<br>nd Project Management|Prior|Individual Consult<br>ant Selection|Open - National||25,000.00|0.00|Under Implement<br>ation|2024-06-07|2024-12-09|2024-06-29||2024-07-04||2024-07-14||2025-03-11||\n\n\nPage 4", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003164", "page": 5, "chunk": 1, "title": "Ethiopia - EASTERN AND SOUTHERN AFRICA- P167794- One WASH?Consolidated Water Supply, Sanitation, and Hygiene Account Project (One WASH?CWA) - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099062426054540434/pdf/P167794-f2695f86-4dd4-4a08-859d-8125729a42d2.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**I.** **STRATEGIC CONTEXT**\n\n\n**A.** **Country Context**\n\n1. **Lebanon has witnessed the largest influx of Syrian refugees compared to the other**\n**neighboring countries affected by the crisis.** By July 2014, the refugee influx had expanded\ndramatically to 1,138,043 people and led to the largest humanitarian emergency operation of its\nkind for many years. Based on the current data, Lebanon has received 39 percent of all Syrian\nrefugees; almost 1,103,707 Syrians have registered and 34,336 are still awaiting registration with\nthe United Nations High Commissioner for Refugees (UNHCR). By the end of 2014, it is\nestimated that the number of Syrian refugees will increase to 1.6 million, equivalent to 37\npercent of Lebanon’s pre-crisis population. <sup>1</sup> [^1: The high refugee influx scenario, which is an unlikely scenario used mainly for illustration and sensitivity\npurposes, is calculated based on a straight line extrapolation from recent refugee inflows. Based on this mechanical\napproach, by end-2014 the refugee population could reach 2.3 million people and would represent a 54 percent\nincrease in Lebanon’s pre-conflict population.]\n\n2. **UNHCR and United Nations (UN) partner agencies promptly established operations**\n**in Lebanon to respond to the crisis, but the support was primarily targeted to Syrian**\n**refugees and not to Lebanese communities whose quality of life and socioeconomic**\n**outcomes are mostly adversely affected by the influx.** As of June 2014, contributions to the\nRegional Response Plans (RRPs) for Lebanon totaled US$390 million, <sup>2</sup> [^2: Eighteen donors had contributed US$166.9 million via UNHCR, and 25 other agencies working in Lebanon had\ncontributed US$223.3 million.] which, despite the large\namount, represent only about 23", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["current data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000020", "page": 9, "chunk": 0, "title": "Lebanon - Emergency Primary Healthcare Restoration Project", "pdf_url": "http://documents1.worldbank.org/curated/en/185271468266958778/pdf/PAD12050PAD0P15264600PUBLIC00Box391428B.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "current data", "label": "VAGUE_DATA", "score": 0.7811605334281921, "start": 374, "end": 386, "probe_score": 0.982, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " activities.\n\n\n3. **Lebanon is one of the countries hardest hit by COVID-19 in the Middle East and North Africa (MENA) region** .\nLebanon is in the midst of three mega-crises: the economic crisis; the COVID-19 pandemic; and the aftermath of\nthe Port of Beirut explosion. The crippling economic crisis starting in October 2019 has greatly constrained the\nhealth system's ability to provide accessible and affordable health services. As of May 4, 2022, Lebanon has\nrecorded a total of 1,097,204 confirmed cases and 10,393 deaths since the start of the pandemic. <sup>1</sup> A total of\n5,602,398 COVID-19 vaccine doses have been administered. <sup>2</sup> Of the total number of vaccinated people, 2,677,312\nreceived at least one dose (approximately 49 percent of the eligible population of ages 12 and older), and\n2,351,269 have been fully immunized with two doses (approximately 43 percent of the eligible population of ages\n12 and older). Among those who received two doses, approximately 24 percent received a third dose. <sup>2</sup>\n\n4. **The World Bank has been supporting Lebanon in strengthening its response to COVID-19 through its existing**\n\n\n1 MoPH COVID-19 Surveillance in Lebanon Daily Report – May 4, 2022\n2 MoPH COVID-19 Surveillance in Lebanon Daily Report – April 25, 2022\n\n\nPage 7 of 54", "output": {"entities": {"named_data": ["MoPH COVID-19 Surveillance in Lebanon Daily Report"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000000", "page": 11, "chunk": 2, "title": "Lebanon - Strengthening Lebanon's COVID-19 Response under the COVID-19 Strategic Preparedness and Response Program (SPRP)", "pdf_url": "http://documents.worldbank.org/curated/en/099410007282239961/pdf/BOSIB09c1bfedd05c098380dc89cfe988b8.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "MoPH COVID-19 Surveillance in Lebanon Daily Report", "label": "NAMED_DATA", "score": 0.669593870639801, "start": 1155, "end": 1205, "probe_score": 0.9469, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Col1|PSNP IV|Col3|IMPLEMENTATION STATUS REPORT (ISR) RF<br>INDICATOR TRACKING SHEET|Col5|Col6|Col7|\n|---|---|---|---|---|---|---|\n||**PSNP IV**|**PSNP IV**|**Reported as of August 28, 2018**|**Reported as of August 28, 2018**|**Reported as of August 28, 2018**|**Reported as of August 28, 2018**|\n|<br>|<br>|<br>|30-Jun-18|30-Jun-18|30-Jun-18|30-Jun-18|\n|<br>|<br>|<br>|Numerator|Denominator|Percentage|Absolute Value<br>(Y/N, absolute<br>number, days, etc)|\n|13|**% OF CLIENTS RECEIVING REGULAR PAYMENTS WITHIN THE**<br>**AGREED TIME FRAME (20 DAYS FOR CASH AND 30 DAYS FOR**<br>**FOOD) **<br>|**% OF CLIENTS RECEIVING REGULAR PAYMENTS WITHIN THE**<br>**AGREED TIME FRAME (20 DAYS FOR CASH AND 30 DAYS FOR**<br>**FOOD) **<br>|||28.5%||\n|<br>|**CASH **|<br>|||40%||\n||RAW DATA<br>SOURCES:||||FIC<br>Report||\n||COMMENTS<br>||This", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["RAW DATA"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:017191", "page": 52, "chunk": 0, "title": "Ethiopia - Phase Four of the Rural Productive Safety Net Project : Joint Review and Implementation Support Mission - June 4-14, 2018", "pdf_url": "https://documents.worldbank.org/curated/en/720621541065692801/pdf/Aide-Memoire-Ethiopia-Rural-Productive-Safety-Net-Project-P163438.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "RAW DATA", "label": "VAGUE_DATA", "score": 0.683533251285553, "start": 769, "end": 777, "probe_score": 0.0318, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "EXECUTIVE SUMMARY\n\n1. A Joint UNHCR/WFP Assessment Mission (JAM) was conducted to assess the viability\nof the on-going operation among newly arrived Ghanaian refugees in Togo and to\ndetermine the need and level of support beyond October 2010 when the current\noperation providing assistance to the refugees will come to an end <sup>1</sup> . This first\nassessment took place almost 5 months after the arrival of refugees in Togo\n\n2. The specific objectives of this JAM included: (i) review the implementation of\nrecommendations of previous missions that have taken place since the influx; (ii)\nassessment of protection and security issues among refugees; (iii) assessment of\naccess to basic services such as heath, water and sanitation, education, shelter and\nfood, (iv) determine the most probable scenario for the forthcoming months on the\nlikelihood of return to Ghana or mid-to long term stay in Togo; and (v) assessment of\nthe food security situation, livelihood and self reliance opportunities with focus on\nfood and non-food needs of refugees and host communities with a view towards a\n‘durable solution’ by December 2011.\n\n3. The findings of this first JAM are based on an extensive review of secondary data in\nreports compiled by WFP, UNHCR and other partners as well as information\ngathered through key informant meetings in Lome, Tandjoare and Dapaong and\nanalysis of data collected in the field. The mission team visited all four refugeehosting villages in Tandjoare Prefecture and conducted 20 focus group discussions\nand 40 household interviews with both refugees and hosts. The findings were\nconclusive enough to suggest an overall trend which was supported by triangulation\nwith other data sources.\n\n4. The main mission findings and recommendations are as follows:\n\n5. Location and numbers – Refugees are located in four villages in the Prefecture of\nTandjoare, Savanes Region in the north of Togo near the border with Ghana. The\ncomprehensive registration conducted by UNHCR in", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["secondary data", "data collected in the field"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000002", "page": 3, "chunk": 0, "title": "MISSION D'EVALUATION CONJOINTE-HCR-PAM: Des besoins des Nouveaux Réfugiés Ghanéens au TOGO", "pdf_url": "http://documents.wfp.org/stellent/groups/public/documents/ena/wfp230273.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "secondary data", "label": "VAGUE_DATA", "score": 0.6371498703956604, "start": 1200, "end": 1214, "probe_score": 0.8474, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data collected in the field", "label": "VAGUE_DATA", "score": 0.5759215950965881, "start": 1378, "end": 1405, "probe_score": 0.2236, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NEWS&utm_medium=email&utm_content=2nd+section+2nd+story+the+guardian&utm_campaign=HQ_EN_therefugeebrief_external_20181010)</u> **<u>.</u>**\nThis article focuses on personal stories of Senegalese refugees in Guinea-Bissau and governmental efforts of naturalizing\nthem as citizens. In December 2017 the Government of Guinea-Bissau made a declaration which was approved in July 2018\nas a new policy of naturalization for 7,000 refugees in the country of 1.8 million population. Since then the UN refugee\nagency has been working with a local contractor to produce and distribute ID cards, naturalization and birth certificates for\nthe refugees and their children.\n\n\n<u>[Yomi Kazeem, The harrowing, step-by-step story of a migrant’s journey to Europe, 25 October 2018](https://qz.com/africa/1341221/the-harrowing-step-by-step-story-of-a-migrants-journey-to-europe/)</u> **<u>.</u>** The article recounts the\nstory of a young migrant from Edo state in Nigeria, who journeyed to Europe following the routes linking Edo state with the\nEU. His journey lasted 9 months, six months longer than the initially three months planned. The article also explains how\nmigration is entrenched in the social fabric in Edo state, as well as government attempts to manage migration and the role\nof smugglers.\n\n\n<u>[4Mi snapshot: aspirations or refugees and migrants from West Africa, MMC West Africa, October 2018.](http://www.mixedmigration.org/resource/4mi-snapshot-aspirations/)</u>\nIn October 2018 MMC West Africa published a 4Mi snapshot with key", "output": {"entities": {"named_data": ["4Mi snapshot"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000266", "page": 9, "chunk": 1, "title": "Monthly Trends Analysis West Africa, October 2018", "pdf_url": "https://reliefweb.int/attachments/1dfa72b2-4ee7-37e0-90ed-3662ea8723c1/ms-wa-1811.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "4Mi snapshot", "label": "NAMED_DATA", "score": 0.604763388633728, "start": 1292, "end": 1304, "probe_score": 0.9476, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nfor cybersecurity. To handle incidents and attacks, Uganda has both a national Computer Emergency Response\nTeam (CERT) at NITA-U and a Communications Sector CERT at the Uganda Communications Commission (UCC).\nThe country benefitted from the Cybersecurity Maturity Model assessment that was undertaken in 2016 and\nupdated in 2020; the emanating recommendations, for instance on capacity building and awareness raising, are\nreflected in the present project’s design. Uganda was nominated as the regional lead on cybersecurity under the\nEast African Northern Corridor Infrastructure Regional Memorandum of Understanding (MoU). In 2018, Uganda\nranked 7 <sup>th</sup> in Africa in the ITU’s Global Cybersecurity Index, and 65 <sup>th</sup> globally. <sup>38</sup> [^38: International Telecommunications Union, 2018., _Global Cybersecurity Index 2018_ . https://www.itu.int/dms_pub/itu-d/opb/str/D-STRGCI.01-2018-PDF-E.pdf] The country’s next challenges for\ncybersecurity are therefore to expand technical capacity, implement best practice governance, and move toward\neffective implementation and sustainability.\n\n\n**16.** **In the area of data protection, Uganda is in the early stages of operationalizing a recently adopted Data**\n**Protection Law.** This landmark legislation, passed in 2019, made Uganda the first East African country to recognize\nprivacy as a fundamental human right, as enshrined in Article 27 of the 1995 Uganda Constitution. It aims to\nprotect individuals and their personal data by regulating processing of personal information by state and nonstate actors, within and outside Uganda. The law expands the rights of individuals to control how their personal\ndata are collected and processed, placing a range of obligations on those processing it, both public bodies and\ncompanies. A year since its enactment, the law remains in need of accelerated implementation and enforcement,\nwith observers reporting that personal data continue to be collected in violation of the law’s principles. <", "output": {"entities": {"named_data": ["Global Cybersecurity Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000075", "page": 18, "chunk": 1, "title": "Uganda - Digital Acceleration Project", "pdf_url": "http://documents1.worldbank.org/curated/en/473041622944887337/pdf/Uganda-Digital-Acceleration-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Global Cybersecurity Index", "label": "NAMED_DATA", "score": 0.5525436401367188, "start": 687, "end": 713, "probe_score": 0.9404, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**7** **ENVIRONMENTAL MANAGEMENT PLAN**\n\n\n\n**7.1**\n\n\n**7.2**\n\n\n\n**Detailed corrective actions plan**\n\n\nThe environmental corrective action plan presented in Table 7-1 collates and summarises the\nrecommendations made in Chapter 5. The Plan also suggests a time period within which the\nactions should be implemented and the persons responsible for specific actions.\n\n\nIt must be emphasised that these timings and allocations for responsibility have been\nproposed as a starting point. It is expected that the Company management will continuously\nreview the plan, so that more realistic target dates, based on availability of funds for corrective\nactions, as well as personnel resources, can be proposed.\n\n\nIn order to monitor the Hydrogen Sulphide (H 2 S) levels from the plant, it is recommended that\nfuture air quality analysis reports to include analysis of H 2 S gases at the power plant so as to\nensure no health risks to workers and to maintained present air quality standards.\n\n\n**Environmental monitoring during construction**\n\n\nEnvironmental monitoring should be an on-going activity as a part of the company operations\nand construction activities in Plant 2. Monitoring should not only focus on meeting legal\ncompliance, but should go further and be used as a tool to predict unforeseen impacts\nresulting from the activities and operations of the company.\n\n\nComprehensive environmental report should be prepared every quarter of the annual year,\ngiving an indication of the trends for each of the various environmental and safety parameters,\nbased on the monitoring data collected. All safety, health and environmental parameters being\nmonitored should be consolidated into a monitoring plan and this plan must be continuously\nupdated.\n\n\n\n**7.3** **Construction of Olkaria Ill Second Plant**\n\n\n**7.3.1** **Environmental management plan**\n\n\nIt is the responsibility of the project manager to incorporate mitigation measures into the\ncontract documents.\n\n\nThe plant safety, health and environmental manager", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["monitoring data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014957", "page": 35, "chunk": 0, "title": "Kenya - Private Sector Power Generation Support Project : environmental assessment (Vol. 8 of 8) : Environmental audit on existing plant operations and construction works for expansion", "pdf_url": "https://documents.worldbank.org/curated/en/570351468047742537/pdf/E27880V80P122600Box382119B00PUBLIC0.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "monitoring data", "label": "VAGUE_DATA", "score": 0.7088024616241455, "start": 1562, "end": 1577, "probe_score": 0.2058, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 4\nPage 4 of 5\n\nextensive retraining of teachers and head-teachers. Temporary teachers will now be recruited\nearlier so that they can benefit from pedagogic training.\n\n\n**E. Justification of Public Finance to Support the Program**\n\nThere is a global consensus that universal access to basic education is the right of each child and this\nhas been widely endorsed most recently at the Education for All Conference in Dakar. The positive\nexternalities of basic education provide ample public finance justification for supporting universal\nbasic education with public funds. In addition, Djibouti's economic future depends heavily on the\nquality and productivity of its work-force as it has few other resources. Basic education is an\nessential pre-condition to improve workforce quality and productivity. Thus, public funding for it is\nalso justified on the grounds of improving Djibouti's development potential.\n\nPublic support for universal basic education in Djibouti can also be justified on the grounds of\nreducing income and gender inequities in enrollment which the Government proposes to address\nthrough a variety of ways discussed above. Random surveys of school children will be done over the\nten year period (including a base-line in 2001) to assess progress in reducing gender gaps and income\ngaps in enrollment.\n\n\n**F. Project Approach versus Budget Support Approach**\n\nThe project approach is considered more appropriate in Djibouti's case because given the urgent fiscal\nconstraints, budget support money may get diverted to finance immediate current needs and the\nschools may never get built. The supply of school places and the quality of schooling is easier to\naddress through a project approach.\n\n\n**G. Fiscal Impact of Program**\n\nAnnex 4, Table 1 illustrates the potential fiscal impact. This appears to be quite manageable. The\nrequired cost estimates include all levels of education, ministry overheads and potential grants to the\nprivate sector. The Government projects the most likely scenario for Djibouti's growth to be 2.4% per\nyear during the period 2000-2010 and expects the budget to grow slightly slower", "output": {"entities": {"named_data": [], "descriptive_data": ["Random surveys of school children"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000100", "page": 40, "chunk": 0, "title": "Bosnia and Herzegovina - Second Electric Power Reconstruction Project", "pdf_url": "http://documents1.worldbank.org/curated/en/583901468768013967/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Random surveys of school children", "label": "DESCRIPTIVE_DATA", "score": 0.926578938961029, "start": 1148, "end": 1181, "probe_score": 0.2289, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "* Popular Benchmarks\n**children.**\n\n\n**Project** **Development** **Outcome** **/** **Impact** **Project reports:** **(from** **Objective** **to Goal)**\n**Objective:** **Indicators:**\n**Assist** **war affected** - Improved social capital and - Initial Social Assessment - Communities in the NSAP\n**communities** **to restore** organizational development; (to establish indicators and target areas are assisted to\n**infrastructure,** **services** **and** - Increased access to and use methodologies for social ensure a reduced risk of\n**build** **local** **capacity for** of social and economic capital and organizational conflict\n**collective** **action.** Priority infrastructure and services development)\nwill be given to areas not - Proportion of NSAP - Annual social assessments; - NACSA complements and\npreviously serviced by investments targeted to newly - NaCSA M&E data; extends the work of other\ngovernment, newly accessible accessible areas, & areas - M&E data of relevant line agencies and rninistries\nand the most vulnerable previously not served, and mninistries; in support of the PRSP's\npopulation groups within those vulnerable people within these - Beneficiary Assessment poverty reduction and\nareas. areas; (BAs) biannually; decentralization objectives\n\n                  - Proportion of sub-projects                   - Participatory evaluation\nthat reflect priorities of reports for a random sample of                   - NACSA is fully integrated\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and", "output": {"entities": {"named_data": ["NaCSA M&E data"], "descriptive_data": ["M&E data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016707", "page": 29, "chunk": 1, "title": "Kenya - Second Arid Lands Resource Management Project", "pdf_url": "https://documents.worldbank.org/curated/en/687271468753266864/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "NaCSA M&E data", "label": "NAMED_DATA", "score": 0.880613386631012, "start": 862, "end": 876, "probe_score": 0.7332, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "M&E data", "label": "DESCRIPTIVE_DATA", "score": 0.580130398273468, "start": 961, "end": 969, "probe_score": 0.5271, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad Rural Mobility and Connectivity Project (P164747)\n\n\n**ANNEX 1: Implementation Arrangements and Support Plan**\n\n\n**COUNTRY: Chad**\n**Chad Rural Mobility and Connectivity Project**\n\n\n**Financial Management**\n\n\n1. The proposed project will be implemented by the PMCU of the MITD. The PMCU is currently\nimplementing the IDA-funded CEMAC Transport-Transit Facilitation Project (P079736, IDA-H3150: US$30\nmillion). The fiduciary compliance of the Transport-Transit Facilitation Project is deemed Moderately\nSatisfactory largely because of the project’s low disbursement rate during the last fiscal year, resulting\nfrom delays in the budget reallocation process. The project’s compliance was, however, deemed\nsatisfactory for the other financial requirements such as timely reporting, adequate staffing, proper\nbookkeeping, appropriate banking arrangement, and sound internal control procedures.\n\n\n2. The current financial and accounting team consists of a finance and administrative specialist, a\nsenior accountant, an assistant accountant, and an internal auditor. No additional staff will be hired.\nHowever, further capacity building of the PMCU will be necessary under the proposed project.\n\n\n3. The FM assessment has concluded that the PMCU FM system is adequate and complies with the\nWorld Bank’s minimum requirements under the Bank Policy/Directive for IPF. Overall, the current system\ncan, with reasonable assurance, provide accurate and timely information on the status of the project, as\nrequired by the World Bank. However, the residual FM risk is substantial, and the following actions are\nrequired to unable the PMCU to adequately manage the implementation of the proposed Rural Mobility\nand Connectivity Project.\n\n\n     - **Internal control.** The Administrative, Financial, and Accounting Procedures Manual currently\nbeing used under the World Bank-financed Transport-Transit Facilitation Project will be\nupdated by an independent consultant to fit the new project needs.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000048", "page": 47, "chunk": 0, "title": "Chad - Rural Mobility and Connectivity Project", "pdf_url": "http://documents.worldbank.org/curated/en/815491545534039786/pdf/Chad-PAD-11302018-636811128215032206.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a v\nManufacturIng 5 7 3.7 4 7 5 0 / s \\\\t oo  Services 475 272 190 201\n\nPrfvate consumpffon 90 7 81 9 938 95 1 20\nGeneral govemment consumption 7 0 9 6 146 17.2 =c ~GDFDl\nImpons of goods and servrcea 39 7 23 6 33 4 373 -3GW_G_____\n\n\n_(average_ _annual growth)_ 1981-9 1991401 2000 2001 Growth ot exports and Imports (%)\n\nAgrutumre -0 6 -2 6 2 2 3 8 oo\nIndustry 0.1 -41 51 5 6 s0\nManUnacturIng 6.9 . .\nServices -5 7 -5.4 4 0 51 \nPrivate oonsumpffon -2 0 -19 10 4 100 -50\nGeneral govemment consumption -5.1 -0 2 41.3 27 9 -100\nGross domestic Investment -06 3 0 50 - EOpois -tr-ports\nImports of goods and services -2 2 -151 85 0 61 3\n\n\nNote 2001 data are pretirrinary eastliates\n'The diamonds show four Key Indicators in the country (in bold) conipared with itS income-group average It data are missing, the diantond wiUt be rrconrrlte\n\n\n-56", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["2001 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008918", "page": 60, "chunk": 2, "title": "Ethiopia - Wolamo Agricultural Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/165661468252880794/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "2001 data", "label": "VAGUE_DATA", "score": 0.7082152366638184, "start": 639, "end": 648, "probe_score": 0.0183, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "-**\n**patriated. In recent years, UNHCR**\n**and States have worked to increase**\n**the use of resettlement as a strategic**\n**durable solution–serving to resolve**\n**some protracted refugees situations,**\n**to create protection space, and to**\n\n\n**15** The need for durable solutions is not limited to\nrefugees: IDPs and stateless persons also require lasting\nresolution to their legal and physical protection needs.\nHowever, due to the lack of reliable and comprehensive\ndata on solutions for other groups, the analysis in this\nsection is confined to durable solutions for refugees.\n\n\n**16** Based on consolidated reports from countries of\nasylum (departure) and origin (return).\n\n\n\n\n\n**16** UNHCR Global Trends 2011 **UNHCR Global Trends 2011** **17**", "output": {"entities": {"named_data": ["UNHCR Global Trends 2011", "UNHCR Global Trends 2011"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001077", "page": 8, "chunk": 2, "title": "UNHCR Global Trends 2011 - A Year in Crisis", "pdf_url": "https://reliefweb.int/attachments/a292fa5d-89b4-372c-8970-0cf327ad3293/4fd6f87f9.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "UNHCR Global Trends 2011", "label": "NAMED_DATA", "score": 0.7634857892990112, "start": 693, "end": 717, "probe_score": 0.9991, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHCR Global Trends 2011", "label": "NAMED_DATA", "score": 0.5808641910552979, "start": 720, "end": 744, "probe_score": 0.9965, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 2\nPage 4 of 4\n\n**Project Component 3 -** US$ **4.10 million**\n\n**Improve the Government's Capacity to Manage Sector Reforms** will be addressed through:\n(i) supporting the activities of the CNOSEGE in its effort to coordinate the reforms and raise\nresources to support the reform; (ii) capacity building support to the Ministry of Education key\nunits such as the Planning Unit _(Service de la Planification),_ and the Education Projects Bureau\n(BEPE); and (iii) other technical assistance necessary to improve private public partnership in\neducation, development of an effective gender strategy, and possible reforms in textbook policy.\n\n\n_Detailed Description of Sub-components:_\n\n\n_(i) CNOSEGE:_ The Executive Secretariat of CNOSEGE is responsible for implementing the\nreform program. The project will finance the secretariat including its fund-raising activities.\n\n\n_(ii) Support to MOE Planning Unit:_ The project will finance capacity building of the Ministry of\nEducation's Planning Unit, through expert assistance in dealing with the collection of educational\nstatistics, the production of a _carte scolaire_ and analysis of census or household survey data, and\nkey staff in the BEPE including the purchase of project management tools (finance and\nprocurement). The planning unit will also carry out the monitoring and evaluation studies\nrequired under the project. In addition, the unit will implement and monitor the Environmental\nManagement Plan (EMP).\n\n\n_(iii) Additional Technical Assistance_ will also be provided to enable the ministry to develop more\ncost effective strategies including exploring the possibility of cost effective public/private\npartnerships. Technical Assistance will also be provided to develop strategies to reduce the\ngender gap in enrollments as well as the gap by income group. Pilot studies will also be financed\nunder the credit for optimal designs in school construction, demand financing, sanitation upkeep\nand maintenance, and", "output": {"entities": {"named_data": [], "descriptive_data": ["census or household survey data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000100", "page": 35, "chunk": 0, "title": "Bosnia and Herzegovina - Second Electric Power Reconstruction Project", "pdf_url": "http://documents1.worldbank.org/curated/en/583901468768013967/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "census or household survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8749487400054932, "start": 1138, "end": 1169, "probe_score": 0.5876, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Table** **1:** Transitions among young (18-21 years old) between work statuses\n\n\n<u>No</u> <u>work</u> <u>Informal</u> <u>work</u> <u>Formal</u> <u>work</u> <u>Total</u>\n\n\nNo work 78 _._ 93 15 _._ 43 5 _._ 64 100\nInformal work 26 _._ 37 63 _._ 07 10 _._ 56 100\n<u>Formal</u> <u>work</u> <u>15</u> <u>14</u> _<u>.</u>_ <u>92</u> <u>70</u> _<u>.</u>_ <u>07</u> <u>100</u>\n\n\n<u>Total</u> <u>53</u> _<u>.</u>_ <u>06</u> <u>29</u> _<u>.</u>_ <u>09</u> <u>17</u> _<u>.</u>_ <u>85</u> <u>100</u>\n\n\n_Notes:_ Author’s calculations using panel data from 2018 and 2019 ENOE surveys.\nTable presents the average probability of maintaining or changing work status from\none period to the next. The rows reflect the initial status, and the columns reflect\nthe final status. Youth are followed for four quarters (3 month periods) between\n2018 and 2019 in staggered cohorts.\n\n\nthe probability of transitioning to formal work from non-employment (5.6%", "output": {"entities": {"named_data": ["ENOE surveys"], "descriptive_data": [], "vague_data": ["panel data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001134", "page": 10, "chunk": 0, "title": "idu0f413d1c0085320451a0b09205fa6e11c0977", "pdf_url": "https://local/prwp/idu0f413d1c0085320451a0b09205fa6e11c0977.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "panel data", "label": "VAGUE_DATA", "score": 0.6598823666572571, "start": 530, "end": 540, "probe_score": 0.9963, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "ENOE surveys", "label": "NAMED_DATA", "score": 0.8992067575454712, "start": 560, "end": 572, "probe_score": 0.9844, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " By the end<br>of Project, it is expected that MYDPs will have been approved and completed for all SLMP-2<br>watersheds, plus 17 new RLLP watersheds.<br>This indicator measures the number of watersheds in the project area for which an MYDP<br>has been approved by the Woreda or regional SLMP coordination platform and fully<br>implemented. In a given major watershed, the MYDP is a collection of multi-year plans for<br>each micro-watershed targeted by the project. The MYDP includes baseline data, basemaps,<br>and detailed information on the activities and interventions prescribed to stabilize each of<br>the targeted micro-watersheds (with timelines and budgets).<br>Each activity within a MYDP is assigned an associated activity area. Percent completion of<br>each MYDP is measured as the sum of the activity areas of completed activities, relative to<br>the total activity area of all the activities included in the MYDP. Note that the sum of the<br>activity areas included in a MYDP is less than the total area of the micro watersheds that will<br>be considered treated when the MYDP is completed.|The Multi-Year Development Plan (MYDP) defines the SLM activities that will be undertaken<br>by the Project to treat each target watershed. At the start of RLLP, 90 MYDPs have been<br>approved for the SLMPII watersheds, and all are more than halfway completed. By the end<br>of Project, it is expected that MYDPs will have been approved and completed for all SLMP-2<br>watersheds, plus 17 new RLLP watersheds.<br>This indicator measures the number of watersheds in the project area for which an MYDP<br>has been", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001481", "page": 7, "chunk": 3, "title": "Disclosable Version of the ISR - Second Ethiopia Resilient Landscapes and Livelihoods Project - P174385 - Sequence No : 7", "pdf_url": "https://documents.worldbank.org/curated/en/099032525151531980/pdf/P174385-a52948c7-6825-44f3-9b20-a53380705961.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "baseline data", "label": "VAGUE_DATA", "score": 0.5765576958656311, "start": 484, "end": 497, "probe_score": 0.0316, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda: Investment for Industrial Transformation and Employment (P171607)\n\n\n\nPage 56 of 92", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000021", "page": 61, "chunk": 0, "title": "Uganda - Investment for Industrial Transformation and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/469061641926083502/pdf/Uganda-Investment-for-Industrial-Transformation-and-Employment-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*|**80**|||||**35**|||**105**|*****||\n|ALEMANIA||*****<br>**104**<br>**93**|||||||||**98**<br>**90**|||\n|||||||||||||||\n\n\n\n120 100 80 60 40 20 0 20 40 60 80 100 120\n\n\n***** Algunas cifras superan el 100% porque las tasas brutas de inscripción incluyen a estudiantes que superan la edad;\n\npor ende, el total puede ser superior a la población del rango etario oficial.\n\n\nLas cifras de la población de acogida de Kenia corresponden a 2019 y las de Alemania, a 2018.\n\n\nLas cifras de México corresponden a 2019-2020 en el caso de las personas refugiadas y a 2018 en el caso de las\n\npersonas no refugiadas.\n\n\n**Fuente:** DATOS DE LAS OPERACIONES DE ACNUR EN EL PAÍS, UNESCO-UIS Y EL MINISTERIO DE EDUCACIÓN DE KENIA.\n\n\n**1 0** A C N U R > **I N F O R M E D E E D U C A C I Ó N 2 0 2 1 > M A N T E N I E N D O E L R U M B O**", "output": {"entities": {"named_data": ["DATOS DE LAS OPERACIONES DE ACNUR"], "descriptive_data": ["cifras de México"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001470", "page": 9, "chunk": 1, "title": "Manteniendo el Rumbo: Los desafíos que enfrenta la educación de las personas refugiadas", "pdf_url": "https://reliefweb.int/attachments/e4b8e725-87c2-33df-9fe8-f675aaacb4af/61365bed4.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "cifras de México", "label": "DESCRIPTIVE_DATA", "score": 0.5001240968704224, "start": 469, "end": 485, "probe_score": 0.897, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "DATOS DE LAS OPERACIONES DE ACNUR", "label": "NAMED_DATA", "score": 0.6136354207992554, "start": 615, "end": 648, "probe_score": 0.9567, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nStrengthening Lebanon’s Covid-19 Response (P178587)\n\n\nguidance on how to respond to these cases will be developed and shared with operators. The GRM will continue to\nbe publicized by the MOPH. As of April 10, 2022, the GRM operator reported a total of 1.12 million consultations\nreceived. <sup>13</sup> [^13: MoPH COVID-19 surveillance in Lebanon, April 10, 2022; 411,643 calls on 1787 hotline and 708,187 calls on 1214 hotline.]\n\n\n**<mark>VI.</mark>** **<mark>GRIEVANCE REDRESS SERVICES</mark>**\n84. Communities and individuals who believe that they are adversely affected by a World Bank supported project may\nsubmit complaints to existing project-level grievance redress mechanisms or the World Bank’s Grievance Redress\nService (GRS). The GRS ensures that complaints received are promptly reviewed to address project-related concerns.\nProject affected communities and individuals may submit their complaint to the World Bank’s independent\nInspection Panel which determines whether harm occurred, or could occur, because of World Bank non-compliance\nwith its policies and procedures. Complaints may be submitted at any time after concerns have been brought directly\nto the World Bank's attention, and World Bank Management has been given an opportunity to respond. For\ninformation on how to submit complaints to the World Bank’s corporate Grievance Redress Service (GRS), please\nvisit: [http://www.worldbank.org/en/projects-operations/products-and-services/grievance-redress-service.](http://www.worldbank.org/en/projects-operations/products-and-services/grievance-redress-service) For\ninformation on how to submit complaints to the World Bank Inspection Panel, please visit _[www.inspectionpanel.org](http://www.inspectionpanel.org/)_ .\n\n\n**", "output": {"entities": {"named_data": ["MoPH COVID-19 surveillance in Lebanon"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000000", "page": 41, "chunk": 0, "title": "Lebanon - Strengthening Lebanon's COVID-19 Response under the COVID-19 Strategic Preparedness and Response Program (SPRP)", "pdf_url": "http://documents.worldbank.org/curated/en/099410007282239961/pdf/BOSIB09c1bfedd05c098380dc89cfe988b8.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "MoPH COVID-19 surveillance in Lebanon", "label": "NAMED_DATA", "score": 0.6341341137886047, "start": 328, "end": 365, "probe_score": 0.804, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\n- Internet enabled phone users, adults\n\n\n- Internet enabled phone users, elderly\n\n\n- Non-phone users, all ages\n\n\nIn addition, the research team facilitated discussions\nwith the following special user groups:\n\n\n- Community leaders\n\n\n- VSLG group members and entrepreneurs\n\n\n- Mobile agents\n\n\n- Charging station operators\n\n\n- INS school students, aged 12-18\n\n\n- INS school teachers\n\n\nHousehold survey of 484 refugee households,\nincluding 244 Burundian refugees, 240 Congolese\nrefugees, 243 men and 241 women, across 11 of the\n12 camp zones. A stratified random sample was\nused to ensure a representative sample of gender,\nage and nationality. All respondents were over the\nage of 18. Responses were gathered from three age\nstrata, including 176 18-25 year olds (36 per cent),\n240 26-50 year olds (50 per cent) and 68 51 years\nand over (14 per cent), corresponding to the age\ndemographic of the total camp population. The\nsurvey collected quantitative data on household and\npersonal access to, use of and ownership of mobile\ndevices, as well as use cases, expenditure and\nconfidence. The survey was administered digitally\nby a team of eight trained local researchers, over\nfive consecutive days.\n\n\n\nThe quantitative and qualitative data presented in\nthis report was gathered by Jigsaw Consult in April\nand May 2017. A mixed methods approach was\nused to gather the perceptions and experiences\nof different stakeholders, including the refugee\npopulation, mobile agents and humanitarian agency\nstaff.\n\n\nPrior to conducting field research, a kick-off\nworkshop was conducted by the Jigsaw Consult\nteam together with members of the GSMA team to\ndiscuss priority research questions, identify existing\nresearch materials and finalise the methodological\napproach. A desk review and series of remote\ninterviews with MNOs, UNHCR and partner agencies\nwas conducted to understand the insights and\npriorities of key stakeholders, and gaps in current\nknowledge and research.\n\n\n\nField research was conducted by the Jigsaw Consult\nteam in Nyarugusu camp in May 2017, facilitated by\nUNHCR. The approach consisted of", "output": {"entities": {"named_data": [], "descriptive_data": ["Household survey of 484 refugee households"], "vague_data": ["quantitative data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001202", "page": 24, "chunk": 1, "title": "Mobile is a Lifeline: Research from Nyarugusu Refugee Camp, Tanzania", "pdf_url": "https://reliefweb.int/attachments/b8a70c46-0699-36bc-a80b-b0381b5033de/60300.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Household survey of 484 refugee households", "label": "DESCRIPTIVE_DATA", "score": 0.8787492513656616, "start": 383, "end": 425, "probe_score": 0.4751, "gold": "NON_MENTION", "gold_tier": "human-final"}, {"text": "quantitative data", "label": "VAGUE_DATA", "score": 0.6213714480400085, "start": 937, "end": 954, "probe_score": 0.6073, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Public Disclosure Copy\n\n\n**The World Bank** Implementation Status & Results Report\nKenya Cash Transfer for Orphans and Vulnerable Children (P111545)\n\n\nOverall, the project is progressing toward meeting the Development Objectives in a satisfactory manner, although some challenges remain.\n\n\n(i) The project has fully disbursed the credit proceeds under the Cash Transfer component in the original IDA credit. The Policy Development and\nInstitutional Strengthening component however continues to experience some delays in procurement. With additional financing for the same component\nto support the broader National Safety Net Program it is critical that technical assistance activities be implemented more expediently. The government\nteam is however making efforts to speed up implementation of the technical assistance and a Joint Review and Implementation Support (JRIS) mission\nis scheduled for June, 2015 to review implementations status of key activities.\n\n\n(ii) Scale-up in coverage of benefiting households: Currently, a total of about 240,000 households are enrolled in the CT-OVC program and are\nreceiving payments, which is well above the original target of the project (of less than 100,000 households). Following the increase in financial\nresources allocated by the Government of Kenya to the Program last fiscal year an additional 90,000 households were enrolled in the program before\nthe end of June 2014. Since there was no increase in budget allocation for this fiscal year, there are no plans to target additional beneficiaries before the\nend of June, 2015. The government is however committed to continue expanding the CT-OVC program and an expansion plan for the National Safety\nNet Program as a whole (including the CT-OVC program) was finalized and approved by the Cabinet Secretary Ministry of Labor, Social Security and\nServices. The expansion plan outlines the planned numbers of households to be enrolled in the coming years and the geographic targeting is informed\nby poverty and vulnerability data. The government is also committed to developing a harmonized targeting approach to increase efficiency of the overall\ntargeting of the NSNP programs. It", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["poverty and vulnerability data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010001", "page": 1, "chunk": 0, "title": "Kenya - Kenya Cash Transfer for Orphans and Vulnerable Children : P111545 - Implementation Status Results Report : Sequence 13", "pdf_url": "https://documents.worldbank.org/curated/en/236931468272403898/pdf/ISR-Disclosable-P111545-05-27-2015-1432755522895.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "poverty and vulnerability data", "label": "VAGUE_DATA", "score": 0.7135429382324219, "start": 1993, "end": 2023, "probe_score": 0.8842, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 𝑅 ~~≥~~ ~~<u>pR</u>~~ <u>70−15</u>\n\n\n\n**NROCs** Non-resource output\noriented countries\n\n**LOGCs** Low-output growth\n\n\n\n**<u>Definition</u>** ~~<u>90</u>~~\n\n~~𝑅~~ <sup>~~�~~</sup> 𝑅 ~~≥~~ ~~<u>pR</u>~~ <u>70−15</u>\n\n90\n\n𝑅𝑅 <sup>�</sup> < pR70−15\n\n\n\n~~<u>90</u>~~\n\n~~𝑅~~ <sup>~~�~~</sup> 𝑅 ~~≥~~ ~~<u>pR</u>~~ <u>70−15</u>\n\n90\n\n𝑅𝑅 <sup>�</sup> < pR70−15\n\n30\n\n𝑔𝑔�𝑦𝑦 ≤ py70−15\n\n𝑔 𝑦\n\n\n\n**<u>Country examples</u>**\n\n<u>Algeria, Cameroon, Myanmar, and Venezuela.</u>\n~~<u>90</u>~~\n\n𝑅 ~~R~~ <u>70−15</u>\n\n\n\n𝑅 Argentina, Finland, Japan, and Vietnam\n\n90\n\nR70−15\n\n\n\noriented countries\n\n\n\n𝑅\n\n\nHaiti, Madagascar, Niger, and Zimbabwe\n30\n\ny70−15 Belgium, Ecuador, Nigeria, and Pakistan\n\n70\n\n<u>𝑦𝑔</u> 𝑦 <u>≤</u> <u>py70−15</u> Bulgaria, Chile, China, and South Korea\n\n<u>70</u", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002357", "page": 15, "chunk": 1, "title": "uncertainty in ex ante poverty and income distribution insights from output growth and natural resource country typologies", "pdf_url": "https://local/prwp/uncertainty-in-ex-ante-poverty-and-income-distribution-insights-from-output-growth-and-natural-resource-country-typologies.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "||**X**|\n|Projects in Disputed Areas OP/BP 7.60|Projects in Disputed Areas OP/BP 7.60|Projects in Disputed Areas OP/BP 7.60|||||**X**|\n|**Legal Covenants**|**Legal Covenants**|**Legal Covenants**|**Legal Covenants**|**Legal Covenants**|**Legal Covenants**|**Legal Covenants**|**Legal Covenants**|\n|**Name** <br> <br>|**Recurrent**|**Due Date**|**Due Date**|**Due Date**|**Due Date**|**Frequency**|**Frequency**|\n\n\nix", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000173", "page": 8, "chunk": 5, "title": "Somali - Urban Investment Planning Project", "pdf_url": "http://documents1.worldbank.org/curated/en/965101617648211610/pdf/Somali-Urban-Investment-Planning-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "ine Ramstad.\n\n\nNRC Kenya assisted with identifying interviewees in Dadaab. The agency has no role in status\ndetermination or resettlement decisions, but their participation could be problematic since they\nare among the service providers in the refugee camps. We also chose to have an NRC\nrepresentative present during most interviews in Dadaab. This was due to interpretation needs,\nNRC Kenya’s ability to provide experience-based comments along the way and to ensure that\ncritical issues that were raised by interviewees could be noted and addressed by NRC or another\nagency.\n\n\nThe interviews took place in NRC offices in the camps. Although movement was severely\nrestricted due to security concerns, there were some visits in the camps and a certain level of\nparticipatory observations. In Egypt, the Arab Network for Environment and Development\n(RAED) and the Psycho-Social Training Institute in Cairo (PSTIC) provided support. The group\ndiscussion took place in the offices of RAED due to security concerns.\n\n\nIn addition interviewing the displaced Somalis, a short desk-study and other key stakeholder\ninterviews were undertaken. Interviewees included NRC, UNHCR and other humanitarian and\ndevelopment agency staff in Kenya and Egypt as well as government officials. We also had one\ndiscussion group (10 people) in Dadaab consisting of people belonging to the host community.\nThe information from the interviews with the displaced people informed the desk-study and\nthese other interviews and vice versa so there was a constant dynamic between the different\nmethods and data sources used. The study also draws on some existing quantitative data\n(Enghoff et al., 2010; Refugee Consortium of Kenya, 2012).\n\n\n3", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["quantitative data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001648", "page": 4, "chunk": 1, "title": "Gaps in Geneva, gaps on the ground: case studies of Somalis displaced to Kenya and Egypt during the 2011 drought", "pdf_url": "https://reliefweb.int/attachments/fe1dff8e-4eb1-3095-977d-9842c4cdfc7c/50c88dbc9.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "quantitative data", "label": "VAGUE_DATA", "score": 0.7852296233177185, "start": 1632, "end": 1649, "probe_score": 0.5935, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Endnotes**\n\n\n_[i Save the Children, More than a third of children surveyed in Afghanistan pushed into child labour, as country marks two years of Taliban](https://reliefweb.int/report/afghanistan/more-third-children-surveyed-afghanistan-pushed-child-labour-country-marks-two-years-taliban-rule#:~:text=KABUL%2C%2015%20August%202023%20%E2%80%93%20More,the%20Children%20said%5Bi%5D.)_\n_[rule - survey of households in six provinces, August 2023](https://reliefweb.int/report/afghanistan/more-third-children-surveyed-afghanistan-pushed-child-labour-country-marks-two-years-taliban-rule#:~:text=KABUL%2C%2015%20August%202023%20%E2%80%93%20More,the%20Children%20said%5Bi%5D.)_\n_[ii UNOCHA, Afghanistan: The alarming effects of climate change by UN Humanitarian - Exposure, 2023](https://unocha.exposure.co/afghanistan-the-alarming-effects-of-climate-change)_\n_[iii UNOCHA, Revised Herat Earthquake Response Plan Afghanistan, 2023](https://reliefweb.int/report/afghanistan/afghanistan-revised-herat-earthquake-response-plan-october-2023-march-2024-november-2023-endarips)_\n_[iv GiHA, Gender Update #1: Forced returns from Pakistan, 2023](https://", "output": {"entities": {"named_data": [], "descriptive_data": ["survey of households in six provinces"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001355", "page": 16, "chunk": 0, "title": "Afghanistan Protection Analysis Update - Update on protracted-crisis and climate-related protection risks trends, May 2024", "pdf_url": "https://reliefweb.int/attachments/d1801032-9ba3-4a6b-9712-b68c28f20d27/pau24_05_protection_analysis_update_afghanistan_may_2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "survey of households in six provinces", "label": "DESCRIPTIVE_DATA", "score": 0.7978385090827942, "start": 394, "end": 431, "probe_score": 0.9755, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "While those countries account for half of the schoolage refugees, their share of the financing envelope is\nonly 20 percent. In other words, **a fifth of the total cost**\n**would cover more than 50 per cent of school-age**\n**refugee children.**\n\n\n2 A broader donor base is needed\n\n\nRefugee education funding is over-reliant on three\nsources of development aid: the US, EU and Germany.\nBut some key alternative forms of funding have\nemerged.\n\n\n» **The World Bank** has committed to scaling up\n\nand coordinating support for refugee education\nin collaboration with other international and\nlocal partners (via its Regional Sub-Window for\nRefugees and Host Communities, under the bank’s\nInternational Development Association).\n\n\n» **The Global Partnership for Education (GPE)** works\n\nwith countries in crisis and conflict, helping to\nstrengthen capacity and resourcing. In 2021, 62 per\ncent of <u>[GPE implementation grants were allocated to](https://assets.globalpartnership.org/s3fs-public/document/file/2022-06-GPE-factsheet-education-refugee-children.pdf?VersionId=UHXFdjR72eTH3kXrdh8bye_kHivOGgqi)</u>\npartner countries affected by fragility and conflict.\n\n\n» **Education Cannot Wait (ECW)** is a global fund\n\ndedicated to education in both emergencies and\nprotracted crises. Since its inception, ECW has\ndisbursed US$680 million in grants to 71 entities\nworking in 46 countries. <sup>16</sup> [^16: ECW grant database, reviewed 17/03/2022] Its 232 emergency\nresponses and 55 multi-year programmes have\nreached over 33 million children.\n\n\n» **Philanthropic foundations and the private sector**,\n\nparticularly when financing is provided through\npartnerships, offer good examples of supporting\nhigh-impact programmes that focus on refugee\neducation.", "output": {"entities": {"named_data": ["ECW grant database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001255", "page": 28, "chunk": 0, "title": "UNHCR Education Report 2022 - All Inclusive: The Campaign for Refugee Education", "pdf_url": "https://reliefweb.int/attachments/c0da3279-23fc-430b-85ab-e28e64895dc7/631ef5a84.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "ECW grant database", "label": "NAMED_DATA", "score": 0.8628643751144409, "start": 1400, "end": 1418, "probe_score": 0.894, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on social development issues"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009602", "page": 24, "chunk": 0, "title": "Uganda - Third Phase of the Road Development Program Project", "pdf_url": "https://documents.worldbank.org/curated/en/212371468782358386/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "data on social development issues", "label": "VAGUE_DATA", "score": 0.581004798412323, "start": 1670, "end": 1703, "probe_score": 0.333, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " elderly and disabled; access to WASH facilities for\npeople with pre-existing, severe physical, neurological or mental disabilities or disorders, as well as persons\nsuffering from chronic illness (WASH WG-Lebanon, February 2014). However, the majority of needs\nassessments reviewed for this MNSA do not identify the unique WASH needs of, or challenges experienced\nby, vulnerable groups in Lebanon.\n\n_Syrian refugees_\n\nAssessments have highlighted the unique concerns and challenges women and children face in terms of\nhygiene. A Lack of access to WASH facilities may affect women‘s reproductive health; some focus group\nparticipants spoke about experiencing menstrual problems and infections as a result of not being able to wash\nproperly,though this was not supported with medical data(ABAAD-OXFAM, September 2013).Although the\nissue of water accessibility is not an issue for schools, critical issues are the unhygienic latrines and washing\nfacilities, which require urgent attention from the MEHE and civil society. (Education Working Group, August\n2013)\n\n\n_Mount Lebanon and South_\n\nPwSN have unique WASH challenges. The term PwSN includes persons with disabilities (those with mobility\nproblems, hearing and visual impairments, intellectual impairments, and mental/psychological impairments),\nchronic diseases (those needing regular medication and/or treatment at a healthcare centre), and older\npersons (those over 60). In an assessment that focused on Mount Lebanon (including Beirut) and the South\nGovernorates, 72.8% of respondents after some prompting stated that they have concerns about WASH\nrelated issues for PwSN, specifically:\n\n\n8Persons with specific needs include but are not limited to persons with disabilities, single-headed households, older persons at risk,\nunaccompanied and separated children, other children at risk, survivors of torture and sexual and gender-based violence (SGBV),\npersons with serious medical conditions.(RRP6)\n\n41", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["medical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000826", "page": 40, "chunk": 1, "title": "MSNA sector chapters - WASH", "pdf_url": "https://reliefweb.int/attachments/79c2ffd5-a9fe-3795-ae41-c38096a16c71/WASH%20CHAPTER%20-FINAL%20April%2022.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "medical data", "label": "VAGUE_DATA", "score": 0.7360807061195374, "start": 774, "end": 786, "probe_score": 0.8211, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "diary, effectively blurring the line between consumption data collected by diary and by recall interview.\n\n\nThis mediation by interviewers is especially likely since most diary surveys instruct interviewers to return\n\n\nevery few days to update the diary in cases where it may not be completed by household members, such\n\n\nas in households with no literate adults.\n\n\nWhile well-implemented diary surveys might be expected to yield higher (and presumably closer\n\n\nto actual) levels of consumption, experimental evidence for this from developing countries is\n\n\nfragmentary. In urban Papua New Guinea, Gibson (1999) found that mean total expenditure per capita\n\n\nwas 14 percent higher (and food consumption 26 percent higher) using a diary rather than a recall survey.\n\n\nHowever, preliminary comparisons of consumption from the Bosnia and Herzegovina LSMS (recall)\n\n\nsurvey with the household budget survey (diary) in 2004 show levels to be similar (World Bank, 2006).\n\n\nThese studies pertain to household-level diaries and thus do not address an important source of\n\n\nmis-measurement – the difficulty of a sole respondent to perfectly capture total household consumption.\n\n\nPersonal diaries are generally considered better for obtaining complete household expenditure or\n\n\nconsumption data because it is unusual, in most societies, for any one household member to know the\n\n\nexpenditure/consumption of every other member, especially on items such as alcohol, tobacco, daily\n\n\ntravel, personal toiletries, daily newspapers/magazines, and meals (especially snacks and lunches) eaten\n\n\noutside the home. In Russia, as part of an effort to study the reliability of the Household Budget Survey, a\n\nrandom sample of households in the 3 <sup>rd</sup> quarter of 2003 were assigned personal diaries rather than the\n\n\nhousehold diary. The personal diary yielded expenditure levels which were 6-11 percent higher than a\n\n\nhousehold diary (World Bank, 2005). However, the personal diary was plagued with non-respondent\n\n\nproblems in this experiment; about 54 percent of households assigned the personal diary did not complete\n\n\nit. Personal diaries", "output": {"entities": {"named_data": ["Bosnia and Herzegovina LSMS", "Household Budget Survey"], "descriptive_data": ["household budget survey"], "vague_data": ["consumption data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004687", "page": 7, "chunk": 0, "title": "wps5501", "pdf_url": "https://local/prwp/wps5501.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "consumption data", "label": "VAGUE_DATA", "score": 0.7689362168312073, "start": 45, "end": 61, "probe_score": 0.9299, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Bosnia and Herzegovina LSMS", "label": "NAMED_DATA", "score": 0.542892575263977, "start": 824, "end": 851, "probe_score": 0.9895, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "household budget survey", "label": "DESCRIPTIVE_DATA", "score": 0.7418228387832642, "start": 879, "end": 902, "probe_score": 0.9511, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Household Budget Survey", "label": "NAMED_DATA", "score": 0.5030252933502197, "start": 1662, "end": 1685, "probe_score": 0.9011, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". Bram Jansen’s recent\nstudy of repatriation from Kakuma camp to South Sudan, for example, records UNHCR’s\ncareful control of go-and-see visits, with leaders “warned by UNHCR not to make any\npublic comments about his trip until some days later... after the team had met and agreed\nupon a common statement” (Jansen 2011: 220).\n\n\n104. UNHCR has also at times displayed a conviction that its staff are better placed than\nrefugee leaders to understand the ‘average’ refugee’s desire to return. This attitude\nundoubtedly reflects experiences in camps where refugees have been subject to\nmanipulation by political elites interested in protecting their position by preventing largescale repatriation, most notoriously in the case of Rwanda’s Hutu extremists after the\ngenocide.\n\n\n105. Such cases appear to have fed into a widespread belief that refugee leaders do not\nrepresent the wishes of refugee populations, and that UNHCR involvement is required so\nthat they can exercise their right to voluntary return. According to the minutes of one\nUNHCR working group in April 1997, “some participants also questioned the validity of\ninsisting on individual voluntariness in repatriation, when refugees are being prevented\nfrom exercising their free will by a minority of militants” (UNHCR Archives).\n\n\n106. As a result of these considerations, as well as the state-centric nature of the\norganization, UNHCR has proved very reluctant to facilitate refugee representation in\nrepatriation processes, even as part of the Tripartite Commissions that frame nearly all\nrepatriation agreements. Yet the potential contribution of refugees to such discussions is\nobvious: in explaining their own interests in and conditions for repatriation, both the\nvoluntariness and sustainability of such movements can be reinforced. Ultimately, UNHCR\n\n\n18", "output": {"entities": {"named_data": ["UNHCR Archives"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001136", "page": 20, "chunk": 1, "title": "Back to where you once belonged: A historical review of UNHCR policy and practice on refugee repatriation", "pdf_url": "https://reliefweb.int/attachments/ac0e243a-1e3f-3352-9041-953b9c015fbd/5225d5de9.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "UNHCR Archives", "label": "NAMED_DATA", "score": 0.8156911134719849, "start": 1272, "end": 1286, "probe_score": 0.0022, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "months o f project implementation, which provides the basis for the procurement methods.\nThis plan has been agreed between the Borrower and the Task Team during negotiations on\nOctober 14, 2004 and i s available at the GLIA Executive Secretariat at glia@rwandal.com or\nother specified GLIA website. It will also be available in the Project’s database and in the\nBank’s external website. The Procurement Plan will be updated in agreement with the Task\nTeam annually or as required to reflect the actual project implementation needs and\nimprovements in institutional capacity.\n\n\nAll goods contracts estimated to cost USD 250,000 or more will be subject to the Bank’s\nprior review in accordance with the procedures in Appendix I o f the Procurement Guidelines.\nAny amendments to existing contracts raising their values to levels equivalent or above the\nprior review thresholds are subject to IDA review. All contracts awarded on basis o f direct\ncontracting will require prior review and clearance o f IDA.\n\n\nAll single source selection will be subject to IDA prior review. Consultancy contracts with\nfirms with estimated value o f USD 100,000 or more, and consultancy contracts with\nindividuals estimated value o f USD 50,000 or more will be subject to prior review by the\nIDA in accordance with the procedures in Appendix I o f the Consultants Guidelines. All out\n\n- f country training/workshops will be subject to IDA review.\n\n\nTable A: Thresholds for Procurement Methods and Prior Review\n\n\n\nContract Value Contracts Subject\n\n\n\nExpenditure\nOrSD) Procurement Method\n\nCategory Based on estimate in\n\n\n\nto Prior Review\n\n(USD millions)\n\n\n\nProcurement Method\n\nCategory Based on estimate in (USD millions)\nthe procurement plan Estimated\n\n\n\n1. Works <250,000 NCB Not Expected\n\n\n\n< 50,000\n2. Goods - 250,000\n\n\n\nShopping\n\n\n\nPost Review\n\n\n\nAll\nThe first 3\n\n\n\n<250,000\n\n\n\n<50,000\n\n\n\nI C B\nNCB\nShopping\n\n\n\n3. Consulting - 100,000\nServices: Firms < 100,000\n\n< 50,000\n\n          - 10,000\nIndividuals -", "output": {"entities": {"named_data": [], "descriptive_data": ["Project’s database"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000021", "page": 59, "chunk": 0, "title": "Africa Region - Great Lakes Initiative on HIV/AIDS (GLIA) Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/188651468741666540/pdf/30267.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Project’s database", "label": "DESCRIPTIVE_DATA", "score": 0.7937772870063782, "start": 332, "end": 350, "probe_score": 0.0139, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a v\nManufacturIng 5 7 3.7 4 7 5 0 / s \\\\t oo  Services 475 272 190 201\n\nPrfvate consumpffon 90 7 81 9 938 95 1 20\nGeneral govemment consumption 7 0 9 6 146 17.2 =c ~GDFDl\nImpons of goods and servrcea 39 7 23 6 33 4 373 -3GW_G_____\n\n\n_(average_ _annual growth)_ 1981-9 1991401 2000 2001 Growth ot exports and Imports (%)\n\nAgrutumre -0 6 -2 6 2 2 3 8 oo\nIndustry 0.1 -41 51 5 6 s0\nManUnacturIng 6.9 . .\nServices -5 7 -5.4 4 0 51 \nPrivate oonsumpffon -2 0 -19 10 4 100 -50\nGeneral govemment consumption -5.1 -0 2 41.3 27 9 -100\nGross domestic Investment -06 3 0 50 - EOpois -tr-ports\nImports of goods and services -2 2 -151 85 0 61 3\n\n\nNote 2001 data are pretirrinary eastliates\n'The diamonds show four Key Indicators in the country (in bold) conipared with itS income-group average It data are missing, the diantond wiUt be rrconrrlte\n\n\n-56", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["2001 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000104", "page": 60, "chunk": 2, "title": "East Timor - Fundamental School Quality Project", "pdf_url": "http://documents1.worldbank.org/curated/en/597541468309559446/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "2001 data", "label": "VAGUE_DATA", "score": 0.7082152366638184, "start": 639, "end": 648, "probe_score": 0.0183, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|employers and private sectors other operational situation Participatory<br>/chambers partners working in and Assessments<br>the areas (e.g., GIZ funding)<br>-collecting individual person-specific Economic Inclusion<br>skills profile data from interested Project Team (with<br>refugees and host communities across key components on<br>all 6 camps, refugee hosting districts labour, skills, and<br>and urban areas through call for employment),<br>expression of interest to register INKOMOKO,<br>themselves (online/paper-based) in their Indego Africa,<br>relevant skills categories with any Maison Shalom,<br>supporting documentations. WVI, Alight, Kepler)<br>-Refugee data may then be tagged with<br>the socio-economic profile module of<br>ProGres v4.<br>Adding skills questions during next<br>verification|Col2|Col3|Col4|Col5|Col6|Col7|\n|---|---|---|---|---|---|---|\n|Organizing a Livelihoods Sector<br>Working Group<br> <br>An open forum for regular discussion,<br>information sharing, mapping exercise,<br>new programming and fund mobilization<br>approach, review of targeting and<br>tracking<br>results<br>in<br>line<br>with<br>global/country<br>plans/strategies<br>(GoR/UNHCR/Partner agencies).<br>UNHCR Livelihoods<br>Team in partnership<br>with MINEMA, Ips,<br>DPs,<br>Other<br", "output": {"entities": {"named_data": [], "descriptive_data": ["skills profile data"], "vague_data": ["Refugee data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001259", "page": 58, "chunk": 0, "title": "MINEMA and UNHCR - Joint Strategy on Economic Inclusion of Refugees and Host Communities in Rwanda 2021-2024", "pdf_url": "https://reliefweb.int/attachments/c126efc8-bb6f-3b22-a152-a44a1b1be079/RWA--MINEMA-UNHCR_Joint_Strategy_of_economic_inclusion_of_refugees_and_host_communities_2021-2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "skills profile data", "label": "DESCRIPTIVE_DATA", "score": 0.8436228632926941, "start": 219, "end": 238, "probe_score": 0.2199, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Refugee data", "label": "VAGUE_DATA", "score": 0.6229816675186157, "start": 659, "end": 671, "probe_score": 0.3615, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nCHAD Improving Learning Outcomes Project (P175803)\n\n\n5. **Chad is highly vulnerable to shocks, whether climatic or security** including prolonged droughts in some areas and\nyearly floods in others, as well as wind erosion and desertification. These contribute to recurrent food crises and\npopulation displacements. Chad is also subject to repeated security threats, including Boko Haram and al Qaida in the\nIslamic Maghreb; and is classified as a Fragility, Conflict and Violence (FCV) country. As of June 30, 2021, there were\n508,307 refugees (mainly from the Sudan and the Central African Republic), as well as 401,511 internally displaced\npersons. <sup>3</sup> [^3: United Nations High Commissioner for Refugees (UNHCR), Operational Data Portal.] This places additional pressure on an education system which has already run out of steam.\n\n\nSectoral and Institutional Context\n\n\n6. **Pre-primary education is still nascent, a large share of primary education is managed by the community, and**\n**only few children can make it up to secondary education.** Pre-primary education is managed by the Ministry for Women\nand Early Childhood Protection (MFPPE) <sup>4</sup> [^4: Pre-primary education services are the responsibility of MFPPE. However, the Ministry of National Education and Civic Promotion (MENPC) is\nresponsible for pre-primary pedagogy.] . It lasts three years aimed at children aged 3-5 years, and the Gross Enrollment\nRate (GER) was 1.1 percent in 2019/20. Primary education is the first stage of basic education; by law, it is free and\ncompulsory. It consists of six years aimed at children aged 6-11 and is divided into three cycles of two years each:\npreparatory (CP), elementary (CE) and medium (CM). Successful completion of Grade Six, as determined by the primary\nschool, allows one to enter upon lower secondary education ( _enseignement", "output": {"entities": {"named_data": ["Operational Data Portal"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000009", "page": 3, "chunk": 0, "title": "Concept Project Information Document (PID) - CHAD Improving Learning Outcomes Project - P175803", "pdf_url": "http://documents.worldbank.org/curated/en/234501637169242309/pdf/Concept-Project-Information-Document-PID-CHAD-Improving-Learning-Outcomes-Project-P175803.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Operational Data Portal", "label": "NAMED_DATA", "score": 0.8268797993659973, "start": 743, "end": 766, "probe_score": 0.9372, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the immediate future. Furthermore, if there are\n\n\neconomies of scale over the domain of market demand, large firms could produce at lower\n\n\naverage costs than smaller ones; thus a competitive equilibrium would not be sustainable and\n\n\na valid policy argument can be made for the establishment of a large firm (or monopoly) in\n\n\norder to gain the benefits of these economies (Kim, 1987).\n\n\nWe define the concepts of cost function, economies of density and scale, and natural\n\n\nmonopoly in section 2. The specification of the cost function that is estimated for each of the\n\n\n2 The one study we found was conducted by Seroa da Motta and Moreira (2006) who compute returns to scale\nfrom a DEA approach using data from Brazil. Findings from this study will be discussed later.\n3 The International Benchmarking Network (IBNET) is developed by the World Bank with the objective to\nimprove the service delivery of water supply and sewerage utilities through the provision of international\ncomparative benchmark performance information. For more information, see www.ib-net.org", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data from Brazil"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003349", "page": 2, "chunk": 1, "title": "wps4137", "pdf_url": "https://local/prwp/wps4137.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "data from Brazil", "label": "VAGUE_DATA", "score": 0.7108087539672852, "start": 706, "end": 722, "probe_score": 0.7217, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " <u>(1.033)</u> <u>(0.054)</u> <u>(0.059)</u>\n\n<u>�</u> <u>wL</u> <u>�</u>\n\n\n\n\n<u>�</u>\n\n\n\n-0.0327 0.899 -0.0374 -0.0608\n\nPY it\n\n<u>(0.038)</u> <u>(1.033)</u> <u>(0.054)</u> <u>(0.059)</u>\n\n<u>�</u> <u>wL</u> <u>�</u>\n\nN 17871 858 16726 28925\n<u>R-sq</u> <u>.0571</u> <u>.0609</u> <u>.0589</u> <u>.0565</u>\n\n\n\nNote: Firm and year …xed e¤ects are always included. Data set: merged NBS and customs data. Column\n\n(1) uses the whole sample; columns (2) and (3) include only domestic private and foreign-invested …rms,\n\nrespectively. Column (4) includes …rms that operate in multiple industries as well. Bootstrapped standard\n\nerrors, clustered at the industry level, are reported in parentheses. - p<0.10; ** p<0.05; *** p<0.01.\n\n\n50", "output": {"entities": {"named_data": [], "descriptive_data": ["NBS and customs data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006537", "page": 52, "chunk": 2, "title": "wps7491", "pdf_url": "https://local/prwp/wps7491.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "NBS and customs data", "label": "DESCRIPTIVE_DATA", "score": 0.6104381084442139, "start": 380, "end": 400, "probe_score": 0.7973, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<u>THE ECONOMIC CASE</u>\n\n\nWe start by defining what we mean by trade facilitation. There is no universal understanding\n\n\n[of what trade facilitation is (Wilson et al., 2002), reflecting differences, as well as some](http://siteresources.worldbank.org/INTTRADECOSTANDFACILITATION/Resources/TradeFacilitationInAPEC.pdf)\n\n\nevolution, in views of what should be the reforms undertaken to reduce the cost of trading. In\n\n\nsimple terms trade facilitation can be thought as the simplification of the trade interface\n\n\nbetween partners. This trade interface is composed in a broad sense of compliance to\n\n\ngovernment rules by traders, enforcement by authorities of these rules (including taxes),\n\n\nexchange of information, financing, insurance, ICT and legal services, transport, handling,\n\n\nmeasurement and storage. We focus therefore in the rest of this paper on this broad\n\n\nconception of trade facilitation as the private and public interventions that help goods cross\n\n\nborders.\n\n\nGovernment interventions in all these aspects of the trade interface affect the magnitude of\n\n\ntransaction costs incurred by traders. For example, the sheer diversity of government\n\n\nregulations, and the replication of their enforcement causes duplication (e.g. compliance cost\n\n\n[with two different standards: Baldwin, 2000) and friction costs (e.g. time lost because of](http://www.nuca.ie.ufrj.br/infosucro/biblioteca/negociacoes/Baldwin_regulatory.pdf)\n\n\nrepeated loading and unloading of merchandise) that regional harmonization and cooperation\n\n\ncould conceptually help address (Schiff and Winters, 2003: 82).\n\n\n_The relevance of geography for the tangible and intangible dimensions of the supply_\n\n\n_chain_\n\n\nCountry borders create costly obstacles to international trade. The empirical reality of the\n\n\n“border effect” is demonstrated by the gravity model of international trade (for a recent\n\n\n[overview see: Anderson and Win", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003671", "page": 5, "chunk": 0, "title": "wps4464", "pdf_url": "https://local/prwp/wps4464.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda: Roads and Bridges in the Refugee Hosting Districts Project (P171339)\n\n\nbetween settlements, the wider Ugandan market and cross border trade. Traders from South Sudan and\nDRC visit the settlements regularly to supply as well as source goods and services. This presents an\nopportunity for local economic development that can address market constraints. The provision of an\nall-weather road transport infrastructure will help ease the burden on the other sectors by enhancing\nconnectivity of the host population and refugees to markets. The existing road infrastructure in West\nNile Sub-Region is of poor quality and not motorable especially during rains. Access to health facilities\nand referral medical units is also encumbered by the dilapidated road network.\n\n\n10. **Uganda was ranked 127** <sup>**th**</sup> **out of 162 countries in the 2018 Gender Inequality Index** <sup>9</sup> . **Gender**\n**inequalities are prevalent in refugee camps in Uganda.** Prevalence rates of gender-based violence (GBV)\nin Uganda are high. According to the Uganda Demographic and Health Survey (UDHS) <sup>10</sup>, 56 percent of\nwomen have experienced spousal violence and 22 percent sexual violence. The figures for Violence\nAgainst Children (VAC) and are also high, with 59 percent of females and 68 percent of males reporting\nexperiencing physical violence during childhood. <sup>11</sup> Adolescent girls in Uganda are more likely to be poor,\nmiss out on school and are at a greater risk of contracting HIV. <sup>12</sup> Of Ugandans ages 13-17 years, one in\nfour girls and one in ten boys reported sexual violence in 2015. <sup>13</sup> Nearly a quarter of teenage girls in\nUganda become pregnant.", "output": {"entities": {"named_data": ["2018 Gender Inequality Index", "Uganda Demographic and Health Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000001", "page": 5, "chunk": 0, "title": "Project Information Document - Uganda: Roads and Bridges in the Refugee Hosting Districts Project - P171339", "pdf_url": "http://documents.worldbank.org/curated/en/109301595258535610/pdf/Project-Information-Document-Uganda-Roads-and-Bridges-in-the-Refugee-Hosting-Districts-Project-P171339.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "2018 Gender Inequality Index", "label": "NAMED_DATA", "score": 0.8261807560920715, "start": 867, "end": 895, "probe_score": 0.9989, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Uganda Demographic and Health Survey", "label": "NAMED_DATA", "score": 0.9088181853294373, "start": 1068, "end": 1104, "probe_score": 0.9969, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Although economic migrants are restricted to specified professions and specified quotas, there is little\ndoubt that their presence has had an impact on the labor market.\n\n\n35. Until early 2016, Syrian refugees were not permitted to work in Jordan. <sup>16</sup> [^16: For more details on labor policies, please see the Technical Assessment of Labor Issues.] Since January 2016,\nthe Government has paved the way for Syrian refugees’ participation in the labor force through several\npolicy actions. These include (a) giving Syrian refugees preference over new economic migrants by\nplacing a temporary moratorium on bringing in new economic migrants and making work permits free\nfor Syrians refugees; (b) easing the documentation Syrians refugees need to apply for work permits;\nand (c) providing an amnesty period for Syrians refugees found working without permits.\n\n\n36. The Jordanian response to the presence of Syrian refugees has been varied. Tensions are higher\nin the northern governorates where the largest number of Syrians refugees live than in the southern\ngovernorates that host few Syrians refugees. According to a recent ILO/FAFO report, <sup>17</sup> [^17: ILO and FAFO. 2015. “Impact of Syrian Refugees on the Jordanian Labour Market.”] two-thirds of\nJordanians in the northern governorates feel that ‘you have to watch out for Syrians refugees’. Although\nthe surveyed Jordanians generally stated that they would be uncomfortable having a Syrian refugee\nmarry into their family, they said that they are comfortable having Syrians refugees in the same village,\nas neighbors, working together, going to the same religious place, and attending the same school.\n\n\n37. There is a widely held perception that the presence of Syrians refugee has caused an increase\nin housing prices as well as increased pressure on public infrastructure and services. The vast majority\nof Jordanian consumers surveyed believe that Syrian refugees strain Jordan’s water and energy\nresources, and that the international community should carry the economic costs of hosting Syrian\nrefugees.\n\n\n38.", "output": {"entities": {"named_data": ["ILO/FAFO report"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000137", "page": 66, "chunk": 0, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents1.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "ILO/FAFO report", "label": "NAMED_DATA", "score": 0.5317662954330444, "start": 1132, "end": 1147, "probe_score": 0.9867, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "second phase for 31 online services and 44 informational services through mobile and\ninternet will also be launched by close of the project.\n\n\n  - Management information system (MIS) software for different institutions such as\nMinistry of Transport, National Library and Archives, and Environment Protection\nAuthority is operational to increase their effectiveness in sharing information at federal\nand regional level. Similarly, to cite some examples, Oromia developed MIS for six (6)\nsector bureaus, Tigray for land and transportation management, Amhara for land and\nfood security Pass, Benshangul for health, education, etc.\n\n\n  - Connecting offices through networking is used in more and more regional offices. This\nhas expanded from 17 in 2005 to 174 in 2012.\n\n\n  - A system has been developed for spelling corrector of Amharic text and web-based\nmalaria expert system, with embedded Amharic and Oromifa languages.\n\n\n  - ICT training manual has been prepared in regions such as Harari, Somali, SNNPR, and\nAmhara.\n\n\n  - ICT curricula for technical and vocational training have been developed in Harari and\nSomali.\n\n\n  - Several ICT-related studies have been conducted in Somali region, and also the following\ndeveloped: the videoconferencing training manual in local language; ICT training\nassessment: IT training strategy and program; hardware and software requirement for the\ncomputerization of the court; ICT fast-track curriculum; and ICT manpower assessment\nand development strategy.\n\n\n  - ICT training needs assessment has been conducted in Afar.\n\n\n  - Amhara region conducted ICT Infrastructure Survey for Amhara National Regional State\nand ICT Impact Assessment in 2012. It has also developed user manuals for data\ncollection, analysis, compilation; training centers management; training documentation;\nas well as for using personal computers for fax.\n\n\n**Output 3—Reforms of Expenditure Management System**\n\n\n  - **Expenditure management Control Program (EMCP).** The financial laws, regulations\nand manuals were rolled out at federal level and regions.\n\n\n  - The procurement", "output": {"entities": {"named_data": ["ICT Infrastructure Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013938", "page": 61, "chunk": 0, "title": "Ethiopia - Public Sector Capacity Building Program Support Project", "pdf_url": "https://documents.worldbank.org/curated/en/500461468275118103/pdf/ICR26970ICR0Et0Box377380B00PUBLIC00.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "ICT Infrastructure Survey", "label": "NAMED_DATA", "score": 0.7674170136451721, "start": 1587, "end": 1612, "probe_score": 0.3932, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "ي** .47\n\nمع وزارة النقل واألشغال العامة ومصلحة سكك الحديد والنقل المشترك، باإلضافة إلى وك لت أخرى **ا** يُعتبَر مسؤوالً مباشرًا عن المشروع إعداد المشروع وتنفيذه\n\nعند الحاجة. إلى ذلك، سيكون مجلس اإلنماء واإلعمار مسؤوالً عن تنفيذ البنى التحتيّة كلّها الخاصة بالمشروع. كما سيتمّ توجيه مساهم ،ة الحكومة إلى المشغلّين\n\nالتي سيتمّ تموي لها من قرض من البنك الدولي، إلى المشغّلين من خالل مجلس اإلنماء واإلعمار .من أجل ضمان اتّساق البيانات الماليّة و سيُشرك مجلس اإلنماء\n\nواإلعمار وزارة النقل واألشغال العامة ومصلحة سكك الحديد والنقل المشترك من أجل إعداد شروط العقد والمواصفات الفنيّة ومراجعتها لل ًمشغّلين وسيكون مسؤوال\n\nعن التفاوض مع المشغّلين بشأن العقود. سيُجري مجلس ا", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000065", "page": 34, "chunk": 2, "title": "Lebanon - Greater Beirut Public Transport Project", "pdf_url": "http://documents1.worldbank.org/curated/en/421781525332123067/pdf/PAD2574-ARABIC-PUBLIC-PAD-final-02262018-AR-Clean-%D9%85%D9%8A.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nStrengthening Public Sector Effectiveness and Statiscal Capacity Project (P151155)\n\n\n_Programmation_ to gain in effectiveness in preparation processes; and (c) providing\nadditional resources to the Preparation Fund ( _Fonds de Maturation_ ) to strengthen project\nappraisal capacity (for MINEDUB/MINSANTE specifically).\n\n     - **Subcomponent 2.2: Enhancing public investment budget execution monitoring.** This\nsubcomponent will include support to (a) pilot enhanced data consolidation by the\nMINEPAT’s division in charge of PIB monitoring from district and regional levels and\nMINFI’s Directorate of Treasury through web-based solutions and performance contracting\nof deconcentrated levels (regional and district levels); (b) enhance data dissemination on\nPIB by providing regular (that is, trimestral) online further details than mere _Journal des_\n_Projets_ (contract details, geo localization, levels of physical and financial execution on a\ntrimestral basis, and so on); and (c) stimulate direct citizens’ PIB execution monitoring by\n(i) building the capacities of existing village development committees ( _comités de_\n_concertation_ or _comités de développement_ ) in monitoring public works and accessing key\ninformation and CLS meetings and (ii) developing an application based on information and\ncommunication technology (ICT) to enable citizens feedback. <sup>27</sup> [^27: Including pictures, through SMS or Internet, and following good practices in terms of Grievance Redress Mechanism such as\nanonymity.] A mechanism will be\nincluded to ensure those feedbacks are fed into monthly and trimestral PIB execution\nmonitoring meetings (CLS). Also, the Cellules PBBS of MINSANTE and MINEDUB will benefit\nfrom tailored capacity building to use those innovative tools for their own PIB monitoring.\n\n     - **Subcomponent 2.3: Strengthening the management of public investment projects**\n**financed by international and bilateral donors.**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000044", "page": 26, "chunk": 0, "title": "Cameroon - Strengthening Public Sector Effectiveness and Statistical Capacity Project", "pdf_url": "http://documents1.worldbank.org/curated/en/305621511406035802/pdf/CAMEROON-PAD2-11012017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " to you? [scale 1-5 representing very unsatisfied to very satisfied, with a|Captures engagement with stakeholders and extent to which project is meeting stakeholder<br>demand. This is based on a survey administered to households in the project watersheds.<br>The survey instrument is comprised of small number of questions (approx. 15-25), which will<br>measure the extent to which the project reflected expectations and preferences of<br>beneficiaries in the project watersheds.<br>Srvey techniques will be used to document male and female beneficiary priorities at project<br>outset. Surveys during and at the close of the project may identify respondents’ satisfaction<br>with project investments, including a specific question about the degree to which<br>respondents felt project activities reflected their preferences (ex post). The survey will<br>include the following question: “How satisfied are you that the project activities associated<br>with RLLP is useful to you? [scale 1-5 representing very unsatisfied to very satisfied, with a|Captures engagement with stakeholders and extent to which project is meeting stakeholder<br>demand. This is based on a survey administered to households in the project watersheds.<br>The survey instrument is comprised of small number of questions (approx. 15-25), which will<br>measure the extent to which the project reflected expectations and preferences of<br>beneficiaries in the project watersheds.<br>Srvey techniques will be used to document male and female beneficiary priorities at project<br>outset. Surveys during and at the close of the project may identify respondents’ satisfaction<br>with project investments, including a specific question about the degree to which<br>respondents felt project activities reflected their preferences (ex post). The survey will<br>include the following question: “How satisfied are", "output": {"entities": {"named_data": [], "descriptive_data": ["survey administered to households in the project watersheds", "survey administered to households in the project watersheds"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001481", "page": 6, "chunk": 3, "title": "Disclosable Version of the ISR - Second Ethiopia Resilient Landscapes and Livelihoods Project - P174385 - Sequence No : 7", "pdf_url": "https://documents.worldbank.org/curated/en/099032525151531980/pdf/P174385-a52948c7-6825-44f3-9b20-a53380705961.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "survey administered to households in the project watersheds", "label": "DESCRIPTIVE_DATA", "score": 0.5994119048118591, "start": 195, "end": 254, "probe_score": 0.3693, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "survey administered to households in the project watersheds", "label": "DESCRIPTIVE_DATA", "score": 0.5546799898147583, "start": 1165, "end": 1224, "probe_score": 0.3264, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "> <br>Monitor private external<br>borrowing and currency<br>mismatches<br> <br>Strengthen financial<br>institutions.<br>|Flexible exchange rates will<br>reduce incentive for currency<br>mismatches but direct controls<br>may also be needed by central<br>bank on volume of private<br>external debt and loan-to-<br>deposit ratios of commercial<br>banks|\n|3. Insure against shifting<br>market sentiment and possible<br>sudden stops<br>_(Second generation)_| <br>Build up foreign exchange<br>reserves<br> <br>Restrict currency<br>mismatches on<br>government and private<br>balance sheets.|―Ideal‖ level of reserves will<br>depend upon short-term<br>external debt, flexibility of<br>exchange rates and extent of<br>currency mismatches|\n\n\n\n_Source:_ Chapter 7, Pinto (forthcoming).\n\n\n21 The first generation crisis model honed in on the inconsistency of fiscal deficits financed by credit\ncreation and a fixed exchange rate; the second generation on confidence crises, international liquidity and\nmultiple equilibria; while the third brought in balance sheet exposures. Key contributions were made by\nKrugman (1979, 1999), Flood and Garber (1984), Obstfeld (1994), Chang and Velasco (2000) and\nBurnside, Eichenbaum and Rebelo (2001). For summaries, see Frankel and Wei (2005) and Pinto\n(forthcoming).\n\n\n18", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004962", "page": 19, "chunk": 1, "title": "wps5786", "pdf_url": "https://local/prwp/wps5786.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "J. Villar, H. Ba’aqeel, G. Piaggio, P. Lumbiganon, J. M. Beliz´an, U. Farnot, Y. Al-Mazrou, G. Car\n\nroli, A. Pinol, A. Donner, et al. Who antenatal care randomised trial for the evaluation of a new\n\n\nmodel of routine antenatal care. _The_ _Lancet_, 357(9268):1551–1564, 2001.\n\n\nW. K. Viscusi and C. J. Masterman. Income elasticities and global values of a statistical life.\n\n\n_Journal_ _of_ _Benefit-Cost_ _Analysis_, 8(2):226–250, 2017.\n\n\nWhite Ribbon Alliance. Respectful maternity care: A Nigeria-focused health workers’ training\n\n\nguide. Technical report, Futures Group, Health Policy Project, 2015.\n\n\nWHO. WHO recommendations for augmentation of labour. Technical report, World Health Orga\n\nnization, 2014.\n\n\nWorld Bank. Life expectancy, 2019. data retrieved from World Development Indicators, [https:](https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=NG)\n\n\n[//data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=NG.](https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=NG)\n\n\nW. Zeng, E. Pradhan, and M. Khanna. Cost-effectiveness analysis of the decentralized facility\n\n\nfinancing and performance-based financing program in nigeria. Technical report, Mimeo, 2021.\n\n\n38", "output": {"entities": {"named_data": ["World Development Indicators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001714", "page": 39, "chunk": 0, "title": "information loss framing and spillovers in pay for performance contracts", "pdf_url": "https://local/prwp/information-loss-framing-and-spillovers-in-pay-for-performance-contracts.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "World Development Indicators", "label": "NAMED_DATA", "score": 0.8252942562103271, "start": 769, "end": 797, "probe_score": 0.3867, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Appendix A**\n\n\nThe values of variables used for the cluster analysis have to be within the interval\n0 and 1. Binary variables tend to drive the clustering process, and therefore most\nvariables have been redefined to a broader set of values inside the interval. Because of\nthis the mean of most variables cannot be interpreted as the proportion with a specific\ncharacteristic. Thus, Table A.1 mainly provides an idea of the variables used for the\nclustering. More detail on the specific variables used for the clustering is given in\nAppendix B. <sup>12</sup> [^12: Variables in Table A.1 in italics are used for the cluster process, whereas the other variables are also\nincluded in the analysis of the specific clusters in Section 4.]\n\n\nThe categorization in behaviors/consequences, protective factors, and risk factors\nis not straight forward since an outcome may also be a factor leading to another outcome,\nand whether a factor is defined as a risk or a protective factor depends on the coding of\nthe variable. The categorization and selection of variables for the clustering process\napplied here is based on the work and advice of Emily Bagby and Wendy Cunningham,\nwho analyzed the cases of Chile and Mexico.\n\n\n<u>Table A.1: Variables used for Cluster Analysis for Argentine Youth, 2005</u>\n**Variable** Mean **Variable** Mean\nNumber of observations 1,275 Age 18.98\n<u>Male</u> <u>0.45</u> <u>Work</u> <u>0.20</u>\n**Behaviors/Consequences** 0.71 **Protective Factors** 0.57\n_Not idle_ _0.86_ _Trust in the government*_ _0.60_\n_Not dropped out of school_ _0.85_ _Trust in the media*_ _0.42_\n_Age started working*_ _0.63_ _Trust in the community*_ _0.47_\n_Age", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003692", "page": 28, "chunk": 0, "title": "wps4485", "pdf_url": "https://local/prwp/wps4485.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Theme|Questions|Responses|\n|---|---|---|\n|**What are the**<br>**efforts in place**<br>**to ensure**<br>**vulnerable or**<br>**disadvantaged**<br>**youth access**<br>**benefits and**<br>**opportunities**? <br>|How can we<br>enhance the<br>participation of<br>Youth who are<br>challenged in<br>accessing or<br>being accessed<br>during project<br>implementation<br>(E.g., those in<br>hard-to serve<br>areas)?|• <br>Having a data base of youth who are challenged in accessing or<br>being accessed and such data being maintained by chiefs;<br>• <br>Employing representatives of the youth who are challenged in<br>accessing or being accessed, to act as the link between the<br>challenged-to-reach youth and organizations;<br>• <br>Enhancing public awareness through public barazas/ meetings;<br>• <br>Use of random selection so as to be fair to the hard-to-access<br>youth;<br>• <br>Leveraging on existing programmes such as food distribution to<br>reach such hard-to-reach youth;<br>• <br>Through awareness campaigns;<br>• <br>Use of social media;<br>• <br>Use of notice boards to disseminate information;<br>• <br>Through youth groups;<br>• <br>Through village leaders reach-", "output": {"entities": {"named_data": [], "descriptive_data": ["data base of youth"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003536", "page": 31, "chunk": 0, "title": "Revised Stakeholder Engagement Plan (SEP) National Youth Opportunities Towards Advancement Project (P179414)", "pdf_url": "https://documents.worldbank.org/curated/en/099071124144018867/pdf/P179414-c35560a0-ce4e-4ef9-a0f3-c2ff52f378ef.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "data base of youth", "label": "DESCRIPTIVE_DATA", "score": 0.7861378192901611, "start": 422, "end": 440, "probe_score": 0.0684, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "AFECTACIONES A LA SALUD PÚBLICA EN LOS MUNICIPIOS MÁS AFECTADOS POR EL DESPLAZAMIENTO Y CONFINAMIENTO\n\n\n\n\n\n\n\n\n\n**Gráfico 11.** Distribución de los casos de tuberculosis pulmonar por área de residencia,\n2022.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nCabecera Centro poblado y rural disperso\n\n\n**Fuente:** Ministerio de Salud y Protección Social. SISPRO. Cubo Sivigila 2022.\n\n\n50 www.acnur.org/pais/colombia", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000173", "page": 49, "chunk": 0, "title": "Afectaciones a la salud pública en los municipios más afectados por el desplazamiento y confinamiento en Colombia, 2022-2023", "pdf_url": "https://reliefweb.int/attachments/0e8cbdce-1700-4a8d-a69c-c08310c11755/Boletin_salud_publica_conflicto_27022025.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " UNHCR globally are\nschool aged children; with an estimated 3.4\nmillion refugee children out of school in\n<u>[2019. 77% of refugee children are enrolled in](https://www.unhcr.org/publications/education/5f4f9a2b4/coming-together-refugee-education-education-report-2020.html)</u>\nprimary education. Enrolment of refugees in\nsecondary education is at 31%, and only 3% for\nhigher education. The 2021 data does indicate\nthat progress is slow coming, with primary\neducation seeing a decline to 68% coverage,\nbut secondary education picking up at 34%,\nand higher education remains constant at 3%.\n\n\n- WFP has supported 3.4 million school children\nwith school feeding programmes in an\nemergency context in 40 countries over the\npast 50 years. In 2018, WFP supported 1.7\nmillion children in emergency contexts in 25\ncountries.\n\n\n\n\n- Based on the 2019 data, there are **48**\n**countries** where WFP has an active interim,\ntransitional or ongoing <u>[Country Strategic Plans](https://www.wfp.org/country-strategic-planning)</u>\n(CSP) that host more than 5,000 refugees –\nwarranting the activation of the UNHCR/WFP\nGlobal Memorandum of Understanding (MOU)\nfor further collaboration and coordination in\nsupport of refugee needs.\n\n\n- Regular food assistance is only provided to\nrefugees in **34 of these countries** ; while no\nfood assistance in provided in 14 countries\nthat have a refugee population above 5,000.\nOf the 34 countries that provide regular food\nassistance to refugees through General Food\nAssistance, **14 countries have a school**\n**feeding programme** that is designed for or\nincludes refugee children.\n\n\n\n**SCHOOL FEEDING PROGRAMMES WITH REFUGEE SCHOOL CHILDREN BY REGION**\n\n\n\n*", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["2021 data", "2019 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001042", "page": 16, "chunk": 2, "title": "Technical note: School feeding programmes in refugee settings technical review considerations for programming school feeding programmes in refugee settings", "pdf_url": "https://reliefweb.int/attachments/9e8666c7-cf8f-4575-9d57-6844263e486c/WFP-0000140511.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "2021 data", "label": "VAGUE_DATA", "score": 0.7112497687339783, "start": 391, "end": 400, "probe_score": 0.0852, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "2019 data", "label": "VAGUE_DATA", "score": 0.7034074664115906, "start": 837, "end": 846, "probe_score": 0.9875, "gold": "DATA_MENTION", "gold_tier": "human-final"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " though they have roughly the same number of children. <sup>68</sup> Given the higher unit\ncost of education in UMICs, the share of financing required in these countries is also higher.\n\n\nThe average unit cost for refugee education varies by income-categorization\nand level of education. The average unit cost for refugee education is US$1,051. In\nLICs, LMICs and UMICs, this figure is US$171, US$663 and US$2,085 respectively. The unit\ncost for refugee students in UMICs is almost 12 times higher on average than that for LICs\nand 3 times higher than that for LMICs. There are also large variations by level of education:\naverage refugee unit costs globally are US$1,156, US$925 and US$1,171 for pre-primary,\nprimary and secondary education, respectively. Table 4 provides the unit costs of education\nfor local and refugee students by level of education.\n\n\n67 UNRWA schools enroll approximately 526,000 students annually at an average unit cost of\nUS$841.50. A case study on the education of Palestinian refugees in UNRWA schools is presented\nin Annex 7.\n\n68 Global Education Monitoring Report. 2019. _Migration, displacement and education: building bridges,_\n_not walls._ Paris: UNESCO.\n\n\n36 The Global Cost of Inclusive Refugee Education", "output": {"entities": {"named_data": ["Global Education Monitoring Report"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001517", "page": 35, "chunk": 1, "title": "The Global Cost of Inclusive Refugee Education, January 2021", "pdf_url": "https://reliefweb.int/attachments/ea59adb5-3c30-3162-aeb6-c79c7b543a39/2020GlobalCostInclusiveRefugeeweb.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Global Education Monitoring Report", "label": "NAMED_DATA", "score": 0.7262104749679565, "start": 1060, "end": 1094, "probe_score": 0.9998, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "://www.businessdictionary.com/definition/country.html) <mark>s (Argentina, Brazil,</mark>\n<mark>Paraguay, and Uruguay) e</mark> [stablished](http://www.businessdictionary.com/definition/establish.html) <mark>under the 1991 T</mark> [reat](http://www.businessdictionary.com/definition/treaty.html) <mark>y of Asunción. Formed on the p</mark> [attern](http://www.businessdictionary.com/definition/pattern.html) <mark>of the</mark>\n<mark>European C</mark> [ommunity's](http://www.businessdictionary.com/definition/community.html) <mark>Treaty Of Rome, it allows</mark> [duty free](http://www.businessdictionary.com/definition/duty-free.html) <mark>inter-Mercosur t</mark> [rade](http://www.businessdictionary.com/definition/trade.html) <mark>and l</mark> [evies a common](http://www.businessdictionary.com/definition/levy.html) <mark>external</mark>\n<mark>tariff (0 to 20 p</mark> [er cent](http://www.businessdictionary.com/definition/percent.html) <mark>) on non-member countries. Its associate countries are Chile, Bolivia, Peru, Colombia and</mark>\n<mark>Ecuador.</mark>\n\nBuilding Communities of Practice for Urban Refugees – Brazil Roundtable Report – UNHCR’s Policy Development", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000834", "page": 4, "chunk": 2, "title": "Building Communities of Practice for Urban Refugees – Brazil Roundtable Report", "pdf_url": "https://reliefweb.int/attachments/7b7f8bd5-ab0a-3e56-b445-51a6ba68b1c5/5613d73c9.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " generate the IFRs, as per IPSAS and to include a module for contracts management.\nThe upgrade should be completed within 3 months of effectiveness. CVDB will be responsible\nfor preparing the quarterly IFRs and annual project financial statements in compliance with\nIPSAS. The reports will consist of (i) “Statement of Cash Receipts and Payments by category”,\n(ii) the list of all signed Contracts per category” showing contract amounts committed, paid, and\nunpaid under each contract, (iii) Reconciliation Statement for the balance of the DA, (iv) budgets\ncompared to actual, and (v) a list of assets (goods and equipment). The Financial Coordinator at\nCVDB will be responsible for collecting the needed data from the participating municipalities to\ncomplete the IFRs and submit to the World Bank within 45 days after the end of the concerned\nperiod.\n\n19. **Internal Controls:** The project will be implemented under the general context of CVDB\ninternal control policies and procedures while direct grants provided to municipalities will follow\nthe Jordan municipalities’ financial bylaw of 2007 and its amendments. There are four levels of\ncontrols under this Project: (i) technical approvals of related departments (at municipalities’\nlevel, this will be performed by the “Public Works Department”, while this task will be\nperformed by the Engineers at the Planning and Development at CVDB; (ii) Finance Department\nchecking and approving payments; (iii) resident Internal Auditors, and (iv) the Audit Bureau\nverifying the financial accuracy and compliance with the applicable laws in Jordan and the grant\nterms and conditions. These controls will be complemented by additional measures related to the\nverification and approval of payments by the Project’s Manager and Finance Team at CVDB,\nfinancial reporting requirements, and disbursement procedures. All financial policies and\nprocedures applicable to the Project will be documented in the OM, which will also outline the\nflow of funds, and reporting and auditing arrangements.", "output": {"entities": {"named_data": [], "descriptive_data": ["data from the participating municipalities"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000089", "page": 49, "chunk": 1, "title": "Jordan - Emergency Services and Social Resilience Project", "pdf_url": "http://documents1.worldbank.org/curated/en/532171468273353365/pdf/PAD7230P1476890AD0October0100final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "data from the participating municipalities", "label": "DESCRIPTIVE_DATA", "score": 0.6833847165107727, "start": 705, "end": 747, "probe_score": 0.0019, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "M) results confirm an impact on monthly food expenditure, showing that<br>households that have received a regular HSNP payment experience an increase in monthly per adult equivalent food expenditure of around Ksh66.<br>However, the spill-over effects observed in the HSNP mean that it is likely that the impact on consumption for HSNP beneficiaries is underestimated. For<br>every shilling injected into the local economy by the HSNP, total incomes are raised by somewhere between 1.38 and 1.93 shillings. Most of this additional<br>income goes to non-beneficiaries of the program, hence producing spill-overs.|<br>**Comments (achievements against targets):** <br>This indicator was to be measured by the CT-OVC Impact Evaluation and the HSNP Impact Evaluation. Unfortunately, the results from the CT-OVC Impact<br>Evaluation show that due to a number of reasons (the quality of the consumption data collected for the end line with food consumption likely to be<br>significantly underreported as well as the high attrition rate), it is difficult to detect the true impact of the CT-OVC program on the household food<br>consumption. <br>According to the HSNP Impact Evaluation, the Propensity-score matching (PSM) results confirm an impact on monthly food expenditure, showing that<br>households that have received a regular HSNP payment experience an increase in monthly per adult equivalent food expenditure of around Ksh66.<br>However, the spill-over effects observed in the HSNP mean that it is likely that the impact on consumption for HSNP beneficiaries is underestimated. For<br>every shilling injected into the local economy by the HSNP, total incomes are raised by somewhere between 1.38 and 1.93 shillings. Most of this additional<br>income goes", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["consumption data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016570", "page": 41, "chunk": 1, "title": "Kenya - National Safety Net Program for Results", "pdf_url": "https://documents.worldbank.org/curated/en/678401626096024355/pdf/Kenya-National-Safety-Net-Program-for-Results.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "consumption data", "label": "VAGUE_DATA", "score": 0.7216458916664124, "start": 883, "end": 899, "probe_score": 0.7245, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ",764.917,25 7709,\n\n\nLocal Currency Accounts\n\nCentral Bank of Kenya [A/c No **1000313878......]** **328,091,857** **676,903,328**\n\n\nTotal local currency balances(KSHS) **328,091,857** **676,903,328**\n\n\nBelow is the Special Deposit Account **(SDA)** movement schedule which shows the flow of funds that\n\nwere voted in the year. These funds have been reported as loans/grants received in the year under the\n\nStatement of Receipts and Payments.\n\n\n**16**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007162", "page": 33, "chunk": 1, "title": "Kenya - AFRICA EAST - P152394 - Transforming Health Systems for Universal Care - Audited Financial Statement", "pdf_url": "https://documents.worldbank.org/curated/en/099635002012231862/pdf/P15239402a11230ae086790daf0f9ffaf2d.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda COVID-19 Response and Emergency Preparedness Project (P174041)\n\n\n**ABBREVIATIONS AND ACRONYMS**\n\n\nCOVID-19 Coronavirus Disease-2019\nHDU High Dependence Unit\nIDA International Development Association\nFA Financing Agreement\nICU Intensive Care Unit\nISR Implementation Status and Results Report\nMOH Ministry of Health\nMPA Multiphase Programmatic Approach\nPDO Project Development Objective\nPEFF Pandemic Emergency Financing Facility\nPPE Personal Protective Equipment\nSPRP Strategic Preparedness and Response Plan\nUCREPP Uganda COVID-19 Response and Emergency Preparedness Plan", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010278", "page": 1, "chunk": 0, "title": "Disclosable Restructuring Paper - Uganda COVID-19 Response and Emergency Preparedness Project - P174041", "pdf_url": "https://documents.worldbank.org/curated/en/255101611918341548/pdf/Disclosable-Restructuring-Paper-Uganda-COVID-19-Response-and-Emergency-Preparedness-Project-P174041.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Goods: is applicable for those contracts identified in the Procurement Plan\ntables;\n\n\nWorks: is applicable for those contracts identified in the Procurement Plan\ntables", "output": {"entities": {"named_data": [], "descriptive_data": ["Procurement Plan\ntables", "Procurement Plan\ntables"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001393", "page": 2, "chunk": 0, "title": "Ethiopia - EASTERN AND SOUTHERN AFRICA- P172479- Strengthen Ethiopia?s Adaptive Safety Net - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099031825041033933/pdf/P172479-0178a376-eaea-4d18-8e9a-673bc0791835.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Procurement Plan\ntables", "label": "DESCRIPTIVE_DATA", "score": 0.6941657066345215, "start": 59, "end": 82, "probe_score": 0.0014, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Procurement Plan\ntables", "label": "DESCRIPTIVE_DATA", "score": 0.5189715623855591, "start": 145, "end": 168, "probe_score": 0.0002, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " end targets were revised after more accurate data was obtained through surveys.<br>\"Quality Assurance service\" is the service of accreditation, calibration, testing, inspection and<br>standard implementation services provided to customers<br>The volume is measured by counting the number of QA services (e.g., calibration of<br>measurement instrument, testing of a product) customers receive (i.e., two customers receiving<br>the same service is counted as two units, a customer receiving two different services is counted<br>as two units too, and so forth).|Baseline and end targets were revised after more accurate data was obtained through surveys.<br>\"Quality Assurance service\" is the service of accreditation, calibration, testing, inspection and<br>standard implementation services provided to customers<br>The volume is measured by counting the number of QA services (e.g., calibration of<br>measurement instrument, testing of a product) customers receive (i.e., two customers receiving<br>the same service is counted as two units, a customer receiving two different services is counted<br>as two units too, and so forth).|\n|Number of accreditation|0.00||25.00||25.00||64.00||\n\n\n\nPage 5 of 12", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["surveys"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:004818", "page": 4, "chunk": 4, "title": "Disclosable Version of the ISR - Ethiopia: National Quality Infrastructure Development Project - P160279 - Sequence No : 15", "pdf_url": "https://documents.worldbank.org/curated/en/099102324170067332/pdf/P160279-838cd0f0-f42f-4c5d-9439-dbcb81576e94.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "surveys", "label": "VAGUE_DATA", "score": 0.513017475605011, "start": 644, "end": 651, "probe_score": 0.0484, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**3.5 Overarching Themes, Other Outcomes and Impacts**\n**(a) Poverty Impacts, Gender Aspects, and Social Development**\n\n56. A gender focal point was established under the Research-Extension-Farmer Linkage Department\n(REFLD) to integrate gender issues into every aspect of the research endeavors i.e. research design;\nimplementation, and M&E processes. ARTP allocated support for recurrent budgets to facilitate research\nanalysis on gender issues. A major factor in the achievements of the unit in recent years has been the\nincrease in the budget allocated to the unit, which had previously operated with minimal financing. In the\npast year the unit held 10 training events on gender analysis for over 237 participants from EIAR\nmanagement, and federal and regional RCs. The unit also coordinated the development of case studies\nand baseline data collection through surveys at eleven RCs to identify gender disaggregated research\npriorities. A workshop presenting survey results was held and the findings are expected to be collected in\na proceedings and a summary report.\n\n57. The Tenth Supervision Mission in 2006 recommended the unit make an inventory of case studies\non how research outcomes have addressed issues faced by women. An initial assessment was undertaken\nand identified several research outputs that could be considered gender-responsive in increasing\nhousehold food security, reducing household drudgery and mitigating HIV/AIDs and poverty. No formal\ninventory was produced but the assessment provided an input into training activities and a more\nsubstantive report, including case studies, will instead be produced based on the results of the surveys.\nThe report is expected to be finalized in 2007. The unit also plans to continue to implement survey\nfindings in developing research proposals and undertake similar surveys at the regional level. While there\nhas been excellent progress in identifying gender issues and initiating a gender-focused research program,\nthere is a need to further institutionalize the collection of gender disaggregated data and the enhancement\nof gender focus of research operations.\n\n**(b)", "output": {"entities": {"named_data": [], "descriptive_data": ["surveys at eleven RCs"], "vague_data": ["gender disaggregated data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008304", "page": 28, "chunk": 0, "title": "Ethiopia - Agricultural Research and Training Project", "pdf_url": "https://documents.worldbank.org/curated/en/126471468256175370/pdf/ICR6190ICR0P001closed0March03102008.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "surveys at eleven RCs", "label": "DESCRIPTIVE_DATA", "score": 0.6799752116203308, "start": 865, "end": 886, "probe_score": 0.4354, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "gender disaggregated data", "label": "VAGUE_DATA", "score": 0.6379285454750061, "start": 2045, "end": 2070, "probe_score": 0.0175, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " extreme vulnerability of the Chadian economy to external shocks makes it difficult to sustainably finance**\n**development, especially social sectors** . Social spending serves as an adjustment variable in times of economic crises. In\nresponse to this situation, the Country developed an Industrialization and Economic Diversification Master Plan (PDIDE)\nin 2020 that seeks to move the country's economic growth rate from around 2 percent in 2017 to more than 8 percent\nper year until 2030. <sup>2</sup> This Plan builds on four priority areas: governance, infrastructure, financing, and human capital.\n\n\n4. The **country’s Human Capital Index (HCI) has remained low during the last decade.** The HCI for Chad went from\n0.29 in 2010 to 0.30 in 2020. Despite this small increase, Chad’s HCI is lower than the average for Sub-Saharan Africa and\nfor low-income countries. This means that a child born in Chad today will be 30 percent as productive when she/he\ngrows up as could be if enjoying complete education and full health. This poor performance is driven largely by the low\nprobability of survival to age five (88 per 100 children born), high levels of stunting (40 percent of children), and poor\neducation participation and quality. A child in Chad can be expected to complete only 5.3 years of school by the age of\n18, but factoring in what is actually learned, this is the equivalent of only 2.8 years.\n\n\n1 World Bank DataBank, World Development Indicators (Poverty Headcount ratio at national poverty lines, 2018).\n2 United Nations Economic Commission for Africa (UNECA)\n\n\nAug 03, 2021 Page 3 of 27", "output": {"entities": {"named_data": ["Human Capital Index", "World Bank DataBank"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000009", "page": 2, "chunk": 1, "title": "Concept Project Information Document (PID) - CHAD Improving Learning Outcomes Project - P175803", "pdf_url": "http://documents.worldbank.org/curated/en/234501637169242309/pdf/Concept-Project-Information-Document-PID-CHAD-Improving-Learning-Outcomes-Project-P175803.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Human Capital Index", "label": "NAMED_DATA", "score": 0.5913615822792053, "start": 624, "end": 643, "probe_score": 0.7585, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "World Bank DataBank", "label": "NAMED_DATA", "score": 0.6532403826713562, "start": 1413, "end": 1432, "probe_score": 0.9982, "gold": "DATA_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**H.E.** Dr. Abraham Tekeste **_-_** 5 **_-_** May **18,** **2017**\n\n**Category** **Amount** **of IDA** **Amount** **of HRITF**\n**(including** **Disbursement** **Disbursement** **Linked** **Result** **Credit Allocated** **Grant Allocated**\n**Linked** **Indicator)** **and Corresponding Value** **(expressed** **in** **SDR)** **(expressed** **in** **US$)**\n\n\n                 - **US$2.662338** million from\nHRITF Grant; SDR **1.733182**\nmillion from Credit No.\n**5209,** for each **1%** increase\n(4)(a) Contraceptive - Increase in Contraceptive **0** **0**\nprevalence rate (for rural prevalence rate in rural\nwomen only) women up to a maximum of\n\n**38%** from baseline of **32%**\n\n\n                - **US$0.55825** million from\n**GFF** Grant; thereafter SDR\n2.211 million from **AF**\nCredit, for each **1%** increase\n**(5)** Health centers - Increase up to a maximum of **3,255,000**\nreporting **HMIS** data in **80%** from baseline **50%**\ntime\n\n                - SDR **108,500** for each **1%*", "output": {"entities": {"named_data": ["HMIS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018092", "page": 4, "chunk": 0, "title": "Official Documents- Amendment to Financing Agreement for Credit 5209-ET and to Grant Agreement for TF014107 (Closing Package)", "pdf_url": "https://documents.worldbank.org/curated/en/781341495813103325/pdf/ITK425962-201704261135.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "HMIS", "label": "NAMED_DATA", "score": 0.8817399144172668, "start": 895, "end": 899, "probe_score": 0.4411, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "wage rigidity. The estimates also imply that the larger is the share of permanent workers\n\n\nand/or the larger is the EPL index, the stronger is this effect. These results are in line with our\n\n\nexpectations, since the existence of permanent contracts complemented with strict labour\n\n\nregulations gives workers more leeway in wage negotiations, which in turn should lead to\n\n\ngreater wage rigidity. In particular, it is harder for firms to cut workers’ wages if the threat of\n\n\nlay-off is more difficult to implement. Thus, permanent contracts impose greater wage rigidity\n\n\nthan temporary contracts as long as permanent workers are more protected by labour\n\n\nregulations. As a consequence, the effect of permanent contracts on wage rigidity should be\n\n\nmore significant in countries with stricter employment protection.\n\n\nThe WDN survey contains information on the structure of agreements applicable for a given\n\n\nfirm. Managers were asked if a collective wage agreement exists and if so, whether it is a\n\n\nfirm-level agreement or a binding agreement that was negotiated at a level outside the firm\n\n\n(e.g. national, sector level, etc). We use this information to analyse the implications that the\n\n\nunion contracts negotiated at different levels have on wage rigidity. For this purpose, we\n\n\nconstruct three non-nested dummy variables that characterise the type of union contract(s)\n\n\napplying to the firm; the first indicating the existence of only a firm-level agreement, the\n\n\nsecond signifying only an outside agreement, and the third being equal to one if a firm has\n\n\nboth firm-level and outside agreements.\n\n\nAppendix 7 gives an overview of the cross-country differences in the incidence of union\n\n\ncontracts negotiated at different levels. This comparison reveals striking contrasts in the\n\n\ntendency of different types of union contracts across the sampled countries. In particular,\n\n\nthere is a group of countries (Austria, Belgium, Spain, France, Italy and Slovenia) where\n\n\nalmost all firms have union contracts and also display a very high incidence of higher-level\n\n\nbargaining agreements. On the other hand most", "output": {"entities": {"named_data": ["WDN survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004351", "page": 28, "chunk": 0, "title": "wps5159", "pdf_url": "https://local/prwp/wps5159.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "WDN survey", "label": "NAMED_DATA", "score": 0.8880794048309326, "start": 827, "end": 837, "probe_score": 0.9523, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " imposed fewer TTBs in response to the euro appreciation\n\n\nearly in the crisis period (see again Figure 1), given the EU’s 1999:Q1-2008:Q3 IRR estimate which\n\n\nindicated that an appreciation of the euro currency historically led to more TTBs.\n\n\nNevertheless, a final contributing explanation for the lack of a major import protection\n\n\nresponse by the United States or the European Union during 2008:Q4-2010:Q4 is related to the\n\n\nmovements in each economy’s bilateral real exchange rates over the period. The historical evidence\n\n\nfor the EU and US is that real currency appreciations led to more import protection through TTBs. As\n\n\nthe grey line in Figure 1 again illustrates for the EU, for much of the 2008-2010 period the euro is\n\n\ndepreciating. Furthermore, shortly after the sharp appreciation of the US dollar in 2009:Q1, the dollar\n\n\n_depreciated_ by a nearly identical amount, and then continued a period of weakening throughout\n\n\n2009-2010. These real depreciations suggest another dampening effect on new EU and US import\n\n\nprotection.\n\n\nrelationship, although the IRR is less precisely estimated. When using real GDP growth at the annual frequency\nin data extended through 2009, the point estimate for the IRR is no longer precisely estimated.\n\n\n23", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data extended through 2009"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005211", "page": 25, "chunk": 1, "title": "wps6038", "pdf_url": "https://local/prwp/wps6038.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "data extended through 2009", "label": "VAGUE_DATA", "score": 0.5438433885574341, "start": 1165, "end": 1191, "probe_score": 0.0619, "gold": "NON_MENTION", "gold_tier": "human-final"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### **Acknowledgements**\n\nThis publication has been commissioned by the Norwegian\n\nRefugee Council (NRC) – in conjunction with the Global Protection\n\nCluster (GPC) – and produced with the assistance of the\n\nNorwegian Ministry of Foreign Affairs (NMFA) and the Swedish\n\nInternational Development Cooperation Agency (SIDA). The\n\ncontents of this publication are the sole responsibility of NRC and\n\ncan in no way be taken to reflect the views of its donors.\n\n\nThe paper was written by Damian Lilly who would like to thank\n\ncolleagues from NRC and the GPC for their invaluable support.\n\nThey include Suze van Meegen, Clarissa Crippa and Dorothy\n\nSang, as well staff at the UN Office for the Coordination of\n\nHumanitarian Affairs (OCHA), the UN Refugee Agency (UNHCR),\n\nand the Organisation for Economic Co-operation and Development\n\n(OECD) who shared and verified the data presented. Thanks also\n\ngoes to the many people who were interviewed, completed the\n\nonline survey and provided comments on the draft report.\n\n\nPublished in November 2020\n\n\nEdited by Steven Ambrus\n\n\nGraphic Design by Richard Edenborough\n\n\nCover image: Newly displaced people waiting on the side of the\nroad after they fled attacks in Barsalogho, Burkina Faso.\nTom Peyre-Costa/NRC\n\n\n**2** BREAKING THE GLASS CEILING: A SMARTER APPROACH TO PROTECTION FINANCING", "output": {"entities": {"named_data": [], "descriptive_data": ["online survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000615", "page": 1, "chunk": 0, "title": "Breaking the glass ceiling: A smarter approach to protection financing", "pdf_url": "https://reliefweb.int/attachments/5a61e891-d2cf-3dc2-8aad-f36756a31e02/breaking-the-glass-ceiling---a-smarter-approach-to-protection-financing-report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "online survey", "label": "DESCRIPTIVE_DATA", "score": 0.6555362939834595, "start": 954, "end": 967, "probe_score": 0.0906, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "(Bruns & Luque, 2014; Leyva et al., 2015), elements of what happens in the classroom are\n\n\ninevitably lost as neither tool captures quantity and quality. This problem is even more acute in\n\n\nlow- and middle-income countries, which are often characterized by high absence rates and low\n\n\ninstructional time (Bold et al., 2017; World Development Report, 2018).\n\n\nThe _Teach_ classroom observation tool addresses this shortfall, as it measures the\n\n\nquantity _and_ quality of teaching. Although the tool is primarily high inference, the Time on\n\n\nTask component includes a simplified version of the Stallings tool to capture whether teachers\n\n\nprovide a learning activity and students are on task.\n\n\nResearch indicates effective teachers maximize the amount of time students spend\n\n\non learning (Wharton-McDonald et al., 1998; Stronge, 2018). In fact, time lost in classroom\n\n\ninstruction is associated with behavior issues and poorer student academic outcomes (Bruns &\n\n\nLuque, 2014; Dobbie & Fryer, 2013; Lavy, 2010; 2015). Using data from seven Latin American\n\n\ncountries, Bruns and Luque (2014) showed that teachers from schools ranked in the top 25th\n\n\npercentile of student learning spent, on average, 80 percent of their time on task, as compared\n\n\nto teachers in the bottom 75th percentile, who, on average, spent only 30 percent of their time\n\n\non task.\n\n\nLike time on learning, student engagement is another important predictor of\n\n\nlearning (Castillo, 2017). In the same study, Bruns and Luque (2014) found when students are\n\n\non task and engaged, they learn significantly more than when they are distracted or off task.\n\n##### 3.1.2. What Are Effective Teaching Practices?\n\n\nThis subsection provides the evidence and ‘content validity’ for the teaching practices captured\n\nin _Teach._ <sup>3</sup>\n\n\nThe Quality", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data from seven Latin American\n\n\ncountries"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007569", "page": 7, "chunk": 0, "title": "wps8653", "pdf_url": "https://local/prwp/wps8653.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "data from seven Latin American\n\n\ncountries", "label": "VAGUE_DATA", "score": 0.6563103199005127, "start": 1029, "end": 1071, "probe_score": 0.9878, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "reported at baseline) drive the response to illness shocks. <sup>16</sup> A male worker who is the highest\n\n\nearner in the household works 0.76 days and 7.6 more hours in response to the illness of another\n\n\nworker compared to another male. The results with usual hours of work lose statistical\n\n\nsignificance at conventional levels, but are still large quantitatively and point in the same\n\n\ndirection as the earnings results.\n\n\nAgain, there is no differential effect for women who are the highest wage earners or have\n\n\nthe highest usual hours of work (as reported in the baseline survey) in their households.  This is\n\n\nnot because too few women report the highest earnings or usual hours of work in their\n\n\nhouseholds to give us the power to detect these effects. Indeed, table A9 shows the joint\n\n\ndistribution of gender and status as the highest earner and member with the longest usual hours\n\n\nof work in the household among the individuals employed at baseline. While it is more common\n\n\nfor men to be the highest earners or have the most usual hours of work in the household –\n\n\nmirroring the result in table 1 that men on average have somewhat larger average hours of work\n\n\nand greater earnings than women – 42 percent of women are the highest earners in their\n\n\nhousehold and 48 percent of women have the highest usual hours of work. <sup>17</sup> Instead, it appears\n\n\nthat even (relatively) high-earning women have caregiving and other duties around the home that\n\n\nprevent them from increasing their labor supply when another worker is ill.\n\n\nWe now turn to another dimension of heterogeneity: risk aversion. The more risk averse\n\n\nan individual, the more he or she will dislike fluctuations in consumption, and thus, the greater\n\n\nthe incentive to increase labor supply in order to smooth consumption. Survey respondents\n\n\n16 Table O1 in the online appendix (http://faculty.washington.edu/rmheath/onlineappendix_HMR.pdf) shows that", "output": {"entities": {"named_data": [], "descriptive_data": ["baseline survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001775", "page": 26, "chunk": 0, "title": "labor supply responses to health shocks evidence from high frequency labor market data from urban ghana", "pdf_url": "https://local/prwp/labor-supply-responses-to-health-shocks-evidence-from-high-frequency-labor-market-data-from-urban-ghana.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "baseline survey", "label": "DESCRIPTIVE_DATA", "score": 0.7968400120735168, "start": 574, "end": 589, "probe_score": 0.9611, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the situation that was agreed upon with\nthe Borrower.\n\nSigned by:\nFinancial Management v I _N_\n##### Specialist K {dO'.i1, O0\n\n(FMS-OPR) Rafika Chaouali, MNSHD Date\n\n\n**Part II:** **Procurement/Contract Management** System\n\nI have reviewed the procurement/contract management system relating to this project, including\nthe format and content of the section on Project Management Reports (PMRs) on procurement\n\nmonitoring. The objective of the review was to determine whether the procurement/contract\nmanagement system adopted by the project conforms to IDA's guidelines for procurement in\ninvestment projects. My review was based on the \"Assessment of Agency's Capacity to\nImplement Project Procurement, Setting of Prior Review Thresholds and Procurement\nSupervision Plan\" guidelines issued by IDA.\n\nI confirm that the project satisfies IDA's minimum procurement management requirements.\nHowever, in my opinion, the project does not have in place an adequate procurement/contract\nmanagement system that can provide the appropriate data on major procurement and contract\nmanagement (PMR - Section 3) as required by IDA.", "output": {"entities": {"named_data": [], "descriptive_data": ["data on major procurement and contract\nmanagement"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000100", "page": 54, "chunk": 1, "title": "Bosnia and Herzegovina - Second Electric Power Reconstruction Project", "pdf_url": "http://documents1.worldbank.org/curated/en/583901468768013967/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "data on major procurement and contract\nmanagement", "label": "DESCRIPTIVE_DATA", "score": 0.6258809566497803, "start": 1032, "end": 1081, "probe_score": 0.0015, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda Digital Acceleration Project – GovNet (P171305)\n\n\n**ANNEX 1: Economic and Financial Analysis**\n\n\n**1.** **The project is expected to contribute to accelerated GDP growth, digitally enabled innovation, long-term**\n**government cost savings due to transformation of service delivery agenda in key sectors, and revenue increases**\n**as well as augmented citizen well-being.** An enhanced telecom market regulation and improved accessibility and\naffordability of broadband services and devices will result in a more dynamic digital sector with expanded digital\ncontent and could be expected to bring tangible opportunities for digital services development and exports in the\narea of digital innovation. Increased digitalization of government services that could be delivered in a cashless and\npaperless manner is expected to generate cost and time savings for both the general population and refugee host\ncommunities. By contributing to clean environmental practices, the improvements to e-waste management\npractices will further make Uganda an even more attractive destination for tourists. The refugees host\ncommunities supported through enhanced skills programs and opportunity/job pathways in the digital era could\ngenerate employment and productivity gains reflected in increased revenues and wages.\n\n**2.** **<mark>The novelty of severa</mark>** **l components (particularly those related to device affordability, digital authentication,**\n**advanced skills, and cybersecurity) as well as data limitations in other areas constrain an accurate estimation**\n**of expected economic and financial returns of the project.** The economic and financial analysis undertaken\nfollows a standard CBA methodology. The model relies on available secondary data and reasonable assumptions <sup>58</sup>\n\n59 60, based on experience and additional evidence from consultations and interviews conducted by the task team\nto conduct a cash flow analysis and resulting financial analysis for three different scenarios: optimistic, pessimistic,\nand neutral. When possible, the model", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["secondary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000075", "page": 59, "chunk": 0, "title": "Uganda - Digital Acceleration Project", "pdf_url": "http://documents1.worldbank.org/curated/en/473041622944887337/pdf/Uganda-Digital-Acceleration-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "secondary data", "label": "VAGUE_DATA", "score": 0.7725064158439636, "start": 1760, "end": 1774, "probe_score": 0.5978, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "###### **1. Introduction**\n\nThe most common practice for measuring poverty in developing countries aims to set\n\n\nabsolute poverty lines, meaning that they have constant purchasing power over commodities.\n\n\nThe cost-of-living indices used for this purpose are typically based on the prices observed at each\n\n\ndate or location (urban versus rural areas, region or country), with an allowance for spending on\n\n\nthose goods (notably non-food items) for which price data are missing. A poverty measure, such\n\n\nas the headcount index or poverty gap index, is then calculated by deflating actual consumptions\n\n\nor incomes at household level by these poverty lines, which can also be used to adjust for\n\n\ndifferences in household size and demographic composition. Such measures have become\n\n\nimportant tools for assessing development progress and guiding policy making.\n\n\nWhat are the conceptual foundations of this practice? On reflection, two axioms are\n\n\ncrucial, and neither is uncontroversial. The first is the subgroup additivity axiom, meaning that\n\n\naggregate poverty is the sum of all individual levels of poverty in the population. This has long\n\n\nbeen considered a desirable feature of a poverty measure. It implies that if poverty increases in\n\n\nany subgroup of the population, and does not change for any other group, then aggregate poverty\n\n\nmust increase; this is the “subgroup monotonicity axiom” of Foster and Shorrocks (1991). The\n\npractice of poverty measurement has largely been confined to additive measures. <sup>2</sup> [^2: Examples include the widely used Foster-Greer-Thorbecke (1984) class of measures. Atkinson\n(1987) reviews other measures in the broad class of additive measures.]\n\n\nAdditivity is not universally accepted. Foster and Sen (1997) argue in favor of non\n\nadditive functional forms as a means of bringing relativist considerations into poverty\n\n\nmeasurement; an example is the Sen (1976) measure, based on weights that reflect rank order in\n\n\nthe income distribution. But even such non-additive measures need not reflect poor peoples’\n\n\nperceptions of relative deprivation. A simple example will suffice", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["price data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003693", "page": 3, "chunk": 0, "title": "wps4486", "pdf_url": "https://local/prwp/wps4486.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "price data", "label": "VAGUE_DATA", "score": 0.7126237154006958, "start": 455, "end": 465, "probe_score": 0.6437, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "OIM, presentadas ante la Contraloría General de la República,\nrespecto a disposiciones contrarias a estándares internacionales\ncontenidas en el reglamento administrativo de la nueva ley de\nmigración y extranjería; la participación en la discusión respecto a\nla aplicación de protección complementaria; y la presentación de\nrecomendaciones sobre el establecimiento de procedimientos\npara la determinación de la condición de apátrida bajo el nuevo\nmarco normativo.\n\n\n**Entre las principales actividades se consideran:**\n\n\n**•** **El ACNUR apoyó al Ministerio del Interior en la organización**\n**del diálogo participativo sobre protección internacional para la**\n**elaboración de la Policía Nacional de Migración y Extranjería,**\nlo que involucró a organizaciones de la sociedad civil, la\nacademia e instituciones públicas.\n\n\n- Representación del ACNUR, con voz pero sin voto, en la Comisión\npara la Determinación de la Condición de Refugiado. Durante\n2022 se participó en ocho sesiones, lo que significó el análisis y\nrecomendaciones de todos los casos sometidos a la Comisión,\nlo que incluyo el desarrollo de minutas especiales respecto\na la necesidad de protección internacional de perfiles\nespeciales de riesgo y la aplicación de causales de exclusión\nsegún las disposiciones de la Convención sobre el Estatuto\nde los Refugiados de 1951 y las directrices de protección\ninternacional del ACNUR.\n\n\n- Durante el segundo semestre de 2022 se realizó la consult", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000538", "page": 41, "chunk": 0, "title": "Movilidad humana en Chile 2022: Promoviendo la integración y contribuyendo al desarrollo del país", "pdf_url": "https://reliefweb.int/attachments/4d724216-b31c-47ea-b34f-e6b45d087b46/Anuario-ACNUR-Chile-2022-compressed.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "45 58335 59535 59445 58335 59535 59445 58335 59535 59445 58335 59535\n\n\n**Note:** In the columns names \"M-\", \"A-\", and \"S-\" stand for manufacturing, agriculture and services respectively.\n\n\nAll regression include exporter-year, country-pair and importer-year fixed effects. ADB-MRIO is used to estimate\n\n\nglobalization dynamics for the period 2015-2021. Robust standard errors, clustered at the country-pair level, are in\n\n\nparentheses. - _p <_ 0.10, ** _p <_ 0.05, *** _p <_ 0.01\n\n\n28", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000642", "page": 29, "chunk": 7, "title": "idu02339027309ee804c64081b400624f4f01534", "pdf_url": "https://local/prwp/idu02339027309ee804c64081b400624f4f01534.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**_Leased Assets_** _as specified under paragraph 5.10_ of the Procurement\nRegulations: Leasing may be used for those contracts identified in the\nProcurement Plan tables. _“Not Applicable”_\n\n\n**_Procurement of Second Hand Goods_** _as specified under paragraph 5.11_ of\nthe Procurement Regulations – is allowed for those contracts identified in the\nProcurement Plan tables _“Not Applicable”_\n\n\n**_Domestic preference_** _as specified under paragraph 5.51_ of the Procurement\nRegulations **_(Goods and Works)_** . _Specify for each_\n\n\nGoods: is applicable for those contracts identified in the Procurement Plan\ntables;\n\n\nWorks: is applicable for those contracts identified in the Procurement Plan\ntables\n\n\n**Other Relevant Procurement Information.**\n\n\n_Procurement of Vehicles and Motor Cycles will be carried out by UNOPS_\n_considering the urgency that the vehicles and motor cycles are critically_\n_needed for project start up and the need to use UNOPS’s expertise on having_\n_long-term relationships with suppliers._", "output": {"entities": {"named_data": [], "descriptive_data": ["Procurement Plan tables"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013601", "page": 1, "chunk": 0, "title": "Ethiopia - AFRICA EAST- P159382- Livestock and Fisheries Sector Development Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/476881611206282918/pdf/Ethiopia-AFRICA-EAST-P159382-Livestock-and-Fisheries-Sector-Development-Project-Procurement-Plan.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Procurement Plan tables", "label": "DESCRIPTIVE_DATA", "score": 0.5558813810348511, "start": 146, "end": 169, "probe_score": 0.0009, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " health related data in a\n\nstandardized manner, albeit the sampling tends to focus on a specific subgroup of the refugee\n\npopulation (households with children under 5 years old, and households with members with\n\nadolescent girls, pregnant and lactating mothers); with the exception of two rounds of SENS\n\nsurvey that is representative of the entire refugee population. In addition to the SENS survey,\n\nthe recent JPDM is another survey, that informs us regularly on the state of food security of\n\nrefugees that relies on a relatively robust Food Consumption Score (FCS) measure.\n\n\nFigure 2: Overview of data mapping on POCs in Rwanda, by sector/theme\n\n\nUNHCR / June 2022 / Version 1", "output": {"entities": {"named_data": ["SENS\n\nsurvey", "SENS survey", "JPDM"], "descriptive_data": [], "vague_data": ["health related data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001182", "page": 17, "chunk": 1, "title": "Mapping thematic area-wise data for Rwanda - Summary of Key Sectors / Thematic Areas and Associated Key Datasets in Rwanda (30 June 2022 | Version 1)", "pdf_url": "https://reliefweb.int/attachments/b4b394b1-1638-45da-b010-8dbc02d2b7a2/Data%20Mapping%20-%20Rwanda%20-%20June%202022.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "health related data", "label": "VAGUE_DATA", "score": 0.5760720372200012, "start": 1, "end": 20, "probe_score": 0.0022, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "SENS\n\nsurvey", "label": "NAMED_DATA", "score": 0.7411454916000366, "start": 299, "end": 311, "probe_score": 0.0002, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "SENS survey", "label": "NAMED_DATA", "score": 0.5472320914268494, "start": 388, "end": 399, "probe_score": 0.6193, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "JPDM", "label": "NAMED_DATA", "score": 0.822043776512146, "start": 413, "end": 417, "probe_score": 0.0, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013838", "page": 19, "chunk": 1, "title": "Kenya - Telecommunications Project", "pdf_url": "https://documents.worldbank.org/curated/en/494531468046805698/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7292463183403015, "start": 272, "end": 283, "probe_score": 0.8771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*Program Financing Data**|**Program Financing Data**|**Program Financing Data**|**Program Financing Data**|**Program Financing Data**|**Program Financing Data**|\n|[ X ]|Loan|[ ]|Grant|Grant|Grant|[x ]|[x ]|Other|Other|Other|Other|Other|Other|\n|[ X ]|Credit|||||||||||||\n|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|**For Loans/Credits/Others (US$, million):**|\n|", "output": {"entities": {"named_data": [], "descriptive_data": ["Program Financing Data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000137", "page": 5, "chunk": 3, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents1.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Program Financing Data", "label": "DESCRIPTIVE_DATA", "score": 0.516079306602478, "start": 1, "end": 23, "probe_score": 0.3232, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " because of the**\n**high repetition and dropout rates** <sup>7</sup> . This is particularly important, as the primary education sector received almost half\nof the education spending (50 percent) in 2017, followed respectively by lower secondary (16 percent), upper secondary\n(16 percent) <sup>8</sup> .\n\n\n11. **Despite substantial numbers of displaced and vulnerable children in the education system, their access to public**\n**schooling is limited.** Roughly 6,000 students are either refugees or internally displaced, and 96,000 are orphans or\notherwise categorized as vulnerable. The former represents only six percent of refugee children of primary school age\n(100,000 total children). <sup>9</sup> Accommodating all refugee and internally displaced children would require extra resources to\nexpand already overcrowded schools; as well as special inclusionary measures for those children who have fallen behind\nin their education and require remedial attention to facilitate their integration. There are 9,000 reported children with a\ndisability in school; this constitutes 0.3 percent of the school population and may indicate access constraints. Indeed,\napproximately 1.5 percent of out-of-school children cite sickness or disability as the reason for not attending. <sup>10</sup>\n\n\n7 Rapport d’Etat du Système Educatif National (RESEN), 2016\n8 Public Expenditure Analysis (PER), 2019\n9 UNHCR, Operational Data Portal. Data from May 2021.\n10 Ibid.\n\n\nAug 03, 2021 Page 6 of 27", "output": {"entities": {"named_data": ["Operational Data Portal"], "descriptive_data": [], "vague_data": ["Data from May 2021"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000009", "page": 5, "chunk": 1, "title": "Concept Project Information Document (PID) - CHAD Improving Learning Outcomes Project - P175803", "pdf_url": "http://documents.worldbank.org/curated/en/234501637169242309/pdf/Concept-Project-Information-Document-PID-CHAD-Improving-Learning-Outcomes-Project-P175803.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Operational Data Portal", "label": "NAMED_DATA", "score": 0.6116937398910522, "start": 1400, "end": 1423, "probe_score": 0.986, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Data from May 2021", "label": "VAGUE_DATA", "score": 0.5546448230743408, "start": 1425, "end": 1443, "probe_score": 0.9983, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " of GNI. The\nsource is the World Bank’s World Development Indicators, which contains, among other things,\nall of the official loans and grants received by developing countries from multilateral or bilateral\nsources. <sup>25</sup> [^25: We cross-checked and verified the consistency of the data with the OECD database.] For this variable, there are two related but somewhat contradictory expectations.\nOne is that aid dependent countries are more likely to undertake public sector (including PFM)\nreforms (Therkildsen 2000 and 2001; see also Fialho Lopes and Fritz 2012), or that there is\npossibly even a reverse causation with donors investing more in countries that show greater\neffort and success with reforming their PFM systems. A contrasting expectation is that aid\ndependent countries invest less in such reforms relative to similar countries that rely more on\ndomestic revenues, due to stronger accountability relationships in the latter and negative\neffects of aid dependence on the coherence of the public sector (Brautigam and Knack 2004 and\nMoss et al. 2006). Thus, the exploration here is whether any clear cross-country pattern, either\npositive or negative, is statistically significant.  To test for potential measurement error of ODA\nand to check our results, we substitute aid with both Country Programmable Assistance (which\nexcludes volatile aid such as debt relief and emergency relief as well as donor overhead cost\nwhich is spent outside of the recipient country) and Technical Cooperation (see Table A3.1,\ncolumns 4 and 5). Finally, we check for inclusion and completion of the HIPC process, to explore\nwhether this group of countries differs significantly in terms of PFM performance from others.\n\nA first macro-political driver that we test is _political stability._ Political stability is widely\nconsidered a necessary ingredient for developing and improving institutions; and as mentioned\nin section 2, earlier work by de Renzio et al. (2011) has confirmed the opposite, i.e. fragility, to\n\n\n23 See Baunsgaard, Villafuerte, Poplaw", "output": {"entities": {"named_data": ["World Development Indicators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006176", "page": 18, "chunk": 1, "title": "wps7084", "pdf_url": "https://local/prwp/wps7084.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "World Development Indicators", "label": "NAMED_DATA", "score": 0.8755258917808533, "start": 40, "end": 68, "probe_score": 0.5095, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nNiger COVID-19 Emergency Response Projet (P173846)\n\n\ngroup workshops and community meetings; (ii) diversification of means of communication and rely more on social\nmedia and online channels. Where possible and appropriate, create dedicated online platforms and chatgroups\n(whatsapp) appropriate for the purpose, based on the type and category of stakeholders; and (iii) use of traditional\nchannels of communications (TV, newspaper, local radios, dedicated phone-lines, and mail) when stakeholders to do\nnot have access to online channels or do not use them frequently. These traditional channels, such as local radios\ncan also be highly effective in conveying relevant information to stakeholders and allow them to provide their\nfeedback and suggestions.\n\n**64. Large volumes of personal data, personally identifiable information and sensitive data are likely to be collected**\n**and used in connection with the management of the COVID-19 outbreak under circumstances where measures to**\n**ensure the legitimate, appropriate and proportionate use and processing of that data may not feature in national**\n**law or data governance regulations, or be routinely collected and managed in health information systems.** In order\nto guard against abuse of that data, the Project will incorporate best international practices for dealing with such\ndata in such circumstances. Such measures may include, by way of example, data minimization (collecting only data\nthat is necessary for the purpose); data accuracy (correct or erase data that are not necessary or are inaccurate), use\nlimitations (data are only used for legitimate and related purposes), data retention (retain data only for as long as\nthey are necessary), informing data subjects of use and processing of data, and allowing data subjects the opportunity\nto correct information about them, etc. In practical terms, operations will ensure that these principles apply through\nassessments of existing or development of new data governance mechanisms and data standards for emergency", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["personal data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000152", "page": 28, "chunk": 0, "title": "Niger - COVID-19 Emergency Response Project", "pdf_url": "http://documents1.worldbank.org/curated/en/876471587417866707/pdf/Niger-COVID-19-Emergency-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "personal data", "label": "VAGUE_DATA", "score": 0.5775589346885681, "start": 798, "end": 811, "probe_score": 0.1234, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Development Economics Technical Study No. 12. Rome, FAO. https://doi.org/10.4060/cb5157en\n\n\nWorld Bank. 2020. World Development Indicators. Washington, DC: World Bank Group. Accessed January 22,\n2020. https:// databank.worldbank.org/source/world-developmentindicators\n\n\nAbdallah, C., Der Sarkissian, R., Termos, S., Darwich, T. & Faour, G. 2018. Agricultural risk assessment for\nLebanon to facilitate contingency & DRR/CCA planning by the Ministry of Agriculture. Beirut, Centre National\nde la Recherche Scientifique (CNRS) and Food and Agriculture Organization of the United Nations (FAO).\n\n\nFAO and UNICEF. (2019). Child Labour in Agriculture: The Demand Side. Beirut, Lebanon: FAO and UNICEF.\nRetrieved from http://www.fao.org/documents/card/en/c/CA2975EN/\n\n\nBahn, Rachel A.; Juergenliemk, Armine; Zurayk, Rami; Debroux, Laurent; Broka, Sandra; Mohtar, Rabi. 2021.\nDigital Revitalization of the Agri-food Sector in Mashreq. Focus on Iraq, Jordan, and Lebanon. Washington,\nDC: World Bank.\n\n\nSep 02, 2021 Page 6 of 10", "output": {"entities": {"named_data": ["World Development Indicators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000036", "page": 5, "chunk": 1, "title": "Project Information Document (PID) - Decent Employment Creation for Vulnerable Lebanese Citizens and Syrian Refugees in Livestock Value Chains - P176547", "pdf_url": "http://documents.worldbank.org/curated/en/665221630592327291/pdf/Project-Information-Document-PID-Decent-Employment-Creation-for-Vulnerable-Lebanese-Citizens-and-Syrian-Refugees-in-Livestock-Value-Chains-P176547.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "World Development Indicators", "label": "NAMED_DATA", "score": 0.6923119425773621, "start": 111, "end": 139, "probe_score": 0.0036, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "9 of this proclamation states that the property situated on a land to be expropriated shall be\nvalued by a committee of not more than five experts having the relevant qualification and to be\ndesignated by the respective _woreda_ and urban administration. The local and federal\ngovernments have different roles in compensation. The _woreda_ and urban administrations are\nresponsible that compensation is paid and ensuring rehabilitation support to the extent possible,\nand maintain data regarding properties removed from expropriated landholdings (Proclamation\nNo. 455/2005 Article 13).\n\nAs per the new Oromia Urban Land Lease Proclamation No.4/2015/16 (2008EC), farmers who\nwill be physically displaced for urban development projects are entitled to get 500 meter square\nof Residence land if they have legal certificate and 160 meter square if they do not have legal\ncertificate and/or aged of 18 years and above in the town.\n\nThe GoE Council of Ministers has also enacted a regulation regarding the assessment of\ncompensation for assets situated on the land. Assets will be detailed into components to calculate\nthe value of the asset. Accordingly, assets on land include buildings, fences, crops (including\nperennial crops), trees, protected grasses, mining license, burial-grounds, and relocated property\n(Regulations No. 135/2007). The assessment of compensation does not include the value of the\nland itself because land is a public property and not subject to sale in Ethiopia. Article 13 of this\nregulation has set the formula to be used for valuating compensation (detailed formula relevant\nto estimate compensation in this ARAP is presented in section 6).\n\nCrops are subdivided into crops and perennial crops, and calculated based on yield per square\nmeter of land multiplied by price per kilogram. Components for building costs include cost per\nsquare meter. Trees could be cut and used by owner plus payment of compensation for loss of\ncontinued income. The cost of machinery, labour for improvement, and any infrastructure", "output": {"entities": {"named_data": [], "descriptive_data": ["data regarding properties removed from expropriated landholdings"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011951", "page": 18, "chunk": 0, "title": "Ethiopia - Trade Logistics Project : resettlement plan : Abbreviated resettlement action plan for the railway spur and livelihoods restoration measures for legacy land taking by government", "pdf_url": "https://documents.worldbank.org/curated/en/370981496823576177/pdf/SFG3422-RP-P156590-Box402913B-PUBLIC-Disclosed-6-7-2017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "data regarding properties removed from expropriated landholdings", "label": "DESCRIPTIVE_DATA", "score": 0.7216230630874634, "start": 481, "end": 545, "probe_score": 0.0896, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Sample is restricted to\nmale _employed_ _nonmigrants_ aged 20-59. Emp. is short for Employed and SE is short for Self-employed. Data source: Bangladesh HIES\n2016-17; Nepal LFS 2017-18; Pakistan LFS 2014-15 and 2017-18. - p _>_ 0.1, ** p _>_ 0.05, *** p _>_ 0.01.", "output": {"entities": {"named_data": ["Nepal LFS 2017-18", "Pakistan LFS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001163", "page": 44, "chunk": 6, "title": "idu0fca87f5e08111046900a713041f7dc8fc15f", "pdf_url": "https://local/prwp/idu0fca87f5e08111046900a713041f7dc8fc15f.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Nepal LFS 2017-18", "label": "NAMED_DATA", "score": 0.7280507683753967, "start": 167, "end": 184, "probe_score": 0.9981, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Pakistan LFS", "label": "NAMED_DATA", "score": 0.7979022264480591, "start": 186, "end": 198, "probe_score": 0.9995, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a large negative impact are possibly more\nlikely to report its occurrence than individuals who could mitigate the effects, thus\ncalling into question the assumption of exogeneity when _S_ is measured using self-reported\nshocks. This is an assumption on which internally valid estimation of _δ_ and _γ_ relies.\n\nUsing objective measures of shocks helps overcome this challenge. This is possible\nfor covariate shocks such as weather and prices for which data on exposure is available. However, even with objective measures of shocks, the variation in the probability\ndistribution of _Shjkt_ cannot be considered exogenous to welfare across households.\n\nWe rely on the following observation to address this: although variation in the probability distribution of _Shjkt_ may not be considered exogenous to welfare across households,\nthe _timing_ of a shock conditional on its distribution is exogenous (Thomas et al., 2010;\nAnttila-Hughes and Hsiang, 2013). Migration in Ethiopia is much lower than in other\ncountries (see World Bank 2015), so bias from migration is quite unlikely. Controlling\nfor the probability of occurrence and using objective measures of shocks improves the\ninternal consistency of estimates of _δ_ and _γ_ for drought and prices.\n\nVariables that reflect the likelihood of a shock occurring, that can allay concern\nabout the community unobserved effects, include dummies for agro-ecological zones of\nEthiopia and moments of the location-specific historical distribution for covariate shocks\nare included in _Xhjt_ . Some studies, e.g. Christiaensen and Subbarao (2005) construct a\npseudo-panel of cohort or community-level data using two cross-section datasets which\nallows community fixed effects to be included. However, in our dataset, the communities\nchosen are not the same in both rounds, and also, our drought shock variable is at the\ncommunity level which precludes the inclusion of community fixed effects, however we\ninclude a zone fixed-effect _", "output": {"entities": {"named_data": [], "descriptive_data": ["cross-section datasets"], "vague_data": ["data on exposure"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006922", "page": 6, "chunk": 1, "title": "wps7920", "pdf_url": "https://local/prwp/wps7920.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "data on exposure", "label": "VAGUE_DATA", "score": 0.5090192556381226, "start": 453, "end": 469, "probe_score": 0.084, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "cross-section datasets", "label": "DESCRIPTIVE_DATA", "score": 0.8715299367904663, "start": 1658, "end": 1680, "probe_score": 0.0615, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " level as_\n_[defined by the SDG 4.1.1b (UIS, 2020). The population of reference for this measure are the grades 4, 5 and 6 (as per the SDG 4.1.1b guidelines)](http://uis.unesco.org/en/topic/out-school-children-and-youth%22http:/uis.unesco.org/en/topic/out-school-children-and-youth)_\n_and age ranges 10 to 14. We use this country level indicator as a proxy for the scale of the learning crisis for all other grades and age ranges 5 to_\n_16. Additionally, this data also assumes that out-of-school children are below the minimum proficiency level._\n\n\nSAVE OUR FUTURE | **PART ONE: EDUCATION TODAY** **12**", "output": {"entities": {"named_data": [], "descriptive_data": ["country level indicator"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000619", "page": 11, "chunk": 6, "title": "Save Our Future: Averting an Education Catastrophe for the World’s Children", "pdf_url": "https://reliefweb.int/attachments/5adf7c8c-cd7f-3709-9d3a-da938afacb79/White-Paper-FINAL.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "country level indicator", "label": "DESCRIPTIVE_DATA", "score": 0.6854338049888611, "start": 322, "end": 345, "probe_score": 0.0116, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the causal effects of business uncertainty from court delays on company\n\n\nturnover, hiring and dismissals are of significant negative direction, and of sizable magnitude\n\n\n(Bamieh et al, forthcoming). Other work using Italian court data studies the effects of court\n\n\ninefficiency on public work performance. Where courts are inefficient, proxied by disposition\n\n\ntimes, Coviello et al (2018) find that public works are delivered with longer delays; that delays\n\n\nincrease for more valuable contracts; that contracts are more often awarded to larger suppliers; and\n\n\nthat a higher share of the payment is postponed after delivery.\n\n\n18", "output": {"entities": {"named_data": [], "descriptive_data": ["Italian court data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001023", "page": 19, "chunk": 1, "title": "idu0c20eb45a08f4504cee09199072bada1c4771", "pdf_url": "https://local/prwp/idu0c20eb45a08f4504cee09199072bada1c4771.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Italian court data", "label": "DESCRIPTIVE_DATA", "score": 0.8626449704170227, "start": 219, "end": 237, "probe_score": 0.7013, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\n_it will still take some time to get enough for a_\n_phone.”_ Burundian, Community leader\n\n\nThis is supported by survey data, which illustrates\nthat households with a higher average monthly\nhousehold expenditure are more likely to own\na device. Households with no device report an\n\n\n45. GSMA, 2017, Accelerating affordable smartphone ownership in emerging markets", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001202", "page": 18, "chunk": 1, "title": "Mobile is a Lifeline: Research from Nyarugusu Refugee Camp, Tanzania", "pdf_url": "https://reliefweb.int/attachments/b8a70c46-0699-36bc-a80b-b0381b5033de/60300.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7406274676322937, "start": 113, "end": 124, "probe_score": 0.9465, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " return). As the refugees did not cultivate, the host communities will\nstill have to share their harvest with refugees, making both refugees and hosts\ndepending on General Food Distributions to complement food at least up to the next\nharvest (in 12 months) provided refugees engage in agriculture next agriculture\nseason.\n\n10. Food security (cont.) –The dietary intake and meal frequency between the two\ngroups is similar: average once per week fish/meat; 3 meals before refugee arrival,\n1-2 meals when refugee arrived before GFD and 3 meals now with GFD. It is\ntherefore recommended to continue the General Food Distribution at least up to\nthe next harvest (in one year). Meantime, efforts should be made to ensure that\nrefugees have all inputs (seeds, fertilizer, tools and land) to engage in agriculture\nnext season (March-May). Further, the JAM recommends a gradual phase-out of\nGeneral Food Distribution after that period with a reasonable timeframe.\n\n11. Development projects –The mission team did not find any ongoing development\nprojects in the villages visited. It is reported that 2 micro-finance institutions\ninitiated micro-credit projects among host communities in the areas. The projects\n\n\n2 2006 MICS and QUIBB surveys report a 10.5% GAM among host community in the province\n3 First GFD took place in July 2010\n\n\niv\nJAM TOGO SEPT 2010", "output": {"entities": {"named_data": ["QUIBB surveys"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000002", "page": 4, "chunk": 1, "title": "MISSION D'EVALUATION CONJOINTE-HCR-PAM: Des besoins des Nouveaux Réfugiés Ghanéens au TOGO", "pdf_url": "http://documents.wfp.org/stellent/groups/public/documents/ena/wfp230273.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "QUIBB surveys", "label": "NAMED_DATA", "score": 0.7133967280387878, "start": 1220, "end": 1233, "probe_score": 0.2984, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nRoads and Employment Project (P160223)\n\n\npercent nationally, with regions of high concentration of refugees witnessing much higher increases. It is\nalso worthwhile noting that the composition of traffic generated by refugees includes a larger share of\nheavy trucks carrying supplies, equipment, and construction materials, which cause disproportionally\nhigher damage to the roads. It is estimated that the influx of refugees have increased the rehabilitation\nand upgrade needs of the road network by about US$50 million yearly. <sup>6</sup> [^6: The World Bank. Lebanon Economic and Social Impact Assessment of the Syrian Conflict. 2013.]\n\n\n11. **The road network is primarily managed by the MPWT and by the Council for Development and**\n**Reconstruction (CDR).** Several agencies are involved in the management of the network. The main road\nnetwork is under the responsibility of the MPWT. Meanwhile, given CDR’s capacity in executing large\nprojects, it is usually entrusted at the request of the Council of Ministers with the construction and\nmaintenance of international roads and some of the primary roads. At the municipal and local level, the\ndelineation of the road sector’s responsibilities between the MPWT and municipalities remain unclear in\nmany cases. MPWT is often compelled, by request from municipalities or in response to political pressure,\nto manage the construction and maintenance of a significant portion of the municipal and local road\nnetworks given the lack of adequate financial and human resources in the municipalities. This diverts\nimportant resources from MPWT’s budget (about 25 percent) that is allocated for the management of the\nnational network.\n\n\n12. **Weak capacity and the absence of asset management tools further undermine the proper**\n**preservation and maintenance of Lebanon’s road network.** The selection and prioritization of road\nconstruction and maintenance is generally done based on political preferences, rather than adequate road\nasset management. While an advanced asset management system was installed in the 1990s,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000008", "page": 16, "chunk": 0, "title": "Lebanon - Roads and Employment Project", "pdf_url": "http://documents.worldbank.org/curated/en/210611486651815142/pdf/Lebanon-Roads-Employment-PAD-P160223-01262017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\n#### **21. Disaster Risk Management and Nature-based Solutions**\n\n**21.1.** **Overview**\nThe significant hazards in Yemen are covered in Section 5.1 and the disaster management\nsystem summarized in Section 5.5.\n\n\nYemen Environment Profile - 35 – September 2023", "output": {"entities": {"named_data": ["Yemen Environment Profile"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000976", "page": 38, "chunk": 3, "title": "Yemen: Environmental Country Profile for Shelter and Settlements - 1st edition, September 2023", "pdf_url": "https://reliefweb.int/attachments/90db844c-725a-4ac9-b111-aaca6fbba623/Yemen%20Environmental%20Shelter%20Country%20Profile.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Yemen Environment Profile", "label": "NAMED_DATA", "score": 0.753070056438446, "start": 214, "end": 239, "probe_score": 0.251, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "36. **Business environment.** Jordan has a very poor track record of implementing business climate\nreforms.This is reflected in poor performance in Doing Business measures such as distance to the frontier\nand the World Economic Forum Competitiveness Index. The reasons for this poor performance relate to a\nlack of systematic processes to identify and implement reforms. Often, reforms are donor driven rather than\ndeveloped organically and, as a result, there is very little buy-in from stakeholders and poor implementation\nof regulations. Processes to ensure implementation of reforms are also weak. **Businesses face a**\n**constraining regulatory environment in Jordan, limiting the potential for formal entrepreneurship**\n**and job creation, including home-based enterprises** . The objective behind the proposed reforms is to\ncreate momentum and address regulatory areas that are important impediments to business growth.\n\n\n37. **This Program aims to institutionalize a systematic ‘home-grown’ process that will improve**\n**the business climate.** This includes (a) establishment of a deliberative and consultative process that\nprovides a menu of reforms; (b) predictability measures to ensure any new reforms are subject to a public\nnotice and consultation process; (c) development of a measurement system to assess implementation\nprogress; and (d) articulation of clear targets. The menu may contain reforms identified at the start of\nimplementation of the PforR as well as those identified through a consultative process during the Program\nlifetime.\n\n\n38. **In approaching the investment climate area, a multipronged approach has been developed.**\n\n\n    - The first prong addresses the medium- to long-term challenge of developing a predictable,\nsystematic approach to regulatory reform. The actions will be identified in consultation with\nthe private sector. A measurement system and a baseline will be put in place.\n\n\n    - The second prong aims to provide immediate impetus to implementing reform by focusing on\none regulatory area highly relevant to the business environment that can", "output": {"entities": {"named_data": ["World Economic Forum Competitiveness Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000137", "page": 20, "chunk": 0, "title": "Jordan - Economic Opportunities for Jordanians and Syrian Refugees Program for Results Project", "pdf_url": "http://documents1.worldbank.org/curated/en/802781476219833115/pdf/Jordan-PforR-PAD-P159522-FINAL-DISCLOSURE-10052016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "World Economic Forum Competitiveness Index", "label": "NAMED_DATA", "score": 0.7416335344314575, "start": 213, "end": 255, "probe_score": 0.9855, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " relevant to the entity's preparation and fair presentation of the financial\nstatements in order to design audit procedures that are appropriate in the circumstances, but not\nfor the purpose of expressing an opinion on the effectiveness of the entity's internal control. An\naudit also includes evaluating the appropriateness of accounting policies used and the\nreasonableness of accounting estimates made by management, as well as evaluating the overall\npresentation of the financial statements.\nWe believe that the audit evidence we have obtained is sufficient and appropriate to provide a\nbasis for our audit opinion.\n9 251-011-5515222 \nFax 251-011-5513083 \nE-mail: ASC@ethionet.com \n1 5720\n251-011-5535012\n251-011-5535015\n251-011-5535016\nPublic Disclosure Authorized\nPublic Disclosure Authorized\nPublic Disclosure Authorized\nPublic Disclosure Authorized", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014649", "page": 0, "chunk": 1, "title": "Ethiopia - Electricity Network Reinforcement and Expansion Project Audit report for the year ended June 30, 2018", "pdf_url": "https://documents.worldbank.org/curated/en/551531549003407068/pdf/Ethiopia-Electricity-Network-Reinforcement-and-Expansion-Project-Audit-report-for-the-year-ended-June-30-2018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "##### **4 Results**\n\n**4.1** **Descriptive** **Results**\n\n\n**4.1.1** **Baseline** **Balance**\n\n\nTable 1 provides summary statistics of covariate balance at baseline by treatment arm. The\n\n\nrespondents in my sample are on average 42 years old. They have 1.9 children on average; 63\n\n\npercent are married. About one-third of the sample lives in a rural area. Small imbalances\n\n\nare observed with respect to educational attainment. One in four respondents has completed\n\n\nhigher education; the percentage is 29 percent in T1 and 23 percent in T2 and control. I\n\n\ncontrol for educational attainment in all regressions and later introduce survey weights as a\n\n\nrobustness check.\n\n\nOn average, 42 percent of my sample work full time and 21 percent are homemakers. The\n\n\nOnline Appendix compares my sample’s geographical spread by governorate to the latest\n\n\nnational statistics (Institut National de la Statistique; 2022a) and shows that it is highly\n\n\ngeographically representative. It also compares the share of age cohorts (Institut National de\n\n\nla Statistique; 2022b): younger cohorts are overrepresented in my sample. In the robustness\n\n\nchecks, I show that weighing down younger cohorts does not affect my conclusions.\n\n\n**4.1.2** **Second-Order** **Beliefs**\n\n\nThe belief that a majority of one’s peers opposes political change may affect individual\n\n\nopinion and behavior. For example, an individual may refrain from taking a particular\n\n\naction or expressing a political opinion because she thinks that society will disapprove of\n\n\nor sanction it. Generalized misperceptions about public opinion may therefore hinder social\n\n\nchange and keep society captured in inefficient social equilibria (see Kuran, 1991). When\n\n\nstudying socially contentious issues such as the reform of law of religious origin, paying\n\n\nattention to individuals’ perceptions of what", "output": {"entities": {"named_data": [], "descriptive_data": ["national statistics"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001348", "page": 22, "chunk": 0, "title": "idu16715ac0d1906814580188631d44bf194b848", "pdf_url": "https://local/prwp/idu16715ac0d1906814580188631d44bf194b848.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "national statistics", "label": "DESCRIPTIVE_DATA", "score": 0.7745879888534546, "start": 852, "end": 871, "probe_score": 0.9543, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "for people with completed primary education. The lower likelihood of HE ownership for people\nwith completed secondary education and above is consistent with secondary education being\nrare, and therefore providing opportunities in relatively high paying non-farm wage and salary\njobs – often a more desirable alternative. Size of NFE is positively associated education, with\nself-employed HE owners without family help being the least educated, HE owners with family\nhelp being more educated and ME owners the most educated, almost as well educated as public\nsector wage workers (figure 12). And as shown below, education does increase earnings for HE\nowners. So while primary education may not be necessary to start a HE or ME, judging but the\nsorting among occupations be education, it seems to help.\n\n\nWhy do owners start HEs? Obviously, to make money. But are they “pushed” or “pulled”\ninto the sector? Consistent with divergent views of informal enterprises over time, many\nanalysts have discussed whether HEs are the „reserve‟ sector, where people end up because they\ncannot find other opportunities (a view associated with the “exclusion” school of thought) or a\ndynamic sector, which people enter to as a positive choice, to exploit an opportunity and/or to\nhave the independence that self-employment brings - a view associated with the “new” view of\ninformality (Maloney, 2004). Household surveys in two of our study countries (Tanzania and R.\nCongo) asked HE owners to report their main reason for starting a business and found that push\nfactors dominated the list. Not being able to find a wage and salary job was the most frequently\ncited reason, but it was cited by less than 40 percent of respondents (multiple responses were\npermitted). The need for income came in a close second, and was the most common in rural\nareas. The most commonly cited pull factor in R. Congo was the desire for independence, while\nin Tanzania the opportunity to", "output": {"entities": {"named_data": [], "descriptive_data": ["Household surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005349", "page": 20, "chunk": 0, "title": "wps6184", "pdf_url": "https://local/prwp/wps6184.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Household surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8769780397415161, "start": 1387, "end": 1404, "probe_score": 0.888, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "countries often lack the capacity to interpret and exploit data to meet the needs of schools and\n[to improve education planning (Piper et al., 2018a). When governments lack data or do not use it](https://doi.org/10.1007/s10833-018-9325-4)\nproperly, they may find themselves making crucial decisions on policies and resource allocation\n[without the necessary data to support their decision-making (World Bank, 2018a).](https://openknowledge.worldbank.org/bitstream/handle/10986/28340/211096ov.pdf)\n\n\n**The use of data can act as a lever of change, helping governments prioritize resources and**\n**monitor improvements for marginalized learners.** Strengthening and expanding data systems\nenable policymakers to gather and analyze school- and learner-level data to then be able to identify the most pressing systemic challenges as well as address areas of inequity. In Pakistan, for example, real-time school monitoring systems feed governance data back to policymakers who can\n[direct funds to struggling schools (GPE, 2019a). Without robust data on workforce management,](https://www.globalpartnership.org/content/pakistan-using-technology-bring-education-most-remote-areas)\n[it is difficult to direct resources to address the needs of rural children (Naylor et al., 2019). Stud-](https://scholar.harvard.edu/mkraft/publications/effect-teacher-coaching-instruction-and-achievement-meta-analysis-causal)\nies on the _Tusome_ program in Kenya suggest that high-quality data enabled teachers to quickly\n[adapt and improve their teaching model by providing rapid feedback (Piper et al., 2018a). Some](https://", "output": {"entities": {"named_data": [], "descriptive_data": ["governance data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000619", "page": 56, "chunk": 0, "title": "Save Our Future: Averting an Education Catastrophe for the World’s Children", "pdf_url": "https://reliefweb.int/attachments/5adf7c8c-cd7f-3709-9d3a-da938afacb79/White-Paper-FINAL.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "governance data", "label": "DESCRIPTIVE_DATA", "score": 0.563444197177887, "start": 931, "end": 946, "probe_score": 0.305, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "g) Generating progress and monitoring reports.\n\n\n48. **Under this project, two types of monitoring are envisaged:** (i) monitoring the project\nperformance with regard to day-to-day progress of project activities (including targets and\nintermediate results) as per the implementation plan; and (ii) evaluating the project with regard to\nachievement of the overall development objective.\n\n_Monitoring_\n\n49. Monitoring will be a continuous function carried out by MoPH/PMU with support from\nthe MoPH HIS team. Specifically, it will comprise of two aspects as follows:\n\n\na) **Establishing a monitoring system (** **_as part of health information system_** **) which will**\n\n**include:** (i) annual work plans, targets, outputs, indicators, and outcomes for each\ncomponent; (ii) baseline data, if available, for each outcome indicator; and (iii) user\nfriendly data entry format and built in methodology that will automatically update the\ntargets, outputs, and signal the achievement gap to alert the implementing agencies. The\nfocus will be on systematic data collection on specified indicators and related\ndeliverables to provide management and the main stakeholders the extent of progress and\nachievement of results and progress in the use of allocated funds.  The data will be\ncollected and reconciled with the PHCCs databases with specific focus on beneficiary\nenrollment and packaged delivered.  This will enable management decisions to be made\nbased on an assessment of whether the program is moving towards its objectives. A\nperiodic financial audit will be conducted which will also help to identify and mitigate\nany potential sign of fraud and governance issues. The program monitoring system will\nrely on regular and accurate data collection and analysis to identify the timely\nimplementation of activities, the achievement of intended results, and positive and\nnegative unintended effects.\n\n\ni. **HIS** will form the basis for a well-functioning monitoring system and will\ncomprise: (i)", "output": {"entities": {"named_data": [], "descriptive_data": ["PHCCs databases"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000020", "page": 53, "chunk": 0, "title": "Lebanon - Emergency Primary Healthcare Restoration Project", "pdf_url": "http://documents1.worldbank.org/curated/en/185271468266958778/pdf/PAD12050PAD0P15264600PUBLIC00Box391428B.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "PHCCs databases", "label": "DESCRIPTIVE_DATA", "score": 0.7760303020477295, "start": 1309, "end": 1324, "probe_score": 0.08, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">260898-GO-RFQ / Supply<br>and Delivery of hay baler<br>equipment<br>|IDA / 59450|Component 1: Upscaling<br>Climate-Smart Agricultural<br>Practices (US$163.8 million<br>equivalent, of which IDA<br>US$150.0 million eq uivalent)|Post|Request for<br>Quotations|Limited<br>|Single Stage - One<br>Envelope||70,588.00|0.00|Pending<br>Implementati<br>on|||||||2021-11-05||||||||2021-11-19||2022-05-18||\n|KE-KERICHO COUNTY-<br>260900-GO-RFQ / Supply<br>and delivery of outdoor<br>portable wireless Bluetooth<br>and water proof speaker<br>|IDA / 59450|Component 1: Upscaling<br>Climate-Smart Agricultural<br>Practices (US$163.8 million<br>equivalent, of which IDA<br>US$150.0 million eq uivalent)|Post|Request for<br>Quotations|Limited<br>|Single Stage - One<br>Envelope||980.40|0.00|Pending<br>Implementati<br>on|||||||2021-11-05||||||||2021-11-18||2022-02-16||\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|NON CONSULTING SERVICES|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|Col10|Col11|Col12|Col13|Col14|Col", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008614", "page": 3, "chunk": 1, "title": "Kenya - AFRICA EAST- P154784- Kenya Climate Smart Agriculture Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/145961602441900118/pdf/Kenya-AFRICA-EAST-P154784-Kenya-Climate-Smart-Agriculture-Project-Procurement-Plan.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "“_\n\n\n\nMy daughter was harassed by teachers for being\n## _“_\npartially deaf, and students in the class did not like her.\nShe was strong but after some time we decided it was\n## not good for her to go to school.  A focus group discussion participant ”\n\n\n\nA focus group discussion participant\n(caregiver) reflected her frustration\n\n\n\nMy parents never sent me to school in Syria because\n## _“_\nthey were worried that I would be bulliedA focus group discussion participant _.”_\n\n\nChildren with disabilities expose to various risks\nacross the region. Children also experience violence,\nexploitation and abuse if they are children of disable\nparents.\n\n\n## _“_\n\n\n\nMy husband is deaf, and we have three children. My\n## “   son has been raped on the way to school (more than\n\nonce), and I feel so hopeless because my husband can’t\nhelp so much, and I look after everyone in the family,\n## and I can’t manage with everything. A focus group discussion participant ”\n\n\n\nA focus group discussion participant\n\n\n\nChildren with disabilities are less likely to know about\ntheir rights because they are more likely to be excluded\nfrom school, and other forms of social participation.\nAlthough no quantitative data is available to demonstrate\nthe extent of violence experience by the children with\ndisabilities, the focus group discussions participants", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["quantitative data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001114", "page": 27, "chunk": 2, "title": "The power of inclusion- Mapping the Protection Responses for Persons with Disabilities Among Refugees in the Middle East and North Africa Region", "pdf_url": "https://reliefweb.int/attachments/a9759a2c-c79d-3881-bf7e-632f1a6e0bf3/74147.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "quantitative data", "label": "VAGUE_DATA", "score": 0.822640061378479, "start": 1177, "end": 1194, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "0.58<br>0.44<br>0.31<br>0.58<br>0.34<br>0.06<br>n.a<br>n.a<br>SSA<br>NGA<br>Nigeria<br>1.942<br>0.05<br>0.73<br>n.a<br>0.39<br>0.5<br>0.43<br>n.a<br>0.3<br>0.19<br>LAC<br>PER<br>Peru<br>1.000<br>0.16<br>0.48<br>0.1<br>0.77<br>0.59<br>0.34<br>0.13<br>0.38<br>0.55<br>ECA<br>ROU<br>Romania<br>1.512<br>0.05<br>0.35<br>0.03<br>0.58<br>0.25<br>0.75<br>n.a<br>n.a<br>n.a<br>SSA<br>SSD<br>South Sudan<br>1.213<br>0.3<br>0.66<br>0.46<br>0.75<br>0.39<br>0.41<br>0.21<br>0.37<br>0.35<br>LAC<br>LCA<br>St. Lucia<br>1.093<br>0.02<br>0.45<br>n.a<br>0.57<br>0", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000520", "page": 42, "chunk": 41, "title": "how did the covid 19 crisis affect different types of workers in the developing world", "pdf_url": "https://local/prwp/how-did-the-covid-19-crisis-affect-different-types-of-workers-in-the-developing-world.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 10\nPage 2 of 2\nDJIBOUTI: School Access and Improvement Program\n\n\nCountry at a Glance\n\n\n_Djibouti_\n\n\n**PRICES and GOVERNMENT FINANCE**\n\n**1979** **1989** **1998** **1999** **Inflation (%)**\n**_Domestic prices_**\n_(% change)_\nConsumer prices .\nImplicit GDP deflator 3.0 **_4_**\n\n**_Government_** _finance_ **2**\n_(% of GDP, includes current grants)_ -,\nCurrent revenue **.4** **95** **Os** **97** 98 99\nCurrent budget balance - GDP deflator e CPI\nOverall surplus/deficit\n\n\n\n**TRADE**\n\n\n\n**1979** **1989** **1998** **1999**\n_(US$ millions)_\nTotal exports (fob)\n\n\n\nn.a.\nn.a.\nManufactures\nTotal imports (cif ..\nFood\nFuel and energy\nCapital goods\n\n\n\nExport price index _(1995=100)_ _._\nImport price index _(1995=100)_\nTerms of trade (1995=100) .\n\n\n**BALANCE of PAYMENTS**\n\n_(US$ rrillions)_ **1979** **1989** **1998** **1999** **Current account balance to GDP ratio (%)**\n\n\n\nExports of goods and services .\nImports of goods and services\nResource balance .. .. **4**\n\n\n\nNet income\nNet current transfers\n##### 1.8 11\n\n\n\nCurrent account balance . **.2**\n\n\n\nFinancing items (net)\nChanges in net reserves .. .\n_Memo:_\nReserves including gold _(US$ millions)_\nConversion rate _(DEC, loca", "output": {"entities": {"named_data": [], "descriptive_data": ["Import price index"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018603", "page": 63, "chunk": 0, "title": "Uganda - Road Sector Institutional Support Technical Assistance Project : environmental assessment (Vol. 2 of 7) : Final report Part 2 - socio cultural assessment", "pdf_url": "https://documents.worldbank.org/curated/en/815311468115453579/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Import price index", "label": "DESCRIPTIVE_DATA", "score": 0.73746258020401, "start": 686, "end": 704, "probe_score": 0.9271, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " World Bank Policy and Directive for Investment Project Financing and will have acceptable\nfinancial management arrangements.\n\nThe risks identified for SEAS are as follows: (i) no prior experience in executing World Bank financed operations;\n(ii) limited human resources to undertake the financial management functions of the project; (iii) SEAS has limited\ninternal control procedures; (iv) SEAS does not produce any financial reports; and (v) SEAS is a public institution\nand falls under the audit of the Supreme Audit Institution (SAI). Although the SAI has the required experience, it\nhas limited human resources capacities. The SAI may not specifically audit the project as part of SEAS’s operations\non a yearly basis which would give limited assurance on the project’s use of funds.\n\nBased on the above risks, the following mitigating measures have been agreed upon for SEAS to reduce the risk\nlevel to moderate: (i) SEAS will recruit a Finance Officer (FO) to work on the project. The World Bank will provide\nthe necessary support and training on World Bank Financial Management procedures; (ii) SEAS will acquire an\naccounting software with specifications acceptable to the World Bank, the software will be used to record the\ndaily transactions and produce the un-audited IFRs. The format of the IFRs will be agreed upon with the World\nBank. The IFRs will be submitted to the World Bank no later than 45 days after the end of each quarter; (iii) for\nthe purpose of the project, SEAS will develop a POM which will contain an financial management chapter\ndescribing in detail the financial management procedures including internal controls; (iv) recruit a technical\nauditor with ToR acceptable to the World Bank to verify that “conditions have been fulfilled/beneficiaries received\n\n\nPage 38 of 44", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000154", "page": 42, "chunk": 1, "title": "Djibouti - Integrated Cash Transfer and Human Capital Project", "pdf_url": "http://documents1.worldbank.org/curated/en/893891558231269265/pdf/Djibouti-Integrated-Cash-Transfer-and-Human-Capital-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "The average unit cost for refugee education is US$1,051. There are large variations by country\nincome categorization: the average unit cost for refugee education in low, lower-middle and\nupper-middle income countries is US$171, US$663 and US$2,085 respectively. This report is\n\naccompanied by a dashboard where host countries can review summaries of country-specific\n\nrefugee numbers, unit costs, cohort average annual costs, and average and total costs by level\nof education. These figures are also provided in the annex of the report.\n\n\nAny methodology that is adopted will rest on a set of assumptions and agreed approaches,\nis likely to use proxies, omit some aspects, and rely on incomplete data sets. The cost of\nrefugee-specific education programmes will differ by country and might not match the global\n\naverage coefficients assumed in this report. These programmes will have to be differentiated\nby areas and years of intervention, geographical scope, technical capacity requirements,\nand so on. This report calls for improved data collection and reporting on refugee education,\n\nespecially regarding demographics, the cost of refugee education programmes and how these\nevolve over time as the initial emergency response becomes a protracted situation, and the\nunit cost of public education in host countries. This will lead to improvements in the process\nof measuring the impact and contributions of host countries and make for more the accurate\nrefugee education financing estimates.\n\n\nWhile this report provides global as well as country-specific financing requirements, it does\nnot attempt to substitute for national planning with inclusive education strategies and costed\nimplementation plans, nor is it meant for cross-country comparisons. It aims to provide an\naggregate dollar estimate of “what it would take” to educate all refugees in their current host\ncountries. The estimates presented in this report do not reflect international commitments or\nobligations, nor current domestic expenditure on refugee education. This report commends\nthe momentum gained in the development of national inclusive education systems and aims\nto support countries by providing guiding principles for", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["incomplete data sets"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001517", "page": 12, "chunk": 0, "title": "The Global Cost of Inclusive Refugee Education, January 2021", "pdf_url": "https://reliefweb.int/attachments/ea59adb5-3c30-3162-aeb6-c79c7b543a39/2020GlobalCostInclusiveRefugeeweb.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "incomplete data sets", "label": "VAGUE_DATA", "score": 0.6107994914054871, "start": 685, "end": 705, "probe_score": 0.0564, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Wasser & Creed-Kanashiro, 2011). In sum, while existing literature suggests that maternal\n\n\nmental disorders and undernutrition may be associated, the evidence supporting a general\n\n\nassociation between parenting quality and undernutrition is mixed, suggesting that parenting and\n\n\nundernutrition may influence child development through mostly distinct pathways.\n\n\nParenting quality clearly has important impacts on child development overall. Both child\n\n\ndevelopment and economic theories suggest two sources of variation in parenting on child\n\n\ndevelopment: first, that different types of parenting may affect different domains of child\n\n\ndevelopment and, second, that parenting may have variable effects on child development\n\n\ndepending on child characteristics and environmental conditions.\n\n\n**_Role of different types of parenting on child development_** . In interactions with young\n\n\nchildren, parents engage in multiple forms of teaching and support. Parenting is the primary\n\n\nmechanism by which children’s health and nutrition, as well as overall growth and development\n\n\nare facilitated (Phillips & Shonkoff, 2000). Emotionally responsive parenting refers to parents’\n\n\nabilities to respond sensitively to children both verbally and physically, while cognitively\n\n\nstimulating parenting refers to parents’ stimulation of learning through use of language,\n\n\nintroduction of new games and ideas, as well as exposure to high-quality learning environments\n\n\n(Bornstein & Putnick, 2012).\n\n\nExisting research suggests some degree of differentiation between domains of parenting:\n\n\nparents who are emotionally responsive are not necessarily cognitively stimulating; in addition,\n\n\nthere is some degree of differentiation demonstrating that emotionally-responsive parenting is\n\n\nespecially important for social/emotional development, while cognitively-stimulating parenting\n\n\npromotes young children’s learning and development. “Negative parenting,” or reliance on\n\n\nharsh, punitive physical and verbal parenting, relates to disruptions in social/emotional\n\n\n4", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007455", "page": 5, "chunk": 0, "title": "wps8529", "pdf_url": "https://local/prwp/wps8529.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " especially when complemented with\n\n\naccess to electricity, is associated with a transformation away from agriculture in the Horn of\n\n\nAfrica. Table 2 reports the results of pooling data from Ethiopia and Kenya for all years. Having\n\n\naccess to a paved road at the district level is associated with a 4 percentage-point reduction in\n\n\nthe employment share of agriculture and a 2 percentage-point increase in the employment share\n\n\nof manufacturing. Combined investments in roads and electricity are associated with a major\n\n\nshift from agriculture to manufacturing and services. Having access to the combined access to\n\n\nroads and electricity at the district level is associated with a 27 percentage-point reduction in\n\n\nthe employment share of agriculture, a 10 percentage-point increase in the employment share of\n\n\nmanufacturing, and a 18 percentage-point increase in the employment share of services. Results\n\n\nby country reported in Tables A4 and A5 in the appendix show that the impacts are similar at the\n\n\ncountry level. The combination of roads and electricity access has a large impact on structural\n\n\nchange.\n\n\nWe then analyze the within-country heterogeneity in structural transformation across dis\n\ntricts, focusing on the share of agricultural employment and the population-weighted distance\n\n\nto the largest town.\n\n\n10", "output": {"entities": {"named_data": [], "descriptive_data": ["pooling data from Ethiopia and Kenya"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001716", "page": 11, "chunk": 1, "title": "infrastructure and structural change in the horn of africa", "pdf_url": "https://local/prwp/infrastructure-and-structural-change-in-the-horn-of-africa.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "pooling data from Ethiopia and Kenya", "label": "DESCRIPTIVE_DATA", "score": 0.6335726976394653, "start": 174, "end": 210, "probe_score": 0.6344, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "well as four Regional Project Committees will be put in place to approve sub-projects selected by\nbeneficiary communities. These committees will be chaired by NaCSA and include staff from\nregional level line ministry staff, NGOs, CBOs and members of civil society. At the national\nlevel, NaCSA will continue its consultations with line ministries and is signing Memoranda of\nUnderstanding with key line ministries to ensure the consistency of the NaCSA approach to\ncommunity driven development with their policies and development strategies and the\navailability of inputs required to ensure sub-project sustainability such as teachers, health\nworkers, teaching materials and medical supplies and equipment.\n\n\n_Project Financial Management and Auditing._ Under the on-going IDA financed CRRP\nProject, financial management and procurement responsibilities were sub-contracted to an\ninternational accounting firm. Since NaCSA's mandate has been extended until end-2008, an\ninternal Finance Department that will also be responsible for procurement, is being created.\nDuring the transition, the contract with the international accounting firm will be extended for\nanother year to provide training to new staff and ensure a smooth transition. A financial\nmanagement assessment was completed and a sumnmary risk analysis is described in Annex 6.\nThe bulk of financial transactions will be decentralized to NaCSA's four regional offices and ten\ndistrict offices. Arrangements for the decentralized flow of funds are described in the Operations\nManual. The regional offices will make payments to NGOs for community mobilization and\ncapacity building and transfer funds in three to four installments for community-based\nsub-projects based on the advancement of work.\n\n\nAn independent auditing firm acceptable to IDA will conduct the annual audit. A request\nfor proposals for the recruitment of the auditing firm has been approved. _The appointment of an_\n\n_independent auditor for the Project is a condition of credit effectiveness._ The audit would\ninclude a financial review and physical inspection of a sample of sub-projects. The auditor will\nvisit sub-project sites to confirm that procurement was consistent", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010957", "page": 14, "chunk": 0, "title": "Uganda - Second Northern Uganda Reconstruction Project (Vol. 1 of 2) : Environment and social management framework", "pdf_url": "https://documents.worldbank.org/curated/en/302601468349441335/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**REFERENCES**\n\n\nBagwell, Kyle and Staiger, Robert W. 1999. ‘An economic theory of GATT’, _American_\n\n\n_Economic Review_ 89(1): 215–48.\n\n\nBagwell, Kyle and Staiger, Robert W. 2002. _The economics of the world trading system_ .\n\n\nCambridge, MA: MIT Press.\n\n\nBaldwin, Richard and Evenett, Simon J. (eds.) 2009. _The collapse of global trade, murky_\n\n\n_protectionism, and the crisis: recommendations for the G20_ . www.VoxEU.org E\n\nbook, March.\n\n\nBown, Chad P. 2010. ‘Global antidumping database’, current version\n\n\n[6.0, http://www.brandeis.edu/~cbown/global_ad/, accessed on 15 February 2010.](http://www.brandeis.edu/%7Ecbown/global_ad/)\n\n\nBown, Chad P. and McCulloch, Rachel 2010. ‘Developing countries, dispute settlement,\n\n\nand the advisory centre on WTO law’, _Journal of International Trade &_\n\n\n_Economic Development_ 19(1): 33–63.\n\n\nBown, Chad P. 2009a. _Self-enforcing trade: developing countries and WTO dispute_\n\n\n_settlement_ . Washington, DC: Brookings Institution Press.\n\n\nBown, Chad P. 2009b. ‘The global resort to antidumping, safeguards, and other trade\n\n\nremedies amidst the economic crisis’ _,_ in Evenett, Hoekman and Cattaneo (eds.),\n\n\n_Effective crisis response and openness: Implications for the trading system._\n\n\nLondon, UK: World Bank and CEPR.\n\n\nBown, Chad P. 2009c. ‘Protectionism is on the rise: antidumping investigations’, in\n\n\nBaldwin and Evenett (eds.)", "output": {"entities": {"named_data": ["Global antidumping database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004491", "page": 35, "chunk": 0, "title": "wps5301", "pdf_url": "https://local/prwp/wps5301.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Global antidumping database", "label": "NAMED_DATA", "score": 0.6521748900413513, "start": 465, "end": 492, "probe_score": 0.0278, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "output": {"entities": {"named_data": [], "descriptive_data": ["household expenditure survey data", "data from the Household Survey"], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000100", "page": 38, "chunk": 1, "title": "Bosnia and Herzegovina - Second Electric Power Reconstruction Project", "pdf_url": "http://documents1.worldbank.org/curated/en/583901468768013967/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "household expenditure survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8699104189872742, "start": 565, "end": 598, "probe_score": 0.7323, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.5808603167533875, "start": 870, "end": 881, "probe_score": 0.1461, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from the Household Survey", "label": "DESCRIPTIVE_DATA", "score": 0.5346028804779053, "start": 1978, "end": 2008, "probe_score": 0.1121, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Financial Management Action Plan**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Action|Date due by|Responsible|\n|---|---|---|---|\n|1|Develop and finalize the Operations Manual which<br>will include an FM chapter|No more than 1 month<br>after project<br>effectiveness|PCM<br>MOSA|\n|2|Develop TORs for project external auditor and<br>submit to the Bank|Within 3 months after<br>project effectiveness|PCM<br>through<br>FOT|\n|3|Develop TORs for internal auditor and submit to<br>the Bank|Within 3 months after<br>project effectiveness|PCM<br>through<br>FOT|\n|4|Appoint a project external auditor acceptable to<br>the Bank|Within 6 months from<br>Project effectiveness|PCM|\n|5|Appoint an internal auditor acceptable to the Bank|Within 6 months after<br>project effectiveness|PCM|\n|6|Quarterly IFRs submitted to the Bank|45 days after the end<br>of each quarter|PCM<br>through<br>FOT|\n|7|Annual project audited PFS, audit report, and<br>project management letter|Within 6 months after<br>the end of each fiscal<br>year period|PCM<br>through<br>FOT|\n|8|Periodical and ad hoc internal audit reports|Based on agreement|PCM|\n\n\n\n**World Bank Supervision**\n\n\n27. A supervision mission will be conducted at least twice a year based on the risk\nassessment of the project. Among the supervision mission objective is to ensure that strong\nfinancial management systems are maintained throughout the life of the project. The IFRs will be\nreviewed on a regular basis by the World Bank team and the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000139", "page": 48, "chunk": 0, "title": "Lebanon - Emergency National Poverty Targeting Program Project", "pdf_url": "http://documents1.worldbank.org/curated/en/810511467987899324/pdf/PAD1030-ENGLISH-P149242-PUBLIC-FINAL-LEB-ENPTP-English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Public Disclosure Copy\n\n\n**The World Bank** Implementation Status & Results Report\nET Competitiveness and Job Creation Proj (P143302)\n\n\nPHINDIRITBL\n\n\n Of which women (Percentage, Custom Supplement)\n\n\nBaseline Actual (Previous) Actual (Current) End Target\n\n\nValue 0.00 0.00 0.00 60.00\n\n\nOverall Comments\n\n\n**Data on Financial Performance**\n\n\n**Disbursements (by loan)**\n\n\nProject Loan/Credit/TF Status Currency Original Revised Cancelled Disbursed Undisbursed Disbursed\n\n\nP143302 IDA-54510 Effective XDR 161.60 161.60 0.00 9.39 152.21 6%\n\n\n**Key Dates (by loan)**\n\n\nProject Loan/Credit/TF Status Approval Date Signing Date Effectiveness Date Orig. Closing Date Rev. Closing Date\n\n\nP143302 IDA-54510 Effective 13-May-2014 20-May-2014 04-Aug-2014 30-Jun-2020 30-Jun-2020\n\n\n**Cumulative Disbursements**\n\n\n6/17/2016 Page 9 of 10\n\nPublic Disclosure Copy", "output": {"entities": {"named_data": [], "descriptive_data": ["Data on Financial Performance"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013445", "page": 8, "chunk": 0, "title": "Ethiopia - ET Competitiveness and Job Creation Proj : P143302 - Implementation Status Results Report : Sequence 05", "pdf_url": "https://documents.worldbank.org/curated/en/465851468275948037/pdf/ISR-Disclosable-P143302-06-17-2016-1466169985277.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Data on Financial Performance", "label": "DESCRIPTIVE_DATA", "score": 0.5358202457427979, "start": 308, "end": 337, "probe_score": 0.0007, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Recurrent|Yearly|Disclosed award decisions of UN<br>Agencies based on the developed<br>tracking system|\n|Undertake<br>assessment study<br>and develop<br>coding and<br>categorization<br>system of<br>procurable items|Fiduciary Systems||Client|Recurrent|Yearly|Developed and implemented the<br>coding and categorization system<br>of procurable items|\n|Gender based<br>violence strategy<br>for the health<br>sector is prepared<br>and implemented<br>and analysis of<br>gender<br>disaggregated<br>HMIS data is<br>conducted|Technical||Client|Recurrent|Yearly|Developed health sector Gender<br>Based Violence strategy and<br>disclosed gender analysis from<br>HMIS.|\n\n\nPage 23 of **!Syntax Error**", "output": {"entities": {"named_data": ["HMIS data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005887", "page": 24, "chunk": 1, "title": "Disclosable Restructuring Paper - Health Sustainable Development Goals Program-for-Results - P123531", "pdf_url": "https://documents.worldbank.org/curated/en/099130003292220474/pdf/P123531096beb60eb0be0d077a47e3077da.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "HMIS data", "label": "NAMED_DATA", "score": 0.8631032705307007, "start": 492, "end": 501, "probe_score": 0.3258, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<br>area/rooms and space for|Provide sufficient working area/rooms and<br>space for seating of staff and record|Throughout<br>project|MOES|\n\n\nPage 79 of 94\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n35 Uganda Registration Services Bureau – responsible for registration of companies in Uganda", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000018", "page": 84, "chunk": 3, "title": "Uganda - Secondary Education Expansion Project", "pdf_url": "http://documents.worldbank.org/curated/en/406361595815248191/pdf/Uganda-Secondary-Education-Expansion-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\n[34 FAO and UNICEF, (2019). Child Labour in Agriculture: The Demand Side.](http://www.fao.org/3/ca2975en/ca2975en.pdf)\n\n\n\n\n- The country’s referral information management system\nis seen as exemplary, overcoming the bottleneck in\neffective referrals to services observed globally. <sup>33</sup> [^33: ILO, (Forthcoming 2021). Global review of child labour responses [Actual title unknown].]\n\n\n- Of particular note is that FAO and ILO are working\ntogether to support the government in addressing\ndemand side risk of child labour, which is not often\nprioritized in the region, even as the need for such\napproaches is widely acknowledged.\n\n\nSeveral gaps were identified:\n\n\n- Stakeholders need to coordinate with the Ministry\nof Education and Higher Education (MEHE) to get\neducation to rural areas and hard to reach places. <sup>34</sup>\n\n\n- Greater investments are needed on reducing child\nlabour risks through greater engagement with families\nand communities, including addressing household\npoverty.\n\n\n- There is a need for more in-depth information,\nespecially with regard to the drivers; the main source of\ndata on child labour is the child protection information\nmanagement system.\n\n\n- There is a need to incorporate the Shawish into child\nlabour response as they are the main actors recruiting\nand hiring children in some areas.\n\n\n19", "output": {"entities": {"named_data": [], "descriptive_data": ["child protection information\nmanagement system"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000489", "page": 17, "chunk": 1, "title": "Child labour within the Syrian refugee response - 2020 Stocktaking Report", "pdf_url": "https://reliefweb.int/attachments/4599421c-86bd-403b-8409-48874f7906c9/220731_Child_Labour_Stocktaking.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "child protection information\nmanagement system", "label": "DESCRIPTIVE_DATA", "score": 0.735951840877533, "start": 1136, "end": 1182, "probe_score": 0.446, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "-02-02|||2023-12-01|2024-03-26|2024-02-13||2024-03-19||2024-11-14||\n|ET-MINT-381332-GO-RFP / T<br>he Supply & Installation of IT<br>Equipment for Integrating th<br>e National Databases|IDA / 68560|2. Digital government and c<br>onnectivity|Prior|Request for Propo<br>sals|Open - Internationa<br>l|Single Stage - Two E<br>nvelope||0.00|Under Imple<br>mentation|||||2023-10-15|2024-06-17|2023-10-20|2024-06-21|||2023-12-04||2024-02-16||2024-03-22||2025-03-22||\n|ET-MINT-381330-GO-RFP / S<br>upply, Delivery and Installati<br>on of IT Related Equipment f<br>or Federated System of Inter<br>net Exchange Points -Rebid|IDA / 68560|2. Digital government and c<br>onnectivity|Prior|Request for Propo<br>sals|Open - Internationa<br>l|Single Stage - Two E<br>nvelope||0.00|Canceled|||||2023-10-05||2023-10-10||||2023-11-21||2024-02-03||2024-03-09||2024-11-04||\n|ET-MINT-387453-GO-RFP / D<br>evelopment, Supply and Conf<", "output": {"entities": {"named_data": ["e National Databases"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:004566", "page": 4, "chunk": 2, "title": "Ethiopia - EASTERN AND SOUTHERN AFRICA- P171034- Ethiopia Digital Foundations Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099100224085520912/pdf/P171034-2e98feae-b5b3-46d7-af26-bd28f187df55.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "e National Databases", "label": "NAMED_DATA", "score": 0.547264575958252, "start": 164, "end": 184, "probe_score": 0.0008, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " contracts identified in the\nProcurement Plan tables **_Not Applicable._**\n\n\n**_Domestic preference_** _as specified under paragraph 5.51_ of the Procurement\nRegulations **_(Goods and Works)_** .\n\n\nGoods: is not applicable for those contracts identified in the Procurement\nPlan tables;\n\n\nWorks: is not applicable for those contracts identified in the Procurement\nPlan tables\n\n\n**Other Relevant Procurement Information.**\n\n\nThe project has a CDD component and the project’s procurement\narrangements for community-based procurement will be in line with the\nprovisions of the Procurement Regulations and “Guidance Note for Design and", "output": {"entities": {"named_data": [], "descriptive_data": ["Procurement Plan tables"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002770", "page": 1, "chunk": 1, "title": "Kenya - EASTERN AND SOUTHERN AFRICA- P176758- NATIONAL AGRICULTURAL VALUE CHAIN DEVELOPMENT PROJECT (NAVCDP) - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099060224221018736/pdf/P17675811bf94802d1957d1677d94d455bf.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Procurement Plan tables", "label": "DESCRIPTIVE_DATA", "score": 0.6515897512435913, "start": 29, "end": 52, "probe_score": 0.0001, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">and<br>appropriately.|Solid<br>wastes<br>at<br>borehole| Community|Operation phase|5,000|\n|**Geologic risks**| Land subsidence <br> Environmental<br>degradation| EMCA,<br>1999<br> Public| Temporary casings may also be installed<br>during drilling in case they notice the<br>soil strata is weak to prevent the|Sinking of ground<br>around the proposed<br>borehole site|Contractor<br>|During<br>construction<br>phase of the|10,000|\n\n\n43", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012140", "page": 54, "chunk": 2, "title": "Kenya - Additional Financing for the Water and Sanitation Services Improvement Project : environmental assessment (Vol. 10 of 14) : Proposed Namboto Secondary School Borehole Water Supply Project", "pdf_url": "https://documents.worldbank.org/curated/en/383661468253778372/pdf/E29050V100AFR000Box385446B00PUBLIC0.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "tudiants ont été séparés de leurs parents et\n\n\nplacés dans des familles d'accueil par les autorités locales dans le but de s'assurer qu'ils\n\n\npoursuivent leurs études. En juin 2019, il y avait 168 élèves à Sebba : 37 dans le secondaire (10\n\n\nfilles et 27 garçons) et 131 dans le primaire (42 filles et 89 garçons), accueilli par 88 familles. Bien\n\n\nque l'intention était d'allouer 2 enfants par famille d'accueil, les circonstances ont incité certains\n\n\nà accueillir jusqu'à 5 enfants. En outre, un soutien psychosocial est nécessaire tant pour les\n\n\nenfants que pour les familles d'accueillit. La formation des familles d'accueil est également\n\n\nnécessaire, puisque seulement 10 d'entre elles ont officiellement le droit de recevoir des enfants,\n\n\ntandis que les 78 autres ont été impliquées pour répondre à l'urgence. <sup>37</sup>\n\n\nDe janvier à mars 2019, 257 enfants vulnérables (157 filles) séparés de leur famille ont été\n\n\nidentifiés et pris en charge. Les <sup>38</sup> travailleurs humanitaires ont convenu qu'il est nécessaire de\n\n\nprocéder à un recensement des cas de séparation familiale qui leur permettrait d'en analyser les\n\n\ncauses et de concevoir des plans de prévention et d'intervention en conséquence. <sup>39</sup>\n\n## **Travail des ", "output": {"entities": {"named_data": [], "descriptive_data": ["recensement des cas de séparation familiale"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001099", "page": 12, "chunk": 1, "title": "Risques et Besoins en matière de protection de l'enfance au Burkina Faso - Analyse des données secondaires - 2019", "pdf_url": "https://reliefweb.int/attachments/a6443b4f-dc18-4632-b17f-7a492dd9c5d6/burkina_faso_sdr_29_august_2019_french_final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "recensement des cas de séparation familiale", "label": "DESCRIPTIVE_DATA", "score": 0.8841142058372498, "start": 1057, "end": 1100, "probe_score": 0.1369, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " go beyond these modest efforts to create the critical\nmass o f regional programs and policies that can make a difference in their collective effort to\nstem the HIV/AIDS pandemic. Mobile populations, networks o f populations which are highly\nmobile and/or represent high risk when mobile (PLWAs), harmonizing health policies,\nprograms and services, and sharing epidemiological, behavioral and program data, all\nrepresent potentially significant mutual benefit.\n\n\nGreat Lakes countries are particularly affected by the HIV/AIDS epidemic with more than _6_\nmillion people living with HIV/AIDS out o f a total o f some 25 million in Sub-Saharan Africa\n(UNAIDS, 2004). It i s estimated that more than 3 million children have been orphaned or\nmade vulnerable by HIV/AIDS in the GLIA countries. With already high levels o f HIV\n\ninfection in the early 199Os, the situation has deteriorated over the past decade with massive\ndisplacement of populations, resulting from conflicts, genocide, natural disasters and difficult\nsocio-economic conditions. Aggregated figures o f adults age 15-49 reflect prevalence rates\nrange from 4.1% to 8.8%. By country it is Burundi (6.0%); DRC (4.2%); Kenya (6.7%);\nRwanda (5.1%); Tanzania (8.8%); and Uganda (4.1%) (December 2003 data provided in\n2004, UNAIDS).\n\n\nHIV/AIDS i s dramatically fueling the TB epidemic with up to 75 percent o f TB patients in\nsome countries co-infected. As can be seen from the figure to the right the trend in HIV\nprevalence in Kenya mirrors closely the pattern o f new TB cases with roughly a five year lag.\nCo-infection i s a particularly serious problem amongst displaced populations in the region\nwho are living in extremely difficult conditions. It i s likely that co-infection rates are\nrelatively high amongst these groups", "output": {"entities": {"named_data": [], "descriptive_data": ["epidemiological, behavioral and program data"], "vague_data": ["December 2003 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000021", "page": 4, "chunk": 1, "title": "Africa Region - Great Lakes Initiative on HIV/AIDS (GLIA) Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/188651468741666540/pdf/30267.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "epidemiological, behavioral and program data", "label": "DESCRIPTIVE_DATA", "score": 0.64979088306427, "start": 361, "end": 405, "probe_score": 0.9767, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "December 2003 data", "label": "VAGUE_DATA", "score": 0.5246630907058716, "start": 1242, "end": 1260, "probe_score": 0.9617, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Table 8: Out-of-sample dynamic forecast performance (RMSE, percent)\n\n\nAll countries\n\n\nTrade weight matrix Distance weight matrix\n\n\nForecast horizon 1 year 2 years 3 years 1 year 2 years 3 years\n\n\nCSD specification\n\n\nNone 2.870 4.605 3.733 2.870 4.605 3.733\nFactor only 2.133 3.965 3.337 2.133 3.965 3.337\nSpatial only 2.262 4.077 3.255 2.333 4.203 3.376\nFactor and spatial 2.094 3.951 3.316 2.146 3.981 3.357\n\n\nAdvanced countries\n\n\nTrade weight matrix Distance weight matrix\n\n\nNone 2.079 5.143 1.955 2.079 5.143 1.955\nFactor only 1.541 4.562 1.016 1.541 4.562 1.016\nSpatial only 1.930 5.045 1.671 1.926 5.050 1.690\nFactor and spatial 1.521 4.498 0.957 1.491 4.475 0.999\n\n\nNotes: The table shows the RMSE of dynamic forecasts over 2014-2016 obtained\n\nwith model estimates using data for 1970-2013 under alternative specifications of\n\ncross-sectional dependence. Specifications including a common factor use an AR(1)\n\nmodel to predict its future values.\n\n#### **5 Conclusion**\n\n\nOutput growth displays substantial comovement across countries. Existing empirical\nliterature has modeled the cross-sectional dependence of growth as reflecting either\nlocalized linkages across countries or regions, or pervasive common shocks - i.e., weak\nand strong cross-sectional dependence, respectively. In this paper we have brought\nboth perspectives together by assessing the international comovement of GDP growth\nin a setting that allows for both spatial dependence and latent common factors, using\nannual GDP growth data over the years 1970–2016 for 117 advanced and developing\ncountries.\n\nIn the paper’s empirical setting, the dynamics of growth", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data for 1970-2013"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000041", "page": 30, "chunk": 0, "title": "adding space to the international business cycle", "pdf_url": "https://local/prwp/adding-space-to-the-international-business-cycle.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "data for 1970-2013", "label": "VAGUE_DATA", "score": 0.6726395487785339, "start": 777, "end": 795, "probe_score": 0.9983, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009841", "page": 62, "chunk": 2, "title": "Kenya - Kiambere Hydroelectric Project", "pdf_url": "https://documents.worldbank.org/curated/en/226641493245755015/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nStrengthening Lebanon’s Covid-19 Response (P178587)\n\n\nin an inclusive and non-discriminatory manner. However, certain groups, including Syrian and Palestinian\nrefugees, have been lagging behind in COVID-19 vaccination (see Table 5) due to multiple challenges including\ndifficulties in navigating the vaccination registration process, vaccine hesitancy, fuel and economic crises, and\ncompeting priorities. A hesitancy survey conducted by International Medical Corps (IMC) in June/July 2021\nshowed that while the proportion of Lebanese willing to take the vaccine has increased by 32 percent, in the\nrefugee community, only a 10 percent increase was noted. In fact, more than 60 percent of refugees did not think\nthe COVID-19 vaccine was safe nor efficient. 10 percent of the surveyed refugees cited transportation to\nvaccination centers and security concerns as barriers to vaccination. According to a recent report on vaccine\nhesitancy among refugees in Lebanon <sup>8</sup> [^8: Vaccine Hesitancy Among the Refugee Community in Lebanon and Ways Forward. NGO joint paper by Oxfam GB, IRC, LHIF, NRC, JRS,\nAUB, and CLDH. November 2021.], Syrian refugees, similarly to Lebanese, had higher hesitancy towards\nspecific types of vaccines compared to others (namely more hesitancy towards the Astrazeneca vaccine compared\nto the Pfizer vaccine). This might have had an impact on the vaccination rates among Syrian refugees as their\npreferred vaccine type was restricted to specific age groups based on the prioritization plan at the initial stages of\nthe campaign. Refugees also expressed a shift in priority from COVID-19 related concerns to challenges arising\nfrom the socio-economic crisis. Several actors have been engaged in efforts to increase registration and\nvaccination among the refugee population. This includes outreach to Syrian refugees by phone and through doorto-door visits to raise awareness on the importance of vaccination and support in the registration process by\nUNHCR. UNHCR’s partners have also deployed mobile units to areas of high Syrian refugee concentrations to\nconduct vaccination. As for the <mark>United Nations Relief and Works", "output": {"entities": {"named_data": [], "descriptive_data": ["hesitancy survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000000", "page": 23, "chunk": 0, "title": "Lebanon - Strengthening Lebanon's COVID-19 Response under the COVID-19 Strategic Preparedness and Response Program (SPRP)", "pdf_url": "http://documents.worldbank.org/curated/en/099410007282239961/pdf/BOSIB09c1bfedd05c098380dc89cfe988b8.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "hesitancy survey", "label": "DESCRIPTIVE_DATA", "score": 0.8063364624977112, "start": 426, "end": 442, "probe_score": 0.9649, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<u><mark>Partie 1: Situation Générale</mark></u>\n\nA) Contexte général\nLa région du Bawku au Ghana a connu des conflits depuis les années 1960 entre les\nrésidents et les migrants qui étaient venus pour le commerce et qui s’y sont installés.\nCependant dans les 3 dernières années les conflits étaient sporadiques et imprévisibles\njusqu'en mars 2010. Le dernier grand conflit qui a connu 28 morts a eu lieu en 2001.\nEnviron 1000 personnes avaient été tuées dans un conflit pour l’accès aux terres entre\n1994 et 1995.\n\nAu début du mois de Mars 2010 une première vague de 300 réfugiés Ghanéens à la\nrecherche de sécurité, fuyant les conflits fonciers entre les villages de Kombatiek et\nNadongou, est arrivée au Togo. Ces 300 personnes sont retournées au Ghana quelques\nsemaines après leur arrivée au Togo. Les conflits du mois d’Avril 2010, suite auxquels\nquatre personnes avaient été tuées, plusieurs autres blessées et des centaines de\npropriétés détruites, ont forcé des milliers de personnes à quitter leur maison pour se\nrefugier au Togo. Les premières estimations avaient fait état de 6000 réfugiés.\nL’enregistrement scientifique réalisé par le HCR au mois de juillet a permis de stabiliser\nles chiffres à 3.664 réfugiés.\n\nLes réfugiés sont actuellement répartis dans 4 villages situés à l’Ouest de la préfecture\nde Tandjou", "output": {"entities": {"named_data": [], "descriptive_data": ["enregistrement scientifique"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000002", "page": 8, "chunk": 0, "title": "MISSION D'EVALUATION CONJOINTE-HCR-PAM: Des besoins des Nouveaux Réfugiés Ghanéens au TOGO", "pdf_url": "http://documents.wfp.org/stellent/groups/public/documents/ena/wfp230273.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "enregistrement scientifique", "label": "DESCRIPTIVE_DATA", "score": 0.6698312163352966, "start": 1103, "end": 1130, "probe_score": 0.798, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "In the U.K., recognition of the experience of having been trafficked as a characteristic\nof a particular social group has been inconsistent. The Immigration Appeal Tribunal\nrecognized a particular social group of ‘women in the Ukraine forced into prostitution\nagainst their will,’ which ‘exists independently of the persecution [the group] fears’ <sup>180</sup>\nHowever, regarding a Nigerian girl who was forced into child prostitution, the same\nTribunal stated that ‘trafficked women do not qualify as a PSG, since what defines\nthem is essentially the fact of persecution.’ <sup>181</sup>\n\n\nWhile it accepted the argument that ‘Nigerian women’ could constitute a social group,\nthe Tribunal unfortunately did not consider combining these two unchangeable,\ncommon and historic characteristics of the women who are ‘trafficked’ and\n‘Nigerian’. The Tribunal’s conclusion that trafficked women do not qualify as a\nparticular social group, without acknowledging that the experience of having been\ntrafficked may also be a characteristic of a particular social group, not only differs\nfrom its earlier decision but also diverts from the UNHCR Guidelines. Some critiques\nof the U.K. case law have also noted its inconsistency in the application of\nmembership of a particular social group. <sup>182</sup> As shown by these cases in the U.K.,\nidentification of particular social groups appears limited as compared to case law of\nAustralia, Canada or the U.S.\n\n\n_Political opinion_\n\n\nThe UNHCR Trafficking Guidelines note that individuals with certain actual or\nperceived political views may be more vulnerable to traffickers, because of the\nreluctance of the state to protect them. <sup>183</sup> Depending on circumstances, those who\nhave particular political opinions may be targeted by criminals related to politically\nopposing groups that may use trafficking as a method of persecution.\n\n\nThe U.S. Board of Immigration Appeals recognized a Chinese woman", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000197", "page": 25, "chunk": 0, "title": "International Protection for Trafficked Persons and Those Who Fear Being Trafficked", "pdf_url": "https://reliefweb.int/attachments/14203aa6-1ec9-34b2-92f3-cdbc4f5d3465/B2DA64611A8A9E02C12573C600476367-unhcr-dec2007.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nGenerating Livelihoods and Opportunities for Women (GLOW) Uganda (P176747)\n\n\n<mark>The construction and furnishing of some small agricultural and some socio-economic facilities (processing plants, day cares,</mark>\n<mark>etc.) and the expansion of micro, small and medium enterprise using project funds will likely carry moderate E&S risks and</mark>\n<mark>impacts but because they are expected to be small scale, influx of labor into benefiting communities is not expected thus</mark>\n<mark>issues such as SEA/SH and the spread of communicable diseases will be low. Likewise, physical and economic displacement</mark>\n<mark>are not expected from the construction activities because they are expected to be carried out in the footprint of land owned</mark>\n<mark>by local governments/Districts. However such works may result in restriction of access and disruption of people’s</mark>\n<mark>livelihoods. The borrower will be required to develop a Resettlement Policy Framework (RPF) to address any impacts on</mark>\n<mark>assets, restricted access and disruptions of livelihoods as provided for in ESS5. If affected, Indigenous Peoples are expected</mark>\n<mark>to benefit through the various project's interventions rather than being negatively impacted. The implementing agency has</mark>\n<mark>no experience implementing World Bank projects and will require a capacity building effort to support environmental and</mark>\n<mark>social risk management by the PIU.</mark>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nJun 15, 2021 Page 12 of 13", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000005", "page": 11, "chunk": 0, "title": "Concept Project Information Document (PID) - Generating Livelihoods and Opportunities for Women (GLOW) Uganda - P176747", "pdf_url": "http://documents.worldbank.org/curated/en/135361626935792550/pdf/Concept-Project-Information-Document-PID-Generating-Livelihoods-and-Opportunities-for-Women-GLOW-Uganda-P176747.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nProgram.\n\n\n_Table 5: Progress toward SDDS subscription from 2014 to 2020_\n\n|Col1|Data Category|Main Components|2014 Assessment|2020 Assessment|\n|---|---|---|---|---|\n|**1 **|**Real Sector**|**Real Sector**|||\n|1.1|National Accounts (NA)|GDP, current and constant prices|Partially met [A, C]|Met|\n\n\n\nPage 22 of 68\n\n\nOfficial Use", "output": {"entities": {"named_data": ["National Accounts (NA)"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011818", "page": 25, "chunk": 1, "title": "Kenya - Statistics Program for Results Project", "pdf_url": "https://documents.worldbank.org/curated/en/361021632404706322/pdf/Kenya-Statistics-Program-for-Results-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "National Accounts (NA)", "label": "NAMED_DATA", "score": 0.5578212738037109, "start": 215, "end": 237, "probe_score": 0.0104, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**1.** **Introduction**\n\n\nIn this paper, we investigate the impact of country legal regimes and company\n\n\ncorporate governance practices on company performance using a cross-country\n\n\nframework. Corporate governance is nowadays a widely used concept with many\n\n\nstudies of country legal regimes and company-specific corporate governance practices\n\n\nand structures. These studies have highlighted some aspects of legal regimes and main\n\n\ncorporate governance practices that are associated with improved company\n\n\nperformance and explored the channels through which corporate governance may\n\n\naffect performance. Although both legal regimes and company practices have been\n\n\nfound to matter in corporate governance, by how much each does and the interaction\n\n\nbetween legal regimes and company practices has not much been researched to date.\n\n\nIn this paper, by using data on practices for companies from different legal regimes,\n\n\nwe investigate not only the impact of country rules and detailed company-level\n\n\npractices on company valuation but also the degree of substitutability or\n\n\ncomplementarity between rules and practices in terms of their effect on company\n\n\nvaluation. We find that the valuation impact of company corporate governance\n\n\npractices varies by legal systems. In particular, we find evidence of overregulation\n\n\nwhen a company already has good corporate governance practices.\n\n\nThe importance of corporate governance has been well established in recent years.\n\n\nCorporate governance can reduce agency problems among shareholders and between\n\n\nmanagers and shareholders, limiting private benefits and expropriation by controlling\n\n\nowners. Better corporate governance also means better monitoring of management,\n\n\nwhich can translate into higher company performance. Much evidence supports these\n\n\ntwo channels (see Dennis and McConnell, 2003; and Claessens, 2006, for recent\n\n\nreviews). Typically though this empirical literature has investigated corporate\n\n\ngovernance from either a country or a company point of view. In their widely cited\n\n\npapers, La Porta et al. (1997, 1998, 2000, henceforth LLSV) show that higher investor\n\n\nprotection at the country level is associated with greater access to finance, more\n\n\ncapital market development, and higher company valuation. Starting with Gompers,\n\n\nIshii and Me", "output": {"entities": {"named_data": [], "descriptive_data": ["data on practices for companies"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002461", "page": 1, "chunk": 0, "title": "wps04140", "pdf_url": "https://local/prwp/wps04140.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "data on practices for companies", "label": "DESCRIPTIVE_DATA", "score": 0.7709134221076965, "start": 866, "end": 897, "probe_score": 0.7642, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "During my review, I observed some **inade** acies in the system; however, they are not senrous\n\n\n\nenough to withhold certification. hav detailed these inadequacies in the attachment, and\nincluded an action plan for remedy thsituation that was agreed upon with the Borrower.\n\n\n\nSigned by: _0 1_\nProcurement Specialist _\"_ i **°S** **TQI** 3 _1_ _,L_\nChristi fitAccraiT&~ Date\nProcureme taff, MNSt\n\n\n\n**Part III: Physical Monitorable Indicators and Overall Assessment**\n\nI have reviewed the project's system for monitoring physical implementation progress, including\nits monitorable indicators for major outputs. In my view, the system cannot provide the\nappropriate data on physical progress (PMR-Section 2) required by IDA.\n\nDuring my review, I observed some inadequacies in the system; however, they are not serious\nenough to withhold certification. I have detailed these inadequacies in the attachment, and\nincluded an action plan for remedying the situation that was agreed upon with the Borrower.\n\nSigned by: i A\n### Task Team Leader 1/ 4 -L- UJ 2, dO\n\nQaiser Khan, MNSHD Date\n\n\n**Part** IV: **Concurrence of** LOA for Eligibility of Project for PMR-Based Disbursements\n\n\nI have conducted a reasonable review of the process followed by the Task Team in assessing the\nproject, and I concur with its recommendation that this project is not eligible for PMR-Based\nDisbursements.\n\nSigned by: C____ __a _\nFMS-LOAADO Andrina Ambrose, LOAEL Date\n\n\nT.\n\n\nThu-Ha Nguyen, LOAEL Date", "output": {"entities": {"named_data": [], "descriptive_data": ["data on physical progress"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000175", "page": 55, "chunk": 0, "title": "Albania - Public Administration Reform Project", "pdf_url": "http://documents1.worldbank.org/curated/en/974831468742813639/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "data on physical progress", "label": "DESCRIPTIVE_DATA", "score": 0.6098982691764832, "start": 665, "end": 690, "probe_score": 0.023, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nCHAD Improving Learning Outcomes Project (P175803)\n\n\n\n\n\nOther Decision (as needed)\n\n\n**B. Introduction and Context**\n\nCountry Context\n\n\n1. **Chad is a land-locked, low-income country of 15.9 million people, with a real gross domestic product (GDP) per**\n**capita of US$ 814** (2019). The annual population growth is 3.1 percent. Two thirds of the population are under the age\nof 25 years and 77 percent live in rural areas. Being the third largest country by land mass in Sub-Saharan Africa, it has a\nrelatively low population density of 12.3 persons per square kilometer. The country is administratively divided into 23\nregions located in three main geographical zones: a desert zone in the north, an arid Sahelian belt in the center, and a\nmore fertile savanna zone in the south.\n\n\n2. **The economy is dominated by agriculture and extractive industries, mainly oil** . The economy grew robustly\nduring the period 2010-14 (roughly 7 percent per annum), but was hit hard by the collapse in oil prices in 2014-15,\nintroducing a period alternating between low and negative growth such that in real terms, GDP per capita is now lower\nthan ten years ago (US$985 (2011). 42 percent of the population lives below the national poverty line. <sup>1</sup> [^1: World Bank DataBank, World Development Indicators (Poverty Headcount ratio at national poverty lines, 2018).] While the country\nis slowly urbanizing (an increase of 1.4 percentage points in the past ten years), agriculture is expected to remain the\nlargest source of employment for the foreseeable future.\n\n\n3. **The extreme vulnerability of the Chadian economy to external shocks makes it difficult to sustainably finance**\n**development, especially social sectors** . Social spending serves as an adjustment variable in times of economic crises. In\nresponse to this", "output": {"entities": {"named_data": ["World Development Indicators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000009", "page": 2, "chunk": 0, "title": "Concept Project Information Document (PID) - CHAD Improving Learning Outcomes Project - P175803", "pdf_url": "http://documents.worldbank.org/curated/en/234501637169242309/pdf/Concept-Project-Information-Document-PID-CHAD-Improving-Learning-Outcomes-Project-P175803.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "World Development Indicators", "label": "NAMED_DATA", "score": 0.8685671091079712, "start": 1292, "end": 1320, "probe_score": 0.9992, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " refugee children have little or no access\nto specialized education programmes and tertiary education, even though the Education Policy and the\n2018–2030 Education and Training Roadmap provide for them.\n\n\n**4.2** **Healthcare**\n\n\nThe Refugees Proclamation provides refugees with access to available health services in Ethiopia under\nthe same conditions as nationals. This includes access to available national sexual and reproductive\nservices for refugee women and girls. There are no further regulations or guidance on how to facilitate this\naccess.\n\n\nData on the number of refugees accessing the national health-care system is not available. Generally,\nrefugees living out of camp access health care provided for by government institutions under the same\nconditions as nationals, but many need financial support for health care. The Government provides\nrefugees living in camp settings with HIV testing and treatment, TB, leprosy, and vaccination services,\nincluding both routine and campaign-based vaccination services, all free of charge. For other health\nservices, refugees in camp settings generally use the camp-based health system but in some contexts\nalso access the national health system in the host community. Correspondingly, on average, 10 per cent of\nthe users of the camp-based health system are host community members. In locations where the host\ncommunity’s health-care facilities are particularly poor, this can reach 30 per cent.\n\n\nA community-based health insurance (CBHI) scheme exists, but it is still in its pilot phase and non-existent\nin most refugee-hosting woredas. The extent to which refugees have the right to be enrolled is unclear.\nThere is no system in place for financing refugee health-care costs in the publicly financed health care\nsystem.\n\n\n**4.3** **Social protection**\n\n\nThe Refugees Proclamation stipulates that ARRA shall ensure that refugees and asylum-seekers with\nspecific needs are provided with special protection commensurately with their needs. There is no further\npolicy that provides guidance on how this is to be", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Data on the number of refugees"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000182", "page": 11, "chunk": 1, "title": "Ethiopia: Refugee Policy Review Framework Country Summary as at 30 June 2020 (March 2022)", "pdf_url": "https://reliefweb.int/attachments/111b3b4a-a284-3f1c-a35d-6fc00eb74ede/Ethiopia%20-%20Refugee%20Policy%20Review.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Data on the number of refugees", "label": "VAGUE_DATA", "score": 0.5246667265892029, "start": 553, "end": 583, "probe_score": 0.0006, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "s will coordinate closely throughout the project cycle with the county\ncoordination team (CCT), an interagency group headed by the County Commissioner. Both PDCs and BDCs are to serve as\numbrella local governance institutions and to play a larger role in local development and resiliency planning for their\ncommunities, as well as serve as an interface between the community and the county government that other development\npartners can utilize. <sup>60</sup> [^60: Types of capacity-building activities include familiarity with conflict/disaster risks and needs identification, resource mapping, local development planning, project\nidentification, budgeting, project implementation, oversight/monitoring, and social audit methods.] They will not take on roles and mandates that already belong to other formal and informal\nauthorities but look to strengthen coordination with them. Dependent on the status of COVID-19 precautions at the time\nof community engagement, additional precautions will be taken to provide extra space for discussions, community\nplanning, and training. BDC/PDC mobilization will also include COVID-19 sensitization as part of community engagement\nprotocols, to protect both BDC/PDC and community members during community organizing efforts.\n\n35. **Gender considerations** will be integrated throughout the project cycle through a two-tiered approach. In the first\ntier, all project sites will receive a core minimum package of activities that forward women’s meaningful participation and\nemployment opportunities under the project. Women in BDCs/PDCs will be supported by community mobilizers to\narticulate their needs and concerns and prepare their priority lists of subprojects to be financed by ECRP-II. Training on\nleadership, governance, and confidence building will be provided. Gender transformative training will be provided to both\nmen and women to deepen the appreciation of women’s enhanced roles in the household and in communities. In the\nsecond tier, where WASH sub-project investments require it, women-led WASH O&M groups will be established to build\nlocal capacities for sustainable service delivery in project communities. <sup>61</sup> Members of the women-led O&M groups", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000027", "page": 14, "chunk": 1, "title": "Concept Project Information Document (PID) - Enhancing Community Resilience and Local Governance Project Phase II - P177093", "pdf_url": "http://documents.worldbank.org/curated/en/538641629099997119/pdf/Concept-Project-Information-Document-PID-Enhancing-Community-Resilience-and-Local-Governance-Project-Phase-II-P177093.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "skilled, refugees are faced with an inability to accrue capital to start or expand small businesses, which\nimpedes their livelihoods creation. Those who pursue economic activities they are trained in often face\nchallenges in finding markets for their goods or services within Kampala. Addressing these barriers in\naddition to adapting livelihoods trainings based on the results of a comprehensive market survey of\nKampala is vital for achieving successful refugee livelihoods in the city.\n\n\nAlthough refugees in Uganda are granted the right to work, this does not mean that access to\nlivelihood services or even work itself is accessible. This research has found that the ability for\nrefugees to create livelihoods in Kampala is increasingly constrained by the laws of KCCA, which\nrestricts work in the informal sector for both refugees and nationals. Some of the barriers refugees\nface are particular to their status as non-nationals, while others are relevant for all people in similar\n(impoverished) financial situations. UNHCR documents state the objective of ensuring refugees can\naccess work and livelihood services in the same manner as local populations; the results of this study\nshow the necessity of increased service provision, particularly regarding access to financial\ninstitutions, in order to reach this objective. Uganda’s new ReHoPE strategy focuses specifically on\nintegrating refugees into public services and programmes, and thus provides a potential programme to\nimplement UNHCR rhetoric into practice.\n\nThe role that ReHoPE can play in development and livelihoods support, including through enabling\nrefugee access to national MFIs, is apparent in an InterAid officer’s statement on the importance of\nReHoPE in the on-the-ground work of the organisation:\n\n\n‘The ReHoPE strategy is guiding us now, whatever we do, we reflect on it. We are now trained to shift\nfrom dependency to development. To do this, we see how closely we can work with local governments\nto make sure refugees are integrated into government programs. Eventually international emergency\norganisations will have little role, instead development organisations will do most work…", "output": {"entities": {"named_data": [], "descriptive_data": ["comprehensive market survey of\nKampala"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001074", "page": 28, "chunk": 0, "title": "New issues in Refugee Research - Research Paper No. 277 - Refugees asked to fish for themselves: The Role of Livelihoods Trainings for Kampala’s Urban Refugees", "pdf_url": "https://reliefweb.int/attachments/a23e063d-0c7b-3098-ab0f-bf456a00320f/56bd9ed89.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "comprehensive market survey of\nKampala", "label": "DESCRIPTIVE_DATA", "score": 0.9310024976730347, "start": 383, "end": 421, "probe_score": 0.6357, "gold": "DATA_MENTION", "gold_tier": "human-final"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " hosting an additional 35 percent of Syrian\nrefugees. Moreover, UN agencies and international donor organizations contracted the majority\nof existing PHCCs for the delivery of care to Syrian refugees. As a result, the gap between\nincreased demand and existing supply is deepening the vulnerability of the Lebanese in these\nareas as competition for health services and resources continues.\n\n\n20. **The unprecedented rise in demand for PHC services associated with the limited**\n**supply is crowding Lebanese out of hospital services and is compromising access to**\n**affordable healthcare.** Comparing the MoPH utilization data <sup>11</sup> for the first six months in 2013\nwith that in 2014, shows that while the number of Syrian patients attending PHCCs increased by\n7.1 percent, the number of Lebanese patients attending the same PHCCs decreased by 16.6\npercent. This is also the case with the number of visits to PHCCs, where the numbers increased\nby 33 percent for Syrians and decreased by 28.9 percent for Lebanese. There is an undocumented\nevidence to suggest that Lebanese are dissatisfied with the long waiting time and lack of\nfinancial support for PHC visits, similar to Syrian refugees. This situation is significantly\ncompromising access of Lebanese citizens to healthcare, putting pressure on the delivery and\nquality of services. In the medium- to long-term, the impact of delayed healthcare for Lebanese,\nparticularly for the vulnerable, could result in increased costs and overall levels of morbidity in\nthe future.\n\n10 International Medical Corps Lebanon, Syrian Refugee Response, January-June, 2013.\n11 Ministry of Public Health, Primary Care Department, September 2014.\n\n\n14", "output": {"entities": {"named_data": ["MoPH utilization data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000020", "page": 13, "chunk": 1, "title": "Lebanon - Emergency Primary Healthcare Restoration Project", "pdf_url": "http://documents1.worldbank.org/curated/en/185271468266958778/pdf/PAD12050PAD0P15264600PUBLIC00Box391428B.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "MoPH utilization data", "label": "NAMED_DATA", "score": 0.7531685829162598, "start": 605, "end": 626, "probe_score": 0.853, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009595", "page": 62, "chunk": 2, "title": "Kenya - Rural Water Supply Project", "pdf_url": "https://documents.worldbank.org/curated/en/211911468089367114/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Berdzuli N, Chua-Oon C, Badran E, Al-Sheyab N, et al. Level, causes and risk factors\nof neonatal mortality, in jordan: results of a national prospective study. Matern Child Health J. (2016) 20:1061–\n71.\n5 [Al-Sheyab NA, Khader YS, Shattnawi KK, Alyahya MS, Batieha A. Rate, Risk Factors, and Causes of](https://pubmed.ncbi.nlm.nih.gov/33194998/)\n[Neonatal Deaths in Jordan: Analysis of Data From Jordan Stillbirth and Neonatal Surveillance System](https://pubmed.ncbi.nlm.nih.gov/33194998/)\n\n[(JSANDS). Front Public Health. 2020 Oct 30;8:595379.](https://pubmed.ncbi.nlm.nih.gov/33194998/)\n\n\n6 Al-Sheyab NA, Khader YS, Shattnawi KK, Alyahya MS, Batieha A. Rate, Risk Factors,\nand Causes of Neonatal Deaths in Jordan: Analysis of Data From Jordan Stillbirth and Neonatal Surveillance\n<u>System (JSANDS). Front Public Health. 2020 Oct 30;8:595379.</u>\n\n\n3", "output": {"entities": {"named_data": ["Jordan Stillbirth and Neonatal Surveillance System"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000596", "page": 2, "chunk": 2, "title": "Strengthening Neonatal Mortality and Stillbirths Audits in Zaatari and Azraq Refugee Camps in Jordan (1 January 2023 - 31 December 2023)", "pdf_url": "https://reliefweb.int/attachments/5807b139-5968-4dd1-aec5-e8a38ee2ca49/Death%20Auditing%20Year%202023.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Jordan Stillbirth and Neonatal Surveillance System", "label": "NAMED_DATA", "score": 0.6322258710861206, "start": 397, "end": 447, "probe_score": 0.5025, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". On achievement of DLI **3,** the Commission is expected to\n\nimplement teacher robust management systems that support achievement of equitable learning\n\nopportunities in public learning institutions. The Commission has achieved this DLI **by** recruiting\n\nand deploying a total of **5,000** teachers to primary schools with the highest teacher shortage.\n\n\nUnder the Investment Project Financing(IPF) and Additional Financing(AF) components, the\n\nCommission was allocated funds to; monitor the achievement of the DLI, procurement of **ICT**\n\nequipment, procurement of teacher robust management system, review of teacher recruitment,\n\nmanagement and development process and development of an action plan to address any gender\n\ngaps. procure Technical Assistance to Analyze TPAD data and to procure Technical Assistance to\n\nmeasure teacher proficiency at midterm and endline of the Program.\n\n\nThe challenge faced in implementation of IPF and **AF** activities was non completion of all the\n\nprocurement activities due to non-responsiveness of tenders. These activities have been rolled over\n\nto the financial year **2025/26.**\n\n\nxi", "output": {"entities": {"named_data": ["TPAD data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000408", "page": 13, "chunk": 1, "title": "Kenya - EASTERN AND SOUTHERN AFRICA - P176867 - Primary Education Equity in Learning Program - Audited Financial Statement", "pdf_url": "https://documents.worldbank.org/curated/en/099013026045035027/pdf/P176867-b93402b4-3eb6-4b08-b8bc-ffbbc8a35895.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "TPAD data", "label": "NAMED_DATA", "score": 0.8597297668457031, "start": 772, "end": 781, "probe_score": 0.2109, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", the MSNA team have found the following response gaps:\n\n\n  - Approximately two-thirds of the 225 vulnerable cazas reportedly do not have WASH programmes. The\nnumber of vulnerable cazas continues to increase as more Syrian refugees come into the country.\n\n  - Hygiene programmes.\n\n  - Water and sanitation infrastructure at the community and municipal levels\n\n  - Longer-term infrastructure projects\n\n\nThe participants of the MSNA SWG workshop identified the following response gaps:\n\n\n  - Rapid response – the time it takes between the start and completion of an intervention\n\n  - Preparedness for an outbreak\n\n  - The strategy – partners do not have one focus geography, but are spread across the area\n\n  - Coordination of an exit strategy (with development projects)\n\n  - Coverage of all areas and all services\n\n  - Collective shelters\n\n  - Extra support for the municipalities\n\n  - Sewage and wastewater treatment\n\n\n**1.5 Future Developments with Possible Impacts on the Sector**\n\n\nBased on the data available, MSNA team have found the following future developments may have an impact\non the sector:\n\n\n  - With dwindling economic resources, access to municipal water is decreasing and alternatives such as\nwater trucking are being used, creating potential over-pumping of wells, which could lead to well\n\n6", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data available"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000826", "page": 5, "chunk": 1, "title": "MSNA sector chapters - WASH", "pdf_url": "https://reliefweb.int/attachments/79c2ffd5-a9fe-3795-ae41-c38096a16c71/WASH%20CHAPTER%20-FINAL%20April%2022.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "data available", "label": "VAGUE_DATA", "score": 0.6088932752609253, "start": 999, "end": 1013, "probe_score": 0.0001, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2 721 Şırnak 17 950 651 560\n<u>Kırıkkale</u> <u>17</u> <u>346</u> <u>837</u> <u>720</u>\n\n(1) Emigrants per 1,000 inhabitants in 1990; (2) Child woman ratio, per 1,00 in 2000\n(3) Education index x 1000 in 2000; (4) Human development index x 1000 in 2000\n\n\n37", "output": {"entities": {"named_data": [], "descriptive_data": ["Education index", "Human development index"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003263", "page": 36, "chunk": 2, "title": "wps4050", "pdf_url": "https://local/prwp/wps4050.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Education index", "label": "DESCRIPTIVE_DATA", "score": 0.519647479057312, "start": 178, "end": 193, "probe_score": 0.7321, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Human development index", "label": "DESCRIPTIVE_DATA", "score": 0.6086586713790894, "start": 214, "end": 237, "probe_score": 0.7679, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|Percentage of refugees pre-registered on<br>the national platform who are fully<br>vaccinated (total and disaggregated by<br>sex)|The indicator will track the<br>number of eligible Syrian<br>and Palestinian individuals<br>in areas with a high<br>concentration of displaced<br>population (in coordination<br>with UNCHR), as many are<br>not issued a national ID<br>and are not reported as<br>refugees in the COVID-19<br>vaccine registration<br>platform. This indicator will|6 months<br>|MOPH<br>reports,<br>National<br>Vaccine digital<br>platform<br>(IMPACT)<br>|<br>Administrative data<br>|<br>PMU/MOPH<br>|\n\n\nPage 43 of 54", "output": {"entities": {"named_data": [], "descriptive_data": ["Administrative data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000000", "page": 47, "chunk": 1, "title": "Lebanon - Strengthening Lebanon's COVID-19 Response under the COVID-19 Strategic Preparedness and Response Program (SPRP)", "pdf_url": "http://documents.worldbank.org/curated/en/099410007282239961/pdf/BOSIB09c1bfedd05c098380dc89cfe988b8.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "Administrative data", "label": "DESCRIPTIVE_DATA", "score": 0.8431527614593506, "start": 657, "end": 676, "probe_score": 0.3856, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " of the 1972 returnees, who were\nseen essentially as foreigners, and even referred to as ’sorciers’ (witches, a\nphenomenon associated with Tanzania). One interviewee suggested that more\npreparatory work should have been done with receiving communities in Makamba,\nwhere fears that the 1972 returnee would try to take their land and homes were\ncirculating.\n\n\n142. One group of 1972 returnees reported that on their first night, stones were\nthrown at the temporary shelter were they were sleeping. There were also reports\nthat the limited return package for the 1972 group, and in particular the absence of\nfood, created something of a burden on the local community. Nonetheless, these\ntensions should not be overstated and in general it appeared that relations between\nthe 1972 returnees and other community members were also relatively good.\n\n\n**Impact on gender relations**\n\n\n143. The April 2007 concept note stated that ‘to the extent possible’ women\nwould be ‘designated as administrators of the cash grant’. However, the default\nmodel eventually implemented was that the account would be placed in the name of\nthe head of household, although a spouse or adult child could also withdraw the\ncash at the COOPEC office provided that he/she was in possession of the account\npassbook. In Ruyigi it was reported that there was a system by which agreement\ncould be reached at the transit centre that the account would be opened in the name\nof a wife or adult child, but this appeared to be used primarily in cases were the head\nof household was disabled or otherwise incapacitated. Female heads of household\n\n\n41 ISTEEBU report, April 2009 cited in _Burundi’s Q1 average inflation rises to 19.8%_ Reuters, 30 April 2009.\n\n\n32", "output": {"entities": {"named_data": ["ISTEEBU report"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001142", "page": 31, "chunk": 1, "title": "Money matters: An evaluation of the use of cash grants in UNHCR's voluntary repatriation and reintegration programme in Burundi", "pdf_url": "https://reliefweb.int/attachments/ad0c70d6-4f4e-351f-9075-0ab37ed9f47f/09B3C2586A4F0ADF492575FA00105DE2-Full_Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "val", "spans": [{"text": "ISTEEBU report", "label": "NAMED_DATA", "score": 0.612520694732666, "start": 1610, "end": 1624, "probe_score": 0.2645, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "||\n|**Cankuzo**|3. Gisagara|83,790|||\n|**Cankuzo**|4. Cendajuru|47,445|||\n|**Muyinga**|5. Gasorwe|119,861|Kinama|7,805|\n|**Muyinga**|6. Buhinyuza|79,639|||\n|**Muyinga**|7. Gashoho|96,632|||\n|**Muyinga**|8. Butihinda|141,629|||\n|**Muyinga**|9. Muyinga|202,054|||\n|**Muyinga**|10. Mwakiro|63,550|||\n|**Muyinga**|11. Giteranyi|221,061|||\n|**Ngozi**|12. Kiremba|136,434|Musasa|8,758|\n|**Ngozi**|13. Nyamurenza|83,615|||\n\n\n35 The actual target beneficiary population in the results framework will be based on an estimated number of subprojects to be\ncompleted and collines to be covered by the project.\n\n\nPage 20 of 86", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000110", "page": 25, "chunk": 1, "title": "Burundi - Integrated Community Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/644221583204472551/pdf/Burundi-Integrated-Community-Development-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "val", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**_Leased Assets_** _as specified under paragraph 5.10_ of the Procurement\nRegulations: Leasing may be used for those contracts identified in the\nProcurement Plan tables. _“Not Applicable”_\n\n\n**_Procurement of Second Hand Goods_** _as specified under paragraph 5.11_ of\nthe Procurement Regulations – is allowed for those contracts identified in the\nProcurement Plan tables _“Not Applicable”_\n\n\n**_Domestic preference_** _as specified under paragraph 5.51_ of the Procurement\nRegulations **_(Goods and Works)_** . _Specify for each_\n\n\nGoods: is applicable for those contracts identified in the Procurement Plan\ntables;\n\n\nWorks: is applicable for those contracts identified in the Procurement Plan\ntables\n\n\n**Other Relevant Procurement Information.**\n\n\n_Procurement of Vehicles and Motor Cycles will be carried out by UNOPS_\n_considering the urgency that the vehicles and motor cycles are critically_\n_needed for project start up and the need to use UNOPS’s expertise on having_\n_long-term relationships with suppliers._", "output": {"entities": {"named_data": [], "descriptive_data": ["Procurement Plan tables"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:006441", "page": 1, "chunk": 0, "title": "Ethiopia - Eastern and Southern Africa- P159382- Livestock and Fisheries Sector Development Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099315005232238539/pdf/P159382033695b0750839e08e96de1b6e07.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Procurement Plan tables", "label": "DESCRIPTIVE_DATA", "score": 0.5558813810348511, "start": 146, "end": 169, "probe_score": 0.0009, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " than that for male beneficiaries. Women will be targeted for inclusion in planning\ncommittees, where relevant, and they will be incentivized to participate in and use all projectfunded services and activities.\n\n116. **The project will also support women’s employment in the energy sector.** Employment\nopportunities will be created for female technicians and engineers in O&M activities. Limited sexdisaggregated data are available, but <mark>global data indicate that women are underrepresented in both</mark>\n<mark>technical and nontechnical roles and that the sector as a whole is male dominated. Field</mark> evidence further\nreports a near-complete lack of women in similar operations in Chad, which explains the baseline to be\nassessed as zero. The key barriers for accessing these jobs were assessed to stem primarily from lack of\nskills/education and social norms/lack of targeted recruitment. Therefore, private O&M companies will\nbe mandated to train and employ female professionals to boost women’s opportunities for joining the\nsector and help them overcome the key barrier of school-to-work transition and access to technical skills\nand men-dominated jobs. They will also be expected to accommodate women through a more equitable\nemployment policy, which is currently lacking in most operations and limits employment possibilities.\n\n117. **M&E.** Several indicators will monitor project progress with respect to gender, including\n(a) A percentage of female-headed households provided with electricity access under the project.\n\n\n\nThis indicator will track progress toward raising the share of electrified households that are female\nheaded to 15 percent. This percentage is based on the level of their prevalence recently measured\nby the survey on the ability and willingness of households to pay for electricity, provided in annex\n6, updating earlier data. This indicator will be applied to Component 1 and Subcomponent 2.3;\n(b) A percentage of women technicians employed in O&M under Component 1 and Subcomponents\n\n\n\n2", "output": {"entities": {"named_data": [], "descriptive_data": ["sexdisaggregated data"], "vague_data": ["global data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 48, "chunk": 1, "title": "Chad - Energy Access Scale Up Project", "pdf_url": "http://documents.worldbank.org/curated/en/860701648216750651/pdf/Chad-Energy-Access-Scale-Up-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "sexdisaggregated data", "label": "DESCRIPTIVE_DATA", "score": 0.7131137251853943, "start": 397, "end": 418, "probe_score": 0.1156, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "global data", "label": "VAGUE_DATA", "score": 0.8299614787101746, "start": 444, "end": 455, "probe_score": 0.2257, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "##### **Introduction**\n\nIt is widely understood that host populations are\naffected by a sudden and large influx of refugees\n(World Bank, 2016). Precisely how they are\naffected, however, remains under-researched and\noften ill-communicated. Several quantitative\nstudies have been carried out on the impact of\nforced displacement on host populations, mainly\nin Colombia, the Great Lakes and increasingly in\nthe Middle East and Europe. However, until\nrecently, this area of study has largely been\nneglected by economists in particular (Ruiz et al,\n2013 and Oxford Refugees Center, 2011). Only a\nfew studies rely on empirical data, and they are\ntypically focused on short-term impacts\n(Kreibaum, 2016 and Ruiz et al, 2013).\n\n\nTanzania, however, is an exception in this\nregard, partly because of its location (surrounded\nby countries periodically affected by conflict) and\nits decades-long history in welcoming and\nassisting large numbers of refugees. Unlike\nseveral other hosting countries, there exists a\nconsiderable body of qualitative, mixed-methods\nand empirical literature, mostly analyzing the\nimpact of refugee inflows from Burundi (1993)\nand Rwanda (1994) on host districts in\nnorthwestern Tanzania. This literature covers a\nrange of impacts including on the labor market,\nenvironment, health and other areas.\n\n\nThe formulation of the forthcoming Global\nCompact on Refugees and implementation of a\nComprehensive Refugee Response Framework\n(CRRF) <sup>1</sup> in countries such as Djibouti, Ethiopia,\nKenya, Rwanda, Somalia and Uganda all stress\nthe inclusion of host communities in efforts to\nextend refugee protection and to bring\n\n\n1 CRRF is a multi-stakeholder approach that aims at\nlinking humanitarian and development efforts during\nthe early stages of an emergency while strengthening\n\n\n\ndevelopment responses to situations of forced\ndisplacement. Therefore, an imperative exists to\nreview what is known about previous\nexperiences of refugee arrival and response and\nthe impacts on host communities. Given the\ndepth and", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["empirical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000309", "page": 7, "chunk": 0, "title": "The Impact of Refugee Presence on Host Populations in Tanzania: A Desk Review, April 2018", "pdf_url": "https://reliefweb.int/attachments/24aad67c-5978-3c21-9bc3-fd41384da2ff/64413.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "empirical data", "label": "VAGUE_DATA", "score": 0.7832895517349243, "start": 611, "end": 625, "probe_score": 0.8232, "gold": "NON_MENTION", "gold_tier": "human-final"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "decentralized \"partnership\" approach to governance that involves line ministnes, NGOs, CBOs, <sup>and</sup> <sup>civil</sup>\nsociety. NCRRR/NaCSA has been supported by the African Development Bank, UNDP, DflD, and IDA.\nIt has provided assistance for more than 500,000 displaced persons, shelter rehabilitation, vocational\ntraining, trauma healing, and micro-finance programs. It has financed 275 community-based sub-projects\nin the areas of health, education, water and sanitation, agriculture and capacity building. These <sup>tasks</sup>\nhave been carried out with considerable support from the 260 NGOs registered in Sierra Leone, of which\n68 are international. These NGOs have been instrumental in ensuring service delivery to remote <sup>areas</sup>\nwhere public services were absent.\n\n\n**3.** **Sector** **issues** **to be** **addressed** **by the** **project and strategic choices:**\n\n**Poverty in a Post-Conflict** **Environment.** Section 2 above outlines the principal characteristics\nof poverty in Sierra Leone and the condition of the country at the close of the civil war. <sup>Access</sup> <sup>of the</sup>\npoor majority to food, shelter, employment opportunities and social services are among the <sup>principal</sup>\n\n\n\nconstraints to post-conflict reconstruction, economic recovery and poverty reduction. District recovery\nassessments reveal that over 340,000 houses were destroyed dunng the war and only 10,000 have been\nrebuilt so far. Government is particularly concerned with the shelter needs of returnees, IDPs <sup>and</sup>\n\n\n\ngovernment employees such as health workers and", "output": {"entities": {"named_data": [], "descriptive_data": ["District recovery\nassessments"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000165", "page": 9, "chunk": 0, "title": "Bosnia and Herzegovina - Community Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/941761468768008234/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "District recovery\nassessments", "label": "DESCRIPTIVE_DATA", "score": 0.861286461353302, "start": 1323, "end": 1352, "probe_score": 0.8419, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".00|07-Feb-2022|35.00|30-Jun-2024|40.00|Jul/2024|\n|1.4. Change in Productivity of<br>small-scale producers -<br>Aquaculture (Cage) Kg/Cubic<br>Meters (Number)|Comments on<br>achieving targets|Comments on<br>achieving targets|This PDO indicator data has been updated during MTR and will be updated during endline<br>survey|This PDO indicator data has been updated during MTR and will be updated during endline<br>survey|This PDO indicator data has been updated during MTR and will be updated during endline<br>survey|This PDO indicator data has been updated during MTR and will be updated during endline<br>survey|This PDO indicator data has been updated during MTR and will be updated during endline<br>survey|This PDO indicator data has been updated during MTR and will be updated during endline<br>survey|\n|2.2. Increase in sales of|63.00|May/2018|63.00|30-May-2018|63.00|30-Jun-2024|90.00|Jul/2024|\n\n\nPage 3 of 11", "output": {"entities": {"named_data": [], "descriptive_data": ["PDO indicator data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:004264", "page": 2, "chunk": 3, "title": "Disclosable Version of the ISR - Livestock and Fisheries Sector Development Project - P159382 - Sequence No : 15", "pdf_url": "https://documents.worldbank.org/curated/en/099090524092617949/pdf/P159382-22bfddfe-5e9c-4596-bdb8-8bbd6db00cf0.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "PDO indicator data", "label": "DESCRIPTIVE_DATA", "score": 0.608920156955719, "start": 230, "end": 248, "probe_score": 0.4105, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " enough money to\nmeet their needs, the refugees were nearly\nequally split (around 0.5% more reported\nno difficulties), with an additional 8% not\nknowing or refusing to answer. According to\nthe National Bank of Poland survey carried\nout in November 2022, 28% of refugees\nsaid they spend less than half of their\nincome on daily expenses, most spend\nbetween 50% and 80%, and 19% spend 80100% of their income.\n\n\n###### Currently between 225 and 350 thousand of refugees from Ukraine are working in Poland. The lower bound is the number from social security, while the higher bound is the product of employment rate from the surveys and working age population with PESEL numbers.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Box 1.** Inflow of savings from Ukraine\n\n\n\n**Chart 13.** Income structure of Ukrainian refugee households\n\n\n**5%** **1%**\n\n\n\nWork (regular-, temporary-,and self-employment in Poland,\nremote employment in Ukraine\n\n\nRemittances from friends/relatives\n\n\nPolish government benefits (Family 500+, cash benefits,\ndisability grants)\n\n\nUkrainian government benefits (pensions, disability grants,\nparental benefits)\n\n\nOther (humanitarian organizations, other sources)\n\n\n\n**Source:** Deloitte elaboration based on the MSNA Poland 2023. The work category includes regular employment, temporary work, self-employment\nand remote work in Ukraine.\n\n\n31 <u>[Cudzoziemcy w polskim systemie ubezpieczeń społecznych (zus.pl)](https://www.zus.pl/documents/10182/2322024/Cudzoziemcy+w+polskim+systemie+ubezpiecze%C5%84+spo%C5%82ecznych_2022.pdf/)</", "output": {"entities": {"named_data": ["National Bank of Poland survey", "MSNA Poland 2023"], "descriptive_data": ["surveys and working age population with PESEL numbers"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 14, "chunk": 2, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "National Bank of Poland survey", "label": "NAMED_DATA", "score": 0.8720319271087646, "start": 193, "end": 223, "probe_score": 0.9996, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "surveys and working age population with PESEL numbers", "label": "DESCRIPTIVE_DATA", "score": 0.5339330434799194, "start": 620, "end": 673, "probe_score": 0.9248, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "MSNA Poland 2023", "label": "NAMED_DATA", "score": 0.8585284948348999, "start": 1263, "end": 1279, "probe_score": 0.9021, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "9\n\n\nStratification by plot size is essential in isolating the population of interest. Because the current literature\n\n\nquestions the accuracy of GPS at smaller areas (Keita & Carfagna, 2009, and Schoning et al., 2005, have\n\n\nsuggested that GPS measurements on plots less than 0.5 hectares are significantly different than CR\n\n\nassessments), collecting measurement data on plots in each strata is necessary if we are to analyze the\n\n\naccuracy of the GPS and farmer estimates at various plot sizes and, particularly, address the issue of\n\n\naccuracy on small areas. More than 80 percent of plots measured in the Wave 1 GHS-Panel were smaller\n\n\nthan 1 hectare. Although compass and rope measurement is more time intensive on larger areas, we did not\n\n\nrestrict the sample by employing an upper limit on area. Rather, we consider it critical to measure plots of\n\n\nall sizes in order to enable the analysis of all plot areas. In Nigeria in particular, the farmer-reported areas\n\n\nand GPS areas have been wildly divergent at all plot sizes, not only the smaller plots on which GPS accuracy\n\n\nis called into question. In measuring plots of all sizes, therefore, we aim to gain an understanding of the\n\n\ndiscrepancy between the two measures at all plot sizes.\n\n\nTable 3 presents sample averages for the explanatory variables used in the analysis including the validation\n\n\nsample and the wave 2 GHS-Panel sample. In the first three columns, we compare the full wave 2 sample\n\n\nwith the validation sample with the difference between the two shown in the third column. There are many\n\n\nsignificant differences between the validation and wave 2 samples, suggesting the validation sample is not\n\n\nrepresentative of the national GHS-Panel survey. Nigeria is a large and diverse country so this is not\n\n\nsurprising given the relatively limited scope of the validation sample. In the middle columns, we limit the\n\n\nwave 2 sample to zones covered by the validation sample (North Central and South West). Comparing the\n\n\nreduced wave 2 sample to the validation sample, there are", "output": {"entities": {"named_data": ["Wave 1 GHS-Panel", "GHS-Panel survey"], "descriptive_data": [], "vague_data": ["measurement data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001776", "page": 10, "chunk": 0, "title": "land measurement bias and its empirical implications evidence from a validation exercise", "pdf_url": "https://local/prwp/land-measurement-bias-and-its-empirical-implications-evidence-from-a-validation-exercise.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "measurement data", "label": "VAGUE_DATA", "score": 0.645893931388855, "start": 352, "end": 368, "probe_score": 0.523, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Wave 1 GHS-Panel", "label": "NAMED_DATA", "score": 0.8398922085762024, "start": 609, "end": 625, "probe_score": 0.9611, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "GHS-Panel survey", "label": "NAMED_DATA", "score": 0.744691014289856, "start": 1715, "end": 1731, "probe_score": 0.9522, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " infrastructure**\n**linking rural and urban areas will be necessary if the growth strategy is to be inclusive.** First of all, few firms\ncomplain about transport as a major constraint to growth in the ICA data – no matter the size of the firm. Keep in\nmind though that the firms included in the ICA survey were located in Lomé. Furthermore, Figure 33 shows to\nwhat extent Togo deviates from the expected level of trade‐related infrastructure according to the World Bank\n\n\n34", "output": {"entities": {"named_data": ["ICA survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004695", "page": 35, "chunk": 2, "title": "wps5509", "pdf_url": "https://local/prwp/wps5509.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "ICA survey", "label": "NAMED_DATA", "score": 0.6458054184913635, "start": 295, "end": 305, "probe_score": 0.9597, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " also lowered women’s reporting of exclusive land ownership but were positively\nassociated with men’s exclusive ownership. This is similar to findings in the literature on how\nmen’s and women’s reported asset ownership varies by experience to negative shocks (see\nQuisumbing et. al (2018) who use data from Bangladesh and Uganda). <sup>29</sup> One reason may be\n\n\n29 Their study also looks at how reporting across different classes of assets (land, livestock, productive equipment,\njewelry) varies by different types of shocks — illness, natural disasters, etc.\n\n\n22", "output": {"entities": {"named_data": [], "descriptive_data": ["data from Bangladesh and Uganda"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000484", "page": 23, "chunk": 1, "title": "getting the gender disaggregated lay of the land impact of survey respondent selection on measuring land ownership and rights", "pdf_url": "https://local/prwp/getting-the-gender-disaggregated-lay-of-the-land-impact-of-survey-respondent-selection-on-measuring-land-ownership-and-rights.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data from Bangladesh and Uganda", "label": "DESCRIPTIVE_DATA", "score": 0.7136132717132568, "start": 297, "end": 328, "probe_score": 0.9259, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\nto higher transportation costs; and (c) needs are greater in more vulnerable, conflict-affected areas. The\nproposed allocation allows the project to support approximately 11 counties that have vulnerability scores\nhigher than 50 (out of 100). However, the number and the list of target counties will change as the\nvulnerability index and its underlying data sets will be updated. There will be two rounds of allocation per\ncounty to maximize communities’ learning-by-doing. Counties will need to meet a set of basic\nperformance indicators to be eligible for the second allocation. These include (a) participation rate of\nwomen, youths, IDPs, and returnees; (b) timely implementation of the subprojects; (c) formation of O&M\ncommittees and development of sustainable O&M measures, among others. All _payams_ and _bomas_ within\nthe target counties will be eligible for subproject budget allocation. Allocations to the _payam_ level will\nfollow the Government’s fiscal transfer formula of 60 percent equal allocation and 40 percent based on\npopulation (utilizing IOM’s DTM projections) <sup>80</sup> [^80: Population figures for urban areas would be calculated based on a headcount or by complementing 2008 census with other data sources (for\nexample, DTM).] whereas all _bomas_ within target _payams_ will receive equal\namount of funding as there are no population data available. Each _payam_ within the same county as well\nas all _bomas_ within the same _payam_ will receive equal amounts as there are no reliable data on their\npopulation sizes. About 65 percent of county allocations will be made available in round one, and more\ncomplex projects will be implemented first to ensure timely project implementation. Should any counties\nbe deemed unfeasible, they will be replaced by ‘replacement counties’ on the long list. In some cases,\ncertain _payams_ within selected counties will be inaccessible or difficult to", "output": {"entities": {"named_data": ["DTM projections"], "descriptive_data": [], "vague_data": ["population data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 76, "chunk": 0, "title": "South Sudan - Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/824121596765983121/pdf/South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "DTM projections", "label": "NAMED_DATA", "score": 0.5909454822540283, "start": 1169, "end": 1184, "probe_score": 0.9504, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "population data", "label": "VAGUE_DATA", "score": 0.6724582314491272, "start": 1455, "end": 1470, "probe_score": 0.6185, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " particularly among the urban population. This will be done\nby providing grants to Gozars and Business Gozars, which will invest the grants in priority market enabling\ninfrastructure. IDLG will establish (i) Gozar Assemblies (GAs) and (ii) Business Gozars Assemblies (BGAs) in the\ncities. A Gozar will be formed from four to five CDCs electing one representative each who will be part of the GA.\nA Business Gozar is a parallel body which will consist of an estimated range of 100 to 300 businesses <sup>19</sup> [^19: The term “businesses”’ refers to small and medium size enterprises (SMEs) as well as microenterprises. These could be, for example,\nshops in formal markets, small semi‐formal shops, vendors, workshops or small factories, etc.], who will\nalso elect their representatives into the BGA. Before a BGA is established, IDLG, in consultation with the\nmunicipality, will conduct a Gozar and Business Gozar Assessment (G/BG‐A) to identify opportunities where EZ‐\nKar investments can have a high economic impact. The G/BG Assessment will be conducted in all IDLG project\ncities by a firm recruited and managed by IDLG. This assessment will include work to identify locations in the city\nwith a high density of businesses where potential Business Gozars could be established, before the identification\nand recommendations for market‐enabling infrastructure takes place at the Gozar or Business Gozar level.\nSubproject proposals identified for implementation by Business Gozars shall be aligned with national public\n\n\n11 Facilitating Partners means international and/or national non‐governmental organizations and agencies that will assist the CDCs, GAs,\nand BGAs with the preparation and implementation of subprojects.\n12 The coverage is expected to be close to 90 percent of the city if using the Afghanistan’s National Statistics and Information Authority\n(NSIA, 2018) urban population figures, which shows that there are 1,210 communities in these urban areas. However, data from UN‐\nHabitat’s ‘", "output": {"entities": {"named_data": [], "descriptive_data": ["urban population figures"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000123", "page": 21, "chunk": 1, "title": "Afghanistan - Eshteghal Zaiee - Karmondena (EZ-Kar) Project", "pdf_url": "http://documents1.worldbank.org/curated/en/714251547070785057/pdf/Afghanistan-Eshteghal-Zaiee-Karmondena-EZ-Kar-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "urban population figures", "label": "DESCRIPTIVE_DATA", "score": 0.8205649256706238, "start": 1878, "end": 1902, "probe_score": 0.5378, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\noffices; (iii) pre-existing Beneficiary Development Program activities; and (iv) existence of available\nprivate, NGO, CSO and public training providers. In addition, some districts of these governorates have\nsignificant numbers of beneficiaries in groups E&F. Selecting these governorates would provide an\nopportunity to pilot the “phasing out strategy” should the government so choose.\n\n\n149. _Beneficiary Profiles in Pilot Governorates._ The PMT was applied to survey data gathered from\nexisting beneficiaries as well as new applicants. Based on the PMT, the beneficiary categories in the pilot\nareas are shown in **Table** **1.** Groups E&F make up 38 percent of the total, with the largest percentage (52\npercent) in Aden. Group A coverage is very small (approximately 1 percent) with Group B coverage for\nthe pilot area about 13 percent, with only 5 percent coverage of this group in Aden. Groups C&D make\nup the largest percentage (48 percent) of beneficiaries in the pilot area, comprising approximately 50\npercent of beneficiaries in both Hodeida (49 percent) and Mukalla (51 percent). The percentage of\nbeneficiaries in each group will be assessed over the duration of the pilot project to determine the impact\nof the SWF targeting policy implementation as well as the rolling out of the public information campaign.\n\n\n\n**Governorate**\n\n\n**Aden**\n\n\n**Hodeida**\n\n\n\n**cases** **total** **total** **total** **total** **total** **total**\n32908 43 1502 3646 10404 9443 7870\n\n’ (negligible) (5%) (11%) (32%) (28%) (24%)\n45605 605 7798 10502 11953 11476 327 1\n\n\n\n**Total** #", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000080", "page": 48, "chunk": 1, "title": "Yemen, Republic of - Social Welfare Fund Institutional Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/495501468170077604/pdf/533550PAD0P117101Official0Use0Only1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.6504313349723816, "start": 464, "end": 475, "probe_score": 0.7517, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">accompanying<br>measures and<br>mechanisms<br>• <br>Implementation of<br>procurement plan,<br>including<br>procurement of<br>goods and works<br>• <br>Preparation of<br>technical<br>specifications for<br>works contracts<br>• <br>Institutional<br>assessment and<br>capacity building of<br>CNARR|• <br>Social<br>Protection<br>• <br>Social<br>development<br>• <br>Procurement<br>and FM<br>• <br>Social and<br>environmental<br>safeguards<br>• <br>Education<br>• <br>Health<br>• <br>WASH<br>• <br>Agriculture<br>• <br>Rural<br>development<br>planning|BB: US$300,000|CFS and NGOs<br>carry out<br>consultations;<br>Communities, line<br>ministries and<br>NGOs with<br>support of<br>UNHCR to<br>identify priority<br>investments;<br>CFS with external<br>support to carry<br>out targeting of<br>beneficiaries of<br>cash transfers and<br>of productive<br>measures;<br>UNHCR support<br>to CNARR|\n|**12-48 months**|• <br>Cash transfers and<br>accompanying<br>measures<br>• <br>Productive measures|• <br>Social<br>Protection<br>• <br>Social<br", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000112", "page": 79, "chunk": 1, "title": "Chad - Refugees and Host Communities Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/658761536982256019/pdf/PAD2809-PAD-PUBLIC-disclosed-9-12-2018-IDA-R2018-0286-1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "allocated for irrigation, industrial, and domestic use. Other allocations yield lower gains.\n\nSimilarly, the Mwache Dam is likely to reduce poverty severity by as much as 51.5 percent in\n\nthe combined allocation scenario. At the disaggregated level, the result is analogous to that\n\nof poverty gap.\n\nWe note that poverty gap declines more than poverty incidence and that poverty severity\n\ndeclines more than poverty gap across all scenarios and groups. Furthermore, as reflected by\n\nthe 2005/06 survey data, poverty is a rural phenomenon in Kenya. Coast inhabitants tend to\n\nhave higher risk of being in poverty compared to the national average. The Mwache Dam not\n\nonly has the potential for reducing poverty but it is also likely to be pro-poor. In the com\nbined allocation scenario, the rural regions are able to lift a greater share of their poor house\nholds out of poverty.\n\n\n**Absolute Number of Poor Households Lifted Out of Poverty**\n\n\nThe microsimulation approach not only allows us to capture the impact of the dam on pov\nerty incidence but also reveals the actual number of poor households lifted out of poverty.\n\nTable 4.6 presents the actual number of poor households likely to be lifted out of poverty\n\nacross the four water allocation scenarios. The results show that about 111,171 poor people\n\ncould be lifted out of poverty if water from the Mwache Dam is allocated to irrigation, domes\ntic, and industrial uses. Allocating all of the water to domestic and industrial users lifts only\n\n10,879 people out of poverty in the Coast Region as a whole.\n\n\n**TABLE 4.6. Changes or Reductions in the Number of Poor People in Kenya**\n\n\n\n\n\n\n\n\n\n\n\n\n\nCoast 10,879 10,879 89,398 111,171\n\n\nRural Q1 1,391 1,391 5,617 5,617\n\n\nRural Q2 0 0 22,204 31,330\n\n\nRural Q3 1,044 1,044 32,201 32,201\n\n\nRural Q4", "output": {"entities": {"named_data": [], "descriptive_data": ["2005/06 survey data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018516", "page": 49, "chunk": 0, "title": "Economywide and distributional impacts of water resources development in the coast region of Kenya : implications for water policy and operations", "pdf_url": "https://documents.worldbank.org/curated/en/808491526362236466/pdf/126189-WP-P145559-PUBLIC-14-5-2018-12-9-47-W.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "2005/06 survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8591446876525879, "start": 487, "end": 506, "probe_score": 0.9612, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "projects seemed to meet with a stronger\n\nfavorable response from the poorest people\n\nthan from wealthier groups, which have\n\ngreater capacity to address the health and\n\neducational needs of their families them\nselves.\n\n\nRespondents perceived MBIFCT interven\ntions as an important factor in the increased\n\nreporting of illegal activities and in willing\nness to participate in park fire control. The\n\nimpacts of MBIFCT benefits were particularly\n\nsignificant for the poorest wealth category\n\n(figure 11).\n\n\n\nImpact assessment\n\n\nA shortcoming of the MBIFCT interventions\n\nwas the small scale of initiatives designed to\n\nimprove livelihoods. Furthermore, first-tier\n\ncommunities perceived that they were not\n\ngiven priority in the allocation of MBIFCT\n\nresources and that the process used to select\n\ncommunities or individuals who would\n\nbenefit from income-generation projects\n\nwas not clear. Park staff and former CARE\n\ncommunity extension agents felt that the\n\nimplementation of MBIFCT-supported proj\nects was unnecessarily centralized within\n\nthe Trust Administrative Unit and that local\n\ncommunities were not involved in project\n\n\n\n\n\n\n\n\n\n\n\nSource: ITFC survey, 2004.\nNote: Wealth categories for the communities surveyed were developed for the survey in consultation with\ncommunity advisory groups (see box 3 in the text). Category 1 is the richest. Chi-square, 0.89; df, 3; p <\n0.827.\n\n\n**37**", "output": {"entities": {"named_data": ["ITFC survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008544", "page": 42, "chunk": 0, "title": "The Bwindi Impenetrable National Park and Mgahinga Gorilla National Park Conservation Project, Uganda : Post implementation impact assessment", "pdf_url": "https://documents.worldbank.org/curated/en/140661503489610970/pdf/116771-WP-UG-P002893-GEFUGAND-PUBLIC.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "ITFC survey", "label": "NAMED_DATA", "score": 0.9031813144683838, "start": 1149, "end": 1160, "probe_score": 0.9926, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012945", "page": 62, "chunk": 2, "title": "Uganda - Industrial Rehabilitation Project", "pdf_url": "https://documents.worldbank.org/curated/en/431331468115757745/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nservices which more than doubled the baseline figures. Although not directly financed by the project, a significant\nincrease was also registered in the utilization of free delivery services offered as part of the free maternity program\nas explained above. However, immunization rate remained persistently low. The annual immunization rate\nremained low throughout the project duration, and the end project rate achieved was lower than the original\nbaseline. This is confirmed by the GAVI Country Fact Sheet on Kenya (2018), which shows DPT 3 coverage had been\nslowly sliding downwards since 2012/13 and in 2017 was estimated at 71 percent based on official country\nestimate. The same report noted that only 15 out of 47 counties achieved a DPT3 coverage of 80 percent or more.\nWhile immunization data was meant to be disaggregated for the North East region, the information was not tracked\nand was therefore unavailable.\n\n\n**Figure 3. Achievement of PDO 1 Indicators**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|PDO 1 Indicators|Baseline|Target|Actual|Status|\n|---|---|---|---|---|\n|**Part 1. Delivery of quality essential health and nutrition services**<br>|**Part 1. Delivery of quality essential health and nutrition services**<br>|**Part 1. Delivery of quality essential health and nutrition services**<br>|**Part 1. Delivery of quality essential health and nutrition services**<br>|**Part 1. Delivery of quality essential health and nutrition services**<br>|\n|Severely malnourished children under five<br>receiving treatment recovered ‐ New 2011|0%", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["immunization data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014474", "page": 19, "chunk": 1, "title": "Kenya - Health Sector Support Project", "pdf_url": "https://documents.worldbank.org/curated/en/538061557159183444/pdf/Kenya-Health-Sector-Support-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "immunization data", "label": "VAGUE_DATA", "score": 0.7319741249084473, "start": 783, "end": 800, "probe_score": 0.8607, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "term consequences by demonstrating the\n\neffectiveness of female political leadership and by increasing acceptance of female political\n\nparticipation as measured by their likelihood of re-election.\n\n#### **III. Setting**\n\n###### III.1. Women’s Status in Afghanistan\n\n\nAfghanistan scores very low on the human development index, especially for social indicators\n\npertaining to women. Specifically, women face particularly extreme constraints on economic, social,\n\nand political activity, owing to three decades of civil conflict, as well as to strict tribal codes and\n\ncultural mores that curtail interactions between unmarried men and women. In rural Afghanistan,\n\nwomen are generally barred from activities outside the household so as to preserve their honor\n\n5", "output": {"entities": {"named_data": [], "descriptive_data": ["human development index"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005430", "page": 6, "chunk": 1, "title": "wps6269", "pdf_url": "https://local/prwp/wps6269.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "human development index", "label": "DESCRIPTIVE_DATA", "score": 0.6587318778038025, "start": 302, "end": 325, "probe_score": 0.9886, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " wheat, whose involvement is considered\nessential for the project to achieve its objective. The suppliers of wheat are grain trading companies, which are selected\nusually by importers’ brokers, who shop for the most advantageous offers, in terms of price and logistics, for meeting the\nwheat specifications needed. The suppliers usually store the wheat at different locations around the world, and\nsometimes buy from loaded ships in the middle of the sea and mobilize the shipment to Lebanon based on most\nconvenient logistic arrangements.\n\n\n28. **The project will put in place several mechanisms to address diversion, misuse and other risks related to wheat**\n**imports.** The Framework Agreements between MOET and wheat importers will provide critical mitigation measures (such\nas, in exchange of the project support, obligation to deliver wheat in Lebanon, mill the wheat and distribute the flour\nwithin a certain timeframe, etc.). Public oversight capacities will be strengthened under Component 2 (third-party\nmonitoring, strengthening the role of the consumer protection agency under MOET, and strengthening the GM\nmechanisms). Third party monitoring arrangements and technical audit (to be financed through Component 2), such as\nsuperintendents, Red Cross volunteers through the Lebanese Red Cross/International Federation of Red Cross and Red\nCrescent Societies, will be introduced to enhance verification. In addition, small shipment size due to constraints on port\nhandling capacity and small grain storage capacity in the private sector limit commodity hoarding risks and speculative\nresale.\n\n29. **The project will equally focus on safeguarding access to affordable bread for poor and vulnerable households,**\n**including refugees** . Through the activities described under Component 2, the project will monitor the accessibility of\nvulnerable communities to affordable bread based on the available combined databases maintained by WFP (for poor\nLebanese households identified under the National Poverty Targeting Program, NPTP/Emergency Social Safety Net\nProject (ESSN) and the United Nations High Commissioner for Refugees (UNHCR). If wheat availability", "output": {"entities": {"named_data": [], "descriptive_data": ["combined databases maintained by WFP"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000019", "page": 19, "chunk": 1, "title": "Lebanon - Wheat Supply Emergency Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/408131653327258940/pdf/Lebanon-Wheat-Supply-Emergency-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "combined databases maintained by WFP", "label": "DESCRIPTIVE_DATA", "score": 0.8644784688949585, "start": 1911, "end": 1947, "probe_score": 0.0371, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " continued to meet regularly to ensure regional coherence at the\nstrategic and operational levels. At the country level, inter-agency mechanisms continued to implement planning, response and\nmonitoring activities, with approximately 40 working groups across the five response countries meeting regularly to coordinate\nimplementation of the plan in an efficient and effective manner. Meanwhile, as an accountability measure to donors, reports\nwere published on a regular basis at both the country and regional levels, including quarterly sectoral dashboards and financial\ntracking by sector and component. Countries also continued to implement their M&E frameworks to better articulate progress and\nstrengthen linkages between outputs and overall strategic objectives. This also offered support to Governments in achieving the\nstrategic objectives of national chapters.\n\n\nDuring 2017, there were examples across the region of the adoption of strong monitoring and two way communication approaches.\nFood Security partners are providing increased accountability to all parties via cutting-edge technological advancements. In\nMay 2017, the Building Blocks pilot was launched in Azraq camp in Jordan, the first large-scale humanitarian use of Blockchain\ntechnology. Building Blocks provides a real-time view into food purchase transactions and allows partners to have increased\noperational oversight and management of cash-based transfer (CBT) operations, ensuring data security and reducing the risk of\nfraud.\n\n\nThe food sector in Jordan also utilizes a Triangulation Database; a system which compiles data from various sources and\nsynthesizes it into actionable intelligence, dashboards, and mapping. The Triangulation Database gathers real time financial\ndata from Building Blocks, financial service providers, retailers, and the sector’s internal data systems. From this data, the sector\ncan conduct monthly financial reconciliation, identify anomalies, generate real time data on expenditure patterns, and ensure\nmaximum transparency and accountability.\n\n\nIn Lebanon, food security partners work to empower Syrian and Lebanese families to have as much control as possible over their\nshopping. Launched in November, the smartphone application ‘Dalili’ enables them to do just this. It collates and displays the", "output": {"entities": {"named_data": ["Triangulation Database", "Triangulation Database"], "descriptive_data": ["real time financial\ndata"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001030", "page": 11, "chunk": 2, "title": "(3RP) Regional Refugee and Resilience Plan 2017 - 2018 in response to the Syria Crisis | 2017 Annual Report [EN/AR]", "pdf_url": "https://reliefweb.int/attachments/9d0a64cf-a831-30be-8e02-dcfa7bd8a7f5/63530.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Triangulation Database", "label": "NAMED_DATA", "score": 0.7001258730888367, "start": 1550, "end": 1572, "probe_score": 0.1378, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Triangulation Database", "label": "NAMED_DATA", "score": 0.532471776008606, "start": 1702, "end": 1724, "probe_score": 0.0163, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "real time financial\ndata", "label": "DESCRIPTIVE_DATA", "score": 0.7484432458877563, "start": 1733, "end": 1757, "probe_score": 0.0422, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "#### **Tables**\n\nTable 1: Shares of Upper-Secondary Enrollment in a selected group of Countries\n\n\n<u>General</u> <u>Pre-vocational</u> <u>Vocational</u>\nArgentina 82% 18%\nBrazil 86% 14%\nChile 67% 33%\n**Mexico** 91% 9%\n\n\n<u>OECD average</u> <u>54%</u> <u>2%</u> <u>44%</u>\n\n\nNOTE: Authors’ elaboration based on Education at a Glance 2011: OECD Indicators, OECD, Paris.\n\n\nTable 2: Effect of the _Oportunidades_ Transfer on Track Choices (1st option)\n\n\nOutcome Variable <u>Vocational</u> <u>General</u> <u>Technical</u>\nParameter OLS-ITT IV-LATE OLS-ITT IV-LATE OLS-ITT IV-LATE\n<u>(1)</u> <u>(2)</u> <u>(3)</u> <u>(4)</u> <u>(5)</u> <u>(6)</u>\n\n\nTreat 0.040** 0.011 -0.051\n(0.019) (0.037) (0.036)\n\n\nTake-up 0.061** 0.017 -0.079\n(0.03) (0.056) (0.056)\n\n\nMean Dep. Var. 0.092 0.465 0.443\nSD Dep. Var. 0.289 0.499 0.497\nObservations 5232 5232 5232 5232 5232 5232\n<u>Clusters</u> <u>2907</u> <u>", "output": {"entities": {"named_data": ["OECD Indicators"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006479", "page": 36, "chunk": 0, "title": "wps7427", "pdf_url": "https://local/prwp/wps7427.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "OECD Indicators", "label": "NAMED_DATA", "score": 0.7962439060211182, "start": 338, "end": 353, "probe_score": 0.9993, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\n**Table 1: Results of the economic and sensitivity analysis**\n\n|Col1|Component 1|Col3|Component 2|Col5|Components 1 and 2|Col7|\n|---|---|---|---|---|---|---|\n||**NPV**|**IRR**|**NPV**|**IRR**|**NPV**|**IRR**|\n|**Baseline scenario**|39,282,725|41.2%|8,529,368|18.9%|47,812,093|34.6%|\n|**Sensitivity analysis**|||||||\n|Costs increase by 10%|32,869,518|32.3%|6,640,439|15.2%|38,461,897|26.6%|\n|Benefits reduce by 10%|26,004,257|28.6%|5,787,502|14.8%|34,533,625|25.6%|\n|Benefits lag by two<br>years|2,607,952|7.5%|4,661,066|11.8%|7,269,018|8.8%|\n\n\n\n_Source:_ World Bank staff estimates.\n\n\n**B. Fiduciary**\n\n\n**(i)  Financial Management**\n\n90. **The overall financial management (FM) responsibility for the implementation of the project will be vested in**\n**the MAFS through a PCU, while MGCSW will execute payments for activities", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 45, "chunk": 0, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". (1993) improved these unit\n\n\ncost estimates by the development of continuous cost functions for stone protected and clay\n\n\ncovered sea dikes, and sand dunes. They also included an allowance for extreme sea levels\n\n\nwhich influences initial dike heights, and roughly doubled global costs compared to Dronkers\n\n\net al. (1990) (see Table 1).\n\n\nTo set the stage, we analyzed possible determinants of unit costs of sea dikes with a\n\n\ncountry-level cross-sectional data set from the DIVA database. The total sample contains\n\n\n248 observations. We removed 47 observations without low-lying land below 10 meters\n\n\nA.D., as these do not have sea dikes. Furthermore, eight outliers with very high asset\n\n\ndensities (e.g. Monaco, Gibraltar, Bahrain) were excluded from the econometric analysis.\n\n\nA least squares regression analysis was performed to investigate how experts appear to\n\n\nhave evaluated the importance of local differences in determinants of unit costs, as revealed", "output": {"entities": {"named_data": ["DIVA database"], "descriptive_data": ["country-level cross-sectional data set"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007643", "page": 48, "chunk": 1, "title": "wps8745", "pdf_url": "https://local/prwp/wps8745.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "country-level cross-sectional data set", "label": "DESCRIPTIVE_DATA", "score": 0.7803930044174194, "start": 431, "end": 469, "probe_score": 0.7343, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "DIVA database", "label": "NAMED_DATA", "score": 0.8705132603645325, "start": 479, "end": 492, "probe_score": 0.9639, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Emergency Food and Nutrition Security Project (P163559)\n\n\n**ANNEX 4: ENVIRONMENT AND SOCIAL SAFEGUARDS ACTION PLAN**\n\n\n**COUNTRY: South Sudan**\n**South Sudan Emergency Food and Nutrition Security Project**\n\n_The following section outlines the requirements of the Environmental and Social Safeguards Action Plan_\n_that has been prepared to ensure compliance with safeguards in line with the World Bank’s Operational_\n_Policy OP 10.00 paragraph 12._\n\n**Background**\n\nThe proposed South Sudan EFNSP is prepared and implemented according to Paragraph 12 of the\nWorld Bank’s Operational Policy 10.00, which allows for certain exceptions to the requirements of the IPF\npolicy, including deferral of safeguards requirements, if the Bank deems the client to be in urgent need of\nassistance.\n\n\n**Almost twelve years after gaining autonomy and then subsequent independence in 2011, South**\n**Sudan still struggles to break out of the conflict trap.** Conflict resumed in December 2013 and, despite a\nbrief period of optimism following the Agreement for the Resolution of Conflict signed in August 2015,\nstill continues. The conflict started in Juba and then was focused on the Greater Upper Nile Region;\nhowever recently there has been organized violence in previously peaceful areas such as Central and\nEastern Equatoria. The hostilities and unrest have led to massive displacement (both because of the\nfighting itself as well as fear of the violence). Available statistics indicate that over 2 million persons are\nnow internally displaced including over 200,000 civilians who have sought protection in the UN PoC sites\nacross the country. Further, some 1.4 million persons have sought refuge in neighboring countries.\n\n\n**Conflict has resulted into a near collapse of the economy.** Currently, the country exhibits all the\nsigns of macroeconomic collapse. There have been sharp declines in output, and a spike in the parallel\nexchange market premium.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Available statistics"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000038", "page": 69, "chunk": 0, "title": "South Sudan - Emergency Food and Nutrition Project", "pdf_url": "http://documents.worldbank.org/curated/en/713081494122547885/pdf/South-Sudan-PAD-04282017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Available statistics", "label": "VAGUE_DATA", "score": 0.5621341466903687, "start": 1475, "end": 1495, "probe_score": 0.968, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|~~H*~~||~~IT~~|\n||||||\n\n\n\n2% 4% 6%\n\n**Female unemployment rate**\n\n\n\n34%\n\n\n\n\n\n\n\n\n\n\n\nThe high level of education of Ukrainians\ncoming to Poland helped them access the\nlabour market. The percentage of higher\neducation for refugees and pre-2022\nmigrants from Ukraine in NBP and UNHCR\nsurveys is significantly higher than for the\nPolish population and even higher than\nfor Ukraine, according to the Labour Force\nSurvey (LFS) in Poland, and its equivalent\nin Ukraine. According to NBP survey from\n2022 the percentage of refugees with\nhigher education was at 48%, while MSNA\n\n\n\n\n\n8% 10%\n\n\n\n\n\n\n\n\n\n\n\n**Source:** Deloitte own elaboration based on Eurostat, <u>[https://nbp.pl/wp-content/uploads/2023/04/Sytuacja-zyciowa-i-ekonomiczna-](https://nbp.pl/wp-content/uploads/2023/04/Sytuacja-zyciowa-i-ekonomiczna-migrantow-z-Ukrainy-w-Polsce_raport-z-badania-2022-r.pdf)</u>\n<u>[migrantow-z-Ukrainy-w-Polsce_raport-z-badania-2022-r.pdf, UNHCR survey conducted from 13.07.2023 to 21.08.2023, and State Statistics](https://nbp.pl/wp-content/uploads/2023/04/Sytuacja-zyciowa-i-ekonomiczna-migrantow-z-Ukrainy-w-Polsce_raport-z-badania-2022-r.pdf)</u>\nService of Ukraine (2021).", "output": {"entities": {"named_data": ["Labour Force\nSurvey", "NBP survey", "UNHCR survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 10, "chunk": 2, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Labour Force\nSurvey", "label": "NAMED_DATA", "score": 0.7889498472213745, "start": 395, "end": 414, "probe_score": 0.8876, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "NBP survey", "label": "NAMED_DATA", "score": 0.6473252177238464, "start": 476, "end": 486, "probe_score": 0.9825, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHCR survey", "label": "NAMED_DATA", "score": 0.6688849329948425, "start": 924, "end": 936, "probe_score": 0.9833, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Emergency Food and Nutrition Security Project (P163559)\n\n\n**<u>Table A3.1. Representative farm gross margins for sorghum and maize</u>**\n<u>Financial Analysis</u> <u>Economic Analysis</u>\nUnit Sorghum Maize Sorghum Maize\n<u>Share of project area</u> <u>%</u> <u>55</u> <u>45</u> <u>55</u> <u>45</u>\nYield kg/ha 900 800 900 800\nCrop price US$/kg 0.55 0.62 0.39 0.68\nOperating costs by Project US$/ha 200 125 170 106\nOperating costs by farmer US$/ha 200 125 170 106\n<u>Gross Margin</u> <u>US$/ha</u> <u>95</u> <u>246</u> <u>6</u> <u>333</u>\nSources: Averages based on field survey data February‐March 2011 as reported in Sebit (2011) and World Bank\n(2012) and authors’ estimates.\n\n\n9. **Economic returns on investment in agricultural productivity** . The financing for component 2.1 is\nUS$5.0 million‐of which 75 percent is assumed to be operating cost ‐ and which is matched by US$3.7\nmillion operating cost borne by farmers, which can include e.g. labor and additional inputs (in addition to\nproject inputs). Financial gross margins and investment costs are converted into economic values. Results\nin Table A3.2 show that the entire investment cost is recovered in benefits in year 1 because it turns a\npositive net benefit of US$2.1 million or US$98/farmer or hectare that", "output": {"entities": {"named_data": [], "descriptive_data": ["field survey data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000038", "page": 66, "chunk": 0, "title": "South Sudan - Emergency Food and Nutrition Project", "pdf_url": "http://documents.worldbank.org/curated/en/713081494122547885/pdf/South-Sudan-PAD-04282017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "field survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8464208841323853, "start": 597, "end": 614, "probe_score": 0.9886, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " all bidders from eligible countries as defined in the\nguidelines. Consultants would be selected in accordance with World Bank Guidelines: Selection and\nEmployment of Consultants by the World Bank Borrowers dated May 2004 (revised October 2006) and\nthe Financing Agreement. In addition, procurement under the proposed operation will be carried out in\naccordance with the “Guidelines on Preventing and Combating Fraud and Corruption in Projects\nFinanced by IBRD Loan/Credits/Grants”, known as the “2006 Anti-Corruption Guidelines”. See Annex **8**\nfor details.\n\n\n**D.** **Social**\n\n\n76. **Poverty targeting.** The project will contribute to increased benefits to rural and urban populations\nthrough the SWF’s focus on poverty targeting based on the PMT method, improving the SWF’s ability to\ntarget those most in need. The project addresses targeting issues at three levels: (i) at the policy level to\nobtain the Government endorsement of the PMT targeting approach with its identification of a large\nnumber of beneficiaries who will be ineligible for cash transfers in the future; (ii) at the technical level by\nbuilding the **SWF** capacity to collect appropriate applicant data on which to apply the PMT as well as\nbuilding staff capacity in PMT methods; and (iii) at the community level with a comprehensive public\ninformation campaign designed in part to inform and encourage the poorest households to apply for\nbenefits. The project will also involve CSOs and NGOs to identify eligible households not yet receiving\nbenefits.\n\n\n77. **Gender.** Since SWF cash transfers go to the head of the household and most household heads are\nmen, it will be important to assess if this determines how money is spent. If male/female spending\npatterns are an issue, the project would establish methodologies for effectively communicating important\nmessages (e.g., nutrition) to both men and women. This may mean", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["applicant data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000080", "page": 24, "chunk": 1, "title": "Yemen, Republic of - Social Welfare Fund Institutional Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/495501468170077604/pdf/533550PAD0P117101Official0Use0Only1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "applicant data", "label": "VAGUE_DATA", "score": 0.6305954456329346, "start": 1165, "end": 1179, "probe_score": 0.0052, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " or low employment level, similar (baseline) or lower\n(conservative) productivity. In the conservative productivity scenario,\nwe assumed approximately 10% lower refugee productivity estimated based\non incomes reported in MSNA Poland 2023 and data from Statistics Poland.\n\n\n**Table 2.** Cumulative changes in main indicators in 2023\n\n\n**SCENARIO 1** **SCENARIO 2** **SCENARIO 3** **SCENARIO 4**\n\n\n\n**Low employment**\n**conservative**\n**productivity**\n\n\n\n**High employment**\n**conservative**\n**productivity**\n\n\n\n**Low employment**\n**baseline**\n**productivity**\n\n\n\n**High employment**\n**baseline**\n**productivity**\n\n\n\nThe main impact of refugees is in growth\nof the economy. Refugees increase both\nsupply as workers and entrepreneurs as\nwell as demand as consumers. Increase\nin GDP is not directly proportional to the\nincrease in population or employment.\nNet benefits are lowered both due to\na decrease in capital to labour ratio as\nwell as an increase in competition on\nthe labour market. Moreover, increase in\ndemand in tight labour market conditions\nresults in higher inflation and lower\nprice competitiveness of Polish products\nwhich lower its overall positive impact.\nNevertheless, the positive impact of\nrefugees on the economy is significant in\nevery scenario considered.\n\n\nIn 2022 it amounts to real GDP\nbeing higher by 0.5-0.8% and in\n2023 cumulatively by 0.7-1.1%.\nThis corresponds to GDP being\nhigher by 24-36.9 billion PLN in\n2023 <sup>43</sup> .\n\n\nIn the long term, total potential GDP should\nbe higher by around 0.9-1.35% due to\nrefugees contributions. <sup>44</sup>\n\n\nOur results are consistent with the\nprevious, similar studies. In estimating\nGDP impacts we take an approach that", "output": {"entities": {"named_data": [], "descriptive_data": ["data from Statistics Poland"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 17, "chunk": 2, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data from Statistics Poland", "label": "DESCRIPTIVE_DATA", "score": 0.696896493434906, "start": 242, "end": 269, "probe_score": 0.9998, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "output": {"entities": {"named_data": [], "descriptive_data": ["random survey"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016663", "page": 16, "chunk": 0, "title": "Ethiopia - Agricultural Minimum Package Project", "pdf_url": "https://documents.worldbank.org/curated/en/684641468243869998/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7714613080024719, "start": 379, "end": 395, "probe_score": 0.582, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "random survey", "label": "DESCRIPTIVE_DATA", "score": 0.7173007130622864, "start": 1487, "end": 1500, "probe_score": 0.012, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*<u>Year 3</u>** **<u>Total</u>**\n\n**(In millions of USD)**\n\n**Health** **16.5** **19.8** **26.0** **62.3**\nHospitalization 11.0 13.1 15.8 39.9\nPrimary Healthcare Services-MOPH 2.3 2.8 5.6 10.7\nMedication (Chronic) 3.2 3.8 4.6 11.6\n**Education** 3.4 5.3 7.0 15.7\n**E-card Food Voucher** 18.0 36.0 70.2 124.2\n\n\n**Total** **37.9** **61.1** **103.2** **202.2**\n\n\nOf which from Government (Health & Education) 19.9 25.1 33.0 78.0\n\nOf which TFL and UNHCR 6.8\n\nOf which from Other (E-card food) 11.2 36.0 70.2 117.4\n\n\n_Source: MOSA NPTP Team & World Bank Staff Calculations_\n\n\n1/ Year 1 refers to 2014/2015, Year 2 to 2015/2016, and Year 3 to 2016/2017 respectively.\n\n\n13. **The expected coverage rate of extremely poor individuals by the end of the project.**\nWe are making the assumption that, by 2016/2017, 100 percent of extremely poor households\nwill be covered with NPTP benefits. Since we are using 2004 HBS data to simulate NPTP\nimpact, we are assuming that the extreme poverty line is US$3.84 per capita per day, and that 7.2\npercent of the population (or 306,251 individuals) were extremely poor in that year, in addition\nto the", "output": {"entities": {"named_data": ["2004 HBS data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000139", "page": 68, "chunk": 1, "title": "Lebanon - Emergency National Poverty Targeting Program Project", "pdf_url": "http://documents1.worldbank.org/curated/en/810511467987899324/pdf/PAD1030-ENGLISH-P149242-PUBLIC-FINAL-LEB-ENPTP-English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "2004 HBS data", "label": "NAMED_DATA", "score": 0.8079614639282227, "start": 900, "end": 913, "probe_score": 0.9925, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "5.1.3 Ministry of Agriculture\n\n\nUnit costs for use in valuation formulae and compensation will be provided by the\nDepartments of Agriculture at the local level, supported by the regional\nAgriculture Bureau. The Ministry of Agriculture will monitor unit costs and follow\nup with Cabinet in terms of issues raised.\n\n5.1.4 Ministry of Capacity Building\n\n\nSection 11 of the LIG ESMF sets out the training and capacity building requirements\nand recommendations for the ESMF, which the Ministry of Capacity Building will\nbe responsible for. Part of this capacity building will include considerations of\nresettlement planning and implementation, as part of the broader environmental\nand social training.\n\n5.2 REGIONAL LEVEL IMPLEMENTING AGENCIES\n\n\nAs described in Section 2.3, the Bureaus of Finance and Economic Development\n(BOFEDs) Planning Unit will be the coordinating body for the LIG at the regional\nlevel using its existing structure and will allocate the LIG funds. It will oversee,\ncoordinate and facilitate the implementation process of LIG across local\ngovernments under its jurisdiction.\n\nThe Bureaus of Finance and Economic Development (BOFED) will therefore be\nresponsible for ensuring that compensation payments are included in the requests\nfor funds, and that they are allocated accordingly.\n\nThe BOFEDs will work with the regional Departments responsible for resettlement\n(eg the Department of Land and Agriculture) to ensure that the RPF is properly\napplied across all relevant subprojects.  This department will review RAPs for all\nsubprojects in their region to ensure that they comply with national requirements\nand the requirements of the RPF. It will work closely with the BOFED to ensure\nthat funds are allocated as committed to in the approved RAP.\n\nThe regional level departments will provide a review and monitoring role, and\nprovide political and administrative support for the implementation of the RAPs.\n\n5.3 LOCAL IMPLEMENTING AGENCIES\n\n\nIn keeping with Ethiopia’s decentralization policy, the responsibility for the\ndevelopment and", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012558", "page": 30, "chunk": 0, "title": "Ethiopia - Additional financing for the Protection of Basic Services Project : resettlement plan : Resettlement policy framework for local infrastructure grant", "pdf_url": "https://documents.worldbank.org/curated/en/409241468243869019/pdf/RP7240P10655901ework0of0100May02007.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEducation Quality Improvement Project (P179363)\n\n\n**I.** **STRATEGIC CONTEXT**\n\n\n**A. Country Context**\n\n\n1. **Moldova, one of the two newest candidate countries of the European Union (EU), currently**\n**faces multiple crises.** Despite a solid economic performance and strong poverty reduction over the past\ntwo decades, Moldova remains among the poorest countries in Europe. <sup>1</sup> [^1: Poverty declined from around 90 percent in the late 1990s to 15 percent in 2019, bouncing back to 18 percent in 2020 due to\nthe pandemic. Source: National Bureau of Statistics 2014–2021.] The COVID-19 pandemic and a\nsevere drought in 2020 and 2022 have revealed the intrinsic vulnerabilities of the country’s economic\ngrowth model, which suffers from limited resilience to shocks. Russia’s invasion of Ukraine has created a\nprotracted and intensified inflation and the energy crisis, negatively affected the purchasing power of\nhouseholds, and squeezed resources available to the Government of Moldova (GoM) to address service\ndelivery challenges and long-term development priorities. The GoM is committed to transforming the\neconomy and has set out an ambitious reform agenda in the National Development Strategy (NDS) <sup>2</sup> [^2: https://gov.md/ro/content/strategia-nationala-de-dezvoltare-moldova-europeana-2030-fost-aprobata-de-guvern.]\n‘European Moldova 2030’ aimed to improve the institutional, governance, and business environment;\nstrengthen competition; stimulate foreign direct investment; invest in human capital; and create jobs to\nreduce labor emigration. With EU candidate status, gained in June 2022, through convergence with\neconomic, social, digital, and environmental standards of the EU, the accession process can open more\nopportunities to unlock growth potential and bring greater prosperity to the people of Moldova.\n\n2. **The NDS recognizes that investments in human capital development of Moldova are critical for**\n**economic growth.*", "output": {"entities": {"named_data": ["National Bureau of Statistics"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000185", "page": 10, "chunk": 0, "title": "Moldova - Education Quality Improvement Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099051123142553305/pdf/BOSIB-624554c1-598f-4576-aa60-cca7d93b64e7.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "National Bureau of Statistics", "label": "NAMED_DATA", "score": 0.5571513772010803, "start": 560, "end": 589, "probe_score": 0.9969, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "meet the needs of teachers and schools. The first component of this project will fully apply this\napproach in the planning and delivery of teacher training. The establishment of unit-based\nteaching practice teams within each teacher education institution to conceptualize, plan, and\noversee the implementation of a teaching practice policy has proven to be an effective strategy\nfor developing up-to-date thinking on how to address the challenges involved in the practical\npreparation of teachers.\n\n39. _Selection of schools and teachers._ The selected schools and teachers, and the preparation\nof both to host and support the development of student teachers, is critical to the success of\nteaching practices. Intensive capacity building needs to be provided for the participating trainers\nof teachers, if the demonstration of teaching techniques and mentoring of student teachers are to\nbe up to date and effective.\n\n40. _Availability of teaching resources._ Facilities and materials used during teacher\ndevelopment programs should be those currently available or soon to be supplied to schools. If\nstudent teachers master those skills and learn how to make effective use of available teaching\naids and facilities in the implementation of student-focused, activity-oriented learning, the\nlikelihood is that they will effectively utilize more sophisticated equipment such as computers\nand video equipment, if and when these become available in schools.\n\n41. _Evaluate programs in a systematic manner._ Very little is known of the impact of inservice teacher professional-development activities on student learning outcomes in developing\ncountries as well as in WBG. While many countries have data on initial teacher education, very\nfew follow-up by collecting data on changes in teaching practices as a result of in-service\nprofessional-development programs. Lack of data and systematic evaluation are hindering the\nunderstanding of which staff development policies are most effective in enhancing teachers’\ncompetencies and performance.\n\n42. _Success requires systematic system support and follow-up_ . Schwille and Dembele\n(2007) <sup>11</sup> carried", "output": {"entities": {"named_data": [], "descriptive_data": ["data on initial teacher education"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000171", "page": 17, "chunk": 0, "title": "West Bank and Gaza - Teacher Education Improvement Project", "pdf_url": "http://documents1.worldbank.org/curated/en/951621468137973426/pdf/492780PAD0P111101Official0Use0Only1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data on initial teacher education", "label": "DESCRIPTIVE_DATA", "score": 0.7650437355041504, "start": 1692, "end": 1725, "probe_score": 0.7195, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " profile of the beneficiaries\nin terms of land access, existing farm system, investment capacity, labor capacity, and location. It was\nnot clear from the ICR what crops like cabbages, potatoes, tomatoes, and intensive dairying (other\nthan through increased manure) would do for the sustainability of land management. Other than\nperhaps ridged potatoes if well aligned on the contour, these are not enterprises generally known for\nholding soil.\n\n  - **Creating opportunities for linking investments in SLM technologies with commercial ventures**\n**and marketing.** The project financed different types of micro-catchment projects including: dairy and meat\n(poultry, dairy cows, dairy goat and fodder) and fruits, nuts and vegetables (onions, ground nuts,\nstrawberries, passion fruit, irish potatoes, French beans) apiculture, aquaculture.\n\n**Outcome**\n\n\n  - Outcome is rated modest. The project direct beneficiaries reached 28,664 (17,617 Men, 11,047 Women,\ncompared to a target of 60,000 beneficiary) in 112 micro-catchments (target: 127 micro-catchments). Also,\nthe impact of project activities on household incomes was not assessed at completion; and the project’s\nefforts to address the gaps in the policy framework and to support institutional capacity for cross-sectoral\nintegrated planning and monitoring of SLM interventions did not materialize. The compressed\nimplementation period-where most achievements happened in the final eighteen months of the project,\nmakes it difficult to predict how much of these achievements will be sustained. Finally, the project suffered\nfrom the lack of baseline data for several outcome/intermediate outcome indicators which hindered the\nassessment of project activities. The following are the project achievements:\n\n  - The project promoted nine SLM technologies and practices in the three catchments areas implementing\nthe project (Cherangani, Taita and Kikuyu-Kinale). While the project was successful in dissemination of\nnew technologies, adoption rates of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009409", "page": 5, "chunk": 1, "title": "Kenya - KE-GEF Ag prd & Sust. Land Mgmt(KAPSLMP)", "pdf_url": "https://documents.worldbank.org/curated/en/200401507327011207/pdf/ICRR-Disclosable-P088600-10-06-2017-1507326997150.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "baseline data", "label": "VAGUE_DATA", "score": 0.6731979250907898, "start": 1595, "end": 1608, "probe_score": 0.0954, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "17, which is considerably higher than the national poverty rate of 21 percent for the same\nyear. This poses significant development challenges to both refugees and host communities. Post COVID19, with the loss of lives and the decline in economic activity, poverty, inequality, and unemployment levels\nare expected to rise sharply.\n\n10. **The GoU has made self-reliance central to Uganda’s refugee response with a** **focus on development**\n**interventions targeting refugee hosting districts.** Central to this refugee model is creating economic\nopportunities in and around the areas hosting refugees to benefit refugees and host communities. However,\nmost refugee hosting areas are in rural and remote locations that increase the challenges for local economic\ndevelopment. About 54 percent of refugees still depend on humanitarian assistance as their main source of\nlivelihood. <sup>9</sup> [^9: World Bank 2019, Informing the Refugee Policy Response in Uganda, Results from the Uganda Refugee and Host Communities 2018\nHousehold Survey] Many refugees and hosts have limited access to productive employment, income-generating\nopportunities and lack human capital. Social impacts are circumscribed by the underlying poverty and\nvulnerabilities exacerbated by weak basic social services delivery, poor infrastructure, and limited market\nopportunities in the refugee hosting settlement areas that impacts refugees and host communities alike. <sup>10</sup> [^10: https://www.worldbank.org/en/topic/fragilityconflictviolence/brief/ugandas-progressive-approach-refugee-management]\nNonetheless, refugees present an untapped source of human capital. Refugees are active economic actors,\nentrepreneurs, with diverse economic lives engaged in a variety of income generating businesses. As\nrefugees live alongside local hosting communities, there is clear economic interdependence between the\nco-habiting communities and evidence of trade activity between settlements, the wider Ugandan market\nand cross border trade. Traders from South Sudan and DRC visit the settlements regularly to supply as well\nas source goods and services. This presents an opportunity for local economic development that can address\nmarket constraints. The provision", "output": {"entities": {"named_data": ["Uganda Refugee and Host Communities 2018\nHousehold Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 13, "chunk": 1, "title": "Uganda - Roads and Bridges in the Refugee Hosting Districts/Koboko-Yumbe-Moyo Road Corridor Project", "pdf_url": "http://documents.worldbank.org/curated/en/834931600048847296/pdf/Uganda-Roads-and-Bridges-in-the-Refugee-Hosting-Districts-Koboko-Yumbe-Moyo-Road-Corridor-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Uganda Refugee and Host Communities 2018\nHousehold Survey", "label": "NAMED_DATA", "score": 0.9167187213897705, "start": 981, "end": 1038, "probe_score": 0.9985, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "br>0.22 (school<br>satisfaction)|\n|Angrist et al. 2020|High-dosage tutoring (phone based)|0.89 (math)|\n|Fryer 2014<br>|Increased instructional time, more effective teachers, high-dosage<br>tutoring, data-driven instruction, culture of high expectations|0.15 (math)|\n|Schueler, Goodman,<br>and Deming 2017|“Acceleration Academies,” intensive, targeted instructional programs<br>taught over vacation breaks by a carefully selected set of teachers and<br>preselected students (Lawrence, Massachusetts, United States)|0.3 (math)<br>0.1 (English)|\n|Kidron and Lindsay<br>2014|Increased learning time programs (meta-analysis)|Mixed effects|\n|Singh, Romero, and<br>Muralidharan 2022|Supplementary instruction program after the pandemic school<br>opening for COVID learning loss recovery|0.17 (math)<br>0.09 (Tamil)|\n\n\n_Source_ : World Bank staff compilation.\n\n**Modelled Costs**\n\n8. Future annual recurrent costs implied by Component 1 were estimated based on per-student\nannual costs of implementing the remedial programs and the rapid assessment. Project costs can be\ndivided into two categories: investment costs which include the setup and the design of new programs\n(for example, design of new pedagogies and teacher training materials) including one-time investment\ncosts (such as teacher training) and the cost of operating these programs each year after they have been\nestablished (for example, implementing the remedial programs for students and the rapid assessment).\nThe investment costs included in the economic analysis are the total project costs per year, the sum of\nwhich is equal to the total project cost. The recurrent annual costs of the remedial program were\nestimated", "output": {"entities": {"named_data": ["World Bank staff compilation"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000185", "page": 65, "chunk": 1, "title": "Moldova - Education Quality Improvement Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099051123142553305/pdf/BOSIB-624554c1-598f-4576-aa60-cca7d93b64e7.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "World Bank staff compilation", "label": "NAMED_DATA", "score": 0.5407088994979858, "start": 822, "end": 850, "probe_score": 0.9951, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " benefits to the population served by the roads.\n\n48. In the absence of comprehensive surveys on the above variables, the economic internal rate of\nreturn (EIRR) for USMID roads were obtained from previous studies with more or less the same\nenvironment to generate the stream of benefits. The Net Present Values show the net economic benefits\n\n\n75 Using up-dated population figures from FY 2017/18.\n\n\n60", "output": {"entities": {"named_data": [], "descriptive_data": ["up-dated population figures"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000062", "page": 67, "chunk": 2, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents.worldbank.org/curated/en/946901526654169395/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "up-dated population figures", "label": "DESCRIPTIVE_DATA", "score": 0.6670713424682617, "start": 354, "end": 381, "probe_score": 0.6286, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and middle\nPrivate sector share in middle schools.\nschools increases to 12%.\n\n\nHigher promotion rates at the Promotion rates at the end of Year books and reports. Assumes enough space at the\nend of the primary school the primary cycle should rise middle schools to\ncycle. from 36% in 1999 to 83% in accommodate the primary\n2010. cycle graduates.\nIncrease participation of girls Enrollment rate for girls Random surveys of Economic situation worsens\nand children from poorer increases faster than boys. school students making it more difficult to\ngroups More children from poorer including a baseline in provide incentives to the poor\ngroups in school. 2001 and follow up to attend.\nsurveys in 2005 and\n2010.", "output": {"entities": {"named_data": [], "descriptive_data": ["Random surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000049", "page": 29, "chunk": 1, "title": "Croatia - Reconstruction Project for Eastern Slavonia, Baranja and Western Srijem", "pdf_url": "http://documents1.worldbank.org/curated/en/347691468746725804/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Random surveys", "label": "DESCRIPTIVE_DATA", "score": 0.5383497476577759, "start": 405, "end": 419, "probe_score": 0.2766, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\nVocational or lower Secondary Higher\n\n\n\nData is limited, but it appears refugees\nfound work in sectors where the labour\nmarket was particularly tight. Publicly\navailable data does not give the numbers\nof social security registrations of native\nworkers by NACE sector. For this reason,\nin the absence of administrative data,\nto approximate the share of Ukrainian\nworkers in particular sectors it was\nnecessary to use Statistics Poland survey\ndata. The share of workers with Ukrainian\ncitizenship grew more in sectors that were\nexperiencing the highest wage and salaries\ngrowth before refugee displacement. This\neased their entry into the labour market.\nThe refugees were also quick to set-up their\nown businesses or become self-employed.\nAccommodation and food, as a sector,\nhas been experiencing a particularly large\ngrowth in wages and salaries in 2021, as it\nre-opened after the Covid-19 pandemic,\nand subsequently it recorded a particularly\nlarge growth in the share of Ukrainian\nworkers. Transportation has been the only\nsector in which the share and number of\nUkrainian workers declined.\n\n\nA significant number of refugees are\nconcentrated in the urban areas of\nPoland. For one, cities generally record\nlower unemployment rates and higher\nwork productivity, though the costs of\nliving remain higher than in rural areas.\nAccording to the active population in the\nPESEL database, over 30% of all PESEL UKR\nholders had them issued in the country’s\n12 biggest cities. At the same time, the\nresults for the MSNA Poland 2023 survey\nsuggest that these 12 biggest cities are\ninhabited by over 35% of refugees.\n\n\n\nRefugees record higher levels of\nemployment inclusion in European\ncountries that have relatively better labour\nmarket situations. In countries with lower\nunemployment, refugees fare better in\nthe labour market. Since women make\nup the majority of refugees of working\nage, the situation of women on the labour\nmarket is especially important. As such,\nfemale unemployment", "output": {"entities": {"named_data": ["Statistics Poland survey\ndata", "PESEL database", "MSNA Poland 2023 survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 10, "chunk": 0, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Statistics Poland survey\ndata", "label": "NAMED_DATA", "score": 0.82492995262146, "start": 567, "end": 596, "probe_score": 0.9774, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PESEL database", "label": "NAMED_DATA", "score": 0.8856232166290283, "start": 1518, "end": 1532, "probe_score": 0.8853, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "MSNA Poland 2023 survey", "label": "NAMED_DATA", "score": 0.9161665439605713, "start": 1658, "end": 1681, "probe_score": 0.9768, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nLebanon: Wheat supply emergency response project (P178866)\n\n\n(ESSP) and UN-administered cash transfer programs for displaced Syrians, addressing demand-side constraints\nregarding economic access of the poor and most vulnerable including refugees to food and food security.\n\n\n**II.** **PROJECT DESCRIPTION**\n\n\n**A. Project Development Objective**\n\n\n**PDO Statement**\n\n\n20. The Project Development Objective (PDO) is to ensure the availability of wheat in Lebanon, in response to the\nglobal commodity market disruptions, and to maintain access to affordable bread by poor and vulnerable households.\n\n\n**PDO Level Indicators**\n\n21. Progress toward the PDO will be monitored through the following key indicators: (1) the cumulative amount of\nwheat procured through the project and delivered in the ports of Beirut and Tripoli (target 250,000 tons); and (2)\nvulnerable beneficiaries with access to affordable bread <sup>6</sup> [^6: The vulnerable beneficiaries (poor Lebanese population and refugees, respectively) will be drawn and sampled based on the current\nWFP and UNHCR databases, respectively. The indicator will track bread consumption, specifically, rather than food security more broadly;\nthe actual values will be determined through the high frequency surveys foreseen during project implementation.] (target: 95 percent vulnerable beneficiaries; vulnerable host\ncommunities: 95 percent; refugees: 95 percent; vulnerable women: 99 percent).\n\n\n22. The project will also track progress through the following Intermediate Results Indicators:\n\n**-** Monthly amounts of wheat procured through the project and delivered in the ports of Beirut and Tripoli\n(target: monthly average of 50,000 tons for the first 5 months of project implementation). <sup>7</sup> [^7: This is based on an assumed wheat price of US$ 500 per ton.]\n\n**-** Percentage of beneficiaries’ feedback addressed through the Grievance Mechanism (GM) within the", "output": {"entities": {"named_data": [], "descriptive_data": ["high frequency surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000019", "page": 17, "chunk": 0, "title": "Lebanon - Wheat Supply Emergency Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/408131653327258940/pdf/Lebanon-Wheat-Supply-Emergency-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "high frequency surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8346472382545471, "start": 1263, "end": 1285, "probe_score": 0.7175, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "at mid-year grew to 1.8 million. A further 1.3 million\nrefugees and asylum-seekers from Myanmar\nremained displaced with most hosted by other\ncountries in the region, notably Bangladesh.\n\nThe humanitarian crisis in **Afghanistan** shows no\nsigns of easing and, at mid-2023, some 9.7 million\nAfghans remained displaced. Conflict may have\nlargely subsided following the Taliban’s takeover of\nAugust 2021, but rising prices, a collapsing economy,\nand ever-increasing restrictions on the rights of\nwomen and girls continue to cause misery. Poverty\nis endemic, half of the population of more than 40\nmillion people faces acute food insecurity, and nearly\n3.3 million people in the country remained displaced\nfrom their homes at mid-2023. The number of Afghan\nrefugees <sup>**21**</sup>, reported globally increased from 5.7\nmillion to 6.1 million, mostly reflecting new population\nestimates reported by the Government of Pakistan.\nTogether, the Islamic Republic of Iran (3.4 million) and\n\n\nFigure 2 **| People forced to flee | 2009 – mid-2023** <sup>**22**</sup>\n\n\n100M\n\n\n80M\n\n\n\nChapter 1\n\n\nPakistan (2.1 million) hosted 90 per cent of all Afghan\nrefugees.\n\n**Nationals of Latin America and the Caribbean**\n**countries** registered around one-third of all new\nindividual asylum applications globally. Most were\nregistered by Venezuelans, Cubans, Colombians,\nNicaraguans and Haitians in the United States of\nAmerica and Mexico, with asylum-seekers risking\nthe dangerous route through the Darien jungle – a\ntreacherous stretch of jungle that separates Colombia\nand Panama.\n\n\nGlobally, 1.6 million new individual asylum applications\nwere made, the largest ever number recorded in the\nfirst six months of the year. Despite 637,700 substantive\ndecisions by States and UNHCR on these asylum\napplications, the volume of", "output": {"entities": {"named_data": [], "descriptive_data": ["new population\nestimates reported by the Government of Pakistan"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001065", "page": 8, "chunk": 0, "title": "UNHCR Mid-Year Trends 2023", "pdf_url": "https://reliefweb.int/attachments/a13b0f58-8b05-4652-84d7-e150dd9e7c6c/Mid-year-trends-2023.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "new population\nestimates reported by the Government of Pakistan", "label": "DESCRIPTIVE_DATA", "score": 0.5075922012329102, "start": 860, "end": 923, "probe_score": 0.9518, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**4**\n\n\n\nThe report does not intend to analyse the system-wide challenges of implementing the Centrality of Protection in\nthe humanitarian response, considering the recent conclusion of the Independent Review of the Implementation\nof the IASC Protection Policy (May 2022). The findings and recommendations of the Independent Review are\ntaken forward by the IASC Principals with support of UNHCR and InterAction as co-champions and IASC Task\nForce 1.² As part of a larger IASC action plan to follow up on the recommendations, the IASC TF 1 is developing\na toolkit to support the HCT’s implementation of the IASC Protection Policy that will comprise 1) a set of\nBenchmarks to support the HCs and HCTs with the implementation of Centrality of Protection and serve as an\naccountability mechanism and 2) an Aide Memoire to provide conceptual clarity.\n\nAcknowledging the findings of the Independent Review and the development of an IASC action plan in follow up,\nthe report does not attempt to suggest any standards for how the Centrality of Protection should be implemented.\nWhile reference is made to the IASC Protection Policy and related reviews and reports on the implementation of\nthe policy, the focus of this report is on practices and efforts that are made towards reducing protection risks in\nhumanitarian operations where the cluster system is activated.\n\n\n\n\n\n\n\n² The IASC Task Force 1 on Centrality of Protection is co-chaired by UNHCR and InterAction.\n\n\n**ANNUAL REPORT ON THE CENTRALITY OF PROTECTION IN HUMANITARIAN ACTION 2022**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001022", "page": 4, "chunk": 0, "title": "IASC Centrality of Protection in Humanitarian Action report for 2022 (November 2023)", "pdf_url": "https://reliefweb.int/attachments/9b093447-5375-4919-908e-3a8e0d29c306/IASC%20Centrality%20of%20Protection%20in%20Humanitarian%20Action%20report%20for%202022.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000049", "page": 62, "chunk": 2, "title": "Croatia - Reconstruction Project for Eastern Slavonia, Baranja and Western Srijem", "pdf_url": "http://documents1.worldbank.org/curated/en/347691468746725804/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEducation Quality Improvement Project (P179363)\n\n\non the RAPID Framework for Learning Recovery and Acceleration, <sup>24</sup> [^24: From Learning Recovery to Education Transformation: Insights and Reflections from the Fourth Survey on National Education\nResponses to COVID-19 School Closures. https://openknowledge.worldbank.org/handle/10986/38112] developed by the World Bank and its\npartners, <sup>25</sup> [^25: PDO level indictors are as follows:] and the findings of the Moldova Digital Education Readiness Assessment (2021–22). <sup>26</sup> [^26: World Bank Group. 2022. Moldova – Digital Education Readiness Assessment 2021-22. Washington, D.C.: World Bank Group.]\n\n22. **The project is also aligned with the World Bank’s Global Crisis Response Framework (GCRF).** The\nGCRF for the World Bank’s operational response aims to provide “mutually re-enforcing support by\naddressing short-term shocks to improve prospects for long-term sustainable development, while\ndeveloping long-term resilience to help prepare for future shocks.” <sup>27</sup> [^27: Navigating Multiple Crises, Staying the Course on Long-term Development: The World Bank Group’s Response to the Crises\nAffecting Developing Countries (English), Washington, DC, World Bank Group.] The project is well aligned with Pillar\n2: “Protecting People and Preserving Jobs,” Pillar 3: “Strengthening Resilience to be better prepared for\nany future crisis and challenges,” and Pillar 4: “Strengthening Policies, Institutions and Investments for\nRebuilding Better” of the GCRF. It is also fully consistent with the World Bank Group’s Climate Change\nAction Plan 2021–2025.\n\n\n**II.** **PROJECT DESCRIPTION**\n\n\n**A. Project Development Objective**\n\n\n**PDO Statement**\n\n23. The objectives of the Project are to:", "output": {"entities": {"named_data": ["Survey on National Education\nResponses", "Moldova Digital Education Readiness Assessment"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000185", "page": 19, "chunk": 0, "title": "Moldova - Education Quality Improvement Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099051123142553305/pdf/BOSIB-624554c1-598f-4576-aa60-cca7d93b64e7.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Survey on National Education\nResponses", "label": "NAMED_DATA", "score": 0.5944828391075134, "start": 245, "end": 283, "probe_score": 0.1873, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Moldova Digital Education Readiness Assessment", "label": "NAMED_DATA", "score": 0.8138424158096313, "start": 496, "end": 542, "probe_score": 0.8814, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Across district governments, local taxes are the biggest chunk of district governments’\nOSR, making local taxes an important revenue source for SNGs. Based on Law Number\n23/2009, district governments in Indonesia are allowed to collect taxes from 11 different\ntax bases. The list includes hotels, restaurants, entertainments, advertisements, street\nlighting, non-metal minerals and rocks, parking, ground water, swallows’ nests, residential\nproperties, and property transfers. This paper investigates the impact of Indonesian\ndistricts’ POS distribution on their acquired hotel and restaurant tax payments.\n\n\nFigure 3: Public Revenues by Components\n\n\nSource: data.worldbank.org\n\n###### **2.2 Domestic Revenue Mobilization in West Manggarai and** **Gorontalo**\n\n\n**2.2.1** **West** **Manggarai**\n\n\nWest Manggarai is one of the eight districts that comprise the island of Flores, located\nin the province of East Nusa Tenggara in Indonesia. It covers an area of 9,450 _km_ <sup>2</sup> and\nhad a population of 274,000 people in 2019. In contrast to Gorontalo, West Manggarai\nis a regency instead of a city government. Regency status is generally linked with less\ndevelopment and vaster area than a city. This regency’s economy is mainly driven by\nagriculture and fisheries.\n\n\nThe district primarily relied on transfers to finance spending in 2020. OSR is a small\nproportion of overall revenues. However, local tax revenues primarily dominated its\nOSR by almost 60% of total OSR. West Manggarai’s top three taxes are Street Lighting\nTax, Property Tax and Restaurant Tax. Restaurant tax contributes IDR 1.7 billion or\n12% of the district’s local tax revenue in 2021. The LG, however, has highlighted the\nimportance of restaurant tax as", "output": {"entities": {"named_data": ["data.worldbank.org"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000557", "page": 6, "chunk": 0, "title": "idu00285b30f058fe040a909971003e14dcb92ca", "pdf_url": "https://local/prwp/idu00285b30f058fe040a909971003e14dcb92ca.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data.worldbank.org", "label": "NAMED_DATA", "score": 0.7131269574165344, "start": 659, "end": 677, "probe_score": 0.9931, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " poverty of female-headed households, making\nspecial provision for women to participate in programme decision-making, and making female\ncaregivers the primary recipient of transfers and complementary activities. Table 11 below shows how\ngender considerations have been incorporated into the design of the five cash transfer programmes of\nthe NSNP. Blank cells indicate either that this aspect has not been incorporated into design or that\nthere is no available information on how or whether it has been considered. As this table shows,\nfurther work is needed to ensure that gender considerations are better addressed in the OPCT, the\nPWSD-CT and the UFS-CT and the currently ongoing reviews and manual preparation will help to\naddress this.\n\n\n**<u>Table 11: How Gender has been Incorporated into Aspects of Programme Design</u>**\n\n\n\n\n\n\n\n|Col1|CT-OVC|HSNP|OPCT|PWSD-CT|UFS-CT|\n|---|---|---|---|---|---|\n|Vulnerability of female-headed<br>households recognized in<br>programme targeting||||||\n|Special provision for women to<br>participate in programme<br>decision-making|*|#||||\n|Women selected as primary<br>recipients of transfer|#|#||||\n|Availability of gender<br>disaggregated data||||||\n|_Notes_:<br> - Indicates that there is information that the issue has been addressed.<br># - Indicates that although there is no information, there is some evidence that practice is in line with<br>the indicator.<br>* - Indicates that the Location OVC committees, which conduct targeting, make no specific provision<br>for women but that provision is made", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["disaggregated data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009749", "page": 41, "chunk": 1, "title": "Kenya - National safety net program for results : technical assessment", "pdf_url": "https://documents.worldbank.org/curated/en/220571468273021745/pdf/809680REVISED0Box385274B00PUBLIC0.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "disaggregated data", "label": "VAGUE_DATA", "score": 0.6475302577018738, "start": 1168, "end": 1186, "probe_score": 0.0074, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". <sup>11</sup> [^11: According to the social security data until 30th September 2023.]\nWhile public data does not distinguish\nbetween refugees entering these sectors\nand pre-2022 Ukrainian workers changing\njobs, it is largely consistent with the MSNA\nPoland 2023 survey, in which the most\nrefugees are employed in manufacturing\n(14%), accommodation and food service\n(12%), and trade and repair (6%).\n\n\nUkrainian refugee households in Poland\n\nto the MSNA Poland 2023 survey, 20% of\nUkrainian refugee households earn less\nthan 3 000 PLN, 41% earn between 3 000\nand 6 000 PLN, and 12% earn more than\n6 000 PLN, while 27% of respondents\npreferred not to answer. That said, the\nstandard of living of Ukrainian refugees\nmay be significantly lower than that of\nnative residents, even at similar incomes,\ndue to their lack of housing, which in\nPoland is usually occupant-owned.\n\n\n\n**Inflow of Ukrainian refugees into**\n**Poland**\nThe beginning of the full-scale war in\nUkraine in February 2022 resulted in large\nflows of refugees, reaching more than\n6 million globally. <sup>3</sup> [^3: As of December 2023, according to UNHCR, based on governmental sources <u>[Situation Ukraine Refugee Situation (unhcr.org)](https://data.unhcr.org/en/situations/ukraine)</u>] Much of this exodus\nhappened through the Polish border.\nAs of October 2023, almost 1 million\nUkrainian refugees were living in Poland <sup>4</sup> [^4: According to the active PESEL UKR database.]\n(Chapter 1). In the past decade, Poland\nexperienced large labour migration from\nUkraine. The number of workers with\nUkrainian citizenship that registered for\nsocial security (this data does not include\nthose working in the shadow economy\nor some minor cases that do not require\nregistration) grew from just 33 thousand interm", "output": {"entities": {"named_data": ["MSNA Poland 2023 survey", "PESEL UKR database"], "descriptive_data": ["social security data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 3, "chunk": 1, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "social security data", "label": "DESCRIPTIVE_DATA", "score": 0.8016659021377563, "start": 39, "end": 59, "probe_score": 0.9995, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "MSNA Poland 2023 survey", "label": "NAMED_DATA", "score": 0.5151168704032898, "start": 450, "end": 473, "probe_score": 0.9955, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PESEL UKR database", "label": "NAMED_DATA", "score": 0.8930263519287109, "start": 1432, "end": 1450, "probe_score": 0.9866, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " of\nemployment in urban areas is in the informal sector <sup>2</sup>, characterized by low productivity and wages. In\naddition, congestion and lack of public transport options in many cities restricts the movement of goods and\npeople. The quality of housing remains inadequate for a large proportion of the urban population, with more\nthan 60 percent of the residents of urban areas living in slums. Finally, the delivery of social services of an\nadequate quality to a rapidly expanding urban population is also a source of concern <sup>3</sup> .\n\n4. **_Rapid Urbanization has resulted in a huge infrastructure backlog_** **.** For example, the backlog of\nbituminized roads in the 14 Municipalities targeted in the current phase of USMID was estimated at around\n\n\n1 Currently the Program targets 14 municipalities, namely: Arua, Gulu, Lira, Mbale, Soroti, Tororo, Jinja, Entebbe, Masaka, Mbarara,\nKabale, Fort Portal, Hoima, and Moroto.\n2 Uganda Urban Labor Force Survey 2009.\n3 World Bank. 2015. _The growth challenge: Can Ugandan cities get to work?_ . Washington, DC: World Bank Group.\n\n\n1", "output": {"entities": {"named_data": ["Uganda Urban Labor Force Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000062", "page": 8, "chunk": 2, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents.worldbank.org/curated/en/946901526654169395/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Uganda Urban Labor Force Survey", "label": "NAMED_DATA", "score": 0.8546139597892761, "start": 939, "end": 970, "probe_score": 0.9985, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n# Non-technical summary\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nSwift legal action facilitated labour market\nintegration of refugees. After the beginning\nof the full-scale war on 26th February\n2022, the European Union activated the\nTemporary Protection Directive on 4th\nMarch 2022, and the Polish parliament\npassed a special act to facilitate refugee\nintegration on 12th March 2022. Ukrainian\nrefugees in Poland were granted instant\naccess to the job market, health care, and\neducation. The authorities granted people\nescaping Ukraine legal residency for a\nperiod of eighteen months and enabled\nthem to access digital services and basic\nadministrative systems like PESEL.\nThus, the policies that have previously\nhampered job market integration of\nrefugees in other contexts, such as\ntemporary labour market bans (Fasani,\nFrattini, & Minale, 2021) and forced\ndispersals (Fasani, Frattini, & Minale, 2022),\nhave been avoided.\n\n\nThe high employment rate of refugees\nin Poland covers not only employees,\nbut also entrepreneurs. Five percent of\nUkrainian refugees registered for social\nsecurity have set up a business or work as\nfreelancers. Similar results can be gleaned\nfrom the Multi-Sector Needs Assessment\nPoland 2023 survey results, which show\nthat slightly more than 5% of respondent\nhouseholds receive income from selfemployment or similar activities.\n\n\n\nAll broad sectors of the economy saw an\nincrease in the number of workers with\nUkrainian citizenship and social insurance\nsince 2021, apart from storage and\ntransportation. The number increased\nthe most in manufacturing (almost by\n34 thousand), accommodation and food\n(more than 18 thousand), and wholesale\nand retail trade (more than 18 thousand). <sup>11</sup>\nWhile public data does not distinguish\nbetween refugees entering these sectors\nand pre-2022 Ukrainian workers changing\njobs, it is largely consistent with the MSNA\nPoland 2023 survey, in which the most\nrefugees are employed", "output": {"entities": {"named_data": ["Multi-Sector Needs Assessment\nPoland 2023 survey", "MSNA\nPoland 2023 survey"], "descriptive_data": [], "vague_data": ["public data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 3, "chunk": 0, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Multi-Sector Needs Assessment\nPoland 2023 survey", "label": "NAMED_DATA", "score": 0.817206621170044, "start": 1290, "end": 1338, "probe_score": 0.886, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "public data", "label": "VAGUE_DATA", "score": 0.8191306591033936, "start": 1841, "end": 1852, "probe_score": 0.9754, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "MSNA\nPoland 2023 survey", "label": "NAMED_DATA", "score": 0.8899217247962952, "start": 1994, "end": 2017, "probe_score": 0.8983, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nLebanon: Wheat supply emergency response project (P178866)\n\n\npercent by the end of 2019, female labor force participation in Lebanon is one-third of the male labor force\nparticipation rate. Survey data shows that after the multiple crises affecting Lebanon, the share of job losses\namong women was notably higher than that among men, even though women comprise less than one-third of\nthe total full-time workforce (follow up to 2019 Enterprise Survey, 2020). The crises have impacted women’s\naccess to economic opportunities in different ways; for example, school closures due to the COVID-19 pandemic\nhave made it difficult for women to manage work and family care responsibilities, so some have exited from the\neconomy. Furthermore, the lockdowns and closures due to the COVID-19 pandemic coupled with the broader\neconomic crisis have exacerbated the risks of violence against women. During the first five months of the\nlockdown, significantly more reports of gender-based violence were captured and recorded by different sources.\nThe Gender-Based Violence Information Management System recorded a 3 percent increase in intimate partner\nviolence by current or former partners; a 5 percent rise in physical assault incidents; and a 9 percent uptick in\nincidents occurring in a survivor’s home (UN Women, 2020).\n\n10. **Recurrent political paralysis and weak governance further complicate recovery.** Lebanon is\ncharacterized by poor governance, with only 4 percent of Lebanese report being satisfied or completely satisfied\nwith their government (Arab Barometer). According to the World Bank’s Lebanon Economic Monitor (LEM, Fall\n2021), elite capture persists despite the severity of the crisis, and it has come to threaten the country’s long-term\nstability and social peace. General elections are scheduled for May 15, 2022. Talks with the International Monetary\nFund (IMF) have been relaunched with a mission in January, February, and March 2022, aiming to develop a\nstabilization", "output": {"entities": {"named_data": ["2019 Enterprise Survey", "Gender-Based Violence Information Management System", "Arab Barometer", "Lebanon Economic Monitor"], "descriptive_data": [], "vague_data": ["Survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000019", "page": 13, "chunk": 0, "title": "Lebanon - Wheat Supply Emergency Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/408131653327258940/pdf/Lebanon-Wheat-Supply-Emergency-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Survey data", "label": "VAGUE_DATA", "score": 0.7226759791374207, "start": 209, "end": 220, "probe_score": 0.9968, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2019 Enterprise Survey", "label": "NAMED_DATA", "score": 0.870204508304596, "start": 447, "end": 469, "probe_score": 0.9892, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Gender-Based Violence Information Management System", "label": "NAMED_DATA", "score": 0.8398399949073792, "start": 1056, "end": 1107, "probe_score": 0.9066, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Arab Barometer", "label": "NAMED_DATA", "score": 0.6667986512184143, "start": 1566, "end": 1580, "probe_score": 0.9662, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Lebanon Economic Monitor", "label": "NAMED_DATA", "score": 0.8013119101524353, "start": 1613, "end": 1637, "probe_score": 0.9746, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["M&E data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000012", "page": 29, "chunk": 2, "title": "Azerbaijan - Pilot Reconstruction Project", "pdf_url": "http://documents1.worldbank.org/curated/en/122111468768674538/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "M&E data", "label": "VAGUE_DATA", "score": 0.5883201956748962, "start": 530, "end": 538, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Asylum Levels and Trends in Industrialized Countries, 2008|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|Col10|\n|---|---|---|---|---|---|---|---|---|---|\n|**Table 21. Top-10 nationalities of asylum applicants by country of asylum, 2007 (continued)**<br>Covering 43 industrialized countries which provided monthly data to UNHCR and Italy which is based on annual data.<br>An asterisk (*) denotes between 1 and 4 applications.|**Table 21. Top-10 nationalities of asylum applicants by country of asylum, 2007 (continued)**<br>Covering 43 industrialized countries which provided monthly data to UNHCR and Italy which is based on annual data.<br>An asterisk (*) denotes between 1 and 4 applications.|**Table 21. Top-10 nationalities of asylum applicants by country of asylum, 2007 (continued)**<br>Covering 43 industrialized countries which provided monthly data to UNHCR and Italy which is based on annual data.<br>An asterisk (*) denotes between 1 and 4 applications.|**Table 21. Top-10 nationalities of asylum applicants by country of asylum, 2007 (continued)**<br>Covering 43 industrialized countries which provided monthly data to UNHCR and Italy which is based on annual data.<br>An asterisk (*) denotes between 1 and 4 applications.|**Table 21. Top-10 nationalities of asylum applicants by country of asylum, 2007 (continued)**<br>Covering 43 industrialized countries which provided monthly data to UNHCR and Italy which is based on annual data.<br>An asterisk (*", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["monthly data", "annual data", "monthly data", "annual data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000427", "page": 32, "chunk": 0, "title": "Asylum Levels and Trends in Industrialized Countries 2008 - Statistical Overview of Asylum Applications Lodged in Europe and selected Non-European Countries", "pdf_url": "https://reliefweb.int/attachments/3ab13bab-8d4b-3f86-b90a-e2540078aef7/2F800689DD12C5A78525758300561F85-unhcr-asylumtrends-mar2009.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "monthly data", "label": "VAGUE_DATA", "score": 0.602530300617218, "start": 300, "end": 312, "probe_score": 0.9647, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "annual data", "label": "VAGUE_DATA", "score": 0.6421864032745361, "start": 350, "end": 361, "probe_score": 0.7019, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "monthly data", "label": "VAGUE_DATA", "score": 0.5303484201431274, "start": 570, "end": 582, "probe_score": 0.9459, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "annual data", "label": "VAGUE_DATA", "score": 0.541702926158905, "start": 620, "end": 631, "probe_score": 0.6983, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " for 2001, except exports (2000)\nDefinitions: Mega large firms are defined as those with annual sales net of VAT above UF600,000 (US$17,172,000), large firms have\n\nsales between UF100,000 (US$2,862,000) and UF600,000, medium firms have sales between UF25,000 (US$715,500) and\nUF100,000, small firms have sales between UF2,400 (US$68,688) and UF25,000 and micro firms have sales below UF2,400.\n\n### **_Overall Corporate Financial Performance_**\n\n\nAn analysis of the financial statements of some 500 firms that file annually with the\n\nChilean Superintendence of Firms and Insurance (the SVS) <sup>**1**</sup> [^1: Superintendencia de Valores y Seguros] was carried out. These\n\n\nstatements include detailed financial accounts and notes in a standard format (the Uniformly\n\nCodified Statistical Form or FECU) <sup>**2**</sup> [^2: Ficha Estadística Codificada Uniforme] . Only private limited firms (Sociedades Anónimas SA),\n\n\nlisted and non-listed, are required to file their accounts with the SVS (public firms and closed\n\n\ncompanies are not required to do so, while insurance companies have distinct requirements).\n\n\nBeyond this legal requirement, filing is also useful to get access to external funding, in\n\n\nparticular to capital market financing. Therefore, filing firms are concentrated among Chile’s\n\n\nlargest firms and among those which have issued bonds or listed equity (such as\n\n\ninfrastructure concession companies). They include only a minority of Chile’s large universe\n\n\nof smaller firms, probably the top ones in terms of openness and access to external financing.\n\n\nWhile the sample can be considered representative of Chile’s large, and mega large universe\n\n\nof firms, the same is not true for medium, small and even more so micro firms", "output": {"entities": {"named_data": ["Ficha Estadística Codificada Uniforme"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003059", "page": 3, "chunk": 1, "title": "wps3845", "pdf_url": "https://local/prwp/wps3845.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Ficha Estadística Codificada Uniforme", "label": "NAMED_DATA", "score": 0.8743817806243896, "start": 827, "end": 864, "probe_score": 0.0007, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Value<br>(quantitative or<br>Qualitative)|0|30|Col4|15|\n|---|---|---|---|---|\n|Date achieved|10/16/2001|12/31/2006||12/31/2006|\n|Comments<br>(incl. %<br>achievement)|||||\n\n\n**(b) GEO Indicator(s)**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Indicator|Baseline Value|Original Target<br>Values (from<br>approval<br>documents)|Formally<br>Revised<br>Target<br>Values|Actual Value<br>Achieved at<br>Completion or<br>Target Years|\n|---|---|---|---|---|\n|**Indicator 1 :**|National Medicinal Plant database established by mid PY3.|National Medicinal Plant database established by mid PY3.|National Medicinal Plant database established by mid PY3.|National Medicinal Plant database established by mid PY3.|\n|Value<br>(quantitative or<br>Qualitative)|<br>0|100%||95%|\n|Date achieved|10/16/2001|12/31/2005||12/31/2005|\n|Comments<br>(incl. %<br>achievement)|||||\n|**Indicator 2 :**|By Year 4, 3 medicinal plants for human healthcare have been scientifically<br>validated and shown positive results.|By Year 4, 3 medicinal plants for human healthcare have been scientifically<br>validated and shown positive results.|By Year 4, 3 medicinal plants for human healthcare have been scientifically<br>validated and shown positive", "output": {"entities": {"named_data": ["National Medicinal Plant database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008658", "page": 10, "chunk": 0, "title": "Ethiopia - Conservation and Sustainable Use of Medicinal Plants Project", "pdf_url": "https://documents.worldbank.org/curated/en/148651468246408672/pdf/ICR5080ICR0P0310Box327353B01public1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "National Medicinal Plant database", "label": "NAMED_DATA", "score": 0.5937380194664001, "start": 469, "end": 502, "probe_score": 0.0141, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Emergency Food and Nutrition Security Project (P163559)\n\n\nbe sufficient to provide 2100 calories per person per day, which is the minimum energy requirement\nnecessary to maintain a normal and active life. In the special cases, where people are fleeing from conflict\nthe rations could include high energy biscuits.\n\n\n**_Subcomponent 1.2: Support to Integrated Management of Malnutrition SDR16.2 million (US$22.0_**\n**_million equivalent)_**\n\n\nSupport under this subcomponent will go towards an integrated nutrition security intervention that\nspecifically seeks to meet the urgent nutritional requirements of children under the age of five and both\nthe pregnant women and lactating mothers. To prevent wasting, the nutritional needs of children,\n(including those in the critical 1000‐day window and those between 6‐59 months) as well as those\npregnant and lactating mothers in areas with GAM rates exceeding 15 percent (and for populations\nclassified as being in crisis and emergency levels by the IPC exercise) will be addressed using specialized\nfoods provided through BSF. The nutrition needs of pregnant and lactating mothers as well as those of\nchildren that already suffer from moderate to acute malnutrition will be addressed through TSF. Support\nwill also be extended to the integrated management of SAM through screening and treatment of SAM\nchildren, establishment of Stabilization Centers, reopening of OTPs; procuring, prepositioning and\ndistributing therapeutic nutrition supplies. For improved effectiveness of the nutrition intervention,\nsupport will be provided for WASH, prevention and treatment of common diseases (e.g. malaria, measles\netc.) as well as for protection services targeting the most vulnerable children and women.\n\n\nEligible beneficiaries would be identified based on surveys and predetermined criteria to be\nimplemented through a facilitated community targeting process, which would determine who, for how\nlong, how much and with what types of food the beneficiary would be supported. Given the current\ninsecurity, special attention will be given to the safety", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["surveys"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000038", "page": 72, "chunk": 0, "title": "South Sudan - Emergency Food and Nutrition Project", "pdf_url": "http://documents.worldbank.org/curated/en/713081494122547885/pdf/South-Sudan-PAD-04282017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "surveys", "label": "VAGUE_DATA", "score": 0.5538368821144104, "start": 1829, "end": 1836, "probe_score": 0.8885, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEducation Infrastructure for Resilience (EU Facility for SuTP) (P162004)\n\n\n**<u>Table 2.2. Present Value of Wage Differential and Economic Impact of Students Dropping Out</u>**\n\n\n\n\n\n\n\n\n\n\n\n|Gender|Level at which Students<br>Drop Out|Number of<br>Students who<br>Drop Out|Present Value of<br>Wage<br>Differential in<br>US$|Economic Impact<br>(US$, millions)|\n|---|---|---|---|---|\n|**Gender**|**Level at which Students**<br>**Drop Out**|**A **|**B **|**A × B**|\n|Male|From basic education|937,000|6,251|5,857|\n|Male|From secondary education|44,000|778|34|\n|Female|From basic education|871,000|5,481|4,774|\n|Female|From secondary education|48,000|535|26|\n|**Total**|**From basic education**|**1,808,000**|**— **|**10,631**|\n|**Total**|**From secondary education**|**92,000**|**— **|**60**|\n||**Total**|**1,900,000**|**— **|**10,691**|\n\n\n45. **A Modified Cost-benefit Analysis Approach for Turkey.** Using existing data and information, a\npreliminary and indicative CEA is being offered for illustrative purposes to highlight", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["existing data and information"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000160", "page": 59, "chunk": 0, "title": "Turkey – Education Infrastructure for Resilience (EU Facility for STUP)", "pdf_url": "http://documents1.worldbank.org/curated/en/926851507911156465/pdf/PAD2161-PUBLIC-P162004.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "existing data and information", "label": "VAGUE_DATA", "score": 0.5020912289619446, "start": 921, "end": 950, "probe_score": 0.83, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Cooking in Displacement Settings: Engaging the Private Sector in Non-wood-based Fuel Supply\n\n\nneeds. It is likely that the figure for average energy usage calculated here is low, since in\na displacement setting people are constrained by resources and cook less than they would\nlike to.\n\n\n**•** The survey was conducted in Kakuma I, which is the oldest and most established subcamp within the Kakuma complex. The results seen in Kakuma I may not be fully reflective\nof the stove type, fuel use, cooking spend, income and general expenditures seen across\nthe remaining camp areas. Projections across the full camp complex are provided as\nestimations only.\n\n\n44   movingenergy.earth", "output": {"entities": {"named_data": [], "descriptive_data": ["survey was conducted in Kakuma I"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000683", "page": 44, "chunk": 0, "title": "Cooking in Displacement Settings: Engaging the Private Sector in Non-wood-based Fuel Supply", "pdf_url": "https://reliefweb.int/attachments/6510434a-c2b7-3626-b9b6-4d4c8fdfe6e4/2019-01-22-PatelGross2.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "survey was conducted in Kakuma I", "label": "DESCRIPTIVE_DATA", "score": 0.6275472044944763, "start": 298, "end": 330, "probe_score": 0.8418, "gold": "DATA_MENTION", "gold_tier": "human-final"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "up> ~~<u>𝜕</u>~~ <sup><u>𝜕</u></sup> **𝜕** <sup>**𝜕**</sup> <sup><u>𝜕</u></sup> ~~<u>𝜕</u>~~ **𝜕** 𝜕 <sup>**𝜕**</sup> <sup>**𝜕**</sup> <sup>**𝜕**</sup>\n\n<u>.075)</u> <sup>~~<u>𝜕</u>~~</sup> <sup>**𝜕**</sup> <sup><u>𝜕</u></sup> <u>−</u> <sup><u>𝜕</u></sup> <sup>**𝜕**</sup> <sup><u>𝜕</u></sup> <sup>**𝜕**</sup> <sup>**𝜕**</sup> <sup>**𝜕**</sup> <sup>**𝜕**</sup> <sup>**𝜕**</sup> <sup>**𝜕**</sup>\n\n~~<u>𝜕</u>~~ **𝜕** ~~<u>𝜕</u>~~ ~~<u>𝜕</u>~~ **𝜕** ~~<u>𝜕</", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000819", "page": 55, "chunk": 24, "title": "idu069c261ca03c920460809bbe0343ae9c8918b", "pdf_url": "https://local/prwp/idu069c261ca03c920460809bbe0343ae9c8918b.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Annex 1:** **Project** **Design** **Summary**\n\n**SIERRA LEONE:** **NATIONAL** **SOCIAL ACTION** **PROJECT**\n\n\n. **Hierarchy o.Qbijctives -'**  - . **diator** **r**, t **,P** **jCitidaI** **r!** **As's-umptIons,Y-**\n**Sector-related** **CAS** **Goal:** **Sector** **Indicators:** **Sector/ country reports:** **(from** **Goal** **to Bank** **Mission)**\nMitigate the risk of renewed 1. National conflict/security- - UNHCR/OCHA reports - Continued peace and\n**conflict** **and lay foundation** related indicators - Household Income and regional security\n**for** **poverty reduction and** 2. Inter-regional disparities in Expenditure Surveys - Economic and political\n**improvements** **in nutrition,** I-PRSP & PRSP core - PETS surveys stability\n**health, education** **and** indicators - Strategic Planning and\n**targeting** **the rural** 3. Inter-regional disparities in Action Process (SPP) reports\n**population,** women **and** Popular Benchmarks\n**children.**\n\n\n**Project** **Development** **Outcome** **/** **Impact** **Project reports:** **(from** *", "output": {"entities": {"named_data": ["Inter-regional disparities in Expenditure Surveys", "PETS surveys"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008446", "page": 29, "chunk": 0, "title": "Kenya - Nairobi Water Supply Project", "pdf_url": "https://documents.worldbank.org/curated/en/135101468047697528/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Inter-regional disparities in Expenditure Surveys", "label": "NAMED_DATA", "score": 0.5622888207435608, "start": 590, "end": 639, "probe_score": 0.0005, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PETS surveys", "label": "NAMED_DATA", "score": 0.6322475075721741, "start": 721, "end": 733, "probe_score": 0.0465, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", it has\ndeclined by 2.6 million. This trend is set to\ncontinue. According to the latest Eurostat\nprojections, without migration, the\npopulation (counting all nationalities) aged\n20-64 years would decrease by 4.8 million\nby 2050. <sup>20</sup> [^20: Eurostat data, <u>[https://ec.europa.eu/eurostat/databrowser/view/proj_23np__custom_8710248/bookmark/table?lang=en&bookmarkId=97472dd3-3dd2-](https://ec.europa.eu/eurostat/databrowser/view/proj_23np__custom_8710248/bookmark/table?lang=en&bookmarkId=97472dd3-3dd2-4aca-a51f-15c98be37466)</u>\n**Source:** Eurostat <u>[Statistics | Eurostat (europa.eu)](https://ec.europa.eu/eurostat/databrowser/view/lfsq_pganws__custom_8677828/bookmark/table?lang=en&bookmarkId=06047812-2bde-4cf8-a627-7d63d65f17db)</u> <u>[4aca-a51f-15c98be37466](https://ec.europa.eu/eurostat/databrowser/view/proj_23np__custom_8710248/bookmark/table?lang=en&bookmarkId=97472dd3-3dd2-4aca-a51f-15c98be37466)</u>]\n\n\n© UNHCR / Anna Liminowicz\n\n\n\n19  Statistics Poland data, <u>[https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-](https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-temporary-stay-from-poland-between-2004-2020,8,14.html)</u>\n<u>[temporary-stay-from-poland-between-2004-2020,8,14.html](https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-temporary-stay-from-poland-between-2004-2020,8,14.html)</u>\n20  Eurostat data, <u>[https://ec.europa.eu/eurostat/databrowser/view/proj_23np__custom_8710248/bookmark/table?lang=en&bookmarkId=97472dd3-3dd2-](https://ec.", "output": {"entities": {"named_data": ["Eurostat data", "Statistics Poland data", "Eurostat data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 8, "chunk": 1, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Eurostat data", "label": "NAMED_DATA", "score": 0.6081667542457581, "start": 250, "end": 263, "probe_score": 0.9976, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Statistics Poland data", "label": "NAMED_DATA", "score": 0.7495577335357666, "start": 965, "end": 987, "probe_score": 0.7274, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Eurostat data", "label": "NAMED_DATA", "score": 0.5457086563110352, "start": 1542, "end": 1555, "probe_score": 0.7274, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " on their level of\neducation. Around 77 percent of women have only reached primary education which means that young\nwomen are less likely to compete in the labor market. The lack of formal jobs in refugee settlements leads\n\n\n11 This index reflects gender-based inequalities in three dimensions – reproductive health, empowerment, and economic activity.\n[http://hdr.undp.org/sites/all/themes/hdr_theme/country-notes/UGA.pdf.](http://hdr.undp.org/sites/all/themes/hdr_theme/country-notes/UGA.pdf)\n12 Uganda Demographic and Health Survey (2016), Uganda Bureau of Statistics (UBOS) and ICF.\n13 Uganda Violence Against Children Survey, Ministry of Gender, Labour and Social Development (2015).\n14 UNICEF: Situation Analysis of Children in Uganda,, Ministry of Gender, Labour and Social Development, 2015\n15 Government of Uganda: Violence Against Children Survey (VACS) Report,, Ministry of Gender, Labour and Social Development,\n2018\n16 Uganda Demographic and Health Survey (2016), Uganda Bureau of Statistics (UBOS) and ICF\n17 UNHCR, 2016, 5-Year Interagency SGBV Strategy, Uganda\n_18_ Northern Uganda and West Nile Humanitarian Development Report – Second Issue- January-February 2018, UN Agencies.\n_[http://ug.one.un.org/sites/default/files/documents/UNACNorthern%20Uganda%20and%20West%20Nile%20Humanitarian%20and](http://ug.one.un.org/sites/default/files/documents/UNACNorthern%20Uganda%20and%20West%20Nile%20Humanitarian%20and%20Development%20Report%20-January-February%202018.pdf)_\n_", "output": {"entities": {"named_data": ["Uganda Demographic and Health Survey", "Uganda Violence Against Children Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 14, "chunk": 2, "title": "Uganda - Roads and Bridges in the Refugee Hosting Districts/Koboko-Yumbe-Moyo Road Corridor Project", "pdf_url": "http://documents.worldbank.org/curated/en/834931600048847296/pdf/Uganda-Roads-and-Bridges-in-the-Refugee-Hosting-Districts-Koboko-Yumbe-Moyo-Road-Corridor-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Uganda Demographic and Health Survey", "label": "NAMED_DATA", "score": 0.7517164945602417, "start": 498, "end": 534, "probe_score": 0.9971, "gold": "DATA_MENTION", "gold_tier": "flip"}, {"text": "Uganda Violence Against Children Survey", "label": "NAMED_DATA", "score": 0.7393099069595337, "start": 590, "end": 629, "probe_score": 0.9911, "gold": "DATA_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " <br> <br>75%<br>97%<br>97%<br> <br> <br>Madagascar<br>DVP<br> <br>42%<br>68%<br>100%<br>100%<br>100%<br> <br>Malawi<br>DVP<br> <br> <br>8%<br>30%<br>29%<br>34%<br> <br>Mali<br>DVP<br> <br>41%<br>67%<br>66%<br>73%<br> <br> <br>Niger<br>DVP<br> <br> <br>73%<br>66%<br>73%<br> <br> <br>Nigeria<br>DVP<br> <br>10%<br>0%<br>4%<br>6%<br>18%<br> <br>Senegal<br>DVP<br> <br> <br>79%<br>66%<br>73%<br>94%<br> <br>Seychelles<br>DVP<br> <br> <br>60%<br>70%<br>69%<br>65%<br>South Africa<br>DVP<br> <br>0%<br>6%<br>30%<br>28%<br>25%<br>Swaziland<br>DVP<br> <br> <br>86%<br>84%<br>84%<br>89%<br> <br>Togo<", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007249", "page": 47, "chunk": 42, "title": "wps8297", "pdf_url": "https://local/prwp/wps8297.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*\n**provinces** . This phased implementation will enable the implementation team to: (i) assess the\noperational processes for the implementation of the targeting and registration processes, in terms of\norganizational capacity, time and costs to inform the subsequent roll-out; and (ii) test the targeting\nefficiency of the proposed CBT and PMT combination, given the prevalence of poverty and the lack of\nreliable consumption data. Lessons from the first eight communes will inform the roll-out in the next\neight communes.\n\n\n**_Sub-component 2.2. Core modules of the Management Information System (US$1.5 million_**\n**_equivalent)_**\n\n\n40. **This sub-component will support the development of basic core modules of the**\n**Management Information System to support the delivery mechanisms of a basic social safety**\n**net system** . These modules will be developed for the cash transfer program and will use a unique\nindividual identification number for each beneficiary. They will include key social program\n\n\n12", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["consumption data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000157", "page": 22, "chunk": 2, "title": "Burundi - Social Safety Nets Project", "pdf_url": "http://documents1.worldbank.org/curated/en/900951482030099834/pdf/1482030098559-000A10458-PAD-Burundi-SSN-11282016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "consumption data", "label": "VAGUE_DATA", "score": 0.7214356660842896, "start": 414, "end": 430, "probe_score": 0.1756, "gold": "NON_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "s and operation manual to <sup>ensure</sup>\nadequate transparency in their operations\n\n\n\n4. Limuted capacity NaCSA has no staff development program, <sup>and</sup> Capacity building would be a major component <sup>of</sup>\n\n\n\nfor sub-project hence there are no training opportunuties <sup>for staff</sup> NSAP. Thus activity would benefit NaCSA <sup>staff at</sup>\n\n\n\npreparation, In addition, except for skills training for <sup>specific</sup> all levels, communities, implementing partners <sup>**in**</sup>\n\n\n\nimplementation, sub-projects, there is no capacity building for cases where they would be used, district <sup>level</sup>\n\n\n\nmonitoring and Implementing Partners and communities <sup>There</sup> <sup>is</sup> authorities and other relevant stakeholders.\nevaluation as little evidence to show that even the few training Implementing Partners would be given clear\n\nwell as for activities are executed fully. guidelines on their role in capacity building\n\n\n\nproject activities. Momtoring of these capacity <sup>building</sup>\nmanagement. activities would be intense.\n\n\n\n5. Limited Line mimustnes' involvement **in** the project <sup>has</sup> Extensive consultations took place with line\n\n\n\ncollaboration been limited to wnting letters **in** support <sup>of</sup> ministry representatives during project <sup>preparation.</sup>\n\n\n\nand cooperation sub-projects or launching ceremonies. Weak Line ministries would be part of sub-project\n\n\n\n**with** **line** intra-mimstenal coordination and an apparent approval committees Formal MOUs would <sup", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000096", "page": 62, "chunk": 2, "title": "Guinea - Multi-Sectoral AIDS Project (MAP)", "pdf_url": "http://documents1.worldbank.org/curated/en/570211468749964429/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Survey of\n\nEnterprises (SLLSE), described in Suresh de Mel et al. (2009). Start-up capital includes land, buildings,\n\nmachinery, and working capital. We see a wide range of initial start-up levels of capital, with 10 percent\n\nof firms starting with US$100 or less, and 23 percent with $500 or less. David McKenzie and Christopher\n\nWoodruff (2006) show similarly that there is a range of different starting capital levels for Mexican\n\nmicroenterprises, with many starting with low amounts.\n\n\n15", "output": {"entities": {"named_data": ["Survey of\n\nEnterprises"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005953", "page": 16, "chunk": 1, "title": "wps6835", "pdf_url": "https://local/prwp/wps6835.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Survey of\n\nEnterprises", "label": "NAMED_DATA", "score": 0.8462398648262024, "start": 1, "end": 23, "probe_score": 0.3155, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|6,993<br>|1,807<br>|1,866<br>|\n|2003<br>|5,435<br>|742<br>|6,177<br>|1,202<br>|1,257<br>|\n|2004<br>|4,986<br>|437<br>|5,423<br>|751<br>|826<br>|\n|2005<br>|5,254<br>|138<br>|5,392<br>|533<br>|584<br>|\n|2006<br>|4,865<br>|87<br>|4,952<br>|N/A<br>|N/A<br>|\n|Total<br>|30,875<br>|3,574<br>|34,449|5,921|6,249|\n\n\n\nBancomext has two main programs: Crediexporta and the Technical Assistance Program\n( _Programa de Asistencia Técnica_ —PAT). Crediexporta is Bancomext’s most important\nfinancing program mainly targeted to SMEs. The program has five different modalities: (i)\n\n\n7", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004378", "page": 8, "chunk": 2, "title": "wps5186", "pdf_url": "https://local/prwp/wps5186.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " refuge in neighboring countries.\n\n\n**Conflict has resulted into a near collapse of the economy.** Currently, the country exhibits all the\nsigns of macroeconomic collapse. There have been sharp declines in output, and a spike in the parallel\nexchange market premium. The economy is expected to further contract by about 11 percent with both\nthe oil and non‐oil sectors expected to decrease. The fiscal deficit remains wide, although real magnitudes\nare difficult to estimate given the hyperinflation and lack of real time data. Based on the 2016/17 budget,\nthe fiscal deficit is estimated at about 14 percent of GDP. Export revenues decreased due to declining oil\nprices and lower oil production. There is an accelerated depreciation of the pound, with the SSP\ndepreciating on the parallel market from SSP 18.5 per US dollar in December 2015 to reach SSP 110 per\nUS dollar in March, 2017. This follows the move to a managed floating exchange rate from a fixed\nexchange rate.\n\n\n**Drought that was experienced in parts of the country over the last cropping season, acting in**\n**concert with several other factors** <sup>**28**</sup> [^28: These include: (i) the current drought in the Horn of Africa, which has reduced overall output in primary exporters Uganda and\nSudan and limited the food imports that South Sudan can viably access; (ii) high food prices mainly driven by depreciation of the\nlocal currency and a very high inflation rate; (iii) declines in crop production from already low levels due to insecurity and\ndisplacement of farmers; and (iv) destabilization of markets due to restrictions to movement in commodity‐supply corridors.] **, has led to extreme scarcity of food and famine in some parts of the**\n**country.** Preliminary findings from the FAO/WFP CFSAM show that partly due to the drought, overall food\nproduction for 2016 (the last harvests of which came in January", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["real time data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000038", "page": 69, "chunk": 1, "title": "South Sudan - Emergency Food and Nutrition Project", "pdf_url": "http://documents.worldbank.org/curated/en/713081494122547885/pdf/South-Sudan-PAD-04282017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "real time data", "label": "VAGUE_DATA", "score": 0.5285136103630066, "start": 512, "end": 526, "probe_score": 0.0008, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " poverty rate, as measured by the\nproportion of population living under the international poverty line of US$1.90 purchasing power parity\n(PPP) per day, has increased substantially from 51 percent in 2009 to 82 percent in 2016. <sup>9</sup> Internally\ndisplaced persons (IDPs) are particularly impoverished where 91 percent fall below the poverty line\ncompared with 86 percent in rural and 75 percent in urban areas. Among IDP camps, Bentiu Protection of\nCivilian (POC) site has the highest poverty rate. <sup>10</sup> The sharp increase in poverty correlates with the\nescalation of violent conflict as well as the macroeconomic crisis and the loss of buying power due to\ndramatic inflation that reached 170 percent in October 2019. Poverty rates were (and remain) the highest\n(an unprecedented over 90 percent) in the states of the Greater Upper Nile region, Eastern Equatoria,\nNorthern Bahr el Ghazal, and Western Bahr el Ghazal. <sup>11</sup> Unsurprisingly, Western Equatoria, which was less\naffected by the conflict, is the only state that retained more stable poverty rate. Poverty in South Sudan\nis not only monetary but multidimensional, and much of the population has remained, returned, or sunk\ndeeper into a state of destitution with extremely low rates of food security and access to basic services. <sup>12</sup>\nChronic and widespread poverty contributes to South Sudan’s ranking of 186 out of 189 countries in the\nHuman Development Index (HDI) 2019, with a life expectancy of only 58 years compared to the global\naverage of 72. <sup>13</sup>\n\n\n5. **The cumulative effects of years of violent conflict, natural disasters, and economic crisis have**\n**taken a significant toll.** As of April 2020, nearly 3.9 million people (over a third of the country", "output": {"entities": {"named_data": ["Human Development Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 15, "chunk": 1, "title": "South Sudan - Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/824121596765983121/pdf/South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Human Development Index", "label": "NAMED_DATA", "score": 0.8055703639984131, "start": 1429, "end": 1452, "probe_score": 0.9851, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad Energy Access Scale Up Project (P174495)\n\n\nfor bulk procurement, for instance of popular-size solar water pumps, will be explored to reduce costs\nthrough economies of scale. Furthermore, the subcomponent will support related awareness-raising\nactivities and technical assistance for the adoption of technical standards.\n\n46. In addition, the subcomponent will provide financing to electrify about 1,000,000 households,\nincluding about 200,000 households residing in refugee camps and host communities and with targeted\nactions to support female-headed ones. The project design is informed by the outcomes of the Survey on\nExpenditure of Households and Informal Sector in Chad ( _Enquête sur la Consommation des Ménages et le_\n_Secteur Informel au Tchad_ [ECOSIT 4] 2019) and a survey on ability and willingness of rural households to\npay for electricity services, conducted in three provinces of Chad in the first half of 2021. <sup>24</sup> [^24: Select outcomes of the survey are in annex 6.] The outcomes\ninclude the following information: (a) 70 percent of the rural population and 27 percent of the urban\npopulation have financial constraints to spend more than US$10 per month for electricity; <sup>25</sup> [^25: Assuming that a household can spend up to 5 percent of its total expenditure for electricity.] (b) about 70\npercent of rural households are interested in acquiring Tier 1 SHSs, assuming that these are of good quality\nand can be made available at the price equivalent to up to three months of household expenditures on\nlighting and phone charging, that is about CFAF 10,000 (US$17.4 equivalent).\n\n47. In an effort to kick-start the market and discover market prices, the first intervention will be\norganized in the form of bulk procurement of up to 200,000 Tier 1 SHSs, split into several lots to attract\nreputable suppliers to the Chad SHS market. These SHSs will be sold in cash with the cost split between", "output": {"entities": {"named_data": [], "descriptive_data": ["survey on ability and willingness of rural households"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 28, "chunk": 0, "title": "Chad - Energy Access Scale Up Project", "pdf_url": "http://documents.worldbank.org/curated/en/860701648216750651/pdf/Chad-Energy-Access-Scale-Up-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "survey on ability and willingness of rural households", "label": "DESCRIPTIVE_DATA", "score": 0.7308420538902283, "start": 801, "end": 854, "probe_score": 0.9382, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "rievance-redress-service) For\ninformation on how to submit complaints to the World Bank Inspection Panel, please visit _[www.inspectionpanel.org](http://www.inspectionpanel.org/)_ .\n\n\n**<mark>VII.</mark>** **<mark>KEY RISKS</mark>**\n\n\n85. **The overall residual risk to achieving the PDO is substantial, with political and governance and macroeconomic**\n**risks rated as high and fiduciary and environment and social risks rated as substantial.**\n\n86. **Political and governance risks are high.** The country is experiencing a socioeconomic crisis that has evolved into\npolitical and social upheaval, potentially affecting the execution of this project., as political instability increased and\nelite capture deepened, paralyzing policy reforms, as the decision-making process in the country has been impacted\nto a great extent by continuous interruptions and deadlocks due to political and sectarian divisions. This risk will be\npartially mitigated by focusing the activities of the project in areas of high concentration of target population.\n\n~~87.~~ **Macroeconomic risk is rated high:** The country is facing a financial crisis, a deep recession, and political and social\nupheaval, as well as the impact of the COVID-19 pandemic. Real GDP has been declining in the last years whereas\nmonetary and financial turmoil along with surging inflation has driven crisis conditions, with the exchange rate further\ndeteriorated in 2021. Mitigation of macroeconomic risks will only come about through the implementation of a\ncomprehensive reform plan that will gain the support of the Lebanese people and the international community, and\nthat will have significant financing behind it.\n\n88. **Fiduciary risks are Substantial.** The residual procurement risk is Substantial (see para 64) and residual FM risk is\nModerate (see para 54). Based on the FM assessment, the FM risk", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000000", "page": 41, "chunk": 1, "title": "Lebanon - Strengthening Lebanon's COVID-19 Response under the COVID-19 Strategic Preparedness and Response Program (SPRP)", "pdf_url": "http://documents.worldbank.org/curated/en/099410007282239961/pdf/BOSIB09c1bfedd05c098380dc89cfe988b8.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " <sup>13</sup> [^13: _[http://pubdocs.worldbank.org/en/689221633557476771/Refugees-in-Chad-The-Road-Forward](http://pubdocs.worldbank.org/en/689221633557476771/Refugees-in-Chad-The-Road-Forward)_] Further details on the refugee and host community population and related project activities\ncan be found in Section II (Project Description) and annex 2.\n\n\n**C.** **Relationship to CPF and Relevance to Higher-Level Objectives**\n\n23. **The project is aligned with the WBG’s Country Partnership Framework (CPF) for the Republic of**\n**Chad for the period of FY16–20** <sup>14</sup> [^14: Report No. 95277-TD, discussed by the Board of Executive Directors on December 10, 2015.] **as well as the WBG’s Country Engagement Note (CEN) for the period**\n**of FY23--FY24 under preparation.** The CPF recognizes the importance of the energy sector as part of\nEngagement Theme 1 focused on strengthening the management of public resources, which includes the\nenergy sector while the CEN envisages investment in energy sector under Focus Area 3 (Resilient\nProductivity and Connectivity) to address of the greatest binding constraint to Chad’s growth and broader\neconomic activity. In addition, the project is expected to support Chad to align with the Next Generation\nAfrica Climate Business Plan, which provides a blueprint to help Sub-Saharan African economies achieve\nlow-carbon and climate-resilient outcomes.\n\n24. **The project will support the implementation of Chad’s long-term development strategy ‘Vision**\n**2030:** **_Le Tchad que nous voulons_** **’.** Given the important role of electricity access in improving people’s\nquality of life, the project will support the implementation of the strategy that is implemented through\nconsecutive five-year development plans. The strategy aims to improve the quality of life of Chadians by\ndeveloping human", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 21, "chunk": 1, "title": "Chad - Energy Access Scale Up Project", "pdf_url": "http://documents.worldbank.org/curated/en/860701648216750651/pdf/Chad-Energy-Access-Scale-Up-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the specific share attribu-_\n_ted to CP._\n\n**•** **“CP component (target > CP PIN**\n**target)”** = Funding reported under the\nProtection sector where Child Protection\nactivities is one component and is coupled\nwith activities from different sectors\nnot exclusively focusing on children, but\nCP activities are clearly identified. One\nexample is gender-based violence and CP\nactivities focusing on women and children.\n\n**•** **“Multiple sectors (shared)”** = Funding\nwith a CP component but with multiple\ndestination sectors – as no disaggregated\nsectoral data is available, the share of\nfunding for CP is unknown.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n**50** **•** <sup>**STILL UNPROTECTED: HUMANITARIAN FUNDING FOR CHILD PROTECTION**</sup> **STILL UNPROTECTED: HUMANITARIAN FUNDING FOR CHILD PROTECTION** **•** **51**", "output": {"entities": {"named_data": [], "descriptive_data": ["disaggregated\nsectoral data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001376", "page": 25, "chunk": 4, "title": "Still Unprotected: Humanitarian Funding for Child protection", "pdf_url": "https://reliefweb.int/attachments/d504b60b-9661-3eec-9f8a-d89117a26098/STC_still_unprotected_report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "disaggregated\nsectoral data", "label": "DESCRIPTIVE_DATA", "score": 0.8643822073936462, "start": 532, "end": 559, "probe_score": 0.1835, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "towards offering tax breaks or subsidies to foreign investors, as such policies are not effec\n\ntive at attracting foreign investors or worthwhile. <sup>15</sup> Rather there should be an engagement\n\n\nin investment promotion efforts aiming at reducing the costs of FDI by providing informa\n\ntion on business conditions and helping foreign investors deal with bureaucratic procedures\n\n\n(UNCTAD, 2018; World Bank, 2018). Thus, the role of investment promotion agencies in\n\n\nfacilitating inward FDI can be vital.\n\n\n15For instance, Haskel et al. (2007) examine within-sector productivity spillovers associated with FDI using\nUK data and conclude that it is quite easy to overpay when extending fiscal incentives to foreign investors.\n\n\n14", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["UK data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000066", "page": 15, "chunk": 0, "title": "are inflows of fdi good for russian exporters", "pdf_url": "https://local/prwp/are-inflows-of-fdi-good-for-russian-exporters.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "UK data", "label": "VAGUE_DATA", "score": 0.640891969203949, "start": 620, "end": 627, "probe_score": 0.7462, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " steering committee will meet at least\ntwice a year on invitation of its president or vice-president.\n\n119. As part of its coordination mandate to extend and strengthen social protection, the **SEP** will facilitate technical\ncoordination between the project activities and those of other government agents within the CNPS at central level and\nthe CPPS at provincial level.\n\n120. The National Office for the Protection of Refugees and Stateless, **ONPRA**, will coordinate and oversee activities\nwith beneficiaries being refugees and host communities. As part of their mandate, they will ensure that refugees and\nhost communities do not face barriers in integrating national social protection plans and programs.\n\n\n121. **Local administrations** will support the project in mobilizing households for the registration and enrolment\nprocesses and will be the main actor of the geographic targeting of the project. Local administrations will prioritize\ncommunes for project implementation based on existing poverty data and their own knowledge.\n\n\n122. **Local communities** will be represented in the project in the form of Project Community Committees at _colline_\nlevel. Their role will be mobilizing beneficiaries for the registration and enrolment processes, assisting on payment days\nand as one of the entry points for grievance redress. Local communities will also participate at the validation processes\nfor beneficiary targeting minimizing inclusion and exclusion errors.\n\n\nPage 38 of 86", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["poverty data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000130", "page": 42, "chunk": 1, "title": "Burundi - Cash for Jobs Project", "pdf_url": "http://documents1.worldbank.org/curated/en/768621641923064747/pdf/Burundi-Cash-for-Jobs-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "poverty data", "label": "VAGUE_DATA", "score": 0.7742266654968262, "start": 1004, "end": 1016, "probe_score": 0.1649, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "years of education, matter for individual earnings and economic growth (e.g., Hanushek and\n\n\nWoessmann 2008). Therefore, even where the number of years of education completed is not\n\n\nadversely affected by civil conflict, such conflict may have deleterious effects on human capital if\n\n\nthe quality of learning deteriorates.\n\n\nFrom an international perspective, this paper contributes to unpacking the complexity that lies\n\n\nbehind the generic term civil conflict. The idiosyncrasies of each conflict highlight the need for\n\n\nadditional research on the impacts of different conflicts to shed light on the range of potential\n\n\neffects rather than a focus on extreme, but thankfully rare, instances.\n\n\nFrom a policy perspective, the present findings call for measures that aim to protect school\n\n\nchildren and teachers from being directly targeted by combatants. As shown in this paper, even\n\n\nwhere primary education systems appear very resilient to surrounding violence, direct targeting of\n\n\nschools, however mild (e.g., brief abductions of pupils and teachers for indoctrination purposes),\n\n\nhas adverse effects on schooling, especially for girls.\n\n\n_NOTES_\n\n\nThe author thanks INSEC for sharing their conflict data and Martha Ainsworth, Quy-Toan Do,\n\n\nHelge Holterman, Steve McIntosh, Gudrun Østby, Kati Schindler, Olga Shemyakina, Helen\n\n\nSimpson, Sarah Smith, Frank Windmeijer, Hassan Zaman, the World Bank’s Nepal Country\n\n\nDirector's office, and participants at two Gender and Conflict Research Workshops at the World\n\n\nBank (Washington) and Peace Research Institute Oslo for their useful comments. The author also\n\n\nthanks three anonymous referees for their valuable comments and suggestions. This work was\n\n\n26", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["conflict data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005619", "page": 27, "chunk": 0, "title": "wps6468", "pdf_url": "https://local/prwp/wps6468.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "conflict data", "label": "VAGUE_DATA", "score": 0.6794712543487549, "start": 1204, "end": 1217, "probe_score": 0.9813, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " be\n\naccompanied by teacher training.\n\nSchool-based management training may not M Training will be carefully designed and implemented with\nchange behavior. input from trainees on expected outcomes, and close\nsupervision by inspectors and advisory-teachers.\n\nDonor funding may not materialize, or materialize M The CNOSEGE will be strengthened to conduct donor\nas planned. visits and gamer support through marketing of the reform.\n\nDespite the new curriculum, teachers continue as M Awareness campaign for teachers to focus on the whole\nin the old system to emphasize subjects which are curriculum and also the tests will move from being\ntested. competitive examinations to assessments.\n\n**Overall Risk Rating** S\n\n\nRisk Rating - H (High Risk), S (Substantial Risk), M (Modest Risk). N(Negligible or Low Risk)\n\n\nIn light of the overall macro-economic conditions of the country, the risk rating is categorized as an \"S\".\n\n\n**3. Possible Controversial Aspects**\n\nThis project has no controversial aspects.\n\n\nG. MAIN **CREDIT** CONDITIONS\n\n\n1. **Effectiveness Condition**\n\nGovernment has deposited the project counterpart funds for the first semester in the Central Bank.\n\n\n**2. Other** [classify according to covenant types used in the Legal Agreements.]", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000049", "page": 26, "chunk": 1, "title": "Croatia - Reconstruction Project for Eastern Slavonia, Baranja and Western Srijem", "pdf_url": "http://documents1.worldbank.org/curated/en/347691468746725804/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "u>Difference</u>\n<u><mark>Lending to states (share)</mark></u> <u><mark>0.0</mark></u> <u><mark>0.0</mark></u> <u><mark>0.2</mark></u> <u><mark>0.2</mark></u> <u><mark>-1.22</mark></u>\n<u><mark>Assets (logs)</mark></u> <u><mark>12</mark></u> <u><mark>1.8</mark></u> <u><mark>12.4</mark></u> <u><mark>1.5</mark></u> <u><mark>-0.22</mark></u>\n<mark>Capital (%)</mark> <mark>11</mark> <u><mark>3.8</mark></u> <u><mark>9.6</mark></u> <u><mark>6.8</mark></u> <u><mark>0.18</mark></u>\n<mark>Liquidity (%)</mark> <mark>6.9</mark> <u><mark>2.3</mark></u> <u><mark>6.4</mark></u> <u><mark>3</mark></u> <u><mark>0", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000391", "page": 68, "chunk": 1, "title": "expansionary austerity reallocating credit amid fiscal consolidation", "pdf_url": "https://local/prwp/expansionary-austerity-reallocating-credit-amid-fiscal-consolidation.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<mark>Ethiopia, and around 40 percent in Nigeria use inorganic fertilizer, which may be more</mark>\n<mark>widespread than common assumptions about smallholder agriculture posit.</mark>\n\nSignificant proportions of farmers use agro-chemicals too, with over 30 percent of households in\nEthiopia and Nigeria using some on their plots. Other studies using the same data find high rates\nof chemical use in storage of harvested farm output in the set of eastern and southern African\nLSMS-ISA countries (Kaminski and Christiaensen 2014), suggesting that the statistics we report\nrepresent lower bounds on total chemical use by farmers across agricultural operations. Because\nthe use of pesticides, herbicides, and fungicides is perhaps more widespread than is widely\nrecognized and because chemicals banned in other countries due to their toxicity are being used\nin SSA (Williamson et al. 2008), this descriptive finding in particular seems to invite further\nresearch to explore the prospective environmental and human health effects, as well as the\nproductivity benefits, of non-trivial agro-chemicals use in African agriculture.\n\n**_2._** **_The incidence of irrigation and mechanization remains quite small._**\n\nWhile agro-chemical and inorganic fertilizer use appear greater, in some cases, than has been\nwidely acknowledged to date, the prevalence of irrigation and tractor use is negligible, just as the\nconventional wisdom and macro-level statistics suggest. AQUASTAT/FAO and World Bank\nestimates report that less than 1 percent of land under cultivation in these countries is irrigated.\nThe household level data we analyze suggest that 1-3 percent of land cultivated by smallholders\nis under irrigation, and that no more than 10 percent of households have any form of water\ncontrol on agricultural plots. Of course, because the LSMS-ISA household data do not include\nlarge scale commercial farms run as firms rather than as households, these figures are likely\nsomewhat downwardly biased as estimates of overall agricultural production", "output": {"entities": {"named_data": [], "descriptive_data": ["household level data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002363", "page": 55, "chunk": 0, "title": "understanding the agricultural input landscape in sub saharan africa recent plot household and community level evidence", "pdf_url": "https://local/prwp/understanding-the-agricultural-input-landscape-in-sub-saharan-africa-recent-plot-household-and-community-level-evidence.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "household level data", "label": "DESCRIPTIVE_DATA", "score": 0.7201108336448669, "start": 1591, "end": 1611, "probe_score": 0.9663, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nagainst them.\n\nOn January 22, it became known that the Federal Service for Supervision of Communications, Information\nTechnology and Mass Media (Roskomnadzor) refused to register the **news agency QHA** . The notice of\nrefusal of registration (Annex 3) does not clarify on what basis the decision was made - Roscomnadzor refers\nonly to Article 13 of the Law On the Media, which only states that the competent authorities have the right to\nrefuse the registration under certain conditions.\n\nOn January 26, at the **ATR channel** there was a search with the involvement of a large number of armed\nriot police, which led to a short-term suspension of analogue broadcasting and paralyzed for a day the work\nof the news service of ATR. The grounds for the search was the operational data that the TV channel has\nmaterials that are relevant to the investigation into the criminal case No.2014467091 on the death of two\npeople during the events of February 26, 2014 in front of the Supreme Council of the ARC, while the\nadministration of the channel at the request of investigators reported that all the materials were destroyed\n(Annex 2).\n\n\nAt the same time, there were no reasonable grounds for the involvement in the investigative actions\nperformed by the Investigative Committee of the Russian Federation and the Center for Combating\nExtremism with the armed riot police. In carrying out the investigations there were facts of hindering\njournalistic activities of channel employees.\n\n\nThe OSCE Representative on Freedom of the Media Dunja Mijatovic condemned the raid of the security\nforces of Crimea to the television company ATR in Simferopol, considering it an interference in the work of\nthe free and independent media.\n\n\nOn January 28, prior to the court hearing related to the citizenship of Alexander Kolchenko, the cameraman\nof the **Chernomorskaya TV channel** was not allowed in the building of the Kiev District Court of\nSimferopol. The security motivated its refusal", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["operational data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001289", "page": 5, "chunk": 1, "title": "Crimean Field Mission on Human Rights: Review of the Situation in Crimea (January 2015) - Analytical Review", "pdf_url": "https://reliefweb.int/attachments/c5ee58f9-2fcc-3e9d-b2fd-447ff06f6553/Crimea_Field_Mission_Report_January_2015_Eng.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "operational data", "label": "VAGUE_DATA", "score": 0.5657731890678406, "start": 767, "end": 783, "probe_score": 0.926, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", and Zenou, 2010;\nÅslund and Rooth, 2007), and Switzerland\n(Müller, Pannatier, and Viarengo, 2022),\nas well as the previously described crosscountry study. This could in principle stem\nfrom scarring on an individual level from\nweak initial opportunities, or persistently\nweak local labour market combined with\nimperfect geographic mobility. The effects\nare hard to disentangle, while Åslund and\nRooth (2007) find some indication that both\nphenomena are at play, Godøy (2017) finds\nevidence only for persistently weak local\nlabour markets.\n\n\n##### Migrants and refugees dispersed away from ethnic enclaves experience weaker labour market inclusion outcomes, and vice versa.\n\nCo-nationals can provide important\ninformation to refugees about employment\nopportunities. In Germany, Battisti, Peri,\nand Romiti (2022) found that immigrants\ninitially located in places with more conationals, as well as well as refugees and\nrepatriated ethnic Germans dispersed to\nsuch places, are more likely to be employed\nin the first 3 years. It was found, however,\nthat these groups had lower probability of\ninvesting in human capital. In Swiss data,\nMartén, Hainmueller, and Hangartner\n(2019) found that refugees dispersed to\nlocations with more co-nationals are more\nlikely to find work, especially in the first 3\nyears. In Danish data, Damm (2014) found that\nhigher skill levels of non-Western immigrant\nmen in an area raises employment probability\nof refugee men, while higher employment\nrates of their co-national men raises their\nearnings. Also in Danish data, Damm (2009)\nfound that larger size of ethnic network in an\narea increases earnings of refugees.\nIn Swedish data, Edin, Fredriksson,\nand Aslund (2003) found that refugees\ndispersed to areas with more co-nationals\nexperience higher earnings.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\nKingdom,", "output": {"entities": {"named_data": [], "descriptive_data": ["Swiss data", "Danish data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 12, "chunk": 2, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Swiss data", "label": "DESCRIPTIVE_DATA", "score": 0.5999523401260376, "start": 1120, "end": 1130, "probe_score": 0.9927, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Danish data", "label": "DESCRIPTIVE_DATA", "score": 0.5668795108795166, "start": 1307, "end": 1318, "probe_score": 0.9708, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nTo account for refugees impact on\neconomy shocks for economy were\ncalibrated according to existing data.\nAs the refugees started coming to Poland\nby the end of February and in March\n2022 it was assumed that their impact\non the economy should be seen starting\nfrom the second quarter of 2022. As such\ntheir primary impact on yearly data was\ndivided as between 2022 and 2023 setting\n¾ of it in 2022 and ¼ in 2023. The total\nnumber of refugees was set according to\nthe newest data from the PESEL registry\n(Chart 3. in Chapter 1). Their employment\nwas calibrated to match data presented\nin Chapter 2. Changes in population and\n\n\n\nlabour supply in Poland were offset by\nequivalent changes for Eastern Europe\nregion <sup>41</sup> [^41: Aggregate region in model consisting of Ukraine, Russia, Belarus, Moldova, Czechia, Slovakia, Hungary, Romania and Bulgaria.] . It was also assumed that refugees\nshould have higher spending needs which\nmeans a lower saving rate than natives.\nMoreover, data shows that it is partially\nfinanced by savings they have in Ukrainian\nbanks which was calibrated as them having\nnegative saving rate while being offset\nby lowering investment levels in Eastern\nEurope <sup>42</sup> [^42: In other words it was assumed that money that would be spent e.g. through credit action for investments in Eastern Europe were spent for\nconsumption in Poland.] . Lastly, their productivity may\ndiffer from productivity of natives (Box 2)\nwhich also was taken into account.\nIn total there were three major sources\nof uncertainty: total level of employment,\nproductivity, and impact on consumption.\n\n\n\nwould increase GDP by 0.9-1.3% – the mid\nto higher bound of our estimate.\nThird, Urban (2022) uses an Oxford\nEconomics model to estimate the impact of\nUkrainian refugees on the potential GDP by\n2030", "output": {"entities": {"named_data": ["PESEL registry"], "descriptive_data": [], "vague_data": ["yearly data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 17, "chunk": 0, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "yearly data", "label": "VAGUE_DATA", "score": 0.6118190884590149, "start": 476, "end": 487, "probe_score": 0.8706, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "PESEL registry", "label": "NAMED_DATA", "score": 0.9067140221595764, "start": 639, "end": 653, "probe_score": 0.9697, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|Table A24<br>Girl survey items Q1‐Q6: Sexual Abuse or Exploitation<br>(Ever; and Conditional Upon Ever, Happened in Past 12 Months)|Col2|Col3|Col4|Col5|\n|---|---|---|---|---|\n|**Question**|**Response options**|**Response options**|**Response options**|**Total**|\n|**Question**|**No**|**Yes**|**DK**|**DK**|\n|Q1. Has anyone, male or female, ever touched<br>you in a sexual way without your permission,<br>but did not try and force you to have sex?|863<br>351<br>2 <br>(70.97%)<br>(28.87%)<br>(0.16%)|863<br>351<br>2 <br>(70.97%)<br>(28.87%)<br>(0.16%)|863<br>351<br>2 <br>(70.97%)<br>(28.87%)<br>(0.16%)|1216|\n|_Q1a. Has this happened in the past 12_<br>_months?_|46<br>305<br>0|46<br>305<br>0|46<br>305<br>0|351|\n|_Q", "output": {"entities": {"named_data": [], "descriptive_data": ["Girl survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006808", "page": 71, "chunk": 0, "title": "wps7797", "pdf_url": "https://local/prwp/wps7797.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Girl survey", "label": "DESCRIPTIVE_DATA", "score": 0.5507534742355347, "start": 14, "end": 25, "probe_score": 0.1539, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">CPF<br>|<br>Country Partnership Framework<br>|\n|<br>CPI<br>|<br>Corruption Perceptions Index<br>|\n|<br>DA<br>|<br>Designated Account<br>|\n|<br>DFIL<br>|<br>Disbursement and Financial Information Letter<br>|\n|<br>DHS<br>|<br>Demographic and Health Survey<br>|\n|<br>ECOSIT<br>|<br>Survey on Expenditure of Households and Informal Sector in Chad (_Enquête sur la_<br>_Consommation des Ménages et le Secteur Informel au Tchad)_ <br>|\n|ERR<br>|<br>Economic Rate of Return<br>|\n|<br>ESCP<br>|<br>Environmental and Social Commitment Plan<br>|\n|<br>ESF<br>|<br>Environmental and Social Framework<br>|\n|<br>ESIA<br>|<br>Environmental and Social Impact Assessment<br>|\n|<br>ESMF<br>|<br>Environmental and Social Management Framework<br>|\n|<br>ESS<br>|<br>Environmental and Social Standard<br>|\n|<br>FM<br>|<br>Financial Management<br>|\n|<br>FNPV<br>|<br>Financial Net Present Value<br>|\n|<br>GBV<br>|<br>Gender-Based Violence<br>|\n|<br>GDP<br>|<br>Gross Domestic Product<br>|\n|<br>GEMS<br>|<br>Geo-Enabling Initiative for Monitoring", "output": {"entities": {"named_data": ["Demographic and Health Survey", "Survey on Expenditure of Households and Informal Sector in Chad"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 2, "chunk": 1, "title": "Chad - Energy Access Scale Up Project", "pdf_url": "http://documents.worldbank.org/curated/en/860701648216750651/pdf/Chad-Energy-Access-Scale-Up-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Demographic and Health Survey", "label": "NAMED_DATA", "score": 0.6179262399673462, "start": 225, "end": 254, "probe_score": 0.2894, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Survey on Expenditure of Households and Informal Sector in Chad", "label": "NAMED_DATA", "score": 0.5497922897338867, "start": 280, "end": 343, "probe_score": 0.3212, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<u>Resettlement Action Plan for ESTDP-Lalibela                                           Page</u> **<u>31</u>** <u>of</u> **<u>85</u>**\n\n\nmainly during the the night. After a compulsory course on _Zema_, which is a form of hymn, all\nother religious courses are elective.\n\nThis is the kind of process most of the clergy in the EOC went through. The system consists of\na series of modules like _Digua_, _Kine_, _Akuakuam_, _Kidase_, _Zimare_ and lessons in New and Old\nTestaments.\n\nHowever, since recent times, problems have been cropping up regarding the religious\neducation. There has been growing complaints from some residents in town about the loud\nchanting from the children during the night. In addition, partly because of their sheer size, the\nstudents are facing difficulties in obtaining food from the public. The traditional practice was\nthat since students came from far off places, they were required to get their food from the\npublic which was regarded as a religious duty and hence willingly provided.\n\nCurrently nine of the vacated _Lasta_ huts, within the church compound, are used for religious\ninstructions during the day time only.\n\nThe church administration as well as the clergy was in favour of keeping both the monastery\nand church schools within the church compound as they were considered part of the heritage.\n\n\n**_2.5.2.7. Economic characteristics of PAPs_**\n\n##### **_2.5.2.7. 1. Economic Characteristics of People to be Relocated_**\n\nThis section presents and discusses the census result pertaining to economic characteristics of\npeople to be relocated in terms of working status, occupational and income profiles aggregately\nfor the whole affected people to be relocated from the core zone and", "output": {"entities": {"named_data": [], "descriptive_data": ["census result"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013676", "page": 30, "chunk": 0, "title": "Ethiopia - Sustainable Tourism Development Project : resettlement plan (Vol. 7 of 7) : Resettlement action plan for Lalibela town", "pdf_url": "https://documents.worldbank.org/curated/en/481931468252604242/pdf/RP7750v70P09810L0RAP0REPORT00Vol-I0.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "census result", "label": "DESCRIPTIVE_DATA", "score": 0.798248827457428, "start": 1502, "end": 1515, "probe_score": 0.4644, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nestimate of the output cost of a disaster occurring January 1st.\n\n\n6 Note at this point that this threshold identification of significant disasters does not mechanically imply a\n\n\ndecline in GDP, also some relationship with GDP dynamics could exist. This is because the identification\n\n\nthreshold looks at the destroyed stock of wealth and production factors rather than the flow of income.\n\n\nGDP is used here as a scaling variable.\n\n7 While we cannot completely control for the disaster’s size, we do separate small and large disasters.\n\n\nThus, only variation in intensity among large disasters is being ignored. Further, the concern that two\n\n\nepisodes may have completely different impact because of their intensity and location is partially\n\n\ncontrolled by imposing that disasters affect a minimum number of people and cause a minimum damage\n\n\nto capital and wealth. Thus disasters that occur in the middle of the desert are not considered as disasters\n\n\nunder our measure. Nonetheless, future work should attempt to consider the disaster’s distance to\n\n\npopulated centers..\n\n\n11", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004749", "page": 13, "chunk": 1, "title": "wps5564", "pdf_url": "https://local/prwp/wps5564.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "d. **Peace Capacities** (What systems or mechanisms exist that are already or could be\n\nused for resolving conflict? Which groups or individuals have the potential to build\npeace and how can they be supported?)\n\nData used to undertake such an analysis should come from as many diverse sources as\npossible (formal and informal) and, if possible, should rely on local sources.\nParticular attention should be paid to _local_ _perceptions_ and _sudden shifts_ in conflict\nfactors as these can indicate vulnerability to violence. The collection and analysis of\nthis information should be done in a transparent manner (with consideration that\nsometimes security conditions will make this difficult). It is important to recognize\nthat not only the final output of this process of collecting and analyzing of conflict\ndata is relevant (i.e., an analysis report or a situation briefing). The process itself,\nincluding the dialogue with staff and stakeholders, the practice of reflection, the\nconsideration of multiple perspectives, etc., can contribute to conflict transformation\nand peace building.\n\n\ne. The findings of the conflict analysis should be directly and systematically linked to\n\nthe decisions that are made regarding programming and implementation strategy.\nWhether the organization’s initiatives aim to explicitly support conflict\ntransformation and peace building, or intend to address identified humanitarian and\ndevelopment needs in a conflict-sensitive manner, the strategy for implementation\nshould consider its potential impact on the conflict and local peace capacities.\n\n\nf. Systems for Monitoring and Evaluation during the project cycle should incorporate\n\nconsideration of the conflict in the target area. Due to the dynamic nature of conflicts,\nit is important that conflict analysis is understood to be an ongoing effort. Conflictsensitive Monitoring and Evaluation should refer to the initial analysis of the conflict\nand include questions such as:\n\n  - How has conflict evolved or changed over time (identify any trends)?\n\n  - How has conflict affected implementation of the project or programme?\n\n  - How has the project affected conflict and peace in the target area", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["conflict\ndata"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000486", "page": 40, "chunk": 0, "title": "Framework for conflict-sensitive programming in Iraq", "pdf_url": "https://reliefweb.int/attachments/4547b9d0-4923-3642-923d-ed61614c7862/7731E06713EF654B8525741E005C01C2-Full_Report.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "conflict\ndata", "label": "VAGUE_DATA", "score": 0.7492347955703735, "start": 801, "end": 814, "probe_score": 0.0606, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "up> Selection of counties will be guided by four criteria: (a) vulnerability, (bi) feasibility,\n(c) equity, and (d) quick wins. To assess the level of needs in a transparent and evidence-based manner,\nthe project has developed a composite vulnerability index comprising the following indicators with equal\nweights: (a) concentration of returnees, (b) access to basic services, (c) food insecurity, (d) incidents of\nviolence, (e) remoteness, and (f) exposure to climate-sensitive natural hazards. <sup>46</sup> The project will prioritize\ncounties with high vulnerability but where there is practical feasibility, that is, not too insecure and\nphysically accessible and where there is support from the county government; ensure equity across both\nconflict-affected areas and more stable areas; and ensure that more conflict-affected areas benefit from\nthe project as they have historically been deprived of assistance due to insecurity. The targeting principles\nare summarized in figure 1.\n\n\n**Figure 1. Geographic Targeting Principles**\n\n\n\n**Vulnerability**\n\n\n•Concentration of\nreturnees\n•Access to basic\nservices\n•Food insecurity\n•Violence\n•Exposure to\nclimate-sensitive\nnatural hazards\n•Remoteness\n\n\n\n**Feasibility**\n\n\n•Accessibility\n•Security\n•Local dynamics\n•County government\nsupport\n\n\n\n**Equity**\n\n\n•Both conflictaffected areas and\nmore stable areas\n\n\n\n**Quick Wins**\n\n\n•LGSDP unfunded\nsubproject\n\n\n\n45 Such practice is in line with how the national budget is being allocated and how other development partners are operating.\n46 Equal weights are assigned to all the indicators because if higher weights are assigned to concentration of returnees, for\nexample, that could work against more unstable, conflict-affected areas from being targeted.\n\n\nJune 22, 2020 Page 11 of 23", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000058", "page": 10, "chunk": 1, "title": "Project Information Document - South Sudan Enhancing Community Resilience and Local Governance Project - P169949", "pdf_url": "http://documents.worldbank.org/curated/en/890401593099068599/pdf/Project-Information-Document-South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project-P169949.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " database of poor households and\nconditional cash transfers. Emergency operations by nature finance short-term measures which often do\nnot have the potential to sustain development impact. Therefore, a follow-up operation should be\nconsidered that can build on the experiences of the emergency operation.\n\n**-** **Adequate attention to an institutional capacity building during preparation despite the emergency**\n**nature of operations is essential** . In Tajikistan, the food crisis response project over-estimated the\ncapacity and willingness of local government officials to assume responsibility for beneficiary selection\nand distribution and underestimated the level of support needed from local governments. On the other\nhand, since emerging from a severe food crisis in 2005, Niger has improved its institutional framework to\nprevent and respond to adverse events. Thus, the World Bank’s rapid response to the client’s request for\nassistance was met by a strong commitment and a high level of preparedness on the part of the\ncounterpart. Limited funds were, thus, able to provide timely and critical resources and technical\nassistance to develop an action plan to strengthen the government’s current programs and assess the\nfeasibility of new pilot programs to respond to the needs of poor and vulnerable people.\n\n**-** **The World Bank can be effective in providing emergency assistance even when the overall governance**\n**environment is weak** . However, it should not undermine governance issues. Building the capacity of\ngovernment apparatus and of communities to play a responsible role and demand accountability from\nthe government are key elements for building governance structures.\n\n\nPage 21 of 46", "output": {"entities": {"named_data": [], "descriptive_data": ["database of poor households and\nconditional cash transfers"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000019", "page": 25, "chunk": 1, "title": "Lebanon - Wheat Supply Emergency Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/408131653327258940/pdf/Lebanon-Wheat-Supply-Emergency-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "database of poor households and\nconditional cash transfers", "label": "DESCRIPTIVE_DATA", "score": 0.9171225428581238, "start": 1, "end": 59, "probe_score": 0.1718, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad Energy Access Scale Up Project (P174495)\n\n\ncookstoves more affordable for households. The outcomes of this subcomponent will largely be beneficial\nto women who are the primary users of these appliances. Switching to improved biomass stoves only (a\nconservative scenario) is expected to result in net emission reduction of 0.135 million tCO2eq over the\nproject lifetime. Beyond reduction in emissions and health benefits, due to increased efficiency, the use\nof improved biomass stoves is expected to reduce consumption of woody biomass by up to 91,500 tons\nof wood. Reduced consumption of woody biomass can lead to a decrease in deforestation rates and thus\npromote building climate resilience by maintaining forest cover. Considering that forest covers help\nprotect communities against the impact of climate hazards, these interventions can further improve the\nadaptive capacity of communities. Another mechanism through which this subcomponent helps build\nadaptive capacity is by increasing the disposable income of households switching to improved biomass\nstoves. Depending upon the current fuel use and tier level of improved biomass stoves, the annual savings\nper household are estimated at US$28–US$37. Finally, by prioritizing solar, biogas, and improved biomass\nstoves, clean cooking solutions will reduce fuelwood consumption. Moreover, biomass to feed improved\nstoves will be sourced from forests that are sustainably managed under Subcomponent 3.3 and in line\nwith the Environmental and Social Framework (ESF)/Environmental and Social Standards (ESS) 6\nrequirements.\n\n55. **Subcomponent 3.3: Restoration and sustainable natural resource management - Phase 2 (IDA**\n**WHR grant: US$11 million).** This subcomponent will support two main sets of activities: (a) integrated\nand participative community forest resources management through community management of natural\nresources and restoration of degraded forests and (b) technical support and capacity building through (i)\ninstitutionalization of forestry-based geographical information system in the Directorate of", "output": {"entities": {"named_data": [], "descriptive_data": ["forestry-based geographical information system"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 30, "chunk": 0, "title": "Chad - Energy Access Scale Up Project", "pdf_url": "http://documents.worldbank.org/curated/en/860701648216750651/pdf/Chad-Energy-Access-Scale-Up-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "forestry-based geographical information system", "label": "DESCRIPTIVE_DATA", "score": 0.7882539629936218, "start": 2032, "end": 2078, "probe_score": 0.0521, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "#### **ANNEX I: Guidelines for Voluntary land donations in CDD projects**\n\nIt is recommended that the basic guidelines to be followed for voluntary land donation be as\n\nfollows:\n\n    - Land to be donated must be identified by the community through a participatory\napproach\n\n    - Impacts of proposed activities on donated land must be fully explained to the donor\n\n    - The potential donor is aware that refusal is an option, and that right of refusal is\nspecified in the donation document the donor will sign\n\n    - The act of donation is undertaken without coercion, manipulation, or any form of\npressure on the part of public or traditional authorities\n\n    - The donor may request monetary or non-monetary benefits or incentives as a\ncondition for donation.In the case of NUSAF3 all donations are non monitoring.\nThey are all voluntarly contributed without any monitory or other conditions\nattached since it is all community activities that will be done on the land\n\n    - The proportion of land that may be donated cannot exceed the area required to\nmaintain the donor’s livelihood or that of his/her household\n\n    - Donation of land cannot occur if it requires any household relocation\n\n    - For community or collective land, donation can only occur with the consent of\nindividuals using or occupying the land\n\n    - Verification must be obtained from each person donating land (either through proper\ndocumentation or through confirmation by at least two witnesses)\n\n    - The implementing agency establishes that the land to be donated is free of\nencumbrances or encroachment and registers the donated land in an official land\nregistry\n\n    - Any donated land that is not used for its agreed purpose is returned to the donor.\n\n\n    - Each voluntary land donation process as guided above will be documented reflecting\ninformed consent and power of choice.\n\n\n**Note: This guidance applies to all voluntary land donations for all CDD projects for**\n**NUSAF 3.**\n\n\n**49 |** P a g e", "output": {"entities": {"named_data": [], "descriptive_data": ["land\nregistry"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019503", "page": 48, "chunk": 0, "title": "Uganda - Third Northern Uganda Social Action Fund Project : indigenous peoples plan : Vulnerable and marginalized people’s action plan", "pdf_url": "https://documents.worldbank.org/curated/en/880281510226836759/pdf/SFG3800-IPP-P149965-Box405309B-PUBLIC-Disclosed-11-9-2017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "land\nregistry", "label": "DESCRIPTIVE_DATA", "score": 0.647502064704895, "start": 1632, "end": 1645, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " mobile money, can give women access to a safe and private savings platform, which can alleviate some of the pressures\n\n\n16 Campos et al. 2015. “Breaking the Metal Ceiling Female Entrepreneurs Who Succeed in Male-Dominated Sectors.” Policy Research\nWorking Paper 7503. December.\n17 World Bank 2019. Profiting from Parity: Unlocking the Potential of Women’s Business in Africa. Washington DC.\n18 Government of Uganda 2018. National Labour Force Survey. UBOS.\n19 Campos, F., Frese, M., Goldstein, M., Iacovone, L., Johnson, H. C., McKenzie, D., and Mensmann, M. 2017. “Teaching personal\ninitiative beats traditional training in boosting small business in West Africa.” _Science_, _357_ (6357), 1287-1290.\n20 Urgent Action Fund 2019. Baseline study: <u>[https://eassi.org/wp-content/uploads/2020/03/Communiqu%C3%A9-on-Women-](https://eassi.org/wp-content/uploads/2020/03/Communiqu%C3%A9-on-Women-Economic-Empowerment-Convening-in-Kampala-2020.pdf)</u>\n<u>[Economic-Empowerment-Convening-in-Kampala-2020.pdf](https://eassi.org/wp-content/uploads/2020/03/Communiqu%C3%A9-on-Women-Economic-Empowerment-Convening-in-Kampala-2020.pdf)</u>\n21 World Bank 2021. High Frequency Phone Survey; Interviews with CARE, IRC, UN Women, April 2021; UNHCR 2020. Inter-", "output": {"entities": {"named_data": ["National Labour Force Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000005", "page": 6, "chunk": 2, "title": "Concept Project Information Document (PID) - Generating Livelihoods and Opportunities for Women (GLOW) Uganda - P176747", "pdf_url": "http://documents.worldbank.org/curated/en/135361626935792550/pdf/Concept-Project-Information-Document-PID-Generating-Livelihoods-and-Opportunities-for-Women-GLOW-Uganda-P176747.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "National Labour Force Survey", "label": "NAMED_DATA", "score": 0.7643706798553467, "start": 422, "end": 450, "probe_score": 0.9629, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " one year; refugee identity cards are valid for three years.</u>\n<u>160</u> <u>PVC stands for “polyvinyl chloride” and is a strong plastic material used for professional ID card printing.</u>\n<u>161</u> <u>World Bank Mobile Money Ecosystem Survey, para. __; Information provided by UNHCR country team.</u>\n<u>162</u> <u>David Manyang Mayar, In South Sudan, a Day of Deadlines, VOICE OF AMERICA, 28 Feb. 2013,</u> <u>[https://www.voanews.com/a/south-sudan-](https://www.voanews.com/a/south-sudan-mobile-phone-pharmaceutical-deadline-registration/1612779.html)</u>\n<u>[mobile-phone-pharmaceutical-deadline-registration/1612779.html.](https://www.voanews.com/a/south-sudan-mobile-phone-pharmaceutical-deadline-registration/1612779.html)</u>\n<u>163</u> <u>[https://media.africaportal.org/documents/Digital-Rights-in-South-Sudan_2021-UPR-Submission.pdf](https://media.africaportal.org/documents/Digital-Rights-in-South-Sudan_2021-UPR-Submission.pdf)</u>\n<u>164</u> <u>[https://mobile.twitter.com/mtnssd/status/1408070581472223233?lang=bg (emphasis added)", "output": {"entities": {"named_data": ["World Bank Mobile Money Ecosystem Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000137", "page": 29, "chunk": 16, "title": "Displaced and Disconnected: East and Horn of Africa and Great Lakes Region (July 2022)", "pdf_url": "https://reliefweb.int/attachments/09a75838-e186-4ff7-8fb4-300bda077a55/Displaced%20and%20Disconnected%20-%20East%20and%20Horn%20of%20Africa%20and%20Great%20Lakes%20Region.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "World Bank Mobile Money Ecosystem Survey", "label": "NAMED_DATA", "score": 0.8893321752548218, "start": 206, "end": 246, "probe_score": 0.9782, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " foundation for democratic and sustainable local\n\n\n\ndevelopment. The Community Development Program will finance social and economic\ninfrastructure and support social capital building activities to facilitate the restoration of basic\nsocial services such as health and education and provide an incentive for teachers, health workers\nand displaced persons to return to their communities. The Rural Public Works and Shelter\nprograms will provide employment for demobilized soldiers and unemployed youth, housing for\ndisplaced persons and feeder roads to stimulate local economic activities. The innovative\nactivities including training and technical support will strengthen local government capacity to\nplan, contract, manage and sustain investments in local development and engage a wide array of\n\n\n\nstakeholders in participatory processes that contribute to sustainable local development.\n\n\n\nTargeting will be consistent with the Government's 2002-2003 National Recovery\nStrategy and the March 3, 2002 Transitional Support Strategy. Resources will be directed to (a)\nnewly accessible areas that have not received any support in more than a decade; and (b) remote\nareas that have received little, if any support from the ongoing IDA-financed CRRP or other\nsimilar projects. The results of the living standards measurement survey currently underway will\nbe available at the end of 2003 and will be used to review the validity of existing targeting\nmodalities.\n\n\nTarget Populations: Target groups include demobilized soldiers and unemployed youth,\nrefugees, IDPs, female-headed households, child laborers, orphans, primary school dropouts,\n\n\n_- 8 -_", "output": {"entities": {"named_data": [], "descriptive_data": ["living standards measurement survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014068", "page": 12, "chunk": 1, "title": "Uganda - Education Sector Adjustment Credit", "pdf_url": "https://documents.worldbank.org/curated/en/509691468760215619/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "living standards measurement survey", "label": "DESCRIPTIVE_DATA", "score": 0.8663687705993652, "start": 1291, "end": 1326, "probe_score": 0.7112, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 6\nPage 5 of 6\n\n\n\n**Table B: Thresholds for Procurement Methods and Prior Review 1**\n\n\n\n**Expenditure Category** **Contract Value** **Contracts Subject to**\n**Threshold** **Procurement** **Prior Review**\n(US$ thousands) Method (US$ millions)\n1. **Works** - US$50,000 NCB All ICB if any.\n< US$50,000 Simplified NCB NCB contracts above US$150,000\nFirst 5 contracts regardless of\nvalue; first 3 contracts for each\n\n\n\nyear starting January 1.\n**2. Goods** - US$100,000 ICB All ICB.\n< US$100,000 NCB NCB contracts above US$70,000\n< US$50,000 IS or NS where there are at First 5 contracts regardless of\n\n\n\nleast 3 capable national value; first 3 contracts for each\nsuppliers. year starting January 1.\n<US$10,000 DC\n**3. Services** - US$50,000 QCBS Contracts above US$200,000\n(Firms) would be advertised in the UNDB.\n\n              - US$25,000 Contracts for firms above\n(Indiv.) CQ US$50,000, and for individuals\nSS above US$25,000.\n< US$25,000 First 5 contracts regardless of\n=< US$15,000 value; first 3 contracts for each\nyear starting January 1.\nAll TORs\n_____________________________________________________________IAll Sole Source\nThresholds generally differ by country and project.", "output": {"entities": {"named_data": ["UNDB"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000049", "page": 47, "chunk": 0, "title": "Croatia - Reconstruction Project for Eastern Slavonia, Baranja and Western Srijem", "pdf_url": "http://documents1.worldbank.org/curated/en/347691468746725804/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "UNDB", "label": "NAMED_DATA", "score": 0.7894626259803772, "start": 809, "end": 813, "probe_score": 0.3126, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nthat if total effort exceeds, “ _total profit is smaller than the maximum profit. The_\n2\n\n_management problem comes down to the reduction of the harvesting level_ ”. The rule they\npropose is the following:\n#### Let ( xi * ) i ∈ N be a competitive equilibrium. Define the proportional rule, PROP ( i ) applied\n\n_to every player i such that:_\n\n\n\n= _xi_ - ⎛⎜ - _<u>M</u>_ ⎞⎟\n⎜ ⎟\n##### ⎝ x ( N ) ⎠\n\n\n##### PROP ( i ) = xi * ⎛⎜ * M\n\n⎜\n##### ⎝ x ( N\n\n\n##### ( i ) = xi * ⎛⎜ * M\n\n⎜\n##### ⎝ x ( N )\n\n\n\n_i_ - ⎜ \n⎜\n\n_x_\n\n\n\n_b_\n_, where_ _M_ = _._\n2\n\n\n\nThus, it is proposed to apply a proportional rule to allocate the harvesting shares among\nthe agents involved, taking into account a sustainable concept for the resource, by which\neach agent can be better off.\n\nAnother important reference about the effects of coalition in fisheries’ management is\nLindroos (2002).\n\n_The Norwegian spring-spawning Herring Fishery_\n\nBjǿrndal, Kaitala, Lindroos and Munro (2000) report an example of a specific case of\nstraddling fishery that is the Norwegian spring-spawning herring. This fishery spawn\n\n\n36", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003286", "page": 35, "chunk": 1, "title": "wps4073", "pdf_url": "https://local/prwp/wps4073.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "support, making it difficult to assess whether a drop in sales/employment or government support came\nfirst. This timing issue is the reason why we do not control for drop in sales or employment in equation 2\n(which we estimate in table 5).\n\nHowever, we conduct robustness checks where we add change in sales or employment to equation 2.\nThe results are in tables A.8 and A.9. They show that firms with larger drops in sales were more likely to\nreceive government support, but for a given change in sales or employment, firms with lower labor\nproductivity were still more likely to receive support.\n\n**5.4 Global Sample**\n\nTo examine whether our findings are specific to ECA countries, we replicate tables 3 and 5 for the global\nsample of 30 countries for which all the data we use are available, thus adding seven countries outside\nECA (listed in panel B in table A.1). This sample includes all countries for which pre-COVID ES data are\navailable for 2018 to 2020 (with fieldwork completion dates in 2019 to 2020). While ES data are\navailable for five additional countries (Cyprus, Greece, Italy, Malta, and Portugal), these countries are\nnot covered by the BTI competition measure.\n\nTable A.10 replicates table 3 with the global sample, and table A.11 replicates table 5. Most of the main\nfindings are similar. The global data show that economic activity was reallocated from less productive to\nmore productive firms during the COVID-19 crisis. This reallocation was greater in countries with more\ncompetitive markets (table A.10). Government support went to firms with lower labor productivity,\nirrespective of their innovativeness (table A.11). The only different main finding in the global sample is\nthat firm size is not correlated with the probability of receiving government support.\n\n\n**6. Conclusion**\n\nWe use ES data to show that during the COVID-19 crisis", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["global data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000186", "page": 15, "chunk": 0, "title": "competition and firm recovery post covid 19", "pdf_url": "https://local/prwp/competition-and-firm-recovery-post-covid-19.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "global data", "label": "VAGUE_DATA", "score": 0.7526512742042542, "start": 1316, "end": 1327, "probe_score": 0.9643, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "micro-level decision makers, each household in the household survey is linked directly to\n\nthe corresponding representative household in the CGE model. Changes in representative\n\nhouseholds’ consumption in the CGE model component are passed down to their corre\nsponding households in the survey data. Only commodities used in the calculation of the\n\npoverty lines are considered.\n\nIn the next step, real total and per capita consumption expenditures are recalculated for\n\neach household in the survey. This new level of per capita expenditure is compared to the\n\nexogenously given poverty line and standard poverty measures are recalculated. Poverty\n\nchanges are evaluated using the standard Foster–Greer–Thorbecke (FGT) poverty measures.\n\nRepresentative households have been disaggregated across three dimensions:\n\n\n- Regional distinction: the Coast region and the rest of Kenya\n\n- Settlement pattern (urban and rural)\n\n- Disaggregation by consumption quintiles\n\n\nMapping between the CGE model representative households and those in the survey were\n\nnecessary to connect the households in the two sets of data. First, survey households were\n\ndistinguished by region: Coast region and the rest of Kenya. Second, within each group,\n\nurban households were distinguished from the rural. Finally, within each group, households\n\nwere classified by consumption quintile. A second level of mapping matched the commodi\nties in the CGE model and SAM with the commodities used in the calculation of the poverty\n\nline. This means that although total household consumption may have been notably affected\n\nin the economywide analysis, the composition in different commodities determines gains in\n\npoverty reduction.\n\nOur analysis, therefore, accounts for the poverty impact in each region across rural and\n\nurban households, each disaggregated by consumption quintile. This allows us to capture the\n\neffect on the bottom 40 (B40) percent of the wealth quintile of the Kenyan population, which\n\nis considered as an indicator of shared prosperity. Although shared prosperity refers to income,\n\nin many cases, household consumption must be used as a proxy for household income, partic\nularly when", "output": {"entities": {"named_data": [], "descriptive_data": ["household survey"], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018516", "page": 27, "chunk": 0, "title": "Economywide and distributional impacts of water resources development in the coast region of Kenya : implications for water policy and operations", "pdf_url": "https://documents.worldbank.org/curated/en/808491526362236466/pdf/126189-WP-P145559-PUBLIC-14-5-2018-12-9-47-W.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "household survey", "label": "DESCRIPTIVE_DATA", "score": 0.8266040682792664, "start": 51, "end": 67, "probe_score": 0.9775, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.5474758744239807, "start": 288, "end": 299, "probe_score": 0.9318, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">�</u>\n\n\n\nf\n\n\n\nNTMnijjX;NTM nij\n\n\n\n\n1 �     - Zij� + � <sup>NTM</sup> NTM nij\n<u>�NTMnij �</u> \n<u>�</u>\n\n\n\n\n<u>�</u>\n\n<u>�</u>\n\n\n\n\n~~�~~ ;\n\n\n\n��1�NTMnij ;\n\n\n\ninvMillnij =\n\n\n\n\n- <u>�</u> Zij <sup>^</sup> - + <sup>^</sup> \n<u>�</u>\n\n- Zij <sup>^</sup> - + <sup>^</sup> \n\n\n\n- Zij <sup>^</sup> - + <sup>^</sup> \n~~�~~\n\n\n\nNTM NTM nij\n\nNTM NTM nij\n\n\n\nwhere we retrieve the inverse Mills ratio, invMillnij; constructed based on <sup>^</sup> - and <sup>^</sup> �NTM ;\n\n\nthe coe¢ cients of the second-stage control variables, Zij; and the average NTM presence,\n\n\nNTM nij:\n\n\nFinally, we also run the …rst-stage regressions for the four interaction terms that involved\n\n\ntari¤s and NTMs, using the interaction terms with t <sup>�</sup> nij and NTM nij as the respective in\n\n20", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000991", "page": 22, "chunk": 1, "title": "idu0b25d29bb0fa0e044ae0904c0235eb8c716a6", "pdf_url": "https://local/prwp/idu0b25d29bb0fa0e044ae0904c0235eb8c716a6.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "in light of the high frequency of pendular movements between Ukraine and host countries)\nindicate an intention for a stable return. Of these 158,000 have returned for between 3 and 6 months and are reported in 2023 statistics,\nwhile 703,000 returned more than 6 months ago and are reported retroactively in 2022. In addition, 353,000 refugees have returned to\nlocations in Ukraine that are not their place of origin. UNHCR estimates that 39,000 of them returned in the first six months of 2023, with\n314,000 having returned in 2022.\n\n\nUNHCR > **MID-YEAR TRENDS 2023** 7", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["2023 statistics"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001065", "page": 6, "chunk": 2, "title": "UNHCR Mid-Year Trends 2023", "pdf_url": "https://reliefweb.int/attachments/a13b0f58-8b05-4652-84d7-e150dd9e7c6c/Mid-year-trends-2023.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "2023 statistics", "label": "VAGUE_DATA", "score": 0.6624873280525208, "start": 210, "end": 225, "probe_score": 0.9475, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Increased competition on the labour\nmarket could partially offset benefits\nfrom refugees. Although (due to a tight\nlabour market) increase in labour force\nis almost entirely absorbed into working\nforce, there should be slight increase\nin unemployment rate. Ultimately, it is\nestimated that it was higher by 0.14-0.25\npp. in 2022 and by 0.18-0.3 pp in 2023\nwhich corresponds to respectively 24-42\nthousand and 33-54 thousand additional\npeople being unemployed <sup>45</sup> [^45: Based on number of economically active people in III quarter of 2023 according to labour market survey.] . In the long\nrun, the unemployment rate should remain\nhigher by 0.15-0.3 pp. Because of that, it is\nestimated that growth of real wages was\nslower in 2022 and 2023. It is estimated\nthat due to the influx of refugees, real\nwages were lower in 2022 by 0.45-0.85%\nand in 2023 by 0.65-1.15%. Although in\neffect this is negative, it also means lower\ninflationary pressure from the labour\nmarket in the short term. Long-term real\nwages should be around 0.55-1.0% lower\nthan in a scenario without refugees.\nThat said, the actual labour market\neffect is likely to be null as evidenced by\neconometric studies (Gromadzki and\nLewandowski, 2023; Peri, 2014), which are\nelaborated on in Chapter 4. Gromadzki\nand Lewandowski (2023) in the early\nmonths of 2022 find no effect of Ukrainian\nrefugees on earnings, employment, and\nunemployment rate of natives and other\nimmigrants, except an actual slight positive\nimpact on the wages of native women.\n\n\nEven with the increase in unemployment\nand lower real wages, an increase in labour\nforce means a higher wage pool, which\nmeans higher tax income.\n\n\n\nMoreover, boosts in private consumption\nboth due to increase in population as\nwell as higher average spending rates\nmeans that refugees increased state\nincome from taxation on consumption.\nThese effects will be strengthened by\ninflux of capital from", "output": {"entities": {"named_data": [], "descriptive_data": ["labour market survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 18, "chunk": 0, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "labour market survey", "label": "DESCRIPTIVE_DATA", "score": 0.8723631501197815, "start": 561, "end": 581, "probe_score": 0.9911, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Bayly 2001; Dirks 2001; Cassan 2015), and the lists have been amended and expanded over time. The Government of\nIndia Act of 1935 listed 417 groups in the list of Scheduled castes. The Constitution of India of 1950 increased this to 821. In\n1956, this was raised to 1,119. After 1976, additional orders were passed that enlarged the number of castes by adding more castes\nas equivalent names and synonyms and sub-castes / tribes of existing SCs and STs. In 1990, an amendment was passed by the\nIndian Parliament to include prior SC groups that had converted to Buddhism. The original list as well as updated lists of SC, ST\ngroups for all states is available through the Ministry of Social Justice and Empowerment, Government of India at the following\nwebsite (accessed on June 1, 2017): https://web.archive.org/web/20120913050030/http://socialjustice.nic.in:80/sclist.php\n\n\n20", "output": {"entities": {"named_data": [], "descriptive_data": ["updated lists of SC, ST\ngroups"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007438", "page": 21, "chunk": 1, "title": "wps8512", "pdf_url": "https://local/prwp/wps8512.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "updated lists of SC, ST\ngroups", "label": "DESCRIPTIVE_DATA", "score": 0.5191950798034668, "start": 600, "end": 630, "probe_score": 0.6838, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<br>MIS/progress<br>reports<br>|Data on indicator will<br>be collected from grant<br>applications and<br>training reports.<br>|MINEMA SPIU, BRD<br>|\n\n\n\nPage 38 of 82", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Data on indicator"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000030", "page": 42, "chunk": 1, "title": "Rwanda - Socio-Economic Inclusion of Refugees and Host Communities in Rwanda Project", "pdf_url": "http://documents1.worldbank.org/curated/en/222811556935409836/pdf/Rwanda-Socio-Economic-Inclusion-of-Refugees-and-Host-Communities-in-Rwanda-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Data on indicator", "label": "VAGUE_DATA", "score": 0.6038422584533691, "start": 32, "end": 49, "probe_score": 0.0249, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Household Survey 2016-2017.<br>Total grid connections by both Umeme and UEDCL confirmed as 166,783 (i.e., 155,088 +<br>11,695)|Average household size of 4.7 people, UBOS National Household Survey 2016-2017.<br>Total grid connections by both Umeme and UEDCL confirmed as 166,783 (i.e., 155,088 +<br>11,695)|\n||0.00|Jan/2022|399,778|10-Dec-2025|399,779|16-Mar-2026|2,525,000.00|Jun/2027|\n\n\nMar 17, 2026 Page 3 of 16", "output": {"entities": {"named_data": ["UBOS National Household Survey"], "descriptive_data": ["Household Survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001374", "page": 2, "chunk": 5, "title": "Disclosable Version of the ISR - Electricity Access Scale-up Project (EASP) - P166685 - Sequence No : 9", "pdf_url": "https://documents.worldbank.org/curated/en/099031726163536335/pdf/P166685-968ea066-da4e-43db-b4a5-07fb06298b58.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Household Survey", "label": "DESCRIPTIVE_DATA", "score": 0.5707517862319946, "start": 1, "end": 17, "probe_score": 0.9987, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UBOS National Household Survey", "label": "NAMED_DATA", "score": 0.8992828726768494, "start": 166, "end": 196, "probe_score": 0.9999, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "(d) _Good targeting is necessary to provide support to those who are most in need._ In an\n\nenvironment of pervasive poverty and fragility such as Burundi, a balance must be struck\nbetween targeting accuracy, cost, and complexity. A combination of geographical,\ncategorical and community-based targeting, and the estimation of household poverty using\nproxy means testing (PMT) will enhance transparency, allow for objective comparisons\nbetween households and empower communities to voice their priorities. The use of\nobjective criteria both for the selection of provinces and communes and for the communitybased targeting will help build transparency in the process.\n\n(e) _Partnering with experienced civil society organizations and NGOs can facilitate the_\n\n_implementation of the project and foster capacity building, particularly at the local level._\nThey will be involved in providing technical assistance for targeting, for the delivery of\nthe accompanying behavior change communication measures and may intervene also in\nsocial accountability mechanisms, such as the complaints and grievance system, to\nstrengthen project governance.\n\n_(f)_ _Ensure that the_ _institutional framework provides concrete value to social protection_\n\n_stakeholders._ The development of a system of effective social safety nets begins with the\ndefinition of a long-term vision and a coherent strategy, but then must bring concrete value\nadded to maintain its momentum. Because social protection is multi-sectoral, instruments\nthat benefit all stakeholders – be they government, donors or civil society organizations –\ncan contribute to operationalizing the institutional framework for social safety nets in\nBurundi. They include a credible targeting methodology and social registry.\n\n(g) _Develop a management information system that informs strategic decision-making._ As\n\ndemonstrated in Liberia, Sierra Leone and Tanzania, an MIS should inform the design and\nimplementation of programs, make it possible to demonstrate their impact to political\ndecision-makers, development partners, and civil society, and enhance global knowledge\nabout social safety nets in fragile environments. This is a potentially crucial ingredient to", "output": {"entities": {"named_data": [], "descriptive_data": ["social registry"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000157", "page": 27, "chunk": 0, "title": "Burundi - Social Safety Nets Project", "pdf_url": "http://documents1.worldbank.org/curated/en/900951482030099834/pdf/1482030098559-000A10458-PAD-Burundi-SSN-11282016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "social registry", "label": "DESCRIPTIVE_DATA", "score": 0.8823293447494507, "start": 1750, "end": 1765, "probe_score": 0.0952, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "between savings and investment, and reform of inter-governmental fiscal relations that\n\n\nsupport greater public spending on health and education.\n\n\nKuijs and Wang (2005) calibrate a more capital-efficient growth scenario for\n\n\nChina in which the economy grows at about the same rate as in recent years, but there\n\n\nis substantially less public savings (with the overall savings rate about one-fifth lower).\n\n\nSo, in thinking about different savings scenarios, we consider one in which the status\n\n\nquo continues, and interpret this as a “stalled reform” scenario in which there continues\n\n\nto be a lot of inefficiency in the public sector and poor intermediation between savings\n\n\nand investment. In our “high reform” scenario we consider a decline in the aggregate\n\n\nsavings rate of one-fifth.\n\n\n_What Will Happen to Productivity in China?_\n\n\nEstimates of TFP growth in China are abundant, vary considerably. <sup>7</sup> [^7: In addition to those cited in the text, see for example Li (1992), Chow (1993), Woo (1995),\nBorenzstein and Ostry (1996), and Hu and Khan (1996).] In a recent\n\n\nvery careful study Young (2003) concludes that various -- although not equally valid -\n\ninterpretations of Chinese data would result in TFP growth rates ranging from 0 to 6\n\n\npercent per year! However, Young's preferred estimate is a very reasonable 1.4 percent\n\n\nper year, for the non-agricultural economy during the period 1978-1998. This estimate is\n\n\nin the same vicinity as Kraay (1996), who estimates a TFP growth rate of 1.8 percent per\n\n\nyear for the period 1978-1994. These two estimates tend to be at the low end of those\n\n\nin the literature. For example, Borensztein and Ostry (1996) and Hu and Khan (1997)\n\n\nprovide estimates of TFP growth of 3.8 and 3.9 percent per year over the period 1978\n\n1994.  In this subsection we make two points. The first is that relatively modest TFP\n\n\ngrowth rates for China", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Chinese data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003015", "page": 23, "chunk": 0, "title": "wps3801", "pdf_url": "https://local/prwp/wps3801.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Chinese data", "label": "VAGUE_DATA", "score": 0.7250047326087952, "start": 1196, "end": 1208, "probe_score": 0.9924, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n||||||||||the te|rritory|of Polan|d.||||||\n|||||||||||||||||||\n|||||||||||||||||||\n|||||||||||||||||||\n|Lau|nch of ass|igning|PESEL n|umber|s to the|refugee|s|||||||||||\n|||||||||||||||||||\n\n\n\n40%\n\n\n30%\n\n\n20%\n\n\n10%\n\n\n0%\n\n\n\nmen\n\n\n\nwomen\n\n\n\n**Chart 3.** Poland-Ukraine border movement balance and registered/active PESEL data\n\n\n\n3000\n\n\n2500\n\n\n2000\n\n\n1500\n\n\n1000\n\n\n500\n\n\n0\n\n\n\n\n\n65+\n\n\n55-64\n\n\n45-54\n\n\n35-44\n\n\n25-34\n\n\n18-24\n\n\n<18\n\n\n25% 20% 15% 10% 5% 0% 5% 10% 15% 20% 25%\n\n\n**Source:** Deloitte own elaboration based on the PESEL database as of October 2023\n\n\n**Chart 5.** Composition of refugee households in Poland\n\n\n60%\n\n\n50%\n\n\n\n\n\nTotal entries-exits of the Polish-Ukrainian border Pesel data\n\n\n**Source:** Deloitte own elaboration based on Polish Border Guard Headquarter and PESEL data.\n\n\n\n\n\n\n\nMost of the refugees from Ukraine\ncurrently living in Poland are women and\nchildren, though over half of the total\npopulation is of working age.\nThe best population data available is the\nactive PESEL", "output": {"entities": {"named_data": ["PESEL data", "PESEL database", "Pesel data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 7, "chunk": 1, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "PESEL data", "label": "NAMED_DATA", "score": 0.5086314082145691, "start": 371, "end": 381, "probe_score": 0.9994, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PESEL database", "label": "NAMED_DATA", "score": 0.8347761631011963, "start": 578, "end": 592, "probe_score": 0.9995, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Pesel data", "label": "NAMED_DATA", "score": 0.5784572958946228, "start": 739, "end": 749, "probe_score": 0.9773, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "000 Palestinian refugees. The country, with large international aid, has managed to provide the\nrefugees with basic services, but this no doubt adds a tremendous pressure on the already weak public\nservice system, especially as the refugees tend to concentrate in already densely populated and\nimpoverished areas. Despite improvements in economic vulnerability, 69 percent of refugee\nhouseholds remained below the poverty line. <sup>4</sup> [^4: Vulnerability Assessment for Syrian Refugees in Lebanon (VASyR-2018) by the United Nations Children’s Fund (UNICEF), United Nations High\nCommissioner for Refugees (UNHCR) and the United Nations World Food Programme (WFP).]\n\n5. **The Government presented the Vision for Stabilization, Growth and Employment, which**\n**aims to increase economic growth and create productive jobs as well as alleviate the burden**\n**of reforms on both host communities and refugees.** The Vision includes four complementary\npillars. The _first pillar_ is a large capital investment program (CIP) which includes a list of more than\n280 infrastructure projects at an estimated cost of US$16 billion (32 percent of GDP) over the 20182025 period. The _second pillar_ is fiscal reform in which the Government committed to an annual 1\npercentage point reduction in the fiscal deficit ratio over the next five years. The _third pillar_ is structural\nreforms to ensure good governance, fight corruption, and modernize the public sector. The _fourth pilla_ r\nis development of productive sectors as well as enabling sectors including infrastructure and electricity.\nThe Vision was presented at the Conference Économique pour le Développement, par Les Réformes\net avec les Enterprises (CEDRE), which took place on April 6, 2018, in Paris, France, as part of the\nfundraising effort for the CIP. If implemented, the plan has significant potential to provide a sustained\nboost to the economy, attract much needed capital inflows, and catalyze job creation for women and\nmen. The new Government, formed on January 31, 2019, promised", "output": {"entities": {"named_data": ["Vulnerability Assessment for Syrian Refugees in Lebanon"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000010", "page": 3, "chunk": 1, "title": "Concept Project Information Document (PID) - Lebanon Electricity Transmission Project - P170769", "pdf_url": "http://documents.worldbank.org/curated/en/235831562864951356/pdf/Concept-Project-Information-Document-PID-Lebanon-Electricity-Transmission-Project-P170769.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Vulnerability Assessment for Syrian Refugees in Lebanon", "label": "NAMED_DATA", "score": 0.68062824010849, "start": 446, "end": 501, "probe_score": 0.9839, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "s tend to have higher rates of entrepreneurship**\n**than native workers.** There may be different reasons for this\nas perhaps immigrants have character traits that make them\nmore inclined towards entrepreneurial activity (unclear in the\ncase of refugees), or maybe it is a way to avoid occupational\ndowngrading as immigrants find it difficult to prove their\neducational and professional credentials from home countries.\nNotwithstanding the reason, such effects are observed across\nthe OECD countries (OECD, 2011). In a recent paper, Anelli,\nBasso, Ippedico, and Peri (2023) look at Italian data, finding that\none standard deviation increase in emigration rate generates\n4.8% decline of business formation in the municipality of origin.\nThe authors use existing migration networks to ensure causality\nof the results. Nevertheless, it is unclear whether immigrantcreated businesses are more successful from the native\nones, but one could speculate that a higher rate of trying new\nbusiness ideas spurs more successes.\n\n\n\nThe escalatation of war 2022 in Ukraine\ncaused a large inflow of refugees into\nPoland. While some refugees from Ukraine\nhave since returned to Ukraine or gone\nfurther to Germany or other countries,\nin October 2023 close to 957 thousand\nremained in Poland (identified by active\nPESEL UKR numbers). They consist\nprimarily of children and working aged\nwomen. Despite the forced nature of\ndisplacement, war trauma, and caregiving\nresponsibilities, refugees from Ukraine\nvery quickly entered the labour market\nas employees and entrepreneurs. The\nprecise number of refugees from Ukraine\nworking in Poland remains uncertain,\nwith our estimates ranging from 225 to\n350 thousand. The lower bound is the\nnumber of social security registrations and\nunderstates the actual figure, as some jobs\nmay not require social contributions or\nremain in the informal sector. The higher\nbound is the product of employment rates\nfrom surveys of refugees from Ukraine,\nand their working age population from\nthe active PESEL UKR database. By JulyAugust 2023 Ukrainian refugee households\nsupported themselves, with 80% of", "output": {"entities": {"named_data": ["PESEL UKR"], "descriptive_data": [], "vague_data": ["Italian data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 20, "chunk": 3, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Italian data", "label": "VAGUE_DATA", "score": 0.7730504870414734, "start": 582, "end": 594, "probe_score": 0.9915, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PESEL UKR", "label": "NAMED_DATA", "score": 0.5219568610191345, "start": 1296, "end": 1305, "probe_score": 0.9915, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n# **1.** Inflow of refugees from Ukraine into Poland\n\n##### Even before the 2022 full-scale war in Ukraine the number of Ukrainians in Poland was substantial and growing, although their precise number is difficult to measure.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 1.** Ukrainian workers with social insurance.\n\n\nRate of change (right axis) Number (left axis)\n\n\n\n**Source:** Deloitte own elaboration based on ZUS data.\n\n\n\n1000\n\n\n750\n\n\n500\n\n\n250\n\n\n0\n\n\n\n\n\n\n\n120%\n\n\n100%\n\n\n80%\n\n\n60%\n\n\n40%\n\n\n20%\n\n\n0%\n\n\n-20%\n\n\n\n\n\n\n\n\n\nA steady inflow of migrants could be\nobserved in the last decade since 2014,\nwhen armed conflict erupted in Eastern\nUkraine. As the Ukrainian economy\nsuffered and its currency lost value, many\nUkrainians came to Poland looking for\nwork. Most of them came on a guest\nworker basis, enabled by a law from 2011,\nthat allowed Ukrainians and five other\nnations to work in Poland for 6 months\nduring a year without a work permit, based\non employers' declaration. This was a\ncircular migration, in which they returned to\nUkraine once the 6 month period expired.\nIn effect most stayed in Poland for less\nthan twelve months and therefore were\nnot included in the resident population or\nother national population estimates.\nA National Bank of Poland research paper\nestimates that between 2014 and 2018,\nbetween one and two million Ukrainian\nworkers arrived in the country (Strzelecki,\nGrowiec and Wyszyński, 2022).\nHard data on the number of Ukrainian\nworkers in Poland before 2022 are limited\n\n\n12\n\n\n\nand might understate their presence.\nThe only hard data on these flows is the\nnumber of Ukrainian workers with social\ninsurance, which nevertheless understates\nthe numbers, as certain kinds of legal\nwork often undertaken by temporary\nemployees did not require it, and some\nUkrainians worked in the shadow economy.\nThe", "output": {"entities": {"named_data": ["ZUS data"], "descriptive_data": [], "vague_data": ["hard data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 6, "chunk": 0, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "ZUS data", "label": "NAMED_DATA", "score": 0.9100434184074402, "start": 530, "end": 538, "probe_score": 0.9775, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "hard data", "label": "VAGUE_DATA", "score": 0.5209677815437317, "start": 1671, "end": 1680, "probe_score": 0.7393, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " particularly\nrelevant as Lebanon imports at least 80% of its food supplies (ESCWA 2016). Real GDP growth is estimated\nto have contracted by 20.3 % in 2020, on the back of a 6.7 % contraction in 2019.\n\n4. **The pandemic and ensuing lockdowns have affected the poor, refugees, and other vulnerable**\n**populations disproportionately, on a global scale as well as on a national scale** . In Lebanon, a wide range\nof vulnerable groups have been negatively impacted by the pandemic ranging from the loss of livelihoods\nof informal workers and micro-entrepreneurs, additional economic insecurity for refugees and migrants,\nto the overlook of the health needs of the elderly and the disabled. <sup>10</sup> Lockdown measures to fight the\npandemic, topped by the global recession, have resulted in permanent and temporary lay-offs with\nparticularly detrimental effects on informal workers. Syrian refugees have experienced economic hardship\nin 2020: there was a 44% increase in refugees under the Survival Minimum Expenditure Basket (SMEB),\nmeaning that 89% now cannot meet their basic needs and are prone to a deprivation of a series of rights. <sup>11</sup>\nIn addition, 83% of migrants surveyed in May 2020 reported that they struggled to make payments for\nfood in the last 30 days. <sup>12</sup> Older people suffer from a lack of health and protection systems. Persons with\ndisabilities have also been disproportionately affected by interrupted health services and social support\nat home, including personal assistance. <sup>13</sup>\n\n5. **The blast further exacerbated socioeconomic hardship, undermined trust in governmental institutions**\n**and increased existing pressures for emigration** . Even before the explosion, the fallout of the economic\ncrisis and the pandemic had led to a significant increase in poverty and a shrinking middle class. The Fall\n2021", "output": {"entities": {"named_data": [], "descriptive_data": ["migrants surveyed in May 2020"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000002", "page": 3, "chunk": 1, "title": "Project Information Document - Support for Social Recovery Needs of Vulnerable Groups in Beirut - P176622", "pdf_url": "http://documents.worldbank.org/curated/en/113021634329877822/pdf/Project-Information-Document-Support-for-Social-Recovery-Needs-of-Vulnerable-Groups-in-Beirut-P176622.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "migrants surveyed in May 2020", "label": "DESCRIPTIVE_DATA", "score": 0.6807783246040344, "start": 1173, "end": 1202, "probe_score": 0.0513, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "9. **Budget and Implementation Arrangements of PF**\n\n\n9.1. **Budget**\n\nIn the case of ERP, inducing restriction of access to natural resources and resulting in loss of income this will be\nfinanced through funds from the Government of Ethiopia. OFLP would not finance restriction of access to\nnatural resources and resulting in loss of income (if happened), which is the responsibility of GoE. Based on\nthe 2013 Central Statistics Authority population projection, the population of Ethiopia has reached 45, 249,998\nmale and 44,826,014 female and a total of 90,076,012 in 2015. Likewise, the population of Oromia based on the\nsame projection reached 33,691,991 in 2015. In line with the REDD+ jurisdictional approach that defines the\ncarbon accounting area, OFLP would cover all of Oromia’s 297 rural and semi-rural Woredas. In these Woredas,\nthere are approximately 1.8 million people living inside or immediately adjacent to existing forests. At this stage,\nit is not possible to estimate the exact number of people who may be affected since the specific sites for the on the\nground investment activities are not known. Site specific detailed socio-economic survey is required to prepare\naccurate budget allocation of the project that induce access restriction. The implementation of the process\nframework will follow the existing arrangements for the ERP implementation, ESMF and RF. Thus, no need for\nseparate institutional arrangement.\n\n<u>Table 6: Template for Preparing Site and on the ground investment Specific Budget</u>\n\n\n44\n\n\n|Col1|Description|Affected category|Col4|Col5|Budget needed|Col7|Col8|\n|---|---|---|---|---|---|---|---|\n||Description|Individual|Household|Community|Individual|Household|Community", "output": {"entities": {"named_data": ["2013 Central Statistics Authority population projection"], "descriptive_data": ["Site specific detailed socio-economic survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:006311", "page": 48, "chunk": 0, "title": "Resettlement Process Framework Oromia Forested Landscape Program – Emission Reduction Project (P151294)", "pdf_url": "https://documents.worldbank.org/curated/en/099240308262232352/pdf/P1512940f464900c4082d60336ea488893f.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "2013 Central Statistics Authority population projection", "label": "NAMED_DATA", "score": 0.8215691447257996, "start": 406, "end": 461, "probe_score": 0.9608, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Site specific detailed socio-economic survey", "label": "DESCRIPTIVE_DATA", "score": 0.8202607035636902, "start": 1120, "end": 1164, "probe_score": 0.0514, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " health and education sector reviews\nin November 2002 and confirmed by the November 2003 review; and (b) water and\nsanitation sector review in September 2003 and confirmed by the March 2004 review.\n\n\n5.9 **Universal Primary Education.** PRSC4 supported the Government goal o f\nuniversal primary education by improving budget allocation to the education sector. The\nprogram document notes that Government allocated a minimum o f 3 1 percent o f\nrecurrent discretionary expenditure for education, o f which no less than 65 percent went\nto primary education. But IMF data show that actual total Government expenditure in\neducation in 2003/04 accounted for 22.2 percent o f the Government’s total domestic\nexpenditure, below the 3 1 percent established in the prior actions. As argued before, this\ni s not necessarily a shortcoming when there is evidence that expenditure in education is\ninefficient. The PRSC4 also supported improvement in the quality o f teaching (pupils per\nteacher), increased access to learning materials (pupils per textbook), and improved\nlearning environment (pupils per classroom). Of the three outcomes, only the target for\naccess to learning materials was achieved, with three pupils per textbook. The other two\noutcomes fell short o f their goals (58 pupils per teacher versus a target o f 52, and 94\npupils per classroom versus a target o f 92). On equity, PRSC4 fell short o f achieving the\n\n\n\n**Universal Primary Education.** PRSC4 supported the Government goal o f\n\n\n\ngoal o f having 12 percent o f girls and boys o f appropriate age range completing primary\ngrade _7,_ as 10.7 percent o f boys and 9.3 percent o f girls did so. Overall, efficacy was\n_modest._\n\n\n\n**22**\nThe PAD notes that “Under the results oriented management approach (ROM), which remains the core component\n\n- f the PRSP, ministries, departments and agencies (MDA", "output": {"entities": {"named_data": ["IMF data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011390", "page": 38, "chunk": 1, "title": "Uganda - First, Second, Third, and Fourth Poverty Reduction Support Credit Projects", "pdf_url": "https://documents.worldbank.org/curated/en/332711468175737633/pdf/489420PPAR01mu101Official0Use0Only1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "IMF data", "label": "NAMED_DATA", "score": 0.7407829165458679, "start": 560, "end": 568, "probe_score": 0.8579, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEducation Quality Improvement Project (P179363)\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Components/<br>Subcomponents|Activity|Climate Mitigation<br>Measures (US$, millions)|Climate-Related Action|Anticipated<br>Mitigation|Anticipated Adaptation|\n|---|---|---|---|---|---|\n||planning||educational infrastructure, including data collection<br>related to safety, inclusiveness, sustainability such<br>as energy management systems, designing and<br>integrating sustainable O&M mechanisms for<br>energy efficiency and renewable energy, digital<br>provision, capacity building required for strategic<br>investment planning with durable and adequate<br>solutions in the face of the climate risks|reduce the<br>energy intensity<br>through<br>efficiency<br>measures and<br>renewable<br>energy options<br>based on the<br>data collection<br>on the energy<br>efficiency of<br>facilities|disasters will be a key<br>consideration in the<br>action plan, as well as<br>the potential for<br>educational institutions<br>to be designated disaster<br>shelters|\n\n\nPage 68 of 68", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data collection", "data collection"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000185", "page": 77, "chunk": 0, "title": "Moldova - Education Quality Improvement Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099051123142553305/pdf/BOSIB-624554c1-598f-4576-aa60-cca7d93b64e7.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data collection", "label": "VAGUE_DATA", "score": 0.5245596170425415, "start": 315, "end": 330, "probe_score": 0.046, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "data collection", "label": "VAGUE_DATA", "score": 0.5423220992088318, "start": 804, "end": 819, "probe_score": 0.0149, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " have acquired Colombian nationality after the adoption of the\n8470 Resolution and the Law 1997, which provides for the acquisition of Colombian nationality of children born in Colombia to Venezuelan\nparents through birth registration regardless of migratory status.\n\n\nUNHCR > **GLOBAL TRENDS 2020** 53", "output": {"entities": {"named_data": [], "descriptive_data": ["birth registration"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000757", "page": 52, "chunk": 2, "title": "Global Trends: Forced Displacement in 2020", "pdf_url": "https://reliefweb.int/attachments/6e8ede0f-1a42-3ab2-bcec-bfafce0bf87f/60b638e37.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "birth registration", "label": "DESCRIPTIVE_DATA", "score": 0.580515444278717, "start": 216, "end": 234, "probe_score": 0.0004, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**I.** **Introduction**\n\nThe Latvian economy made great strides in recovering from the economic shock of the\nearly transition and the adverse after-effects of the 1998 Russian financial crisis. GDP\ngrowth has been robust, averaging close to 6% p.a. over the past five years. Inflation is\nlow. The currency is stable. Internal and external deficits are at sustainable levels.\nAnnual FDI inflows and gross fixed capital formation, which grew at a 19% annual rate\nbetween 1996 and 2001, <sup>1</sup> [^1: Latvia Innovation survey, chapter 3, page 17.] are both at relatively healthy levels. Standards of living and\nconsumption are both growing at a steady pace. And perhaps most importantly, Latvia\nbecame a member of the European Union on May 1, 2004. Nevertheless, Latvia faces\nserious challenges to its future growth and prosperity despite these impressive\nachievements and the outward appearance of macroeconomic stability and economic\nprogress.\n\nMost of Latvia’s growth to date has come from pent up consumer demand and efficiency\ngains generated by structural reforms, privatization, and reallocating resources from loss\nmaking enterprises to more profitable enterprises. Unfortunately, these are one-off gains,\nnot inexhaustible reservoirs of growth. Latvian enterprises will be able to sustain\neconomic growth and create high wage jobs only by becoming internationally\ncompetitive, innovating, accumulating new knowledge and technology, and finding a\nhigh value added niche in the European and global division of labor.\n\nLooked at from this vantage point, the picture is not so rosy. Simply and starkly stated, a\nwide variety of recent studies suggest that the Latvian economy is not particularly\ncompetitive and, even more worrisome, they indicate that Latvia is not well positioned to\ngain ground in the race for global competitiveness, prosperity, and rising standards of\nliving. All this bodes poorly for Latvia’s future competitiveness and prosperity unless\nleaders of Latvia’s business, government, university, and scientific communities develop\nand implement clear, concrete policies to address", "output": {"entities": {"named_data": ["Latvia Innovation survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002704", "page": 4, "chunk": 0, "title": "wps3457", "pdf_url": "https://local/prwp/wps3457.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Latvia Innovation survey", "label": "NAMED_DATA", "score": 0.8552177548408508, "start": 502, "end": 526, "probe_score": 0.9918, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "8\n\n\nmaintenance, and adaptable skills in galvanizing\nlocal communities into participating in the school\nmanagement and maintenance.\n\n**Financing of Non-Salary Recurrent Costs**\n\nOverall fiscal constraints. The Government is reaching out to communities for\nschool maintenance and it is expected that donors\nwill cover some recurrent costs. As mentioned\nabove, the project will finance books and other\neducational materials.\n\n**Limited Role of Private Sector**\n\nRole of private sector is limited due to financial and To reach full primary enrollment requires increasing\nhuman resource constraints. the share of enrollment in private schools. The\nGovemment is planning a series of incentives for\nprivate schools including simplified registration\n\nprocedures and tax exemptions. A study is underway\nto examine the constraints to private provision of\neducation. Based on this study the Government will\nissue a decree to facilitate private provision of\neducation. This decree will serve as a trigger from\nPhase I to Phase II of this APL.\n\nThe project will finance private sector teacher\n\ntraining through the programs developed within the\nCFPEN (see above).\n\n\n**4. Program description and performance triggers for subsequent loans**\n\nThe proposed APL will support the Government's ten-year program to increase enrollment at the\nprimary level. The support will be in the context of the medium to long-term expenditure estimates\noutlined in Table 1 and will include support for investment and recurrent costs.\n\n\n**Phase I** (US$10.0 million over three years starting in March 2001) will support the immediate\nresponse to the unmet demand by increasing capacity in primary schools. It will also finance books\nand educational materials, the purchase of which has been deferred due to the lack of recurrent budget\nresources. Some attention will be given to increasing the number of places in mniddle schools because\nthis is an essential precondition for converting the competitive examination at the end of the primary\ncycle to a non-competitive assessment. Phase I will finance teacher training, and the development of\nnew curricula for the reformed Grade", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000041", "page": 11, "chunk": 0, "title": "Jordan - Community Infrastructure Project", "pdf_url": "http://documents1.worldbank.org/curated/en/294581468773394111/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " setting all spatio-temporally varying covariates at a reference value. We use country\nmeans. <sup>30</sup> Make reference predictions with this data set.\n\n\n3. For each group of covariates defined in step 1, set the levels of the data to the observed values\n\nwhile keeping all the other covariates at reference values as defined in the previous step, then\n\ngenerate a new set of predictions.\n\n\n4. For each set of predictions generated in the previous step, subtract the reference predictions\n\ngenerated in step 2. Then, from this prediction difference, calculate the lowest value in each\n\ndistrict across all time periods and subtract these.\n\n\n5. Standardize the prediction differences generated in the previous step to [0,1] by dividing them\n\nby their sum, then multiply by probabilities predicted when all data are set to observed levels.\n\n\nonly 8 assessment cycles are available for cross-validation and errors are heavily driven by the first two\nperiods. Again, good performance was established in a holdout, binarized outlooks scoring respectively 9 _._ 3\nand 16 _._ 3 points while the model-based predictions missed the outcome by only 1 _._ 6 and 3 _._ 2 points. Finally,\nfew assessments are available for the Republic of Yemen which has stayed near 100% crisis in all but the first\nperiod, no difference was ever recorded between near-term preliminary assessments and final outcomes in\nUganda, and Zambia never experienced crisis. When focusing on the remaining 16 countries for validation,\nRMSE in the near-term was identical for model-based predictions and binarized outlooks, while on the\n8-month target the model reduced RMSE by 48% increasing only 0 _._ 6 points compared to the binarized\nnear-term outlook.\n\n29“Markets” includes all features calculated from food prices and “Conflict” all features derived from the\nconflict data. The Environmental Factors are divided in two", "output": {"entities": {"named_data": [], "descriptive_data": ["conflict data"], "vague_data": ["data set"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001981", "page": 19, "chunk": 1, "title": "predicting food crises", "pdf_url": "https://local/prwp/predicting-food-crises.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data set", "label": "VAGUE_DATA", "score": 0.5310379862785339, "start": 145, "end": 153, "probe_score": 0.087, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "conflict data", "label": "DESCRIPTIVE_DATA", "score": 0.6398640871047974, "start": 1829, "end": 1842, "probe_score": 0.9304, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\ndevelopment of the three-year strategy envisaged by the Global\nCompact on Refugees to expand resettlement and complementary\npathways. Data will be updated on a regular basis, with the report\nintended to be issued by UNHCR-OECD every two years. The next\nreport will be completed in 2020, covering 2018-2019 data.\n\n**43** These nationalities were selected because they account for more\nthan half of the world’s refugees under UNHCR’s mandate and\nhave a high recognition rate for those applying for asylum in\nOECD countries.\n\n**44** [See: ec.europa.eu/eurostat/documents/3859598/9315869/KS-](http://ec.europa.eu/eurostat/documents/3859598/9315869/KS-GQ-18-004-EN-N.pdf%20)\n[GQ-18-004-EN-N.pdf](http://ec.europa.eu/eurostat/documents/3859598/9315869/KS-GQ-18-004-EN-N.pdf%20)\n\n\n\nUNHCR > **GLOBAL TRENDS 2018** 33", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["2018-2019 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000649", "page": 31, "chunk": 2, "title": "UNHCR Global Trends: Forced Displacement in 2018", "pdf_url": "https://reliefweb.int/attachments/5ee61624-975c-3354-9b7e-f2c1e9c8185a/5d08d7ee7.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "2018-2019 data", "label": "VAGUE_DATA", "score": 0.7267340421676636, "start": 297, "end": 311, "probe_score": 0.5634, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|\n\n\n\n54 The plan, according to the POM, will contain a complete overview of all activities for the coming year under the DLI 8. The plan will also specify the target areas, districts, urban centers\nand parishes, based on analysis of the needs and coverage. The plan will also specify the allocation formulas, based on quick assessment of the needs of the 7 target areas.\n55 This will clarify the land rights in the wake of pressure on land occasioned by influx of refugees. The data base will provide quick information on land ownership in case any entity needs\nto acquire land for any purpose.\n56 This will encompass, minimum mission p.a. to each target areas to ensure that the LGs mainstream the PDPs in the annual work-plans, support identification of eligible projects, and\nensure that procurement processes are conducted in accordance with the legal framework.\n\n31", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data base"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000062", "page": 38, "chunk": 2, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents.worldbank.org/curated/en/946901526654169395/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data base", "label": "VAGUE_DATA", "score": 0.6851150393486023, "start": 478, "end": 487, "probe_score": 0.0016, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " new\neducation law (approved in August 2000) sets in place the conditions for broadening participation in\nDjibouti's education system. It provides for setting up school management committees with parent\n\nand community involvement. The law also provides for the creation of conditions to increase private\nsector participation in education.\n\n\n_6.3 How does the project involve consultations or collaboration with NGOs or other civil society_\n_organizations?_\n\n\nThe National Educational Forum consulted all stakeholders including NGOs and civil society during\nthe initial preparation. In addition, the project foresees the increased involvement of parent\nassociations or community-based associations in the management of project activities on the ground\n(i.e., operations & maintenance).\n\n\n_6.4 What institutional arrangements have been provided to ensure the project achieves its social_\n_development outcomes?_\n\n\nThe DGEN will be responsible for monitoring the gender gap in enrollment issues, and the gap\nbetween the poorest and the richest quintiles, and related education services available to them. The\ndata collection on enrollment will be strengthened by the capacity building support provided to the\nMinistry of Education's planning unit - thus over time these issues can be effectively monitored.\nTriggers are included in the APL phasing to ensure that various social development goals are met e.g.\ndecreasing the enrollment gap between the rich and the poor, decreasing the gender gap and increasing\ncommunity participation in school management.\n\n\n_6.5 How will the project monitor performance in terms of social development outcomes?_\n\n\nThe MOE planning unit will monitor enrollment paying attention to gender gaps, socioeconomic gaps\n\nand performance of students by socioeconomic class through use of surveys of students.", "output": {"entities": {"named_data": [], "descriptive_data": ["surveys of students"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000049", "page": 24, "chunk": 1, "title": "Croatia - Reconstruction Project for Eastern Slavonia, Baranja and Western Srijem", "pdf_url": "http://documents1.worldbank.org/curated/en/347691468746725804/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "surveys of students", "label": "DESCRIPTIVE_DATA", "score": 0.8922238349914551, "start": 1811, "end": 1830, "probe_score": 0.3477, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " especially the women who have no<br>significant sources of income (Freedom House 201867). Figures<br>from the 2014 Uganda National Population and Housing<br>Survey indicate that 32 percent of women were not involved<br>in any economic activities, compared to only 26 percent of<br>men (National Housing and Population Census 2014).<br>|<br> <br> <br> <br>• <br>Sub-component 3.2 includes<br>Digital Access program that<br>will support various access<br>affordability initiatives to<br>increase direct access to<br>internet, particularly for<br>women.<br>• <br>The program will integrate<br>feedback by women<br>beneficiaries in the design<br>and target households in<br>refugees and host districts<br>that are among the most<br>vulnerable and left behind in<br>terms of access to mobile<br>devices.<br>• <br>Public Internet access points<br>(Wi-Fi hotspots) and<br>community Internet access<br>schemes (telecenters) with<br>women-friendly opening<br>hours and in women-friendly<br>locations such as markets,<br>informal women’s group<br>meeting locations, water<br>collection points, and public<br>food distribution centers<br>(Sub-components 1.2, 3.1,<br>and 3.2).<br> <br>|<br> <br>|\n|<br>**Low level of digital skills and high incidence of online violence**<br>**especially within refugee and host communities**<br>• <br>While digital skills in Uganda", "output": {"entities": {"named_data": ["National Housing and Population Census 2014"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000023", "page": 63, "chunk": 1, "title": "Uganda - Digital Acceleration Project", "pdf_url": "http://documents.worldbank.org/curated/en/473041622944887337/pdf/Uganda-Digital-Acceleration-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "National Housing and Population Census 2014", "label": "NAMED_DATA", "score": 0.7550765872001648, "start": 287, "end": 330, "probe_score": 0.0187, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nBeirut Housing Rehabilitation and Cultural and Creative Industries Recovery (P176577)\n\n\nstemming from interventions mainly come from the activities of Subcomponent 1.1 Residential Housing Rehabilitation.\nThe main environmental risks associated with this subcomponent may include: (i) consumption of energy, water, and\nbuilding materials (paints, cement, steel, sand, electrical supplies, etc) for buildings rehabilitation; (ii) the generation of\ndomestic solid waste, demolition, and hazardous waste (including asbestos-containing materials from demolition sites);\n(iii) nuisance, related to dust generation, vibration, and noise; (iv) occupational health and safety (OHS) workforce\nhazards, including risk of accidents from inadequate working conditions at construction sites and from covid-19 infection;\n(v) community health and safety (CHS) hazards resulting from work activities particularly for residents and communities\naround the proposed rehabilitation sites; and (vi) disruptions to traffic due to movement of workers and materials which\ncan result in  disruption of access and possible increase in roads accidents.\n\n\n**72.** **Other risks/impacts might result from other project activities conducting public awareness campaigns both on-**\n**site and virtually, and from capacity building activities and technical and grant support to local governments, cultural**\n**organizations and practitioners. These risks/impacts include mainly health and safety risks related to Covid-19, road**\n**accidents, and mismanaged waste, including solid and e-waste.** While UN-Habitat has good technical expertise in\nhousing and has been supporting the municipalities of Beirut and Bourj Hammoud including capacity building at the\nmunicipal level, this is the first project it is implementing under the ESF. This could result in implementation challenges\nand is an additional reason for rating Environmental risk as substantial. UN-Habitat is expected to establish a PMT, which", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 32, "chunk": 0, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " those identified in Chongqing Municipal Government's\n_Master Plan for Experimental Reform_ (World Bank, 2009). <sup>33</sup> Shihezi City, a county-level\ncity under the direct jurisdiction of Xinjiang Province, also enters our dataset. <sup>34</sup> [^34: There are 4 county-level cities in Xinjiang that are under the direct jurisdiction of Xinjiang Province. These\ncities are also called \"sub-prefecture-level cities\" or \"vice-prefecture-level cities\" (http://en.wikipedia.org/wiki/\n<u>Sub-prefecture-level_city). Shihezi City is included in our sample because, after Urumqi, it is the second largest</u>\ncity in terms of population in Xinjiang (http://en.wikipedia.org/wiki/Shihezi). It is also the only sub-prefecturelevel city in Xinjiang for which adequate data was available.]\n\nOur sample size of 331 regions exceeds that of previous studies in the empirical NEG\nliterature which have made use of prefectural level data (Au and Henderson, 2006; Hering\nand Poncet, 2010a; and Bosker _et al_ ., 2010). This is because these studies have, by and large,\nrestricted themselves to prefectural level cities.\n\n_Variables used in the estimation of the urban and rural wage equations_\n\n**Urban wage rate (** **_w_** <sup>**_U_**</sup> **):** proxied by average disposable income per capita for urban\nhouseholds. Urban household disposable income is the actual income at the disposal of\nmembers of a household which can be used for final consumption, other non-compulsory\nexpenditure and savings. It is equal to the total income of an urban household minus\npayments to cover income tax and personal contributions to social security, and the income\nsubsidy received by a sample household for keeping a diary. **Source:** _Regional Economic_\n_Statistical Yearbook 2008_ .\n\nData is missing for 14 prefectures on this variable. These missing values have been filled-in-provincial", "output": {"entities": {"named_data": [], "descriptive_data": ["prefectural level data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004665", "page": 35, "chunk": 1, "title": "wps5479", "pdf_url": "https://local/prwp/wps5479.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "prefectural level data", "label": "DESCRIPTIVE_DATA", "score": 0.8599857687950134, "start": 905, "end": 927, "probe_score": 0.5154, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<br>education) in all secondary<br>schools. The enrollment rate<br>is calculated as the number<br>of boys (girls) studying in<br>real profile in grades 9-12 in<br>a given year, expressed as a<br>percentage of the total<br>number of boys (girls)<br>enrolled in grades 9-12<br>(Baseline: Girls: 27%; Boys:|<br> <br>Annual<br>|EMIS<br>|EMIS data<br>|CTICE, MoER, PMT<br>|\n\n\nPage 40 of 68", "output": {"entities": {"named_data": ["EMIS data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000185", "page": 49, "chunk": 1, "title": "Moldova - Education Quality Improvement Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099051123142553305/pdf/BOSIB-624554c1-598f-4576-aa60-cca7d93b64e7.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "EMIS data", "label": "NAMED_DATA", "score": 0.8238853812217712, "start": 333, "end": 342, "probe_score": 0.9429, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " various stages of project development, in line with legal and\npolicy frameworks including the UNRA Environment and Social Management System (2019)\nguidelines on stakeholder engagements.\n\nStakeholder engagement is an interactive process that aims to build and maintain an open and\nconstructive relationship with stakeholders and thereby facilitate and enhance project management\nof its activities and operations, including its environmental and social effects and risks. It is a more\ninclusive and continuous process between a project (and or developer) and those potentially affected\nby or have an interest in the project.\n\nIn the context of this SEP, a stakeholder refers to individuals or groups who: (a) are affected or likely\nto be affected by the project (project-affected parties); and (b) may have an interest in the project\n(other interested parties). They may include local communities, national and local authorities,\nneighboring projects, and non-governmental organizations (WB-ESS10).\n\n\n6", "output": {"entities": {"named_data": ["WB-ESS10"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003667", "page": 16, "chunk": 2, "title": "Stakeholder Engagement Plan (SEP) UpdateMay2024 Uganda: Roads and Bridges in the Refugee Hosting Districts/Koboko-Yumbe-Moyo Road Corridor Project (P171339)", "pdf_url": "https://documents.worldbank.org/curated/en/099071924132540217/pdf/P171339-aae74234-d195-4884-a7eb-f09c67d2034e.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "WB-ESS10", "label": "NAMED_DATA", "score": 0.5021226406097412, "start": 987, "end": 995, "probe_score": 0.4286, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "DTM Mali – Décembre 2021\n\n|Mali - Indice de Stabilité|Décembre 2021|\n|---|---|\n|<br>**Source : Direction Nationale du Développement Social - DNDS** <br>|<br>**Source : Direction Nationale du Développement Social - DNDS** <br>|\n\n\n##### Perception de la stabilité\n\n\nAu niveau des 305 localités, les informateurs clés ont affirmé qu’un peu plus de trois quart (87%) des communautés\nse sentaient en sécurité dans leurs lieux de déplacement. Cependant, au niveau de 13% des localités évaluées, les\ncommunautés ne se sentaient pas en sécurité. Ceux-ci concernent principalement les localités évaluées dans les\ncercles de Bankass, Douentza, Bandiagara, Tenenkou et Ansongo.\n\n\nGraphique 25 : Sentiment de la communauté sur la situation sécuritaire\n\n\n\n\n##### **35**", "output": {"entities": {"named_data": ["DTM Mali – Décembre 2021", "Mali - Indice de Stabilité"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001542", "page": 40, "chunk": 0, "title": "Mali : Rapport Matrice de Suivi des Déplacements (DTM) Décembre 2021", "pdf_url": "https://reliefweb.int/attachments/ef131fcc-6e46-3a05-983e-452f0f0f5ef6/dtm_decembre_2021.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "DTM Mali – Décembre 2021", "label": "NAMED_DATA", "score": 0.5258611440658569, "start": 0, "end": 24, "probe_score": 0.9937, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Mali - Indice de Stabilité", "label": "NAMED_DATA", "score": 0.7194601893424988, "start": 27, "end": 53, "probe_score": 0.9885, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". changes\nin _Mi2_ for all _i_ importers) and would make us stray from this paper’s objective. Leaving this question to\nfuture research, our concern remains with bilateral trade; MR is only relevant for our efforts to calculate\nthe bilateral comparative static effects correctly.\n\n#### **4. Data and estimation**\n\n\nWe use the same data as Baier & Bergstrand (2007), <sup>11</sup> [^11: We thank Scott Baier and Jeff Bergstrand for facilitating our use of the data.\n12The analyses covers the period from 1960 till 2000 and a total of 119 new agreements have been implemented\nsince 2000, with about 50% of them being S-S and 40% being N-S agreements.] which come from various sources: nominal\nbilateral trade flows for 96 trading partners and at 5 year intervals from 1960 till 2000 come from the\nInternational Monetary Fund's Direction of Trade Statistics; nominal GDPs are from the World Bank's\nWorld Development Indicators (2003); bilateral distances, language and adjacency dummy variables\nwere compiled from the CIA Factbook; and the FTA dummy variable was calculated using appendices in\nLawrence (1996) and Frankel (1997) as well as various websites detailed in the Data Appendix. It includes\nfull FTAs and customs unions but not partial agreements. 10% of them are between Northern countries,\n31% between Northern and Southern countries and 49% between countries from the South. A list of the\ntrade agreements analyzed, including a classification of them into North-North, North-South and SouthSouth FTAs is detailed in the Data Appendix together with a table containing the 96 potential trading\npartners. <sup>12</sup>\n\n\nOur estimation approach draws on that of Baier & Bergstrand (2007) but instead of having only one\ndummy for the FTA, we split agreements into those between two Northern countries, between two\nSouthern countries and between a Northern country and a Southern country. The criteria to classify\n\n10 For example, countries 1 and 2 can be Chile", "output": {"entities": {"named_data": ["Direction of Trade Statistics", "World Development Indicators", "CIA Factbook"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004808", "page": 11, "chunk": 1, "title": "wps5626", "pdf_url": "https://local/prwp/wps5626.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Direction of Trade Statistics", "label": "NAMED_DATA", "score": 0.8960198760032654, "start": 825, "end": 854, "probe_score": 0.9917, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "World Development Indicators", "label": "NAMED_DATA", "score": 0.9027988314628601, "start": 895, "end": 923, "probe_score": 0.9824, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "CIA Factbook", "label": "NAMED_DATA", "score": 0.8654388785362244, "start": 1015, "end": 1027, "probe_score": 0.9904, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n# **2.** Situation of refugees from Ukraine on the labour market in Poland\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 7.** Unemployment rate\n\n\n12%\n\n\n10%\n\n\n8%\n\n\n6%\n\n\n4%\n\n\n2%\n\n\n0%\n\n\n**Source:** Harmonized data, Eurostat, <u>[Statistics | Eurostat (europa.eu)](https://ec.europa.eu/eurostat/databrowser/view/une_rt_m/default/table?lang=en)</u>\n\n\n##### Refugees from Ukraine fit well into the needs of the Polish labour market.\n\nUkrainians arrived on a labour market that\nstructurally needs more workers, as the\ndomestic population is ageing rapidly, while\nthe economy is growing. High levels of\neducation, cultural proximity and previous\nconnections to Poland helped refugees\nadapt to the labour market. Furthermore,\nPoland made an important and strategic\npolicy decision by promptly opening\nthe labour market and supporting their\ninclusion.\n\n\n16\n\n\n\n17\n\n\n\n**Chart 6.** Working age population with Polish citizenship (20-64 years old)\n\n\n\n25\n\n\n24\n\n\n23\n\n\n22\n\n\n21\n\n\n20\n\n\n\n\n\n\n\n\n\n\n\nThe number of people of working age\nin Poland is shrinking and is expected\nto keep declining. Although substantial\nmigrations from Poland after EU accession\nin 2004 <sup>19</sup> [^19: Statistics Poland data, <u>[https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-](https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-temporary-stay-from-poland-between-2004-2020,8,14.html)</u>\n<u>[temporary-stay-from-poland-between-2004-2020,8,14.html](https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-temporary-stay-from-poland-between-2004-2020,8,14.html)</u>] distort population data, the\ndomestic", "output": {"entities": {"named_data": ["Statistics Poland data"], "descriptive_data": ["Harmonized data"], "vague_data": ["population data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 8, "chunk": 0, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Harmonized data", "label": "DESCRIPTIVE_DATA", "score": 0.5011885762214661, "start": 309, "end": 324, "probe_score": 0.993, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Statistics Poland data", "label": "NAMED_DATA", "score": 0.7888239622116089, "start": 1275, "end": 1297, "probe_score": 0.9929, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "population data", "label": "VAGUE_DATA", "score": 0.6540866494178772, "start": 1857, "end": 1872, "probe_score": 0.6838, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "economies. <sup>6</sup> Aggregate or macroeconomic indicators based on average household indebtedness,\n\n\nhowever, mask the likely concentration of borrowing among selected households, including among\n\n\nthose that are more vulnerable or less able to service their debt in the event of an economic slowdown.\n\n\nDebt holding could vary significantly across household income groups, across age and other\n\n\ndemographic groups. To answer the above questions on the welfare and stability implications of\n\n\nincreasing household indebtedness, micro-level data are therefore necessary. <sup>7</sup> [^7: To date, most micro-level studies focus on one country, such as Żochowski and Zajączkowski (2007) on Poland, NBS\n(2006) on the Slovak Republic, CNB (2009) on the Czech Republic, Beer and Schulz (2007) on Austria, Holló (2007) on\nHungary. These studies do _not_ assess the drivers of household debt holding and, because they are country specific, do not\nexplore cross-country differences in household indebtedness. In addition, a recent study of Bosnia and Herzegovina (Chen\nand Chivakul 2008) looks at household credit market participation (self-reported desire to borrow) and credit constraint\n(whether refused a loan). Even in more advanced economies outside Central Europe, analyses of micro data on household\ndebt have been few and very recent. See for example BIS (2007) and Dynan and Kohn (2007). Crook (2006) reports that\nmost studies using survey data focus on the US, though there are some limited recent work on the UK and Italy.]\n\n\nThis paper (i) documents the recent rapid increase in access to consumer and mortgage credit\n\n\nby households in the new EU member countries, (ii) compares use of mortgage credit by households of\n\n\ndifferent characteristics across old and new EU member countries, and (iii) assesses whether mortgage\n\n\nholding can result in a financial burden, at least during the period preceding the current global financial\n\n\ncrisis. We use aggregate data as well as household-level data in our analysis. Specifically,", "output": {"entities": {"named_data": [], "descriptive_data": ["micro-level data", "household-level data"], "vague_data": ["survey data", "aggregate data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004394", "page": 5, "chunk": 0, "title": "wps5202", "pdf_url": "https://local/prwp/wps5202.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "micro-level data", "label": "DESCRIPTIVE_DATA", "score": 0.6702619194984436, "start": 533, "end": 549, "probe_score": 0.939, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.6066370606422424, "start": 1441, "end": 1452, "probe_score": 0.8747, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "aggregate data", "label": "VAGUE_DATA", "score": 0.6754942536354065, "start": 1962, "end": 1976, "probe_score": 0.6952, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "household-level data", "label": "DESCRIPTIVE_DATA", "score": 0.6419244408607483, "start": 1988, "end": 2008, "probe_score": 0.6586, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " who will have flexibility in setting costrecovering tariffs (subject to a ceiling) and selecting the appropriate generation, distribution, and\nmetering technologies (subject to minimum standards). The project will provide capacity-building\nsupport to ARSE, with respect to regulation of grid- and mini-grid-based systems.\n(d) **Clean cooking.** Local innovation and localized solutions are critical for long-term sustainability.\n\nCooking is a contextualized system with no one-size-fits-all solution. Although projects share\ncommon barriers, the best solutions will vary by location owing to differences in cooking behavior,\nculture, resources, institutions, and market conditions. Therefore, the project will empower the\ndevelopment of localized solutions, based on lessons from international experience, including the\nlatest technology innovations.\n\n\n\n**IV.** **PROJECT APPRAISAL SUMMARY**\n\n\n**A.** **Technical, Economic and Financial Analysis**\n\n\n**Technical Analysis**\n\n\n77. The choice of technical solutions for electrification was informed by the preliminary outcomes of\nthe ongoing national electrification analysis for Chad that prioritized isolated power systems for cities,\nmini-grids for towns, and SSSs for rural areas. The analysis considered the density of population, the\nexisting and potential loads, the existing power systems, the planned construction of the high-voltage\ntransmission line connecting the Chad and Cameroon power systems, and the ability and willingness of\nhouseholds to pay for electricity services.\n\n78. Component 1 will support grid-based electrification in N’Djamena, 12 cities with existing grids,\nand cities and towns with no grids. It will rely on well-established and commercially available technologies\nthat do not pose any major technical challenges. A technical design of the continued electrification of\nN’Djamena will be prepared by a competitively selected owner’s engineer hired under the CCPIP. The\nOwner’s Engineer will subsequently accompany SNE in supervising", "output": {"entities": {"named_data": [], "descriptive_data": ["national electrification analysis for Chad"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 37, "chunk": 1, "title": "Chad - Energy Access Scale Up Project", "pdf_url": "http://documents.worldbank.org/curated/en/860701648216750651/pdf/Chad-Energy-Access-Scale-Up-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "national electrification analysis for Chad", "label": "DESCRIPTIVE_DATA", "score": 0.6717489957809448, "start": 1090, "end": 1132, "probe_score": 0.0111, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". Orientation, counseling and skills training activities will focus on providing a foundational\nset of skills to ex-combatants as they begin the transition to civilian life. The survey on signatory\nmovements found that traditional authorities, leaders of signatory movements; as well as\ncombatants recognize the importance of having skills in the aftermath of the DDR program. In\neach community, there will be an ex-combatant focal point who will support the project with\nfeedback, concerns and suggestions, as well as monitoring purposes.\n\n25. In addition, for those combatants identified as requiring psychosocial support during\nscreening in cantonments, the Project will provide counseling during the first six months.\nPsychosocial suffering and mental and behavioral disorders are risk factors for socio-economic\n\n14 Exact duration will be determined depending on the type of the skills training.\n\n\n6", "output": {"entities": {"named_data": [], "descriptive_data": ["survey on signatory\nmovements"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000148", "page": 16, "chunk": 1, "title": "Mali - Reinsertion of Ex-combatants Project", "pdf_url": "http://documents1.worldbank.org/curated/en/848361679677867655/pdf/Mali-Reinsertion-of-Ex-combatants-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "survey on signatory\nmovements", "label": "DESCRIPTIVE_DATA", "score": 0.9368733167648315, "start": 178, "end": 207, "probe_score": 0.3776, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Analysis of the impact of refugees from Ukraine on the economy of Poland**\n\n\n**Economists have advanced an array of factors that could be causing these macro-level effects. While macro-level**\n**regressions show a positive impact of immigration on productivity, they cannot show the exact channels through which**\n**these effects come about. It is thus uncertain which are dominant. Among them are:**\n\n\n# Conclusions\n\n\n\n**Analysis of the impact of refugees from Ukraine on the economy of Poland**\n\n\n\nDeloitte’s D.Climate general equilibrium\nmodel finds that refugees from Ukraine\ncontributed 0.7-1.1% to GDP cumulatively in\n2023. In the long-term this effect will grow\nto 0.9-1.35% as the economy fully adjusts.\nThe increases in government revenue from\ndirect and indirect taxes due to wages\nand private consumption of refugees from\nUkraine was likewise modelled.\nThese increases amounted to 0.8-1.0%\nhigher general government revenues in\n2022, 1.3-1.6% in 2023, and 0.95-1.13%\nin the long term. This implies that, while\nthere are no precise public data on the\ngovernment support to refugees from\nUkraine, while a government official quoted\ncost figures of 15-20 billion PLN in 2022\nand around 5 billion in 2023 <sup>50</sup> [^50: E.g. vice-president of Polish Development Found Bartosz Marczuk estimated it at around 16 billion PLN, but this estimation also included spending of\nNGOs which was combined with spendings of local governments <u>[Polska pomoc dla Ukrainy 2022 - ile kosztowała? - Infor.pl.](https://www.infor.pl/prawo/nowosci-prawne/5635962,Polska-pomoc-dla-Ukrainy-2022-ile-kosztowala.html)</u>] have been\nalready offset by refugees via taxes of\n12.3-15.2 billion PLN in 2022 and 18.2-22.5\nbillion PLN in 2023.\n\n\nAll the modelling results are conservative\nlower bound estimates, as econometric\nstudies from other", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["public data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 20, "chunk": 0, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "public data", "label": "VAGUE_DATA", "score": 0.7248950004577637, "start": 1044, "end": 1055, "probe_score": 0.9561, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " will be implemented first to ensure timely project implementation. Should any counties\nbe deemed unfeasible, they will be replaced by ‘replacement counties’ on the long list. In some cases,\ncertain _payams_ within selected counties will be inaccessible or difficult to access for a number of reasons.\nThey may also be among the most deserving of project investments due to the vulnerability of their\npopulations. In such cases, efforts will be made to adapt a participatory methodology for the\ncircumstances at hand, to engage surrounding _payams_ and counties in investment and resolution\nstrategies for such locations, or to defer investment until a later round when conditions improve.\n\n\n**Figure 2.10. Subproject Budget Allocation**\n\n\n8. **Use of community labor.** The project will encourage contractors to use local labor in the\ninfrastructure construction or rehabilitation to the extent possible. Emphasis will be given to the inclusion\nof various social groups facing marginalization or barriers to participation (for example, women, youth,\nreturnees, ethnic minority groups, and people with disabilities) and ensuring their access to community\ninfrastructure and daily wage labor opportunities. It will be especially important to include women in the\n\n\n80 Population figures for urban areas would be calculated based on a headcount or by complementing 2008 census with other data sources (for\nexample, DTM).\n\n\nPage 71 of 94", "output": {"entities": {"named_data": ["DTM"], "descriptive_data": ["2008 census"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 76, "chunk": 1, "title": "South Sudan - Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/824121596765983121/pdf/South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "2008 census", "label": "DESCRIPTIVE_DATA", "score": 0.6600024700164795, "start": 1363, "end": 1374, "probe_score": 0.0902, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "DTM", "label": "NAMED_DATA", "score": 0.8937270641326904, "start": 1413, "end": 1416, "probe_score": 0.0021, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "In particular, we compare the change in the satisfaction with food consumption of both\n\n\nthe head and the spouse to the change in the share of households where the most senior\n\n\nwoman (most often the head’s spouse) claimed to “not have enough food or money to\n\n\nhave food.” Similar to the question on satisfaction, the interpretation of “enough” might\n\n\nvary from household to household, and a respondent’s interpretation of “enough” might\n\n\nhave changed following the capture of Sana’a. Also, there could have been a difference\n\n\nin opinion between household heads and the most senior woman in the house about the\n\n\nadequacy of food consumption.\n\n\nTable 6 re-estimates the baseline specification, but uses the indicator for whether\n\n\nthe household had enough food. Column (1) demonstrates that there was an increase\n\n\nin the share of households where the most senior woman reported not having enough\n\n\nto eat following the capture of the city of 8.5 percentage points. Columns (2) and (3)\n\n\nrespectively limit the sample to households where the head did and did not finish primary\n\n\nschool. The results were stronger for less educated households that were more strongly\n\n\nand immediately impacted by the capture. These patterns are consistent with previously\n\n\nestimated changes in food security following the capture of Sana’a (e.g., Tandon 2019). <sup>30</sup>\n\n\nFurthermore, given that each household answered both the question on satisfaction\n\n\nwith food consumption and whether the household had enough to eat, we are able to\n\n\nidentify households where the two metrics did not align well. Specifically, we use an indi\n\ncator equal to one if the household did not have enough food but did report being satisfied\n\n\nwith food consumption as the dependent variable and re-estimate the baseline specifica\n\ntion. We use separate indicators for alignment between the head’s satisfaction with food\n\n\nconsumption and whether the most senior woman in the house claimed there was enough\n\n\nfood, and for alignment between the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000826", "page": 18, "chunk": 0, "title": "idu06ca2ef8a0b8400459d09f400e9038b642fb6", "pdf_url": "https://local/prwp/idu06ca2ef8a0b8400459d09f400e9038b642fb6.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda: Roads and Bridges in the Refugee Hosting Districts Project (P171339)\n\n\nmanagement; (iv) training on FIDIC contracts and contract management in general; (v) recruitment and\ndeployment of adequate staff <sup>61</sup> [^61: hiring of specialists including an environmental specialist, a social development specialist, a valuer, and two road inspectors] to ensure sufficient inhouse technical capacity to support the bidding\nprocess and to supervise the contractors and consultants; (vi) to enhance the Environment and Social\nSafeguards compliance on site, the Resident Engineer shall have knowledge on Environment and Social\nsafeguards and the Contractors must present Environmental and social safeguards staff that meet minimum\nrequirements before works are allowed to commence; (vii) preparation of contract management plans; (viii)\ntimely provision of funds for compensating PAPs and for maintenance; (ix) at least 40 percent of the\ncontinuous section of the corridor to be acquired before award of works; (x) engagement of a short term\nConsultant Procurement Specialist proficient in the World Bank procedures and with ToR acceptable to the\nWorld Bank to support the processing of these contracts; (xi) UNRA has put in place a peer review\nmechanism to ensure completeness of the evaluation criteria; and (xii) put in place a procurement\ncomplaints records system.\n\n\n~~.~~ **<u>C. Legal Operational Policies</u>**\n\n\n\n\n\n**D. Environmental and Social**\n\n\n108. **Management of Environmental and Social Aspects.** The proposed 105 km-long Koboko-Moyo-Yumbe road\nupgrade will entail construction of a 7.0 m carriageway (2 x 3.5m lanes), including key features such as shoulders,\nservice and parking lanes, raised paved walkways (including the covered drain) in the major towns of Koboko,\nYumbe and Moyo; and in the minor towns of Lodonga and Kuru, bus lay bays in larger locations with high levels\nof public activity, replacement of existing cross drainage structures", "output": {"entities": {"named_data": [], "descriptive_data": ["procurement\ncomplaints records system"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 45, "chunk": 0, "title": "Uganda - Roads and Bridges in the Refugee Hosting Districts/Koboko-Yumbe-Moyo Road Corridor Project", "pdf_url": "http://documents.worldbank.org/curated/en/834931600048847296/pdf/Uganda-Roads-and-Bridges-in-the-Refugee-Hosting-Districts-Koboko-Yumbe-Moyo-Road-Corridor-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "procurement\ncomplaints records system", "label": "DESCRIPTIVE_DATA", "score": 0.7355613112449646, "start": 1353, "end": 1390, "probe_score": 0.0489, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "# Appendix. Model Calibration\n\n\n##### D.Climate is CGE 51 model developed by Deloitte Economic Institute based on GTAP model 52 . If source of data is not specified it means that shocks were calibrated to data from the model database.\n\nIt was assumed that impact of refugees on\nthe Polish economy was felt as combined\nfour different shocks: to population, labour\nsupply, average propensity to save, and\nproductivity, with shocks to population and\nlabour supply being balanced by equivalent\nshocks in Eastern Europe <sup>53</sup> [^53: Region combined from: Russia, Belarus, Ukraine, Moldova, Czechia, Slovakia, Hungary, Romania, and Bulgaria.] .\nMoreover, as part of assumed increase\nin spending by Ukrainians in Poland was\nfinanced by savings from Ukraine this was\nbalanced by equivalent negative shock on\ninvestment in Eastern Europe.\n\n\nShock to population was calibrated to\nmatch data for residents of Poland from\nStatistics Poland and number of refugees\nbased on PESEL UKR. Equivalent shock in\nEastern Europe was calculated using data\nfor population in this region from World\nPopulation Prospects UN.\n\n\n\nShock to labour supply was calibrated\nto match data of working Ukrainians\npresented in chapter 2. As we didn’t have\ndata of number of unemployed refugees,\nwe calibrated it that an increase in the\nnumber of workers due to an increase in\nlabour supply matched employment data\nin two variants: lower (around 225 thou.)\nand higher employment (around 350 thou.).\nTotal increase in labour supply in Poland\nwas balanced by equal decrease of labour\nsupply in Eastern Europe.\n\n\nShock to propensity to save was calculated\nin two steps. First and foremost, it was\nassumed that due to their precarious life\nsituation refugees won’t save any income.\nAs such shock was set to match shock for\nthe population <sup>54</sup> [^54: All shocks are percent deviations.] . Additionally, to account\nfor spending of savings from Ukraine, data\nfrom the National Bank of Ukraine on\ncash", "output": {"entities": {"named_data": ["PESEL UKR", "World\nPopulation Prospects UN"], "descriptive_data": ["data for residents of Poland", "data\nfor population in this region", "data of working Ukrainians"], "vague_data": ["employment data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 21, "chunk": 0, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data for residents of Poland", "label": "DESCRIPTIVE_DATA", "score": 0.8638429045677185, "start": 883, "end": 911, "probe_score": 0.9983, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PESEL UKR", "label": "NAMED_DATA", "score": 0.900190532207489, "start": 967, "end": 976, "probe_score": 0.9527, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data\nfor population in this region", "label": "DESCRIPTIVE_DATA", "score": 0.7129075527191162, "start": 1034, "end": 1068, "probe_score": 0.9942, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "World\nPopulation Prospects UN", "label": "NAMED_DATA", "score": 0.767244279384613, "start": 1074, "end": 1103, "probe_score": 0.9994, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data of working Ukrainians", "label": "DESCRIPTIVE_DATA", "score": 0.8193343281745911, "start": 1155, "end": 1181, "probe_score": 0.9773, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "employment data", "label": "VAGUE_DATA", "score": 0.6340323686599731, "start": 1366, "end": 1381, "probe_score": 0.8191, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "its Public Expenditure\nTracking Survey (PETS)\n\nscorecard inproves each\nsemester\n\n\n\n**Project Components /** **Inputs:** **(budget for** each Project reports: (from Components to\nSub-components: component) Outputs)\n\n\n\n1. Community Driven - US$ 28.0 million (IDA $25.0 <sup>- M&E data</sup> - Cormnunities emnpowered\n\n\n\n**Program** (CDP) million) - Quarterly progress reports; and responsible for\nimplementing sub-projects;\n\n                                                  - Implemnenting partners <sup>are</sup>\ncomnpetent to support\n**2.** Pilot and Special\n\n\n\n**Programs in** Newly cormmunities;\n\n                                                - Implementing partners\n**Accessible** **Areas**\n\n                - US$ 2.0 mnillion (ODA <sup>$1.75</sup> participate in capacity building\n\n\n\n**(a)** **Rural Public Works** million) activities;\n\n                - US$ 2.0 million (IDA <sup>$1.75</sup>                - Operations Manual and\n\n\n\n**(b)** **Shelter** Program **for** million) annexed Handbooks for Direct\n\nFinancing to Communities <sup>and</sup>\n**Vulnerable** **Groups**\n\n               - US$ 10.0 million (IDA <sup>$6.5</sup>                - NaCSA and IDA Public Works are thorough,\n\n\n\n3. **Project** **Manaeem2nt** <sup>**and**</sup> <sup>million)</sup> administrative data appropriate, and clear in\n\n\n\ndefining the and\n**In", "output": {"entities": {"named_data": ["Public Expenditure\nTracking Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010305", "page": 32, "chunk": 0, "title": "Uganda - Second Education Project", "pdf_url": "https://documents.worldbank.org/curated/en/257101468114871359/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Public Expenditure\nTracking Survey", "label": "NAMED_DATA", "score": 0.8658173084259033, "start": 4, "end": 38, "probe_score": 0.357, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "output": {"entities": {"named_data": [], "descriptive_data": ["random survey"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010408", "page": 16, "chunk": 0, "title": "Kenya - Baringo Pilot Semi-arid Areas Project", "pdf_url": "https://documents.worldbank.org/curated/en/264151468040735476/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7714613080024719, "start": 379, "end": 395, "probe_score": 0.582, "gold": "NON_MENTION", "gold_tier": "flip"}, {"text": "random survey", "label": "DESCRIPTIVE_DATA", "score": 0.7173007130622864, "start": 1487, "end": 1500, "probe_score": 0.012, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Figure 9: Percentage of students having access to means of online education\n\nSource: SAEB 2017\n\n\nHowever, it also shows that about 90% of the students across Brazil has access to television and\nsome states in Brazil, namely Amazonas, Piaui, Parana, Distrito Federal and _Maranhao_ have already\nbegun to broadcast educational content through television. According to the student vulnerability\nindex, published by World Bank, Roraima is one of the most vulnerable states in Brazil, where\nstudents face high dropout, less family support, higher incidence of working and lower technology.\nSince most of the Venezuelan children are living in Roraima, they are more susceptible to disrupted\nlearning due to the pandemic.\n\n\nSchool closures also mean that the social safety nets through schools are also a↵ected. Many\nchildren depended on the school meals as their only source of nutritious meals. Consequently, Law\n13,987/2020 has been enacted by the federal government, allowing the resources originally allocated\nto providing school meals in all public schools (under the national School Meals Program—PNAE)\nto be used to buy basic food baskets for disadvantaged families. Before this change, many municipalities were already distributing food baskets to the families of vulnerable students (World Bank, 2020).\n\n\nE↵ect of the COVID-19 pandemic on the labor market is heterogenous, a↵ecting some types\nof jobs more than others. Unfortunately, the risk of employment disruptions are higher in service\nbased jobs and Venezuelans, as discussed previously, are heavily concentrated in those service sector\n\n\n28", "output": {"entities": {"named_data": ["student vulnerability\nindex"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000075", "page": 29, "chunk": 0, "title": "Policy Research Working Paper 9605: Integration of Venezuelan Refugees and Migrants in Brazil", "pdf_url": "https://reliefweb.int/attachments/013ad1f5-bb54-390e-8874-f0ec29458336/Integration-of-Venezuelan-Refugees-and-Migrants-in-Brazil.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "student vulnerability\nindex", "label": "NAMED_DATA", "score": 0.5777921080589294, "start": 370, "end": 397, "probe_score": 0.7676, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "-Q1 Q3-Q2 Q4-Q3<br>Q1<br>Q2<br>Q3<br>Q4<br>Italy|**Table 10. Origin of asylum applicants in Europe by quarter, 2007**<br>Covering 37 European countries which provided monthly data to UNHCR (excluding Italy).<br>Total<br>2007<br>No. of applications (excluding Italy)<br>Change (%)<br>Share (%)<br>including<br>Origin<br>Q1<br>Q2<br>Q3<br>Q4<br>Total<br>Q2-Q1 Q3-Q2 Q4-Q3<br>Q1<br>Q2<br>Q3<br>Q4<br>Italy|**Table 10. Origin of asylum applicants in Europe by quarter, 2007**<br>Covering 37 European countries which provided monthly data to UNHCR (excluding Italy).<br>Total<br>2007<br>No. of applications (excluding Italy)<br>Change (%)<br>Share (%)<br>including<br>Origin<br>Q1<br>Q2<br>Q3<br>Q4<br>Total<br>Q2-Q1 Q3-Q2 Q4-Q3<br>Q1<br>Q2<br>Q3<br>Q4<br>Italy|Total<br>2007<br>including<br>Italy|\n|Origin|No. of applications (excluding Italy)|No. of applications (excluding Italy)|No. of applications (excluding Italy)|No. of applications (excluding Italy)|No. of applications (", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["monthly data", "monthly data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000427", "page": 22, "chunk": 11, "title": "Asylum Levels and Trends in Industrialized Countries 2008 - Statistical Overview of Asylum Applications Lodged in Europe and selected Non-European Countries", "pdf_url": "https://reliefweb.int/attachments/3ab13bab-8d4b-3f86-b90a-e2540078aef7/2F800689DD12C5A78525758300561F85-unhcr-asylumtrends-mar2009.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "monthly data", "label": "VAGUE_DATA", "score": 0.7005274891853333, "start": 167, "end": 179, "probe_score": 0.9262, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "monthly data", "label": "VAGUE_DATA", "score": 0.5927183032035828, "start": 521, "end": 533, "probe_score": 0.9072, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "# Abstract\n\n\n\nThe beginning of the full-scale\nwar in Ukraine in February\n2022 resulted in a large outflow\nof refugees, reaching more\nthan 6 million globally.\n\n\nMuch of this exodus happened through the\nPolish border. As of October 2023, almost\n1 million Ukrainian refugees were living in\nPoland. While in the past decade Poland\nexperienced large labour migration from\nUkraine, the refugee inflow had a\ndifferent demographic composition.\nIt primarily included working age women\n(41%) and children (40%). These refugees\nfrom Ukraine did not plan to move, and\nmany had special needs. Despite these\ndifficulties, refugees began entering\nthe labour market surprisingly quickly –\nattaining an employment rate of 28% in\nMay 2022 and 65% in November 2022\n(NBP, 2023). By July-August 2023 Ukrainian\nrefugee households supported themselves,\nwith 80% of their incomes coming from work. <sup>1</sup> [^1: Deloitte calculations based on Multi-Sector Needs Assessment Poland 2023 survey data provided by UNHCR.]\n\n\nWe find that refugees from Ukraine who\nremain in Poland as workers, entrepreneurs,\nconsumers, and taxpayers have a positive\nimpact on economic output, which will\nincrease in the long run. Results of our\ngeneral equilibrium Deloitte D.Climate\nmodel show that refugees from Ukraine\ncontributed 0.7-1.1% to the Gross Domestic\nProduct in 2023. In the long-term this effect\nwill grow to 0.9-1.35%. In our model, the\n\n\n\nlong-term is defined as the period over\nwhich the economy fully adjusts to the\nshock of the initial refugee inflow; it does not\ninclude other aspects, e.g. refugee children\ngrowing-up and entering employment.\nThese results are consistent with previous,\nsimilar studies. However, they should be\ntreated as lower-bound estimates, as we do\nnot allow for the possibility of an increase\nin the labour force triggering a positive\nproductivity shock (e.g., due to increased\nspecialisation), because there is little data to\ncredibly estimate its size.\n\n\nA feature of our modelling approach is", "output": {"entities": {"named_data": ["Multi-Sector Needs Assessment Poland 2023 survey data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 2, "chunk": 0, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Multi-Sector Needs Assessment Poland 2023 survey data", "label": "NAMED_DATA", "score": 0.8479331135749817, "start": 923, "end": 976, "probe_score": 0.9991, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEthiopia Rural Productive Safety Net Project (P163438)\n\n\nimproving their food security, and targeting is progressive largely due to the quality of community-based household\ntargeting. Relative to non-beneficiaries, RPSNP beneficiaries in both highlands and lowlands are poorer, have fewer\ndurable assets, have an older household head and live in places with less vegetation. The assessment drew attention to\nthe declining relevance of food security as a defining characteristic of the poorest as only one in ten people in Ethiopia\nsuffer from self-reported food shortages, but one in four live below the poverty line. This leads to recommendations\nwhich are discussed in the Lessons Learned section.\n\n**Environmental and Climate Impacts**\n45. **The RPSNP aimed to address environmental degradation as an underlying cause of food insecurity through**\n**public works (PW).** The planning and implementation of PW sub-projects relies on a community-based approach to\nintegrated watershed management, contributing to the rehabilitation of entire community watersheds, improved\nagricultural productivity and livelihoods, and climate change adaptation and mitigation. Overall, the PW program\ncovers around 12,000 watersheds. The 2019 PWIA found that across ten watersheds and rangeland areas sampled,\n183,000 tons CO2/Anum were sequestered, as well as substantial improvements in watershed resource management.\nAcross 8 sampled watersheds, soil erosion was reduced by 36 percent, woody biomass in non-pastoral watersheds\nincreased by 169 percent, and carbon sequestration resulting from increased vegetation cover increased from 3.25 to\n4 MT Co2 per hectare between 2015 and 2019. This translated into livelihoods and health benefits for agricultural\nhouseholds: crop yields in sample watersheds grew by 24 percent, irrigated crop production rose from 12 to 26 percent\nof households (including 6 to 12 percent for female-headed households), and access to safe water increased to 100\npercent in several watersheds while incidence of diarrhea fell by 3.6 percent between", "output": {"entities": {"named_data": ["2019 PWIA"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005448", "page": 23, "chunk": 0, "title": "Ethiopia - Rural Productive Safety Net Project", "pdf_url": "https://documents.worldbank.org/curated/en/099120423100031042/pdf/BOSIB05f9c7f7f0730a6bd0a0071798cc86.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "2019 PWIA", "label": "NAMED_DATA", "score": 0.7006025910377502, "start": 1242, "end": 1251, "probe_score": 0.996, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " crisis situations, by building\nresilience and contributing to human capita development; and (ii) mitigating the spillovers of FCV by addressing forced\ndisplacement situation in the country by supporting the most vulnerable and marginalized communities that are affected\nby conflict and climate-related shocks. The project is also aligned with the Strategy’s focus on high-priority issues,\nincluding: (i) investing in human capital; (ii) creating livelihood opportunities by creation of employment and economic\nopportunities; (iii) building community resilience and preparedness with regard to the impacts of climate change and\nenvironmental degradation. In addition, it is also in line with the World Bank’s Africa Strategy, as the project supports\ncritical priority areas, including: (i) investing in people with focus on human capital development; (ii) addressing FCV\nDrivers; and (iii) supporting climate change mitigation and adaptation. Lastly, a strong focus on gender is mainstreamed\nacross the project, and the project’s focus on facilitating women’s economic inclusion is in line with the World Bank\nGroup’s Gender Strategy.\n\n23. **The SNSOP closely reflects the objectives of IDA19 WHR and IDA Crisis Response Window (CRW), which will be**\n**leveraged to support the Government’s priorities and strategies for responding to natural and/or man-made crises.** In\nOctober 2021, as part of the WHR eligibility process, the Government finalized a strategy and action plan, entitled the\nCommunity Empowerment and Socioeconomic Development Strategy for Refugee Hosting Areas in South Sudan, for\ndurable solutions to the refugee situation in the country. The strategy highlights area-based, inclusive approaches that\nrespect the rights of displaced populations through programs that renovate or construct public infrastructure, improve\nfood security, address shortcomings in delivery of health, education, and vocational training, and strengthen social\nprotection, livelihood, and income generation opportunities. While the strategy has only recently been developed, the\nWorld", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000057", "page": 19, "chunk": 1, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|12 a 17|18 a 59|60 y >|\n|---|---|---|---|---|---|\n|<br> <br>MUJER|2|4|13|81|10|\n|<br>HOMBRE|4|6|6|93|7|\n\n\n\n**Gráfico 8**\n**Rango de Edad - Personas Refugiadas**\n**Período 2015 - Registradas por la PMH**\n\n\n200\n\n\n150\n\n\n100\n\n\n50\n\n\n\n\n\n\n\n|Col1|0 a 4|5 a 11|12 a<br>17|18 a<br>59|60 y >|\n|---|---|---|---|---|---|\n|Series1|6|10|19|174|17|\n\n\n**Fuente:** Informe final de gestión 2015, Proyecto: Asistencia y Atención a\npersonas del interés del ACNUR en Guatemala / Monitoreo y cabildeo\npara fortalecer la protección de refugiados/as, solicitantes de asilo y otras\npersonas desplazadas en Centroamérica.", "output": {"entities": {"named_data": ["Registradas por la PMH"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000275", "page": 24, "chunk": 1, "title": "Realidad de la Integración Local de la Población Refugiada en Guatemala: Diagnóstico Participativo 2015", "pdf_url": "https://reliefweb.int/attachments/1f3fb641-89af-3c49-b06c-0240386b157c/10907.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Registradas por la PMH", "label": "NAMED_DATA", "score": 0.6037344336509705, "start": 179, "end": 201, "probe_score": 0.463, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", and city change procedures for\nforeigners under IP, TP, and residence permit holders. It should also be noted that citizens of the Republic of Türkiye who are residing\nin the four provinces (Hatay, Malatya, Adıyaman and Kahramanmaraş) that are most affected by the earthquakes are not considered\nas “hosting communities” since the impacts of the earthquakes still affects populations and services in the affected provinces while\nsome families and individuals remain displaced. The residual humanitarian needs of the affected individuals should be covered by\npartners who are assisting the affected refugee population. In line with this approach, an estimation of the people in need in these\nfour provinces is based on the latest data and estimates from humanitarian partners active in responding to the earthquakes as well\nas government provided data. The target population figures for the host community are based on the number of Turkish nationals\nreached in previous years, and it is assumed that systems-strengthening efforts and multi-layered capacity development support to\npublic institutions will also benefit the host community (although this is difficult to quantify).", "output": {"entities": {"named_data": [], "descriptive_data": ["government provided data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000157", "page": 5, "chunk": 2, "title": "Türkiye 3RP - Regional Refugee and Resilience Plan in Response to the Syria Crisis 2025 Update", "pdf_url": "https://reliefweb.int/attachments/0c321f49-717c-573b-8b08-cf248c7cf5ed/EN%20-%203RP%202025%20-%20Appeal%20Overview.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "government provided data", "label": "DESCRIPTIVE_DATA", "score": 0.8405929803848267, "start": 828, "end": 852, "probe_score": 0.5169, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " across\nan individual’s working life. The earnings of an individual with a particular level of education and age (the\nage-earnings profile) are modelled based on the Mincerian earnings function presented in table 2.1.\nIndividuals are assumed to be able to earn from ages 15 to 65, and the proportion of individuals at each\nlevel of education is based on the educational attainment of individuals ages 25 to 19 in the 2020 Labor\nForce Survey (LFS).\n\n\n**<u>Table 2.1. Modelled Age-Earnings Profile</u>**\n\n|Variables|Mincerian Earnings Function Estimates|Mean (individuals ages 20 to 29)|\n|---|---|---|\n|Higher education|1.027|0.34|\n|Vocational education|0.454|0.3|\n|Secondary complete|0.275|0.13|\n|Secondary incomplete|0.03|0.22|\n|Experience|0.024|Varies by age|\n|Experience squared|−0.0005|Varies be age|\n|Female|−0.248|0.522|\n|Constant|7.46|1|\n\n\n\n_Note_ : Mincerian earnings coefficients are from MCC (2014) using data from 2006. The constant has been adjusted\nto convert into annual earnings in 2023 US$. Proportions of individuals in each educational category and female\nare based on the LFS 2020.\n\n5. Modelled effect sizes for (a) increasing teacher effectiveness for student learning (Subcomponent\n1.1) and (b) supporting innovative instructional practices (Subcomponent 1.3) range from 0.05 SD to 1.3\nSD based on effect sizes of similar programs worldwide. Professional development programs have been\nshown to have positive effects on student learning outcomes (Popova et al. 2018). Table 2.2 presents a\nsummary", "output": {"entities": {"named_data": ["2020 Labor\nForce Survey", "LFS 2020"], "descriptive_data": [], "vague_data": ["data from 2006"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000185", "page": 63, "chunk": 1, "title": "Moldova - Education Quality Improvement Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099051123142553305/pdf/BOSIB-624554c1-598f-4576-aa60-cca7d93b64e7.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "2020 Labor\nForce Survey", "label": "NAMED_DATA", "score": 0.8539642095565796, "start": 417, "end": 440, "probe_score": 0.9887, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from 2006", "label": "VAGUE_DATA", "score": 0.698535144329071, "start": 914, "end": 928, "probe_score": 0.6863, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "LFS 2020", "label": "NAMED_DATA", "score": 0.8003987073898315, "start": 1090, "end": 1098, "probe_score": 0.9825, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "6\n\n\nThere is strong support in the Government for increasing resources for education, and the Government\nmade a commitment to increase education's share of budget from 16% in 2001-02 to 25% in 2009-10.\n\n\nOne of the reasons for choosing an APL with a ten-year perspective is that the education budget\nshortages will continue to be a constraint in the next few years. Over this period, Government\n\nexpenditures in non-priority areas will be brought under control and Government expenditures on\neducation can be expected to increase significantly. Despite the manageability in the long-run, the\nshort-run prospects on the budget are more challenging and donors will need to finance some recurrent\ncosts. The proposed APL will be implemented in three phases with distinct triggers (see Section B. 4).\nAs a result, a 10-year projection of enrollments and education costs has been developed (which is the\noverall framework for the APL), and a detailed five year plan and project proposals have been\nprepared (which is the framework for the first phase of the APL).\n\n\n3. Sector issues **to be addressed by the project and strategic choices**\n\nThe project will directly address all the issues below except for higher education.\n\n\n_Issues/Sector Problems_ _Government strategy and project proposal_\n\n**School Places**\n\nThe immediate problem in Djibouti City and The Government's strategy includes a combination\nsurrounding suburbs and other towns is the lack of of building more schools and continuing with the\nschool places due to the strong demand for schooling. double-shifting policy. The project will finance new\nclassrooms, sanitation services, and school furniture.\n\n**Equity, Gender, Disparities**\n\nChildren from poorer families, rural children, and The Government will construct schools in underespecially girls do not always attend school. The served areas, particularly in poorer parts of Djiboutirecent Household Expenditure Survey states that Ville where almost 70% of the population lives.\nmajor reasons for the", "output": {"entities": {"named_data": [], "descriptive_data": ["Household Expenditure Survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000090", "page": 9, "chunk": 0, "title": "Albania - Emergency Road Repair Project", "pdf_url": "http://documents1.worldbank.org/curated/en/543691468740389779/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Household Expenditure Survey", "label": "DESCRIPTIVE_DATA", "score": 0.6417368054389954, "start": 1906, "end": 1934, "probe_score": 0.9529, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 6\nPage 6 of 6\n\n\n**Disbursement**\n\n\n**Allocation of credit proceeds (Table** C)\n\n\n**Table** C: **Allocation of Credit Proceeds**\n\n\n**Ex enditure Cate o** **Amount in SDRs** **Financin Percentage**\nCivil Works 3170000.00 100% of foreign expenditures; 90% of\nlocal expenditures\nGoods 1730000.00 100% of foreign expenditures; 90% of\nlocal expenditures\nConsultant Services and Training 2120000.00 100%\nIncremental Operating Costs:\n(a) audit fees 30000.00 100%\n(b) other expenditures 240000.00 90%\nRefund of the Project Preparation Fund 220000.00\nUnallocated 290000.00\n\n**Total Project Costs** 7800000.00\n\n**Total** 7800000.00\n\n\n_Operational costs include communication expenses, office supplies, furniture, audit fees, vehicle insurance and_\n_maintenance of vehicles and equipment._\n\n\nWorld Bank User\nP:\\Djibouti\\Hd\\44585\\NEG\\EnglishPAD\\Annex6.doc\n\n1 _1117/00_ 9:56 AM", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000049", "page": 48, "chunk": 0, "title": "Croatia - Reconstruction Project for Eastern Slavonia, Baranja and Western Srijem", "pdf_url": "http://documents1.worldbank.org/curated/en/347691468746725804/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nCameroon COVID-19 Preparedness and Response Project (P174108)\n\n\n**Global Fund** <u>MoPH</u> <u>EUR 257,640</u> <u>Cash</u> <u>Received</u> <u>Health, support to the National HIV/AIDS Control Program.</u>\nMoPH EUR 197,252 Cash Received Health, Support to the National Malaria Control Program.\n\n\nMoPH EUR 73,897 Cash Received <mark>Health, Support to the National TB program.</mark>\n\n\n\nCameroon\nNational\nAssociation for\nFamily Welfare\n<u>(CAMNAFAW)</u>\n\n\n\nEUR 590,376 Cash Received <mark>Health, Support to CAMNAFAW responsible of HIV prevention activities for key</mark>\n<mark>populations.</mark>\n\n\n\nMoPH EUR 1,630,670 Cash Received <mark>Procurement of PPE through UNDP.</mark>\n<mark>3 million surgical masks, 1.1 million gloves, 25,000 gowns, 30,000 shoe covers).</mark>\n\n\nMoPH EUR 191,471 Cash Received Support for the tailoring of DHIS-2 to support data collection for COVID-19 and\ncontact tracing activities.\n\n\n<u>MoPH</u> <u>EUR 580,000</u> <u>Cash</u> <u>Received</u> <u>Procurement of test and consumable required to perform COVID-19 testing.</u>\nMoPH EUR 8,124,867 Cash Pending Health: PPE, support to Laboratory (test, consumable, support to test/result\nsubmissi transportation, community response.\non\nfunding\n<u>request</u>\n\nMoPH EUR Cash Pledged Health: PPE, support to Laboratory (test", "output": {"entities": {"named_data": ["DHIS-2"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000169", "page": 48, "chunk": 0, "title": "Cameroon - COVID-19 Preparedness and Response Project", "pdf_url": "http://documents1.worldbank.org/curated/en/947711605111284278/pdf/Cameroon-COVID-19-Preparedness-and-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "DHIS-2", "label": "NAMED_DATA", "score": 0.6639779806137085, "start": 853, "end": 859, "probe_score": 0.0211, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", to account\nfor spending of savings from Ukraine, data\nfrom the National Bank of Ukraine on\ncash withdrawals and retail transactions\nfrom Ukrainian bank cards in Poland was\nused <sup>55</sup> and then calibrated to data for\nprivate consumption in Poland. Additionally,\nthe same data was used to calibrate the\nnegative shock to investment in Eastern\nEurope.\n\n\n\nFor productivity two options were tested.\nFirstly, neutral impact: no shock to\nproductivity. Secondly, lower productivity of\nworkers from Ukraine negatively impacting\ntotal labour productivity. These shocks were\ncalibrated to match the difference in data\nbetween refugees income from labour in\nUNHCR survey and average wage in Poland\nfrom Statistics Poland weighted by refugees\nshare in total workforce.\n\n\nAs one period in the model is set to one\nyear and refugees started coming to Poland\nby the end of February 2022 it was assumed\nthat their impact on economy started being\nfelt starting from II quarter of the year.\nAs such shocks were set so that ¾ of shocks\nwere calibrated to data from 2022 and ¼ to\ndata for 2023 <sup>56</sup> .\n\n\n\n51  Computational General Equilibrium.\n52  Global Trade Analysis Project, <u>[GTAP Models: Current GTAP Model (purdue.edu).](https://www.gtap.agecon.purdue.edu/models/current.asp)</u>\n53  Region combined from: Russia, Belarus, Ukraine, Moldova, Czechia, Slovakia, Hungary, Romania, and Bulgaria.\n54  All shocks are percent deviations.\n55 <u>[Oversight of financial market infrastructures (bank.gov.ua)](https://bank.gov.ua/en/payments/oversite)</u>\n56  E.g. for total increase in number of workers of 350 thousand around 262.5 thou. was set to have happened in 2022 while rest in 2023.", "output": {"entities": {"named_data": ["data\nfrom the National Bank of Ukraine", "UNHCR survey"], "descriptive_data": ["data for\nprivate consumption in Poland"], "vague_data": ["data from 2022"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 21, "chunk": 1, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data\nfrom the National Bank of Ukraine", "label": "NAMED_DATA", "score": 0.7609729766845703, "start": 51, "end": 89, "probe_score": 0.9987, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data for\nprivate consumption in Poland", "label": "DESCRIPTIVE_DATA", "score": 0.6093855500221252, "start": 216, "end": 254, "probe_score": 0.9774, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHCR survey", "label": "NAMED_DATA", "score": 0.8161389231681824, "start": 655, "end": 667, "probe_score": 0.9653, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from 2022", "label": "VAGUE_DATA", "score": 0.5461053848266602, "start": 1043, "end": 1057, "probe_score": 0.9704, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "DJIBOUTI\nSchool Access and Improvement Program\n\n\n**Project Appraisal Document**\n\n\nMiddle East and North Africa Region\n\nMNSHD\n\n\n\nDate: November 17, 2000 Team Leader: Qaiser M. Khan\n\n\n\nCountry Director: Inder K. Sud Sector Director: Baudouy\nProject **ID:** P044585 Sector(s): EP - Primary Education, ES - Secondary\n\n\n\n. Education\nLending Instrument: Adaptable Program Loan <sup>(APL)</sup> Theme(s): Education; Gender and development\n\n\n\nPoverty Targeted Intervention: N\n\n\n\nProgram Fin ncing Data\n\n\n\nEstimated\nAPL Indicative Financing Plan Implementation Period (Bank FY) Borrower\n\n\n\n**IBRD** Others **Total** **COMMITMENT** **Closing**\n**US$** m % US$ m US$ m Date Date\nAPL 1 10.00 75.8 3.20 13.20 03/31/2001 06/30/2005 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\n________________ Education\n\n\n\nAPL 2 10.0 65.8 5.20 15.20 07/01/2005 06/30/2008 Republic of\n\n\n\nLoan/ Credit Djibouti\n\n\n\nCredit Ministry of\n\n\n\ni_________ ________________ Education\n\n\n\nAPL 3 10.00 41.0 14.40 24.40 07/01/2008 06/30/2011 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\nEducation\n\n\n\nTotal 30.00 22.80 52.80\nProject Financing Data Credit\nFor Loans/Credits/Others: Amount (US$m): 10.0\n\n\n\nProposed Terms: Standard Credit\n\n\n\nGrace period (years): 10 Years to maturity: 40\nCommitment fee: 0.50% (0% for FY01) Service charge: 0.75", "output": {"entities": {"named_data": ["Project Financing Data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000049", "page": 4, "chunk": 0, "title": "Croatia - Reconstruction Project for Eastern Slavonia, Baranja and Western Srijem", "pdf_url": "http://documents1.worldbank.org/curated/en/347691468746725804/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Project Financing Data", "label": "NAMED_DATA", "score": 0.5102046728134155, "start": 1106, "end": 1128, "probe_score": 0.1169, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nprovided the bulk of assistance to refugees, IDPs, and to a lesser extent to host communities. The\nUS Government and ECHO are also providing substantial additional funding for humanitarian\ninterventions through NGOs.\n\n\n17. **To provide targeted support to poor and vulnerable Chadians, the Government has**\n**taken steps to develop a safety net system that is also suitable for the inclusion of refugees.**\nUnder the World Bank/Multi-Donor Trust Fund (MDTF)- funded PFS, the Government of Chad\nestablished the _Cellule Filets Sociaux_ (CFS) in 2016 to manage its safety net programs, particularly\ncash transfers and cash-for-work schemes. A Unified Social Registry (USR) is also being\ndeveloped, with the aim of combining information from selected social programs funded by the\nGovernment and external partners into a single database. The CFS is implementing the project\nusing a flexible approach to identification, targeting and registration of poor and vulnerable\nhouseholds. The objective is to have in place a highly adaptable system that can be scaled up to\nrespond to urgent situations, such a sudden inflow of refugees, that impacts host communities. <sup>18</sup> [^18: As part of the combined efforts to assist the Government in building a shock-responsive social protection system, many WFP,\nECHO and UNHCR partners (NGOs) are using the harmonized questionnaire during the lean season. The harmonized questionnaire\nwas introduced by Government Decree 038/PR/PM/MEPD/SE/SG/DGEP/2017 dated September 23, 2017 and it is the first step\ntoward building a Unified Social Registry (USR). Currently the Government, through the _Cellule Filets Sociaux_, is moving towards\nfinalizing the USR manual and procuring all necessary hardware (servers, mainframes) and software to establish the registry. It is\nenvisaged that a USR unit will eventually be created within the Government.]\n\n\n17 The 2017-2021 National Development Plan (NDP) is the Government of Chad’s first five-year strategy. It aims at supporting the\nGovernment’s longer-term development", "output": {"entities": {"named_data": ["Unified Social Registry"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000035", "page": 17, "chunk": 1, "title": "Chad - Refugees and Host Communities Support Project", "pdf_url": "http://documents.worldbank.org/curated/en/658761536982256019/pdf/PAD2809-PAD-PUBLIC-disclosed-9-12-2018-IDA-R2018-0286-1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Unified Social Registry", "label": "NAMED_DATA", "score": 0.719845175743103, "start": 642, "end": 665, "probe_score": 0.009, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Emergency Food and Nutrition Security Project (P163559)\n\n\n|Indicator Name|Core|Unit of<br>Measure|Baseline|End Target|Frequency|Data Source/Methodology|Responsibility for<br>Data Collection|\n|---|---|---|---|---|---|---|---|\n|<br>Description:|<br>Description:|<br>Description:|<br>Description:|<br>Description:|<br>Description:|<br>Description:|<br>Description:|\n\n\n\n\n\n\n\n\n\n\n|Col1|Name: Number of<br>pregnant and lactating<br>women consuming<br>blended supplementary<br>food in the intended<br>quantities|Col3|Number|0.00|80000.00|Monthly|Progress reports|MAFS/WFP|Col10|\n|---|---|---|---|---|---|---|---|---|---|\n||<br>Description:|<br>Description:|<br>Description:|<br>Description:|<br>Description:|<br>Description:|<br>Description:|<br>Description:|<br>Description:|\n\n\n|Col1|Name: Number of<br>individuals provided with<br>WASH services|Col3|Number|0.00|200000.00|Quarterly|Progress reports|MAFS/UNICEF|Col10|\n|---|---|---|---|---|---|---|-", "output": {"entities": {"named_data": ["South Sudan Emergency Food and Nutrition Security Project"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000038", "page": 36, "chunk": 0, "title": "South Sudan - Emergency Food and Nutrition Project", "pdf_url": "http://documents.worldbank.org/curated/en/713081494122547885/pdf/South-Sudan-PAD-04282017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "South Sudan Emergency Food and Nutrition Security Project", "label": "NAMED_DATA", "score": 0.6361859440803528, "start": 19, "end": 76, "probe_score": 0.0443, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda Climate Smart Agricultural Transformation Project (P173296)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Institutional<br>Structure|Role|Responsibilities|\n|---|---|---|\n|||• <br>Submit quarterly activity reports and accountability<br>reports to the NPCU.<br>• <br>Support NARO in the implementation of livestock<br>projects.|\n|Uganda National<br>Meteorological<br>Authority (UNMA)|• <br>Planning and<br>implementation of<br>project activities|• <br>Develop workplans and budgets for NPCU approval.<br>• <br>Develop procurement specifications and requirements.<br>• <br>Initiate activity and procurement requests.<br>• <br>Undertake activities, report and account.<br>• <br>Participate in procurement of required facilities and<br>materials<br>• <br>Build capacity of stakeholders in the interpretation and<br>use of weather information.<br>• <br>Collect, generate, interpret and disseminate<br>climate/weather data and information.<br>• <br>Submit quarterly activity reports and accountability<br>reports to the NPCU.|\n|National Technical<br>Advisory Committee<br>(NTAC)|• <br>Technical Advisory|• <br>Provide technical guidance to NPCU on project<br>implementation.<br>• <br>Review and approve selected CRG proposals for<br>financing.|\n|**REGIONAL/ZONAL LEVEL**|**REGIONAL/ZONAL LEVEL**|**REGIONAL/ZONAL LEVEL**|\n|Zonal<br>Technical<br>Committee", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["climate/weather data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002169", "page": 65, "chunk": 0, "title": "Uganda - Climate Smart Agricultural Transformation Project", "pdf_url": "https://documents.worldbank.org/curated/en/099050012052240654/pdf/BOSIB05e6fc47e0770aeec00ad5e11774f2.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "climate/weather data", "label": "VAGUE_DATA", "score": 0.540471613407135, "start": 898, "end": 918, "probe_score": 0.0095, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "-PSFU-345069-CS-CDS / C<br>onsulting services for evaluat<br>ion of performance of UWA B<br>oard of Trustees|IDA / 65380|Tourism Development Initiat<br>ives|Post|Direct Selection|Direct - National||0.00|Under Implement<br>ation|2023-03-03|2023-04-13|2023-03-13||||2023-05-17||2023-06-16||\n|UG-PSFU-364428-CS-CDS / C<br>onstruction supervision of th<br>e Proposed redevelopment of<br>Tourism and Wildlife facilities<br>at Uganda Wildlife Education<br>Centre, Plot 56/57 Lugard Av<br>enue, Entebbe|IDA / 65380|Tourism Development Initiat<br>ives|Post|Direct Selection|Direct - National||0.00|Under Implement<br>ation|2023-06-23|2023-06-22|2023-07-03||||2023-09-06||2024-04-03||\n|UG-PSFU-374017-CS-INDV /<br>Consultancy Services for a Pr<br>ocurement Specialist|IDA / 65380|Project Implementation|Post|Individual Consult<br>ant Selection|Open - National||0.00|Under Implement<br>ation|2023-08-04|2023-09-06|2023-09-22||2023-10-13||2023-11-17||2024-05-15||\n|UG-PSFU-374021-CS-INDV /<br>Recruitment of Clerk of Work<br>s|IDA / 65380", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002933", "page": 14, "chunk": 2, "title": "Uganda - EASTERN AND SOUTHERN AFRICA- P130471- Competitiveness and Enterprise Development Project (CEDP) - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099061224071016015/pdf/P130471-53975660-b137-4a85-8bf8-68d19b0de349.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Independent Evaluation Group (IEG)** Implementation Completion Report (ICR) Review\nKE-Youth Empowerment Project (FY10) (P111546)\n\n\n   - tracer studies; and\n\n   - feedback from employers.\n\n\nb. M&E Implementation\n\nM&E activities were successfully implemented (reflecting well on the implementation performance of KEPSA). The system appears to have\nbeen implemented largely as planned, apart from the activities that were dropped at restructuring. When some technical shortcomings of\nconsultants' work on the impact evaluation came to light, the World Bank provided intensive technical assistance to the study and even\ncomplemented the consultant's work with a staff-led analysis of the collected data (reflecting well on the World Bank's performance). The\nresulting study is published as a Policy Research Working Paper. The impact evaluation was designed to support causal inference and costbenefit analysis. The study offers insights for similar programs in other countries and in Kenya. Certain limitations arising from attrition are\nclearly noted. A gender assessment was also carried out and influenced operational decisions.\n\n\nc. M&E Utilization\n\nArguably one of the stronger and more unusual features of this project was the manner in which M&E findings were used to inform\ncontinuous fine tuning. Training content, targeting mechanisms, and communication and outreach were adjusted in light of data. The\ngovernment's decision to continue and scale up the youth employability activities in a follow-on project reflects in part the fact that the results\nwere well documented thanks to the design and execution of the M&E system. Design of the follow-up operation was informed by lessons\nlearned and documented by the M&E system.\n\nM&E quality is rated High due to the comprehensive design, successful execution, and effective use of M&E.\n\n\nM&E Quality Rating\nHigh\n\n\n**11. Other Issues**\n\n\na. Safeguards\n\nThis project was originally assessed as Safeguards Category B, triggering OP 4.01 (Environmental Assessment", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["collected data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:011524", "page": 8, "chunk": 0, "title": "Kenya - KE-Youth Empowerment Project (FY10)", "pdf_url": "https://documents.worldbank.org/curated/en/341501487967487230/pdf/ICRR-Disclosable-P111546-02-24-2017-1487967476844.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "collected data", "label": "VAGUE_DATA", "score": 0.7305995225906372, "start": 686, "end": 700, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Table **3:** Impact of **NPTP** on extreme poverty\n\n\nExree ovrt **rte7.19** **5.06** **2.13** **29.6%**\nExree ovrt gp1.40 **0.87** **0.53** **37.9%**\n\nExrmePvet svriy0.43 0.24 **0.19** 44.1%\nGini coefficient **39.25** **39.00** **0.26** **0.7%**\n_Source:_ Author's calculations using 2004 Household Budget Survey and ADePT\n\n\n**19.** Thus, with perfect coverage, **NPTP** can be expected to reduce the extreme poverty rate in\nLebanon from **7.19** percent to **_5.06_** percent or **by** **30** percent (Table **3** **).** It is important to note that\nextreme poverty gap and extreme poverty severity would decrease **by** even more in percent terms\n**(38** and 44 percent, respectively). Needless to say, these are significant gains in terms of poverty\nreduction.\n\n\n20. Here, we perform sensitivity analysis to relax our strong assumption of perfect coverage.\nFor each level of coverage, this would consist of drawing a certain share (say, **10** percent) of\nextremely poor households in the 2004 HBS, adding the average value of **NPTP** to their\nconsumption, calculating the extreme poverty rate with **NPTP,** and repeating this sufficient\nnumber of times **(100** times) to generate an average impact on extreme poverty", "output": {"entities": {"named_data": ["2004 Household Budget Survey", "ADePT", "2004 HBS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000109", "page": 89, "chunk": 0, "title": "Lebanon - Social Promotion and Protection Project", "pdf_url": "http://documents1.worldbank.org/curated/en/643811468055144236/pdf/749060PAD0P124010Box374388B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "2004 Household Budget Survey", "label": "NAMED_DATA", "score": 0.8294970393180847, "start": 284, "end": 312, "probe_score": 0.9861, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "ADePT", "label": "NAMED_DATA", "score": 0.829636812210083, "start": 317, "end": 322, "probe_score": 0.983, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "2004 HBS", "label": "NAMED_DATA", "score": 0.7396511435508728, "start": 992, "end": 1000, "probe_score": 0.9895, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nBeirut Housing Rehabilitation and Cultural and Creative Industries Recovery (P176577)\n\n\n\n\n\n\n\n|households|receive support through<br>knowledge-sharing<br>activities, and trainings to<br>streamline their processes<br>and promote capacity-<br>development related to<br>housing|Col3|itoring and<br>Evaluation<br>Reports.<br>Attendance<br>list|training events<br>conducted. A list of<br>participants will be<br>collected during the<br>activities and<br>integrated into the<br>housing rehabilitation<br>database.|Team/UN-Habitat|\n|---|---|---|---|---|---|\n|Of which, are female|Number of female-staff<br>members from DGA and<br>municipalities that will<br>receive support to<br>streamline their processes<br>and promote capacity-<br>development related to<br>housing|Annual<br>|Progress<br>Reports<br>Monitoring<br>and<br>Evaluation<br>Reports. List<br>of<br>participants<br>integrated<br>into the<br>Housing<br>Rehabilitatio<br>n Database<br>|The progress report will<br>monitor the number of<br>training events<br>conducted. A list of<br>participants will be<br>collected during the<br>activities and<br>disaggregated by<br>demographics.<br>|Project Management<br>Team/UN-Habitat<br>|\n|Person-days of temporary employment<br>created under the project|", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 44, "chunk": 0, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nAgriculture Cluster Development Project (P145037)\n\n\nThe Agriculture Cluster Development Project (ACDP) is financed by an International Development Association (IDA)\ncredit (IDA Cr. No. 5611-UG) of US$150 million that was approved by the Board on April 9, 2015. Following delay in\nobtaining Parliamentary ratification and meeting effectiveness conditionalities, the project became effective on\nJanuary 23, 2017, and is scheduled to close on March 31, 2022. The Project Development Objective (PDO) is to raise\non-farm productivity, production, and marketable volumes of selected agricultural commodities in specified clusters.\n\n\nFollowing a slow start to implementation due to delays in achieving effectiveness and deployment of the ElectronicVoucher Management Agency (e-VMA), a critical element for provision of agro-inputs subsidies through the Electronic\nVoucher Management System (e-VMS), the disbursement rate was at 25.09% during the implementation mission in\nNovember 2019. Project implementation since then, turned around. In terms of the expenditure performance, the\nproject has achieved a disbursement rate of 71.5 percent as at December 2020. This strong disbursement is attributed\nto the physical performances made in major project areas including the provision of agro-inputs through e-vouchers to\nbeneficiary farmers, operationalization and disbursement of matching grants, and start of rehabilitation works on road\nchokes. The project management also improved significantly, and other areas of improvement have included the\nmuch-strengthened Monitoring and Evaluation (M&E) capacity, the revitalization of agricultural statistics, and the\nintegration and use of digital technologies including the Geographic Information System (GIS).\n\n\nAs a result of these measures significant progress has been achieved in several areas. These have included a total of\n296,378 beneficiaries enrolled under the e-Voucher system with 157,276 of these (53 percent of enrolled) having\nreceived agro-inputs under the time bound and diminishing", "output": {"entities": {"named_data": [], "descriptive_data": ["agricultural statistics"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014796", "page": 2, "chunk": 0, "title": "Disclosable Restructuring Paper - Agriculture Cluster Development Project - P145037", "pdf_url": "https://documents.worldbank.org/curated/en/560661530279701977/pdf/Disclosable-Restructuring-Paper-Agriculture-Cluster-Development-Project-P145037.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "agricultural statistics", "label": "DESCRIPTIVE_DATA", "score": 0.7642040252685547, "start": 1639, "end": 1662, "probe_score": 0.3365, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Indicator Description**\n\n\n.\n\n**<u>Project Development Objective Indicators</u>**\n\n\n\n|Indicator Name|Description (indicator definition etc.)|Frequency|Data Source / Methodology|Responsibility for Data<br>Collection|\n|---|---|---|---|---|\n|Beneficiaries of Safety Nets<br>programs (number)|This indicator measures the number of<br>individual beneficiaries covered by safety<br>nets programs supported by the Bank.<br>Safety nets programs intend to provide<br>social assistance (kind or cash) to poor and<br>vulnerable individuals or families,<br>including those to help cope with<br>consequences of economic or other shock.|<br>Yearly|Cash Transfer Program<br>MIS|Project Implementation<br>Unit|\n|Beneficiaries of Safety Nets<br>programs - Female<br>(number)|This indicator measures female<br>participation in SSN programs. It has the<br>same definition as the \"Beneficiaries of<br>Safety Nets programs\" but applies only to<br>female. This indicator will yield a measure<br>of coverage of SSN projects disaggregated<br>by gender (in absolute numbers)|<br>Yearly|Cash Transfer Program<br>MIS|Project Implementation<br>Unit|\n|Beneficiaries of Safety Nets<br>programs - Unconditional<br>cash transfers (number)|Follows the safety nets programs’<br>classification used in SP Atlas.|Yearly|Cash Transfer Program<br>MIS|Project Implementation<br>Unit|\n|Proportion of households<br>enrolled in the registry<br>living below the extreme<br>poverty line|", "output": {"entities": {"named_data": ["SP Atlas"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000157", "page": 42, "chunk": 0, "title": "Burundi - Social Safety Nets Project", "pdf_url": "http://documents1.worldbank.org/curated/en/900951482030099834/pdf/1482030098559-000A10458-PAD-Burundi-SSN-11282016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "SP Atlas", "label": "NAMED_DATA", "score": 0.7940115332603455, "start": 1268, "end": 1276, "probe_score": 0.6743, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " in large metropolitan areas that offer\nthe most opportunities. Initially, in the first\nmonth after the outbreak of the full-scale\nwar in Ukraine, the number of renting\noffers in the OLX and Otodom portals\ndropped by approximately 60%, though it\nlater returned to previous levels.\n\n\n\n\n\nSince the beginning of the Russian invasion,\nthe number of Ukrainian workers covered by\nsocial security insurance in Poland increased\nby 126 thousand. The true increase\nof insured refugees however is larger.\nBy checking previous insurance status,\nZUS identified 228 thousand newly\nregistered insured persons active on 31st\nMarch 2023. <sup>31</sup> [^31: <u>[Cudzoziemcy w polskim systemie ubezpieczeń społecznych (zus.pl)](https://www.zus.pl/documents/10182/2322024/Cudzoziemcy+w+polskim+systemie+ubezpiecze%C5%84+spo%C5%82ecznych_2022.pdf/)</u> 32  According to NBP (2023), there were few respondents in this situation, and they most likely had secured other sources of income.] Considering the number\nof Ukrainians with active PESEL UKR at\nthe time, this would yield an employment\nrate of 43%. As this number does not take\ninto account jobs not covered by social\ninsurance and informal work, this can\nalign with the over 60% employment rate\nnoted in the surveys. This number does\nnot take into account over 500 thousand\nUkrainians that were paying social security\ncontributions before the beginning of the\nfull-scale war and remained in Poland after\nits outbreak.\n\n\nThe refugees present in Poland, while\nnot without difficulties, are largely able\nto provide for themselves and their\nfamilies. As reported in the Deloitte\n\n\n\nUkraine Refugee Pulse, which is based on\na survey carried out between October\nand December 2022, 40% of respondents\nhave enough income to meet basic needs\nor are able to support the same lifestyle\nthey had in Ukraine, while 60% say they do\nnot have enough income or have to rely on\nsavings and welfare. At the", "output": {"entities": {"named_data": ["Deloitte\n\n\n\nUkraine Refugee Pulse"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 14, "chunk": 1, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Deloitte\n\n\n\nUkraine Refugee Pulse", "label": "NAMED_DATA", "score": 0.9311078786849976, "start": 1601, "end": 1634, "probe_score": 0.3801, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nLebanon: Wheat supply emergency response project (P178866)\n\n\ninterventions: (1) establish social accountability groups or committees in selected localities by monitoring\navailability of affordable bread in the WFP-eligible shops which provide support to vulnerable communities; (2)\nconducting a baseline survey and periodic monitoring using random sampling based on UNHCR and WFP\nbeneficiary lists; and (3) strengthening the MOET’s GM system. At the same time, the findings of the baseline\nsurvey and subsequent tracer surveys will be used to generate periodic action plans to address the feedback\nreceived from beneficiaries through the surveys’ implementation.\n\n**B. Fiduciary**\n\n\n**(i)  Financial Management**\n\n\n65. The project will be implemented by MOET in line with World Bank policies that are standard for project\nimplementation, including the “Procurement Regulations” dated November 2020.\n\n\n66. The Financial Management (FM) assessment conducted for MOET found that the FM risk, as a component\nof the fiduciary risk, is rated as Substantial. With the proposed mitigating measures, MOET will meet the World\nBank’s FM requirements and will have an acceptable FM system. The residual FM risk rating would be Moderate\nafter mitigating measures. The details of the FM assessment and arrangements are included in Annex 1.\n\n\n67. A single segregated Project Designated Account in US Dollars will be opened at the BdL under MOET in\nthe name of the project. Funds will be channeled from the World Bank to the Ministry of Finance’s treasury\naccount and then transferred to the project designated account opened at the BdL. Disbursements will follow the\nguidelines and the modalities specified in the Loan Agreement and Disbursement and Financial Information Letter.\n\n\n68. The general accounting principles for the project will be as follows: (a) project accounting will cover all\nsources and uses of project funds, including payments made and expenses incurred. Project accounting will be\nbased on cash", "output": {"entities": {"named_data": [], "descriptive_data": ["UNHCR and WFP\nbeneficiary lists"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000019", "page": 29, "chunk": 0, "title": "Lebanon - Wheat Supply Emergency Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/408131653327258940/pdf/Lebanon-Wheat-Supply-Emergency-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "UNHCR and WFP\nbeneficiary lists", "label": "DESCRIPTIVE_DATA", "score": 0.6097001433372498, "start": 385, "end": 416, "probe_score": 0.9136, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["M&E data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008156", "page": 29, "chunk": 2, "title": "Ethiopia - Seed Systems Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/116821468744299057/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "M&E data", "label": "VAGUE_DATA", "score": 0.5883201956748962, "start": 530, "end": 538, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Pacific\nbore the brunt of one in two (59 per cent) internal\nchild displacements by dangerous storms over that\ntime period. <sup>10</sup> By 2090, almost half of the 2.8 billion\npeople that could be affected by heatwaves are\nprojected to live in Southern Asia. <sup>11</sup> Nearly 90 per\ncent of countries defined as \"extremely high risk\"\nby the Children’s Climate Risk Index are considered\nfragile contexts.\n\n##### #6. When children move because of\n\nclimate-related threats, how far\nwill they go?\n\nMost children on the move in a\nchanging climate will not cross\nborders.\n\n\nMost projections suggest that when they do leave\nhome to adapt to the threats of climate change,\nchildren will move within their own countries. This is\nsupported by multiple studies and meta-analyses, as\nwell as the United Nations Intergovernmental Panel\non Climate Change. <sup>12, 13, 14, 15, 16, 17</sup>\n\n\n##### #1.\n\n\n\nWhile we know climate change\ncan be directly and indirectly\nlinked to patterns of human\nmobility and displacement, do\nwe have the data to estimate to\nwhat extent child mobility has\nbeen or will be affected?\n\nClimate change is difficult to\nisolate as a driver of human\nmobility; this, coupled with a\nlack of child-specific data and\nresearch on the links between\nmigration, displacement and\nclimate change, means the\nnumber of children who are and\nwill be on the move as climate\nchange intensifies remains\nunclear.\n\n\n\npredicted regionally, particularly in sub-Saharan\nAfrica. <sup>3</sup>\n\n- The number of asylum applications to the\nEuropean Union has been forecast to increase as\nglobal temperatures rise; estimates range from\nan additional 98,000 applications to 660,000\napplications per year by 2100, varying by climate\nchange scenario. <sup>4</sup>", "output": {"entities": {"named_data": ["Children’s Climate Risk Index"], "descriptive_data": [], "vague_data": ["child-specific data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000606", "page": 2, "chunk": 1, "title": "Climate mobility and childhood: Examining the risks, closing the data and evidence gaps for children on the move (September 12, 2024)", "pdf_url": "https://reliefweb.int/attachments/590b8abf-89dd-499b-ace4-9e6d5545f09d/Executive-summary-Climatemobility-and-childhood.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Children’s Climate Risk Index", "label": "NAMED_DATA", "score": 0.6493906378746033, "start": 347, "end": 376, "probe_score": 0.9616, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "child-specific data", "label": "VAGUE_DATA", "score": 0.6233546137809753, "start": 1204, "end": 1223, "probe_score": 0.1216, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|**Component 3: Road Safety**|\n|Development<br>and<br>operationalization of the Road<br>Accident Database Management<br>System<br>Training<br>and<br>awareness<br>campaigns in the Project area|• <br>Road<br>safety<br>awareness<br>campaigns in the Project area,<br>and road safety data collection<br>and management as part of<br>contingency planning including<br>accident data attributed to<br>climate<br>change<br>such<br>as<br>increased runoff and higher<br>temperatures which increase<br>the pavement deterioration<br>hence the ride quality of the<br>road<br>and<br>necessitating<br>frequent<br>maintenance<br>routines.<br>• <br>Use<br>the<br>Road<br>Accident<br>Database Management System<br>to inform decision making<br>towards targeted interventions<br>that make the road safer to<br>users and more resilient to<br>climate change||\n\n\n\nPage 78 of 80", "output": {"entities": {"named_data": [], "descriptive_data": ["road safety data"], "vague_data": ["accident data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 82, "chunk": 1, "title": "Uganda - Roads and Bridges in the Refugee Hosting Districts/Koboko-Yumbe-Moyo Road Corridor Project", "pdf_url": "http://documents.worldbank.org/curated/en/834931600048847296/pdf/Uganda-Roads-and-Bridges-in-the-Refugee-Hosting-Districts-Koboko-Yumbe-Moyo-Road-Corridor-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "road safety data", "label": "DESCRIPTIVE_DATA", "score": 0.5024296045303345, "start": 267, "end": 283, "probe_score": 0.0119, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "accident data", "label": "VAGUE_DATA", "score": 0.6551704406738281, "start": 361, "end": 374, "probe_score": 0.0483, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " (305 in Koboko District, 423 in Moyo District and\n1,780 in Yumbe District). There are 741 structures located in the proposed RoW; they include permanent/semipermanent buildings and others such as gates, soak pits, pit latrines, fences and perimeter walls etc. It is also\nestimated that about 266 households will be physically displaced as a result of the Project while another 2002\nPAPs across the three districts will be economically displaced. Taking into account that project preparation\ntimelines are relatively short, there will be particular attention to ensure adequate quality of the RAP especially\nin terms of (i) designing Livelihood Restoration Plans, (ii) appropriate measures to support PAPs from vulnerable\ngroups and those with disabilities, and (iii) carrying out a comprehensive census. PAPs will continue to be engaged\nthroughout the RAP processes and particularly during its implementation to address any issues that might have\nbeen missed out in earlier studies. Additional measures may include thorough screening at project preparation,\nthe project proponent’s commitment to monitoring, implementing agreed measures and institutional\nstrengthening measures. All affected properties will be subjected to a transparent valuation process and will be\npromptly and adequately compensated. A Livelihood Restoration Plan has been developed as part of the RAP\n\n\nPage 43 of 80", "output": {"entities": {"named_data": [], "descriptive_data": ["comprehensive census"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 47, "chunk": 2, "title": "Uganda - Roads and Bridges in the Refugee Hosting Districts/Koboko-Yumbe-Moyo Road Corridor Project", "pdf_url": "http://documents.worldbank.org/curated/en/834931600048847296/pdf/Uganda-Roads-and-Bridges-in-the-Refugee-Hosting-Districts-Koboko-Yumbe-Moyo-Road-Corridor-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "comprehensive census", "label": "DESCRIPTIVE_DATA", "score": 0.741782546043396, "start": 783, "end": 803, "probe_score": 0.0948, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "estimated based on the following parameters: 70 percent loss when flood depth reaches 3.4 to 4.6\nm; 50 percent loss for depth between 3.0 and 3.4 m; 25 percent loss in cases of 2.7 to 3.0 m\ndepth; and 5 percent loss when floods reach 2.2 to 2.7 m depth.\n\n\n14. Field observations showed that each household owns livestock, averaging one cow, one\ngoat or sheep, and four poultry. The value of livestock flood losses was estimated based on the\nnumber of households displaced by the floods in 2011 (about 805 households), the value of the\nlivestock per household, and expected depth of the floods.\n\n\n15. For the assessment of flood damages on schools, eight primary and two secondary\nfacilities were visited with a Civil Works Public Officer who assisted in valuing flood damages\nfrom recent flood events. Most toilets needed to be rebuilt and buildings showed cracks and\nholes in most classes. The estimation of flood losses was done with the specialists and only\nconsidered physical damages, such as the building of new toilets and rehabilitation of both class\nand office blocks, and considering the different flood depth scenarios as mentioned above. Other\nsocial losses, including disruption in education, were not quantified in the analysis but are critical\nnonetheless. For example, the 2011 floods happened when students were about to submit their\nfinal exams, and students had to be evacuated to other schools that were not affected. Lower\nprimary students had to postpone their exams for one month.\n\n\n16. In assessing damages on houses, about 10 percent of the houses in the area have iron\nsheet and brick walls and 90 percent have thatched or iron sheet roofing but mud walls. The\nvalue of house structures was estimated with the Public Works Officer, and the corresponding\nflood maps were used for determination of the structures affected at different flood depths. In the\ncase of roads and culverts, avoided losses from floods were estimated with a Ministry of Public\nWorks officer from", "output": {"entities": {"named_data": [], "descriptive_data": ["flood maps"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008539", "page": 64, "chunk": 0, "title": "Kenya - Water Security and Climate Resilience Project : additional financing", "pdf_url": "https://documents.worldbank.org/curated/en/140371468178181251/pdf/PAD1387-PJPR-P117635-P151660-IDA-R2015-0167-1-Box391454B-OUO-9.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "flood maps", "label": "DESCRIPTIVE_DATA", "score": 0.86959308385849, "start": 1780, "end": 1790, "probe_score": 0.0478, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "## ISOLATED AND INSECURE\n\n##### Isolation and insecurity have become part of everyday life for many Syrian refugee children. Some prefer to be alone; others are kept at home by their parents, who fear for their safety in unfamiliar surroundings.\n\nTensions within and between refugee and host\n\ncommunities often intensify these fears. The\n\nhome environment is not always free of tensions\n\neither, given the stressful conditions under\n\nwhich many Syrian refugees live. This can also\n\njeopardize the safety and well-being of children.\n\n##### Tensions and Safety\n\n\nThe influx of Syrian refugees has had a\n\nmajor impact within Lebanon and Jordan,\n\ndestabilizing local economies and putting\n\npressure on housing and infrastructure.\n\n\nA poll conducted in Lebanon in May 2013\n\nwith 900 Lebanese adults found that 54 per\n\ncent agreed with the statement that “Lebanon\n\nshould not receive more Syrian refugees.” <sup>4</sup>\n\nA similar survey conducted in July 2013 with\n\n\n4. National opinion poll conducted 15-21 May 2013 undertaken by Fafo\nIndependent Research Foundation in cooperation with Information\nInternational, available at http://bit.ly/1dclayy accessed 27 October 2013.\n\n\nI’tmad, 17, lives in a collective shelter in Lebanon that houses\nmore than 700 Syrian refugees. Most days she stays inside in\nthe single room that her family shares. UNHCR / E. Dorfman\n\n\n\nThe Future of Syria: Refugee Children in Crisis\n\n\n1,800 Jordanians found that 73 per cent were\n\nopposed to receiving more Syrian refugees. <sup>5</sup> [^5: July 2013 survey of 1,800 Jordanian nationals, ‘Current Issues in Jordan,’ by\nthe Centre for Strategic Studies at the University of Jordan. The survey was\nled by Dr. Walid Alkhatib.]\n\n\nFather Nour Al-Sahawneh, of the Christian\n\nand Missionary Alliance Church in Mafraq,\n\nJordan, said that based on his interactions with\n\nthe local community, “Jordanians are starting\n\nto see this as a crisis for them as well.”\n\n\nSecurity issues and community tensions are\n\nparticularly acute in", "output": {"entities": {"named_data": ["Current Issues in Jordan"], "descriptive_data": ["poll conducted in Lebanon in May 2013", "National opinion poll conducted 15-21 May 2013", "survey of 1,800 Jordanian nationals"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001052", "page": 25, "chunk": 0, "title": "The Future of Syria – Refugee Children in Crisis [EN/AR]", "pdf_url": "https://reliefweb.int/attachments/a03a03d0-b6cf-3c9d-8855-7963e4fff514/Future-of-Syria-UNHCR-v13.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "poll conducted in Lebanon in May 2013", "label": "DESCRIPTIVE_DATA", "score": 0.7366824746131897, "start": 730, "end": 767, "probe_score": 0.9826, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "National opinion poll conducted 15-21 May 2013", "label": "DESCRIPTIVE_DATA", "score": 0.7282133102416992, "start": 965, "end": 1011, "probe_score": 0.9859, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey of 1,800 Jordanian nationals", "label": "DESCRIPTIVE_DATA", "score": 0.8726353645324707, "start": 1528, "end": 1563, "probe_score": 0.9988, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Current Issues in Jordan", "label": "NAMED_DATA", "score": 0.7027047276496887, "start": 1566, "end": 1590, "probe_score": 0.9439, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 6\nPage 3 of 6\n\n\nLarge consultant contracts for amounts above US$200,000 will be advertised through the UN's\n_Development Business,_ for which expressions of interest will be requested. Following the short-listing\nprocess, Quality and Cost-Based Selection (QCBS) will be the preferred method of selection.\n\n\nImpact assessments and small-size sampling surveys will be carried out using Selection Based on\nConsultant's Qualifications (CQ) for contracts estimated to cost less than US$25,000, and Single-Source\n\nSelection (SS) for services not exceeding US$15,000.\n\n\n**Table A: Project Costs by Procurement Arrangements**\n\n(US$ million equivalent)\n\n\n**Expenditure Category** **Procurement** **Methodl**\n**ICB** **NCB** **Other** <sup>**2**</sup> **N.B.F.** **Total Cost**\n\n**1. Works** **0.00** 5.30 0.60 0.00 5.90\n(0.00) (4.90) (0.50) (0.00) (5.40)\n**2. Goods** 0.80 0.41 0.05 0.00 1.26\n(0.76) (0.30) (0.04) (0.00) **(1.10)**\n**3. Services** **0.00** **0.00** 3.41 0.05 3.46\n!:_________________ _ X **:(0.00)** **(0.00)** (3.30) (0.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000100", "page": 45, "chunk": 0, "title": "Bosnia and Herzegovina - Second Electric Power Reconstruction Project", "pdf_url": "http://documents1.worldbank.org/curated/en/583901468768013967/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nLebanon: Wheat supply emergency response project (P178866)\n\n\n**F. Lessons Learned and Reflected in the Project Design**\n\n\n48. **The project primarily builds on the lessons learned from the GFRP, which embodied the World Bank’s response**\n**to the 2008 global food crisis** . GFRP mixed fast-track funding from the International Bank for Reconstruction and\nDevelopment and International Development Association with trust fund grants to help governments address the\nimmediate food crisis, while encouraging agricultural policies that will increase resilience in the future. Key lessons also\nreflected in the project design are summarized below:\n\n\n**-** **Simple design of emergency operations is crucial for rapid response** .  A simple design of emergency\noperations is a key for success. The design of the project should focus on responding to the government’s\nshort-term priority and to the urgent needs of the beneficiaries, as a key factor in the project’s successful\nimplementation.\n\n**-** **Establishing an effective monitoring and evaluation (M&E) system in the context of a crisis response**\n**operation is a challenge, but its importance should not be underestimated** .\n\n**-** **Emergency responses can help in crafting longer-term responses to vulnerability** . For example, in\nNicaragua, the food crisis response project was used as an opportunity to move forward the long-standing\nagenda for developing emergency responses to food price crisis in a country that constantly faces them\nand needs a comprehensive long-term response. In the Philippines, the emergency response catalyzed a\nnascent reform agenda in social protection, including a standardized database of poor households and\nconditional cash transfers. Emergency operations by nature finance short-term measures which often do\nnot have the potential to sustain development impact. Therefore, a follow-up operation should be\nconsidered that can build on the experiences of the emergency operation", "output": {"entities": {"named_data": [], "descriptive_data": ["standardized database of poor households"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000019", "page": 25, "chunk": 0, "title": "Lebanon - Wheat Supply Emergency Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/408131653327258940/pdf/Lebanon-Wheat-Supply-Emergency-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "standardized database of poor households", "label": "DESCRIPTIVE_DATA", "score": 0.8872570395469666, "start": 1673, "end": 1713, "probe_score": 0.0563, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " set of indicators will be used to track progress\ntowards achievement of the project’s PDO. The M&E system will ensure that information flows\nadequately among participating agencies, ministries, and other relevant institutions and to\ndocument project implementation progress and impact of project activities in a timely and\neffective manner. This is essential in helping management make the right decisions, ensure close\nmonitoring of activities and real-time evaluation of progress achieved, and to promote the\nrelevance of the planned reinsertion activities in a changing environment. Baseline data will be\ncollected by a designated M&E agency as part of project preparation.\n\n49. The M&E unit will produce monthly, quarterly, and annual project reports through the\nreinsertion MIS. This system will consist of one robust database that will monitor the\nbeneficiaries in the reinsertion and follow-up phase of the project, as well as track the\nimplementing partners providing various support. These reports can be accessed electronically\nby various government partners and donors. In addition, ad hoc assessments will be conducted as\nwell as studies based on identified needs. This will include formal assessments of the project\nbeneficiaries in the reinsertion process as well as regular tracer beneficiary surveys that will\ncombine qualitative and quantitative data. A mid-term review and final implementation report\nwill be conducted in collaboration with donors and government. During the Mid-Term Review,\nprogress towards reaching the project objectives will be evaluated and remedial action will be\ntaken as needed. Beyond traditional M&E requirements, the project will also deliver quarterly\ninternal and annual external audits to track fiduciary management, expectations and next steps.\n\n19 See Annex 6: Donor Roundtable Conclusions.\n\n\n13", "output": {"entities": {"named_data": ["reinsertion MIS"], "descriptive_data": ["tracer beneficiary surveys"], "vague_data": ["Baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000148", "page": 23, "chunk": 1, "title": "Mali - Reinsertion of Ex-combatants Project", "pdf_url": "http://documents1.worldbank.org/curated/en/848361679677867655/pdf/Mali-Reinsertion-of-Ex-combatants-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Baseline data", "label": "VAGUE_DATA", "score": 0.5055881142616272, "start": 587, "end": 600, "probe_score": 0.0008, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "reinsertion MIS", "label": "NAMED_DATA", "score": 0.6825939416885376, "start": 768, "end": 783, "probe_score": 0.0111, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "tracer beneficiary surveys", "label": "DESCRIPTIVE_DATA", "score": 0.883039653301239, "start": 1290, "end": 1316, "probe_score": 0.0042, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2024-01-12/los-batwa-de-uganda-marginados-en-nombre-de-la-conservacion.html](https://elpais.com/planeta-futuro/2024-01-12/los-batwa-de-uganda-marginados-en-nombre-de-la-conservacion.html)</u>\n26 Ibid.\n27 Interview with Gad Shemajere, a mutwa Leader at the National Level held on Wednesday 5th October, 2022 in Bundibugyo.\n28  Fauna &Flora International (October 2013), Batwa cultural values in Bwindi Impenetrable and Mgahinga Gorilla National\nParks, Uganda. A report of a cultural assessment. University of Science and Technology (2020).\n29 Mbarara University of Science and Technology (2020), The marginalization of the Batwa people of Southwestern Uganda,\nas an indigenous community; Bwindi Mgahinga Conservation Trust (2016) Batwa Population Census Report.\n\n\n17", "output": {"entities": {"named_data": ["Batwa Population Census Report"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000071", "page": 16, "chunk": 2, "title": "Vulnerable and Marginalized Group Plan Uganda Investing in Forests and Protected Areas for Climate-Smart Development Project (P170466)", "pdf_url": "https://documents.worldbank.org/curated/en/099010526114520853/pdf/P170466-b89bfbf8-f773-4e04-8924-7e4de7658972.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Batwa Population Census Report", "label": "NAMED_DATA", "score": 0.8671600222587585, "start": 729, "end": 759, "probe_score": 0.6616, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020791", "page": 62, "chunk": 2, "title": "Ethiopia - Wolamo Agricultural Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/963601468256732438/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Emergency Food and Nutrition Security Project (P163559)\n\n\ndifficult for Bank staff and other independent agencies to access the project sites and confirm that project\nresources have been utilized efficiently and economically towards the development objective.\n\n\n23. Other risks relate to the rapidly deteriorating macroeconomic situation in South Sudan coupled with\nthe significant depreciation of the local currency relative to the US$, which could further present a risk of\nmisapplication of project resources. These risks are effectively mitigated by the involvement of UN\nagencies in the implementation of the project. The UN agencies have adequate technical and fiduciary\ncapacity to implement similar types of emergency operations. The three UN agencies will each sign\ncontracts with MAFS as a basis for their engagement. During the course of implementation, the agencies\nwill submit quarterly utilization (progress and financial) reports, which will be validated by the PIU in line\nwith the existing contracts, before sharing with the Bank. Further, the UN has got adequate machinery to\naccess insecure locations and project sites.\n\n\n24. Funds disbursed into the DA for the implementation of component 3 will be ring‐fenced from\nministry‐wide fiduciary risks by ensuring segregated project accounts (DA), cashbooks and financial\nstatements, operated, maintained and prepared by the MAFS ‐ based PIU. The PIU will maintain an up‐to‐\ndate contract register as well as an assets register. Similarly, the FM team will prepare monthly bank\nreconciliation statements to ascertain the accuracy of the cash balances in the DA. Fiduciary oversight will\nbe effected by the IAD, the NAC, and other private audit firms working with the two Government\ninstitutions. The in‐year internal audit reviews will be conducted at least once a year and the audit reports\nwill be shared with MAFS, MoFP and the Bank for review and comments.\n\n\n**Funds flow and Disbursement arrangements**\n\n\n25. Disbursement of the Grant will use advances, reimbursement", "output": {"entities": {"named_data": [], "descriptive_data": ["contract register", "assets register"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000038", "page": 51, "chunk": 0, "title": "South Sudan - Emergency Food and Nutrition Project", "pdf_url": "http://documents.worldbank.org/curated/en/713081494122547885/pdf/South-Sudan-PAD-04282017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "contract register", "label": "DESCRIPTIVE_DATA", "score": 0.6167263388633728, "start": 1475, "end": 1492, "probe_score": 0.0035, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "assets register", "label": "DESCRIPTIVE_DATA", "score": 0.5843027830123901, "start": 1507, "end": 1522, "probe_score": 0.0095, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " inclusive education and safe schools, and climate change. The key teaching-learning\npractices will be derived from research findings on effective pedagogy and will include the use of scripted lesson plans.\nIt will provide teachers with classroom management techniques, including how to rotate students using the covered\nspaces to be provided under sub-component 2.2 and how to leverage student peer instruction. It will also build capacities\nto implement school- and local-level practices that promote effective pedagogy, including how to conduct lesson\nobservations using a standardized format and provide peer feedback and mentoring to promote CPD at the school level.\nIt is expected that these training themes will subsequently be built into the pedagogical days organized by the department\ncenters responsible for the in-service training of primary teachers (CDFCEP). Further, subsequent to the pedagogical\ndays, school directors and teachers will be expected to continue the CPD process by, among others, performing regular\nclassroom observations and providing feedback and mentoring. These will be periodically monitored by local pedagogical\nsupport staff, and findings will be used to provide focus and material for local pedagogical days. The training will be\ndelivered in two phases, to enable a period of practice and reflection that should leverage the effectiveness of the second\nphase.\n\n\n13. All schools will also be provided with digital devices and solar charging equipment, such that there is one device\nper two teachers. The device will be pre-loaded with content including the training modules; scripted lesson plans based\non the curriculum, aligned with the textbooks and incorporating the key effective teaching-learning practices covered by\nthe training; videos of effective teaching-learning techniques in practice; supplementary teaching-learning materials to\ncomplement those provided in the textbook; and procedures and tools for mentoring and feedback, including a classroom\nobservation format and other relevant professional development activities. The training will include how to use the\ndigital device and materials.\n\n\n**_Sub-component 1.3: Teaching and Learning Materials_**\n\n\n39 For instance, the TEACH classroom", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000009", "page": 18, "chunk": 1, "title": "Concept Project Information Document (PID) - CHAD Improving Learning Outcomes Project - P175803", "pdf_url": "http://documents.worldbank.org/curated/en/234501637169242309/pdf/Concept-Project-Information-Document-PID-CHAD-Improving-Learning-Outcomes-Project-P175803.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "cleanliness, lighting and ventilation, prices, POS system, quality,\nwillingness to partnership, line of credit);\n\n        - Post-qualification;\n\n        - Agreement with merchants was signed with the NGO (WFP guarantor);\n\nthen this was modified to having WFP signing the agreement.\n\niv. Commercial bank BDL & Merchants (regulation of relationship):\n\n        - The bank signs contracts with merchants to cover commercial relationship\n\n(General conditions) and WPA project parameters (Special conditions);\n\n        - Merchants should be cleared by the central bank (Banque Du Liban);\n\n        - The BLF provides regular updates to WFP and advises on fraudulent\n\nsuspicions, leaving to WFP the authority to act.\n\nv. Field visit outcomes:\n\n        - Field visitors are in charge of (i) Distribution e-card, (ii) household\n\nsurveys (monthly level of effort of 40 person days with an average\ncoverage of 16 households per day), (iii) shop monitoring (once per month\nminimum).\n\n        - Invoices are itemized and attached to the card receipt.\n\n31. Record keeping; Inventory: Both agencies have a satisfactory system.\n\n\na. The PCM/FOT has an extensive experience in record keeping and the accounting\n\nsystem contain an inventory field.\n\nb. WFP conducts physical count once yearly. In 2008, the software IPSAS/ Wings was\n\nimplemented for inventory purposes. For food procured items, a separate system (that\nis in the process to be integrated in Wings) records the commodity transaction. In the\ncurrent project WFP is implementing, the commercial selected bank tracks the e-cards\nin order to monitor the transferred moneys. Monthly financial reports are produced.\n\n32. Current Staffing:\n\n\na. At the PCM, two committees process procurement: Supply Committee (head of\n\ncommittee, one engineer, one administrative, one IT) and Acceptance committee (head\nof committee and 5 members). Housed at PCM, FOT had customized the procurement\nresources and financial management as per the needs of the ESP", "output": {"entities": {"named_data": [], "descriptive_data": ["household\n\nsurveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000139", "page": 51, "chunk": 0, "title": "Lebanon - Emergency National Poverty Targeting Program Project", "pdf_url": "http://documents1.worldbank.org/curated/en/810511467987899324/pdf/PAD1030-ENGLISH-P149242-PUBLIC-FINAL-LEB-ENPTP-English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "household\n\nsurveys", "label": "DESCRIPTIVE_DATA", "score": 0.8949342370033264, "start": 808, "end": 826, "probe_score": 0.0001, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " problem paying teacher and other public servant salaries. However, from an\neconomic point of view, the project is a high priority for the development needs of Djibouti development cannot be sustained in a country with a 39% gross enrollment rate in primary education.\nDjibouti's only resource is its people and the quality of human capital needs to be improved. An\nincreasing source of earnings for Djibouti is remittances sent by Djiboutians working abroad, and in\norder to continue to benefit from this, Djibouti needs to improve the skill base of its population.\n\n\nInequities are high both by income group and by gender. The project will try to address equity\nproblems by financing schools in poorer areas of Djibouti-Ville and in rural areas as well as running\nsensibilization programs. There is still a risk that the poorest will stay out school. The Government has\ndeveloped a ten-year strategy to reach full primary enrollment. There is significant donor interest in\nfinancing the investment costs and some donors are also interested in fmancing recurrent costs to give\nthe Govemment time to reorient its own expenditures to priority areas such as education.\n\n\nThe overall public finance issues are currently being addressed through an IMF facility and IDA plans\nto undertake a structural adjustment program. A key element of the policy matrix under discussion for\nan IDA structural adjustment is a sufficient increase in allocation to the social sectors, particularly the\neducation sector. The strong level of support for education at the highest levels of Government is\nlikely to assure that adequate budget resources are found for the education sector.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014416", "page": 25, "chunk": 1, "title": "Kenya - Smallholder Coffee Improvement Project", "pdf_url": "https://documents.worldbank.org/curated/en/534211468914087372/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "ncies; (iii) random validation interviews by external evaluator; “Trainees” refers to<br>staff from MoLF, NVI, NAIC, NAHDIC, VDFACA, EAS, AH system and VS supported under<br>component B. This PDO indicator refers to Component B.<br>As per the M&E plan this indicator is measured in midterm and endline survey|\n|**Respond promptly and effectively to an eligible crisis or emergency**|**Respond promptly and effectively to an eligible crisis or emergency**|**Respond promptly and effectively to an eligible crisis or emergency**|**Respond promptly and effectively to an eligible crisis or emergency**|**Respond promptly and effectively to an eligible crisis or emergency**|**Respond promptly and effectively to an eligible crisis or emergency**|**Respond promptly and effectively to an eligible crisis or emergency**|**Respond promptly and effectively to an eligible crisis or emergency**|**Respond promptly and effectively to an eligible crisis or emergency**|\n|Indicator Name|Baseline|Baseline|Actual (Previous)|Actual (Previous)|Actual (Current)|Actual (Current)|Closing Period|Closing Period|\n|Indicator Name|Value|Month/Year|Value|Date|Value|Date|Value|Month/Year|\n|5. Time lapse between early<br>warning information and<br>disbursement toward<br>response (Weeks)|2.50|May/2018|3.00|07-Feb-2022|3.00|30-Jun-2024|2.00|Jul/2024|\n|5. Time lapse between early<br>warning information and<br>disbursement toward<br>response (Weeks", "output": {"entities": {"named_data": [], "descriptive_data": ["midterm and endline survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:004264", "page": 4, "chunk": 3, "title": "Disclosable Version of the ISR - Livestock and Fisheries Sector Development Project - P159382 - Sequence No : 15", "pdf_url": "https://documents.worldbank.org/curated/en/099090524092617949/pdf/P159382-22bfddfe-5e9c-4596-bdb8-8bbd6db00cf0.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "midterm and endline survey", "label": "DESCRIPTIVE_DATA", "score": 0.8665796518325806, "start": 282, "end": 308, "probe_score": 0.9828, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", and Safety (ESHS) compliance is rated Satisfactory with a 75 percent Completion of Corrective and Preventive\nActions (CAPAs) arising from routine ESHS inspections and audits. Regular and retroactive ESHS measures are being\nimplemented to improve the project’s performance on health and safety. These efforts translate into stable\ncommunity support for the project, contingent on continuous improvement in the implementation of safeguarding\nmeasures. Compliance with the legal covenants is maintained except the client’s obligation to provide adequate\ncounterpart funding for the project and the covenants related to the Joint Authority that are been changed through\nthis restructuring to reflect the new regulatory environment.\n\n17. **The overall risk level for this project is assessed as High.** The project is subject to significant Macroeconomic and\nEnvironmental and Social risks, with Substantial risks identified in Political and Governance areas, Sector Strategies\nand Policies, Technical Design, Institutional Capacity and Sustainability, Fiduciary matters, and Stakeholder\nengagement. Limited fiscal resources and potential cash-flow delays may lead to grievances and claims; these are\nbeing addressed through IDA financing of the RAPs. Extensive land acquisition and community impacts surrounding\n\n\nOfficial Use Only Page 5", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000173", "page": 10, "chunk": 2, "title": "Disclosable Restructuring Paper - Coastal Region Water Security and Climate Resilience Project - P145559", "pdf_url": "https://documents.worldbank.org/curated/en/099011326105042656/pdf/P145559-bcc88824-fc19-4536-97f1-a75f480a71d6.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " under PSNP 6; (iii) Liquidity challenges at banks in Tigray and Afar;\n(iv) Limited time and capacity to register PSNP beneficiaries for Fayda ID before June 2026; and (v) Limited\nmonitoring mechanism to track the linkages to available social services.\n\n1. The PSNP’s rating, based on World Bank implementation support reporting requirements during the last\nsix months are:\n\n|Project Ratings|Previous|Current|\n|---|---|---|\n|**Project Development Objective (PDO)**|**S **|**S **|\n|**Implementation Progress**|**S **|**S **|\n|Component 1: Adaptive Productive Safety Net|S|S|\n|Component 2: Improve Shock Responsiveness of the Rural Safety Net|S|*S|\n|Component 3: Systems, Capacity Development, and Program<br>Management Support|S|S|\n|Financial Management|MS|MS|\n|Project Management|S|S|\n|Counterpart Financing|S|HS|\n|Procurement|MS|MS|\n|Environmental and Social|S|S|\n|Monitoring and Evaluation|MS|S|\n\n\n\n<mark>*While there have been challenges with shock response data and number in need in Ethiopia, this is outside of</mark>\n<mark>the scope of the program. The program’s requirement is to complete shock response on time, which was</mark>\n<mark>reported as 98 percent timeliness in the reporting period. In addition, the Early Warning Dashboard and the</mark>\n<mark>Drought Assistance Plan was prepared.</mark>\n\n\n2\n\n\nOfficial Use Only", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["shock response data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002528", "page": 1, "chunk": 1, "title": "Ethiopia - Strengthen Ethiopia’s Adaptive Safety Net (SEASN) Project : Joint Review and Implementation Support Mission - February 16 to March 26, 2026", "pdf_url": "https://documents.worldbank.org/curated/en/099051926135017367/pdf/P172479-f0929df7-2bed-4b01-bf2f-17e7b9f7dd8d.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "shock response data", "label": "VAGUE_DATA", "score": 0.63446044921875, "start": 946, "end": 965, "probe_score": 0.0545, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nLebanon: Wheat supply emergency response project (P178866)\n\n\nTo address price risks and monitor access to affordable bread, the project will finance third-party monitoring agency\n(TPMA), such as mobilization of Red Cross Volunteers with the Lebanese Red Cross/International Federation of Red Cross\nand Red Crescent Societies at community level/downstream. The TPMA will facilitate price data collection for flour at the\nmill, for bread at the bakeries, and for bread at retail outlets, on a weekly basis and for a sample of outlets across all\ngovernorates. At the same time, the project will finance high frequency ‘Listening to Poor and Vulnerable Household\nSurveys’, entailing data collection on bread prices and consumption for the poor and vulnerable households, by\nconducting random sampling and surveying (biweekly) using UNHCR and WFP beneficiary lists. This information will be\ntriangulated at MOET level with information consolidated from the consumer protection agency, GM, and WFP price\nmonitoring system, and used to adopt appropriate remedies, such as activating the preferential distribution clause\nforeseen in the Framework Agreement, for bakeries in areas where most of the poor and vulnerable groups are located.\nAll monitoring reports will be published on Central Inspection’s IMPACT online platform.\n\n35. **The component will also support consultancy services and technical assistance that will strengthen MOET’s**\n**oversight function as well as capacity** **to manage the gradual transition from the current wheat subsidy system to a**\n**more market-oriented system** . This will include developing a better price monitoring and data system (both for wheat\nand bread); developing an implementation plan for gradually removing wheat subsidies and bread prices and potentially\nincreasing importers’ financial participation in wheat import purchases, to be informed by the complementary activities\ndescribed below; conducting an adequate stakeholder outreach and communication about these reforms; and\nstrengthening regional cooperation around food security and risk management in the", "output": {"entities": {"named_data": ["Listening to Poor and Vulnerable Household\nSurveys", "UNHCR and WFP beneficiary lists", "WFP price\nmonitoring system"], "descriptive_data": ["price monitoring and data system"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000019", "page": 21, "chunk": 0, "title": "Lebanon - Wheat Supply Emergency Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/408131653327258940/pdf/Lebanon-Wheat-Supply-Emergency-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Listening to Poor and Vulnerable Household\nSurveys", "label": "NAMED_DATA", "score": 0.7745883464813232, "start": 635, "end": 685, "probe_score": 0.1039, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "UNHCR and WFP beneficiary lists", "label": "NAMED_DATA", "score": 0.6635661125183105, "start": 847, "end": 878, "probe_score": 0.9488, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "WFP price\nmonitoring system", "label": "NAMED_DATA", "score": 0.757767915725708, "start": 1007, "end": 1034, "probe_score": 0.5167, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "price monitoring and data system", "label": "DESCRIPTIVE_DATA", "score": 0.512176513671875, "start": 1648, "end": 1680, "probe_score": 0.0244, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEducation Infrastructure for Resilience (EU Facility for SuTP) (P162004)\n\n\n6. **To tackle challenges faced by the SuTP, a legal framework was established by issuing Law No.**\n**6458 on Foreigners and International Protection in 2013 and Regulation No. 29153 on Temporary**\n**Protection of Syrians in 2014.** <sup>**5**</sup> [^5: All Syrians who entered the country after April 27, 2011 were retroactively placed under temporary protection,\nwhich provides access to registration and documentation and to services.] While the primary responsibility for emergency response and\ncoordinating humanitarian needs are fulfilled by the Prime Minister Disaster and Emergency\nManagement Authority (AFAD), relevant ministries and local authorities, depending on their respective\narea of jurisdiction, assume responsibility to provide registered SuTP with access to education, health\ncare, social services, and labor markets.\n\n\n7. **Since the beginning of the crisis in 2011, the Government of Turkey has spent an estimated**\n**US$12 billion, largely from national emergency funds, to meet the SuTP’s immediate humanitarian**\n**and basic needs.** Receiving a large number of people from Syria led the Government to take necessary\nmeasures for alleviating the strain on social services, supporting acceptable living conditions, and\npreventing negative effects on human development of SuTP and the national population. Integrating\nSuTP into host communities—social, economic, and cultural life—and providing them accessibility to\nemployment opportunities are priorities for the Government. As such, the Government has undertaken\ncommendable steps to facilitate access to critical public services such as education and health and also\nmade regulatory changes to ease access to labor markets.\n\n\n8. **As it related to education, the general framework of the national education system in Turkey**\n**is set by the Basic Law of National Education No. 1739 and issued in 1973.** By law, regardless of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000160", "page": 11, "chunk": 0, "title": "Turkey – Education Infrastructure for Resilience (EU Facility for STUP)", "pdf_url": "http://documents1.worldbank.org/curated/en/926851507911156465/pdf/PAD2161-PUBLIC-P162004.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad - Refugees and Host Communities Support Project (P164748)\n\n\n\n|Col1|Col2|Col3|Col4|committee and the<br>World Bank.|Col6|\n|---|---|---|---|---|---|\n|Beneficiaries in targeted areas<br>included in the Unified Social Registry-<br>-Female||||||\n|Beneficiaries in targeted areas<br>included in the Unified Social Registry-<br>-Refugees||||||\n|Eligible refugees with identity documents<br>issued by CNARR||Every six<br>months.<br>|CNARR<br>|CNARR, in consultation<br>with UNHCR, will<br>provide a bi-annual<br>report to CFS on the<br>number of eligible<br>refugees receiving an<br>ID, to be measured<br>against total number of<br>refugees.<br>|CNARR and CFS.<br>|\n|Eligible refugees with identity<br>documents issued by CNARR--Female<br>||||||\n\n\n|Monitoring & Evaluation Plan: Intermediate Results Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **|**Definition/Description **|**Frequency **|**Datasource **|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|", "output": {"entities": {"named_data": ["Unified Social Registry"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000035", "page": 51, "chunk": 0, "title": "Chad - Refugees and Host Communities Support Project", "pdf_url": "http://documents.worldbank.org/curated/en/658761536982256019/pdf/PAD2809-PAD-PUBLIC-disclosed-9-12-2018-IDA-R2018-0286-1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Unified Social Registry", "label": "NAMED_DATA", "score": 0.6969541311264038, "start": 223, "end": 246, "probe_score": 0.0036, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " will: (a) target messages to areas where\nvulnerable groups, including refugees and IDPs, reside to inform them about safety measures and benefits; (b)\ntailor messages to the elderly and those with medical risks including their target family members and health care\nproviders; and (c) provide information for Persons Living with Disabilities (PLWD) in accessible formats. To track\nlevels of engagement by those who stand to benefit directly from the Project, one Intermediary Results Indicator\nhas been adopted; “Percentage of interviewed vaccine recipients reporting satisfaction with the COVID-19\nvaccination service that they received”.\n\n**T.Gender**\n\n\n80. **Lebanon has made progress in reducing the differences between women and men in human capital**\n**endowments, particularly on health, but gender inequality continues to be endemic in the country.** One of the\nmain factors that constrain access use of health services by women in Lebanon is adequate affordability of care.\nMore women than men report being unable to afford health care, and access to health insurance is even more of\na challenge in the very north and southern regions, compared to central Lebanon. Likewise, barriers to health\naccess among refugees continue to be challenging for women, as transportation costs and drug fees remain major\nimpediments. During the COVID-19 pandemic, 69 percent of reported deaths have been on males, compared to 31\npercent on female. Reports of infection are also higher among men, with 54 percent of men infected as compared\nto 46 percent of women. the infection numbers among the health workforce are higher for women than men (60\npercent of women compared to 40 percent of men) because women are more highly concentrated among frontline\nworkers: 58 percent of pharmacists and 81 percent of nurses) (UN Women, NCLW, UNFPA, and WHO 2020b, Salti\nand Mezher 2020; The World Bank 2021).\n\n81. **Gender-based differences also exist in", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000000", "page": 39, "chunk": 1, "title": "Lebanon - Strengthening Lebanon's COVID-19 Response under the COVID-19 Strategic Preparedness and Response Program (SPRP)", "pdf_url": "http://documents.worldbank.org/curated/en/099410007282239961/pdf/BOSIB09c1bfedd05c098380dc89cfe988b8.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "## **Annex 4: Technical Assessment – Addendum**\n\n1. **A technical assessment was undertaken in October 2017** for USMID AF operation in accordance\nwith Bank Policy, Program for Results Financing. The following sections constitute a summary of the\nTechnical Assessment, which focused on up-date of the USMID TA conducted in 2012. The assessment\nwas based on a series of comprehensive studies, lessons learnt from implementation to date including the\ncompleted Mid-Term Review and a series of review missions. Moreover, as the Program will be up-scaling\nto eight additional municipalities, a detailed review of the capacity, preparedness and performance of the\nadditional municipalities as well as comparison on key dimensions with the original 14 municipalities was\nundertaken.\n\n**Detailed Program Description**\n\n\n2. **The design of USMID AF is an extension of the current program and will retain all its major**\n**components.** The current phase had a total Program Budget of US$ 160 million, of which IDA funding\nconstitutes US$ 150 million and GoU funding is US$ 10 million **.** USMID currently supports 14 municipal\nLGs as well as the Ministry of Lands, Housing and Urban Development (MLHUD). The largest part of the\nfunding goes to the LG level – the municipal development grant (now named DDEG under the IGFTR)\nUS$ 136 million, and the CB grants (CBG) US$ 15 million with the balance going to support results at the\nMLHUD level to support CB activities as well as Program implementation. The last grant cycle has just\nbeen released, based on the results from the annual performance assessments (APA).\n\n3. **USMID AF will provide support to part of the overall GoU Intergovernmental Fiscal**\n**Transfer Reform Program**, which is aiming at improving the overall grant system, including size,\nallocation, modalities and efficiency in the use of", "output": {"entities": {"named_data": [], "descriptive_data": ["annual performance assessments"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000062", "page": 53, "chunk": 0, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents.worldbank.org/curated/en/946901526654169395/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "annual performance assessments", "label": "DESCRIPTIVE_DATA", "score": 0.8784513473510742, "start": 1569, "end": 1599, "probe_score": 0.4967, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "||2023-07-19||\n|ET-AA FSPSNA/AKAKI K/S/C3-<br>290018-CS-INDV / Recruitme<br>nt of Apprenticeship Specialis<br>t for Youth Employment Rollo<br>ut in Addis Ababa City Admin<br>istration, Akaki Kality Sub Cit<br>y Administration Labor, Enter<br>prise and Industry Developm<br>ent Office|IDA / D7320|Foster Urban Youth Employ<br>ment|Post|Individual Consult<br>ant Selection|Open||3,876.00|0.00|Under Implement<br>ation|2022-04-25|2022-06-06|2022-06-08||2022-06-23||2022-07-19||2023-07-19||\n|ET-AA FSPSNA/ARADA S/C/1-<br>290021-CS-INDV / Recruitme<br>nt of Apprenticeship Specialis<br>t for Youth Employment Rollo<br>ut in Addis Ababa City Admin<br>istration, Arada Sub City Adm<br>inistration Labor, Enterprise<br>and Industry Development Of|IDA / D7320|Foster Urban Youth Employ<br>ment|Post|Individual Consult<br>ant Selection|Open||3,876.00|0.00|Under Implement<br>ation|2022-04-25|2022-06-06|2022-06-08||2022-06-23||2022-07-19||2023-07-19||\n|ET-AA FSPSNA/ARADA S/C/2-<br>290024-CS-INDV / Recruitme<br>nt of Apprenticeship Special", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003926", "page": 3, "chunk": 8, "title": "Ethiopia - EASTERN AND SOUTHERN AFRICA- P169943- Urban Productive Safety Net and Jobs Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099080503202336052/pdf/P169943069c4f10b008b51028402e03884b.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " of<br>Petroleum and Energy<br>|\n\n\n|Monitoring & Evaluation Plan: Intermediate Results Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **|**Definition/Description **|**Frequency **|**Datasource **<br>|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|New electricity connections in N'Djamena||Quarterly<br>|Reports of<br>SNE, progres<br>s reports of<br>PIU<br>|<br>Data provided by SNE<br>operational units and<br>Owner's Engineer<br>|<br>PIU of SNE<br>|\n\n\nPage 53 of 87", "output": {"entities": {"named_data": [], "descriptive_data": ["Data provided by SNE"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 58, "chunk": 1, "title": "Chad - Energy Access Scale Up Project", "pdf_url": "http://documents.worldbank.org/curated/en/860701648216750651/pdf/Chad-Energy-Access-Scale-Up-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Data provided by SNE", "label": "DESCRIPTIVE_DATA", "score": 0.6593791246414185, "start": 441, "end": 461, "probe_score": 0.2066, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "The LVEMP originally included trials to assess the environmental and economic usefulness\nof chemical control of the hyacinth, but these trials were abandoned as being too socially,\neconomically and environmentally risky.\n\n\nWhy was it necessary to use the hyacinth shredding tender as the core of a detailed\nevaluation of the environmental impact _of the shredding/chopping method of control_, instead of\ndoing a detailed EA as part of project preparation? In the absence of sufficient baseline data, and\ndata describing analogous activities in other similar environments, there is virtually no chance of\npreparing a meaningful and useful EA. There are not sufficient data on the water quality or\nphysical limnology of the Lake to be able to accurately describe either the current situation, or\nany large-scale changes in the Lake likely to result from shredding, or any other intervention in\nthe Lake or its catchment. The largest component of the LVEMP is designed to collect sufficient\nwater quality and limnology data from the Lake to create a reasonable scientific baseline, which\nwould enable environmental assessment of development and management actions in the future.\n\n\n_<u>The Scope and Design of the Pilot (as basis of an ongoing EA)</u>_\n\n\nThe LVEMP is designed to collected baseline data, identify and prioritize problems and to\nexperiment with possible solutions to these problems through a series of experimental pilots. The\ntender to shred water hyacinth was prepared in keeping with the experimental approach. It is not\nlarge enough to cause significant impact on the ecology of Lake Victoria, but of sufficient size\n(shredding up to 1500 ha of floating water hyacinth mats) to allow water quality monitoring to\npick up changes in surrounding Biological Oxygen Demand (BOD), phytoplankton\nabundance/species composition, conductivity etc, that might be indicative of the impact of this\nmethod of control, should it have widespread use in the Lake at some point in the future.\n\n\nMore particularly, the water hyacinth shredding pilot is important because traditional\nharvesting/removal of weed to dry land", "output": {"entities": {"named_data": [], "descriptive_data": ["water quality and limnology data"], "vague_data": ["baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020447", "page": 30, "chunk": 0, "title": "Kenya - Lake Victoria Environmental Management Project : Inspection Panel Report and Recommendation : Kenya - Lake Victoria Environmental Management Project : Inpection Panel Report and Recommendation", "pdf_url": "https://documents.worldbank.org/curated/en/941631468774530549/pdf/21933.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "baseline data", "label": "VAGUE_DATA", "score": 0.685762882232666, "start": 485, "end": 498, "probe_score": 0.2217, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "water quality and limnology data", "label": "DESCRIPTIVE_DATA", "score": 0.7881003022193909, "start": 988, "end": 1020, "probe_score": 0.0397, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " GoC and SNE to delineate their respective roles and\nresponsibilities that should improve SNE operational and financial performance. These activities will help\nput SNE on a recovery path.\n\n20. **The WBG’s strategy to support energy access in Chad pursues a two-pronged approach:**\n**(a) off-grid electrification driven by the private sector to promptly boost access and (b) national grid-**\n**based electrification by SNE that is strategically important but will take time to materialize.** In the past,\nit was virtually impossible to sustainably increase energy access without addressing basic issues\nconcerning sector institutions, policies, and regulations. These fundamentals are still valid and essential\nfor national grid-based access and regional power trade and are supported by the WBG in Chad as outlined\nin the preceding paragraphs. However, international experience, including in Africa, shows that it takes\nsignificant time and effort to address sector systemic issues required for sustainable electricity supply and\nelectrification by the national power utility, as well as regional power trade. At the same time, private\nsector-led off-grid electrification, and notably via SSS, which have seen a rapid development in the past\ndecade worldwide and especially in Africa, offers an excellent opportunity to rapidly advance the access\nagenda despite systemic issues facing the Chad power sector and SNE in particular. The WBG energy\naccess strategy in Chad capitalizes on this opportunity and places high importance on private sector-led\noff-grid electrification to efficiently achieve results on the ground and help the country meet its ambitious\nelectricity access target of 53 percent by 2030.\n\n21. **The proposed Chad Energy Access Scale Up Project (CEASP) aims to boost access from about 6**\n**percent today to 30 percent or about 1 million households by 2027, mostly by the private sector.** The\nproject design was informed by the preliminary outcomes of the ongoing national electrification analysis\nfor Chad that prioritizes isolated power", "output": {"entities": {"named_data": [], "descriptive_data": ["national electrification analysis\nfor Chad"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 20, "chunk": 1, "title": "Chad - Energy Access Scale Up Project", "pdf_url": "http://documents.worldbank.org/curated/en/860701648216750651/pdf/Chad-Energy-Access-Scale-Up-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "national electrification analysis\nfor Chad", "label": "DESCRIPTIVE_DATA", "score": 0.6329658627510071, "start": 1985, "end": 2027, "probe_score": 0.0074, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "In its efforts to respond to the high levels of poverty and vulnerability, Burundi developed a National Social**\n**Protection Policy (NSPP, 2011), a Social Protection Strategy (2015) and a Social Protection Law (2020) to define the**\n**legal framework for contributory and non-contributory social assistance** . The Law describes available contributory\nregimes for formal and informal workers and details the eligibility criteria for social assistance and social insurance. The\nLaw also ratifies the existing coordination mechanisms for social protection and determines that a social registry will be\nthe main targeting instrument for social protection programs. The Social Protection Strategy is under review and details\nall programs aim at providing contributory and non-contributory social assistance to Burundians.\n\n20. **Government funding for safety nets is limited.** Through the 2019/2020 national budget, the proportion of the\nnational budget allocated to the social protection sector was 2.75 percent of GDP, increasing from 1.6 percent in 2016 <sup>22</sup> .\nFrom this budget, free healthcare represented 19.3 percent, followed by university’s grants representing 16 percent and\nthen seeds and agricultural inputs representing 13.5 percent. Humanitarian assistance represented 7.5 percent of total\nsocial protection spending while prevention and care for vulnerable groups including victims of Gender Based Violence\n(GBV) and persons living with Human Immunodeficiency Virus represented 18.3 percent.\n\n\n22 UNICEF. Analysis of Social Protection and Finance Law. 2021.\n\n\nPage 13 of 86", "output": {"entities": {"named_data": [], "descriptive_data": ["social registry"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000130", "page": 17, "chunk": 1, "title": "Burundi - Cash for Jobs Project", "pdf_url": "http://documents1.worldbank.org/curated/en/768621641923064747/pdf/Burundi-Cash-for-Jobs-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "social registry", "label": "DESCRIPTIVE_DATA", "score": 0.8632777333259583, "start": 577, "end": 592, "probe_score": 0.0713, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " work address these issues even\nthough the final product is not presented as a PSIA. A comprehensive poverty assessment was\nconducted in 2006, and as part of the work for the 2006 Country Economic Memorandum the\nBank has developed a SAM-based CGE model (MAMS) as a tool to simulate the impact on\nhousehold groups of specific investments, policies and various economic and price shocks. This\ncould provide a useful tool for ex ante PSIA in future. A PSIA on land in Northern Uganda is\nbeing conducted jointly by the Ministry of Lands and the World Bank, and a joint\nTanzania/Uganda PSIA to assess the Local Government Revenue Policies and their impacts in\nthe two countries is ongoing.\n\n\nThe assessment of the poverty and social impact of the measures proposed by the PEAP and\nsupported by the PRSC is carried out in the context of Uganda’s PEAP monitoring system, and\nin particular the biannual household surveys that analyze, among other things, poverty trends and\ndynamics. These national surveys provide a rich source of information on household socioeconomic characteristics, including consumption expenditures, employment, and access to social\nservices. The surveys are complemented by the more qualitative participatory poverty\nassessments. Emphasis is increasingly being placed on outcomes in the PEAP monitoring, and\non indicators which provide direct information on the status of poverty in all its dimensions.\n\n\nBecause the PRSC instrument supports policy and institutional reforms intended to create a\nstronger institutional framework for development, it includes support for improved management\nof forest and water resources. Negative direct impacts on the environment as a result of the\nPRSC itself are expected to be minimal. The potential for land acquisition, resettlement, and", "output": {"entities": {"named_data": ["PEAP monitoring system"], "descriptive_data": ["biannual household surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015499", "page": 3, "chunk": 1, "title": "Uganda - Sixth Poverty Reduction Support Credit", "pdf_url": "https://documents.worldbank.org/curated/en/607981468308936037/pdf/PID010Appraisal0Stage.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "PEAP monitoring system", "label": "NAMED_DATA", "score": 0.7263780832290649, "start": 840, "end": 862, "probe_score": 0.142, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "biannual household surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8797500729560852, "start": 886, "end": 912, "probe_score": 0.1402, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", at 37.3 percent.\n\n2. **Economic progress is not being evenly distributed across the country** . The north and northeast regions of the country,\nwhere Arid and Semi-Arid Land (ASAL) areas are concentrated, are characterized by poverty rates that are persistently\nhigher than the rest of the country. Additionally, larger households, those headed by individuals with lower education\nlevels, female-headed households, and households with children are all associated with higher poverty rates.\nRefugees, the majority of whom also reside in ASAL areas, are also a vulnerable group, facing high food insecurity and\nlimited employment opportunities.\n\n3. **Kenya hosts a significant population of refugees and asylum seekers.** There are over 550,000 refugees and almost\n200,000 asylum seekers in the country, with the majority residing in the Dadaab Camps (320,572) in Garissa County\nand Kakuma Camp and Kalobeyei Integrated Settlement (215,995) in Turkana County. The camps and settlement are\nmanaged by the Government of Kenya’s (GoK) Department of Refugee Services (DRS), with support from the United\nNations High Commissioner for Refugees (UNHCR) and other humanitarian and development partners. The GoK’s\ncommitment to the welfare of refugees and host communities, and to the Global Compact on Refugees, is evident in\nthe enactment of the Refugees Act of 2021, which provides refugees more rights and protections, and by drafting the\nShirika Plan, (2024), which seeks to create more integrated host community and refugee settlements where access to\n\n\n1 World Bank. Kenya Poverty and Equity Assessment 2023 - From Poverty to Prosperity: Making Growth More Inclusive (English). Washington, D.C.:\nWorld Bank Group.\n\n\nPage 2", "output": {"entities": {"named_data": ["Kenya Poverty and Equity Assessment 2023"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:004204", "page": 2, "chunk": 1, "title": "Appraisal Program Information Document (PID)", "pdf_url": "https://documents.worldbank.org/curated/en/099083124034034959/pdf/P501648-4766565b-a2b6-4106-85a4-9cb7a5a150cb.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Kenya Poverty and Equity Assessment 2023", "label": "NAMED_DATA", "score": 0.5555357933044434, "start": 1565, "end": 1605, "probe_score": 0.9981, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_(c)_ _Enabling evidence-based policy making for poverty reduction._ This sub-component will:\n\n\n\n(i) _Support_ _the_ _functioning_ _of_ _the_ _Social-IMC_ _and_ _creation_ _of_ _a_ _poverty analysis_\n\n\n\n_capability._ In order to build capacity for evidence-based policymaking for poverty\nreduction, SPPP will finance (i) technical assistance to support the Inter-ministerial\nCommittee for Social Policy (Social-IMC) and its Secretariat; (ii) technical assistance\nto establish a Poverty Analysis Team, whose role will be to assess the poverty and\ninequality situation in Lebanon using Household Budget Survey (HBS) data; and (iii)\nthe design and implementation of the next HBS (in **2017),** which will be a large\n\n\nsample survey representative at the governorate _(Mohafazat) level._\n\n\n\n**_Component 4: Project Management_** **(US$2.2** million total cost, of which **US$2.0** million to be\nfinanced from IBRD)\n\n\n**16.** The project will finance a team which will carry out key cross-component functions,\nincluding: (i) overall project coordination, working closely with the teams responsible for the\nimplementation of the other project components (see Annex IV) and reporting to the Minister on\noverall project progress; (ii) implementation of the fiduciary functions of the project, including\nprocurement, financial management and internal audit, as well as ensuring external audits are\nundertaken in compliance with requirements; and (iii) supporting the management of Component\n\n**1.** The PM is foreseen as a temporary structure to last the duration of the project, after which it\nwill cease to exist. For this reason, it is expected that during project implementation, the PM will\nbuild", "output": {"entities": {"named_data": ["Household Budget Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000109", "page": 47, "chunk": 0, "title": "Lebanon - Social Promotion and Protection Project", "pdf_url": "http://documents1.worldbank.org/curated/en/643811468055144236/pdf/749060PAD0P124010Box374388B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Household Budget Survey", "label": "NAMED_DATA", "score": 0.8101816773414612, "start": 584, "end": 607, "probe_score": 0.4767, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Figure 2: Average monthly wage against the proportion of employed women at**\n**various public sector organizations**\n\n\nThe benefits are predominantly paid as part of male wages on behalf of their families. See Appendix Table A2 for the list of\norganizations. The regression line is a simple OLS regression for the two plotted variables. The line is not necessarily the best possible\nfit for the data; it only illustrates a possible relationship that we exploit rigorously in the analysis. The average compensation is based\non both male and female Kuwaiti employees.\n_Source:_ Kuwait Civil Service Commission (2019) and authors’ calculations\n\n\nThe figures above suggest that our lists of organizations and occupation types are\nanalytically meaningful. But they are also somewhat limited. Fortunately, our data set\nalso offers more comprehensive variables representing specific occupations and\nworkplaces that we translated to English from Arabic using Google Translate API. While\nthe categorizations prove to have high explanatory power, Table **3** suggests the need for\ncaution when using the two variables because many categories represent very few\nemployees. For example, the table indicates that at least 50 percent of classified\noccupations have only one observation. We show below that robustness checks—in\nwhich we drop occupations and workplaces representing fewer than 10 employees—do\nnot substantively change the results.\n\n\n9", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data set"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001030", "page": 10, "chunk": 0, "title": "idu0c6265d500cef20460f0a7db0f2dbebe73b23", "pdf_url": "https://local/prwp/idu0c6265d500cef20460f0a7db0f2dbebe73b23.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data set", "label": "VAGUE_DATA", "score": 0.65424644947052, "start": 806, "end": 814, "probe_score": 0.4602, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\n**Table 1.** Ukrainian employment rate in EU.\n\n\n**Employment rate** **Main sectors of employment** **Date** **Source**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n**Source:** Deloitte elaboration based on the aggregation in OECD International Migration Outlook 2023. The calculation methods of employment\nrates vary between the countries, the results for Poland, the United Kingdom, Czech Republic and Italy are based on surveys. Additionally, the\ndifferent statistical offices and organisations may use different employment and working age definitions.\n\n\n\nCurrently, DIW Berlin data shows that the\nemployment of refugees from Ukraine is\nmuch lower in Germany, although many\naspire to find employment. In a weekly\nreport from 12th July 2023 the German\nInstitute for Economic Research (DIW\nBerlin), a survey conducted in the first\nquarter of 2023 finds that only 18% of\nworking age refugees were employed\n(Kollman, 2023). Among the non-employed,\nhowever, as many as 93% declare\nwillingness to begin working, of which\n71% as soon as possible or within a year.\nImportantly, many refugees are currently\nattending language courses in Germany\n\n- 65% in early 2023 with a further 10%\nalready having completed a course. 87%\nalso took part in inclusion courses that\nwere offered. Per the report, since the\nbeginning of the full-scale war,, around one\nmillion people have fled to Germany, while\nEurostat data on beneficiaries of temporary\nprotection show that there were around 1.17\nmillion Ukrainians under such schemes in\nGermany <sup>30</sup> [^30: Eurostat data, <u>https://ec.europa.eu/eurostat/databrowser/view/migr_asytpsm/default/table?lang=en</u>] .\n\n\nAmong working refugees there is a\nsignificant number of entrepreneurs.\nThe high employment rate of refugees in\nPoland covers not", "output": {"entities": {"named_data": ["OECD International Migration Outlook 2023", "DIW Berlin data", "Eurostat data on beneficiaries of temporary\nprotection", "Eurostat data"], "descriptive_data": ["survey conducted in the first\nquarter of 2023"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 13, "chunk": 0, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "OECD International Migration Outlook 2023", "label": "NAMED_DATA", "score": 0.7287906408309937, "start": 344, "end": 385, "probe_score": 0.9999, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "DIW Berlin data", "label": "NAMED_DATA", "score": 0.8686275482177734, "start": 688, "end": 703, "probe_score": 0.9881, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey conducted in the first\nquarter of 2023", "label": "DESCRIPTIVE_DATA", "score": 0.5984160304069519, "start": 920, "end": 965, "probe_score": 0.9396, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Eurostat data on beneficiaries of temporary\nprotection", "label": "NAMED_DATA", "score": 0.6313542127609253, "start": 1505, "end": 1559, "probe_score": 0.1036, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Eurostat data", "label": "NAMED_DATA", "score": 0.6078804731369019, "start": 1662, "end": 1675, "probe_score": 0.9991, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009765", "page": 62, "chunk": 2, "title": "Ethiopia - Road Rehabilitation Project", "pdf_url": "https://documents.worldbank.org/curated/en/221381468032097471/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " assessment of applications for\nhumanitarian visa; and research and piloting of projects\nin the area of other admission pathways.\n\n\n\nMENA: 2017\nProjected needs\nand targets\n\n\nThe total projected resettlement needs for the MENA\nregion in 2017, identified by UNHCR offices is 280,915\npersons. This marks a decrease compared with the\nprojected needs for the region of 369,334 individuals\nin 2016. The reason for the decrease in the total\nresettlement needs is largely methodological: firstly,\nsince UNHCR has not been able to verify the presence\nof registered refugees in Libya due to the security\nenvironment, a different approach to the calculation of\nthe needs was adopted compared with previous years;\nand secondly, the number of registered Syrian refugees\nin Lebanon did not increase as anticipated due to the\nchange of residency requirements in Lebanon in early\n2015, thus impacting on projected resettlement needs\nwhich are calculated based on the projected population\nfigures. This apparent reduction does not reflect a\ndecrease in the resettlement needs, which remain high\nfor Syrians and other refugee populations in the region.\n\n\nIt should also be noted that the projected resettlement\nneeds and targets for the MENA region do not include\nthe relevant figures for Turkey, where 275,000 Syrian\nrefugees are projected to be in need of resettlement.\nIt is estimated that ten per cent of the Syrian refugee\npopulation are in need of resettlement, amounting\nto projected resettlement needs in 2017 for a total\nof 477,000 Syrians in Egypt, Iraq, Jordan, Lebanon\nand Turkey <sup>1</sup> [^1: \u0007This calculation is based on the projected Syrian refugee population\nin these five operations at the end of 2016.] . This marks a 16 per cent increase in the\nprojected resettlement needs for Syrian refugees\ncompared with 2016 when 410,000 Syrians were\nestimated to be in need of resettlement in the same five\noperations.\n\n\nProjected submissions from the MENA region in 2017\nare 50,500; mainly Syrian refugees in Jordan, Lebanon,\nEgypt, and Iraq, which represents an almost 100%\nincrease from 2016", "output": {"entities": {"named_data": [], "descriptive_data": ["projected population\nfigures", "projected Syrian refugee population"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001537", "page": 51, "chunk": 1, "title": "UNHCR Projected Global Resettlement Needs 2017", "pdf_url": "https://reliefweb.int/attachments/eee018b4-3938-3398-bbb8-4e2153fba0f4/575836267.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "projected population\nfigures", "label": "DESCRIPTIVE_DATA", "score": 0.8050801157951355, "start": 951, "end": 979, "probe_score": 0.0748, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "projected Syrian refugee population", "label": "DESCRIPTIVE_DATA", "score": 0.708558976650238, "start": 1626, "end": 1661, "probe_score": 0.3057, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " sourced from Ukraine (80 percent of\ntotal wheat imports), and Russia (16 percent of total wheat imports), respectively.\n\n3. **The conflict comes at a time when Lebanon has been grappling with the direst of shocks**, starting with\nthe acute economic and financial crises, compounded by the COVID-19 pandemic, and finally the Port of Beirut\nexplosion. In 2019, Lebanon faced an economic and financial crisis due to a stop in capital inflows, which led to\nsystemic failures across the banking sector, debt, and the exchange rate. A shortage of United States (US) dollars\nin the market resulted in multiple exchange rates, as well as informal restrictions and control mechanisms on\ndeposits held in US dollars and on transfers out of the country. The COVID-19 pandemic and subsequent\nlockdowns exacerbated the situation, directly affecting people’s health, livelihoods, and food security. The Port of\nBeirut explosion in August 2020 had significant negative economic impacts, including the loss of livelihoods,\nplacing further strain on the economy. In the face of these crises, Lebanon’s gross domestic product plummeted\nfrom close to US$52 billion in 2019 to a projected US$21.8 billion in 2021, a 58 percent contraction. Such a\nsignificant and rapid contraction is usually associated with conflicts or wars. The compounding nature of these\nchallenges makes a recovery difficult, with long-term implications for the welfare of Lebanese households.\n\n4. **The crises increased unemployment, further worsening household welfare.** One in five workers has lost\na job since October 2019, while 61 percent of firms surveyed decreased the number of permanent workers by 43\npercent on average (World Bank Enterprise Surveys, 2019–2020). Medium-sized and large firms laid off a larger\nnumber of workers: 76 percent of large firms downsized by an average of 37 percent, while 70 percent of mediumsized firms shrank by 43 percent. These numbers cover only formal firms, and", "output": {"entities": {"named_data": ["World Bank Enterprise Surveys"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000019", "page": 11, "chunk": 1, "title": "Lebanon - Wheat Supply Emergency Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/408131653327258940/pdf/Lebanon-Wheat-Supply-Emergency-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "World Bank Enterprise Surveys", "label": "NAMED_DATA", "score": 0.9227860569953918, "start": 1685, "end": 1714, "probe_score": 0.9968, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "sup> (0.005)\ncomm_org 0.922 (0.046) 0.980 (0.038) 0.968 (0.022)\nsouth 0.875 <sup>*</sup> (0.064) 0.907 <sup>*</sup> (0.047) 0.939 <sup>***</sup> (0.017)\n<u>centre</u> <u>0.892</u> <sup>***</sup> <u>(0.033)</u> <u>0.961</u> <u>(0.046)</u> <u>0.934</u> <sup>***</sup> <u>(0.018)</u>\n<u>chi2</u>\np\n\n\n\n42", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001628", "page": 45, "chunk": 3, "title": "idu1f657cd6a183a5143921b0791c9d6c882a4c7", "pdf_url": "https://local/prwp/idu1f657cd6a183a5143921b0791c9d6c882a4c7.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nAfghanistan: Eshteghal Zaiee - Karmondena (EZ-Kar) (P166127)\n\n\n**ANNEX 10: Consultative Process with GoIRA, Development Partners and Private Sector**\n10. During the EZ‐Kar project preparation period, DiREC’s technical working groups provided the platform for\nconsultations and recommendations, many of which are reflected in the activities and design choices of EZ‐Kar.\nSome of key features include the following: (i) a stakeholder driven design approach; (ii) the opportunity to\ndevelop synergies with other Bank and IFC projects and projects of other donors; (iii) considering the absorptive\ncapacity of GoIRA to implement; and (iv) a sharp focus on the short‐medium to long term economic opportunity\naspect of the returnee and IDP challenge. The project also tries to address the inherent complexity of dealing\nwith returnees in Pakistan by supporting only those measures considered necessary.\n\n11. There was significant engagement with stakeholders to design the regional and national interventions. GoIRA\nestablished four working groups, which included all concerned ministries and the private sector to inform project\ndesign. These working groups looked at incentives, infrastructure, regulatory reform, and skills. A parallel\nengagement with city mayors sought municipal perspectives. The views of returnees were obtained through\ndirect consultation with Afghan repatriation _shuras_, the Embassy of Afghanistan in Pakistan, and surveys. The\nWorld Bank task team also ensured that humanitarian actors and other international agencies, such as Office of\n(OCHA), UNHCR, and International Organization for Migration (IOM), were involved during the design\ndiscussions. UNCHR has been heavily involved in the design of Component 1 and will continue to work with the\nWorld Bank task team during implementation and supervision of this work.\n\n12. The decision to focus on developing economic opportunities for a broad range of needs (social service delivery,\nhousing, and social cohesion) is premised", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["surveys"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000123", "page": 88, "chunk": 0, "title": "Afghanistan - Eshteghal Zaiee - Karmondena (EZ-Kar) Project", "pdf_url": "http://documents1.worldbank.org/curated/en/714251547070785057/pdf/Afghanistan-Eshteghal-Zaiee-Karmondena-EZ-Kar-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "surveys", "label": "VAGUE_DATA", "score": 0.677046537399292, "start": 1455, "end": 1462, "probe_score": 0.8766, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "A bridge to life in the UK\n\n## EXECUTIVE SUMMARY\n\n\n\n**1. INTRODUCTION – AIMS AND CONTEXT**\n**OF THE RESEARCH**\n\n\nThe Refugee Council has commissioned this research\nto help policy makers, funders and other stakeholders\nto understand the role of refugee-led community\norganisations (RCOs) and how they contribute to wider\npolicy objectives such as integration, inclusion, cohesion\nand equality. It also examines the challenges faced by\nRCOs and how civil society support organisations and\nother support can help RCOs to oveRCOme these\nchallenges and sustain and develop their contributions\nto integration.\n\n\nRCOs are defined as organisations led mainly by people\nfrom communities whose members include significant\nnumbers of refugees, and whose services and activities are\nintended for refugees. RCOs may define their communities\nby nationality, language or geographical area, while others\nserve specific groups such as women or young people.\nOthers focus on a specific need or service.\n\n\nThe role of RCOs in integration has been recognised in\nprevious policies on refugee integration. These have now\nbeen replaced by a broader focus on integration in the\ncontext of wider community.\n\n\nThis research explores the activities of RCOs, the outcomes\nthey deliver for their communities and how these outcomes\ncontribute to current policies on integration as well as\nother policies that focus on themes that are often cited to\ndefine integration: identity and sense of belonging, civic\nparticipation, independence, English proficiency,\nemployment, education, health and cohesion.\n\n\n**2. METHODOLOGY**\n\n\nThe methodology was designed to explore the three\nmain issues addressed by the research: the activities and\noutcomes of RCOs and their role in integration; the\nchallenges faced by RCOs; and support to help RCOs\nsustain and develop their role in integration. It was also\ndesigned to explore the local context in which RCOs\noperate, including policy, funding and support. The\nmethodology thus included four main elements:\n\n\nA **review", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001328", "page": 3, "chunk": 0, "title": "A bridge to life in the UK: Refugee-led community organisations and their role in integration (October 2018)", "pdf_url": "https://reliefweb.int/attachments/cc625cfb-c5d9-3500-a07e-3f8eca765f83/A_bridge_to_life_in_the_UK_Oct_2018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " go down a little, the effects on the different sub-samples are stable to this change\n\n\n(results not shown).\n\n\nI test if reported infant mortality is connected with debt relief at Decision Point of the HIPC Ini\ntiative by using DHS data on infant mortality from earlier surveys. <sup>8</sup> Here, I apply a test developed by\n\n\nKudamatsu (2012) in which the average infant mortality rate of mothers born in the same year, in the\n\n\nsame country, and who give birth in the same year is compared between the used DHS and an earlier\n\n\nDHS. If recall bias is a serious problem, the infant mortality rate would change systematically in relation\n\n\nto HIPC at Decision Point. Judging from the results in Table 7, this does not appear to be the case.\n\n\nSecond, if fertility choices vary by women’s socioeconomic status and if this is systematically related\n\n\nto HIPC, one concern may be that the results on debt relief at Decision Point are driven by differences in\n\n\nfertility rather than infant mortality since the women who identify the effect of debt relief in the within\n\nmother estimations are different from other mothers in terms of age, poverty levels, formal schooling,\n\n\nand residency. The comparison of infant mortality between women in HIPCs and non-HIPCs giving\n\n\nbirth in the same years in the within-mother estimations would consequently be less credible. Again,\n\n\nI follow Kudamatsu (2012) to investigate if fertility of mothers changes depending on socioeconomic\n\n\nCompletion Point before or in 2006 and in the year of Completion Point for HIPCs which reached Completion Point after\n2006.\n8Earlier surveys available for 44 countries in the sample.\n\n\n13", "output": {"entities": {"named_data": ["DHS data on infant mortality"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006880", "page": 14, "chunk": 1, "title": "wps7872", "pdf_url": "https://local/prwp/wps7872.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "DHS data on infant mortality", "label": "NAMED_DATA", "score": 0.6820827126502991, "start": 228, "end": 256, "probe_score": 0.8564, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "## **Realidad de la Integración Local de la** **Población Refugiada en Guatemala**\n#### **Diagnóstico Participativo 2015**", "output": {"entities": {"named_data": ["Diagnóstico Participativo 2015"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000275", "page": 2, "chunk": 0, "title": "Realidad de la Integración Local de la Población Refugiada en Guatemala: Diagnóstico Participativo 2015", "pdf_url": "https://reliefweb.int/attachments/1f3fb641-89af-3c49-b06c-0240386b157c/10907.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Diagnóstico Participativo 2015", "label": "NAMED_DATA", "score": 0.6355234980583191, "start": 90, "end": 120, "probe_score": 0.0018, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " of\nthe PISA index for economic, social and cultural status were below Level 2 on Reading in PISA (considered the minimum\nof adequate performance), 72 percent of children from families from the lowest quintile of the PISA index were below\nlevel 2. Foundational learning (literacy and numeracy) in early grades paves the way for future learning, and differences\nin educational attainment become magnified through youth and adult life in the acquisition of human capital. Without\nany claims regarding causation, it is useful to look at labor earnings, which are more closely related to human capital than\nearnings from other assets. OECD figures show that 32 percent of 25–64-year-olds in Costa Rica with low levels of\neducational attainment (below upper-secondary education) earned less than half of the median earnings for the country\nand were thus at risk of poverty, if not already poor. <sup>10</sup> [^10: OECD Education at A Glance, 2023, Table A4.2. The correlation (not causation) between socio-economic conditions, academic achievement and\nlabor market outcomes is a global phenomenon. For the OECD countries as a whole in 2018, the percentage of below Level 2 performers from the\ntop quintile of the PISA index for economic, social and cultural status, was 8%; while for the bottom quintile, the figure was 49%. For the labor market\nfigures quoted in the text, 30% of 25-64 year olds for the OECD countries correspond to the 32% mentioned in the text for Costa Rica.]\n\n**Employability**\n\n6. **In addition to foundational learning, Costa Rica’s education system requires a renewed emphasis on**\n**competencies for employability, including cognitive, technical and digital skills, socioemotional competencies, and**\n**English language skills.** Costa Rica’s economy diversified from agricultural commodity exports in the 2000s to an economy\ncentered on high-tech manufacturing and services. Costa Rica contributes to at least 5 major high-tech global value chains:\nelectronics, medical", "output": {"entities": {"named_data": ["OECD figures"], "descriptive_data": [], "vague_data": ["labor market\nfigures"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000189", "page": 11, "chunk": 1, "title": "Costa Rica - Results in Education (CORE) Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099111524150039416/pdf/BOSIB-8191b179-7209-4faa-b5e0-11783bcd492d.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "OECD figures", "label": "NAMED_DATA", "score": 0.6750604510307312, "start": 631, "end": 643, "probe_score": 0.9809, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "labor market\nfigures", "label": "VAGUE_DATA", "score": 0.6536896824836731, "start": 1329, "end": 1349, "probe_score": 0.77, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda: Roads and Bridges in the Refugee Hosting Districts Project (P171339)\n\n\n46. The grant would finance the construction cost of civil works and costs of construction supervision\nconsultants, third-party audit consultants, safeguards management consultants for implementation of\nResettlement Action Plans, consultants/NGOs for implementation of GBV, VAC, and HIV/AIDS action plans,\nRoad User Satisfaction Survey consultants, and monitoring and evaluation consultants during the\nconstruction period. All the remaining costs, including the costs of maintenance during the maintenance\nperiod, preparation of environmental and social risk management documents as well as detailed\nengineering designs of civil works, land acquisition, and resettlement and rehabilitation will be met through\nthe government funds. The scope of civil works will include widening of formation width, pavement\nstrengthening and widening, rehabilitation of existing structures, earthworks, construction of new\npavement, structures, drainage facilities, improvement of junctions, and provision of road safety features.\nThe designs, as a minimum, will conform to the relevant standards, codes and manuals of the MoWT and\nincorporate features to enhance climate resilience and road safety. Climate change adaptation measures\ninclude realigning the road network to reduce exposure to natural hazards, raising road formation levels\nwith due consideration to maximum flood levels, adjusting the embankment slopes, enhancing drainage,\nimproving road permeability, using under drains, introducing debris deflectors, conducting scour checks,\npreventing erosion, using roads for water management, monitoring conditions and establishing early\nwarning systems, and improving pavement and bridge design. In keeping with the findings from the gender\nassessment and stakeholder consultations, the designs also include service roads, pedestrian sidewalks and\ncrossings, roadside vending facilities, bus bays, speed calming measures, and lighting in urban areas. Also,\nto alleviate barriers for women employed in Project civil works, contractual provisions will be included to\nprovide adequate and safe basic amenities such as separate toilets, changing rooms etc. For non-skilled\nlabor, the Contractors shall be encouraged", "output": {"entities": {"named_data": ["Road User Satisfaction Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 26, "chunk": 0, "title": "Uganda - Roads and Bridges in the Refugee Hosting Districts/Koboko-Yumbe-Moyo Road Corridor Project", "pdf_url": "http://documents.worldbank.org/curated/en/834931600048847296/pdf/Uganda-Roads-and-Bridges-in-the-Refugee-Hosting-Districts-Koboko-Yumbe-Moyo-Road-Corridor-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Road User Satisfaction Survey", "label": "NAMED_DATA", "score": 0.5734335780143738, "start": 404, "end": 433, "probe_score": 0.2905, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nImportantly, most of the income of\nUkrainian nationals living in Poland, both\nrefugees and pre-2022 migrants, comes\nfrom their work. Our calculations based\non the UNHCR MSNA Poland 2023 survey\nresults show that 80% of refugee income\ncomes from employment, with other\nsources on average playing a much lesser\nrole. The income brackets presented in the\nsurvey show that 20% of households earn\nless than 3000 PLN, 41% earn between\n3,000 and 6,000 PLN and 12% earn more\nthan 6,000 PLN, while 27% of respondents\npreferred not to answer. Meanwhile, in the\nNBP (2023) survey conducted in November\n2022 the net income of refugees oscillated\nbetween 2,000 and 3,000 PLN, while the\nnet income of pre-2022 migrants was\ncloser to between 3,000 and 4,000 PLN.\nIn the case of Ukrainians that were out\nof work, the monthly income was more\nvaried, especially because there were fewer\nprevious migrants in this situation.\nThe median income for non-employed prewar immigrants was around 2,500 PLN <sup>32</sup> .\nAmong refugees from Ukraine remaining\nout of work at the time of the survey, the\nmedian income equaled around 600 PLN.\n\n\nThe standard of living of refugees from\nUkraine may be significantly lower than\nnatives, even at similar incomes due to\ntheir lack of housing capital. 87% of the\npopulation in Poland resided in owneroccupied housing in 2021 and 2022,\naccording to Eurostat. As most refugees\nfrom Ukraine do not possess housing of\ntheir own in Poland, they need to rent in a\nrelatively tight market, especially when they\nreside in large metropolitan areas that offer\nthe most opportunities. Initially, in the first\nmonth after the outbreak of the full-scale\nwar in Ukraine, the number of renting\noffers in the OLX and Otodom portals\ndropped by approximately 60%, though it\nlater", "output": {"entities": {"named_data": ["UNHCR MSNA Poland 2023 survey", "NBP (2023) survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 14, "chunk": 0, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "UNHCR MSNA Poland 2023 survey", "label": "NAMED_DATA", "score": 0.8903824090957642, "start": 239, "end": 268, "probe_score": 0.9899, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "NBP (2023) survey", "label": "NAMED_DATA", "score": 0.8841383457183838, "start": 626, "end": 643, "probe_score": 0.8845, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " have relatively better labour\nmarket situations. In countries with lower\nunemployment, refugees fare better in\nthe labour market. Since women make\nup the majority of refugees of working\nage, the situation of women on the labour\nmarket is especially important. As such,\nfemale unemployment rates explain 36%\nof the variation in refugees from Ukraine\nemployment rates in studies from 11 EU\nMember States <sup>22</sup> [^22: After excluding Germany and Switzerland as outliers. 23  Due to possible differences in methodologies data from this surveys should not be directly compared]\n\n\n**Chart 10.** Female unemployment and refugees from Ukraine employment in Europe\n\n\n70%\n\n\n\n**Chart 11.** Education attainment of Poles and Ukrainians\n\n\n**Eurostat** Poland LFS 2022\n\n\n\n**UNHCR**\n\n**(2023)**\n\n\n**NBP**\n**(2022)**\n\n\n**Ukrstat**\n\n\n\n11%\n\n\n56%\n\n\n48%\n\n\n46%\n\n\n\n30%\n\n\n\nRefugees from Ukraine VII-VIII 2023\n\n\nRefugees from Ukraine XI 2022\n\n\nPre-2022 migrants from Ukraine XI 2022\n\n\nUkraine LFS 2020\n\n\n\n29%\n\n\n20%\n\n\n17%\n\n\n29%\n\n\n\n60%\n\n\n14%\n\n\n33%\n\n\n37%\n\n\n\n37%\n\n\n\n60%\n\n\n50%\n\n\n40%\n\n\n30%\n\n\n20%\n\n\n10%\n\n\n0%\n\n\n\n\n|PL XI<br>PL VII-VIII|2022<br>2023 U|K**|Col4|Col5|\n|---|---|---|---|---|\n||~~CZ~~<br> <br>|LT<br>|SE||\n|||DK<br>NL||EE|\n||||FR|**R = 0,36**|\n|||IE<br>|||\n||DE<br>|~~H*~~||~~IT~~|\n||||||\n\n\n\n2% 4% 6%\n\n**Female unemployment rate**\n\n\n\n34%\n\n\n\n\n\n\n\n\n\n\n\nThe", "output": {"entities": {"named_data": ["Poland LFS 2022", "NBP", "Ukrstat"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 10, "chunk": 1, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Poland LFS 2022", "label": "NAMED_DATA", "score": 0.7854381203651428, "start": 747, "end": 762, "probe_score": 0.9924, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "NBP", "label": "NAMED_DATA", "score": 0.5747954249382019, "start": 792, "end": 795, "probe_score": 0.9496, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Ukrstat", "label": "NAMED_DATA", "score": 0.7766139507293701, "start": 813, "end": 820, "probe_score": 0.9496, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " under the regional No Lost\nGeneration strategy. <sup>45</sup> The work also aligns with the national Child Protection Policy, developed by the\nMinistry of Education and Higher Education, in the form of its education personnel and psychosocial\nsupport counsellors. A combination of United Nations High Commissioner for Refugees (UNHCR), World\nHealth Organization (WHO), United Nations Children’s Emergency Fund (UNICEF) and others provide\nthese services to both refugees from Syrian and vulnerable Lebanese, while United Nations Relief and\nWorks Agency for Palestine Refugees United Nations Relief and Works Agency for Palestine\nRefugees (UNRWA) provides these services to Palestinian refugees.\n\n**Persons with Disabilities and Older Persons**\n\n\n20. **Conditions for persons with disabilities and Older Persons (OPs) had been deteriorating since 2019 as**\n**the compound crises affected these groups disproportionately.** <sup>46</sup> The POB explosion only exacerbated\nthese vulnerabilities further. In fact, at the end of 2019, the Ministry of Social Affairs – which had\npreviously delivered services to persons with disabilities – rescinded its support services due to budgetary\nshortages. In turn, civil society partners providing services to persons with disabilities and OPs recorded a\nsignificant increase in their Lebanese caseload over the course of 2020. <sup>47</sup> In late May 2020, a Rapid Needs\nAssessment conducted by HelpAge International in Beirut identified that 68% of people aged 50 and above\nhad at least one disability or impairment. <sup>48</sup> While reliable data quantifying the impact of the blast on these\nnumbers does not exist, an August 2021 Human Rights Watch investigation estimated that 150 people\n\n\n[41https://www.moph.gov.lb/userfiles/files/Mental%20Health%20and%20Substance%20Use%20Strategy%20for%20", "output": {"entities": {"named_data": ["Rapid Needs\nAssessment"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000002", "page": 8, "chunk": 1, "title": "Project Information Document - Support for Social Recovery Needs of Vulnerable Groups in Beirut - P176622", "pdf_url": "http://documents.worldbank.org/curated/en/113021634329877822/pdf/Project-Information-Document-Support-for-Social-Recovery-Needs-of-Vulnerable-Groups-in-Beirut-P176622.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Rapid Needs\nAssessment", "label": "NAMED_DATA", "score": 0.5602559447288513, "start": 1400, "end": 1422, "probe_score": 0.0014, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nremain in the informal sector. The higher\nbound is the product of employment rates\nfrom surveys of refugees from Ukraine,\nand their working age population from\nthe active PESEL UKR database. By JulyAugust 2023 Ukrainian refugee households\nsupported themselves, with 80% of their\nincomes coming from work. <sup>49</sup>\n\n##### We find that refugees from Ukraine as workers, entrepreneurs, consumers, and taxpayers had a positive impact on economic output, which will increase in the long run.\n\n\n\n49  Deloitte calculations based on Multi-Sector Needs Assessment Poland 2023 survey data provided by UNHCR.\n50  E.g. vice-president of Polish Development Found Bartosz Marczuk estimated it at around 16 billion PLN, but this estimation also included spending of\nNGOs which was combined with spendings of local governments <u>[Polska pomoc dla Ukrainy 2022 - ile kosztowała? - Infor.pl.](https://www.infor.pl/prawo/nowosci-prawne/5635962,Polska-pomoc-dla-Ukrainy-2022-ile-kosztowala.html)</u>", "output": {"entities": {"named_data": ["PESEL UKR database", "Multi-Sector Needs Assessment Poland 2023 survey data"], "descriptive_data": ["surveys of refugees from Ukraine"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 20, "chunk": 4, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "surveys of refugees from Ukraine", "label": "DESCRIPTIVE_DATA", "score": 0.9160913228988647, "start": 89, "end": 121, "probe_score": 0.9909, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PESEL UKR database", "label": "NAMED_DATA", "score": 0.8056085109710693, "start": 172, "end": 190, "probe_score": 0.9899, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Multi-Sector Needs Assessment Poland 2023 survey data", "label": "NAMED_DATA", "score": 0.7976388335227966, "start": 531, "end": 584, "probe_score": 0.9901, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "The analysis is performed separately for men and women as factors driving their educational <sup>14</sup> [^14: The data support the separate estimation of the regression equations for men and women. I estimated two base specifications of\nthe main regression equations with the dependent variable (DV) being “completed basic education or more” and “completed\nsecondary school or more” where I added interactions between the independent variables and the female dummy. I then used a\njoint F-test to evaluate whether the estimated coefficients on the interaction terms and the female dummy were equal to zero. The\ntest has rejected the equality of coefficients on the independent variables for men and women (DV: “completed basic education\nor more” - F(8, 67) = 4.07, p= 0.0005; DV: “completed secondary school or more” - F(8, 67) = 30.38, p=0.000). Therefore, all\nsubsequent regressions were estimated separately for men and women.]\n\n\nand employment experiences are very different in Tajikistan. In Equation (1) the main coefficient of\n\n\ninterest is γ2, or the interaction between the dummy variables for being of school age during the conflict\n\n\nand also living in the areas highly affected by conflict. By comparing the estimated coefficients for men\n\n\nand women it is possible to establish the gender specific impact of exposure to the conflict, while a\n\n\ncomparison of the coefficients across cohorts shows the cohort-specific impact. For example, the\n\n\nestimated coefficient on the cohort term will demonstrate whether the younger cohort achieved less\n\n\neducation than the older cohort or whether the cohort is more likely to be employed.\n\n\nThe correct estimation of Equation 1 is based on the following assumptions. First, in the absence\n\n\nof conflict activity in the exposed regions, all raions had a similar time trend and would have all been on\n\n\nthe same time trend after 1992 if the civil war had not occurred (parallel trend assumption). Second, there\n\n\nare no omitted time-varying and region", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004916", "page": 16, "chunk": 0, "title": "wps5738", "pdf_url": "https://local/prwp/wps5738.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " working refugees there is a\nsignificant number of entrepreneurs.\nThe high employment rate of refugees in\nPoland covers not only employees, but\nalso the self-employed. The available data\nalso shows that refugees from Ukraine\nin Poland are likely to start their own\nbusinesses. ZUS (social security) statistics\non insured refugees indicate that around\n5% of them have set up a business or are\nfreelancers. Similar results can be gleaned\nfrom the MSNA Poland 2023 survey results,\nwhich show that slightly more than 5% of\nrespondent households receive income\nfrom self-employment or similar activities.\nThis percentage appears to be slightly\nhigher for men, at over 6%, than women.\n\n\n\n\n\n30  Eurostat data, <u>https://ec.europa.eu/eurostat/databrowser/view/migr_asytpsm/default/table?lang=en</u>\n\n\n\n26 27", "output": {"entities": {"named_data": ["ZUS (social security) statistics\non insured refugees", "MSNA Poland 2023 survey results", "Eurostat data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 13, "chunk": 1, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "ZUS (social security) statistics\non insured refugees", "label": "NAMED_DATA", "score": 0.5030498504638672, "start": 277, "end": 329, "probe_score": 0.4385, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "MSNA Poland 2023 survey results", "label": "NAMED_DATA", "score": 0.6828482151031494, "start": 445, "end": 476, "probe_score": 0.7324, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Eurostat data", "label": "NAMED_DATA", "score": 0.7962659597396851, "start": 688, "end": 701, "probe_score": 0.0, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "THEMATIC SESSIONS\n\n\n⊲ Recommendations\n\n\n**1.** Sufficient multi-year funds need to be allocated and localised to ensure effective\n\nparticipation of displaced communities and the communities that host them. This\n\nalso includes the resources to facilitate feedback mechanisms of participatory\n\napproaches.\n\n\n**2.** NGOs need to continue to advocate for States to uphold the rights of IDPs.\n\n\n**3.** NGOs should ensure they build community resilience and leadership to enhance\n\nIDP participation in decision-making processes.\n\n\n**4.** Putting in place timely and appropriate feedback and accountability mechanisms is\n\nessential to ensure a participatory approach in all aspects of responding to IDP\n\nsituations.\n\n###### Promoting national responsibility for prevention, responses and solution to internal displacement: The value of laws and policies\n\n\nNational authorities are primarily responsible for the protection of internally displaced people and ensuring\n\nsupport is accessible to displaced and host communities. Furthermore, States have the responsibility to prevent,\n\nrespond to, and help solve displacement. However, this responsibility is a challenge with the limited capacity of\n\ninstitutions and limited funding. Various regional bodies have played a role in urging states to develop national\n\nlaws that are in line with the Guiding Principles on Internal Displacement, which has resulted in a number of\n\ncountries adopting policies and strategies to respond to internal displacement. For example, instruments such\n\nas the 2006 Great Lakes Protocol and the 2009 Kampala Convention are providing guidance for safeguarding\n\nthe rights of IDPs.\n\n\nResponding to internal displacement requires multi-stakeholder collaboration in order to sustain the\n\nprogrammes. Key-actors include the host and displaced communities, the local and national authorities and in\n\nsome instances non-state armed actors where displacement is a result of conflict. Reliable data on IDP numbers\n\nand increased information on their challenges and solutions are necessary to attain resources and develop\n\ntargeted programmes that are sufficient to meet the immediate and long-term needs of the communities. The\n\nrole of the State is at the core of all planning and implementation", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Reliable data on IDP numbers"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001325", "page": 18, "chunk": 0, "title": "UNHCR Annual Consultations with NGOs 2018 Report: Putting People First", "pdf_url": "https://reliefweb.int/attachments/cc4fb919-410a-35e4-a233-79a87d4311b6/2018%20Final%202018%20Rapporteur%20Report%20on%20the%20Annual%20Consultations%20with%20Non-Governmental%20Organisations_v4.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Reliable data on IDP numbers", "label": "VAGUE_DATA", "score": 0.5984074473381042, "start": 1948, "end": 1976, "probe_score": 0.0571, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\n**ANNEX 5: Natural Hazard Risk Analysis and DRM Activities**\n\n\n1. **South Sudan is highly susceptible to hydro-meteorological and climate-related hazards, but as**\n**detailed assessments and maps are largely missing, the understanding of hydro-meteorological hazards**\n**and their associated risks remains limited.** South Sudan is prone to both recurrent drought and flood events.\nSince independence in 2011, the country suffered severe droughts (2011, 2015) and floods (2014, 2017,\n2019) <sup>112</sup> with high numbers of casualties, displacement, and loss of livestock severely affecting people’s\nlivelihoods and the country’s development efforts. <sup>113</sup> Aggregated data sets based on global models <sup>114</sup> are\navailable for South Sudan (see figure 5.1), but more granular data regarding the frequency and intensity of\nnatural hazards; exposed assets (people, buildings, livestock, and so on); as well as the location of flood\nprotection infrastructure are largely missing, making it difficult to assess the level of protection or the need\nfor flood protection and disaster response measures at the local level. <sup>115</sup>\n\n\n**Figure 5.1. Population in South Sudan Exposed to River Flooding**\n\n\n_Source:_ Own map design, based on Fathom-Global (2019) and UNITAR (2019).\n\n\n2. **Climate change is expected to increase the likelihood and intensity of hydro-meteorological**\n**hazards.** Climate trend analyses show that since the mid-1970s summer rainfall decreased by 10−20 percent\nacross parts of the country <sup>116</sup> and droughts have become more", "output": {"entities": {"named_data": [], "descriptive_data": ["Aggregated data sets based on global models"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 90, "chunk": 0, "title": "South Sudan - Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/824121596765983121/pdf/South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Aggregated data sets based on global models", "label": "DESCRIPTIVE_DATA", "score": 0.711916983127594, "start": 771, "end": 814, "probe_score": 0.7576, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " défis humanitaires de la région sont : (i) le contexte sécuritaire qui s’est énormément dégradé en raison de la<br>recrudescence des conflits intercommunautaires; (ii) les mouvements forcés de population et les difficultés d’accès aux services sociaux de base ; (iii) une<br>augmentation des besoins humanitaires (Source :Profil humanitaire de la région de Mopti, février 2019).|La**région de Mopti** a été marquée par les conflits intercommunautaires et les actes de violence, y inclus les graves exactions de droit de l’homme, perpétrés contre<br>des civils qui ont poussé des milliers de personnes à se déplacer. Au 30 juin 2019, on compte 50 643 PDIs (49% d’hommes et 51% de femmes) dont 76% vivent avec<br>les communautés hôtes et 24% sur les sites spontanés, ainsi que 41 108 PDIs retournés (48% d’hommes et 52% de femmes), et 4 374 rapatriés du Burkina Faso, de<br>la Mauritanie et du Niger. L’insécurité alimentaire touche 8% de la population (soit 217 000 personnes). Près de 154 00 élèves n’ont pas accès à l’école dans la région<br>de Mopti en raison du nombre élevé d’écoles non fonctionnelles. Par ailleurs, 12,6% des localités disposent de CSCom (dans la localité) tandis", "output": {"entities": {"named_data": ["Profil humanitaire de la région de Mopti"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000661", "page": 0, "chunk": 5, "title": "Matrice d’analyse des risques de protection – Région de Mopti (Septembre 2019)", "pdf_url": "https://reliefweb.int/attachments/612d1fdf-fa43-4d80-9c2c-76ea55e36c43/annexe_2b_-_matrice_danalyse_des_risques_de_protection_-_mopti_-_version_finale.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Profil humanitaire de la région de Mopti", "label": "NAMED_DATA", "score": 0.7433203458786011, "start": 323, "end": 363, "probe_score": 0.9781, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000090", "page": 19, "chunk": 1, "title": "Albania - Emergency Road Repair Project", "pdf_url": "http://documents1.worldbank.org/curated/en/543691468740389779/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7292463183403015, "start": 272, "end": 283, "probe_score": 0.8771, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a gender officer and his/her role; whether the MLG\nhas a gender plan and budget; existence of any gender focused program or project in the MLG; citizens’ engagements, and the\nmonitoring and evaluation of gender activities; grievances mechanism; availability of gender documents, and gender gaps and how\nit could be addressed.\n53 funded by Ministry of Gender Labour and Social Development, Northern Uganda Social Action Fund (NUSAF 3), SWEGU and\nthe Local Governments.\n\n\n25", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000006", "page": 32, "chunk": 2, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents.worldbank.org/curated/en/143681526614252328/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " communicate with\ntheir families and host communities. As such, the Uganda Digital Acceleration Project (UDAP) will be laying\nan important foundation needed to enable digital services delivery from key development actors serving\nrefugees and RHDs. COVID-19 pressures have further highlighted the impact of this digital divide on\nrefugees. The need for information on fluctuating market prices, accessing mobile learning platforms, and\nsupporting MSMEs with information, finance and learning support have all increased within refugee\nsettlements which have seen periodic lock downs.\n\n\n**12.** **The growing amount of e-waste also presents challenges to the ICT sector.** A survey conducted by\nUNEP in 2017 <sup>45</sup> [^45: UNEP] demonstrate that the amount and flow of e-waste is rising fast with the estimated stock\nof e-waste at 1,900 MT. It has an estimated annual growth of 25,000 tons. A recent study has projected\nthat between 2018 and 2022, there will be an average of 4,500 tons per year of e-waste generated from\ncommunications end user equipment only (phones, televisions, computers and radios). <sup>46</sup> [^46: UNEP]\n\n**13.** **Uganda has put in place the legal, policy, strategic and technical foundations for cybersecurity**\n**resilience and is optimizing them, while shifting focus to next-stage good practices in governance,**\n**capacity building and steady-state sustainability.** With an increasing number of digital platforms\nand services being rolled out by Uganda’s public and private sectors and investments made into\nnetworks and applications, Uganda has prioritized the strengthening of its cybersecurity, information\nsecurity and data protection frameworks. In 2018, cyber-attacks cost the Ugandan economy an\nestimated US$52 million, up from US$42 million in 2017 and US$35 million in 2016. The most\naffected sectors are the Government sector,", "output": {"entities": {"named_data": [], "descriptive_data": ["survey conducted by\nUNEP in 2017"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000033", "page": 7, "chunk": 1, "title": "Project Information Document - Uganda Digital Acceleration Program - P171305", "pdf_url": "http://documents.worldbank.org/curated/en/630051615474731857/pdf/Project-Information-Document-Uganda-Digital-Acceleration-Program-P171305.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "survey conducted by\nUNEP in 2017", "label": "DESCRIPTIVE_DATA", "score": 0.8160179853439331, "start": 672, "end": 704, "probe_score": 0.4686, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Project Financing Data(in USD Million)**|. <br>**Project Financing Data(in USD Million)**|. <br>**Project Financing Data(in USD Million)**|. <br>**Project Financing Data(in USD Million)**|. <br>**Project Financing Data(in USD Million)**|. <br>**Project Financing Data(in USD Million)**|\n|[  ]<br>Loan|[ X ]<br>IDA Grant|[ X ]<br>IDA Grant|[  ]<br>Guarantee|[  ]<br>Guarantee|[  ]<br>Guarantee|[  ]<br>Guarantee|\n|[  ]<br>Credit|[  ]<br>Grant|[  ]<br>Grant|[  ]<br>Other|[  ]<br>Other|[  ]<br>Other|[  ]<br>Other|\n|Total Project Cost:|Total Project Cost:|40.00|40.00|Total Bank Financing:|Total Bank Financing:|40.00|\n|Financing Gap:|Financing Gap:|0.00|0.00||||\n\n\n.", "output": {"entities": {"named_data": [], "descriptive_data": ["Project Financing Data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000157", "page": 5, "chunk": 5, "title": "Burundi - Social Safety Nets Project", "pdf_url": "http://documents1.worldbank.org/curated/en/900951482030099834/pdf/1482030098559-000A10458-PAD-Burundi-SSN-11282016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Project Financing Data", "label": "DESCRIPTIVE_DATA", "score": 0.5741447806358337, "start": 0, "end": 22, "probe_score": 0.4885, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "** of potential resettlement cases remains\na challenge, with the exception of the enhanced\nresettlement of Congolese programme (under which\nCongolese refugees are identified in large numbers\nby their arrival dates, thus greatly facilitating the\nresettlement process). Inaccurate or lack of registration\ndata in some operations, and lack of capacity to carry\nout registration reverification exercises, continue\nto pose a challenge in the identification of potential\nresettlement cases and result in insufficient resettlement\nreferrals. This is a particular challenge on a large\ncontinent, where the majority of refugees are located\n\n\n1 \u0007In 2012 a group proposal for 10,000 Congolese refugees out of\nRwanda was approved by the USA. A second proposal for Rwanda is\nunder discussion.\n\n\n\nin remote camp locations or dispersed across urban\nareas. While resettlement identification and processing\nhas considerably improved where data re-verification\nexercises have taken place, such as in Rwanda (2012),\nBurundi (2013), Uganda (2012, 2013, 2015-2016),\nTanzania (2014), Djibouti (2014/2015), Chad (2015),\nand currently ongoing in Cameroon, much remains to\nbe done to increase data verification and to keep the\nalready collected data current. Systematic efforts have\nalready been undertaken to involve protection and other\nstaff as well as partners in strengthening identification\nmechanisms.\n\n\nResettlement from sub-Saharan Africa takes place\nin 36 countries, most with multiple processing sites.\nThe camps/settlements are often in remote locations\nfar from the capitals, resulting in considerable\n**logistical and access challenges** relating to travel,\nweather and sometimes security. In spite of all the\ninvestments already undertaken, the logistics around\nresettlement processing in Africa remains very resource\nintensive. In Tanzania, the future completion of the\nnew processing site in Makere (close to Nyarugusu\nCamp), generously funded by the USA, will alleviate\nsome of the aforementioned logistical difficulties.\nIn Kenya, Somali refugees from Dadaab camp will\ncontinue to be temporarily transported to Kakuma\ncamp for resettlement", "output": {"entities": {"named_data": [], "descriptive_data": ["registration\ndata"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001537", "page": 22, "chunk": 1, "title": "UNHCR Projected Global Resettlement Needs 2017", "pdf_url": "https://reliefweb.int/attachments/eee018b4-3938-3398-bbb8-4e2153fba0f4/575836267.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "registration\ndata", "label": "DESCRIPTIVE_DATA", "score": 0.8529685735702515, "start": 290, "end": 307, "probe_score": 0.0099, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " sector in each country is then the sum of all utilities’ subsidies in that country.\n\n\nNine countries represented in the IBNET database are estimated to have a negative subsidy. Most of these\nare developed countries, where efficiency may be pushed beyond the level assumed in the Chilean\nmodel. <sup>24</sup> Where this is the case, subsidies are assumed to be zero.\n\n\n**3.10 Estimating the subsidies for countries not in IBNET**\n\n\nTo extrapolate subsidy estimates to countries not included in the database, we first separate out China\nand India, while the remaining countries are grouped into four clusters—high income, upper middle\nincome, lower middle income, and low income—based upon the World Bank’s country classifications by\nincome for fiscal year 2019. Next, for water and sanitation separately, we calculate an average subsidy\nper person served for countries with representation in IBNET, disaggregated into the four clusters (see\nAppendix B). Then, for countries not in the IBNET database, we multiply the per person subsidy for its\ncluster by the total population served by the respective service (estimated by multiplying the country’s\ncoverage rate <sup>25</sup> [^25: Water and/or sanitation coverage data from the World Health Organization/United Nations Children’s Fund for 3 countries\n(Austria, Isle of Man, and Micronesia), in addition to the 6 previously cited with partial IBNET data, were incomplete, and were\nthus supplemented by additional data and estimates. Refer to Appendix B for details.] and its total population). Since the main drivers for these estimates are the unit cost in\nthe asset base calculations, the results presented in the report assume a +/-10 percent variation in the\nunit asset base estimates.\n\n\n22 China and India were not extrapolated due to low proportional representation in IBNET and a general lack of data availability.\n\n23 Water and/or sanitation coverage data for 6 countries (Bahrain, Fiji, Indonesia,", "output": {"entities": {"named_data": ["IBNET database"], "descriptive_data": ["Water and/or sanitation coverage data", "Water and/or sanitation coverage data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000381", "page": 14, "chunk": 2, "title": "estimating the magnitude of water supply and sanitation subsidies", "pdf_url": "https://local/prwp/estimating-the-magnitude-of-water-supply-and-sanitation-subsidies.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "IBNET database", "label": "NAMED_DATA", "score": 0.8409490585327148, "start": 121, "end": 135, "probe_score": 0.8305, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Water and/or sanitation coverage data", "label": "DESCRIPTIVE_DATA", "score": 0.6906128525733948, "start": 1183, "end": 1220, "probe_score": 0.7404, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Water and/or sanitation coverage data", "label": "DESCRIPTIVE_DATA", "score": 0.6302485466003418, "start": 1877, "end": 1914, "probe_score": 0.0375, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<br>|\n|Grievances responded and/or resolved<br>within the stipulated service standards for<br>response times (dis-aggregated by<br>gender, refugees, hosts)|<br>Percentage of grievances of<br>Project Affected People<br>responded and/or resolved<br>within the stipulated service<br>standards|Semi-<br>annually<br>|Environment<br>al and Social<br>Management<br>System<br>|Data compilation<br>|Monitoring and<br>evaluation consultants,<br>UNRA<br>|\n|Percentage increase in employment of<br>women (those in refugee camps of Bidi<br>Bidi, Lobule, and Palorinya)|Percentage increase in<br>women employment (those<br>in selected refugee camps)|six-<br>monthly<br>|Monitoring<br>reports<br>|Government data, M&E<br>reports<br>|Monitoring and<br>evaluation consultants,<br>UNRA<br>|\n|Number of women employed though<br>cooperatives supported by the project|Number of women<br>employed though<br>cooperatives supported by<br>the project|Semi-<br>annually<br>|Data<br>collected by<br>monitoring<br>and<br>evaluation<br>consultants<br>|surveys<br>|Monitoring and<br>evaluation consultants,<br>UNRA<br>|\n\n\nPage 57 of 80", "output": {"entities": {"named_data": [], "descriptive_data": ["Government data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 61, "chunk": 1, "title": "Uganda - Roads and Bridges in the Refugee Hosting Districts/Koboko-Yumbe-Moyo Road Corridor Project", "pdf_url": "http://documents.worldbank.org/curated/en/834931600048847296/pdf/Uganda-Roads-and-Bridges-in-the-Refugee-Hosting-Districts-Koboko-Yumbe-Moyo-Road-Corridor-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Government data", "label": "DESCRIPTIVE_DATA", "score": 0.6654642224311829, "start": 682, "end": 697, "probe_score": 0.6913, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", undermined trust in governmental institutions**\n**and increased existing pressures for emigration** . Even before the explosion, the fallout of the economic\ncrisis and the pandemic had led to a significant increase in poverty and a shrinking middle class. The Fall\n2021 LEM estimated that poverty rates have surged from 28% in 2019 to 55.3% in 2020. <sup>14</sup> [^14: Lebanon Economic Monitor, Fall 2020. World Bank.] As of Spring\n2021, projections using older data suggest that well over half of Lebanon’s population was under the\n\n\n5 Lebanon Economic Monitor, Spring 2021. World Bank.\n6 Lebanon Economic Monitor, Fall 2020. World Bank.\n7 Bank Byblos (February 2020) Lebanon This Week ‘Lebanon’s expats’ remittances drop by 20% in H1 of 2020 in Xinhuanet.\n8 Lebanon Economic Monitor, Spring 2021. World Bank.\n9 World Food Program (December 2020) Lebanon, VAM Update of Food Price and Market Trends.\n<u>[https://reliefweb.int/sites/reliefweb.int/files/resources/WFP-0000122981.pdf](https://reliefweb.int/sites/reliefweb.int/files/resources/WFP-0000122981.pdf)</u>\n10 <u>[https://www.unicef.org/lebanon/media/5616/file](https://www.unicef.org/lebanon/media/5616/file)</u>\n11 <u>[https://reliefweb.int/report/lebanon/vasyr-2020-key-findings-2020-vulnerability-assessment-syrian-refugees-lebanon](https://reliefweb.int/report/lebanon/vasyr-2020-key-findings-2020-vulnerability-assessment-sy", "output": {"entities": {"named_data": ["Fall\n2021 LEM", "Lebanon Economic Monitor"], "descriptive_data": [], "vague_data": ["older data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000002", "page": 3, "chunk": 2, "title": "Project Information Document - Support for Social Recovery Needs of Vulnerable Groups in Beirut - P176622", "pdf_url": "http://documents.worldbank.org/curated/en/113021634329877822/pdf/Project-Information-Document-Support-for-Social-Recovery-Needs-of-Vulnerable-Groups-in-Beirut-P176622.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Fall\n2021 LEM", "label": "NAMED_DATA", "score": 0.6262965798377991, "start": 262, "end": 275, "probe_score": 0.9986, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Lebanon Economic Monitor", "label": "NAMED_DATA", "score": 0.5205308794975281, "start": 372, "end": 396, "probe_score": 0.999, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "older data", "label": "VAGUE_DATA", "score": 0.5176940560340881, "start": 459, "end": 469, "probe_score": 0.9909, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "addition, participating households consumed more and better quality food after receiving the transfer and\n60 percent of the beneficiaries were able to keep more of the food they produced for their own\nconsumption. The Malawi Cash Transfer Program also showed improvement in food consumption where\n93 percent of the intervention households reported improved food consumption. In addition, in Malawi\nand Zambia, the transfer also increased dietary diversity and number of meals consumption per day. In\nMalawi, average meals per day among beneficiaries significantly increased from 1.5 meals per day for\nchildren and adults at baseline to an average of 2.4 meals per day meals per day. In addition, impact\nevaluations from these programs also suggest that UCTs can be appropriate responses to acute food crisis;\nlong term cash transfers as part of a social protection strategy are feasible and help to alleviate chronic\npoverty and increase the resilience of households to deal with periodic shocks.\n\n\n221. **Education benefits.** UCT programs in South Africa, Malawi and Zambia show a positive impact\non education. In Zambia and South Africa, the largest impacts indentified on enrollment rates concern\nvery young children, suggesting that improved nutrition and health may have increased school attendance.\nEvidence from the Zambia scheme shows that between the baseline data and program evaluation, school\nenrollment for children between the ages of 5-1 **8** increased significantly with the largest increase between\n\n14-15 years. In terms of gender disparities, girls were disadvantaged compared to the boys, indicating\nthat with a low transfer level, parents often send only one child and it is usually a boy. The Malawi\nprogram provided a protective function with respect to schooling: after one year, children in beneficiary\nhouseholds had doubled their enrollment rates compared to comparison households, with drop rates half\nas large as children in comparison households. The beneficiary group also had fewer school absences per\nmonth.\n\n\n222. **Expected benefits from the Beneficiary Development Program.** _Component_ **2** of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000080", "page": 74, "chunk": 0, "title": "Yemen, Republic of - Social Welfare Fund Institutional Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/495501468170077604/pdf/533550PAD0P117101Official0Use0Only1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "baseline data", "label": "VAGUE_DATA", "score": 0.6409826874732971, "start": 1361, "end": 1374, "probe_score": 0.9372, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nGreater Beirut Public Transport Project (P160224)\n\n\nThe ESIA was prepared based on the feasibility study, and therefore some variations in the scope of\nactivities might occur once final designs are furnished. The CDR committed that site-specific ESMPs\n(additional ESMPs) will be prepared as part of the final design packages to cater for mitigation of any\nunwarranted impacts that might arise. In addition, the CDR committed to employing the World Bank\nsafeguards policies (or equivalent) for the activities carried out in parallel to the BRT system, particularly\nthe A1 highway.\n\n\n104. **Two stakeholder consultations rounds were carried out during the ESIA preparation.** The first\nconsultation was held during the scoping phase of the ESIA on January 19, 2017, and the second\nconsultation was held once a final draft ESIA was furnished on September 7, 2017. The consultations\nrounds were announced publicly in the media and attended by concerned authorities including the\nLebanese Ministry of Environment, academia, NGOs, and the public. The ESIA report (with executive\nsummary in Arabic and English) have been disclosed in country on October 20, 2017 (on the CDR website)\nand are available as hard copies at the premises of the CDR. The final ESIA report has also been disclosed\non the World Bank’s external website on October 24, 2017.\n\n\n105. **The ESIA indicated that the project will result in positive impacts on air quality, reduced GHG**\n**emissions, and reduced noise levels once the BRT system is fully operational.** The ESIA studied the\ndifferent atmospheric emissions resulting from the operation of the transportation fleet with and without\nthe BRT system in the project influence zone, for 2023. The study consisted of assessing the future\nincremental emissions due to the project while considering the anticipated change in traffic circulation\nand modal shares due to the operation of the BRT system. The comparison of the two scenarios resulted", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000022", "page": 44, "chunk": 0, "title": "Lebanon - Greater Beirut Public Transport Project", "pdf_url": "http://documents.worldbank.org/curated/en/471241521338566907/pdf/PAD-final-02262018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " data. Based on the MultiSector Needs Assessment Poland 2023\nsurvey conducted in July-August 2023, we\ncalculate that 80% of the income of refugee\nhouseholds is derived from employment,\nwith an additional 5% coming from\nremittances and 2% from Ukrainian pension\nbenefits. In economic terms, refugees\nfrom Ukraine in Poland are not receivers\nof social services and charity, but primarily\nconsumers, employees, and entrepreneurs.\n\n\nIn Chapter 3, we estimate the economic\nimpact of refugees from Ukraine in Poland\nin general equilibrium Deloitte D.Climate\nmodel. This is the gold standard of\neconomic modelling on the macro-level,\nwhich comprehensively accounts for the\nsupply side of the economy including\nlabour supply and productivity, and the\ndemand side including consumption\nas well as taxation. Unfortunately, such\nmacroeconomic models cannot account for\nhow exactly refugees and other migrants\nenable native workers to specialise in\nbetter paid professions (occupational\nupgrading), or how firms allow for new\nskills by adapting different production\ntechnologies. As such, our estimates\nshould be treated as a conservative lower\nbound of the effect.\n\n\n\nFurthermore, in Chapter 4, we move\nbeyond theoretical modelling, to examine\nempirical studies on how immigrants\nand refugees impact not just output, but\nlabour productivity as well. This effect\ncomes not from traditional supply-demand\nanalysis, but from increased specialisation.\nImmigrants enable occupational upgrading\nof residents, supply new skills to firms,\nenter household works services that allow\nhighly productive native women to increase\nlabour supply, and exhibit high rates of\nentrepreneurship.", "output": {"entities": {"named_data": ["MultiSector Needs Assessment Poland 2023\nsurvey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 5, "chunk": 1, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "MultiSector Needs Assessment Poland 2023\nsurvey", "label": "NAMED_DATA", "score": 0.908876359462738, "start": 20, "end": 67, "probe_score": 0.9999, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### 1.8 11\n\n\n\nCurrent account balance . **.2**\n\n\n\nFinancing items (net)\nChanges in net reserves .. .\n_Memo:_\nReserves including gold _(US$ millions)_\nConversion rate _(DEC, locaW/US$)_ 177.7 177.7 177.7\n\n\n**EXTERNAL DEBT and RESOURCE FLOWS**\n\n**1979** **1989** **1998** **1999**\n_(US$ millions)_ **Compositlon of total debt, 1998 (USS milIlona)**\nTotal debt outstanding and disbursed 26 **179** 288\nIBRD 0 0 0\nIDA 0 26 50 49 G 15 B\n\nTotal debt service 2 15 6\nIBRD 0 0 0 C: 9\nIDA 0 0 1 1\n\nComposition of net resource flows E: 119\nOfficial grants 5 32 48\nOfficial creditors -1 3 2\nPrivate creditors 0 -1 0\nForeign direct investment 0 0 6 D: **95**\nPortfolio equity 0 0 0\n\nWorld Bank program\n\nCommitments 0 9 3 A  - IBRD E - Bilateral\nDisbursements 0 2 2 1 B - IDA D - Other rrultilateral F **-** Private\nPrincipal repayments 0 0 0 0 C- IMF G - Short-term\nNet flows 0 2 2 1\nInterest payments 0 0 0 0\nNet transfers 0 2 1 1\n\n\nNote: This table was produced from the Development Economics central database. 9/13/00", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000049", "page": 63, "chunk": 1, "title": "Croatia - Reconstruction Project for Eastern Slavonia, Baranja and Western Srijem", "pdf_url": "http://documents1.worldbank.org/curated/en/347691468746725804/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9087857007980347, "start": 960, "end": 998, "probe_score": 0.6996, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "/data2.unhcr.org/en/situations/ukraine](https://data2.unhcr.org/en/situations/ukraine)</u>\n\n\n14\n\n\n\n**Source:** Deloitte own elaboration based on the results of the MSNA Poland 2023 survey\n\n\n\n15", "output": {"entities": {"named_data": ["MSNA Poland 2023 survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 7, "chunk": 3, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "MSNA Poland 2023 survey", "label": "NAMED_DATA", "score": 0.9333467483520508, "start": 164, "end": 187, "probe_score": 0.9996, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nIntegrated Cash Transfer and Human Capital Project (P166220)\n\n\n\n\n\n\n\n|Project<br>Beneficiaries of Safety Nets programs<br>Quarterly administrativ Routine monitoring SEAS<br>- Other cash transfers programs<br>e data<br>(number)|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|Beneficiary women with a child aged 0-6<br>months practicing exclusive breastfeeding<br>Percentage of beneficiary<br>women with a child aged 0-<br>6 months who participate in<br>community sessions<br>Twice<br> <br>Survey<br> <br>Survey at middle and<br>end of project<br> <br>SEAS<br>|Beneficiary women with a child aged 0-6<br>months practicing exclusive breastfeeding<br>Percentage of beneficiary<br>women with a child aged 0-<br>6 months who participate in<br>community sessions<br>Twice<br> <br>Survey<br> <br>Survey at middle and<br>end of project<br> <br>SEAS<br>|Beneficiary women with a child aged 0-6<br>months practicing exclusive breastfeeding<br>Percentage of beneficiary<br>women with a child aged 0-<br>6 months who participate in<br>community sessions<br>Twice<br> <br>Survey<br> <br>Survey at middle and<br>end of project<br> <br>SEAS<br>|Beneficiary women with a child aged 0", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000063", "page": 35, "chunk": 0, "title": "Djibouti - Integrated Cash Transfer and Human Capital Project", "pdf_url": "http://documents1.worldbank.org/curated/en/419881558381476102/pdf/Djibouti-Integrated-Cash-Transfer-and-Human-Capital-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Decision Note)**|<br>**Safeguards Deferral (from Decision Review Decision Note)**|<br>**Safeguards Deferral (from Decision Review Decision Note)**|<br>**Safeguards Deferral (from Decision Review Decision Note)**|\n|Will the review of Safeguards be deferred?  [  ]  Yes     [ X ]   No|Will the review of Safeguards be deferred?  [  ]  Yes     [ X ]   No|Will the review of Safeguards be deferred?  [  ]  Yes     [ X ]   No|Will the review of Safeguards be deferred?  [  ]  Yes     [ X ]   No|Will the review of Safeguards be deferred?  [  ]  Yes     [ X ]   No|Will the review of Safeguards be deferred?  [  ]  Yes     [ X ]   No|Will the review of Safeguards be deferred?  [  ]  Yes     [ X ]   No|Will the review of Safeguards be deferred?  [  ]  Yes     [ X ]   No|Will the review of Safeguards be deferred?  [  ]  Yes     [ X ]   No|Will the review of Safeguards be deferred?  [  ]  Yes     [ X ]   No|Will the review of Safeguards be deferred?  [  ]  Yes     [ X ]   No|Will the review of Safeguards be deferred?  [  ]  Yes     [ X ]   No|Will the review of Safeguards be deferred?  [  ]  Yes     [ X ]   No|Will the review of Safeguards be deferred?  [  ]  Yes     [ X ]   No|Will the review of Safeguards be deferred?  [  ]  Yes     [ X ]   No|Will the review of Safeguards be deferred?  [  ]  Yes     [ X ]   No|\n|**Project Financing Data(in US$ Million)**|**Project Financing Data(in US$ Million)**|**Project Financing Data(in US$ Million)**", "output": {"entities": {"named_data": [], "descriptive_data": ["Project Financing Data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000139", "page": 6, "chunk": 3, "title": "Lebanon - Emergency National Poverty Targeting Program Project", "pdf_url": "http://documents1.worldbank.org/curated/en/810511467987899324/pdf/PAD1030-ENGLISH-P149242-PUBLIC-FINAL-LEB-ENPTP-English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Project Financing Data", "label": "DESCRIPTIVE_DATA", "score": 0.5604020357131958, "start": 1323, "end": 1345, "probe_score": 0.7359, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "ant Selection|Open - National||20,000.00|0.00|Under Implement<br>ation|2024-12-05|2024-12-23|2025-01-08||2025-01-18||2025-02-17||2027-02-07||\n|ET-NIDP-461785-CS-INDV / H<br>iring of Brand and Event Coor<br>dinator for NIDP|IDA / 74630|Building institutions and trus<br>t|Post|Individual Consult<br>ant Selection|Open - National||20,000.00|0.00|Under Implement<br>ation|2024-12-05|2024-12-23|2025-01-08||2025-01-23||2025-02-12||2027-02-02||\n|ET-NIDP-461786-CS-INDV / H<br>iring of Legal Specialist for NI<br>DP|IDA / 74630|Building institutions and trus<br>t|Post|Individual Consult<br>ant Selection|Open - National||20,000.00|0.00|Under Implement<br>ation|2024-12-05|2025-02-15|2025-01-08||2025-01-18||2025-02-11||2027-02-01||\n|ET-NIDP-461788-CS-INDV / H<br>iring of Junior Lawyer for NID<br>P|IDA / 74630|Building institutions and trus<br>t|Post|Individual Consult<br>ant Selection|Open - National||20,000.00|0.00|Pending Impleme<br", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:001274", "page": 5, "chunk": 2, "title": "Ethiopia - EASTERN AND SOUTHERN AFRICA- P179040- Ethiopia Digital ID for Inclusion and Services Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099031026100011486/pdf/P179040-ef62d53a-1e16-4cab-b48b-6db136862da2.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "136. To address the shortcomings of the cash transfer cycle as identified above, **_Sub-component_** _1.1_\nwill support the services of a long-term advisor to assist SWF to develop and test procedures for each step\nof the cycle. The long-term advisor will provide “hands-on” training and further development of the\nOperations Manual and its technical annexes as required. All 1,600 SWF staff (at all three levels) will be\ntrained in the cash transfer procedures and processes specific to their area of responsibility by technical\nexperts identified by the long-term advisor. Study tours as well as exchange visits with other relevant\ncountries would be implemented.\n\n\n137. An essential cash transfer program component as identified in the cash transfer cycle above is a\nresponsive MIS that links data entered at the district, governorate and head office to program operations.\nAn effective MIS would provide up-to-date information for case management (e.g., beneficiaries\nrequiring recertification, etc.) as well as information for managers on the status of program elements, such\nas applications, enrolments, payments, recertifications, and beneficiary development program\nparticipation. At the present time, the existing MIS system does not receive inputs from operations\ndepartments, highlighting the lack of connection between all cash transfer operations and the IT system.\n\n\n138. The sub-component provides the services of an MIS expert to put an effective MIS in place\nmodule by module. Training for all program staff will cover every aspect of the SWF data collection,\ninput, application of the PMT, analysis and utilization of results, and reporting. An MIS manual would be\n\n\n40", "output": {"entities": {"named_data": [], "descriptive_data": ["SWF data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000080", "page": 45, "chunk": 0, "title": "Yemen, Republic of - Social Welfare Fund Institutional Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/495501468170077604/pdf/533550PAD0P117101Official0Use0Only1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "SWF data", "label": "DESCRIPTIVE_DATA", "score": 0.5911371111869812, "start": 1556, "end": 1564, "probe_score": 0.0284, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " NPTP|Component 1: Administration of the NPTP|Component 1: Administration of the NPTP|Component 1: Administration of the NPTP|Component 1: Administration of the NPTP|Component 1: Administration of the NPTP|3.89|3.89|3.89|3.89|3.89|\n|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|3.76|3.76|3.76|3.76|3.76|\n|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|0.55|0.55|0.55|0.55|0.55|\n|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|", "output": {"entities": {"named_data": [], "descriptive_data": ["Institutional Data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000139", "page": 6, "chunk": 13, "title": "Lebanon - Emergency National Poverty Targeting Program Project", "pdf_url": "http://documents1.worldbank.org/curated/en/810511467987899324/pdf/PAD1030-ENGLISH-P149242-PUBLIC-FINAL-LEB-ENPTP-English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Institutional Data", "label": "DESCRIPTIVE_DATA", "score": 0.5252237915992737, "start": 1208, "end": 1226, "probe_score": 0.2474, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "53. Under the Uganda rainfall condition, the frequency of flooding in most municipalities is between\n10 to 15 times in a year lasting 3 to 4 hours per flooding. Private and commercial vehicles are disrupted\nleading to loss of time and income. Improved drainage also leads to improvements to the environment and\nhealth benefits from reduced incidence of water borne disease. The internal rate of return obtained in\nprevious studies in similar environments was used to estimate the stream of benefits generated by improved\ndrainage. The EIRR of drainage under USMID was calculated at 6%.\n\n**Increase in Property Values**\n\n54. Improvements in urban roads in all the municipalities sampled has led to increases in value of\nproperties (land, buildings) and rental prices of properties in the adjacent areas of the constructed roads\nranging from 20% to 100% as per the table below. In Hoima municipality, the sharp increase in both rent\nand land values can also be attributed to speculations about oil extraction impact on the local economy.\n\n**Table 9: Changes in Rent and Land values**\n\n\n**Employment Creation**\n\n55. Construction of urban roads created direct and indirect jobs during construction. However, most of\nthe urban road infrastructure projects visited had been completed or partially completed. It was only\nNyakana road in Fort Portal where construction was still ongoing and therefore data on employment was\nobtained. The construction of Nyakana road in Fort Portal with a length of 0.94km, was directly employing\n56 workers out of which, 10% were highly skilled, 10% were skilled and 80 % unskilled. The highly skilled\nworkers, skilled workers and unskilled workers were earning UGX35,000, UGX25,000 and UGX12,000\nper day respectively. The construction of the road was also indirectly employing approximately 70 workers.\nThe construction of the road was expected to last for one year and three months.\n\n56. It can therefore be estimated from this data that construction of one kilometer creates", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on employment"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000062", "page": 69, "chunk": 0, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents.worldbank.org/curated/en/946901526654169395/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data on employment", "label": "VAGUE_DATA", "score": 0.6891720294952393, "start": 1393, "end": 1411, "probe_score": 0.4287, "gold": "NON_MENTION", "gold_tier": "human-final"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "distributional effect of higher poverty (Proposition 2). Which effect dominates is an empirical\n\n\nquestion.\n\n###### **4. Data and descriptive statistics**\n\nIn keeping with the bulk of the literature, the country is the unit of observation. <sup>15</sup> [^15: It is known that aggregation can hide the true relationships between the initial distribution and growth,\ngiven the nonlinearities involved at the micro level (Ravallion, 1998); identifying the deeper structural relationships\nwould require micro data, and even then the identification problems can be formidable.]\n\n\nHowever, unlike past data sets in the literature on growth empirics, this one is firmly anchored to\n\n\nthe household surveys, in keeping with the focus on the role played by poverty and inequality,\n\n\nwhich is measured from surveys. By calculating the poverty and inequality statistics directly\n\n\nfrom the primary data, at least some of the comparability problems found in existing data\n\n\ncompilations from secondary sources can be eliminated. However, there is no choice but to use\n\n\nhousehold consumption or income, rather than the theoretically preferable concept of wealth.\n\n\nI found almost 100 developing and transition countries with at least two suitable\n\nhousehold surveys since about 1980. Virtually all of the surveys are nationally representative. <sup>16</sup> [^16: The only exception was that urban surveys were also used (for both the first and last survey) for Uruguay\nwhere over 90% of the population lives in urban areas. Results were robust to dropping these urban surveys.]\n\n\nFor the bulk of the analysis I restrict the sample to the 90 countries in which the earliest available\n\n\nsurvey finds that at least some households lived below the average poverty line for developing\n\ncountries (described below). <sup>17</sup> [^17: The data set was constructed from _<u>[PovcalNet](http://econ.worldbank.org/povcalnet)</u>_ in December 2008.]", "output": {"entities": {"named_data": ["PovcalNet"], "descriptive_data": ["household surveys", "household surveys"], "vague_data": ["micro data", "primary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004168", "page": 10, "chunk": 0, "title": "wps4974", "pdf_url": "https://local/prwp/wps4974.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "micro data", "label": "VAGUE_DATA", "score": 0.6074279546737671, "start": 500, "end": 510, "probe_score": 0.4718, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "household surveys", "label": "DESCRIPTIVE_DATA", "score": 0.7932275533676147, "start": 682, "end": 699, "probe_score": 0.8781, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "primary data", "label": "VAGUE_DATA", "score": 0.5186811685562134, "start": 880, "end": 892, "probe_score": 0.8951, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "household surveys", "label": "DESCRIPTIVE_DATA", "score": 0.5828154683113098, "start": 1237, "end": 1254, "probe_score": 0.3453, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "PovcalNet", "label": "NAMED_DATA", "score": 0.8764424920082092, "start": 1859, "end": 1868, "probe_score": 0.9991, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "org/en/documents/details/104427 )</u>\n\n\nUrban M. (2022). Refugees will lift economy's potential, but challenges remain,\nResearch Briefing | Poland. Oxford Economics, <u>[https://www.oxfordeconomics.](https://www.oxfordeconomics.com/wp-content/uploads/2022/05/Poland-Refugees-will-lift-economys-potential-but-challenges-remain.pdf)</u>\n<u>[com/wp-content/uploads/2022/05/Poland-Refugees-will-lift-economys-](https://www.oxfordeconomics.com/wp-content/uploads/2022/05/Poland-Refugees-will-lift-economys-potential-but-challenges-remain.pdf)</u>\n<u>[potential-but-challenges-remain.pdf](https://www.oxfordeconomics.com/wp-content/uploads/2022/05/Poland-Refugees-will-lift-economys-potential-but-challenges-remain.pdf)</u>\n\n\n45\n\n\n\nD’Amuri, F., & Peri, G. (2014). Immigration, jobs, and employment protection:\nevidence from Europe before and during the great recession. Journal of the\nEuropean Economic Association, 12(2), 432-464.\n\n\nDeloitte (2023), Ukraine Refugee Pulse report, <u>[https://www2.deloitte.com/pl/pl/](https://www2.deloitte.com/pl/pl/pages/zarzadzania-procesami-i-strategiczne/articles/Ukraine-Refugee-Pulse-report", "output": {"entities": {"named_data": ["Ukraine Refugee Pulse report"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 22, "chunk": 3, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Ukraine Refugee Pulse report", "label": "NAMED_DATA", "score": 0.7448049187660217, "start": 945, "end": 973, "probe_score": 0.0902, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Second, we have information on each parcel’s mode of acquisition (inherited, purchased, or leased). As\n\nland markets are very inactive, the majority (3,814) of households cultivate only land they inherited. In\n\naddition to estimating relevant equations for the entire sample, we can thus restrict our sample to include\n\nonly these households for whom levels of fragmentation are exogenous and not affected by household\n\ndecisions, to avoid concerns about endogeneity.\n\n\nFinally, we have detailed information on inputs, including hired and family labor and machinery as well\n\nas outputs by parcel in each season. Amounts of own and hired male, female, and child labor are reported\n\nby activity, i.e. for land preparation, sowing/transplanting, weeding, fertilizer application, pest control,\n\nirrigation, harvesting separately. We value them using wage rates from the village survey. Cost of own or\n\nhired machinery and bullocks is computed using the village level rental rate. Home produced seed is\n\nvalued using market or village-level prices. Irrigation charges include water and non-labor operating cost\n\ni.e. electricity and fuel for canal or bore wells. Total output value is calculated by aggregating the value\n\nacross the parcels and crops for each household.\n\n\nTable 1 illustrates that average holding size in the sample is 4.5 acres in 3.2 parcels (1.7 ac./parcel), with a\n\nSimpson index of 0.47 and an average parcel-parcel distance of 858 m that takes some 18 min to traverse.\n\nThese measures vary across states but are only weakly correlated with each other. For example, relatively\n\nlarge holdings are not necessarily more fragmented, as indicated by the example of Gujarat where holding\n\nsize is about 6 ac. but, with an average of 1.16 parcels and a Simpson index of 0.07, fragmentation is low.\n\nWith 1.3 km on average, mean parcel-homestead distances are nevertheless quite large. By", "output": {"entities": {"named_data": [], "descriptive_data": ["village survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006177", "page": 10, "chunk": 0, "title": "wps7085", "pdf_url": "https://local/prwp/wps7085.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "village survey", "label": "DESCRIPTIVE_DATA", "score": 0.8962422609329224, "start": 866, "end": 880, "probe_score": 0.958, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad Energy Access Scale Up Project (P174495)\n\n\n**ANNEX 3: Gender Gap Analysis**\n\n\n\n**Rationale: Why a Focus on Gender in Energy Matters**\n\n1. Access to reliable household energy, clean and efficient cookstoves, or productive-use equipment\ncan reduce energy poverty and time spent on drudgery and give women and men additional incomeearning opportunities. In Chad, some key elements to consider include the following:\n\n\n\n(a) **Distribution of household heads.** About 22.1 percent of households in Chad are headed by\n\n\n\nfemales. The share is slightly higher in urban areas in general (23.6 percent); it is lower in\nN'Djamena (19.3 percent), <sup>43</sup> [^43: The data on the distribution of household heads were updated by a survey on ability and willingness of households to pay for\nelectricity services, completed in 2021. Details are provided in annex 6.] as detailed in Table 3.1. However, the project target with respect to\nelectrification of female-headed households is set at 15 percent according to more recent data\non the share of female-headed households in Chad that are provided in annex 6.\n\n\n\n\n\n|Location|Male (%)|Female (%)|\n|---|---|---|\n|<br>Nationwide<br>|<br>78.0<br>|<br>22.1<br>|\n|<br>Urban<br>|<br>76.5<br>|<br>23.6<br>|\n|<br>Rural<br>|<br>78.4<br>|<br>21.6<br>|\n|<br>N’Djamena<br>|<br>80.7<br>|<br>19.3<br>|\n\n\n(b)", "output": {"entities": {"named_data": [], "descriptive_data": ["data\non the share of female-headed households in Chad"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 76, "chunk": 0, "title": "Chad - Energy Access Scale Up Project", "pdf_url": "http://documents.worldbank.org/curated/en/860701648216750651/pdf/Chad-Energy-Access-Scale-Up-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data\non the share of female-headed households in Chad", "label": "DESCRIPTIVE_DATA", "score": 0.5343268513679504, "start": 1040, "end": 1093, "probe_score": 0.841, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "HDs. To increase digital inclusion of RHDs and refugees, the\ncomponent will extend national backbone connectivity, with the needs of last-mile connectivity in refugee\nsettlements and hosting communities determined in close collaboration with humanitarian agencies. This will\naddress both supply-side and demand-side connectivity needs, with the work carried out in close implementation\narrangements with humanitarian organizations.\n\n**Economic and Financial Analysis**\n\n**72.** **The project is expected to generate significant positive socioeconomic and financial impacts through long-**\n**term public cost savings, efficiency, and productivity gains, fueled by greater digital adoption, expansion of e-**\n**services, and digitally enabled innovation.** Improved accessibility and affordability of broadband services will\nresult in a more dynamic digital sector and will fuel the ability of Uganda’s innovator to develop new solutions to\nserve both local and international markets. Increased digitalization of government services that could be delivered\nin a cashless and paperless manner are expected to generate cost and time savings for both the general population\nand refugee host communities. By contributing to clean environmental practices, the improvements to e-waste\nmanagement practices will further make Uganda an even more attractive destination for tourists. Support to\nrefugee communities with enhanced skills and opportunity/job pathways are expected to generate employment\nand productivity gains.\n\n**73.** **The economic and financial analysis undertaken follows a standard Cost-Benefit Analysis (CBA)**\n**methodology.** However, the novelty of several components (particularly those related to addressing the needs of\nrefugee host communities) as well as data limitations in other areas, constrained an accurate estimation of the\nexpected economic and financial returns of this project. The model relies on available secondary data and\nreasonable assumptions based on experience and additional evidence from consultations and interviews\nconducted during project preparation. The model includes adjustments for COVID-19-related shocks in GDP and\noverall digitalization of service delivery to run the cash flow", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["secondary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000023", "page": 40, "chunk": 1, "title": "Uganda - Digital Acceleration Project", "pdf_url": "http://documents.worldbank.org/curated/en/473041622944887337/pdf/Uganda-Digital-Acceleration-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "secondary data", "label": "VAGUE_DATA", "score": 0.7729973793029785, "start": 1935, "end": 1949, "probe_score": 0.5328, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "DJIBOUTI\nSchool Access and Improvement Program\n\n\n**Project Appraisal Document**\n\n\nMiddle East and North Africa Region\n\nMNSHD\n\n\n\nDate: November 17, 2000 Team Leader: Qaiser M. Khan\n\n\n\nCountry Director: Inder K. Sud Sector Director: Baudouy\nProject **ID:** P044585 Sector(s): EP - Primary Education, ES - Secondary\n\n\n\n. Education\nLending Instrument: Adaptable Program Loan <sup>(APL)</sup> Theme(s): Education; Gender and development\n\n\n\nPoverty Targeted Intervention: N\n\n\n\nProgram Fin ncing Data\n\n\n\nEstimated\nAPL Indicative Financing Plan Implementation Period (Bank FY) Borrower\n\n\n\n**IBRD** Others **Total** **COMMITMENT** **Closing**\n**US$** m % US$ m US$ m Date Date\nAPL 1 10.00 75.8 3.20 13.20 03/31/2001 06/30/2005 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\n________________ Education\n\n\n\nAPL 2 10.0 65.8 5.20 15.20 07/01/2005 06/30/2008 Republic of\n\n\n\nLoan/ Credit Djibouti\n\n\n\nCredit Ministry of\n\n\n\ni_________ ________________ Education\n\n\n\nAPL 3 10.00 41.0 14.40 24.40 07/01/2008 06/30/2011 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\nEducation\n\n\n\nTotal 30.00 22.80 52.80\nProject Financing Data Credit\nFor Loans/Credits/Others: Amount (US$m): 10.0\n\n\n\nProposed Terms: Standard Credit\n\n\n\nGrace period (years): 10 Years to maturity: 40\nCommitment fee: 0.50% (0% for FY01) Service charge: 0.75", "output": {"entities": {"named_data": ["Project Financing Data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015217", "page": 4, "chunk": 0, "title": "Uganda - Second Economic and Financial Management Project", "pdf_url": "https://documents.worldbank.org/curated/en/588481468779155929/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Project Financing Data", "label": "NAMED_DATA", "score": 0.5102046728134155, "start": 1106, "end": 1128, "probe_score": 0.1169, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " World\nBank/MDTF-financed PFS, which uses a combination of geographic targeting, community-based\ntargeting, and proxy means testing (PMT), with some filters mainly related to the presence of\nchildren below 12 years and pregnant women. <sup>21</sup> [^21: For more details on the targeting methodology, see Supplemental Attachments, Targeting Methodology available in the project\nfile.] The project will rely on the refugee household\ndata collected by WFP and UNHCR in August 2017 using tools closely aligned with the CFS\nharmonized questionnaire. The targeting methodology will be tested to ensure its applicability to\nrefugees and adapted as needed. Moreover, these activities will be complemented by a strong\ncommunications campaign designed in partnership with humanitarian agencies to ensure that the\nprogram is seen as fair to both refugees and host communities.\n\n30. **Sub-component 2.1 aims to increase households’ consumption for a period of two**\n**years.** Regular small cash payments will enable beneficiaries to stabilize their general household\nconsumption levels. Cash transfers will be delivered on a quarterly basis in full alignment with\nthe ongoing PFS, implemented by the _Cellule Filets Sociaux_, which is already delivering cash\ntransfers to 6,200 households in Logone Occidentale and Bahr-El-Ghazel (in addition to managing\na cash-for-work program in N’Djamena). Households will be added to the program on a gradual\nbasis throughout with three consecutive rounds of interventions starting in the East, moving to the\nSouth after one year, and then to the Lake region. The cash transfers will be accompanied by\nmeasures being developed under the PFS to improve human development indicators, with a focus\non early childhood development.\n\n31. **Sub-component 2.2 (US$5.2 million equivalent) will seek to increase household**\n**resilience and self-reliance** **in targeted areas through small grants to selected households to**\n**support productive and climate-smart income-generating activities**", "output": {"entities": {"named_data": [], "descriptive_data": ["refugee household\ndata"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000035", "page": 22, "chunk": 1, "title": "Chad - Refugees and Host Communities Support Project", "pdf_url": "http://documents.worldbank.org/curated/en/658761536982256019/pdf/PAD2809-PAD-PUBLIC-disclosed-9-12-2018-IDA-R2018-0286-1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "refugee household\ndata", "label": "DESCRIPTIVE_DATA", "score": 0.8861410617828369, "start": 415, "end": 437, "probe_score": 0.3297, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 12.** Structure by occupational group of all employed persons and refugees from Ukraine\n\n\nAll employed persons Ukrainian refugees\n\n\n\n\n\n\n\n40% 30% 20% 10% 0% 10% 20% 30% 40%\n\n\n\n\n\n**Source:** Deloitte own elaboration based on Statistics Poland and ZUS data.\n\n\n24  Due to possible differences in methodologies data from this surveys should not be directly compared\n25  Elementary occupations include: Cleaners and helpers; Agricultural, forestry and fishery labourers; Labourers in mining, construction, manufacturing\nand transport; Food preparation assistants; Street and related sales and services workers; Refuse workers and other elementary workers.\n\n22\n\n\n\n23\n\n\n\n26  Act of March 12, 2022 on assistance to citizens of Ukraine in connection with the armed conflict on the territory of the country", "output": {"entities": {"named_data": ["ZUS data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 11, "chunk": 2, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "ZUS data", "label": "NAMED_DATA", "score": 0.833343505859375, "start": 246, "end": 254, "probe_score": 0.9297, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " of refugees.\nIn Swedish data, Edin, Fredriksson,\nand Aslund (2003) found that refugees\ndispersed to areas with more co-nationals\nexperience higher earnings.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\nKingdom, 56% in Sweden, 53% in Lithuania\nand 51% in the Czech Republic. The estimate\nfor Poland was based on November 2022\nNational Bank of Poland survey data.\nThis relatively high value is supported by a\nUNHCR Assessment from 2nd November,\nin which survey results show that 72% of\nrefugees are in the labour force, with 61%\nemployed and 11% unemployed.\nThe most refugees are employed in\nmanufacturing – 14%, accommodation and\nfood service – 12%, and trade and repair –\n6%. 89% of the survey respondents were\nwomen <sup>29</sup> .\n\n\n\n27  Deloitte elaboration based on the aggregation in OECD International Migration Outlook 2023\n28  After the closing date for our report, NBP (2024) published new data, showing a slight drop in Ukrainian refugees employment rate to 62% that does not\nchange our general conclusions.\n29  UNHCR Multi Sectorial Needs Assessment October 2023", "output": {"entities": {"named_data": ["November 2022\nNational Bank of Poland survey data", "OECD International Migration Outlook 2023"], "descriptive_data": [], "vague_data": ["Swedish data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 12, "chunk": 3, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Swedish data", "label": "VAGUE_DATA", "score": 0.7030082941055298, "start": 17, "end": 29, "probe_score": 0.9998, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "November 2022\nNational Bank of Poland survey data", "label": "NAMED_DATA", "score": 0.6199876070022583, "start": 345, "end": 394, "probe_score": 0.9998, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "OECD International Migration Outlook 2023", "label": "NAMED_DATA", "score": 0.6344680786132812, "start": 823, "end": 864, "probe_score": 0.8972, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<br>Q3<br>Q4<br>Italy|**Table 8. Origin of asylum applicants in 43 industrialized countries by quarter, 2007**<br>Covering 43 countries which provided monthly data to UNHCR (excluding Italy). <br>Total<br>2007<br>No. of applications (excluding Italy)<br>Change (%)<br>Share (%)<br>including<br>Origin<br>Q1<br>Q2<br>Q3<br>Q4<br>Total<br>Q2-Q1<br>Q3-Q2<br>Q4-Q3<br>Q1<br>Q2<br>Q3<br>Q4<br>Italy|**Table 8. Origin of asylum applicants in 43 industrialized countries by quarter, 2007**<br>Covering 43 countries which provided monthly data to UNHCR (excluding Italy). <br>Total<br>2007<br>No. of applications (excluding Italy)<br>Change (%)<br>Share (%)<br>including<br>Origin<br>Q1<br>Q2<br>Q3<br>Q4<br>Total<br>Q2-Q1<br>Q3-Q2<br>Q4-Q3<br>Q1<br>Q2<br>Q3<br>Q4<br>Italy|**Table 8. Origin of asylum applicants in 43 industrialized countries by quarter, 2007**<br>Covering 43 countries which provided monthly data to UNHCR (excluding Italy). <br>Total<br>2007<br>No. of applications (excluding Italy)<br>Change (%)<br>Share", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["monthly data", "monthly data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000427", "page": 20, "chunk": 3, "title": "Asylum Levels and Trends in Industrialized Countries 2008 - Statistical Overview of Asylum Applications Lodged in Europe and selected Non-European Countries", "pdf_url": "https://reliefweb.int/attachments/3ab13bab-8d4b-3f86-b90a-e2540078aef7/2F800689DD12C5A78525758300561F85-unhcr-asylumtrends-mar2009.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "monthly data", "label": "VAGUE_DATA", "score": 0.67354816198349, "start": 151, "end": 163, "probe_score": 0.9605, "gold": "DATA_MENTION", "gold_tier": "flip"}, {"text": "monthly data", "label": "VAGUE_DATA", "score": 0.5814653635025024, "start": 523, "end": 535, "probe_score": 0.9611, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nIntegrated Community Resilience Project (P506969) PROJECT APPRAISAL DOCUMENT\n\n\nwith the Djibouti Vision 2035 and the National Development Plan and was submitted at the 29 <sup>th</sup> Session of the Conference\nof the Parties to the United Nations Framework Convention on Climate Change (UNFCCC COP 29) in November 2024. The\nrevised NDC sets out Djibouti’s new goal to reduce greenhouse gas (GHG) emissions to 41.3 percent by 2030. It also\nspecifies key priority areas for emission reductions in energy, agriculture, forestry, land use, and waste management, and\nadaptation priorities in agriculture, water resources, and coastal areas. <sup>19</sup> [^19: World Bank, 2025, Djibouti Climate Change Development Report (CCDR)] Project’s activities can be considered Paris\nAligned from a mitigation perspective as they are not likely to hinder Djibouti’s low carbon development pathway <sup>20</sup> [^20: Project’s activities are exposed to identified climate risks (extreme heat, droughts, floods), but each activity financed under this operation will\n<u>integrate climate-resilient design to reduce material risks to an acceptable level.</u>] .\n\n21. **Climate Co-Benefits** . Local communities are vulnerable to extreme weather events due to their location’s\nexposure to these events and limited adaptive capacity due to multidimensional poverty. The project will provide C4N\nsupport to help vulnerable individuals cope during shocks in areas where the combined exposure to hazards and\nvulnerability is among the highest in the country. Indeed, hazard mapping shows that the share of population exposed to\nflooding in the Dikhil region is estimated to be a bit higher than one-third of the exposure level in Djibouti Ville. The\nfinancial inclusion subcomponent will further build communities’ resilience to these shocks. Resilient infrastructure\nsupported by the project will contribute to the objectives of the NAP strengthening community resilience.\n\n\n**II.** **PROJECT DESCRIPTION", "output": {"entities": {"named_data": [], "descriptive_data": ["hazard mapping"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000180", "page": 16, "chunk": 0, "title": "Djibouti - Integrated Community Resilience Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099022525185016955/pdf/BOSIB-87c444de-4797-4bf9-b654-4932a7fb0112.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "hazard mapping", "label": "DESCRIPTIVE_DATA", "score": 0.6763390302658081, "start": 1565, "end": 1579, "probe_score": 0.7347, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Monitoring and Evaluation Arrangement**\n\n\n162. In order for monitoring and evaluation to be completed, several different types of data will be\ncollected during the six-year project period. This data will together allow for reporting of the results\nindicators and also be used for the purposes of impact evaluation.\n\n\n163. For _Component_ _1,_ the primary source of data will be the entry forms for new applicants and the\nassessments of beneficiaries who are due for recertification. The information on new applicants and also\non beneficiaries due for recertification will be collected by the district offices, which will enter them into\nthe electronic databases and then transmit the information to the branch offices and eventually the head\noffice in Sana’a. The forms and assessments will obtain all the information necessary for the application\nof the PMT method. The district offices will collect the data on a timely basis and provide them to the\nbranch offices without significant delay. The PMT method will be applied to the data at the main office\nin order to classify households in one of the six PMT groups. The Monitoring and Evaluation Department\nat the SWF will ensure that the data are tabulated in time to meet the monitoring requirements of the\nproject.\n\n\n164. There will also be regular monitoring to ensure that the cash transfer and beneficiary development\nprocesses are being implemented in a manner that ensures targets in the Results Framework (Annex 4) are\nmet. Specifically, it will be the responsibility of the branch (i.e. Governorate) offices to compile monthly\nstatistics on the number of beneficiaries it has had contact with, the number of new applications received\nand processes annually, the number of appeals received and responded to annually, and also the number\nof beneficiaries who receive various BDP services (including health and education services, skills\ntraining, and access to microcredit). The statistics will be provided by the district offices to the branch\noffices, which will then report the statistics to the Monitoring and Evaluation Department at the SWF", "output": {"entities": {"named_data": [], "descriptive_data": ["electronic databases", "monthly\nstatistics"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000080", "page": 56, "chunk": 0, "title": "Yemen, Republic of - Social Welfare Fund Institutional Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/495501468170077604/pdf/533550PAD0P117101Official0Use0Only1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "electronic databases", "label": "DESCRIPTIVE_DATA", "score": 0.536919116973877, "start": 643, "end": 663, "probe_score": 0.2355, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "monthly\nstatistics", "label": "DESCRIPTIVE_DATA", "score": 0.5152921080589294, "start": 1583, "end": 1601, "probe_score": 0.1461, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "term nature of\nmost of these stays (6 months in a span 12\nmonths), fact that one person could hold\nseveral permits (as a result of changing jobs\nor positions within the same company),\nlegal changes, and decentralized nature of\npermits all hinder the reliability of these\nfigures. Two-thirds of such migrants have\nbeen men, some of whom left families\nin Ukraine temporarily to bring or send\nmoney back. Migration has been primarily\nbased on firm sponsorship, where\ncompanies provided job offers and handled\nformalities, which resulted in very high\nemployment rates – 94% as of November\n2022 according to NBP (2023) estimates.\n\n\n\nThe refugee inflow had a different\ndemographic composition than the pre2022 economic migration. It primarily\nincluded working age women (41%) and\nchildren (40%). <sup>5</sup> [^5: According to the active PESEL UKR database in October 2023.] Refugees from Ukraine did\nnot plan to move, and many had special\nneeds. In October 2023, nearly half of all\nrefugee households included a person\nwith a chronic illness, and some 10%\nincluded one with a Washington Group\nlevel 3 disability. Over a third included a\nsingle parent and a fifth an elderly person. <sup>6</sup> [^6: Deloitte calculations based on Multi-Sector Needs Assessment Poland 2023 survey data provided by UNHCR.]\nDespite these difficulties, refugees began\nentering the labour market surprisingly\nquickly – attaining an employment rate of\n28% in May 2022 and 65% in November\n2022 among working age persons (NBP,\n2023) –\n##### **753 thousand** Ukrainian workers, including 225 thousand refugees, had registered for social security by September 30, 2023.\n\n\n\n**Situation of Ukrainian refugees on the**\n**labour market in Poland**\nUkrainian refugees, despite war trauma\nand other difficulties, have quickly\nbecome a part of society as **consumers,**\n**employees, entrepreneurs, and**\n*", "output": {"entities": {"named_data": ["PESEL UKR database", "Multi-Sector Needs Assessment Poland 2023 survey data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 3, "chunk": 2, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "PESEL UKR database", "label": "NAMED_DATA", "score": 0.9148136377334595, "start": 832, "end": 850, "probe_score": 0.9824, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Multi-Sector Needs Assessment Poland 2023 survey data", "label": "NAMED_DATA", "score": 0.807432234287262, "start": 1226, "end": 1279, "probe_score": 0.9992, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " that are reasonable in the circumstances.\n\nWSTF Management accept responsibility for the Project's financial statements, which have been\nprepared on the Cash Basis Miethod of Financial Reporting, using appropriate accounting policies in\naccordance with International Public Sector Accounting Standards.\n\nManagement are of the opinion that the Project's financial statements give a true and fair view of the\nstate of Project's transactions during the financial year/period ended June **_30,_** 2020, and of the Project's\nfinancial position as at that date. Management further confirm the completeness of the accounting\nrecords maintained for the Project, which have been relied upon in the preparation of the Project\nfinancial statements as well as the adequacy of the systems of internal financial control.\n\nManagement confirm that the Project has complied fully with applicable Government Regulations and\nthe terms of external financing covenants, and that Project funds received during the financial\nproperly year/period accounted under audit for. were used for the eligible purposes for which they were intended and were\n\n\n**Approval of the Project** financial statements\n\nThe Project financial statements were approved **by** the _Chief Executive_ _Officer,_ _Project Manager and_\n_the Acting_ **_iSJE~._** _ChiefManager_ - -2020 _Financefor_ Kenya Urban Water and Sanitation **(KUWAS)** OBA project on\nand signed **by** them.\n\n\nICil Fahmy MShie\nFrot Manager\nIsmail Fahmy M. Shaiye **Ag.** Chief Manager Finance\nFidelis Tamangani\nSamwel Gitau Mbugua\n**ICPAK** Member Number: **2868**\n\n\nix", "output": {"entities": {"named_data": [], "descriptive_data": ["accounting\nrecords"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018755", "page": 10, "chunk": 1, "title": "KUWAS OBA Projects Audit Report for FY 2019_2020.pdf", "pdf_url": "https://documents.worldbank.org/curated/en/824941612258743616/pdf/KUWAS-OBA-Projects-Audit-Report-for-FY-2019-2020-pdf.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "accounting\nrecords", "label": "DESCRIPTIVE_DATA", "score": 0.5360349416732788, "start": 608, "end": 626, "probe_score": 0.0009, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the services sector—because there is no equivalent of ad valorem\n\n\ntariffs, for example—they are nonetheless believed to be very large (Miroudot et al., Forthcoming).\n\n\nCosts include communication—which can be proxied by geographical and cultural distance—as well as\n\n\ntrade policies that tend to open markets or reduce regulatory heterogeneity, such as RTAs.\n\n\nConcretely, we specify:\n\n\n4 Our results are qualitatively very similar if we use alternative thresholds, such as $0.5m or $0.18m (the tenth\npercentile of the trade data). These robustness checks are available on request.\n5 Although a cross-sectional approach is appropriate in light of previous work, the use of data for 2009 is not\nunproblematic because it might be affected by the global financial crisis.\n\n\n14", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["trade data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005838", "page": 15, "chunk": 1, "title": "wps6712", "pdf_url": "https://local/prwp/wps6712.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "trade data", "label": "VAGUE_DATA", "score": 0.6931113004684448, "start": 521, "end": 531, "probe_score": 0.702, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " are foreseen. However, the vagaries of climate change may contribute to the relative\ninsecurity of rural populations that are highly dependent on natural resources. Rainfall is the\nprimary water source for agriculture and livestock, and the wadi/river systems are an important\nsource of water in the East and Lake Chad areas. Under the project, potential negative\nenvironmental impacts would be site specific and manageable with good practice measures. There\nare also opportunities to enhance the resilience of populations through sustainable management of\nnatural resources. Safeguards implementation will be led by CFS, which has developed the\ncapacity to implement World Bank safeguards through the PFS. However, the extent of the\nenvironmental and social risks and safeguards instruments goes beyond what CFS has already\nimplemented and will require additional environmental and social capacity building. Further, the\ncomplex national procedures for clearance of environmental and social assessments and impact\nmitigation instruments pose a risk of delaying implementation. Close collaboration with the\nMinistry of Environment will be required to align project safeguards with national policies and get\nclearance for the use of such instruments in a timely manner.\n\n95. **Stakeholder risk is** **_High_** **given the fragile country context and the tensions inherent**\n**to managing refugee inflows,** **particularly in areas with substantial development needs and**\n**dwindling natural resources** . Although project activities will be designed with a view toward\nmaintaining social cohesion and mitigating potential conflicts (a communication strategy and clear\nand transparent selection criteria for areas of intervention and beneficiaries will be essential\nelements of this), a multitude of factors both within and outside of the project could affect relations\nwith refugees. Project areas are also prone to risks relating to gender equity and SGBV, which the\nproject will mitigate through accompanying measures such as community awareness and\n\n38 Marcel Ferland, _Rapport d’Evaluation Institutionnelle du PARCA (Projet d’Appuis aux Refugiés et aux Communautés", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000112", "page": 41, "chunk": 1, "title": "Chad - Refugees and Host Communities Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/658761536982256019/pdf/PAD2809-PAD-PUBLIC-disclosed-9-12-2018-IDA-R2018-0286-1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|KE-MOTI-238027-CS-QCBS /<br>CONSULTANCY SERVICES FO<br>R MAPPING AND DEVELOPME<br>NT OF A NATIONAL GEO DAT<br>ABASE OF SLUMS AND INFOR<br>MAL SETTLEMENTS IN KENYA|IDA / 67590|Institutional capacity develo<br>pment for slum upgrading|Prior|Quality And Cost-<br>Based Selection|Open - Internationa<br>l|Col7|1,600,000.00|0.00|Canceled|2021-06-11|2022-07-29|2021-07-02|2022-10-15|2021-08-15|Col16|Col17|Col18|2021-09-12|Col20|2021-10-12|Col22|2021-11-16|Col24|2021-12-21|Col26|2022-04-20|Col28|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n|KE-MOTI-382313-CS-QCBS /<br>CONSULTANCY SERVICES FO<br>R AN OPERATOR/CONSORTIU<br>M TO IMPLEMENT SETTLEME<br>NT LEVEL COMMUNITY DEVEL<br>OPMENT PLANS (PHASE 1) IN<", "output": {"entities": {"named_data": ["NATIONAL GEO DAT"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:002671", "page": 36, "chunk": 0, "title": "Kenya - EASTERN AND SOUTHERN AFRICA- P167814- Second Kenya Informal Settlements Improvement Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099052824092538084/pdf/P1678141f74b8c0a118e9e1b34e4018edac.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "NATIONAL GEO DAT", "label": "NAMED_DATA", "score": 0.6931742429733276, "start": 91, "end": 107, "probe_score": 0.0063, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda Digital Acceleration Project – GovNet (P171305)\n\n\n**ANNEX 1: Economic and Financial Analysis**\n\n\n**1.** **The project is expected to contribute to accelerated GDP growth, digitally enabled innovation, long-term**\n**government cost savings due to transformation of service delivery agenda in key sectors, and revenue increases**\n**as well as augmented citizen well-being.** An enhanced telecom market regulation and improved accessibility and\naffordability of broadband services and devices will result in a more dynamic digital sector with expanded digital\ncontent and could be expected to bring tangible opportunities for digital services development and exports in the\narea of digital innovation. Increased digitalization of government services that could be delivered in a cashless and\npaperless manner is expected to generate cost and time savings for both the general population and refugee host\ncommunities. By contributing to clean environmental practices, the improvements to e-waste management\npractices will further make Uganda an even more attractive destination for tourists. The refugees host\ncommunities supported through enhanced skills programs and opportunity/job pathways in the digital era could\ngenerate employment and productivity gains reflected in increased revenues and wages.\n\n**2.** **<mark>The novelty of severa</mark>** **l components (particularly those related to device affordability, digital authentication,**\n**advanced skills, and cybersecurity) as well as data limitations in other areas constrain an accurate estimation**\n**of expected economic and financial returns of the project.** The economic and financial analysis undertaken\nfollows a standard CBA methodology. The model relies on available secondary data and reasonable assumptions <sup>58</sup>\n\n59 60, based on experience and additional evidence from consultations and interviews conducted by the task team\nto conduct a cash flow analysis and resulting financial analysis for three different scenarios: optimistic, pessimistic,\nand neutral. When possible, the model", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["secondary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000023", "page": 59, "chunk": 0, "title": "Uganda - Digital Acceleration Project", "pdf_url": "http://documents.worldbank.org/curated/en/473041622944887337/pdf/Uganda-Digital-Acceleration-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "secondary data", "label": "VAGUE_DATA", "score": 0.7725064158439636, "start": 1760, "end": 1774, "probe_score": 0.5978, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " affected people\ntotals.\n\n\nAt a global level, the most thorough and most cited database of disaster losses that tracks these variables is EMDAT. At a national level, the expanding series of disaster\nloss databases following the DesInventar methodology\nprovide disaggregated loss figures per jurisdiction. Due\nto the fact that each DesInventar database is administered by each participating country, there are slight\nvariations in structure and more significant variations\nin coverage and low-end thresholds for inclusion. In the\npast this has made inter-country comparison difficult.\nIn 2015 IDMC is going to use the ISDR’s GAR data universe, which has been pre-screened to insure the highest\nlevel of inter-country comparison, thus largely removing this substantial limitation to previous DesInventar\ndatasets.\n\n\nIn all of these datasets, mortality data is of the highest\nquality, while homeless and affected population information can be somewhat less accurate, especially for\nsome particular types of hazard. Homeless data appears\nto be most accurately represented in earthquake events,\nand least well tracked in flood events. Storms and floods\nhave both the highest number of entries and total in\nterms of mortality and homelessness, which makes their\nindividual hazard analyses rather more robust due to\nthe larger sample sizes.\n\n\nLandslides, and smaller events in general, receive\nsubstantially less attention due to a combination of\ndifficulty in collecting data on so many events and\nproblems that can arise from a change in methodology.\nThese can include a lowering of thresholds for inclusion,\nthat would drastically increase the number of entries\nfor these types of events. For example, EM-DAT utilises\n\n\n\nDisaster-related displacement risk: Measuring the risk and addressing its drivers 39", "output": {"entities": {"named_data": ["DesInventar database", "GAR data universe", "EM-DAT"], "descriptive_data": [], "vague_data": ["mortality data", "Homeless data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000972", "page": 36, "chunk": 2, "title": "Disaster-related displacement risk: measuring the risk and addressing its drivers", "pdf_url": "https://reliefweb.int/attachments/906b2c91-c448-3dbe-bd8b-e5dbf81c1d04/NRC-Displacement-Risk-Analysis-EFA-FINAL.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "DesInventar database", "label": "NAMED_DATA", "score": 0.5049671530723572, "start": 331, "end": 351, "probe_score": 0.0004, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "GAR data universe", "label": "NAMED_DATA", "score": 0.6972755193710327, "start": 624, "end": 641, "probe_score": 0.1778, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "mortality data", "label": "VAGUE_DATA", "score": 0.7500144243240356, "start": 840, "end": 854, "probe_score": 0.1965, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Homeless data", "label": "VAGUE_DATA", "score": 0.5842372179031372, "start": 1012, "end": 1025, "probe_score": 0.0574, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "EM-DAT", "label": "NAMED_DATA", "score": 0.6709161400794983, "start": 1698, "end": 1704, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "###### **Refugee resettlement**\n\nAccording to government statistics, 59,500\nresettlement arrivals were reported by 12 countries\nin the first six months of 2023, an increase of 17,200\nor 41 per cent compared to the same period of the\nprevious year. Nevertheless, resettlement arrivals in\nthe first half of 2023 constituted only 3 per cent of the\n2 million people globally that UNHCR estimated were\nin need of resettlement. <sup>**44**</sup>\n\n\nThe **United States of America** welcomed the highest\nnumber of resettled refugees (31,900), with most of\nthem originating from the Democratic Republic of the\nCongo (11,200), followed by Syria (4,900), Myanmar\n(3,800) and Afghanistan (3,300). Almost 23,500\nrefugees were resettled to **Canada**, mainly from\nAfghanistan (5,900), Syria (4,900) and Myanmar (3,800).\n\n###### **Refugee local integration**\n\n\nDuring the first half of 2023, 20,500 refugees from 111\ncountries obtained citizenship in 15 countries, 25 per\ncent fewer (6,700) than during the same period in the\nprevious year. Given the lack of comprehensive data,\nthese figures should be considered as indicative only.\n\n\n\nChapter 5\n\n\nConsistent with the previous year, refugees in\n**the Kingdom of the Netherlands** (10,700) and\n**Canada** (9,400) accounted for almost all of those\nwho naturalized or obtained permanent residence.\nRefugees who obtained their host country’s\ncitizenship or were granted permanent residence\nwere mainly from Syria (5,600), Eritrea (2,200) and\nthe Islamic Republic of Iran (1,400).\n\n###### **Returns of internally displaced** **people**\n\n\nDuring the first", "output": {"entities": {"named_data": [], "descriptive_data": ["government statistics"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001065", "page": 28, "chunk": 0, "title": "UNHCR Mid-Year Trends 2023", "pdf_url": "https://reliefweb.int/attachments/a13b0f58-8b05-4652-84d7-e150dd9e7c6c/Mid-year-trends-2023.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "government statistics", "label": "DESCRIPTIVE_DATA", "score": 0.848296046257019, "start": 46, "end": 67, "probe_score": 0.9966, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "investments include roads, solid waste management, street lighting, greenery, servicing industrial land and\ntourist sites, parks for micro-enterprises and cottage industries, youth centers and incubators, etc.\nCompliance with the investment menu will be a minimum condition and be verified by the APA each\nProgram year. If a municipal LG has not invested Program funds in full compliance with the investment\nmenu, it will be sanctioned in the following year. Municipal LGs will be required to identify and prepare\ninvestments in a participatory manner and use the screening tools developed under USMID and the new\nDDEG guidelines. Participatory approaches and proper planning and budgeting will be promoted through\nthe annual assessments, and municipal LGs will be incentivized to involve the divisions, the municipal\ndevelopment forum as well as the private sector in the prior dialogue on planning and budgeting as well as\nmonitoring of execution.\n\n10. **Institutional strengthening for infrastructure provision will continue in USMID AF, targeting**\n**both the participating municipalities as well as MoLHUD and MDAs** . Firstly, the participating\nmunicipalities will receive grants to strengthen their capacities to execute their mandates for delivering a\nwide range of urban infrastructure and services. Each municipal LG will be required to develop a\ncomprehensive institutional strengthening plan that will respond to its capacity gaps especially those that\nwill be unearthed by the annual assessments under the Program and to ensure that the plan is executed on\neligible expenditures. The activities will continue to focus on: tooling, discretionary capacity building\n/institutional strengthening, and career development. US$ 10 million will be provided as Municipal\nInstitutional Strengthening Grant (ISG) as part of the overall DDEG allocation. Secondly, MoLHUD, which\nis responsible for the oversight of Program implementation as well as other MDAs, will also receive support\nto perform their mandate for urban development as well as for providing supply driven institutional support\nto the municipalities for activities which can be pooled together for economies of scale and that cut across\nall municipalities", "output": {"entities": {"named_data": [], "descriptive_data": ["annual assessments"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000062", "page": 55, "chunk": 0, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents.worldbank.org/curated/en/946901526654169395/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "annual assessments", "label": "DESCRIPTIVE_DATA", "score": 0.5710852742195129, "start": 719, "end": 737, "probe_score": 0.2362, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nAn ageing population coupled with a growing\neconomy causes labour shortages. Despite\nfalling number of available workers, the Polish\neconomy is growing steadily, as it modernises\nand converges to the level of development of\nold EU Member States. Despite the Covid-19\npandemic, real GDP growth averaged 3.7%\nduring the last decade. As a result, due to\nsteady demand for labour since 2019, the\nharmonised unemployment rate in Poland\nhas not exceeded 4%, oscillating around\n3% in recent years. According to Eurostat\ndata, in September 2023, harmonized\nunemployment in Poland reached 2.8%, the\nsame level as Malta. In the entire EU, only the\nCzech Republic reached a lower level: 2.7%.\nVacancies stood at record heights before\n\n\n\nthe refugee inflow. Before the refugee\ninflux, the share of companies reporting\nvacancies in the quarterly NBP survey\nstood at 49% in Q4 2021 – the highest\nlevel on record. This helps to explain the\nrelative ease of the refugees' labour market\ninclusion in terms of employment rates.\nAfter refugee inflow, the share of firms\nreporting vacancies stopped growing and\ndeclined slightly to 45% in Q3 2023. This\npartly indicates the fact that many refugees\nentered the labour market, and partly a\ncyclical economic slowdown. Despite that,\nthe labour market remains relatively strong.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 9.** Change in the number of workers registered for social security with Ukrainian citizenship by NACE sector between end of Q3\n2023 and 2021\n\n\nThousands\n\n\n\n\n\nManufacturing\n\n\nAccommodation and food service activities\n\n\nWholesale and retail trade; repair of motor vehicles and motorcycles\n\n\nHuman heatlh and social work activities\n\n\nAdministrative and support service activities\n\n\nEducation\n\n\nInformation and communication\n\n\nProfessional, scientific and technical activities\n\n\nPublic administration and defense; compulsory social security\n\n\nConstruction\n\n\nFinancial and insurance activities\n\n\nAgriculture, forestry and fishing\n\n\nReal estate activities\n\n\nWater supply: sewerage, waste management and", "output": {"entities": {"named_data": ["Eurostat\ndata", "quarterly NBP survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 9, "chunk": 0, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Eurostat\ndata", "label": "NAMED_DATA", "score": 0.7754862308502197, "start": 580, "end": 593, "probe_score": 0.9993, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "quarterly NBP survey", "label": "NAMED_DATA", "score": 0.6938711404800415, "start": 899, "end": 919, "probe_score": 0.9884, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "THE ROLE OF HOUSING SUPPORT AND EMPLOYMENT FACILITATION IN ECONOMIC VULNERABILITY OF REFUGEES FROM UKRAINE\n\n\n\n(selling house or land, using degrading sources of\nincome, taking on high-risk or illegal jobs) and\ncrisis-level (reducing essential health and education\nexpenditures, selling productive assets) coping\nstrategies. This statistic is even worse for those that\nfall below the poverty line <sup>8</sup> [^8: A household is defined to fall below the poverty line if its members fall below the poverty line on individual basis (the\nequivalized income of all household members is the same)], standing at 10% and 18%\nrespectively. Female-led households (where all\nadult members are female) report having to engage\nin harmful coping strategies more often than their\nmale-led counterparts.\n\n\n**<u>SHARE OF REFUGEE HOUSEHOLDS ADOPTING HARMFUL</u>**\n**COPING STRATEGIES ABOVE AND BELOW THE POVERTY**\n**LINE, %** <sup>**1**</sup> [^1: The statistic on emergency strategies may have been affected by\nthe survey wording on illegal work]\n\n\nAbove the poverty line Below the poverty line\n\n\n\n\n\n\n\n10%\n\n\n\n10%\n\n\n\nhousing fully subsidized by the government\n(notably, in Slovakia this share stands at 81%). Eight\npercent are being hosted free of charge by locals.\nSeventeen percent pay for rent only partially for\nvarious reasons, such as living with extended family,\npartially subsidized by the host government or\nemployer. Those that fully pay rent report this being\ntheir number one expense, constituting 40% of the\ntotal household budget.\n\n\nImportantly, support with accommodation expenses\nreduces the calculated poverty rate of refugees\nfrom Ukraine to 32% (from 50%) if it is considered to\nbe an indirect source of income <sup>9</sup> [^9: Its magnitude can be computed as the difference between the median equivalized market rent in the region and the actual\nequivalized accommodation expense] . This essentially\nmeans that rental aid, in whatever", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000000", "page": 4, "chunk": 0, "title": "3", "pdf_url": "https://local/jad_paddy_docs/3.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**Uganda’s development agenda is elaborated in the National Development Plan**\n**(NDP II) 2015/16 to 2019/20** . The NDP is aligned with the National Vision 2040 and the\nSustainable Development Goals (SDGs), and is aimed at propelling Uganda to middle-income\nstatus by 2020. Enhancing human capital development and strengthening mechanisms for highquality, effective, and efficient service delivery are two of the four primary development\nobjectives of the NDP. The NDP highlights the need to address the challenges of weak public\nsector management to improve service delivery.\n\n\n**B.** **Sectoral and Institutional Context**\n\n\n**Uganda is among the countries with the highest burdens of HIV/AIDS, malaria and**\n**tuberculosis globally.** Other key conditions contributing to its burden of disease are lower\nrespiratory infections, meningitis, peri/neonatal complications and diarrheal diseases. <sup>3</sup> [^3: The Global Burden of Disease Study 2010 and Health Management Information System (HMIS). The diseases\ntogether accounted for over 50 percent of all disability-adjusted life years in 2010. These years quantify both\npremature mortality (years of life lost) and disability (years of life lost to disability).] Women\nand children are the most affected and bear a disproportionate burden of disease in Uganda.\nWhile communicable diseases remain prevalent, non-communicable diseases are a growing\nconcern. The high disease burden is further complicated by disparities in health outcomes across\nregions (Table 1).\n\n\n**Table 1: Regional Reproductive and Child Health Disparities**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|TFR (%)|FP Unmet<br>need (%)|CPR (%)|PNM (per<br>1,000)|NMR<br>(per<br>1,000)|U5MR<br>(per<br>1,000)|Teenage<br>Pregnancy<br>(%)|\n|---|-", "output": {"entities": {"named_data": ["Global Burden of Disease Study 2010", "Health Management Information System"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019169", "page": 13, "chunk": 0, "title": "Uganda - Reproductive, Maternal, and Child Health Services Improvement Project", "pdf_url": "https://documents.worldbank.org/curated/en/854971471534008736/pdf/PAD-07182016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Global Burden of Disease Study 2010", "label": "NAMED_DATA", "score": 0.5502309799194336, "start": 918, "end": 953, "probe_score": 0.9999, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Health Management Information System", "label": "NAMED_DATA", "score": 0.8070066571235657, "start": 958, "end": 994, "probe_score": 0.888, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the Procurement Regulations and the following conditions:\n\n\n_In accordance with paragraph 5.3 of the Procurement Regulations, the request for_\n_bids/request for proposals document shall require that Bidders/Proposers submitting_\n_Bids/Proposals present a signed acceptance at the time of bidding, to be_\n_incorporated in any resulting contracts, confirming application of, and compliance_\n_with, the Bank’s Anti-Corruption Guidelines, including without limitation the Bank’s_\n_right to sanction and the Bank’s inspection and audit rights. The form of the Letter_\n_of Acceptance is attached in Appendix 1._\n\n\n**_Leased Assets_** _as specified under paragraph 5.10_ of the Procurement Regulations:\nLeasing may be used for those contracts identified in the Procurement Plan tables:\n**Not Applicable.**\n\n\n**_Procurement of Second Hand Goods_** _as specified under paragraph 5.11_ of the\nProcurement Regulations – is allowed for those contracts identified in the\nProcurement Plan tables: **Not Applicable.**", "output": {"entities": {"named_data": [], "descriptive_data": ["Procurement Plan tables"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005036", "page": 0, "chunk": 1, "title": "Uganda - EASTERN AND SOUTHERN AFRICA- P166570- Uganda Secondary Education Expansion Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099110923134537496/pdf/P1665700ee41c40880901606e8f59988b84.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Procurement Plan tables", "label": "DESCRIPTIVE_DATA", "score": 0.6423171758651733, "start": 755, "end": 778, "probe_score": 0.0261, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank** Implementation Status & Results Report\nEthiopia Flood Management Project (P176327)\n\n\n**Risks**\n\n\n**Systematic Operations Risk-rating Tool**\n\n\nRisk Category Rating at Approval Previous Rating Current Rating\n\n\nPolitical and Governance High High High\n\n\nMacroeconomic Moderate Moderate Moderate\n\n\nSector Strategies and Policies Substantial Substantial Substantial\n\n\nTechnical Design of Project or Program Substantial Substantial Substantial\n\nInstitutional Capacity for Implementation and\nSubstantial Substantial Substantial\n<u>Sustainability</u>\n\nFiduciary Substantial Substantial Substantial\n\n\nEnvironment and Social High High High\n\n\nStakeholders Moderate Moderate Moderate\n\n\nOther Moderate Moderate Moderate\n\n\nOverall Substantial Substantial Substantial\n\n\n**Results**\n\n\n**PDO Indicators by Objectives / Outcomes**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n11/18/2023 Page 2 of 8", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005155", "page": 1, "chunk": 0, "title": "Disclosable Version of the ISR - Ethiopia Flood Management Project - P176327 - Sequence No : 02", "pdf_url": "https://documents.worldbank.org/curated/en/099111823074533335/pdf/P176327044632f0c40b523005b834e26a04.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\n5. **Counties were then ranked based on the vulnerability index score.** Each of the above six\nindicators were aggregated into a single z-score with equal weighting, and the aggregate z-scores were\nrescaled from 0 to 100, with 100 being the most vulnerable. Most counties with high vulnerability are in\nEastern Equatoria, Jonglei, Upper Nile, and Western Bahr-el-Ghazal, most of which were heavily conflict\naffected.\n\n\n**Figure 2.8. County Vulnerability** **Figure 2.9. County Accessibility**\n\n\n6. Once counties with higher vulnerability score are long listed, they will be short-listed considering\nfeasibility. Feasibility will be assessed based on levels of insecurity, physical accessibility, a more nuanced\nqualitative conflict assessment, and the willingness of the county government. The result will be\ntriangulated through consultations with key stakeholders such as the government, development partners,\nand the civil society before finalizing. All _payams_ and _bomas_ within the selected counties will be eligible\nfor financing. To accommodate the fluid conditions on the ground, the final list of possible target counties\nwas determined at appraisal using the latest data sets.\n\n\n7. **Subproject budget allocation.** The subproject budget allocation will be allocated at the county\nlevel on a per capita basis using the latest county-level population projection used by all humanitarian\nagencies for consistency. US$10 and US$15 per capita will be allocated for rural and urban areas,\nrespectively, which is 43 percent higher than the allocation under the LGSDP. This is deemed appropriate\nas (a) costs of construction materials have increased; (b) costs will be higher in conflict-affected areas due\n\n\nPage 70 of 94", "output": {"entities": {"named_data": [], "descriptive_data": ["county-level population projection"], "vague_data": ["data sets"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 75, "chunk": 0, "title": "South Sudan - Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/824121596765983121/pdf/South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data sets", "label": "VAGUE_DATA", "score": 0.6110047698020935, "start": 1281, "end": 1290, "probe_score": 0.6539, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "county-level population projection", "label": "DESCRIPTIVE_DATA", "score": 0.863386332988739, "start": 1441, "end": 1475, "probe_score": 0.7393, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nCash for Jobs Project (P175327)\n\n\nof both of it is to build the capacity of the GoB to monitor its own programs in the Social Protection sector. In this sense,\nseveral instruments will support the monitoring of the project and Social Protection programs in general:\n\n\n\na. The Social Registry. It will help the MNSSAHRG, and SEP monitor the socio-economic situation of the poor and\n\nvulnerable households in Burundi. The socio-economic data being collected through the registry will allow\ngovernment to monitor the situation and better design social policies. The registry will also collect data on\nbeneficiaries enrolled in different social programs allowing to monitor the coverage of these.\nb. The project will support the mid-term review of the Social Protection Strategy that is meant to be approved\n\nat the beginning of 2022.\nc. SEP/CNPS will receive technical and financial support to perform their coordination tasks and lead the Social\n\nProtection Working Group allowing for a better monitoring of Social Protection interventions by different\npartners.\n\n128. PDO indicators and Intermediate Results Indicators of the project will be measured through different instruments.\nThese include process evaluations; regular spot checks and beneficiary surveys through mobile phone to evaluate the\nquality of implementation: the efficiency of the targeting and payment processes; and the overall satisfaction with the\nprogram. The key delivery mechanisms put in place for the project, such as the MIS, will enable the project to produce\nregular progress reports. The PIU will organize annual financial audits for the project, annual reviews of progress, and a\nmid-term review to guide the project implementation after the first 2.5 years of implementation. The mid-term review\nwill involve project’s stakeholders and civil society in the review of performance, intermediary results, institutional\narrangements, and outcomes. It will confirm the plans and processes for expansion of the project.\n\n129. A Monitoring and Evaluation manual was produced under Merankabandi. The manual will be updated for", "output": {"entities": {"named_data": ["Social Registry"], "descriptive_data": [], "vague_data": ["socio-economic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000130", "page": 44, "chunk": 0, "title": "Burundi - Cash for Jobs Project", "pdf_url": "http://documents1.worldbank.org/curated/en/768621641923064747/pdf/Burundi-Cash-for-Jobs-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Social Registry", "label": "NAMED_DATA", "score": 0.7073997855186462, "start": 295, "end": 310, "probe_score": 0.2211, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "socio-economic data", "label": "VAGUE_DATA", "score": 0.6770516633987427, "start": 439, "end": 458, "probe_score": 0.2862, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " and specific behavior change communication on this issue.\n\n56. **The grievance redress mechanism** will be a key tool to assess on-going issues, including\ncoerced transfer of a portion of the cash. The promotion activities will be open to all community\nmembers on a voluntary basis for non-beneficiary households to foster change in community social\nnorms. Both the process and the impact evaluations will track potential changes in conflict\n\n57. **Approximately one percent of the Burundian population is Batwa** . Initial data\ncollection for the indigenous peoples’ framework showed that an estimated 7,000 Batwa\nhouseholds were living in the provinces where the project will operate (300 in Ruyigi, 2,000 in\nKaruzi, 2,200 in Gitega and 2,500 in Kirundo). These data will be updated after the planned Batwa\nhousehold census in these provinces. Given the experience of the Concern pilot, it is expected that\nbetween one and six percent of the project beneficiaries will be Batwa. Given their overall level\nof poverty and exclusion, the indigenous peoples’ framework <sup>27</sup> [^27: Cadre de planification en faveur de la population Batwa dans le cadre du Projet d’Appui aux filets sociaux, Octobre\n2016.] seeks to ensure that eligible Batwa\nhouseholds can participate fully in the project activities and mitigate any potential negative impact\narising from the project’s intervention.\n\n58. **The framework was developed with a participatory and inclusive methodology**, with\nconsultations through individual interviews and focus groups with guides designed for this\npurpose. These consultations through participatory diagnosis allowed to reflect the socioeconomic situation of the Batwa, the actions needed to help address this situation, the risks inherent\nin the implementation of project activities and potential mitigation measures <sup>28</sup> [^28: The consultations took place in each of the four provinces over the week of September 20, 2016.] .\n\n\n26 Umumbyeyi _et al_ . 2014 report that 18.8 percent of rural women in the Southern", "output": {"entities": {"named_data": [], "descriptive_data": ["Batwa\nhousehold census"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000157", "page": 79, "chunk": 1, "title": "Burundi - Social Safety Nets Project", "pdf_url": "http://documents1.worldbank.org/curated/en/900951482030099834/pdf/1482030098559-000A10458-PAD-Burundi-SSN-11282016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Batwa\nhousehold census", "label": "DESCRIPTIVE_DATA", "score": 0.8511409163475037, "start": 804, "end": 826, "probe_score": 0.0256, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Professional Certificate (CTPC) which will make their qualifications equivalent to that of a\nlicensed teacher graduating from accredited teacher education programs. The CDTP will define\nthe type of certificate that successful participants in the program would obtain. This program\nwould be highly motivational, as it would give under-qualified teachers the opportunity to\nupgrade their skills and enhance their teaching careers and become eligible for promotions and\nother benefits.\n\n28. The MOEHE selected four universities in the West Bank (Birzeit, Al-Quds, Hebron, and\nAl-Najah Universities) and one university in Gaza which is Al-Azhar. In the case of Gaza, AlAzhar University will be a “focal point” and will coordinate with other relevant universities in\nGaza. The MOEHE selected these universities based on their previous experience in skills\nupgrading for under-qualified teachers, coupled with geographic considerations to ensure\ncoverage throughout the West Bank. The same considerations were applied for Gaza and AlAzhar was deemed most appropriate. During the appraisal mission, the Bank’s team discussed\nthe selection process for these universities and concluded that it was appropriate and well\njustified in the current context.\n\n29. This component will fund: (i) two local consultants that will provide technical assistance\nand implementation support to NIET (one of the consultants will be based in Gaza); and (ii)\ninternational technical assistance to be provided by a well-known institution with extensive\nexperience in professional development and in-service teacher training. This international\ninstitution will assist NIET and the selected HE institutions with the preparation of tools to\nassess the level of competencies and skills of class teachers and, based on this assessment, to\ndesign a modular program for upgrading their skills. It will also provide implementation support\nfor the evaluation of phase one and the preparation of a plan for scaling up this initiative using\nthe evaluation data; (iii) training of trainers to be provided by the international institution; (iv)\nfunds to finance the delivery", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["evaluation data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000171", "page": 15, "chunk": 0, "title": "West Bank and Gaza - Teacher Education Improvement Project", "pdf_url": "http://documents1.worldbank.org/curated/en/951621468137973426/pdf/492780PAD0P111101Official0Use0Only1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "evaluation data", "label": "VAGUE_DATA", "score": 0.7144191265106201, "start": 2007, "end": 2022, "probe_score": 0.2586, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " foundation for democratic and sustainable local\n\n\n\ndevelopment. The Community Development Program will finance social and economic\ninfrastructure and support social capital building activities to facilitate the restoration of basic\nsocial services such as health and education and provide an incentive for teachers, health workers\nand displaced persons to return to their communities. The Rural Public Works and Shelter\nprograms will provide employment for demobilized soldiers and unemployed youth, housing for\ndisplaced persons and feeder roads to stimulate local economic activities. The innovative\nactivities including training and technical support will strengthen local government capacity to\nplan, contract, manage and sustain investments in local development and engage a wide array of\n\n\n\nstakeholders in participatory processes that contribute to sustainable local development.\n\n\n\nTargeting will be consistent with the Government's 2002-2003 National Recovery\nStrategy and the March 3, 2002 Transitional Support Strategy. Resources will be directed to (a)\nnewly accessible areas that have not received any support in more than a decade; and (b) remote\nareas that have received little, if any support from the ongoing IDA-financed CRRP or other\nsimilar projects. The results of the living standards measurement survey currently underway will\nbe available at the end of 2003 and will be used to review the validity of existing targeting\nmodalities.\n\n\nTarget Populations: Target groups include demobilized soldiers and unemployed youth,\nrefugees, IDPs, female-headed households, child laborers, orphans, primary school dropouts,\n\n\n_- 8 -_", "output": {"entities": {"named_data": [], "descriptive_data": ["living standards measurement survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000165", "page": 12, "chunk": 1, "title": "Bosnia and Herzegovina - Community Development Project", "pdf_url": "http://documents1.worldbank.org/curated/en/941761468768008234/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "living standards measurement survey", "label": "DESCRIPTIVE_DATA", "score": 0.8663687705993652, "start": 1291, "end": 1326, "probe_score": 0.7112, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*migration status**\n\n\n\n**Figure 9** **\u0007Poverty rate by households’**\n\n**migration status**\n\n\n\n45\n50\n\n40\n\n\n\n40\n\n\n30\n\n\n\n35\n\n\n30\n\n\n25\n\n\n\n20\n20\n\n15\n\n\n10\n10\n\n5\n\n\n\n\n\nNo Move Returnee IDP Economic No Move Returnee IDP\n\n\n\nEconomic\n\nMigrant\n\n\n\nMigrant\n\n\n\nNotes: Vertical bar indicates the 95% confidence interval\nSources: Authors’ calculation based on ALCS 2013–14 Sources: Authors’ calculation based on ALCS 2013–14\n\n\nPoverty and vulnerability are widespread in Afghanistan. **Mobility—irrespective of its forced and/or**\n**economic motives—is associated with a lower risk of poverty** (Figure 9); returnee households have\na significantly lower poverty risk compared to non-mobile households <sup>14</sup> . The poverty rate among\nreturnee households is 29.4 percent compared to 40.5 percent among non-mobile households. This\nlower poverty risk, however, is entirely explained by differences in literacy and in urbanization, with\nrefugee households being more likely to have a literate household head and to live in an urban area\ncompared to non-mobile households.\n\n\n6", "output": {"entities": {"named_data": ["ALCS 2013–14"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000681", "page": 5, "chunk": 1, "title": "Fragility and Population Movement in Afghanistan", "pdf_url": "https://reliefweb.int/attachments/64f35fee-a97c-32da-bd8d-46c676fc52a2/108733-REVISED-PUBLIC-WB-UNHCR-policy-brief-FINAL.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "ALCS 2013–14", "label": "NAMED_DATA", "score": 0.5813259482383728, "start": 343, "end": 355, "probe_score": 0.9962, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " of trainees/participants, duration, staff months, timing, and\nestimated costs will be submitted to IDA for review and approval before initiating the process. The\nappropriate methods of selection will be derived from the detailed schedule. After the training, each\nbeneficiary will be requested to submit a brief report indicating what skills have been acquired and how\nthese skills will contribute to enhance his/her performance and contribute to attainment of the PDO.\nReports by the trainees, including completion certificate/diploma upon completion of training, shall be\nprovided to the project coordinators, will be kept as parts of the records, and will be shared with the\nWorld Bank if required.\n\n9. **Operating costs.** Operating costs financed by the project are incremental expenses, incurred by\nthe PIUs or its regional representations, based on the annual work plans and budgets as approved by IDA,\non account of project implementation, management, and M&E, including office supplies; bank charges;\nvehicles operation; maintenance and insurance; maintenance of equipment and buildings;\ncommunication costs; travel and supervision costs (that is, transport, accommodation, and per diem);\ncosts related to utilities and office space rental; and salaries of contracted and temporary staff. The related\ngoods/services will be procured using the procurement procedures specified in the PIM and accepted and\napproved by the World Bank.\n\n10. **Procurement assessment of the SNE PIU.** Procurement capacity of the existing SNE PIU is overall\nsatisfactory. It is currently rated Moderately Satisfactory according to the last PRAMS. <sup>41</sup> Table 1.4\nsummarizes the main risks/issues and mitigation actions to be taken by SNE.\n\n\n41 PRAMS = Procurement Risk Assessment and Management System.\n\n\nPage 62 of 87", "output": {"entities": {"named_data": ["PRAMS"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 67, "chunk": 1, "title": "Chad - Energy Access Scale Up Project", "pdf_url": "http://documents.worldbank.org/curated/en/860701648216750651/pdf/Chad-Energy-Access-Scale-Up-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "PRAMS", "label": "NAMED_DATA", "score": 0.5000333786010742, "start": 1628, "end": 1633, "probe_score": 0.0003, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " for 15-74 (broadest available) age group, and earnings by educational attainment are taken from the GUS (2022) “Structure of\nwages and salaries by occupations in October 2020”.\n37  Note that the numbers of Ukrainian refugees and all workers numbers by poviats are taken from ZUS Statistical Portal on 30th September\n2023 from the universe of workers registered for social security (this does not cover the informal sector and some jobs that do not require social\nsecurity). Ukrainian refugees are identified by PESEL UKR. Salaries and wages are taken from Statistics Poland BDL GUS database for 2022, but\ncover only the enterprise sector (firms with 10 or more employees).\n38  Note that there is no publicly available administrative data on the sectoral distribution of Ukrainian refugees. We proxied their sectors by\ntaking the difference in workers with Ukrainian citizenship registered for social security between H1 2023 and end of 2021 in A-Q 1-letter NACE\nsections. For the general population we used employment in the 15+ age group in Q2 2023 from the Eurostat Labour Force Survey. Earnings by\nNACE section have been taken from Statistics Poland Statistical Bulletin wages and salaries for the enterprise sector and public sector in Q2 2023.\n39  Note that Ukrainian refugees have been allocated to firm sizes based on the July-August 2023 UNHCR (2023) survey, while general workers\nfrom the GUS (2023) “Employment in the national economy in 2022”. Productivity of firms by size is based on gross value added per person\nemployed in industry, construction, and market services sectors (broadest available) in 2021 from Eurostat Structural Business Statistics.\n40  Note that data on occupations of Ukrainian refugees is for persons with PESEL UKR registered for social security on 30th September 2023. It\nis then compared to the general population by nine main occupational groups from GUS LFS in Q2 2023 and earnings from GUS (2023) “Structure", "output": {"entities": {"named_data": ["ZUS Statistical Portal", "Statistics Poland BDL GUS database", "Eurostat Labour Force Survey", "Statistics Poland Statistical Bulletin", "UNHCR (2023) survey", "Eurostat Structural Business Statistics", "GUS LFS"], "descriptive_data": ["data on occupations of Ukrainian refugees"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 16, "chunk": 3, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "ZUS Statistical Portal", "label": "NAMED_DATA", "score": 0.7892969250679016, "start": 276, "end": 298, "probe_score": 0.5255, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Statistics Poland BDL GUS database", "label": "NAMED_DATA", "score": 0.6732257008552551, "start": 557, "end": 591, "probe_score": 0.9996, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Eurostat Labour Force Survey", "label": "NAMED_DATA", "score": 0.8545132875442505, "start": 1060, "end": 1088, "probe_score": 0.9358, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Statistics Poland Statistical Bulletin", "label": "NAMED_DATA", "score": 0.5409024953842163, "start": 1136, "end": 1174, "probe_score": 0.8278, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHCR (2023) survey", "label": "NAMED_DATA", "score": 0.6744912266731262, "start": 1347, "end": 1366, "probe_score": 0.0077, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Eurostat Structural Business Statistics", "label": "NAMED_DATA", "score": 0.8062437772750854, "start": 1625, "end": 1664, "probe_score": 0.0009, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data on occupations of Ukrainian refugees", "label": "DESCRIPTIVE_DATA", "score": 0.7614626288414001, "start": 1680, "end": 1721, "probe_score": 0.388, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "GUS LFS", "label": "NAMED_DATA", "score": 0.8313433527946472, "start": 1891, "end": 1898, "probe_score": 0.0019, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Is 7 and 8 Results on Physical Planning, Land Tenure Security and Urban Infrastructure Development in Refugee Host Areas.64 **|**DLI Matrix for DLIs 7 and 8 Results on Physical Planning, Land Tenure Security and Urban Infrastructure Development in Refugee Host Areas.64 **|**DLI Matrix for DLIs 7 and 8 Results on Physical Planning, Land Tenure Security and Urban Infrastructure Development in Refugee Host Areas.64 **|**DLI Matrix for DLIs 7 and 8 Results on Physical Planning, Land Tenure Security and Urban Infrastructure Development in Refugee Host Areas.64 **|\n|**Disbursement Link**<br>**Indicators (DLIs)**|**Total**<br>**Financing**<br>**allocated to**<br>**DLI (million**<br>**US$)**|**As % of Total**<br>**Financing**<br>**Amount**<br>|**DLI Baseline**|**Indicative timeline for DLI achievement**|**Indicative timeline for DLI achievement**|**Indicative timeline for DLI achievement**|**Indicative timeline for DLI achievement**|**Indicative timeline for DLI achievement**|\n|**Disbursement Link**<br>**Indicators (DLIs)**|**Total**<br>**Financing**<br>**allocated to**<br>**DLI (million**<br>**US$)**|**As % of Total**<br>**Financing**<br>", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000006", "page": 41, "chunk": 3, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents.worldbank.org/curated/en/143681526614252328/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\nsubprojects; and (d) continued accessibility and permissive security. Allocations to the _payam_ level will\nfollow the Government’s fiscal transfer formula of 60 percent equal allocation and 40 percent based on\npopulation (utilizing IOM’s DTM projections) whereas all _bomas_ within target _payams_ will receive equal\namount of funding as no population data are available <sup>52</sup> [^52: Population figures for urban areas would be calculated based on a headcount or by complementing 2008 census with other data sources (for\nexample, DTM.)] (see annex 2 for details).\n\n\n33. **Use of community labor.** The project will encourage contractors to utilize local labor in the\ninfrastructure construction or rehabilitation to the extent possible. Emphasis will be placed on the\ninclusion of various social groups facing marginalization or barriers to participation (for example, women,\nyouth, returnees, ethnic minority groups, and people with disabilities) and ensuring their access to daily\nwage labor opportunities. It will be especially important to include women in the design and construction\nof WASH facilities, for instance, to ensure these facilities are rehabilitated in ways that promote security\nand effective management on completion. The project will harmonize, to the extent possible, the labor\nprovisions adopted by the World Bank’s SSSNP and coordinate salary levels with UN coordination cluster\nstandards.\n\n\n**Component 2. Local Institution Strengthening (US$14.17 million equivalent)**\n\n\n34. **Subcomponent 2.1. Community Institution Strengthening.** This subcomponent supports the\nparticipatory planning process for the identification of subprojects that will be financed under Component\n1, monitoring of the construction and O&M of subprojects, and capacity building of the community\ninstitutions. Specific activities under this subcomponent include (a) community mobilization; (b)\nparticipatory risk mapping/analysis and risk mitigation training; (c) support for community institutions on\nparticipatory development", "output": {"entities": {"named_data": ["DTM projections"], "descriptive_data": [], "vague_data": ["population data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 26, "chunk": 0, "title": "South Sudan - Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/824121596765983121/pdf/South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "DTM projections", "label": "NAMED_DATA", "score": 0.5569634437561035, "start": 342, "end": 357, "probe_score": 0.9374, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "population data", "label": "VAGUE_DATA", "score": 0.6955037117004395, "start": 445, "end": 460, "probe_score": 0.662, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "LG, OPM, NEMA, UCC, PPDA, and other\nsectoral agencies such as the MoES, MAAIF, JLOS, MoH, MTIC, MTWA, NIRA, UBOS; the Ministry of Gender; and\nthe working group of the CRRF for its role among refugees and RHDs. The TC will meet at least once a quarter\nto ensure timely and smooth implementation progress. The Project Coordinator will ensure inter-institutional\ncollaboration and coordination among different agencies. Ad hoc project implementation teams (PITs) will be\nestablished for the purposes of implementing specific activities of the project. The PITs, represented by key\nstakeholders from partner agencies, will be guided by the decisions of the TC. The summary of the technical\nleads and partner agencies involved in the implementation of each sub-component is presented in annex 3.\n\n**B.** **Results Monitoring and Evaluation Arrangements**\n\n\n**65.** **The project results framework will form the basis of the results M&E arrangements.** M&E of the UDAPGovNet will be embedded in the various components of the project, and TA provided through the project will\ninclude support for M&E. The arrangements for results monitoring are detailed in Section VII and will be supported\nusing the Geo-Enabled Monitoring and Supervision (GEMS) Initiative. NITA-U will collect, compile, and analyze the\nresults data and prepare M&E reports. Where surveys are required to populate baseline or progress data for\nspecific indicators, the M&E specialist on the PIU will be coordinating the implementation of such surveys and\nutilizing funds from component 4, Project Management, to procure the needed surveying services. NITA-U will\n\n\nPage 26 of 76", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["results data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000023", "page": 38, "chunk": 1, "title": "Uganda - Digital Acceleration Project", "pdf_url": "http://documents.worldbank.org/curated/en/473041622944887337/pdf/Uganda-Digital-Acceleration-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "results data", "label": "VAGUE_DATA", "score": 0.659404993057251, "start": 1298, "end": 1310, "probe_score": 0.0119, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "east Developed Countries. These are typically low- or lower-middle-income countries confronting severe structural](https://www.un.org/development/desa/dpad/least-developed-country-category.html)</u>\nimpediments to sustainable development. The list of countries is revised every three years.\n\n\nUNHCR > **MID-YEAR TRENDS 2023** 15", "output": {"entities": {"named_data": ["MID-YEAR TRENDS 2023"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001065", "page": 14, "chunk": 2, "title": "UNHCR Mid-Year Trends 2023", "pdf_url": "https://reliefweb.int/attachments/a13b0f58-8b05-4652-84d7-e150dd9e7c6c/Mid-year-trends-2023.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "MID-YEAR TRENDS 2023", "label": "NAMED_DATA", "score": 0.541584849357605, "start": 303, "end": 323, "probe_score": 0.0081, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ") بكلفة (يناير/كانون الثاني– 2014 العام\n\n\n\n**. توقعات تمويل كلفة األدوية واللقاحات 1 الجدول**\n\n\n\n\n\n\n\n\n\n\n\n14\n\n|جمانربلا ليومت|% ليومتلا|قرافلا<br>رلوادلاب(<br>)يكريملاأ|ةيلعفلا ةفلكلا<br>ةيودللأ<br>)رلوادلاب(|هاجتلا<br>يدعاصتلا<br>% لّدعمب<br>3|يتلا ةيودلاأ<br>اهؤرا ش ّمت<br>)رلوادلاب(|Col7|\n|---|---|---|---|---|---|---|\n||||-<br>|-<br>|74,652,457|2010<br>|\n||||-<br>|-<br>|77,975,809|2011<br>|\n|5,000,000<br>|50%<br>|10,220,000|90,160,000<br>|79,940,000||2012<br>|\n|29,400,000|100%<br>|29,400,000|112,212,965|82,740,000||2013<br>|\n|15,960,000|50%<br>|31,920,000|117,180,000|85,260,000||2014<br>|\n|50,470,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000128", "page": 41, "chunk": 3, "title": "Jordan - Emergency Project to Assist Jordan Partially Mitigate Impact of Syrian Conflict : الأردن-مشروع الطوارئ لمساعدة الأردن جزئيا تخفيف أثر الصراع السوري", "pdf_url": "http://documents1.worldbank.org/curated/en/751611469076936591/pdf/78129-PAD-ARABIC-Box396288B-PUBLIC-Emergency-Project-to-Assist-Jordan-Partially-Mitigate-Impact-Of-Syrian-Conflict-P145865-PAD-Arabic.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " <sup>22</sup> The average income abroad of applicants is around\n\n\n$120,000; the median is considerably lower at about $84,000. Average incomes in Malaysia, for\n\n\nthose who returned, are actually higher with the average and median around $137,000 and\n\n\n20 The electronic administrative records are missing information for 18 percent of our sample. Note that the electronic\nrecords are not used to determine whether an application is accepted, rather TalentCorp prepares a paper file on each\napplicant. The characteristics of those missing, including their return status, are near identical to the overall sample,\nsuggesting they are missing at random.\n21 For 21 percent of the sample income abroad is missing. In addition, to deal with measurement error we exclude\noutlying income observations. Most importantly, the income abroad question on the REP application is ambiguous in\nwhether annual or monthly income should be reported. The large majority of respondents seem to have reported annual\nincome, but we exclude reported incomes of less than $24,000 (14 percent of observations) since these could plausibly\nbe monthly wages. Our results are robust to varying this cutoff income. We also exclude the top 1 percent of income\nobservations. The characteristics of individuals with income information missing or below the cutoffs are near\nidentical to those of the remainder of the sample, including their return probability.\n22 PPP conversion rates are from the World Bank Development Indicators. 2011 numbers are inflated by the change\nin the US Consumer Price Index.\n\n\n10", "output": {"entities": {"named_data": ["World Bank Development Indicators", "US Consumer Price Index"], "descriptive_data": ["electronic administrative records"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006882", "page": 11, "chunk": 1, "title": "wps7875", "pdf_url": "https://local/prwp/wps7875.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "electronic administrative records", "label": "DESCRIPTIVE_DATA", "score": 0.8046085834503174, "start": 260, "end": 293, "probe_score": 0.0451, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "World Bank Development Indicators", "label": "NAMED_DATA", "score": 0.8997779488563538, "start": 1464, "end": 1497, "probe_score": 0.7644, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "US Consumer Price Index", "label": "NAMED_DATA", "score": 0.653802752494812, "start": 1546, "end": 1569, "probe_score": 0.2936, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the Ministries members of the CNPS. The analysis of the data will provide a portrait\nof the extreme poor, their access to services and their livelihood strategies which can help inform\nthe design of poverty reduction programs and interventions to increase the extreme poor’s access\nto basic services. Information-sharing protocols will be developed so that programs that target the\nextreme poor can have access to the information but that the information remains secure.\n\n30. **The proposed methodology will be initially implemented in the 8 selected rural**\n**communes of the Karuzi and Ruyigi provinces and then will be reviewed for the**\n**implementation in the additional 8 communes in Gitega and Kirundo provinces** to: (i) assess\nthe operational processes for the implementation of the targeting, in terms of organizational\ncapacity and credibility, time and costs, (ii) test the targeting efficiency of the proposed CBT and\nPMT combination given the prevalence of poverty and the dearth of reliable consumption data.\nThe first phase results will inform the roll-out in the next eight communes.\n\n31. **As part of the registration process, the project will register the national ID number**\n**of the proposed cash transfer recipient and a potential substitute.** An estimated 20 percent of\nBurundians do not have an ID card and this proportion reached 30 percent among the beneficiaries\nof the _Terintambwe_ pilot). If needed, the project will coordinate with the Ministry of Interior for\nthe provision of national identity cards to potential recipients of the cash transfer program. This\nwill also help ensure their access to other public services and increase their citizen participation in\nsociety.\n\n\n46", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["consumption data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000157", "page": 56, "chunk": 1, "title": "Burundi - Social Safety Nets Project", "pdf_url": "http://documents1.worldbank.org/curated/en/900951482030099834/pdf/1482030098559-000A10458-PAD-Burundi-SSN-11282016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "consumption data", "label": "VAGUE_DATA", "score": 0.7187802791595459, "start": 1007, "end": 1023, "probe_score": 0.8119, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Okollo – **Northern** ; and Kapchorwa, Sironko & Bukedea **Eastern** . Meetings and Key Informant Interviews were held with relevant district technical officers\nincluding Chief Accounting Officer, District Environment Officers, District Natural Resource\nOfficers, District Water Officers, District Agricultural Officers and Community Development\nOfficers among others. A couple of civil works sites under UgIFT were inspected in Wakiso and\nKapchorwa Districts.\n\n\n15. Findings from literature review and face to face consultative meetings were compiled in a draft ESSA\nthat informed a stakeholder validation/consultation with various participants from the relevant line\nministries and agencies, Non-Governmental Organizations, and Civil Society Organizations.\nSpecifically: MoFPED, MoGLSD, MoES, MoLG, MWE, NEMA, Bank Information Centre (BIC),\nCenter for Domestic Violence Prevention (CEDOVIP), World Vision Uganda (WVU), Joy for\nChildren (JFC) and BRAC\n\nThe meeting was scheduled for early April 2020 but because of the COVID-19 government-imposed\nrestrictions, it was cancelled and instead, the stakeholders were sent an electronic version of the draft\nESSA report and asked to provide feedback via email. The team compiled the various inputs which\nranged from small reports, emails, and tracked changes into the original report. Relevant and pertinent\ncomments/suggestions were incorporated into this report and a comment/response matrix prepared\n(See Annex 4 for details). In addition, the findings from the monitoring of UGIFT I forms part of the\nbasis for the analysis and report for AF ESSA.\n\n\n**1.5** **ESSA Core Principles**\n\n\n16. The ESSA Update considered the strength and gaps in the system with respect to the “six core\nprinciples” of the World Bank Policy for Program-for-Results Financing. These principles establish\nthe policy and planning elements that are necessary to achieve outcomes consistent with PforR\nobjectives. They", "output": {"entities": {"named_data": ["monitoring of UGIFT I"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016653", "page": 9, "chunk": 1, "title": "Final Addendum to Environmental and Social Systems Assessment (ESSA) - UGANDA INTERGOVERNMENTAL FISCAL TRANSFERS - ADDITIONAL FINANCING - P172868", "pdf_url": "https://documents.worldbank.org/curated/en/684011598018287987/pdf/Final-Addendum-to-Environmental-and-Social-Systems-Assessment-ESSA-UGANDA-INTERGOVERNMENTAL-FISCAL-TRANSFERS-ADDITIONAL-FINANCING-P172868.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "monitoring of UGIFT I", "label": "NAMED_DATA", "score": 0.6438128352165222, "start": 1512, "end": 1533, "probe_score": 0.0293, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "## Introduction\n\n##### Nearly two years after the beginning of the full-scale war in Ukraine, the positive impact of the refugees on the Polish economy becomes clearly visible.\n\n\n\nOn their arrival, the impact of refugees\non the economy primarily manifested\nthrough higher consumption, that was\nfinanced mainly by increased governmental\nspending, civil society, international\norganisations, and savings brought\nfrom Ukraine. While these added to a\nsignificant initial increase in consumption,\nmultiple sources of financing and a lack of\naggregated data (particularly on general\ngovernment expenses) make its magnitude\nuncertain. Although in the short term it\nstimulated the economy, drawing just on\nsavings was not sustainable. Over time,\nhowever, refugees started to work as\nemployees and entrepreneurs, adding\nnot only to the demand, but also to the\nsupply of the economy, contributing to its\nlong-term growth. The focus of this report\nis this structural impact of refugees on\nthe economy as consumers, employers,\nentrepreneurs, and taxpayers.\n\n\nThe beginning of the full-scale war in\nUkraine resulted in a large inflow of\nrefugees into Poland outlined in Chapter 1.\nThis cohort differs from the pre-2022\nUkrainian economic migrants, most notably\nin its demographic makeup which primarily\ncomprises children and working age women.\n\n\nThe government quickly granted refugees\nfrom Ukraine access to the labour market,\nhealthcare, and schooling, facilitating the\nprocess of inclusion described in Chapter\n2. Considering their psychological stress\nand needs in terms of child and elderly\ncare, refugees began entering the labour\n\n\n\nmarket surprisingly quickly – attaining\nan employment rate of 28% in May 2022\nand 65% in November 2022 (NBP, 2023).\nBy 30th September 2023 more than\n10 thousand ran their own businesses\naccording to the administrative social\nsecurity ZUS data. Based on the MultiSector Needs Assessment Poland 2023\nsurvey conducted in July-August 2023, we\ncalculate that 80% of the income of refugee\nhouseholds is derived from employment,\nwith an additional 5% coming from\nremittances and 2% from Ukrainian pension", "output": {"entities": {"named_data": ["administrative social\nsecurity ZUS data"], "descriptive_data": [], "vague_data": ["aggregated data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 5, "chunk": 0, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "aggregated data", "label": "VAGUE_DATA", "score": 0.6490753889083862, "start": 536, "end": 551, "probe_score": 0.612, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "administrative social\nsecurity ZUS data", "label": "NAMED_DATA", "score": 0.7135217189788818, "start": 1831, "end": 1870, "probe_score": 0.9935, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Table 1 below summarizes the average\n\nmeasurements found in recent LSMS-ISA surveys. <sup>4</sup> The SR-GPS difference observed in Nigeria is\n\n\nconsiderably larger than in the four other LSMS surveys listed.\n\n\n<<< TABLE 1 HERE >>>\n\n\n3 While the differences observed in Nigeria are quite large nationwide, particular states and enumerators see\nsignificantly larger divergences. The two states with the highest discrepancy in measurements are Osun and Ondo\n(10,469% and 11,534%, respectively). Within those two states, three particular interviewers contribute to the\nmajority of the difference suggesting that the problem may be largely the product of human error such as incorrect\nuse of the GPS device or inaccurate recording of self-reported and/or GPS figures.\n4 One important difference between the GHS-Panel and the other LSMS-ISA surveys presented here is that in the\nGHS-Panel farmers are allowed to use nonstandard area units when estimating plot size while all the other surveys\nonly allow farmers to report in standard units (acres, square meters, or hectares). This may partially explain why the\nself-reported/GPS difference is so much large in Nigeria.", "output": {"entities": {"named_data": ["LSMS-ISA surveys", "GHS-Panel", "GHS-Panel"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001776", "page": 8, "chunk": 1, "title": "land measurement bias and its empirical implications evidence from a validation exercise", "pdf_url": "https://local/prwp/land-measurement-bias-and-its-empirical-implications-evidence-from-a-validation-exercise.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "LSMS-ISA surveys", "label": "NAMED_DATA", "score": 0.7759618163108826, "start": 68, "end": 84, "probe_score": 0.6001, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "GHS-Panel", "label": "NAMED_DATA", "score": 0.6665964126586914, "start": 804, "end": 813, "probe_score": 0.0, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "GHS-Panel", "label": "NAMED_DATA", "score": 0.6208656430244446, "start": 875, "end": 884, "probe_score": 0.0051, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<br>people above 16 were<br>able to prove their<br>identity digitally while<br>receiving e-Services<br>|NITA-U<br>|\n|User satisfaction with effectiveness of<br>digital public services (gender<br>disaggregated)|Percentage of users of<br>digital public<br>services reporting<br>satisfaction with the<br>efficiency of the transaction<br>( gender disaggregated)<br>|<br>Annually<br>|online<br>surveys,<br>mobile and<br>web apps,<br>and surveys<br>|<br>U-report, online<br>surveys, mobile and<br>web apps, and surveys<br>|NITA-U<br>|\n|Public and private entities in compliance<br>with National Information Security<br>Framework (NISF) through audits<br>|<br>Number of public and<br>private entities in<br>compliance with the<br>National Information<br>Security Framework (NISF)<br>through audit program<br>|Annually<br> <br>|<br>Audit reports<br> <br>|NITA-U monthly reports<br> <br>|NITA-U<br> <br>|\n|Periodic publication of citizen<br>engagement reports on grievance redress|<br>Periodic publication of<br>citizen engagement reports|Annually<br>|U-report,<br>online|Four(4) reports will be<br>published per year for a|NITA-U<br>|\n\n\nPage 43 of 76", "output": {"entities": {"named_data": [], "descriptive_data": ["NITA-U monthly reports", "citizen engagement reports"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000023", "page": 55, "chunk": 1, "title": "Uganda - Digital Acceleration Project", "pdf_url": "http://documents.worldbank.org/curated/en/473041622944887337/pdf/Uganda-Digital-Acceleration-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "NITA-U monthly reports", "label": "DESCRIPTIVE_DATA", "score": 0.5425897836685181, "start": 847, "end": 869, "probe_score": 0.0049, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "citizen engagement reports", "label": "DESCRIPTIVE_DATA", "score": 0.5617794990539551, "start": 1003, "end": 1029, "probe_score": 0.0987, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "> <br>JPIP has recorded some key achievements, including on**infrastructure** (construction under way or<br>completed at 17 sites; a Directorate of Building Services created);**performance management** (performance<br>contracts rolled out to court stations; and a new administrative data and case management system<br>implemented);**backlog reduction** (almost 50,000 very old cases resolved); skills development (3100 people<br>have been trained);**strategic and administrative reform** (launches of the Judiciary Strategic Plan; High<br>Court Registry Operations Manual; and the Human Resources and Financial Management Policies and<br>Procedures Manual).<br> <br>A mid-term review was undertaken from March to July 2015. The task team and key justice stakeholders i)<br>analyzed project data (including on procurement and disbursement bottlenecks), as well as performance data<br>emerging from JPIP-funded initiatives (including the new case management system, court user and<br>employee engagement surveys, the national case census and performance contracts) along with population<br>surveys, and ii) facilitated extensive consultations with staff, judicial officers and management, CSOs,<br>donors, the private sector, constitutional bodies, legal practitioners and academics.<br> <br>The key findings of the MTR were: i) the overall project design and implementation structure has made it<br>difficult to achieve effective, coherent and noticeable results. Structuring the project’s components by input<br>types (e.g. ‘training’, ‘infrastructure’), involving a large number of implementing units (21) and an annual<br>work planning process oriented around the needs of each unit has undermined a focus on development<br>outcomes, increased transaction", "output": {"entities": {"named_data": [], "descriptive_data": ["employee engagement surveys", "national case census"], "vague_data": ["project data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018521", "page": 5, "chunk": 1, "title": "Kenya - Judicial Performance Improvement Project : restructuring", "pdf_url": "https://documents.worldbank.org/curated/en/808831467995387617/pdf/RES19393-PJPR-P105269-PUBLIC-Restructuring-Paper-Finalized.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "project data", "label": "VAGUE_DATA", "score": 0.7333726286888123, "start": 782, "end": 794, "probe_score": 0.1686, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "employee engagement surveys", "label": "DESCRIPTIVE_DATA", "score": 0.5914020538330078, "start": 982, "end": 1009, "probe_score": 0.6293, "gold": "NON_MENTION", "gold_tier": "flip"}, {"text": "national case census", "label": "DESCRIPTIVE_DATA", "score": 0.8150312304496765, "start": 1015, "end": 1035, "probe_score": 0.2159, "gold": "DATA_MENTION", "gold_tier": "human-final"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda: Roads and Bridges in the Refugee Hosting Districts Project (P171339)\n\n\n|Indicator Name|PBC|Baseline|End Target|\n|---|---|---|---|\n|in place (Text)||||\n|Crash data entered into system, publicly reported, and used in<br>decision making (Yes/No)||No|Yes|\n|Annual number of fatalities or serious injuries involving<br>construction vehicles or at construction sites (Number)<br>||0.00|0.00|\n\n\n\n\n\n\n\n\n\n\n\n\n\n|RESULT_FRAME_TBL_IO|Col2|Col3|Col4|\n|---|---|---|---|\n|<br> <br>**Indicator Name**<br>|<br>**PBC**<br>|<br>**Baseline**|<br>**End Target**|\n|**Road Upgrading Works**|**Road Upgrading Works**|**Road Upgrading Works**|**Road Upgrading Works**|\n|Roads rehablitated (CRI, Kilometers)||0.00|105.00|\n|Roads rehabilitated - rural (CRI, Kilometers)||0.00|105.00|\n|Roads rehabilitated - non-rural (CRI, Kilometers)||0.00|0.00|\n|Increase in road user satisfaction on the Project road corridor<br>(dis-aggregated by gender, refugees, hosts) (Text)||Baseline surveys to be done|Rating of 4 out of 5|\n|Local labor among unskilled employment created under the<br>works contracts (dis-aggregated by gender, refugees", "output": {"entities": {"named_data": [], "descriptive_data": ["Crash data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 56, "chunk": 0, "title": "Uganda - Roads and Bridges in the Refugee Hosting Districts/Koboko-Yumbe-Moyo Road Corridor Project", "pdf_url": "http://documents.worldbank.org/curated/en/834931600048847296/pdf/Uganda-Roads-and-Bridges-in-the-Refugee-Hosting-Districts-Koboko-Yumbe-Moyo-Road-Corridor-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Crash data", "label": "DESCRIPTIVE_DATA", "score": 0.6922372579574585, "start": 179, "end": 189, "probe_score": 0.065, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Chapter 5\n\n\n**•** **Complementary pathways** can expand third country solutions, ease pressure on host\ncountries and enhance refugees’ self-reliance, including through education pathways or\nlabour mobility. <sup>**40**</sup>\n\n**•** **Family Reunification**, a right enshrined in international law as well as national laws around the\nworld, allows refugees, IDPs and returnees to look after each other, and to start new lives\ntogether.\n\nAssessing and reporting on whether **IDPs have overcome their displacement related**\n**vulnerabilities** requires a multi-faceted, comprehensive approach, as set out in the international\nrecommendations on internally displaced persons statistics (IRIS). <sup>**41**</sup> This can take place in IDPs’\nplace of habitual residence (i.e. after return), in their current place of displacement, or after settling\nelsewhere in their country. In almost all countries in which people have been internally displaced,\nthe availability of data to inform this approach remains extremely limited and efforts to generate\nand improve such data to better measure durable solutions for IDPs continue. In the meantime,\nUNHCR continues to report on **IDPs that have returned to their place of origin** .\n\n\nFigure 12 **| Durable solutions for refugees in the first six months of each year | 2019-2023**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n2019 2020 2021 2022 2023\n\n*Resettlement figures are according to government statistics.\n\n\n###### **Refugee returns**\n\nIn the first half of 2023, 404,000 refugees voluntarily\nreturned from 63 different countries of asylum to 23\ncountries of origin (see Figure 12). Most spontaneous\nreturns that took place in the first half of the year\noccurred in contexts not entirely conducive to return\nin safety and dignity, and they may not be", "output": {"entities": {"named_data": [], "descriptive_data": ["government statistics"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001065", "page": 26, "chunk": 0, "title": "UNHCR Mid-Year Trends 2023", "pdf_url": "https://reliefweb.int/attachments/a13b0f58-8b05-4652-84d7-e150dd9e7c6c/Mid-year-trends-2023.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "government statistics", "label": "DESCRIPTIVE_DATA", "score": 0.8655892610549927, "start": 1409, "end": 1430, "probe_score": 0.9171, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", 2016_\n_Note:_ BEmONC _=_ Basic Emergency Obstetric and Neonatal Care; CEmONC = Comprehensive Emergency\nObstetric and Neonatal Care; ICCM = integrated community childhood management; KMC = kangaroo mother care;\nLLIN = long-lasting insecticide treated bednets; PNC = post-natal care; SGBV = sexual and gender based violence;\nBCC = behavior change communication; IMNCI = integrated management of neonatal and childhood illnesses;\nEMTCT = elimination of mother to child transmission of HIV; ART = antiretroviral therapy; MPDR = maternal and\nperinatal death reviews; IEC = information, education, and communication; IPT = Intermittent Presumptive\nTherapy; FP = Family Planning; PAC = Post Abortal Care; Births, Deaths Registration.\n\n\n\n36", "output": {"entities": {"named_data": ["Births, Deaths Registration"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019169", "page": 47, "chunk": 2, "title": "Uganda - Reproductive, Maternal, and Child Health Services Improvement Project", "pdf_url": "https://documents.worldbank.org/curated/en/854971471534008736/pdf/PAD-07182016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Births, Deaths Registration", "label": "NAMED_DATA", "score": 0.5788539052009583, "start": 700, "end": 727, "probe_score": 0.2208, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " (a) Designated Account (DA) denominated in U.S.\ndollars where disbursements from IDA will be deposited and payment in U.S. dollars will be made from and (b)\nProject Account: This will be denominated in local currency. Transfers from the DA (for payment of transactions\nin local currency) will be deposited on this account in accordance with project objectives.\n\n\n27. The signatories for the project accounts will be in accordance with the Public Finance Management Act,\nTreasury Accounting Instructions, and the National Information Technology Authority Act 2009.\n\n\n**Disbursement Arrangements**\n\n\n28. The project will be on a Report Based Disbursement Method. An initial disbursement will be deposited in\nthe project DA based on a six-month cash flow forecast for the project based on the approved work plan.\nSubsequent disbursement will be based on the semi-annual IFRs submitted to the World Bank together with the\nrelevant applications. The IFRs will be submitted for disbursement every six months as a minimum but can submit\nmore requests as need arises. In compliance with the report-based guidelines, the project will be expected to: (a)\nsustain satisfactory FM rating during project supervision, (b) submit IFRs consistent with the agreed form and\ncontent within 45 days of the end of each reporting period, and (c) submit a Project Audit Report by the due date.\n\n\nPage 59 of 76", "output": {"entities": {"named_data": [], "descriptive_data": ["semi-annual IFRs"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000023", "page": 71, "chunk": 1, "title": "Uganda - Digital Acceleration Project", "pdf_url": "http://documents.worldbank.org/curated/en/473041622944887337/pdf/Uganda-Digital-Acceleration-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "semi-annual IFRs", "label": "DESCRIPTIVE_DATA", "score": 0.6152121424674988, "start": 856, "end": 872, "probe_score": 0.083, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Emergency Food and Nutrition Security Project (P163559)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Indicator Name|Core|Unit of<br>Measure|Baseline|End Target|Frequency|Data Source/Methodology|Responsibility for<br>Data Collection|\n|---|---|---|---|---|---|---|---|\n|**Name:**Amount of TSF<br>availed to beneficiaries||Metric<br>ton|0.00|5.00|Monthly<br>|Progress reports<br>|MAFS/WFP/UNICEF<br>|\n|<br>Description:|<br>Description:|<br>Description:|<br>Description:|<br>Description:|<br>Description:|<br>Description:|<br>Description:|\n|||||||||\n|**Name:**Amount of seeds<br>and planting materials<br>distributed to eligible<br>beneficiaries||Metric<br>ton|0.00|300.00|Seasonally<br>|Progress reports<br>|MAFS/FAO/NGOs<br>|\n|<br>Description:|<br>Description:|<br>Description:|<br>Description:|<br>Description:|<br>Description:|<br>Description:|<br>Description:|\n|||||||||\n|**Name:**Number of animals<br>vaccinated against<br>common diseases||Number|0", "output": {"entities": {"named_data": ["South Sudan Emergency Food and Nutrition Security Project"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000038", "page": 38, "chunk": 0, "title": "South Sudan - Emergency Food and Nutrition Project", "pdf_url": "http://documents.worldbank.org/curated/en/713081494122547885/pdf/South-Sudan-PAD-04282017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "South Sudan Emergency Food and Nutrition Security Project", "label": "NAMED_DATA", "score": 0.6653256416320801, "start": 19, "end": 76, "probe_score": 0.0791, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "24", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007644", "page": 25, "chunk": 0, "title": "wps8746", "pdf_url": "https://local/prwp/wps8746.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*\n\n\n**A.** **PDO**\n\n\n19. **The development objectives of the proposed Project are** to provide regular cash\ntransfers to extreme poor and vulnerable households with children in selected areas while\nstrengthening the delivery mechanisms for the development of a basic social safety net system.\nVulnerable households are defined as food insecure households.\n\n20. **The key delivery mechanisms for a basic social safety net system will include** a\ntargeting process with a beneficiary database, a management information system with a payment\nmodule, and a basic monitoring and evaluation system.\n\n\n**Project Beneficiaries**\n\n21. **The direct project beneficiaries are the households registered in the beneficiary**\n**database, which receive the cash transfers** . The direct beneficiaries within the household are:\n(i) women – as cash transfer recipients and targets of some of the behavior change activities; and\n(ii) children under 12 years of age – as targets of the behavior change activities and human capital\ninvestments. Other direct beneficiaries also include the two implementing agencies – the\nSEP/CNPS and the Social Assistance and National Solidarity Directorate of the MDPHASG –\nthrough capacity-strengthening activities. Indirect beneficiaries include: households living in the\n_collines_ where the cash transfer program and its complementary interventions operate through the\n_colline_ -level behavior change triggered by promotion activities and the impacts of the cash\n\n\n7", "output": {"entities": {"named_data": [], "descriptive_data": ["beneficiary database"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000157", "page": 17, "chunk": 1, "title": "Burundi - Social Safety Nets Project", "pdf_url": "http://documents1.worldbank.org/curated/en/900951482030099834/pdf/1482030098559-000A10458-PAD-Burundi-SSN-11282016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "beneficiary database", "label": "DESCRIPTIVE_DATA", "score": 0.8006970286369324, "start": 470, "end": 490, "probe_score": 0.0387, "gold": "NON_MENTION", "gold_tier": "flip"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " program. These <sup>will be abridged</sup> <sup>so</sup> <sup>that key policies</sup> <sup>and procedures</sup> <sup>are</sup>\nclearly understood by beneficiaries, <sup>and when appropriate</sup> <sup>translated into the local</sup> <sup>language.</sup> <sup>The</sup>\nHandbooks are an integral part of the <sup>Operations</sup> <sup>Manual</sup> <sup>and are annexed</sup> <sup>to the</sup> <sup>manual. The</sup>\nManual and Handbooks will be used <sup>by other partners</sup> <sup>supporting</sup> <sup>NaCSA</sup> <sup>including</sup> <sup>AfDB,</sup> <sup>DflD</sup>\n\nand UNDP.\n\nAn Inter-agency Forum, described <sup>in the Manual,</sup> <sup>will</sup> <sup>be organized</sup> <sup>in each</sup> <sup>district and</sup>\nwill meet on a quarterly basis and <sup>share information.</sup> <sup>A National</sup> <sup>Project Approval</sup> <sup>Committee</sup> <sup>as</sup>\n\n\n_-9-_", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000052", "page": 13, "chunk": 4, "title": "Croatia - Municipal Environmental Infrastructure Project", "pdf_url": "http://documents1.worldbank.org/curated/en/367181468770702078/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". The data for these indicators will be collected every six months during the RAP\nimplementation by the implementing agency which is KIMAWASCO, SCRCC and an\nindependent NGO working in the area to ensure triangulation of data. LRCCs will also assist with\nthe collection of monitoring data of the RAPs implementation.\n\n\nFinancial records will be maintained by KIMAWASCO to permit calculation of the final cost of\nresettlement and compensation per individual or household and they will be included in the\nmonitoring report. The statistics will also be provided to the external independent consultant/\nagency that will be contracted on an annual basis to monitor the implementation of the RAPs.\n\n\n**_Abbreviated Resettlement Action Plan for_**\n**_Kilifi Sanitation Development Projects under KIMAWASCO in Kilifi County_** **_6-1_**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["monitoring data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000444", "page": 30, "chunk": 1, "title": "Kenya - Water and Sanitation Development Project : Resettlement Plan (Vol. 6 of 3) : Abbreviated Resettlement Action Plan Report for Kilifi Ablution - Mtaani Kibaoni", "pdf_url": "https://documents.worldbank.org/curated/en/099015003242286733/pdf/P1566340deb18005408f7902c7448249f90.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "monitoring data", "label": "VAGUE_DATA", "score": 0.6527010202407837, "start": 272, "end": 287, "probe_score": 0.0518, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". At the end of 2022, sex-disaggregated\ndata was available for 75 per cent of the 4.4\nmillion stateless people reported worldwide. Data\ndisaggregated by both sex and age was reported for\n62 per cent of the population.\n\n\nBased on the data available for 75 per cent of the\nstateless population, slightly more women and girls\nare stateless (51 per cent) than men and boys. In\nBangladesh, where the largest stateless population\nis reported, just over half of the stateless populations\nare children (53 per cent).\n\n\n\n46 UNHCR > **GLOBAL TRENDS 2022**", "output": {"entities": {"named_data": [], "descriptive_data": ["sex-disaggregated\ndata"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001233", "page": 45, "chunk": 1, "title": "Global Trends: Forced Displacement in 2022", "pdf_url": "https://reliefweb.int/attachments/bd8c87c6-0df8-4a74-ad7e-4c4ae18f4b34/global-trends-report-2022.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "sex-disaggregated\ndata", "label": "DESCRIPTIVE_DATA", "score": 0.8205932378768921, "start": 22, "end": 44, "probe_score": 0.7403, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "neighboring countries. The payment mechanisms that will be selected, through a competitive\nbidding process, will demonstrate the following competencies: ability to pay, accessibility (safe\npayment network and good connectivity), transparency, proven reliability, acceptable transaction\ncosts, efficiency, capacity of planning and monitoring. Payment providers may differ in each\nprovince (or other geographical grouping as some of the selected communes are contiguous) to\nguarantee accessibility across the program’s area of operation. The payment study has identified\npotential bank and mobile providers in all provinces.\n\n12. **Co-responsibilities and verification.** The cash transfer program aims to provide\npredictable and regular income to extreme poor households so as to enable them to increase\nconsumption and invest in the foundations of their children’s human capital. Given the limited\nadministrative capacity, beneficiary households will initially be required to participate in the\nbehavior change communication activities described in sub-component 1.2 but the payments will\nnot be conditional on attendance. As the provision of basic services and the capacity to monitor\nimprove, the program will explore the provision of making the payments conditional on the actual\nparticipation in the BCC activities and possibly on the use of basic services (verified through the\nhealth card or the primary school attendance records). Participation in the behavior change\nactivities will be recorded in the MIS. The cash transfer recipient, her husband and other adults\nwill be expected to participate in the main BCC activities, with absences collected and transmitted\nto the provincial and central program offices. In a first step, a local program official (from the\nCFDC) and the _colline_ focal point will visit the household, assess the reason for missing the session\n(illness, accident) and encourage them to participate in the future. If and when payments become\nconditional, in a second step, two consecutive absences without justification may cause the\nsuspension of half of the following payment. Decisions about conditionalities will be taken at the\nproject mid-term based", "output": {"entities": {"named_data": ["MIS"], "descriptive_data": ["primary school attendance records"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000157", "page": 50, "chunk": 0, "title": "Burundi - Social Safety Nets Project", "pdf_url": "http://documents1.worldbank.org/curated/en/900951482030099834/pdf/1482030098559-000A10458-PAD-Burundi-SSN-11282016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "primary school attendance records", "label": "DESCRIPTIVE_DATA", "score": 0.9049555659294128, "start": 1402, "end": 1435, "probe_score": 0.2661, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "MIS", "label": "NAMED_DATA", "score": 0.6304317712783813, "start": 1510, "end": 1513, "probe_score": 0.0964, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ",\nFlash appeals and other appeals, the Bangladesh Rohingya JRP and the Venezuela RMRP. For all\nother RRPs, requirements data from the RFT was used, with the exception of Ukraine, for which\nrequirements data was sourced from the RRP document. Note that child protection requirements for\nthe Syria RRP do not include Egypt and Turkiye, for which data are not available.\n\nWhen calculating the GHO total requirements, the figures for some regional refugee response plans\nare adjusted to avoid double counting their overlap with the refugee response chapter of HRPs.\nHowever, at the level of child protection, the refugee response requirements under HRPs are not\ndisaggregated. Substituting RFT data on child protection requirements for those on FTS allows for a\nmore complete and accurate picture of child protection requirements without double counting.\n\nNote on calculation of overall child protection funding received:\n\nTo calculate total child protection funding received, data from FTS was used for all HRPs, Flash\nAppeals and other appeals, the Bangladesh Rohingya JRP, the Venezuela RMRP and Ukraine. For all\nother RRPs, tracked funding data from the RFT was used.\n\nNote on coordinated appeals analysed:\n\nChild protection coverage rates were calculated for all 26 2023 HRPs, Bangladesh Rohingya JRP\nand Venezuela RMRP (using FTS data) and 16 country level refugee plans across five regional RRPs\n(using RFT data). These country level plans were selected where data were available for both funding\nrequirements and funding received, for the response overall and for child protection. No countries\nunder the Ukraine RRP were included in the plans analysed, and Ukraine was excluded from the\ncalculation of overall RRP coverage rates as child protection funding data on RFT were incomplete\nand, as with other regional plans, no country level data were available on RFT or FTS.\n\n\nAll data was correct as of 9th July 2024.\n\n\nAnalysis of funding for child protection in humanitarian action in 2023 24", "output": {"entities": {"named_data": ["data from FTS"], "descriptive_data": ["requirements data from the RFT", "tracked funding data from the RFT", "child protection funding data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001396", "page": 23, "chunk": 1, "title": "Unprotected: Analysis of funding for child protection in humanitarian action in 2023 [EN/AR]", "pdf_url": "https://reliefweb.int/attachments/d83e4226-2276-42dc-b7c3-61adf6b752ed/Unprotected%20--%20Analysis%20of%20funding%20for%20child%20protection%20in%20humanitarian%20action%20in%202023.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "requirements data from the RFT", "label": "DESCRIPTIVE_DATA", "score": 0.6366464495658875, "start": 107, "end": 137, "probe_score": 0.9729, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from FTS", "label": "NAMED_DATA", "score": 0.6755688786506653, "start": 973, "end": 986, "probe_score": 0.9532, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "tracked funding data from the RFT", "label": "DESCRIPTIVE_DATA", "score": 0.7117105722427368, "start": 1124, "end": 1157, "probe_score": 0.9462, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "child protection funding data", "label": "DESCRIPTIVE_DATA", "score": 0.640242874622345, "start": 1737, "end": 1766, "probe_score": 0.8043, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " a year and the audit reports\nwill be shared with MAFS, MoFP and the Bank for review and comments.\n\n\n**Funds flow and Disbursement arrangements**\n\n\n25. Disbursement of the Grant will use advances, reimbursement, direct payments and payments under\nSpecial Commitments including full documentation or against statements of expenditure, as appropriate.\nFor components 1 and 2, a lump sum amount will be disbursed in the form of UN blanket commitments\nto WFP and UNICEF (Component 1), and FAO (Component 2) following submission of a duly executed\ncontract between the respective UN agency and MAFS and a Payment Request from that agency (see Fig\nA2.2). WFP, UNICEF and FAO will then provide quarterly funds utilization reports to the PIU within 45 days\nafter the end of the quarter, which will be used to account for expenditures in the Bank records.\n\n\n26. For Component 3, the proceeds of the Grant will be disbursed into the DA following the transaction–\nbased SoE method. The PIU will submit Withdrawal Applications accompanied by SoE incurred to the\nWorld Bank for replenishment of the DA. The project will also maintain a local currency sub‐project\naccount for making payments denominated in local currency. Funds will only be transferred from the main\nDA to the local currency sub‐account in order to meet immediate payment obligations. No significant cash\nbalances will be maintained in local currency to reduce the foreign exchange exposure risk. MAFS will be\nresponsible for initiating, incurring and authorizing expenditures under the Project in accordance with the\nspecified procedures and initiating the payment process with all the required supporting documentation.\nDetailed disbursements arrangements are documented in the Disbursement Letter.\n\n\nPage 48 of 80", "output": {"entities": {"named_data": [], "descriptive_data": ["Bank records"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000038", "page": 51, "chunk": 1, "title": "South Sudan - Emergency Food and Nutrition Project", "pdf_url": "http://documents.worldbank.org/curated/en/713081494122547885/pdf/South-Sudan-PAD-04282017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Bank records", "label": "DESCRIPTIVE_DATA", "score": 0.7165502309799194, "start": 833, "end": 845, "probe_score": 0.0018, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### 1.8 11\n\n\n\nCurrent account balance . **.2**\n\n\n\nFinancing items (net)\nChanges in net reserves .. .\n_Memo:_\nReserves including gold _(US$ millions)_\nConversion rate _(DEC, locaW/US$)_ 177.7 177.7 177.7\n\n\n**EXTERNAL DEBT and RESOURCE FLOWS**\n\n**1979** **1989** **1998** **1999**\n_(US$ millions)_ **Compositlon of total debt, 1998 (USS milIlona)**\nTotal debt outstanding and disbursed 26 **179** 288\nIBRD 0 0 0\nIDA 0 26 50 49 G 15 B\n\nTotal debt service 2 15 6\nIBRD 0 0 0 C: 9\nIDA 0 0 1 1\n\nComposition of net resource flows E: 119\nOfficial grants 5 32 48\nOfficial creditors -1 3 2\nPrivate creditors 0 -1 0\nForeign direct investment 0 0 6 D: **95**\nPortfolio equity 0 0 0\n\nWorld Bank program\n\nCommitments 0 9 3 A  - IBRD E - Bilateral\nDisbursements 0 2 2 1 B - IDA D - Other rrultilateral F **-** Private\nPrincipal repayments 0 0 0 0 C- IMF G - Short-term\nNet flows 0 2 2 1\nInterest payments 0 0 0 0\nNet transfers 0 2 1 1\n\n\nNote: This table was produced from the Development Economics central database. 9/13/00", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:021277", "page": 63, "chunk": 1, "title": "Kenya - Nairobi Water Supply Project", "pdf_url": "https://documents.worldbank.org/curated/en/995321468091475515/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9087857007980347, "start": 960, "end": 998, "probe_score": 0.6996, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<u>Resettlement Action Plan for ESTDP-Lalibela                                           Page</u> **<u>57</u>** <u>of</u> **<u>85</u>**\n\n\narchitect and a construction technologist supported by assistants did all the measuring and sketches of\nthe built up structures. A general guideline was developed for the specification of construction\ncomponents based on the specification from the Zone administration for such purposes and general\nengineering practice for property valuation.\n\n\nThe method used for the assessment of the value of properties followed standard quantity surveying\nmethod. All built up structures were measured and based on the measurement of components of\nconstructions, sections were drawn and materials of construction were noted. The drawn plans and\nsections were then used to quantify the different components of the constructions\n\n\nThe quality of the quantity surveying was assured as house to house survey was done and all structures\nwere measured reasonably accurately <sup>21</sup> [^21: The measurement of structures was done by a new 50 meter long measuring tape. The houses are not orthogonal\n(rectangular or clear shaped) and do not have uniform wall thickness. Moreover, there are additions over a long\nperiod of time which made sketching of the units difficult. However, for all practical purposes, all structures were\nmeasured fairly accurately. The measurement was checked and verified by each owner and found to be accurate.] . Some of the components could not be measured or accurately\nrepresented as the houses do not have engineering plans before construction. Such components include\ndepth of foundations, under-base construction of floors, gauges of corrugated iron sheet roofs, and\ndepth and construction materials of dry pit latrines. In all cases procedures which ensured advantages of\nthe owners were adopted.\n\n\nThe unit rate provided by the zone administration was found to reflect reasonably the market value for\nall construction components. However, the unit rate directive does not cover all construction\ncomponents. The items not covered by the directive were estimated through market research. These", "output": {"entities": {"named_data": [], "descriptive_data": ["house to house survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013676", "page": 56, "chunk": 0, "title": "Ethiopia - Sustainable Tourism Development Project : resettlement plan (Vol. 7 of 7) : Resettlement action plan for Lalibela town", "pdf_url": "https://documents.worldbank.org/curated/en/481931468252604242/pdf/RP7750v70P09810L0RAP0REPORT00Vol-I0.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "house to house survey", "label": "DESCRIPTIVE_DATA", "score": 0.918300211429596, "start": 908, "end": 929, "probe_score": 0.0013, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ",\nwith observers reporting that personal data continue to be collected in violation of the law’s principles. <sup>39</sup> In\nresponse, a Data Protection Office (DPO)—whose mandate will be to lead the implementation of the law, issue\ncodes and regulations, and provide for administrative, civil, or criminal sanctions and penalties—must be\nestablished, resourced, and enabled. Due to the present hold put on creating new government agencies, it is\nenvisioned that this DPO will be established as an independent entity under NITA-U. While recruitment of\npersonnel has started, the DPO will require substantial capacity building and logistical set-up. The project seeks\nto support some of those priority efforts.\n\n**17.** **The WB has partnered with the GoU in its efforts to address these bottlenecks and leverage**\n**opportunities through the RCIP-5 Project,** currently under implementation and set to close in February 2022.\n\n\n38 International Telecommunications Union, 2018., _Global Cybersecurity Index 2018_ . https://www.itu.int/dms_pub/itu-d/opb/str/D-STRGCI.01-2018-PDF-E.pdf\n39 https://privacyinternational.org/news-analysis/3385/one-year-what-has-ugandas-data-protection-law-changed\n\n\nPage 6 of 76", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["personal data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000023", "page": 18, "chunk": 2, "title": "Uganda - Digital Acceleration Project", "pdf_url": "http://documents.worldbank.org/curated/en/473041622944887337/pdf/Uganda-Digital-Acceleration-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "personal data", "label": "VAGUE_DATA", "score": 0.5558508634567261, "start": 32, "end": 45, "probe_score": 0.1913, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<u>Resettlement Action Plan for ESTDP-Lalibela                                           Page</u> **<u>9</u>** <u>of</u> **<u>85</u>**\n\n\nThe RAP will be implemented according to the implementation schedule that outlines the sequence of\nactivities and possible simultaneity of tasks to be accomplished. This implementation schedule will be\npresented to the impacted communities in a half day workshop prior to commencement of activities. It\nis suggested that the land acquisition process has to be conducted first. This is to be followed by ground\nsurveying, site development work and allotment of plots with clear demarcations. Parallel with this, the\nlivelihood and income restoration program shall be initiated. Once plots are allotted through lottery\nmethod in accordance to their plot category, the compensation money shall be automatically paid\ntogether with the acquisition of title deed and the approval of building permit. Construction of houses\nshall be carried out while the project affected persons reside in their existing homes and the\nmunicipality should support the elderly and other vulnerable persons in building their homes. Once the\nresettlement site is developed and the homes are constructed, the project affected persons will be\nrelocated to their new settlement site by demolishing their old homes.\n\n\nThe RAP includes the socio-economic situation of households in the Core Zone (Adishade, Chifrgoch\nand Gebriel Sefer), Mikael Ghibi and the host community in Kurakur area. The census indicated that\nthe number of households living in the three localities ( _Adishadie, Chifrgoch and Gebriel sefer_ ) is 562\nwith a total of 2025 household members living in 430 housing units. The survey also revealed that\nabout 59 and 41 percent of the housing units in the three localities were occupied by home owners and\ntenants, respectively. About 63 percent of the household members claim that they have lived in the\nCore Zone since birth and still 18 percents indicated", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["census"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:013676", "page": 8, "chunk": 0, "title": "Ethiopia - Sustainable Tourism Development Project : resettlement plan (Vol. 7 of 7) : Resettlement action plan for Lalibela town", "pdf_url": "https://documents.worldbank.org/curated/en/481931468252604242/pdf/RP7750v70P09810L0RAP0REPORT00Vol-I0.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "census", "label": "VAGUE_DATA", "score": 0.5567845702171326, "start": 1499, "end": 1505, "probe_score": 0.6711, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Figure 2: Model Fit - Labor force participation around retirement\n\n\n51", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000478", "page": 53, "chunk": 0, "title": "gender pension gaps in a private retirement accounts system a dynamic model of household labor supply and savings", "pdf_url": "https://local/prwp/gender-pension-gaps-in-a-private-retirement-accounts-system-a-dynamic-model-of-household-labor-supply-and-savings.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " is about three times the current operating budget of NFA; thus, the**\n**project’s long-term impact will be the sustainability of NFA.** Similarly, the 1500ha\nestablished under Nile Basin Reforestation Project, Rwoho is expected to generate about\nUShs 46,950,000,000 (US$16,78 million) from round wood.\n\n_Projected sales from Charcoal from Kasagala CFR_\nAccording to a feasibility study carried out for carbon trade in Kasagala by Unique Forestry\nconsultants, assuming five years of no harvesting and stocking, the area could produce about\n1tone of charcoal (200 bags) annually and generate about UShs 14,000,000 (about US$\n5,600) at current Kampala price of UShs. 70,000 per bag. The trend in charcoal prices shows\na steady increase from UShs. 8,000 in 2005 to 70,000 in 2012 in Kampala, especially as the\nresource will become more geographically distant and scarce. With good branding and\nmarketing even higher prices are possible. Under the circumstances, if the area is harvested in\nblock rotations, it is likely to produce UShs 210 million (approximately US$84,000) in 20\nyears.\n\n**(ii)** **MSWC carbon finance activities** <sup>**119**</sup>\n\nThe assessment below, although using multiple estimates and assumptions, provides an\noverview of the carbon finance situation.\n\n\n**1. Assessment case: CPA Jinja** _(most performing and first CPA)_\n\n\n118 Revenues are projected based on conservative estimates of site productivity and current market prices (NFA\naverage bidding rates for round wood 2012/13).\n119 Sources used: PoA 2008, WB 04/2013 verification mission document, MoWE SPRs 2010/11, 2011/12,\n2012/13.\n\n\n66", "output": {"entities": {"named_data": ["MoWE SPRs"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019460", "page": 76, "chunk": 4, "title": "Uganda - Second Environmental Management and Capacity Building Project", "pdf_url": "https://documents.worldbank.org/curated/en/876451468114257745/pdf/ICR21480P0730890Box0377356B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "MoWE SPRs", "label": "NAMED_DATA", "score": 0.8447074294090271, "start": 1576, "end": 1585, "probe_score": 0.9993, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " rural areas. Refugee women/girls are at high risk of\nseveral forms of GBV including sexual exploitation and abuse (SEA), rape, forced and child marriage and\nintimate partner violence (IPV) <sup>17</sup> . Socio-cultural norms, economic insecurity, alcohol and substance abuse,\nweak law enforcement, limited response services and capacity and, weak social support systems were\nidentified as the key drivers of GBV in the refugee camps. Studies also reveal that women in the refugee\ncamps are vulnerable to different forms of violence, including continuation of sexual violence cases against\nwomen coming from South Sudan <sup>18</sup> . Analysis from a qualitative study showcased that GBV increases during\nharvest time and when families receive cash payments, driven by conflicts over the use of income. <sup>19</sup> GBV is\nalso linked to women and girls (particularly refugees) acquiring fuel.\n\n\n12. **Gender inequalities are prevalent in refugee camps in Uganda.** Women and children comprise 82 percent\nof Uganda’s overall refugee population, about 56 percent of refugees are below the age of fifteen, and 25\npercent are younger than five years of age <sup>20</sup> . School enrollment and retention rates among girls in the\nrefugees hosting districts are exceptionally low, a result of their domestic responsibilities, child marriage,\nteenage pregnancy, long distances to schools, and lack of sanitation facilities and supplies, among other\nfactors <sup>21</sup> . A quantitative data collection in 18 refugee settlements across Uganda reveals that the capacity\nof younger people to engage in the labor market and become employable depends on their level of\neducation. Around 77 percent of women have only reached primary education which means that young\nwomen are less likely to compete in the labor market. The lack of formal jobs in refugee settlements leads\n\n\n11 This index reflects gender-based inequalities in three", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["quantitative data collection"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 14, "chunk": 1, "title": "Uganda - Roads and Bridges in the Refugee Hosting Districts/Koboko-Yumbe-Moyo Road Corridor Project", "pdf_url": "http://documents.worldbank.org/curated/en/834931600048847296/pdf/Uganda-Roads-and-Bridges-in-the-Refugee-Hosting-Districts-Koboko-Yumbe-Moyo-Road-Corridor-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "quantitative data collection", "label": "VAGUE_DATA", "score": 0.5940452218055725, "start": 1473, "end": 1501, "probe_score": 0.0094, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", & Rusu, A. B. (2013). Women’s legal rights over 50 years:\n\nprogress, stagnation or regression?. _World Bank Policy Research Working Paper_, (6616).\n\n\nHallward-Driemeier, M., & Gajigo, O. (2015). Strengthening economic rights and women’s\n\noccupational choice: The impact of reforming Ethiopia’s family law. _World Development_, 70,\n260-273.\n\n\nHyland, M., Djankov, S., & Goldberg, P. K. (2020). Gendered laws and women in the\n\nworkforce. _American Economic Review: Insights_, 2(4), 475-90.\n\n\nHyland, M., Djankov, S., & Goldberg, P. K. (2021). Do Gendered Laws Matter?. _LSE Financial_\n\n_Markets Group_ .\n\n\nIslam, A., Muzi, S., & Amin, M. (2019). Unequal laws and the disempowerment of women in the labour\n\nmarket: evidence from firm-level data. _The Journal of Development Studies_, 55(5), 822-844.\n\n\nJohnson, S. (2004). Gender norms in financial markets: Evidence from Kenya. _World Development_, 32,\n\n1355–1374.\n\n\nJoireman, S. F. (2008). The mystery of capital formation in Sub-Saharan Africa: women, property rights\n\nand customary law. _World Development_, 36(7), 1233-1246.\n\n\nKenny, C., & Patel, D. (2017). Gender laws, values, and outcomes: Evidence from the World Values\n\nSurvey. Center for Global Development Working Paper 452 (2017).\n\n\nKilara, T., Magnoni, B., & Zimmerman, E. (2014). The business case for youth", "output": {"entities": {"named_data": [], "descriptive_data": ["firm-level data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000597", "page": 24, "chunk": 1, "title": "idu01137fc5100ae204e9a0a0c20b39dddd48f92", "pdf_url": "https://local/prwp/idu01137fc5100ae204e9a0a0c20b39dddd48f92.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "firm-level data", "label": "DESCRIPTIVE_DATA", "score": 0.5380001664161682, "start": 728, "end": 743, "probe_score": 0.1031, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "the full sample – choice and nonchoice – and apply that level of skewness to all of the residuals in their\nsimulation exercise. <sup>24</sup> In addition, as noted above, they motivate dropping the high consumption\nobservations from the PK Bangladesh data set, the 16 observations with the highest consumption in\nparticular, that they call “the ones most responsible for the model‐violating skew in the error,” in an\neffort to reduce the “bias” from skewness.  However, a (weighted) 86 percent of these 16 observations\nare non-choice observations and thus cannot be implicated in any bias arising from skewness. These\nhigh consumption (i.e., non-poor) observations are primarily non-choice because they are so well off\nthey are ineligible for microcredit, and thus it is expected that their consumption would be at the righttail of the distribution. It also suggests that the level of skewness and excess kurtosis is much lower in\nthe sub-sample that matters, those with choice, than in the sub-sample most affected by the trimming\nstrategy of RM – those without choice. Moreover, even if the errors in the choice sub-sample have\nskewness and excess kurtosis, we have shown that identification that arises from the inclusion of\ncovariates in the model swamps any possibly faulty additional identification that may arise from\nspecifying error distributions when the first-stage is Tobit, and which is demonstrated below with the\nactual Bangladesh data. <sup>25</sup>\n\n\nReaders of RM may incorrectly form the view that the positive female effects estimated by PK are the\nresult of up to 16 observations having both female borrowers and very large values of household\nconsumption, a combination that one might expect to make female credit effects more positive. That is,\nit might be expected that a very few program participants who report doing extraordinarily well can\nmake a program look more effective than it is", "output": {"entities": {"named_data": ["PK Bangladesh data set"], "descriptive_data": [], "vague_data": ["Bangladesh data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005922", "page": 13, "chunk": 0, "title": "wps6801", "pdf_url": "https://local/prwp/wps6801.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "PK Bangladesh data set", "label": "NAMED_DATA", "score": 0.8703485131263733, "start": 237, "end": 259, "probe_score": 0.9317, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Bangladesh data", "label": "VAGUE_DATA", "score": 0.6365370154380798, "start": 1435, "end": 1450, "probe_score": 0.0776, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " refugees and host\ncommunities. In addition, the project will support the integration of these target groups into the National Social Registry\nto ensure that they have access to other social programs. The project will also identify other policy gaps related to\nrefugees and host communities and will finance technical assistance to develop adequate policies to close these gaps.\n\n77. On the operational side, refugees and host communities will benefit as well from the cash transfers, productive\ninclusion and jobs activities and accompanying measures on human capital development from Components 1 and 2 of\nthe project. The project will benefit at least 20,000 refugees and host community households. At least 40 percent of the\nbeneficiaries of this component will be refugees, which represents 8,000 refugee households (44 percent of their total).\n\n\n78. Targeting of refugees will be based on the development of a PMT using the socio-economic data already collected\nby the World Bank and UNHCR. Given the sensitivity of targeting in refugee camps, specific refugee targeting committees\ncomposed of refugee members will be formed and trained to help validate and potentially correct the beneficiary lists.\n\n79. ONPRA oversees coordinating and providing security to refugee camps. Several donors including the World Bank,\nthe European Union and UNHCR will provide support to refugees through different angles. The project will support\nONPRA to play their coordination and supervision role by providing human resources, technical, equipment and\noperational support and by organizing capacity building sessions with its staff members.\n\n80. The project will explore a collaboration with UNHCR for the quality control of the activities in the refugee camps\nand host communities. On top of ensuring that activities are delivered with high quality standards, UNHCR will be\nsupported to monitor and evaluate that the protection framework remains adequate.\n\n\nPage 27 of 86", "output": {"entities": {"named_data": ["National Social Registry"], "descriptive_data": [], "vague_data": ["socio-economic data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000130", "page": 31, "chunk": 1, "title": "Burundi - Cash for Jobs Project", "pdf_url": "http://documents1.worldbank.org/curated/en/768621641923064747/pdf/Burundi-Cash-for-Jobs-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "National Social Registry", "label": "NAMED_DATA", "score": 0.705193042755127, "start": 118, "end": 142, "probe_score": 0.0037, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "socio-economic data", "label": "VAGUE_DATA", "score": 0.6615017056465149, "start": 930, "end": 949, "probe_score": 0.0512, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nChad Energy Access Scale Up Project (P174495)\n\n\n\n\n\n\n\n\n\n\n\n|Table 6.2. Select Results of|the Survey Surveyed Provinces|Col3|Col4|Col5|\n|---|---|---|---|---|\n|<br> <br>|<br>**Surveyed Provinces**<br>|<br>**Surveyed Provinces**<br>|<br>**Surveyed Provinces**<br>|**Average**<br>|\n|<br> <br>|<br>**Guéra**<br>|<br>**Kanem**<br>|<br>**Logone**<br>**Occidental**<br>|<br>**Logone**<br>**Occidental**<br>|\n|Household size, number of people<br>|5.4<br>|4.6<br>|<br>6.8<br>|5.8<br>|\n|<br>Female-headed households, percentage<br>|<br>9.4<br>|<br>26.6<br>|<br>10.4<br>|<br>13.3<br>|\n|<br>Male-headed households, percentage<br>|<br>90.6<br>|<br>73.4<br>|<br>89.6<br>|<br>86.7<br>|\n|<br>Use of mobile money, percentage<br>|<br>12.0<br>|<br>11.0", "output": {"entities": {"named_data": ["Chad Energy Access Scale Up Project"], "descriptive_data": ["Survey Surveyed Provinces"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 90, "chunk": 0, "title": "Chad - Energy Access Scale Up Project", "pdf_url": "http://documents.worldbank.org/curated/en/860701648216750651/pdf/Chad-Energy-Access-Scale-Up-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Chad Energy Access Scale Up Project", "label": "NAMED_DATA", "score": 0.5814213156700134, "start": 19, "end": 54, "probe_score": 0.8523, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Survey Surveyed Provinces", "label": "DESCRIPTIVE_DATA", "score": 0.5875920653343201, "start": 110, "end": 135, "probe_score": 0.9685, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\neducational attainment from November 2022\nsurvey) to 19% (July-August 2023) higher\n\nearnings than the general population. <sup>36</sup>\n\n\nPoviat-level geographical distribution of\nUkrainian refugees is more concentrated in\nhigh productivity agglomerations, implying\n7% higher earnings than for other workers\nregistered for social security. <sup>37</sup>\n\n\nThere is no publicly available hard data on the\nsectoral distribution of Ukrainian refugees,\nwhich we proxy by the growth in employees\nwith Ukrainian citizenship registered for social\nsecurity since the outbreak of the full-scale\nwar in Ukraine (unfortunately this to some\nextent will be Ukrainian workers previously\npresent in Poland who changed jobs) – this\nimperfect proxy implies 7% lower earnings\nthan general workers. <sup>38</sup>\n\n\n\nSmaller firm sizes of employers\nof Ukrainian refugees imply their\n8% lower productivity (and thus earnings)\nfrom the general population. <sup>39</sup>\n\n\nMost of all, occupational distribution of\nUkrainian refugee workers from ZUS implies\n21% lower earnings from the general\npopulation when measured by nine large\noccupational groups and 23% lower by\ndetailed occupations. <sup>40</sup>\n\n\n\n5000 6000 7000 8000 9000 10000 11000 12000\n\n\n**Average monthly gross earnings in enterprise sector in poviat of employment in 2022**\n\n\nNatives and other immigrants\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n36  Note that these percentages are only indicative, as Ukrainian refugee educational attainment is assumed on the basis of November 2022 NBP\n(2023) survey for 18+ age group and July-August 2023 UNHCR (2023) survey for 15+ age group, while the general population is taken from the 2022\nLabour Force Survey for 15-74 (broadest available) age group, and earnings by educational attainment are taken from the GUS (2022) “Structure of\nwages and salaries by occupations in October 2020”.\n37  Note that the numbers of Ukrainian refugees and all workers", "output": {"entities": {"named_data": ["NBP\n(2023) survey", "UNHCR (2023) survey", "2022\nLabour Force Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 16, "chunk": 2, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "NBP\n(2023) survey", "label": "NAMED_DATA", "score": 0.7006943821907043, "start": 1504, "end": 1521, "probe_score": 0.0869, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHCR (2023) survey", "label": "NAMED_DATA", "score": 0.7259112000465393, "start": 1561, "end": 1580, "probe_score": 0.002, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2022\nLabour Force Survey", "label": "NAMED_DATA", "score": 0.8501085638999939, "start": 1647, "end": 1671, "probe_score": 0.5191, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " GBV,\ndeforestation and environmental management, and socioeconomic status informing refugee policy. The findings\nof these are being operationalized through WHR-financed projects including this one. These risks are then being\nmanaged jointly through effective in-country coordination mechanisms which include the UNHCR, OPM,\ndevelopment and humanitarian partners, and other parts of the GoU, spearheaded by the CRRF Steering Group,\nwhich meets quarterly. The WB co-chairs the CRRF Development Partners Group which provides another effective\nplatform to ensure joint management of the above risks, including on protection issues, with the GoU and other\nhumanitarian and development organizations. The project will work through these coordination mechanisms.\nRefugee Sector Response Plans referenced earlier have been developed to institutionalize refugee support within\nnational systems, and the JLIRP has strong digital components. The WB will work closely with the UNHCR to\ncontinually monitor the protection environment throughout project implementation, including on registration\ndata management and access to digital services.\n.\n\n\nPage 36 of 76", "output": {"entities": {"named_data": [], "descriptive_data": ["registration\ndata"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000023", "page": 48, "chunk": 1, "title": "Uganda - Digital Acceleration Project", "pdf_url": "http://documents.worldbank.org/curated/en/473041622944887337/pdf/Uganda-Digital-Acceleration-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "registration\ndata", "label": "DESCRIPTIVE_DATA", "score": 0.6030963659286499, "start": 1070, "end": 1087, "probe_score": 0.0098, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*|**987**|**530**|**1517**|**65.12**|**34.88**|**100%**|\n\n\n\n_<u>Source</u>_ : _Adapted from Kanungu District Education Department_\n\nConsidering the gender pattern of the 3 schools visited for the social assessment, all of them are headed\nby male head teachers but the proportion of female teachers is fair compared to the general district\npicture, that is, 33%, 33% and 40% for Kihembe, Nyamirama II and Nyamirama Twimukye PS\nrespectively. All the teachers at the schools are qualified except one male teacher at Nyamirama II PS\nwho is employed on private terms and is a Senior 4 leaver.\n\nThe illiteracy rate of women in Kanungu is much higher than that of men. Functional Adult Literacy\n(FAL) statistics show that both men and women participate, however females respond more to FAL than\nmales. For example the district had a total of 4998 learners in 2010 of which was about 80% (or 3989)\nwere females. Even the participation of FAL instructors is skewed in favour of women that is, 68% (or\n216) of the 316 instructors were female implying that it is also a domain left for women, after all they are\nthe most illiterate and besides, it is not an economically lucrative activity for men to enthusiastically\nparticipate.\n\n\n**8.3 Gender Disaggregated Data for Schools**\nGender disaggregated data on most parameters of primary education in Kanungu does not exist both at the\ndistrict and school level. The district education department does not have most gender disaggregated data\nfor schools as efforts to obtain these were unsuccessful. The only gender disaggregated data available at\ndistrict level is the number of children with special needs enrolled in school per class and the total number\nof teachers in the district", "output": {"entities": {"named_data": [], "descriptive_data": ["Functional Adult Literacy\n(FAL) statistics", "Gender Disaggregated Data", "Gender disaggregated data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:015739", "page": 58, "chunk": 1, "title": "Uganda - Global Partnership for Education (GPE) Teacher and School Effectiveness Project : indigenous peoples plan (Vol. 3 of 3) : Social assessment in Kaabong and Kanungu districts", "pdf_url": "https://documents.worldbank.org/curated/en/623441468316988425/pdf/IPP6560v30P133000PUBLIC00Box379832B.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Functional Adult Literacy\n(FAL) statistics", "label": "DESCRIPTIVE_DATA", "score": 0.6233813762664795, "start": 662, "end": 704, "probe_score": 0.9452, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Gender Disaggregated Data", "label": "DESCRIPTIVE_DATA", "score": 0.5806776881217957, "start": 1228, "end": 1253, "probe_score": 0.4287, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Gender disaggregated data", "label": "DESCRIPTIVE_DATA", "score": 0.516867458820343, "start": 1268, "end": 1293, "probe_score": 0.3546, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " is more uncertain, resulting in the\n\n\n\nneed to finance their consumption using\ncapital generated outside the country e.g.\nsavings from their home countries.\n\n\nHigh employment rate of Ukrainian\nrefugees translates into more workers and\nthus additional economic growth. In July\n2022, OECD estimated the contribution of\nUkrainian refugees to the labour force and\nemployment in European host countries,\nbased on a 2014 Labour Force Survey adhoc module that includes refugee labour\nmarket outcomes and 2019 LFS with\noutcomes of recent non-EU migrants.\nThey estimated that Ukrainian refugees\nwould increase employment in Poland by\n1.2-1.8% (Dumont & Lauren, 2022).\nAs refugee employment rates are higher\nthan expected, the actual increase is higher,\nbetween 1.4% and 2.2% (estimates of 0,230,35 million relative to LFS employment).\n\n\n##### To assess the impact of refugees on the Polish economy, a simulation was performed using the Deloitte D.Climate model 33,34 .\n\nIt is a general equilibrium model using consumer and producer optimalisation to\ncalculate changes in the economy in response to shocks. This allows to assess the\nimpact of shocks considering supply and demand channels as well as connections\nbetween different sectors of economy. This provides information about their total\nimpact on many aspects of the economy including the labour market, government\nrevenue as well as main economic aggregates. It is deemed the most appropriate\ntool to account for refugees’ multi-layered impact. To account for the effects of other\nshocks happening in the economy (such as the energy crisis) counterfactual analysis\nwas performed using the newest data for the Polish economy. In other words, we\nwere able to isolate the refugee inflow from all other shocks in the economy, like\nthe other macroeconomic consequences of the war in Ukraine. The results were\ncalculated for 2022 and 2023 with additional long-term analysis to check how the\neconomy would adapt assuming no new shocks including no counter-shocks <sup>35<", "output": {"entities": {"named_data": ["2014 Labour Force Survey", "2019 LFS"], "descriptive_data": ["newest data for the Polish economy"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 15, "chunk": 2, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "2014 Labour Force Survey", "label": "NAMED_DATA", "score": 0.8527010083198547, "start": 411, "end": 435, "probe_score": 0.6603, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2019 LFS", "label": "NAMED_DATA", "score": 0.8316810727119446, "start": 498, "end": 506, "probe_score": 0.7001, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "newest data for the Polish economy", "label": "DESCRIPTIVE_DATA", "score": 0.7196968793869019, "start": 1638, "end": 1672, "probe_score": 0.8279, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "serves du foyer ou de la communauté, ou aux manques de moyens du foyer à cause\nd’un revenu trop bas ou de prix trop hauts. En février 2022, 88,4% des foyers de l’Extrême-Nord dépensaient\nplus de 50% de leurs revenus en nourriture. Les prix atteignent leur pic en août, juste avant les récoltes, ce qui\naffecte la consommation des ménages. Les familles semblent faire face à des pénuries de nourriture entre avril\net juin, quand le labour et les semis sont en cours. Après juillet, la situation s’améliore rapidement, jusqu’à la fin\nde l’année. <sup>68</sup> [^68: WFP, Seasonal Analysis of Severe Acute Malnutrition, Far North Region, Cameroon, Mai 2022.]\n\n\nLes conflits intercommunautaires ont causé des dommages matériels, du pillage, des cessations d’activités, à\ncause desquels les déplacés souffrent d’une situation urgente en termes d’insécurité alimentaire. 76% des foyers\nont un score de consommation alimentaire pauvre ou limité, et 73% ont un score de diversité alimentaire bas.\nEn ce qui concerne les retournés, 85% des foyers sont dans une situation de vulnérabilité alimentaire. Cette\nsituation est aggravée dans les foyers comprenant des femmes enceintes ou allaitantes, et des enfants de moins\nde 5 mois. <sup>69</sup>\n\n\n61 Commune de Logone-Birni, Plan Communal de Développement de Logone-Birni, Novembre 2014", "output": {"entities": {"named_data": ["Seasonal Analysis of Severe Acute Malnutrition"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000568", "page": 20, "chunk": 2, "title": "Analyse conjointe Logone-Birn, juillet 2022 (Analyse mise à jour en décembre 2022)", "pdf_url": "https://reliefweb.int/attachments/54321629-d14b-474b-88a4-ff4d8a35233b/analyse_conjointe_logone-birni_-_hdp_nexus.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Seasonal Analysis of Severe Acute Malnutrition", "label": "NAMED_DATA", "score": 0.8079694509506226, "start": 569, "end": 615, "probe_score": 0.9915, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_Environmental and Social Management Framework (ESMF)_\n\n\n**Figure 2-2: The main drainage basins of Kenya**\n\n\nKenya’s four largest inland water bodies (Lake Victoria, Lake Turkana, Lake Naivasha, and\nLake Baringo) account for about 1.9 per cent of the land area (Figure 3-2). The majority of\nKenya’s lakes, including both saline and freshwater, and closed and open basin systems, are\nlocated within the Great East African Rift Valley. Kenya’s major permanent rivers originate\nin the highlands. The Nzoia, Yala, Sondu Miriu, and Migori rivers drain into Lake Victoria.\nThe EwasoNgiro River is found in the northeastern part of the country and the Tana and Athi\nrivers flow in the southeastern part. The rivers draining into Lake Victoria (covering over 8\nper cent of Kenya’s land area) provide about 65 per cent of Kenya’s internal renewable\nsurface water supply. The Athi River drainage area (11per cent of Kenya’s land area) provides\n7 per cent, the lowest share among Kenya’s major drainage areas (MOWI). Overall, Kenya is\na classified as a water scarce country with only 647 cubic meters of renewable fresh water per\ncapita (Shadrack Mulei Kithiia 2012). The same is characterized by high spatial and temporal\nvariability and extremes of drought and flood more particularly over the last 10 years.\n\n\n**2.2.3** **Biological Environment**\n\n\nKenya's land is covered by different types of vegetation according to the climate, topography,\nand other physical factors. The major categories are grassland, forests, semi-deserts, and\nmountains. Anthropogenic activities and impacts on the land continue to alter the\ndistribution, amount, and health of these ecosystems (Survey of Kenya 2003).\n\n\n_Secondary Education Quality Improvement Project_ 31", "output": {"entities": {"named_data": ["Survey of Kenya"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019951", "page": 30, "chunk": 0, "title": "Kenya - Secondary Education Quality Improvement Project : environmental assessment (Vol. 2 of 2) : Environmental and social management framework", "pdf_url": "https://documents.worldbank.org/curated/en/909331501144203050/pdf/SFG3491-V2-EA-P160083-Box405291B-PUBLIC-Disclosed-7-27-2017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Survey of Kenya", "label": "NAMED_DATA", "score": 0.7770411372184753, "start": 1663, "end": 1678, "probe_score": 0.9944, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " has been\ngenerally good and, as the political relation with Somaliland improved (partly as a\nresult of the 1998-2000 \"border war\" with Eritrea), the repatriation operation flowed\nmore smoothly.\n\nOn the Somaliland side there was the fear of the impact of reduced food aid in the\ncamps (part of the food was \"repatriating\" from Ethiopia to Somaliland) on an\neconomy already battered by the livestock ban of January 1998, which caused a\ntemporary halt in the operation. There was also some horse trading involved as the\nMRRR often made its consent for the start of repatriation convoys subject to an\nincrease of the \"incentives\" for the police and civilian personnel escorting the\nconvoys and to the implementation of \"pet projects\", which often involved exhausting\nnegotiations.\n\nBut in the end, the repatriation operation managed to re-start and by the end of 2001\nthe UNHCR teams in Jijiga and Hargeisa together with their respective counterparts\nmanaged to achieve the considerable result of closing two and a half camps (Teferi\nBer and Darwanaji, plus Hartasheikh B) and almost closing a third one (Daror). The\nfluctuations in the population figures are summarized in the table below.\n\n**The realities of repatriation from Ethiopia to Somaliland**\n\nThe repatriation from Ethiopia to Somaliland presented some specific aspects. First\nwe should remark that there are a number of \"southern\" Somalis estimated at around\n\n\n19", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["population figures"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000627", "page": 20, "chunk": 1, "title": "Pastoral society and transnational refugees: population movements in Somaliland and eastern Ethiopia 1988 - 2000", "pdf_url": "https://reliefweb.int/attachments/5b736a44-4630-37c1-a829-ee5b20c50410/9EFD2E782966683AC1256C55002FA5DE-unhcr-som-31aug.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "population figures", "label": "VAGUE_DATA", "score": 0.5277488231658936, "start": 1134, "end": 1152, "probe_score": 0.0022, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": ["1999 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012957", "page": 62, "chunk": 2, "title": "Kenya - Bura Irrigation Settlement Project", "pdf_url": "https://documents.worldbank.org/curated/en/431731468273692045/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "1999 data", "label": "VAGUE_DATA", "score": 0.6582925319671631, "start": 688, "end": 697, "probe_score": 0.5672, "gold": "NON_MENTION", "gold_tier": "flip"}, {"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9035401940345764, "start": 758, "end": 796, "probe_score": 0.9023, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "lerks in Place<br>DLI 7: Results<br>on<br>physical<br>planning, land<br>tenure security<br>and<br>urban<br>infrastructure<br>development<br>in<br>Program|Actual Nos.<br>Target (MoLHUD<br>results in support<br>to the window)|14<br>NA|14<br>NA|14<br>NA|14<br>NA|14<br>NA|Not yet due<br>Old DLI 7 – IFMS rolled out<br>dropped. This is a new DLI for<br>specific results to be achieved by<br>MoLHUD in support to the sub-<br>window.|\n|**DLIs (targets &**<br>**disbursements)**<br>DLI<br>1:<br>Program LGs<br>have met all<br>Program<br>Minimum<br>Conditions<br>DLI<br>2:<br>Program LGs<br>have<br>strengthened<br>institutional<br>performance<br>DLI<br>3:<br>Program LGs<br>have<br>implemented<br>Infrastructure<br>Action Plans<br>DLI<br>4:<br>Program LGs<br>have<br>implemented<br>Institutional<br>Strengthening<br>Plans<br>DLI<br>5:<br>MoLHUD has<br>executed<br>Performance<br>Improvement<br>Plans<br>for<br>Program LGs<br>DLI<br>", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000006", "page": 25, "chunk": 9, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents.worldbank.org/curated/en/143681526614252328/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", where host communities already face challenges\nof their own. These returnees could be stigmatized as the host communities perceive them as a health\nrisk and competitors for scarce resources. Compounded by the delay in the appointment of governors and\nthe resulting power vacuum, intercommunal tensions are on the rise.\n\n\n7. **Gender disparities and inequalities are staggering.** South Sudan ranks in the bottom third of\ncountries for the HDI’s life-course gender gap <sup>21</sup> [^21: HDI’s life-course gender gap compiles 12 indicators that analyze gender gaps in choices and opportunities across the lifespan including\neducation, labor and work, political representation, time use, and social protection. HDI’s women’s empowerment dashboard compiles 13\nwoman-specific empowerment indicators in three categories: reproductive health and family planning, violence against women and girls, and\nsocioeconomic empowerment.] and women’s empowerment. <sup>22</sup> [^22: UNDP. 2018. _Human Development Indices and Indicators: 2018 Statistical Update - South Sudan._] Local governance and\naccess to services in South Sudan take on specific gendered dimensions, such that women and girls are\naffected disproportionately compared to men and boys. A steeped patriarchal structure leads to male\ndecision-makers or gatekeepers in local community leadership structures, customary law and restorative\njustice settings, policy and security forces, and within homes. One survey shows the civic and political\nparticipation of men at 84 percent compared to women at 15 percent. The percentage of women in\nleadership roles was highest in Western Bahr el Ghazal state (30.3 percent) and lowest in Warrap State\n(4.9 percent). <sup>23</sup> [^23: Kenwill International Limited. 2015 _. Fortifying Equality and Economic Diversification (FEED): Improved Livelihoods in South Sudan._ Gender\nAssessment Report, World Vision, July 2015.] In addition, there are limited income-generating opportunities for women. When women\ndo generate income, decisions on how", "output": {"entities": {"named_data": ["women’s empowerment dashboard"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 16, "chunk": 2, "title": "South Sudan - Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/824121596765983121/pdf/South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "women’s empowerment dashboard", "label": "NAMED_DATA", "score": 0.6392110586166382, "start": 718, "end": 747, "probe_score": 0.9323, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "The Future of Syria: Refugee Children in Crisis\n\n\nNewly arrived refugees at the Jordan-Syria border await transport to Za’atari refugee camp in Jordan. UNHCR / O. Laban-Mattei\n\n\n\nUNHCR registration sites in Beirut, Tripoli and Tyre.\n\nSome organizations run unique programmes, such\n\nas Korea Food for the Hungry International, which\n\noffers tae kwon do for children in Za’atari camp.\n\n\nIn southern Lebanon, Terre des Hommes runs a\n\nprogramme where “animators” visit refugee homes\n\nfor up to two hours, engaging children with activities\n\nsuch as storytelling, puppetry, face-painting and\n\ngames. An Intersos “Child Smart Bus” in southern\n\nLebanon brings recreational and educational\n\nactivities to 64 local villages, particularly targeting\n\nisolated 6- to 13-year-old girls and boys.\n\n##### Tensions in the Home\n\n\nMost Syrian refugee families are living in conditions\n\nthat are drastically worse from what they used to\n\nknow in Syria. ”Home” today is a tent, caravan,\n\ncollective shelter or crowded apartment shared\n\nwith extended family. Some lack electricity.\n\nWhen it is available, they cannot afford to pay\n\nthe bills to run basic appliances like a fridge.\n\n\nMany depend on humanitarian assistance to\n\nsurvive. The difficulties they face are compounded\n\nby an uncertain future, the unknown fate of\n\nmissing family and friends, financial concerns\n\n\n\nand a lost sense of purpose. All this creates\n\na tense and uneasy environment, which can\n\nbe psychologically damaging for children\n\nand can trigger violence in the home.\n\n\nAlthough only anecdotal information was collected\n\non domestic violence involving Syrian children,\n\nhumanitarian workers expressed overall concern\n\nabout the situation. Opinion varied as to whether\n\nthe prevalence of domestic violence against\n\nchildren has increased as a result of displacement.\n\nSome people interviewed—including a psychiatrist\n\nin Lebanon with over ten years of experience\n\nin Syria—said it is not uncommon for Syrian\n\nmothers and fathers alike to use a degree of\n\nphysical force when disciplining their children,\n\nparticularly among families from rural areas. They", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["anecdotal information"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001052", "page": 30, "chunk": 0, "title": "The Future of Syria – Refugee Children in Crisis [EN/AR]", "pdf_url": "https://reliefweb.int/attachments/a03a03d0-b6cf-3c9d-8855-7963e4fff514/Future-of-Syria-UNHCR-v13.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "anecdotal information", "label": "VAGUE_DATA", "score": 0.6713259220123291, "start": 1537, "end": 1558, "probe_score": 0.0786, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "We also compare the distribution of the demeaned markups for the CES production\n\n\nfunction. Notice that our proposed QMLE method is unable to recover the labor coef\n\nficient parameter _βL_ when _ρ_ differs significantly from zero. Thus, we can only compare\n\n\nthe demeaned sequence of markups instead of the level. Figure 2 shows the results when\n\n\nconsidering _ρ_ = 0 _._ 5. Results suggest that the centered distribution changes markedly for\n\n\nthe DLW case. The variance is much larger and the mass of the distribution is not equal to\n\n\nzero. The estimated impact of regulation on markups will thus be biased. In this case, one\n\n\ncannot uncover either the level or the impact of other variables on the changes in markups.\n\n\nHowever, the QLME distributional result is similar to the simulated data - hence policy\n\n\ninference is possible using QLME, but not DLW.\n\n### **6 Conclusions**\n\n\nUncovering the effects of regulation policies on productivity and markups using the methods\n\n\nof Ackerberg et al. (2015) and De Loecker and Warzynski (2012) leads to several endogene\n\nity issues and produces biased estimates which are sensitive to: (1) the functional form of\n\n\nthe production function; (2) the omission of demand shifters; (3) the absence of price infor\n\nmation; (4) the violation of the Markov process for productivity; and (5) misspecification\n\n\nwhen marginal costs are excluded in the estimation process. Mindful of these constraints,\n\n\nwe use regulation as a pure exogenous process to identify variation in markups. Given the\n\n\nhard constraint on data availability (i.e. unobservable prices and unknowable production\n\n\nfunctions), we establish a methodology that allows for a consistent estimate of the impact\n\n\nof change in regulation on change in markup.\n\n\nBuilding on the work of Doraszelski and Jaumandreu (2019) and Ackerberg et", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["simulated data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000546", "page": 27, "chunk": 0, "title": "identification properties for estimating the impact of regulation on markups and productivity", "pdf_url": "https://local/prwp/identification-properties-for-estimating-the-impact-of-regulation-on-markups-and-productivity.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "simulated data", "label": "VAGUE_DATA", "score": 0.566800057888031, "start": 783, "end": 797, "probe_score": 0.8625, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### 1.8 11\n\n\n\nCurrent account balance . **.2**\n\n\n\nFinancing items (net)\nChanges in net reserves .. .\n_Memo:_\nReserves including gold _(US$ millions)_\nConversion rate _(DEC, locaW/US$)_ 177.7 177.7 177.7\n\n\n**EXTERNAL DEBT and RESOURCE FLOWS**\n\n**1979** **1989** **1998** **1999**\n_(US$ millions)_ **Compositlon of total debt, 1998 (USS milIlona)**\nTotal debt outstanding and disbursed 26 **179** 288\nIBRD 0 0 0\nIDA 0 26 50 49 G 15 B\n\nTotal debt service 2 15 6\nIBRD 0 0 0 C: 9\nIDA 0 0 1 1\n\nComposition of net resource flows E: 119\nOfficial grants 5 32 48\nOfficial creditors -1 3 2\nPrivate creditors 0 -1 0\nForeign direct investment 0 0 6 D: **95**\nPortfolio equity 0 0 0\n\nWorld Bank program\n\nCommitments 0 9 3 A  - IBRD E - Bilateral\nDisbursements 0 2 2 1 B - IDA D - Other rrultilateral F **-** Private\nPrincipal repayments 0 0 0 0 C- IMF G - Short-term\nNet flows 0 2 2 1\nInterest payments 0 0 0 0\nNet transfers 0 2 1 1\n\n\nNote: This table was produced from the Development Economics central database. 9/13/00", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018341", "page": 63, "chunk": 1, "title": "Kenya - Fourth Industrial Development Bank (IDB) Project", "pdf_url": "https://documents.worldbank.org/curated/en/797551468272364205/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9087857007980347, "start": 960, "end": 998, "probe_score": 0.6996, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " earn their livelihoods, is key to achieving the\ngoals. Fertility rates remain high (at five births per woman), as does the population growth rate, meaning that most\nhouseholds have few income earners and several dependents, and much of the care responsibilities fall on women. In this\ncontext, supporting women micro-entrepreneurs to move further up the value chain or into other, more profitable\nsectors, will help harness women's contributions to the economy and contribute to greater growth overall.\n\n\n25. **This project is also aligned with Bank-financed operations aimed at promoting gender inclusion and WEE.** These\ninclude the Skills Development Project (P145309); the Agricultural, Technological, and Advisory Services Project\n(P109224); the Reproductive, Maternal and Child Health Services Improvement project, and NUSAF. The project’s work\nwith refugees will build on and partner closely with DRDIP project in refugee-hosting districts.\n\n\n**C. Proposed Development Objective(s)**\n\n\nTo enhance the economic and social empowerment of women entrepreneurs in Uganda\n\n\n26. **The proposed outcome indicators to measure achievement of the PDO are** :\n\n\n    - Increase in household income, including the contribution of women\n\n    - Increase in productive assets\n\n    - Increase in the number of women-led enterprises in project locations\n\n    - Increase in household welfare\n\n    - Increase in women’s decision-making.\n\n\n27. Potential outcome indicators will be explored during preparation to ensure that baseline data exist, that they are\nmeasurable, and that approaches to measure them are available to provide accurate results at reasonable cost.\n\n\nJun 15, 2021 Page 9 of 13", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000005", "page": 8, "chunk": 1, "title": "Concept Project Information Document (PID) - Generating Livelihoods and Opportunities for Women (GLOW) Uganda - P176747", "pdf_url": "http://documents.worldbank.org/curated/en/135361626935792550/pdf/Concept-Project-Information-Document-PID-Generating-Livelihoods-and-Opportunities-for-Women-GLOW-Uganda-P176747.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "baseline data", "label": "VAGUE_DATA", "score": 0.7189329266548157, "start": 1510, "end": 1523, "probe_score": 0.0001, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nIntegrated Cash Transfer and Human Capital Project (P166220)\n\n\nfinanced by the project will support the expansion of the PNSF outside the capital in sub-prefectures and ‘chef-lieux’\ntargeted based on poverty and remoteness by the Department of Statistics and Demographic Studies (DISED). Household\neligibility criteria, while yet to be finalized, are expected to include the following: (i) households with young children, (ii)\nbelow the threshold for the Proxy-Means Test (PMT) developed to assess household welfare in regional capitals ‘cheflieux’; and (iii) through community-based targeting in rural areas. Beneficiaries of cash transfers will not include refugees,\nthough they will be eligible to participate in accompanying measures sessions under the following sub-component.\n\n\n**Sub-component 1.2: Community-based accompanying measures to improve human capital (US$1.0 million)**\n\n26. This component will finance the design and the implementation of community-level behavior change sessions that\nwill constitute the soft conditionality for the conditional cash transfers. The sessions will center around themes related\nto human capital development, particularly those linked to the early years/early childhood development agenda. The\ncontent of the community-level sessions is still being identified but will likely include: (i) simulation of cognitive\ndevelopment; (ii) promotion of good parenting practices; (iii) encouragement for attendance of school-age children in\nschool; (iv) encouragement of practices to prevent child malnutrition; (v) hygiene promotion; and (vi) information\nsessions on the creation of income-generating activities; and (vii) information sessions for refugee and migrant\nhouseholds on their rights and responsibilities. Nutrition-related interventions will be harmonized with those supported\nby the “Zero Stunting Initiative” led by the Ministry of Health (MOH), supported by a World Bank-financed operation.\nParticipation in these", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000063", "page": 17, "chunk": 0, "title": "Djibouti - Integrated Cash Transfer and Human Capital Project", "pdf_url": "http://documents1.worldbank.org/curated/en/419881558381476102/pdf/Djibouti-Integrated-Cash-Transfer-and-Human-Capital-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "surgeries, other respiratory diseases (pneumonia and bronchitis), other cancers, and tuberculosis are included\nas major causes of the costs associated with medical care. Data on these costs have been collected based on\nvarious academic, national, and international sources.\n\n\n**Table 6. Total Medical Cost of Tobacco-Related Cases**\n\n\n**<u>Cost item</u>** _<u>Ischemic disease</u>_ _<u>Stroke</u>_ _<u>Other cardiovascular diseases</u>_ _<u>COPD</u>_ _<u>Other respiratory</u>_ _<u>Lung cancer</u>_ _<u>Other cancers</u>_ _<u>Total</u>_\nGoverment cost\n584 684 438 244 244 633 633\n(US$)\n\nOut-of-pocket cost\n389 456 292 163 163 422 422\n(US$)\n\n_Tobacco attributed_\nMen, % 24 25 25 56 29 91 44\nWomen, % 2 2 2 17 3 27 3\nCases, men 32,720 10,069 5,476 6,643 10,766 7,902 2,207 75,782\nCases women 3,567 1,222 543 393 1,124 1,099 51 7,999\nTotal tobacco36,286 11,290 6,019 7,036 11,890 9,000 2,259 83,781\nattributed cases\n\nTotal government\n21,191,269.28 7,722,360.00 2,636,370.18 1,716,808.40 2,901,145.36 5,697,101.28 1,429,826.73 43,294,881\ncost (US$)\n\nTotal out-of-pocket\n4,127,512.85 5,148,240.00 1,757,580", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Data on these costs"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007186", "page": 14, "chunk": 0, "title": "wps8227", "pdf_url": "https://local/prwp/wps8227.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Data on these costs", "label": "VAGUE_DATA", "score": 0.5352343916893005, "start": 170, "end": 189, "probe_score": 0.7354, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\npeople (both because of the fighting itself as well as fear of the violence). Available statistics indicate that\nover 2 million persons are now internally displaced including over 200,000 civilians who have sought\nprotection in the United Nations (UN) Protection of Civilian (PoC) sites across the country. Further, an\nestimated 1.4 million persons have sought refuge in neighboring countries.\n\n\n3. **Conflict has resulted in a near collapse of the economy.** Currently, the country exhibits all the signs\nof macroeconomic collapse. There have been sharp declines in output, and a spike in the parallel exchange\nmarket premium. The economy is expected to further contract by about 11 percent with both the oil and\nnon‐oil sectors expected to decrease. The fiscal deficit remains wide, although real magnitudes are\ndifficult to estimate given the hyperinflation and lack of real time data. Based on the 2016/17 budget, the\nfiscal deficit is estimated at about 14 percent of Gross Domestic Production (GDP). Export revenues\ndecreased due to declining oil prices and lower oil production. Oil production is expected to decrease to\nabout 120,000 barrels per day this fiscal year down from 165,000 barrels per day in 2014, itself less than\nhalf of peak production before independence in 2011. There is an accelerated depreciation of the pound,\nwith the South Sudan Pound (SSP) depreciating on the parallel market from SSP 18.5 per US dollar in\nDecember 2015 to reach SSP 110 per US dollar in March, 2017. This follows the move to a managed\nfloating exchange rate from a fixed exchange rate.\n\n\n4. **Poverty levels remain high and are on the upward spiral.** Estimates for 2015, indicated that 66\npercent of the population lives below the poverty line (US$32 per month), a proportion that rises to 71\npercent in the rural areas. However, mainly because of displacement, poverty is now more endemic with\nestimates of at least 80 percent of the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["real time data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000038", "page": 12, "chunk": 1, "title": "South Sudan - Emergency Food and Nutrition Project", "pdf_url": "http://documents.worldbank.org/curated/en/713081494122547885/pdf/South-Sudan-PAD-04282017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "real time data", "label": "VAGUE_DATA", "score": 0.5702568888664246, "start": 874, "end": 888, "probe_score": 0.5249, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " not have a demand for loans and those who\nhave demand and are able to obtain the loans.\n\n\nCredit-constrained agents include three types of agents that are undistinguishable in the survey data. The\nfirst group comprises rural agents who claim they have a demand for loans, but are not considered\ncreditworthy because of the high risk or low return on their prospective investment. This means that the\nlenders may require high interest rates to compensate for increased risks, and thus those agents would not\nborrow. The second group encompasses creditworthy clients that could not convey the sufficient signals\nabout their creditworthy and that lenders could not identify because of the underlying lending technology.\nLastly, credit-constrained agents also include potential debtors that are willing to pay higher interest rates,\nbut that creditors reject to avoid an adverse selection problem.\n\n\n**5.** **Participation in loan markets**\n\n\nIn the analysis of participation in loan markets, we focus on only three outcomes because of data\nlimitations. The first outcome includes those agents that do not demand loans. The second outcome\nstudied is the so-called credit-constrained group, which includes both those who had demand but did not\napply and those who applied and got rejected. <sup>11</sup> The last outcome includes those that have demand and are\n\n\n9 Farmers and microenterprises predominantly respond with the first of these three reasons and less than 1 percent of the total\npopulation responds with reasons (b) and (c). Among enterprises reasons, (a) is still predominant while about 5 percent of the\npopulation also claims reasons (b) and (c).\n\n10 This is another possible dimension of credit constraints. However, the survey data indicates that only 3-5 percent of those who\nobtain the loans report that they applied for a larger amount. As a result, the incidence of “partially constrained” is minimal, and\nit is not studied in this report.\n\n11 An", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:004207", "page": 9, "chunk": 1, "title": "wps5014", "pdf_url": "https://local/prwp/wps5014.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.5410667657852173, "start": 181, "end": 192, "probe_score": 0.9612, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "cluster and inter-area correlations are large and are not explicitly accounted for. Central to the ELL\n\n\napproach is the fact that it is not generally possible to separate the overall location effect into the\n\n\narea level effect ‘η’ and the cluster level effect ‘ _e_ ’ and, in general, just a single location effect can\n\n\nbe calculated. Thus, in the simulation phase, the ELL method requires that one either assumes that\n### the estimated location effect measured by ση *2 = (ση 2 +σ e 2 ) is entirely a cluster level effect - an\n\n\noptimistic assumption that rules out any correlation at a higher level - or that it occurs entirely at the\n\n\narea level, a conservative assumption that will likely lead to an overstatement of the variance of the\n\n\nestimate. <sup>9</sup> [^9: See details in Elbers, Lanjouw and Lanjouw (2002) or Demombynes et al (2006). Tarozzi and Deaton (2007) claim\nthat application of the conservative assumption, while feasible, is not appealing as it would inevitably result in estimates\nof poverty that are so imprecise as to be unusable. For this reason they conclude that the “optimistic” assumption is\nessentially unavoidable for the ELL methodology. We shall empirically assess this assertion in greater detail below.]\n\n\nHow large are inter-cluster correlations in practice? Given the availability of income data in\n\n\nthe Census, we can analyze in this study the presence of inter-cluster correlation at multiple levels.\n\n\nWithin the state, we discern five possible locational levels above the household at which inter\n\ncluster correlations might apply: the meso-region, micro-region, municipality, district and\n\n\nenumeration level (see Table 3).  We use the full census data to estimate a single model for the\n\n\nstate as a whole, including a set of locational controls (aggregated from unit record census data and\n\n\nincluded as regressors) at the enumeration area, district and municipality level. We apply mixed\n\neffects maximum likelihood estimation and decompose the overall error term into a household\n\n\ncomponent and separate sub-components", "output": {"entities": {"named_data": [], "descriptive_data": ["census data", "unit record census data"], "vague_data": ["income data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:003720", "page": 18, "chunk": 0, "title": "wps4513", "pdf_url": "https://local/prwp/wps4513.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "income data", "label": "VAGUE_DATA", "score": 0.6628915071487427, "start": 1328, "end": 1339, "probe_score": 0.7972, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "census data", "label": "DESCRIPTIVE_DATA", "score": 0.6879379749298096, "start": 1691, "end": 1702, "probe_score": 0.0782, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "unit record census data", "label": "DESCRIPTIVE_DATA", "score": 0.7922515273094177, "start": 1814, "end": 1837, "probe_score": 0.3223, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Emergency Food and Nutrition Security Project (P163559)\n\n\n**I.** **STRATEGIC CONTEXT**\n\n\n**A. Country Context**\n\n\n1. **South Sudan is a resource‐rich country and emerged from a prolonged civil war for independence**\n**in 2005, but continues to face enormous challenges to sustainable peace, recovery, reconstruction and**\n**development.** The civil war had crippling effects on the social fabric of the country including the disruption\nand forced displacement of entire families, communities and social systems. It is estimated for example,\nthat at the end of hostilities in 2005, about 50 percent of the population in South Sudan was internally\ndisplaced while another 25 percent had fled the country. The war also had a debilitating effect on\nproductive infrastructure and on a range of production systems and led to isolation of entire communities\nfrom economic opportunities and services. In addition, the depreciation of human capital as a result of\nthe war removed‐ possibly forever‐ a significant portion of adults and youth from skilled labor markets.\n\n\n2. **Almost twelve years after gaining autonomy and then subsequent independence in 2011, South**\n**Sudan is still struggling to break out of the conflict trap.** Conflict resumed in December 2013 and, despite\na brief period of optimism following the Agreement for the Resolution of Conflict signed in August 2015,\nstill continues. The conflict started in Juba and then was focused on the Greater Upper Nile Region;\nhowever, recently this has changed and there has been organized violence in previously peaceful areas\nsuch as Central and Eastern Equatoria. The hostilities and unrest have led to massive displacement of\npeople (both because of the fighting itself as well as fear of the violence). Available statistics indicate that\nover 2 million persons are now internally displaced including over 200,000 civilians who have sought\nprotection in the United Nations (UN) Protection of Civilian (", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["Available statistics"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000038", "page": 12, "chunk": 0, "title": "South Sudan - Emergency Food and Nutrition Project", "pdf_url": "http://documents.worldbank.org/curated/en/713081494122547885/pdf/South-Sudan-PAD-04282017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Available statistics", "label": "VAGUE_DATA", "score": 0.6252572536468506, "start": 1791, "end": 1811, "probe_score": 0.9811, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "### 1.8 11\n\n\n\nCurrent account balance . **.2**\n\n\n\nFinancing items (net)\nChanges in net reserves .. .\n_Memo:_\nReserves including gold _(US$ millions)_\nConversion rate _(DEC, locaW/US$)_ 177.7 177.7 177.7\n\n\n**EXTERNAL DEBT and RESOURCE FLOWS**\n\n**1979** **1989** **1998** **1999**\n_(US$ millions)_ **Compositlon of total debt, 1998 (USS milIlona)**\nTotal debt outstanding and disbursed 26 **179** 288\nIBRD 0 0 0\nIDA 0 26 50 49 G 15 B\n\nTotal debt service 2 15 6\nIBRD 0 0 0 C: 9\nIDA 0 0 1 1\n\nComposition of net resource flows E: 119\nOfficial grants 5 32 48\nOfficial creditors -1 3 2\nPrivate creditors 0 -1 0\nForeign direct investment 0 0 6 D: **95**\nPortfolio equity 0 0 0\n\nWorld Bank program\n\nCommitments 0 9 3 A  - IBRD E - Bilateral\nDisbursements 0 2 2 1 B - IDA D - Other rrultilateral F **-** Private\nPrincipal repayments 0 0 0 0 C- IMF G - Short-term\nNet flows 0 2 2 1\nInterest payments 0 0 0 0\nNet transfers 0 2 1 1\n\n\nNote: This table was produced from the Development Economics central database. 9/13/00", "output": {"entities": {"named_data": ["Development Economics central database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012139", "page": 63, "chunk": 1, "title": "Kenya - Group Farm Rehabilitation Project", "pdf_url": "https://documents.worldbank.org/curated/en/383521468914054732/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Development Economics central database", "label": "NAMED_DATA", "score": 0.9087857007980347, "start": 960, "end": 998, "probe_score": 0.6996, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "6\n\n\nThere is strong support in the Government for increasing resources for education, and the Government\nmade a commitment to increase education's share of budget from 16% in 2001-02 to 25% in 2009-10.\n\n\nOne of the reasons for choosing an APL with a ten-year perspective is that the education budget\nshortages will continue to be a constraint in the next few years. Over this period, Government\n\nexpenditures in non-priority areas will be brought under control and Government expenditures on\neducation can be expected to increase significantly. Despite the manageability in the long-run, the\nshort-run prospects on the budget are more challenging and donors will need to finance some recurrent\ncosts. The proposed APL will be implemented in three phases with distinct triggers (see Section B. 4).\nAs a result, a 10-year projection of enrollments and education costs has been developed (which is the\noverall framework for the APL), and a detailed five year plan and project proposals have been\nprepared (which is the framework for the first phase of the APL).\n\n\n3. Sector issues **to be addressed by the project and strategic choices**\n\nThe project will directly address all the issues below except for higher education.\n\n\n_Issues/Sector Problems_ _Government strategy and project proposal_\n\n**School Places**\n\nThe immediate problem in Djibouti City and The Government's strategy includes a combination\nsurrounding suburbs and other towns is the lack of of building more schools and continuing with the\nschool places due to the strong demand for schooling. double-shifting policy. The project will finance new\nclassrooms, sanitation services, and school furniture.\n\n**Equity, Gender, Disparities**\n\nChildren from poorer families, rural children, and The Government will construct schools in underespecially girls do not always attend school. The served areas, particularly in poorer parts of Djiboutirecent Household Expenditure Survey states that Ville where almost 70% of the population lives.\nmajor reasons for the", "output": {"entities": {"named_data": [], "descriptive_data": ["Household Expenditure Survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:009698", "page": 9, "chunk": 0, "title": "Ethiopia - Second Development Bank of Ethiopia Project", "pdf_url": "https://documents.worldbank.org/curated/en/217951468032101177/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Household Expenditure Survey", "label": "DESCRIPTIVE_DATA", "score": 0.6417368054389954, "start": 1906, "end": 1934, "probe_score": 0.9529, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "up> <sup>numerous</sup> <sup>settings</sup> <sup>demonstrate</sup> <sup>that</sup> <sup>consumption</sup> <sup>declines</sup> <sup>following</sup>\n\nthe onset of violence (e.g., <sup>_<u>δC</u>_</sup> _δV_ <sup>_<u>i</u>_</sup> <sup>_<_</sup> <sup>0).</sup> <sup>In</sup> <sup>such</sup> <sup>a</sup> <sup>case,</sup> <sup>the</sup> <sup>probability</sup> <sup>of</sup> <sup>a</sup> <sup>person</sup> <sup>reporting</sup>\n\n\nto be satisfied with consumption might actually increase following a shock that caused\n\n\nconsumption to decrease (i.e., _δV_ <sup>_<u>δφ</u>_</sup> <sup>_>_</sup> <sup>0).</sup>\n\n\nIn such a case, the first and third term of the bracketed expression on the RHS of\n\n\n_δVδφ_ <sup>are</sup> <sup>positive,</sup> <sup>while</sup> <sup>the</", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:000826", "page": 33, "chunk": 2, "title": "idu06ca2ef8a0b8400459d09f400e9038b642fb6", "pdf_url": "https://local/prwp/idu06ca2ef8a0b8400459d09f400e9038b642fb6.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "from Decision Review Decision Note)**|\n|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|\n|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million", "output": {"entities": {"named_data": [], "descriptive_data": ["Project Financing Data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000011", "page": 6, "chunk": 1, "title": "Lebanon - Municipal Services Emergency Project", "pdf_url": "http://documents1.worldbank.org/curated/en/119441469672145615/pdf/PAD10180PAD0P14972400PUBLIC00Box391431B.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Project Financing Data", "label": "DESCRIPTIVE_DATA", "score": 0.5579208135604858, "start": 863, "end": 885, "probe_score": 0.3438, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " the first round of education benefits **-** free school textbooks and waivers of school fees for general\neducation students (pre-primary, primary and secondary) as well as vocational students **-** were distributed.\n\n**16** The estimated number of poor in 2012 was determined based on the 2012 population in Lebanon (World Development\nIndicator) and the extreme poverty rate of **7.2** percent (2004 Household Budget Survey, latest available).\n\n\n\n**17** Silva et al. (2012). _Inclusion and Resilience: The_ _Way Forward for Social Safety Nets in_ _the Middle East and North Africa._\n**MENA** Development Report. World Bank, Washington **DC.**\n\n\n\n**15** Moussa, _Z_ **(2011).** Impact Evaluation of the Community Development Program of the Economic and Social Fund for\nDevelopment **(ESFD).** The Economic and Social Fund for Development. Beirut, Lebanon.\n\n\n\n**19** The Consultation and Research Institute (2012). Impact Study of Sub-Projects Implemented Under the Community\nDevelopment Project.\n\n\n\n12", "output": {"entities": {"named_data": ["World Development\nIndicator", "2004 Household Budget Survey"], "descriptive_data": ["2012 population in Lebanon"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000109", "page": 11, "chunk": 3, "title": "Lebanon - Social Promotion and Protection Project", "pdf_url": "http://documents1.worldbank.org/curated/en/643811468055144236/pdf/749060PAD0P124010Box374388B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "2012 population in Lebanon", "label": "DESCRIPTIVE_DATA", "score": 0.5875164866447449, "start": 290, "end": 316, "probe_score": 0.3825, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "World Development\nIndicator", "label": "NAMED_DATA", "score": 0.7194849252700806, "start": 318, "end": 345, "probe_score": 0.257, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "2004 Household Budget Survey", "label": "NAMED_DATA", "score": 0.8325852751731873, "start": 396, "end": 424, "probe_score": 0.7395, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ">2</sup> With a strong reliance on subsistence farming and pastoralism, rural\ncommunities are particularly affected by extreme weather events and natural disasters, including the\nrecent desert locust invasion. Historical records show a large year-to-year variability in precipitation, but\ndroughts have become more frequent and widespread since the 1960s. <sup>3</sup> The seasonality and intensity of\nthe rainy season are also changing, resulting in more frequent and extreme flooding in many parts of the\ncountry. More intense and variable weather events are predicted for the future. <sup>4</sup> [^4: ThinkHazard (2019). South Sudan.] The consequences of\nclimate volatility are intensifying intercommunal conflict over natural resources, ongoing population\ndisplacement, and worsening food insecurity. The 2019 exceptionally intense seasonal flood, with 900,000\npeople affected and an estimated 420,000 displaced, illustrates the country’s extreme climate\nvulnerability. The current desert locust crisis—the worst to hit the Horn of Africa in over 25 years—\nrepresents an unprecedented threat to food security and livelihoods in the region and could lead to\nfurther suffering, displacement, and potential conflict. According to the most recent FAO desert locust\nsituation update, <sup>5</sup> [^5: FAO (Food and Agriculture Organization of the United Nations). Desert Locust situation update (13 July 2020)] some of the swarms in Kenya are expected to migrate northwards across South Sudan\nto the summer breeding areas in Sudan. The expanding swarms could affect more than 2.7 million people,\nmany living in areas with severe food insecurity and in need of humanitarian assistance. <sup>6</sup> [^6: FSC (Food Security Cluster). Situation Report (17 June 2020))]\n\n\n1 UNOCHA (United Nations Office for Coordination of Humanitarian Affairs). 2020. _Humanitarian Needs Overview 2020_, p. 3\n2 Germanwatch. 2019. _Global Climate Risk Index 2020_, p. 42.\n3 United", "output": {"entities": {"named_data": ["FAO desert locust\nsituation update"], "descriptive_data": ["Historical records"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 14, "chunk": 1, "title": "South Sudan - Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/824121596765983121/pdf/South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Historical records", "label": "DESCRIPTIVE_DATA", "score": 0.6308143734931946, "start": 210, "end": 228, "probe_score": 0.9848, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "FAO desert locust\nsituation update", "label": "NAMED_DATA", "score": 0.6978318095207214, "start": 1248, "end": 1282, "probe_score": 0.9883, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ", have quickly\nbecome a part of society as **consumers,**\n**employees, entrepreneurs, and**\n**taxpayers** . Currently between <mark>225 and</mark>\n<mark>350 thousand</mark> refugees from Ukraine are\nestimated to be working in Poland. The\nlower bound is the number from social\nsecurity data, while the higher bound is\nthe product of employment rate from the\nsurveys and working age population with\nactive PESEL UKR numbers (Chapter 2).\n\n\nStructural worker shortages, one of\nthe lowest unemployment rates in the\nEuropean Union, record high vacancies,\nand high education attainment of refugees\neased their labour market integration. The\nnumber of Polish citizens aged 20-64 has\ndeclined by 2.6 million from its peak in early\n2010. <sup>7</sup> [^7: According to the Labour Force Survey data from Eurostat.] Despite COVID-19 and geopolitical\nshocks, the unemployment rate oscillated\nin recent years around 3% in Poland, and\nin February 2022 only Czechia exhibited a\nlower rate in the EU. <sup>8</sup> [^8: According to the harmonized unemployment rates from Eurostat.] In Q4‘2021 the share\nof companies reporting vacancies stood at\n49%, the highest level on record, and has\nbeen slowly declining since then. <sup>9</sup> [^9: According to the quarterly NBP survey.]\nIn July-August 2023, 56% of refugees\ndeclared possessing tertiary education and\ntheir employment rate has been almost\none-third higher than for others. <sup>10</sup> [^10: According to the UNHCR (2023) survey.]\n\n\n\n3 As of December 2023, according to UNHCR, based on governmental sources <u>[Situation Ukraine Refugee Situation (unhcr.org)](https://data.unhcr.org/en/situations/ukraine)</u>\n4 According to the active PESEL UKR database.\n5", "output": {"entities": {"named_data": ["Labour Force Survey data from Eurostat", "UNHCR (2023) survey", "Situation Ukraine Refugee Situation", "active PESEL UKR database"], "descriptive_data": ["social\nsecurity data", "quarterly NBP survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 3, "chunk": 3, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "social\nsecurity data", "label": "DESCRIPTIVE_DATA", "score": 0.8248899579048157, "start": 269, "end": 289, "probe_score": 0.9971, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Labour Force Survey data from Eurostat", "label": "NAMED_DATA", "score": 0.6963623762130737, "start": 763, "end": 801, "probe_score": 0.999, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "quarterly NBP survey", "label": "DESCRIPTIVE_DATA", "score": 0.6724424362182617, "start": 1239, "end": 1259, "probe_score": 0.9762, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "UNHCR (2023) survey", "label": "NAMED_DATA", "score": 0.8195039629936218, "start": 1451, "end": 1470, "probe_score": 0.9926, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Situation Ukraine Refugee Situation", "label": "NAMED_DATA", "score": 0.5385103225708008, "start": 1553, "end": 1588, "probe_score": 0.2281, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "active PESEL UKR database", "label": "NAMED_DATA", "score": 0.6766122579574585, "start": 1671, "end": 1696, "probe_score": 0.735, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " heatlh and social work activities\n\n\nAdministrative and support service activities\n\n\nEducation\n\n\nInformation and communication\n\n\nProfessional, scientific and technical activities\n\n\nPublic administration and defense; compulsory social security\n\n\nConstruction\n\n\nFinancial and insurance activities\n\n\nAgriculture, forestry and fishing\n\n\nReal estate activities\n\n\nWater supply: sewerage, waste management and remediation activities\n\n\nElectricity, gas, steam and air conditioning supply\n\n\nMining and quarrying\n\n\nTransportation and storage\n\n\n\n**-1**\n\n\n\n**34**\n\n\n\n\n\n\n\n**Chart 8.** Share of companies reporting vacancies\n\n\n50%\n\n\n40%\n\n\n30%\n\n\n20%\n\n\n10%\n\n\n0%\n\n\n\n\n\n\n\nC\n\n\nI\n\n\nG\n\n\nQ\n\n\nN\n\n\nP\n\n\nJ\n\n\nM\n\n\nO\n\n\nF\n\n\nK\n\n\nA\n\n\nL\n\n\nE\n\n\nD\n\n\nB\n\n\nH\n\n\n\n\n\n**Source:** Deloitte own elaboration based on ZUS data.\n\n\n\n(more than 18 thousand), and wholesale\nand retail trade (more than 18 thousand).\nThe only sector that has seen a decline\nwas transportation and storage (by more\nthan 1 thousand). Unfortunately, public\ndata does not report how much of this\nchange is due to the refugees from Ukraine\nentering these sectors, or how much due\nto pre-2022 Ukrainian workers changing\ntheir jobs.\n\n\n\n2006\n-Q4\n\n\n\n2008\n\n-Q2\n\n\n\n2009\n\n-Q4\n\n\n\n2011\n\n-Q2\n\n\n\n2012\n-Q4\n\n\n\n2014\n-Q2\n\n\n\n2015\n\n-Q4\n\n\n\n2017\n-Q2\n\n\n\n2018\n\n-Q4\n\n\n\n2020\n-Q2\n\n\n\n2021\n-Q4\n\n\n\n2023\n-Q2\n\n\n\nThe number of workers with Ukrainian\ncitizenship since the beginning of the\nfull-scale war in Ukraine grew in all NACE <sup>21</sup>\nsectors apart from transportation and\nstorage. Since 2021, just before the\nescalation of war in 2022 in Ukraine,\nthe number of workers with Ukrainian\ncitizenship and social security insurance\ngrew the most in manufacturing (almost by\n34 thousand), accommodation and food\n\n\n\n**Source:** Deloitte own elaboration based on estimated data from <u>[https://nbp.pl/publikacje/cykliczne-materialy-analityczne-nbp/]", "output": {"entities": {"named_data": ["ZUS data"], "descriptive_data": [], "vague_data": ["public\ndata"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 9, "chunk": 1, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "ZUS data", "label": "NAMED_DATA", "score": 0.9001956582069397, "start": 770, "end": 778, "probe_score": 0.9555, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "public\ndata", "label": "VAGUE_DATA", "score": 0.7339048981666565, "start": 977, "end": 988, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " area. Differences in the extent of noise\npresent in the training data, as well as the reference evaluation measure, will not necessarily affect the\nranking of different types of models within the same context. But it explains much of the wide variation\nin R <sup>2</sup> observed in Table 1 across different studies, which underscores the benefits of evaluation studies\nthat compare different methods in the same context, using the same reference measure.\n\n\nGualavisi and Newhouse (2022) offer another stark example of how sensitive predictive accuracy is to\nthe source of training data. Using a census extract from 10 districts in Malawi, the analysis compared\nestimates of average village welfare imputed into a household census with estimates derived from\ncombining a survey with publicly available geospatial indicators. However, it also considers a third\noption, which involves hypothetically supplementing the survey with a partial registry, a “microcensus”\nthat interviews all households in a randomly selected 450 of the 4,500 villages with geolocated data.\nThis involves a two-step approach, where welfare is first predicted into the partial registry and then a\ngeospatial model is trained against the partial registry predictions.\n\n\nUsing a partial registry in this way yields an R <sup>2</sup> of 0.35, as opposed to 0.01 for the geospatial poverty\nmap based on survey data and 0.02 for the wealth estimates from Chi et al. (2021). These R <sup>2</sup> values are\nmuch lower than those cited in the previous section. The weak correlation between the Chi et al (2021)\nestimates and these census-based predictions reflects the challenge of distinguishing between village\nwelfare levels in this context. In particular, the sample consists of 4,500 villages, in 10 poor Malawian\ndistricts, for which names could be matched between the census and the Unified Beneficiary Registry\ndata containing household geocoordinates. In this context, the Chi et al", "output": {"entities": {"named_data": ["Unified Beneficiary Registry\ndata"], "descriptive_data": ["census extract from 10 districts in Malawi", "household census"], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001122", "page": 11, "chunk": 1, "title": "idu0ef5eaec903663043e60812b09f97c83f5551", "pdf_url": "https://local/prwp/idu0ef5eaec903663043e60812b09f97c83f5551.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "census extract from 10 districts in Malawi", "label": "DESCRIPTIVE_DATA", "score": 0.8871538043022156, "start": 597, "end": 639, "probe_score": 0.95, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "household census", "label": "DESCRIPTIVE_DATA", "score": 0.7296401262283325, "start": 715, "end": 731, "probe_score": 0.1313, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.6357887983322144, "start": 1374, "end": 1385, "probe_score": 0.5599, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Unified Beneficiary Registry\ndata", "label": "NAMED_DATA", "score": 0.8477479219436646, "start": 1858, "end": 1891, "probe_score": 0.5142, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "||Szczecin<br>||Gdańsk||||\n||Poznański|Bydgoszcz||~~Katowice~~||||\n|||||Łęczyń|ski||Lubiński|\n\n\n|Col1|Col2|Col3|Col4|Col5|Col6|Col7|Col8|\n|---|---|---|---|---|---|---|---|\n|||||||||\n|||||||||\n|||||||||\n|||||Warszawa||||\n|||||||||\n|||||||||\n|||Łodź|Wrocław|Kraków|||R² = 0,16|\n||Poz|nański|Szczecin|||||\n|||Gdańsk<br>~~Bydgoszcz~~||Katowice<br>Łęczy|ński||Lubiński|\n\n\n\n5000 6000 7000 8000 9000 10000 11000 12000\n\n\n**Average monthly gross earnings in enterprise sector in poviat of employment in 2022**\n\n\n\n\n\n8%\n\n\n7%\n\n\n6%\n\n\n5%\n\n\n4%\n\n\n3%\n\n\n2%\n\n\n1%\n\n\n0%\n\n4000\n\n\n10%\n\n\n9%\n\n\n8%\n\n\n7%\n\n\n6%\n\n\n5%\n\n\n4%\n\n\n3%\n\n\n2%\n\n\n1%\n\n\n0%\n\n4000\n\n\n\nUkrainian refugee educational attainment\nimplies from 18% (assuming refugees’\neducational attainment from November 2022\nsurvey) to 19% (July-August 2023) higher\n\nearnings than the general population. <sup>36</sup>\n\n\nPoviat-level geographical distribution of\nUkrainian refugees is more concentrated in\nhigh productivity agglomeration", "output": {"entities": {"named_data": [], "descriptive_data": ["November 2022\nsurvey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 16, "chunk": 1, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "November 2022\nsurvey", "label": "DESCRIPTIVE_DATA", "score": 0.8483458757400513, "start": 726, "end": 746, "probe_score": 0.967, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nCosta Rica Results in Education (CORE) (P181174)\n\n\nprovision of hardware (notebook computers and tablets) and connectivity for primary and secondary schools; in addition\nto computers, the Project will provide other equipment such as smart boards, projectors, headphones, robotics and\nrelated physical computation kits, routers to enhance internal connectivity); <sup>26</sup> [^26: It is expected that most of the hardware will be leased to MEP, as explained in the next paragraph. Computational services would be provided\nthrough modular mobile carts that will be wheeled to classrooms. Modeling with empirical data indicates that 153,785 computers would be sufficient\nto cover the needs of PNFT. PNFT has two dimensions: the first comprises computational thinking or computational science, which concerns the\nimplementation of the PNFT curriculum that requires 2 mandatory lessons per week. Dimension 2 comprises the use of computers and digital tools\n<u>for all subjects in the curriculum, which is expected to grow over time as progress in Dimension 1 generates awareness, interest, and capabilities.</u>] and (iii) support to the development and\nimplementation of a hybrid learning policy, its operational plan, and a communication strategy. This last activity would\ninclude the development of a national learning platform for virtual learning; implementation of a monitoring mechanism,\nsuch as the World Bank’s Education and Technology Readiness Index (ETRI); and development of digital resources such as\ne-books, multimedia contents, simulation exercises, and educational applications, as part of a unified learning\nmanagement and competency certification system. As with foundational learning, implementation of the PNFT as part of\nthe curriculum (it is not optative) will ensure that equal opportunity will be provided for girls and boys for all modules,\nand that girls will not lag behind boys in digital competencies, including coding and robotics. Computer Science teachers\nwould be specially trained to make sure that coding and robotics activities are gender inclusive (for example in the choice", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["empirical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000189", "page": 20, "chunk": 0, "title": "Costa Rica - Results in Education (CORE) Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099111524150039416/pdf/BOSIB-8191b179-7209-4faa-b5e0-11783bcd492d.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "empirical data", "label": "VAGUE_DATA", "score": 0.8254767060279846, "start": 621, "end": 635, "probe_score": 0.9432, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "unhcr.org/en/situations/ukraine)</u>\n4 According to the active PESEL UKR database.\n5 According to the active PESEL UKR database in October 2023.\n6 Deloitte calculations based on Multi-Sector Needs Assessment Poland 2023 survey data provided by UNHCR.\n\n\n06\n\n\n\n7  According to the Labour Force Survey data from Eurostat.\n8  According to the harmonized unemployment rates from Eurostat.\n9  According to the quarterly NBP survey.\n10 According to the UNHCR (2023) survey.\n11 According to the social security data until 30th September 2023.\n12 Deloitte calculations based on Multi-Sector Needs Assessment Poland 2023 survey data provided by UNHCR.", "output": {"entities": {"named_data": ["Labour Force Survey data from Eurostat", "Multi-Sector Needs Assessment Poland 2023 survey data"], "descriptive_data": ["quarterly NBP survey", "social security data until 30th September 2023"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 3, "chunk": 4, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Labour Force Survey data from Eurostat", "label": "NAMED_DATA", "score": 0.7073627710342407, "start": 279, "end": 317, "probe_score": 0.9701, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "quarterly NBP survey", "label": "DESCRIPTIVE_DATA", "score": 0.660219132900238, "start": 404, "end": 424, "probe_score": 0.0, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "social security data until 30th September 2023", "label": "DESCRIPTIVE_DATA", "score": 0.7203654646873474, "start": 487, "end": 533, "probe_score": 0.9598, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Multi-Sector Needs Assessment Poland 2023 survey data", "label": "NAMED_DATA", "score": 0.547087550163269, "start": 569, "end": 622, "probe_score": 0.9996, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Policy Research Working Paper 10762\n\n### **Abstract**\n\nThis study documents the impacts of climate change on\n\nfirm-level productivity by matching a globally comparable\nand standardized survey of nonagricultural firms covering\n154 countries with climate data. The findings show that\nthe overall effects of rising temperatures on productivity are negative but nonlinear and uneven across climate\nzones. Firms in hotter zones experience steeper losses with\nincreases in temperature. A 1 degree Celsius increase from\nthe typical wet-bulb temperature levels in the hottest climate zone (25.7 degrees Celsius and above) results in a\nproductivity decline of about 20.8 percent compared to\nfirms in the coldest climate zone. The effects vary not only\nbased on the temperature zones within which firms are\n\n\n\nlocated, but also on other factors such as firm size, industry\nclassification, income group, and region. Large firms, firms\nin manufacturing, and those in low-income countries and\nhotter climate zones tend to experience the biggest productivity losses. The uneven impacts, with firms in already\nhotter regions and low-income countries experiencing\nsteeper losses in productivity, suggest that climate change is\nreinforcing global income inequality. If the trends in global\nwarming are not reversed over the coming decades, there is\na heightened risk of widening inequality across countries.\nThe implications are especially dire for the poorest countries\n\nin the hottest regions.\n\n\n\nThis paper is a product of the World Bank Office of the Chief Economist, Africa Region and the International Monetary\n\nFund. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to\ndevelopment policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://\nwww.worldbank.org/prwp. The authors may be contacted at wkassa1@worldbank.org.\n\n\n_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development_\n_issues. An objective of the series is", "output": {"entities": {"named_data": [], "descriptive_data": ["survey of nonagricultural firms"], "vague_data": ["climate data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001529", "page": 1, "chunk": 0, "title": "idu1bc4ad5bd1491a1475d18b0e1339d04cbc643", "pdf_url": "https://local/prwp/idu1bc4ad5bd1491a1475d18b0e1339d04cbc643.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "survey of nonagricultural firms", "label": "DESCRIPTIVE_DATA", "score": 0.925554096698761, "start": 185, "end": 216, "probe_score": 0.9933, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "climate data", "label": "VAGUE_DATA", "score": 0.7814769744873047, "start": 245, "end": 257, "probe_score": 0.9776, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "up> Only about 13 percent of women are paid employees compared with\n23.3 percent of men. <sup>12</sup> [^12: UBOS Labour Force Surveys, 2013 and 2018.] Women also tend to hold lower-level positions: only 1.9 percent of women are employed as a\nmanager or administrator, and only 2.4 percent as an associate professional, compared with male rates of 2.4 and 3.4\npercent respectively. <sup>13</sup> [^13: UBOS 2018. Uganda Labour Force Survey.]\n\n\n**Table 1: Sex Segregation in the Labor Market (UBOS 2011/12 and 2016/17)**\n\n|Employment Status|2011/12|Col3|Col4|2016/17|Col6|Col7|\n|---|---|---|---|---|---|---|\n||**Male**|**Female**|**Total**|**Male**|**Female**|**Total**|\n|Paid employee|23.3|11.3|17.3|26.1|13.0|19.5|\n|Self-employed|58.1|66.3|62.2|69.5|79.8|74.8|\n|Contributing family worker|18.6|22.4|20.5|3.9|6.9|5.4|\n|Other forms of work|n/a|n/a|n/a|0.4|0.3|0.4|\n\n\n\n8. **Uganda has a strong culture of entrepreneurship, including among women.** The Global Enterprise Monitor survey\n(2012) ranked it the most entrepreneurial country in the world, with 88 percent of respondents saying they felt they had\n“high", "output": {"entities": {"named_data": ["UBOS Labour Force Surveys", "Uganda Labour Force Survey", "Global Enterprise Monitor survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000005", "page": 4, "chunk": 1, "title": "Concept Project Information Document (PID) - Generating Livelihoods and Opportunities for Women (GLOW) Uganda - P176747", "pdf_url": "http://documents.worldbank.org/curated/en/135361626935792550/pdf/Concept-Project-Information-Document-PID-Generating-Livelihoods-and-Opportunities-for-Women-GLOW-Uganda-P176747.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "UBOS Labour Force Surveys", "label": "NAMED_DATA", "score": 0.8861328959465027, "start": 109, "end": 134, "probe_score": 0.9957, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Uganda Labour Force Survey", "label": "NAMED_DATA", "score": 0.7849100828170776, "start": 413, "end": 439, "probe_score": 0.9977, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Global Enterprise Monitor survey", "label": "NAMED_DATA", "score": 0.8727930784225464, "start": 950, "end": 982, "probe_score": 0.9947, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSupport for Social Recovery Needs of Vulnerable Groups in Beirut (P176622)\n\n\nrisks including child marriage, domestic violence and intimate partner violence, sexual exploitation and\nassault, as well as intimidation and fear of violence within their communities. <sup>34</sup> Among Syrian refugees,\nthe most reported forms of violence against women and girls include physical assault, domestic and sexual\nviolence, emotional abuse, denial of resources, and forced and child marriage.\n\n**Psycho-social wellbeing**\n\n\n16. **The amalgam of the different crises affecting Lebanon have had a dire effect on the psycho-social**\n**wellbeing of its population, where levels of stress, worry, and pain soared to record levels in 2019, even**\n**before the shocks of the COVID-19 pandemic and the POB explosion.** In 2019, Gallup data showed that\nLebanese adults have experienced the most emotional blow between 2018 and 2019 worldwide. Their\nNegative Experience Index rose 18 points, while their Positive Experience Index score dropped 12 points. <sup>35</sup>\nThe percentage of Lebanese who experienced sadness more than doubled, from 19% to 40%, and nearly\ntwice as many were angry in 2019 (43%) compared to 2018 (23%). A national representative survey in\nLebanon conducted prior to the Syrian conflict showed that one in six people met criteria for at least one\nmental disorder, with 27% of these classified as “serious”. <sup>36</sup> Embrace, an NGO running a national suicide\nprevention hotline (1564), reported its call volume to have tripled between 2019 and 2020, with 18-to34-year-olds consistently accounting for more than half of this number but the share of other age brackets\ngrowing. <sup>37</sup> The call volume continued to increase in the", "output": {"entities": {"named_data": ["Gallup data"], "descriptive_data": ["national representative survey in\nLebanon"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000002", "page": 7, "chunk": 0, "title": "Project Information Document - Support for Social Recovery Needs of Vulnerable Groups in Beirut - P176622", "pdf_url": "http://documents.worldbank.org/curated/en/113021634329877822/pdf/Project-Information-Document-Support-for-Social-Recovery-Needs-of-Vulnerable-Groups-in-Beirut-P176622.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Gallup data", "label": "NAMED_DATA", "score": 0.8387576937675476, "start": 830, "end": 841, "probe_score": 0.9966, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "national representative survey in\nLebanon", "label": "DESCRIPTIVE_DATA", "score": 0.9042227268218994, "start": 1232, "end": 1273, "probe_score": 0.9714, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "I 2<br>Program LGs<br>have<br>strengthened<br>their<br>institutional<br>performance in<br>seven thematic<br>areas (as scored<br>in the APA)|110<br>million<br>US$|First<br>APA|0|By Program<br>completion|0|100%|Disbursement from the Bank to GoU will be determined as:<br>Compliance of MLGs with minimum access conditions;<br>Sum of scores of all MLGs calculated (non-minimum condition compliant<br>LGs are assigned a score of zero) and divided by 18;<br>A. If score equal to target for FY, full allocation,<br>B. If score below target for FY, pro-rata reduction,<br>C. If score above target for FY, pro-rata increase.<br> <br>Disbursement will be made provided that previous disbursements from GoU<br>to LGs have all been made.|\n\n\n40", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000006", "page": 47, "chunk": 2, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents.worldbank.org/curated/en/143681526614252328/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "_Sierra Leone_\n\n\nPRICES and GOVERNMENT FINANCE\n\n1981 1991 2000 2001 Inflation (%)\n_Domest)c_ _pHces_\n_(% change)_ c 1\nConsumer prices 16 7 102 7 -0.9 3 0 30 _< _\nImplicit GDP deflator 8 7 128 8 6 2 6 1 20\n\n_Govemment finance_ _10_\n_(% of GDP,_ _includes curent_ grants) 0\nCurrentrevenue .. 112 182 178 .10. 98 97 93 99 00 01\nCurrent budget balance .. -5 8 -4.5 -7 1 - GDP deflator _ CPI\nOverall surplus/deficit -10 4 -10.6 -12 3\n\n\nTRADE\n\n1981 1991 2000 2001 Export and Import levels (USS mnIll.)\n_(US$ millions)_\nTotal exports (fob) 147 176 75 78 400\nRutile . 72\nDiamonds (recorded) 32 10 21 300\nManufactures\nTotal imports (cHf) 317 158 161 303 20\nFood . 53 66 72 100\nFuel and energy 26 29 3d _ _8_\nCaptal goods .. 38 18 22  - __\n96 D6 97 9o 99 00 01\nExport price index _(1995=100)_ 90 86 87\nImport price Index (1995=100) 93 93 92 mExports ***Mrrports**\nTerms of trade (1995-100) 97 93 94\n\n\n\nBALANCE of PAYMENTS\n\n\n\n1981 1991 2000 2001 Curmnt account balance to GDP _(%)_\n_(US$_ _millions)_\nExports of goods and services 163 244 110 116 0\nImports of goods and services 349 226 212 252\nResource balance -186 18 -102 -137 .a*\n\n\n\nExports of goods and services 163 244 110 116 0\nImports of goods and services 349 226 212 252\nResource balance -186 18 -102 -137 .a*\n\nNet income -28 -60 -18 -20\nNet current", "output": {"entities": {"named_data": [], "descriptive_data": ["Export price index", "Import price Index"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012956", "page": 61, "chunk": 0, "title": "Ethiopia - Technical report on the Road Rehabilitation Project", "pdf_url": "https://documents.worldbank.org/curated/en/431611468032098571/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Export price index", "label": "DESCRIPTIVE_DATA", "score": 0.6043785214424133, "start": 751, "end": 769, "probe_score": 0.209, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Import price Index", "label": "DESCRIPTIVE_DATA", "score": 0.5586132407188416, "start": 792, "end": 810, "probe_score": 0.8072, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nThe Skilling Up Lebanon (SUL) Project\n\n\n**BASIC INFORMATION**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|A. Basic Project Data|Col2|Col3|Col4|\n|---|---|---|---|\n|Project ID<br>P176444|Parent Project ID (if any)|Environmental and<br>Social Risk<br>Classification<br>Low|Project Name<br>The Skilling Up Lebanon (SUL)<br>Project|\n|Region<br>MIDDLE EAST AND NORTH<br>AFRICA|Country<br>Lebanon|Date PID Prepared<br>12-Mar-2021|Estimated Date of Approval|\n|Financing Instrument<br>Investment Project<br>Financing|Borrower(s)<br>Beirut Digital District (BDD)<br>Talent Development Hub|Implementing Agency<br>Beirut Digital District<br>(BDD) Talent<br>Development Hub||\n\n\n\n**PROJECT FINANCING DATA (US$, Millions)**\n\n\n**SUMMARY-NewFin1**\n\n|Total Project Cost|0.35|\n|---|---|\n|**Total Financing**|0.35|\n|**Financing Gap**|0.00|\n\n\n\n**DETAILS-NewFinEnh1**\n\n|Non-World Bank Group Financing|Col2|\n|---|---|\n|Trust Funds<br>|0.35|\n|Lebanon Syrian Crisis Trust Fund|0.35|\n\n\n\n**B. Introduction and Context**\nCountry Context\n_Advancements in technologies will continue to have an increasingly significant impact on jobs in the coming_\n_years and decades_ . According", "output": {"entities": {"named_data": [], "descriptive_data": ["PROJECT FINANCING DATA"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000056", "page": 1, "chunk": 0, "title": "Project Information Document (PID) - The Skilling Up Lebanon (SUL) Project - P176444", "pdf_url": "http://documents.worldbank.org/curated/en/888861615794372950/pdf/Project-Information-Document-PID-The-Skilling-Up-Lebanon-SUL-Project-P176444.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "PROJECT FINANCING DATA", "label": "DESCRIPTIVE_DATA", "score": 0.5592765212059021, "start": 660, "end": 682, "probe_score": 0.1404, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " to modern energy solutions is\nalso expected to increase income-generating opportunities and improve the socioeconomic situation of\nhouseholds and MSMEs, with an expected positive impact on education and overall lifestyle. This means\nthat the results from the economic analysis can be considered as conservative estimates of the overall\neconomic benefits of the project.\n\n9. **The project is also expected to bring some benefits from reduced GHG emissions and local**\n**pollution.** In addition to the quantifiable benefits discussed above, the economic analysis also considers\n\n\n59 It is noted that this is a regional estimate as for Chad, such data are not available.\n60 Results of the household expenditure survey are provided in annex 6.\n\n\nPage 78 of 87", "output": {"entities": {"named_data": [], "descriptive_data": ["household expenditure survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 83, "chunk": 2, "title": "Chad - Energy Access Scale Up Project", "pdf_url": "http://documents.worldbank.org/curated/en/860701648216750651/pdf/Chad-Energy-Access-Scale-Up-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "household expenditure survey", "label": "DESCRIPTIVE_DATA", "score": 0.9004391431808472, "start": 688, "end": 716, "probe_score": 0.0638, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " level of development of a host economy_ . Various aspects have been found to enhance\n\nbackward linkages and productivity spillovers. Sanchez-Martin, De Pinies, and Antoine (2015) and\n\nAmendolagine et al. (2013) find that a country’s _level of GDP_ is positively associated with MNC\n\naffiliates’ use of local suppliers. Farole and Winkler (2014) report a positive productivity effect of an\n\ninteraction variable between the presence of MNC affiliates and the _level of spending on_ _education_ in\n\nhost economies. Developing countries with relative high levels of GDP and education expenditures can\n\nbe expected to incorporate larger pools of suitable suppliers—suppliers that are also more likely to be\n\nable to benefit from technology dissemination and productivity spillovers.\n\n\n_Institutional characteristics_ _of host economies._ These characteristics also affect the use of local\n\nsuppliers and productivity spillovers. Amendolagine et al. (2013) find that the quality of institutions in\n\nSub-Saharan African countries is important for local sourcing, indicated by an estimated positive effect", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001907", "page": 15, "chunk": 1, "title": "multinational corporation affiliates backward linkages and productivity spillovers in developing and emerging economies evidence and policy making", "pdf_url": "https://local/prwp/multinational-corporation-affiliates-backward-linkages-and-productivity-spillovers-in-developing-and-emerging-economies-evidence-and-policy-making.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2008, the SWF launched and completed an extensive national survey’ to further identify the poor and\nvulnerable in Yemen and apply improved targeting methods to the data collected in order to expand the\nprogram to cover those in need. It is expected that beneficiary application for SWF support and\nassessments of applicants’ eligibility will be a continuous process. The SWF newly established database\nis the most comprehensive national record of poor and vulnerable individuals available in Yemen. Such a\nnational database can be used to target and coordinate other funds and benefits across a range of social\nprograms.\n\n\n9. **The implementation of the** **SWF** **reforms and program expansion are entering a critical**\n**period requiring immediate technical assistance, policy guidance, capacity building and training**\n**support.** Technical assistance has been provided by the European Commission (EC) for several years,\nand more recently the World Bank has provided initial guidance on CT program design including\ntargeting. A draft core Operations Manual reflecting key reform elements of the program was developed\nin 2009 through World Bank technical assistance. Further guidance on (i) poverty-based targeting; (ii)\nreaching the ultra poor; (iii) phasing out the ineligible beneficiaries; (iv) assessing benefit levels; and (v)\nCT program fiscal implications and sustainability issues, is needed.\n\n\n10. Successful cash transfer programs build broad credibility and accountability among beneficiaries\nand other stakeholders. Over time, the SWF benefit payment system has shifted from people delivering\nactual cash (“cashiers”) to using intermediary agencies (i.e., post offices, banks) to control corruption in\nthe flow of cash transfer funds. Yet about 38 percent of the cash benefits is still being delivered by\ncashiers. The use of new technologies (e.g., mobile banks) to deliver 100 percent of funds through secure\nmechanisms needs to be explored and supported. The SWF needs to establish and apply clear and\ntransparent rules on", "output": {"entities": {"named_data": ["SWF newly established database"], "descriptive_data": ["extensive national survey", "national database"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000080", "page": 9, "chunk": 0, "title": "Yemen, Republic of - Social Welfare Fund Institutional Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/495501468170077604/pdf/533550PAD0P117101Official0Use0Only1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "extensive national survey", "label": "DESCRIPTIVE_DATA", "score": 0.7225503921508789, "start": 40, "end": 65, "probe_score": 0.2395, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "SWF newly established database", "label": "NAMED_DATA", "score": 0.7468171119689941, "start": 371, "end": 401, "probe_score": 0.1174, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "national database", "label": "DESCRIPTIVE_DATA", "score": 0.5804727673530579, "start": 506, "end": 523, "probe_score": 0.0216, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "output": {"entities": {"named_data": [], "descriptive_data": ["random survey"], "vague_data": ["statistical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019780", "page": 16, "chunk": 0, "title": "Ethiopia - Market Towns Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/898301468030352834/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "statistical data", "label": "VAGUE_DATA", "score": 0.7714613080024719, "start": 379, "end": 395, "probe_score": 0.582, "gold": "NON_MENTION", "gold_tier": "human-final"}, {"text": "random survey", "label": "DESCRIPTIVE_DATA", "score": 0.7173007130622864, "start": 1487, "end": 1500, "probe_score": 0.012, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "�\n\n\n\n\n\n \n\n\n���\n\n���\n\n���\n\n \n��\n\n\n\n\n\n\n\n�� ��\n\n \n��\n\n\n\n\n \n\n\n\n\n \n��\n\n\n\n\n\n\n\n�) �)\n\n\n���)\n\n\n\n$\n\n\n\n%\n\n&\n\n\n\n%\n\n&\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n\n%\n\n&\n\n\n\n%\n\n&\n\n\n\n\n\n\n\n\"\n\n��#� \n- - \n\n\n\n- \n\n\n��\n\n\n\n\n\n\n\n��\n\n\n\n%\n\n&\n\n\n \n\n\n��\n\n\n\n\n - \n\n\n\n\n\n\n\n���\n\n\n\n\n \n\n\n\n\n��� \n\n\n��\n\n\n\n\n��\n\n\n\n) ��\n\n\n\n\n- \n\n\n!\n\n\n\n����� \n\n\n���\n\n\n\n\n\n\n\n\n\n\n \n���\n\n\n \n\n\n���", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005658", "page": 30, "chunk": 0, "title": "wps6509", "pdf_url": "https://local/prwp/wps6509.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " analytics (ASA) (P176730), a payment\nsystems assessment is being carried out. The assessment will evaluate the performance of the payment system used under Merankabandi and will\nassess its scalability. In addition, the assessment will identify other existing e-payment options in the country that could complement the phonebased system in the case this is not scalable at national level.\n29 The _colline_ (“hill”) is the lowest administrative unit in Burundi\n30 This amount might be revised during the project implementation based on the Consumer Price Index.\n31 A mapping exercise of NGOs implementing human capital development and productive inclusion activities was carried out during project\npreparation. The assessment showed that there is an important number of international and national NGOs operating in all provinces of the\ncountry.\n\n\nPage 21 of 86", "output": {"entities": {"named_data": ["Consumer Price Index"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000130", "page": 25, "chunk": 2, "title": "Burundi - Cash for Jobs Project", "pdf_url": "http://documents1.worldbank.org/curated/en/768621641923064747/pdf/Burundi-Cash-for-Jobs-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Consumer Price Index", "label": "NAMED_DATA", "score": 0.6519708037376404, "start": 539, "end": 559, "probe_score": 0.0021, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "satisfied two or more rainy seasons; - Progress reports submitted\n2b.3 100% of houses benefit by implementing partners;\nmarginalized population                 - Beneficiary assessments\ngroups (female headed                 - NaCSA M&E data\nhouseholds, disabled and their\nfamilies); and\n2b.4 100% of beneficiaries\nwere selected by beneficiary\ncommunities.\n\n\n**3.** Proiect Management and\nInnovative Activities - NaCSA administrative data - Qualified implementing\n\n                                  - Capacity building event partners available to provide\n**3(a)** **Capacities of** assessments; capacity building and IEC\n**communities,** **chiefdomns,** **and** 3a.1 At least 5 successful - Participatory project activities at all levels;\n**district authorities to select,** capacity building events completion reviews; - A qualified full-time M&E\n**implement and maintain** carried out each year; - IDA supervision missions specialist is provided to\n**projects established** **and** NaCSA by another donor\n**strengthened** agency\n\n**3(b)** **Information, Education** 3b. 1 At least 40% of HHs are - Beneficiary assessments; - Non-NSAP activities\n**and Communication** aware of program; - NaCSA adrninistrative data; undertaken by NaCSA do not\n3b.2 At least 60%of chlefdom                  - IDA aide-memoires and detract from NaCSA ability to\nand district governments project status reports; and implement project.\naware of NSAP coverage,\ntargeting, methodology, and\nresults; and\n3b.3 At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA", "output": {"entities": {"named_data": ["NaCSA M&E data", "NaCSA administrative data", "NaCSA adrninistrative data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:021013", "page": 31, "chunk": 0, "title": "Ethiopia - Second Telecommunications Project", "pdf_url": "https://documents.worldbank.org/curated/en/977411468243875909/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "NaCSA M&E data", "label": "NAMED_DATA", "score": 0.8557507395744324, "start": 226, "end": 240, "probe_score": 0.0002, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "NaCSA administrative data", "label": "NAMED_DATA", "score": 0.7650092840194702, "start": 412, "end": 437, "probe_score": 0.0006, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "NaCSA adrninistrative data", "label": "NAMED_DATA", "score": 0.6916330456733704, "start": 1188, "end": 1214, "probe_score": 0.4531, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nRefugees from Ukraine are not yet\nutilising their full potential in the Polish\nlabour market. In May 2022, 46% of\narriving refugees declared that they had\nno knowledge of the Polish language\n(NBP, 2023). Over time, this percentage\nimproved, with data from November 2022\nshowing a result of 21%, though this still\nrepresents a large group of people who\ndo not know the local language <sup>24</sup> [^24: Due to possible differences in methodologies data from this surveys should not be directly compared], placing\nthem at risk of limiting possible jobs to\nthose below their educational level. Nearly\n40% of Refugees from Ukraine insured\nat ZUS on 30th June 2023 in Poland were\nemployed in elementary occupations <sup>25</sup> [^25: Elementary occupations include: Cleaners and helpers; Agricultural, forestry and fishery labourers; Labourers in mining, construction, manufacturing\nand transport; Food preparation assistants; Street and related sales and services workers; Refuse workers and other elementary workers.],\n\n\n\nwhile for all employed persons in Q2 2023\nthis percentage was only 5%. Furthermore,\nthe Deloitte Ukraine Refugee Pulse report\nindicates that 50% of respondents point\nto language barriers as an obstacle to\naccessing services to meet basic needs\n(Deloitte, 2023). Meanwhile, in the MSNA\nPoland 2023 survey, when asked about\nencountered barriers for accessing the\nlabour market, 34% of respondents\npointed to lack of language knowledge.\n\n\nSmooth inclusion of refugees on labour\nmarket thus far was enabled by proper\npolicies. In response to the war escalation\n\n\n\nin Ukraine and the influx of refugees into\nthe EU, prompt actions were taken both at\nEU and national level.\n\n\nRefugees from Ukraine in the European\nUnion are covered by the Temporary\nProtection Directive TPD, which was\nactivated on 4th March 2022 (European\nCouncil, 2022). The regulation aims to\nsupport EU Member States’ asylum\nschemes and to ensure harmonised\nrights for the incoming", "output": {"entities": {"named_data": ["Deloitte Ukraine Refugee Pulse report", "MSNA\nPoland 2023 survey"], "descriptive_data": [], "vague_data": ["data from November 2022"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 11, "chunk": 0, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data from November 2022", "label": "VAGUE_DATA", "score": 0.7676340341567993, "start": 322, "end": 345, "probe_score": 0.9875, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Deloitte Ukraine Refugee Pulse report", "label": "NAMED_DATA", "score": 0.8660871982574463, "start": 1185, "end": 1222, "probe_score": 0.9841, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "MSNA\nPoland 2023 survey", "label": "NAMED_DATA", "score": 0.9171611666679382, "start": 1377, "end": 1400, "probe_score": 0.9876, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**C.** **Sectoral and Institutional Context**\n\n\n9. Even prior to the onset of the Syrian conflict and the inflow of large numbers of Syrian\nrefugees, poverty in Lebanon was significant and regional disparities in living conditions were\nacute. It is estimated that nearly 27 percent of the Lebanese population, or 1.2 million people, are\npoor, living on less than US$4 per day, and seven percent, or 300,000 people, are extremely\npoor, living on less than US$2.40 per day (UNDP, 2008). <sup>3</sup> [^3: In 2013, the poverty rate was updated using the Consumer Price Index to US$3.84 for the lower (food) poverty line.] Poverty is significantly higher in\nsome regions, with the highest concentration of poor people found in the North governorate (52.5\npercent), followed by the South governorate (42 percent) and the Beka’a (29 percent).\n\n10. The Syrian conflict is projected to increase the poverty headcount of those below the\nupper poverty line by 170,000 people by end 2014. Simulations using household expenditures\ndata show that, between 2012 and 2014, poverty in Lebanon was projected to continue its\ndownward path in the absence of the Syrian conflict. In its presence, however, about 120,000\nLebanese are estimated to have been pushed into poverty in 2013, which is approximately three\npercent of the Lebanese (pre-conflict) population. If the current patterns were to continue, by\n2014 another 50,000 are expected to join the ranks of the poor. By 2014, the rate of poverty\nincidence in Lebanon would therefore be four percent higher due to the impact of the Syrian\nconflict. At the same time, the existing poor (about one in seven Lebanese) would be pushed\ndeeper into poverty through the impact on lower wages and higher unemployment rates.\n\n11. Geographically, the majority of the Syrian refugees", "output": {"entities": {"named_data": [], "descriptive_data": ["household expenditures\ndata"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000139", "page": 13, "chunk": 0, "title": "Lebanon - Emergency National Poverty Targeting Program Project", "pdf_url": "http://documents1.worldbank.org/curated/en/810511467987899324/pdf/PAD1030-ENGLISH-P149242-PUBLIC-FINAL-LEB-ENPTP-English.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "household expenditures\ndata", "label": "DESCRIPTIVE_DATA", "score": 0.8469590544700623, "start": 996, "end": 1023, "probe_score": 0.8508, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " policies in Finland,\nGermany, Ireland, Netherlands, Norway,\nSweden, Switzerland and the UK (no data\nfor Denmark). They find that non-EU15\nrefugees aged 25-64 who arrived when a\ndispersal policy was in place experience\n4.5 percentage points lower employment\nrates than for those not exposed to such\na policy. This may understate the effect,\nas for refugees who arrived 10 or less\nyears before the survey, the effect is\n17.5 percentage points, while it becomes\nstatistically insignificant afterwards.\nFor the six countries for which data on\nresidence is available, non-dispersed\nrefugees show clearly stronger clustering in\neconomically stronger regions (measured\nby GDP per capita).\n\n\n24\n\n\n\n25\n\n\n\nEconomic research on dispersal policies\nand labour market inclusion focuses on\nthe strength of local labour markets and\nsize of local ethnic networks. While some\nscholars find only the strength of local\nlabour markets to be significant and not\nco-national networks (Foged, Hasager, and\nPeri, 2022), or inconsistent results for conational networks (Müller, Pannatier, and\nViarengo, 2022), others find effects only for\nco-national networks (Damm, 2014).\n\n\nMigrants dispersed to weaker labour\nmarkets experience poorer inclusion\noutcomes in subsequent years, and vice\nversa. These outcomes can pertain to\nemployment, earnings, or human capital\naccumulation, and have been shown in\nDenmark (Foged, Hasager, and Peri, 2022;\nAzlor, Damm, and Schiltz-Nielsen, 2020),\nGermany (Aksoy, Giray, Poutvaara, and\nSchikora, 2020), Norway (Godøy, 2017),\nSweden (Åslund, Östh, and Zenou, 2010;\nÅslund and Rooth, 2007), and Switzerland\n(Müller, Pannatier, and Viarengo, 2022),\nas well as the previously described crosscountry study. This could in principle stem", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on\nresidence"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 12, "chunk": 1, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data on\nresidence", "label": "VAGUE_DATA", "score": 0.6544746160507202, "start": 532, "end": 549, "probe_score": 0.3768, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " immigrant inflow comprised less educated workers.\n\n\n39\n\n\n\nMacroeconomic modelling generally finds\nthat immigration increases output, while\ncross-country econometric estimates\nfind also positive impacts on labour\nproductivity. The first approach builds\na theoretical model of the economy\ncalibrated to the particular circumstances,\nwhich allows us to simulate counterfactuals\nand observe all changes in the economy.\nThe second approach relies on empirical\ndata, usually over many years and\ncountries, trying to isolate the effect of\nimmigration, but gives no information on\nthe channels through which these effects\noperate. In the present case it would not\nbe practical to follow anything else than the\nfirst approach. Unfortunately, it relies on\nthe canonical labour market model.\nAs Peri (2014) elaborates, that model\nassumes that immigration is simply a\nshift in the labour supply for a given\nlabour demand and given labour supply\nof native workers. It further assumes\nthat immigrants are essentially identical\nto natives in that they enter the same\n\n\n38\n\n\n\noccupations and perform the same tasks,\nthe native workers do not change their\noccupations and tasks, while firms do\nnot adjust (at least in the short term).\nIn effect, immigrants grow output, but\nslightly lower wages. This is the case in\nthe modelling performed (Chapter 3), as\nwell as in the NBP general equilibrium\nmodelling exercise for the pre-2022\nUkrainian workers 2013-2018 performed\nby Gradzewicz, Jabłonowski, Sasiela, and\nŻółkiewski (2021). Conversely, Peri (2014)\nsurveys 270 econometric estimates from\n27 studies published over the 1982-2013\nperiod on the impact of immigration\non native wages. He shows that effects\nfor a very large immigrant inflow of 10\npercentage points (five-times larger than\nthe refugees from Ukraine share in Poland)\non native wages range from -1% to +1%,\nwith most estimates clustered around zero,\nfrom -0.1% to +0.1%. Similarly, Gromadzki\nand Lewandowski (2023) examine\neconometrically the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["empirical\ndata"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 19, "chunk": 2, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "empirical\ndata", "label": "VAGUE_DATA", "score": 0.7871390581130981, "start": 446, "end": 460, "probe_score": 0.0095, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEducation Quality Improvement Project (P179363)\n\n\nin line with international best practices. The need for data-informed, evidence-based decision-making is\ncrucial for enhancing the effectiveness of resource use and improving the quality of education. The\nassessment and EMIS data should help identify constraints to learning and iteratively adapt school\nconditions through smarter investments in the education sector.\n\n20. **The proposed project would complement the work done by other development partners and**\n**education stakeholders.** The scale and interconnected nature of the challenges Moldova faces, in\ncomparison with the fiscal space afforded by public finances and development partner allocations, require\ncareful choice of focus to maximize the development impact of the new project. The Education Sector\nPlan and Education Strategy 2030 identify the following priority areas in the education sector: (a)\ndigitalizing the educational system, (b) strengthening human capital in education (through teacher\nprofessional development), and (c) improving infrastructure/learning environment. The Global\nPartnership for Education (GPE) multiplier grant of US$5 million, approved in 2022 and implemented by\nthe United Nations Children's Fund (UNICEF), is focused on digital transformation of primary and\nsecondary education. Therefore, the proposed project with World Bank financing and the expected new\nGPE multiplier grant of US$5 million will focus on enhancing teacher effectiveness and improving the\nquality and resilience of learning environments in selected educational institutions with the lower\nsocioeconomic composition and serving a larger number of disadvantaged students. It will also support\ntechnical assistance (TA) and capacity building for reforms—all in tight collaboration with other\ndevelopment partners. This will help ensure smarter investments in the education sector and\nsustainability of results. The project will be financed by IBRD and by the GPE, Early Learning Partnership\n(ELP) multi-donor trust fund, and Global Concessional Financing Facility (GCFF). The activities will build\nupon the current ELP", "output": {"entities": {"named_data": ["EMIS data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000185", "page": 18, "chunk": 0, "title": "Moldova - Education Quality Improvement Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099051123142553305/pdf/BOSIB-624554c1-598f-4576-aa60-cca7d93b64e7.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "EMIS data", "label": "NAMED_DATA", "score": 0.7408868074417114, "start": 289, "end": 298, "probe_score": 0.6851, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " with, or benefit from, developed infrastructure.|Percentage of households in program areas reporting<br>satisfaction with, or benefit from, developed infrastructure.|\n|Value<br>(Quantitative or<br>Qualitative)|0|75%||HH felt they<br>benefit from (range<br>for 4 regions):<br>Roads: 53–76%<br>Water: 29-69%<br>Soil conservation:<br>22-67%|\n|Date achieved|01/01/2005|06/30/2006|||\n|Comments<br>(incl. % achievement)<br>|Baseline Survey preliminary results by region, aggregated<br>results not yet available.|Baseline Survey preliminary results by region, aggregated<br>results not yet available.|Baseline Survey preliminary results by region, aggregated<br>results not yet available.|Baseline Survey preliminary results by region, aggregated<br>results not yet available.|\n\n\n\n\n- 22", "output": {"entities": {"named_data": [], "descriptive_data": ["Baseline Survey preliminary results by region", "Baseline Survey preliminary results by region"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016507", "page": 24, "chunk": 3, "title": "Ethiopia - Productive Safety Nets Project (APL1)", "pdf_url": "https://documents.worldbank.org/curated/en/674291468246407282/pdf/ICR80P0877070Box327426B01PUBLIC1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Baseline Survey preliminary results by region", "label": "DESCRIPTIVE_DATA", "score": 0.5897651314735413, "start": 419, "end": 464, "probe_score": 0.2856, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Baseline Survey preliminary results by region", "label": "DESCRIPTIVE_DATA", "score": 0.528156578540802, "start": 507, "end": 552, "probe_score": 0.0509, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "s|Limited<br>|Single Stage - One<br>Envelope||||0.00|Pending<br>Implementa<br>tion|||||||2020-06-15||||||||2020-08-10||2020-12-08||\n|ET-MOE-177325-CW-RFQ /<br>Procurement for<br>Construction of 2 separate<br>blocks latrine (4 seats for<br>boys and 4 seats for girls<br>with urinals and hand<br>washing facilities) and new<br>water supply in Gelana<br>Woreda implemented by<br>Oromia Education Bureau<br>|IDA / 64450|Institutional Water Supply,<br>Sanitation, and Hygiene<br>(Institutional WASH)|Post|Request for<br>Quotations|Limited<br>|Single Stage - One<br>Envelope||||0.00|Pending<br>Implementa<br>tion|||||||2020-06-15||||||||2020-08-10||2020-12-08||\n|ET-MOE-177326-CW-RFQ /<br>Procurement for<br>Construction of 2 separate<br>blocks latrine (4 seats for<br>boys and 4 seats for girls<br>with urinals and hand<br>washing facilities) and new<br>water supply in Boke<br>Woreda implemented by<br>Oromia Education Bureau<br>|IDA / 64450|Institutional Water Supply,<br>Sanitation, and Hygiene<br>(Institutional WASH)|Post", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:010348", "page": 12, "chunk": 2, "title": "Ethiopia - AFRICA- P167794- One WASH?Consolidated Water Supply, Sanitation, and Hygiene Account Project (One WASH?CWA) - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/259541590735310670/pdf/Ethiopia-AFRICA-P167794-One-WASH-Consolidated-Water-Supply-Sanitation-and-Hygiene-Account-Project-One-WASH-CWA-Procurement-Plan.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nEducation Quality Improvement Project (P179363)\n\n\nages 6–7 years were on the waiting list for a place in preschools. The situation was aggravated by the\nRussia’s invasion of Ukraine, which triggered a massive influx of refugees. Over 107,000 Ukrainian\nrefugees remain currently in Moldova, of which 53 percent are children and around 11,500 are between\n0 and 4 years of age. The lack of places in the kindergarten is an issue not only for children but also for\nparents, particularly mothers, <sup>19</sup> [^19: Despite a large influx of women into the main jobs in the service sector, they continue to be underrepresented in the workforce\nand earn less than men. The main cause of the differences is related to the greater responsibilities of women in raising their\nchildren and housework. The data for 2019 prove that the existence of a preschool-age child in the family significantly influences\nthe presence of men and women on the labor market. In the urban area, the employment rate of men with at least one child is\n76.2 percent, while for women it is only 41 percent, representing a gender gap of 35.1 percentage points.] The GoM committed to expand ECEC coverage for younger cohorts of 2year-olds, particularly for disadvantaged children. Over 20,000 seats need to be created in 1,000 new\nclassrooms with appropriate learning environment and trained educators. The GoM is working to\nincentivize the private sector participation in the ECEC provision, which is currently in the nascent stage,\nthrough revisions of regulatory environment and financing mechanism.\n\n**Resilient and High-Quality Teaching and Learning Environment**\n\n15. **The COVID-19 pandemic highlighted the importance of having a resilient, high-quality learning**\n**environment, but schools in Moldova appear to be weak in resilience to external shocks.** Resilience of\nschools is defined as the ability and capacity to withstand natural and man-made hazards, featuring\nteaching and learning environment that both protects", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data for 2019"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000185", "page": 16, "chunk": 0, "title": "Moldova - Education Quality Improvement Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099051123142553305/pdf/BOSIB-624554c1-598f-4576-aa60-cca7d93b64e7.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data for 2019", "label": "VAGUE_DATA", "score": 0.8119204640388489, "start": 814, "end": 827, "probe_score": 0.9917, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " to that of Russia in terms of the Gini index reduction. As in Russia, in Belarus\nthe PGT scenario delivers more equalization than the PDI scenario (Lopez-Calva et al., 2017). Poverty reduction\nin Belarus is lower. However, it does not mean that the fiscal interventions reduce poverty less in Belarus than in\nRussia, it is merely the reflection of the fact that the 4 USD PPP poverty in Belarus is zero in disposable income,\nso the reduction in poverty is at its maximum possible level.\n\n\nThe Belarusian taxation has a very different redistribution impact when compared to the EU. In most of the EU\ncountries, the PIT tax is equalizing due to its progressive nature. The flat PIT structure in Belarus, however, delivers\nvery little redistribution, while the redistribution task is completely delegated to the expenditure side of the fiscal\npolicy. Given the high level of possible tax evasion in Belarus, this design of the fiscal policy is optimal. The VAT\ntax, in contrast, is not regressive in Belarus, unlike in many EU countries. This is achieved through multiple VAT\nexemptions.\n\n\n**5.** **Conclusions**\n\n\nThis paper presents the assessment of fiscal incidence in Belarus using the Commitment to Equity (CEQ) methodology developed in Lustig & Higgins (2016). Using the household budget survey and aggregate data we have\nallocated fiscal interventions across households. The allocation allows us to measure the effect of fiscal policies on\nredistribution and poverty.\n\n\nFiscal policies in Belarus effectively redistribute income from the top to the bottom of income distribution - 97.5%\nof population with market income below 10 USD PPP benefit from these policies. The direct transfers (including\npensions) and direct taxes lower the national poverty measure by 17 percentage points. They also decrease the Gini\n\n\n34", "output": {"entities": {"named_data": [], "descriptive_data": ["household budget survey"], "vague_data": ["aggregate data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:007176", "page": 35, "chunk": 2, "title": "wps8216", "pdf_url": "https://local/prwp/wps8216.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "household budget survey", "label": "DESCRIPTIVE_DATA", "score": 0.902252733707428, "start": 1276, "end": 1299, "probe_score": 0.2577, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "aggregate data", "label": "VAGUE_DATA", "score": 0.7370420098304749, "start": 1304, "end": 1318, "probe_score": 0.9749, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\n- Advance with the development of training and\n\nawareness plans on the Displacement Law for all\n\npublic bodies involved in identifying and\n\nresponding to the population.\n\n\n- Strengthen the inter-institutional and\n\nmultisectoral coordination mechanisms within the\n\nframework of the CIPPDV, which allows them to\n\ndesign and execute a general plan for the\n\nimplementation of the Law in the short and\n\nmedium term.\n\n\n- Include actions to respond to internal\n\ndisplacement within the framework of its powers,\n\nthrough its annual operational plans and\n\ninstitutional strategic plans in line with the powers\n\nassigned in the Law.\n\n\n- Develop information campaigns aimed at the\n\ngeneral population so that displaced and at-risk\n\npeople can learn about their rights and the\n\nmechanisms to access them.\n\n\n- Promote and guarantee the consultation and\n\neffective participation of internally displaced\n\npersons and persons at risk of displacement at all\n\nlevels of design and implementation of public\n\npolicy.\n\n\n- Foster and strengthen autonomous\n\norganizational and advocacy processes in\n\nrelation to the response to internal displacement.\n\nIt is essential to strengthen the role of monitoring,\n\nfollow-up and oversight of civil society\n\norganizations for the correct and transparent\n\nimplementation of the Law.\n\n\n## **7**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000656", "page": 6, "chunk": 1, "title": "Honduras - IDP Law - April 2023", "pdf_url": "https://reliefweb.int/attachments/600eb2cb-9f93-46cc-bf02-5e40fef52935/Honduras%20-%20IDP%20Law%20Report%20-%20April%202023.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "-Household-Survey\n19 http://documents.worldbank.org/curated/en/571081569598919068/Informing-the-Refugee-Policy-Response-in-UgandaResults-from-the-Uganda-Refugee-and-Host-Communities-2018-Household-Survey\n20 Uganda Digital Economy for Africa (DE4A) Report, Country Diagnostic, 2020\n21 Uganda Digital Economy for Africa (DE4A) Report, Country Diagnostic, 2020\n\n\nJan 15, 2021 Page 5 of 26", "output": {"entities": {"named_data": [], "descriptive_data": ["Household-Survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000033", "page": 4, "chunk": 3, "title": "Project Information Document - Uganda Digital Acceleration Program - P171305", "pdf_url": "http://documents.worldbank.org/curated/en/630051615474731857/pdf/Project-Information-Document-Uganda-Digital-Acceleration-Program-P171305.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Household-Survey", "label": "DESCRIPTIVE_DATA", "score": 0.57745760679245, "start": 1, "end": 17, "probe_score": 0.925, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\nparticipatory mapping of the prevalent hazards and the exposure hot spots, such as damageprone community infrastructure, storage facilities, settlement or roads and bridges. These\nmapping activities use state-level hazard and risk maps <sup>125</sup> as a starting point for more refined,\ncontextualized validation of the model-based assessments.\n\n\n(c) As part of the participatory resource mapping, existing hazard protection infrastructure is\ncatalogued and local needs are assessed for structural measures (for example, levees, flood\nwalls, drainage) and/or non-structural measures (for example, early warning, hazard-informed\nsettlement development and improved disaster response).\n\n\n(d) DRM-related priority needs and the list of DRM measures are consolidated at the community\n\nlevel with the other subprojects.\n\n\n(e) If selected from the PPL, the respective DRM measures will be costed and evaluated, that is,\n\nregarding their technical requirements and feasibility.\n\n\n(f) Finally, training of DRM focal points at the _boma_ / _payam_ level is to ensure adequate O&M of\nthe DRM measures while also aiming to strengthen local DRM capacities in general.\n\n\n125 These are generated in the complementary, GFDRR-funded DRM-FCV Nexus project “Assessment and Analysis of Intersectional Risk in South\nSudan” on the basis of the Fathom Global flood model (2019) and available population and settlement exposure data.\n\n\nPage 87 of 94", "output": {"entities": {"named_data": [], "descriptive_data": ["state-level hazard and risk maps", "population and settlement exposure data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 92, "chunk": 0, "title": "South Sudan - Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/824121596765983121/pdf/South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "state-level hazard and risk maps", "label": "DESCRIPTIVE_DATA", "score": 0.8586950898170471, "start": 306, "end": 338, "probe_score": 0.8025, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "population and settlement exposure data", "label": "DESCRIPTIVE_DATA", "score": 0.8821970820426941, "start": 1475, "end": 1514, "probe_score": 0.6098, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Strengthened municipal capacity achieved by central government**|**DLIs 5 and 6: Strengthened municipal capacity achieved by central government**|**DLIs 5 and 6: Strengthened municipal capacity achieved by central government**|**DLIs 5 and 6: Strengthened municipal capacity achieved by central government**|**DLIs 5 and 6: Strengthened municipal capacity achieved by central government**|\n\n\n58 In the areas of linkage between municipal physical development plan, five-year development plan and budgeting; municipal own source revenue; procurement performance; municipal\ncore financial management; execution/implementation of budget for improved urban service delivery; including LED, accountability and transparency (monitoring and communication);\nenvironmental and social sustainability.\n59 See the verification tool. Average score of all MLGs in the annual performance assessment, DLI 2. The targets are based on the estimates, based on review of the Mock Assessment\nconducted in November 2017.\n60 See **the verification tool** . Average score of all MLGs in the annual performance assessment, DLI 2.\n61The reason for disbursing against the adoption of capacity building plan in FY2018/19 is as follows: The performance assessments will be done between September and November of\neach FY. These assessments will measure LG performance in the preceding FY and will impact grant disbursement for the following FY. LG budgeting and planning process starts in\nDecember and runs through June, using the indicative grant funding amounts announced at the end of the assessment in November. Therefore, the execution of the first Program capacity\nbuilding plan), will be measured in the assessment in Sept-Nov 2020, and its findings will affect disbursements in FY2021/22.\n\n33", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000006", "page": 40, "chunk": 3, "title": "Uganda - Support to Municipal Infrastructure Development Program Project : additional financing", "pdf_url": "http://documents.worldbank.org/curated/en/143681526614252328/pdf/UGANDA-PAD-04272018.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 2\nPage 4 of 4\n\n**Project Component 3 -** US$ **4.10 million**\n\n**Improve the Government's Capacity to Manage Sector Reforms** will be addressed through:\n(i) supporting the activities of the CNOSEGE in its effort to coordinate the reforms and raise\nresources to support the reform; (ii) capacity building support to the Ministry of Education key\nunits such as the Planning Unit _(Service de la Planification),_ and the Education Projects Bureau\n(BEPE); and (iii) other technical assistance necessary to improve private public partnership in\neducation, development of an effective gender strategy, and possible reforms in textbook policy.\n\n\n_Detailed Description of Sub-components:_\n\n\n_(i) CNOSEGE:_ The Executive Secretariat of CNOSEGE is responsible for implementing the\nreform program. The project will finance the secretariat including its fund-raising activities.\n\n\n_(ii) Support to MOE Planning Unit:_ The project will finance capacity building of the Ministry of\nEducation's Planning Unit, through expert assistance in dealing with the collection of educational\nstatistics, the production of a _carte scolaire_ and analysis of census or household survey data, and\nkey staff in the BEPE including the purchase of project management tools (finance and\nprocurement). The planning unit will also carry out the monitoring and evaluation studies\nrequired under the project. In addition, the unit will implement and monitor the Environmental\nManagement Plan (EMP).\n\n\n_(iii) Additional Technical Assistance_ will also be provided to enable the ministry to develop more\ncost effective strategies including exploring the possibility of cost effective public/private\npartnerships. Technical Assistance will also be provided to develop strategies to reduce the\ngender gap in enrollments as well as the gap by income group. Pilot studies will also be financed\nunder the credit for optimal designs in school construction, demand financing, sanitation upkeep\nand maintenance, and", "output": {"entities": {"named_data": [], "descriptive_data": ["census or household survey data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012139", "page": 35, "chunk": 0, "title": "Kenya - Group Farm Rehabilitation Project", "pdf_url": "https://documents.worldbank.org/curated/en/383521468914054732/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "census or household survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8749487400054932, "start": 1138, "end": 1169, "probe_score": 0.5876, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "I. **STRATEGIC CONTEXT**\n\n**A.** **Country Context**\n\n\n1. **Burundi’s economic performance improved over the last decade but the gains are**\n**fragile and poverty and vulnerability remain widespread.** After the Arusha breakthrough peace\nagreements in 2000 and the subsequent decline in violence by 2005, the Government of Burundi\nmanaged to stabilize the country's economy in a fragile environment. However, since early 2015,\nthe political crisis has reversed some of these previous gains and triggered a severe economic\ncrisis, which impacts the most vulnerable and their ability to meet basic needs <sup>1</sup> [^1: Burundi – Fragility Assessment Note – March 2016] . The economy\ncontracted by seven percent in 2015 and prospects for recovery are still uncertain. At the same\ntime, several donors have suspended aid to the country, decreasing the overall contribution from\n13 to 10.3 percent of Gross Domestic Product (GDP) between 2014 and 2015. Furthermore, public\ndebt is increasing.\n\n2. **The latest poverty data** <sup>**2**</sup> [^2: 67.1 percent in 2006 and 64.9 percent in 2014] **shows that nearly two-thirds of Burundians are poor and**\n**that the 2015 Millennium Development Goals (MDG) target on poverty reduction (17.1**\n**percent) was not met** . Per capita gross national income more than doubled between 2005\n(US$130) and 2013 (US$280) in nominal terms, but fell to US$270 in 2015. The country is now\nthe second poorest in Africa after Malawi. To start reducing poverty significantly, the economic\ngrowth rate would have to reach at least seven percent; growth would need to become more\ninclusive, especially in rural areas; and a strong safety net would need to be put in place in order\nto prevent the deepening", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["poverty data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000157", "page": 11, "chunk": 0, "title": "Burundi - Social Safety Nets Project", "pdf_url": "http://documents1.worldbank.org/curated/en/900951482030099834/pdf/1482030098559-000A10458-PAD-Burundi-SSN-11282016.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "poverty data", "label": "VAGUE_DATA", "score": 0.7362188696861267, "start": 1008, "end": 1020, "probe_score": 0.9226, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Project** **Manaeem2nt** <sup>**and**</sup> <sup>million)</sup> administrative data appropriate, and clear in\n\n\n\ndefining the and\n**Innovative Activities**\n\n\n\nresponsibilities of all parties;\nNaCSA retains competent\n**(a) Capacity Building**\n\n\n\nstaff;\n\n                                             - Other governnent and donor\n**(b)** **Information and**\n\nsupport mobilized for\n\n\n\nsupport mobilized for\n**Sensitization**\ndecentralization to\ncomplement NaCSA efforts;\n(c) **Monitoring and**\n\n\n\n**Evaluation**\n\n\n\n**(d)** **Technical Assistance**\n\n\n(e) **Operating** Expenses\n\n\n\n-28", "output": {"entities": {"named_data": [], "descriptive_data": ["administrative data"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:018893", "page": 32, "chunk": 1, "title": "Ethiopia - Cultural Heritage Project", "pdf_url": "https://documents.worldbank.org/curated/en/833811468744299980/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "administrative data", "label": "DESCRIPTIVE_DATA", "score": 0.6927050352096558, "start": 64, "end": 83, "probe_score": 0.562, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "PE will be responsible for drawing up the list of schools to be constructed/rehabilitated for each\nyear of the project, as well as conducting site visits.\n\n\nA General Procurement Notice (GPN) will be forwarded to IDA for publication in the United Nation's\njournal _Development Business,_ so as to advertise major activities with regard to works, goods and\n\nconsultant services which would be required under an international competitive bidding process. Such\nNotices are to be updated every year until all contracts and assignments have been awarded.\n\n\nThe BEPE has on its staff a junior procurement officer who has been trained by a seasoned resident\nprocurement consultant (during the course of 8 months). In addition, two other staff working in the BEPE,\n\n(the architect and the financial officer) are both familiar with IDA procurement guidelines, both having\nreceived on-the-job training from experts or from procurement staff on past IDA projects. The:\nprocurement assessment recommended that a seasoned senior procurement officer be recruited, who\nwould be responsible for the overall procurement process, and who would manage the procuremenlt\nplanning and monitoring, and supervise the junior procurement officer. This is necessary to ensure\nquality and internal control. It is recommended that the junior procurement officer benefit fromn\nadditional procurement training, and that the senior procurement officer be recruited within the next 8\nmonths, under TORs acceptable to the Bank.\n\n\n**Procurement Documentation**\n\n\nThe Credit would finance civil works, goods, technical assistance, and contractual teacher salaries.\nProcurement under the Credit would be carried out in accordance with the World Bank's Guidelines for\n_\"Procurement under IBRD Loans and Credits\"_ - January 1995, and revised up to January 1999, and\n\n_\"Selection and Employment of Consultants by World Bank Borrowers\" -_ January 1997 and revisions up to\nJanuary 1999. Project components financed by other external donors would follow the respective donor\nregulations.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:019153", "page": 43, "chunk": 1, "title": "Kenya - Telecommunications Project", "pdf_url": "https://documents.worldbank.org/curated/en/853991468285057419/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank** Implementation Status & Results Report\nTransforming Health Systems for Universal Care (P152394)\n\n\n**Data on Financial Performance**\n\n\n**Disbursements (by loan)**\n\n\nProject Loan/Credit/TF Status Currency Original Revised Cancelled Disbursed Undisbursed % Disbursed\n\n\nP152394 IDA-58360 Effective USD 150.00 150.00 0.00 141.29 6.42 96%\n\n\nP152394 TF-A2561 Effective USD 40.00 40.00 0.00 31.88 8.12 80%\n\n\nP152394 TF-A2792 Closed USD 1.10 1.10 0.00 0.95 0.15 86%\n\n\n**Key Dates (by loan)**\n\n\nProject Loan/Credit/TF Status Approval Date Signing Date Effectiveness Date Orig. Closing Date Rev. Closing Date\n\n\nP152394 IDA-58360 Effective 15-Jun-2016 04-Jul-2016 29-Sep-2016 30-Sep-2021 30-Sep-2023\n\n\nP152394 TF-A2561 Effective 15-Jun-2016 04-Jul-2016 29-Sep-2016 30-Sep-2021 30-Jun-2023\n\n\nP152394 TF-A2792 Closed 15-Jun-2016 04-Jul-2016 04-Jul-2016 30-Jun-2020 31-May-2022\n\n\n**Cumulative Disbursements**\n\n\n12/13/2022 Page 7 of 8", "output": {"entities": {"named_data": ["Data on Financial Performance"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:003853", "page": 6, "chunk": 0, "title": "Disclosable Version of the ISR - Transforming Health Systems for Universal Care - P152394 - Sequence No : 14", "pdf_url": "https://documents.worldbank.org/curated/en/099073301312327009/pdf/P152394098c5620e40963c07d8151af8f62.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Data on Financial Performance", "label": "NAMED_DATA", "score": 0.6341397166252136, "start": 119, "end": 148, "probe_score": 0.0013, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<br>month. The indicator will be<br>measured based on data<br>collected regularly and<br>reported by the Ministry of<br>Economy and Trade.|Monthly,<br>on the last<br>day of each<br>month.<br>|Ministry of<br>Economy and<br>Trade<br>|Ministry of Economy<br>and Trade will collect,<br>process, and<br>centralize price and<br>quantity data from<br>contracts, invoices,<br>other commercial<br>documents presented<br>by the eligible<br>importers<br>|Ministry of Economy and<br>Trade<br>|\n|Percentage of beneficiaries’ feedback<br>addressed through the GM within the<br>timeframe publicly communicated by the<br>project|The indicator will track the<br>extent to which the<br>feedback from project<br>beneficiaries is recorded<br>and addressed.|Biweekly<br>|MOET<br>|Data will be collected<br>through the project GM<br>as described in the<br>POM<br>|MOET<br>|\n|Improved wheat and bread price<br>monitoring system implemented by MOET|<br>The improved price<br>monitoring system will|Daily (for<br>internation|Source of<br>international|International data will<br>be collected from open|MOET<br>|\n\n\nPage 37 of 46", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["International data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000019", "page": 41, "chunk": 1, "title": "Lebanon - Wheat Supply Emergency Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/408131653327258940/pdf/Lebanon-Wheat-Supply-Emergency-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "International data", "label": "VAGUE_DATA", "score": 0.7566803097724915, "start": 1027, "end": 1045, "probe_score": 0.3818, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " good, passing, and failing.\n\n   - **Junior secondary student comprehensive development evaluation (implementation starts**\n**with the Grade 6 cohort in 2018).** The evaluation emphasizes student’s experience in selfinitiated research projects and participation in social and vocational activities. The evaluation\nwill be in the form of an essay, which will form a required part for graduation from junior\nsecondary education.\n\n   - **Senior secondary education enrollment system (implementation starts with the Grade 6**\n**cohort in 2018).** Nearly half of the enrollment of the leading high schools will be allocated to\njunior secondary that have no competitive admissions criteria for incoming primary school\ngraduates to enter.\n_<u>Source:</u>_ <u>Shanghai Education Commission (https://mp.weixin.qq.com/s/0MbaKjvmEtfkaIlshIiMiw).</u>\n\nIn the meantime, there has already been evidence of the positive effect of this curriculum reform\non the overall student ability well-being. Yu and Mocan (2018) investigated the causal effect of\nthis high school curriculum reform on students’ educational outcomes in university, as well as on\ntheir happiness, mental and physical health, self-confidence, confidence in their academic ability,\nand attitudes toward learning. Using survey data on students from 15 universities and employing\na difference-in-differences strategy, the research found that the curriculum reform had a significant\nand positive effect on all student outcomes analyzed. Specifically, students who were exposed to\nthe new curriculum in high school have better academic performance in university, are more\nwilling to learn and master the course material, are more engaged in social activities in university,\nand are more confident in their academic and overall ability. In addition, the students who were\n\n\n44", "output": {"entities": {"named_data": [], "descriptive_data": ["survey data on students from 15 universities"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:001999", "page": 45, "chunk": 1, "title": "progress and challenges of upper secondary education in china", "pdf_url": "https://local/prwp/progress-and-challenges-of-upper-secondary-education-in-china.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "survey data on students from 15 universities", "label": "DESCRIPTIVE_DATA", "score": 0.8504157662391663, "start": 1270, "end": 1314, "probe_score": 0.8233, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " rate of native or other\nimmigrants, except an actual slight positive\nimpact on the wages of native women.\nEven in a conservative scenario that\nassumes negative effects of labour\nmarket competition in the form of higher\nunemployment and slower real wage\ngrowth, an increase in the labour force\ntranslates into larger personal incomes and\nhigher private consumption, which results\nin a larger tax revenue. These effects were\nstrengthened by an influx of capital from\nabroad.\n\n###### In total, the general government revenue increased by 0.8-1.1% in 2022 and 1.05-1.45% in 2023. In monetary terms, this amounts to 10.1-13.7 billion PLN in 2022 and 14.7-19.9 billion PLN in 2023.\n\n\n\nIf estimates quoted by a government offical\nof public expenses on refugees of around\n15 billion PLN in 2022 and 5 billion in 2023 <sup>13</sup> [^13: E.g. vice-president of Polish Development Found Bartosz Marczuk estimated it at around 16 billion PLN, but this estimation also included spending of\nNGOs which was combined with spendings of local governments <u>[Polska pomoc dla Ukrainy 2022 - ile kosztowała? - Infor.pl.](https://www.infor.pl/prawo/nowosci-prawne/5635962,Polska-pomoc-dla-Ukrainy-2022-ile-kosztowala.html)</u>]\nare accurate, we can conclude that they\nwere more than offset by the additional tax\nrevenue. In the long-term, refugees should\nincrease yearly government revenue by\naround 0.85-1.3%.\n\n\n**Unaccounted positive externalities**\nAll our theoretical economic modelling\nresults are conservative lower bound\nestimates, as econometric studies from\nother countries have found immigration\nto have additionally a positive impact\non labour productivity that cannot be\naccounted for using the available data.\nAccording to these econometric studies,\nimmigration can not only raise economic\noutput (i.e., more workers equal more\nproduction), but more importantly labour\nproductivity (i.e., more value added per\nworker)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["available data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 4, "chunk": 2, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "available data", "label": "VAGUE_DATA", "score": 0.5525404214859009, "start": 1689, "end": 1703, "probe_score": 0.6607, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " potential GDP should\nbe higher by around 0.9-1.35% due to\nrefugees contributions. <sup>44</sup> [^44: Note that long term refers to the time when the economy fully adjusts with no additional shocks. We do not model the current refugees from Ukraine\nchildren growing up and entering the labour market.]\n\n\nOur results are consistent with the\nprevious, similar studies. In estimating\nGDP impacts we take an approach that\nis most similar to the previous studies of\nthe pre-2022 Ukrainian migrants by NBP\neconomists (Gradzewicz, Jabłonowski,\nSasiela, and Żółkiewski, 2021; Strzelecki,\nGrowiec, and Wyszyński, 2022), but unlike\nthe previous Oxford Economics and ours\nimpact estimates of Ukrainian refugees\n(Urban, 2022; Deloitte, 2022) we do not\nallow for the possibility of a positive\nproductivity shock, because there is little\ndata to credibly estimate its size. Below,\nwe summarise impacts yielded by these\nstudies. As studies were done under\ndifferent assumptions on the number of\n\n\n\n\n\n\n\n\n\n41  Aggregate region in model consisting of Ukraine, Russia, Belarus, Moldova, Czechia, Slovakia, Hungary, Romania and Bulgaria.\n42  In other words it was assumed that money that would be spent e.g. through credit action for investments in Eastern Europe were spent for\nconsumption in Poland.\n\n\n34\n\n\n\n43  Data from forecast of Ministry of Finance from October 2023, <u>[Wytyczne dotyczące wskaźników makroekonomicznych - Ministerstwo Finansów - Portal](https://www.gov.pl/web/finanse/wytyczne-sytuacja-makroekonomiczna)</u>\n<u>[Gov.pl (www.gov.pl).](https://www.gov.pl/web/finanse/wytyczne-sytuacja-makroekonomiczna)</u>\n44  Note that long term refers to the time when the economy fully adjusts with no additional shocks", "output": {"entities": {"named_data": [], "descriptive_data": ["Data from forecast of Ministry of Finance"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 17, "chunk": 3, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Data from forecast of Ministry of Finance", "label": "DESCRIPTIVE_DATA", "score": 0.8212373852729797, "start": 1295, "end": 1336, "probe_score": 0.973, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "** <br>The HFA Baseline report found that 40 percent of kebeles (4 out of 10) in the highlands and 87.5 percent of kebeles (7 out of 8) in the lowlands used one<br>committee structure for targeting of PSNP and HFA beneficiaries. Achievement at completion is based on an aggregate of highlands and lowlands kebeles<br>(11 out of 18 total kebeles). This question was not included in the 2021 HFA assessment or the 2022 PSNP performance report so no updated<br>measurement is available to measure progress. <br>**Source**: 2018 IFPRI HFA Baseline Report.|<br>**Comments (achievements against targets):** <br>The HFA Baseline report found that 40 percent of kebeles (4 out of 10) in the highlands and 87.5 percent of kebeles (7 out of 8) in the lowlands used one<br>committee structure for targeting of PSNP and HFA beneficiaries. Achievement at completion is based on an aggregate of highlands and lowlands kebeles<br>(11 out of 18 total kebeles). This question was not included in the 2021 HFA assessment or the 2022 PSNP performance report so no updated<br>measurement is available to measure progress. <br>**Source**: 2018 IFPRI HFA Baseline Report.|<br>**Comments (achievements against targets):** <br>The HFA Baseline report found that 40 percent of kebeles (4 out of 10) in the highlands and 87.5 percent of kebeles (7 out of 8) in the lowlands used one<br>committee structure for targeting of PSNP and HFA beneficiaries. Achievement at completion is based on an aggregate of highlands and lowlands kebeles<", "output": {"entities": {"named_data": ["2018 IFPRI HFA Baseline Report"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005448", "page": 39, "chunk": 2, "title": "Ethiopia - Rural Productive Safety Net Project", "pdf_url": "https://documents.worldbank.org/curated/en/099120423100031042/pdf/BOSIB05f9c7f7f0730a6bd0a0071798cc86.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "2018 IFPRI HFA Baseline Report", "label": "NAMED_DATA", "score": 0.5436077117919922, "start": 520, "end": 550, "probe_score": 0.9991, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Emergency Food and Nutrition Security Project (P163559)\n\n\n16. **The agricultural potential is huge but largely unrealized.** Favorable soil, water, and climatic\nconditions render more than 70 percent of South Sudan’s total land area suitable for crop production and\n60 percent of the country’s population already lives in high to medium potential areas. However, less than\n4 percent of the total land area is currently cultivated, and at 0.8‐0.9 tons per ha (FAO/WFP, 2011),\naverage cereal yields are lower than those in Uganda (1.6 tons per ha), Kenya (2 tons per ha) and Ethiopia\n(3 tons per ha).\n\n\n17. **Years of conflict and displacement have destroyed household capacity as well as productive**\n**relationships, traditional markets, infrastructure, and social and economic institutions that support the**\n**sector.** As a result, most agriculture in the country is now subsistence and is characterized by limited use\nof productivity enhancing measures, limited acreage (0.32 ha per capita against a per capita land holding\nof 13 ha), high costs of production <sup>6</sup> [^6: High production costs are mainly due to high daily wage rates juxtaposed to high labor requirements for preparing (especially\nbush clearance) land for cultivation.], and low output per hectare. Most farmers produce less food than\nthey require for subsistence and nearly 75 percent of all farming households experience food shortages\n(hunger gap) for at least three months a year. National level data shows that despite some increase in\narea cropped under cereals, total production has been on the decline since 2005 and that production\ngenerally lags consumption by an average of 30 percent. IPC analyses show that populations in Phases 2\n(Stressed), 3 (Crisis) and 4 (Emergency) have been increasing steadily over time (Figure 3).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["National level data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000038", "page": 17, "chunk": 0, "title": "South Sudan - Emergency Food and Nutrition Project", "pdf_url": "http://documents.worldbank.org/curated/en/713081494122547885/pdf/South-Sudan-PAD-04282017.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "National level data", "label": "VAGUE_DATA", "score": 0.6728533506393433, "start": 1493, "end": 1512, "probe_score": 0.9808, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " do so for safety and economic reasons.\nAfghan returnee households are large and although most families have at least one person working for pay, they\nhave low job stability and low wages. According to survey data, most returnees work as daily wage laborers in\nnon‐agriculture and they generally experience a decrease in the employment rate, wage, and job stability after\nreturning to Afghanistan. Data indicate that there were as many men as women among Afghans living in Pakistan\nin 2011 but more women (54 percent) than men returned to Afghanistan between 2015 and 2017. <sup>31</sup> [^31: World Bank. “Living conditions and settlement decisions of recent Afghan returnees: Findings from a 2018 World Bank Phone Survey of\nAfghan Returnees”, _forthcoming_ .]\n\n\n**D. Results Chain**\n\n44. The project supports, through a programmatic, multi‐sector, multi‐implementation agency approach, the short,\nmedium, and long‐term measures required to increase economic integration of Afghan returnees, IDPs, and host\ncommunities in the cities supported by the project. The project will implement a range of policy and operational\nactivities identified through multiple consultations and surveys with the GoIRA, potential beneficiaries, and\nstakeholders (e.g. UN agencies, civil society, refugees). These measures include, among others: (a) provision of\ncivil documents and information services to Afghan refugees in Pakistan; (b) creation of job opportunities through\nlabor intensive public works; (c) removal of regulatory red tapes (such as cumbersome processes of applying for\nconstruction permits), (d) provision of and improvements to market infrastructure at municipal and Gozar levels\nwhich for years have had limited business activity. Together, these measures are expected to strengthen an\nenabling environment for economic opportunities in the target cities where there is a high influx of displaced\npeople which will facilitate new business activities, create immediate short‐term jobs, and promote economic\nopportunities. This theory of change is expressed in the flow‐", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000123", "page": 26, "chunk": 1, "title": "Afghanistan - Eshteghal Zaiee - Karmondena (EZ-Kar) Project", "pdf_url": "http://documents1.worldbank.org/curated/en/714251547070785057/pdf/Afghanistan-Eshteghal-Zaiee-Karmondena-EZ-Kar-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "survey data", "label": "VAGUE_DATA", "score": 0.7626906633377075, "start": 202, "end": 213, "probe_score": 0.7549, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "*5**\n\n71 0\n**13** 0\n**44** **5**\n\n\n**1887-97** **1e97-07**\n\n\n**4 7** **3 3**\n**8 4** **4** **5**\n5 0 **9** **9**\n5 4 **4 3**\n\n**3 0** 1 5\n-0 **I** 8 7\n**14 6** 0 8\n**159** **3 0**\n\n\n```\n Q\n```\n\n**-10**\n\n\n**_-20_**\n\n\n\n**_7_**\n\n\n\n**-E-** **-lrrwrls**\n\n\n\nNote 2007 data we preliminary **estmates**\nThis tacde was produced **from** the Development Ecunomlcs LDB database\n\n- nie **413-** **_sthow_** four **k e y** tndicators in the counby (in bold) compared with its iraome-gnxg, **average** **If** data ore **mkssing.** **_the_** diamond **wilt**\n**be** mmplete\n\n\n80", "output": {"entities": {"named_data": ["Ecunomlcs LDB database"], "descriptive_data": [], "vague_data": ["2007 data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000080", "page": 85, "chunk": 5, "title": "Yemen, Republic of - Social Welfare Fund Institutional Support Project", "pdf_url": "http://documents1.worldbank.org/curated/en/495501468170077604/pdf/533550PAD0P117101Official0Use0Only1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "2007 data", "label": "VAGUE_DATA", "score": 0.659112811088562, "start": 257, "end": 266, "probe_score": 0.8681, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "Ecunomlcs LDB database", "label": "NAMED_DATA", "score": 0.8239709138870239, "start": 344, "end": 366, "probe_score": 0.9616, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<br>Qualification<br>Selection|Open - National<br>||150,000.00|0.00|Pending<br>Implementation|2021-08-12||2021-09-02||2021-10-16||||||||2021-11-15||2021-12-20||2022-12-20||\n|KE-NT-243837-CS-CQS /<br>Consultancy for Medium Term<br>Survey on Affordable Housing<br>|IBRD / 89580|Technical Assistance|Post|Consultant<br>Qualification<br>Selection|Open - National<br>||295,000.00|0.00|Pending<br>Implementation|2021-08-12||2021-09-02||2021-10-16||||||||2021-11-15||2021-12-20||2022-12-20||\n|KE-NT-243841-CS-CQS /<br>Consultancy for<br>Standardization of Mortgage<br>Lending Practices<br>|IBRD / 89580|Technical Assistance|Post|Consultant<br>Qualification<br>Selection|Open - National<br>||100,000.00|0.00|Pending<br>Implementation|2021-08-19||2021-09-09||2021-10-23||||||||2021-11-22||2021-12-27||2022-12-27||\n\n\nPage 1", "output": {"entities": {"named_data": ["Survey on Affordable Housing"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016920", "page": 1, "chunk": 13, "title": "Kenya - AFRICA EAST- P165034- Kenya Affordable Housing Finance Project - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/701481605801173997/pdf/Kenya-AFRICA-EAST-P165034-Kenya-Affordable-Housing-Finance-Project-Procurement-Plan.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Survey on Affordable Housing", "label": "NAMED_DATA", "score": 0.5637704133987427, "start": 230, "end": 258, "probe_score": 0.0106, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**6** Persons who are displaced within their country and to whom UNHCR extends\nprotection and/or assistance. It also includes people in IDP-like situations. This\ncategory is descriptive in nature and includes groups of persons who are inside\ntheir country of nationality or habitual residence and who face protection risks\nsimilar to those of IDPs but who, for practical or other reasons, could not be\nreported as such.\n\n**7** IDPs of concern to UNHCR who have returned to their place of origin during 2018.\n\n**8** Refers to persons who are not considered as nationals by any State under\nthe operation of its law. This category refers to persons who fall under the\nagency’s statelessness mandate because they are stateless according to this\ninternational definition, but data from some countries may also include persons\nwith undetermined nationality. The figures reported includes stateless persons\nwho are also refugees from Myanmar or IDPs in Myanmar. Most of these people\noriginate from Rakhine State. UNHCR’s statistical reporting currently follows\na methodology that reports on one legal status as a person of concern only.\nHowever, due to the extraordinary size of the newly displaced stateless population\nin Bangladesh, UNHCR considered it important to reflect the dual status that\nthis population group possesses as to do otherwise might convey the mistaken\nimpression that the overall number of stateless persons has declined significantly,\npending a review of UNHCR reporting on statelessness. This approach will not\nbe replicated in the database and in the Excel version of this table, and therefore,\n[figures may differ. See Annex Table 7 at http://www.unhcr.org/statistics/18-WRD-](http://www.unhcr.org/statistics/18-WRD-table-7.xls)\n[table-7.xls for detailed notes.](http://www.unhcr.org/statistics/18-WRD", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data from some countries"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000649", "page": 67, "chunk": 0, "title": "UNHCR Global Trends: Forced Displacement in 2018", "pdf_url": "https://reliefweb.int/attachments/5ee61624-975c-3354-9b7e-f2c1e9c8185a/5d08d7ee7.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data from some countries", "label": "VAGUE_DATA", "score": 0.7050071954727173, "start": 771, "end": 795, "probe_score": 0.8046, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " urban ones). What is more, the food-dedicated budget coefficients were much\nhigher for poorer households and also remained fairly high for richer rural households\n\n\n2 Source: United Nation Office for the Coordination of Humanitarian Affairs (OCHA).\n3 Kolbe et al. (2010) estimated that 158,679 people in Port-au-Prince died during the quake or in the six-week\nperiod afterwards owing to injuries or illness.\n4 According to the Household Living Conditions Survey (HLCS), 2001.\n\n\n3", "output": {"entities": {"named_data": ["Household Living Conditions Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:005027", "page": 4, "chunk": 2, "title": "wps5850", "pdf_url": "https://local/prwp/wps5850.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Household Living Conditions Survey", "label": "NAMED_DATA", "score": 0.8766892552375793, "start": 428, "end": 462, "probe_score": 0.9985, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "output": {"entities": {"named_data": [], "descriptive_data": ["household expenditure survey data", "data from the Household Survey"], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000049", "page": 38, "chunk": 1, "title": "Croatia - Reconstruction Project for Eastern Slavonia, Baranja and Western Srijem", "pdf_url": "http://documents1.worldbank.org/curated/en/347691468746725804/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "household expenditure survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8699104189872742, "start": 565, "end": 598, "probe_score": 0.7323, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.5808603167533875, "start": 870, "end": 881, "probe_score": 0.1461, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from the Household Survey", "label": "DESCRIPTIVE_DATA", "score": 0.5346028804779053, "start": 1978, "end": 2008, "probe_score": 0.1121, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " 2.2.2 Percentage of students in schools with secure Wifi connection**|\n|Description<br>|This indicator measures the proportion of students in primary and secondary schools with wifi connection in all<br>classrooms in use by students.<br>|\n|Frequency<br>|Annual<br>|\n|Data source<br>|MEP Department of Statistics|\n|Methodology for Data<br>Collection<br>|Annual end-of-year school survey.|\n|Responsibility for Data<br>Collection<br>|MEP Department of Statistics<br>|\n|**IRI 2.2.3 Percentage of Grade 9 students who participate in the Bebras Challenge competition**|**IRI 2.2.3 Percentage of Grade 9 students who participate in the Bebras Challenge competition**|\n|Description<br>|This indicator measures Grade 9 students annual participation in the Bebras challenge as registered online by MEP’s<br>Department of Technological Resources for Education (DRTE) or successor department in charge of the PNFT<br>|\n|Frequency<br>|Annual<br>|\n|Data source<br>|Online registration for Bebras|\n|Methodology for Data<br>Collection<br>|Bebras participation is registered for each school through online portal|\n|Responsibility for Data<br>Collection<br>|DRTE or successor department in charge of PNFT<br>|\n|**IRI 2.3.1 Item Bank for automatized learning assessments developed**|**IRI 2.3.1 Item Bank for automatized learning assessments developed**|\n|Description<br>|This indicator measures the development and regular update of an item bank with validated items for use in<br>standardized assessments in primary and secondary schools for selected subjects and", "output": {"entities": {"named_data": [], "descriptive_data": ["Annual end-of-year school survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000189", "page": 37, "chunk": 1, "title": "Costa Rica - Results in Education (CORE) Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099111524150039416/pdf/BOSIB-8191b179-7209-4faa-b5e0-11783bcd492d.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Annual end-of-year school survey", "label": "DESCRIPTIVE_DATA", "score": 0.9138479828834534, "start": 354, "end": 386, "probe_score": 0.313, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " was poor in 2021 as floods affected both agriculture and oil production and subnational\nconflict flareups constrained economic activities in parts of the country. Consequently, the economy is estimated to have\ncontracted by 5.1 percent in FY2020/21 and poverty to have increased by 2.3 percentage points to 79.3 percent <sup>2</sup> [^2: World Bank (2022). Towards a Jobs Agenda - South Sudan Economic Monitor (February 2022): Washington, DC] . The\nrecent shocks had detrimental effects on household welfare as income from farming was already reduced for 38 percent\nof households (HHs) and had stopped entirely for 11 percent of HHs during the COVID-19 pandemic in 2020 <sup>3</sup> [^3: World Bank (2020). Socioeconomic impacts of COVID-19 - South Sudan Economic Update (December 2020): Washington, DC] . Inflation\naveraged 43 percent in FY2020/2021 (compared to 33 percent in FY2019/2020) but was on a declining path in the first\nhalf of FY2021/2022. However, high frequency data indicate that food prices started increasing in February 2022.\nNevertheless, inflation is expected to decline gradually over the medium term and will benefit from improved fiscal and\nmonetary discipline, exchange rate market liberalization, and deepening public financial management reforms. South\nSudan’s fiscal position benefited from higher than projected oil revenue, improved domestic revenue mobilization, and\nfiscal consolidation efforts. The overall FY2020/21 budget deficit is estimated to have narrowed to about 6.9 percent of\nGross Domestic Product (GDP) from 9.8 percent in FY2019/20. Nevertheless, the government is accumulating arrears to\npublic service salaries, currently estimated at about two percent of GDP or five months of salaries, while South Sudan\nremains at high risk of debt distress, with total public debt estimated at 59.5 percent of GDP at end of FY2020/21. Given\ndeclining oil production and the lingering effects of climate shocks, the economy could", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["high frequency data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000153", "page": 11, "chunk": 1, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents1.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "high frequency data", "label": "VAGUE_DATA", "score": 0.7571456432342529, "start": 963, "end": 982, "probe_score": 0.4024, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\n\n\n\n\n\n\n\n|Monitoring & Evaluation Plan: PDO Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **|**Definition/Description **|**Frequency **|**Datasource **|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|Beneficiaries of social safety net programs||This indicator<br>will be<br>measured at<br>least on a<br>quarterly<br>basis during<br>missions and<br>ISRs<br>|SNSOP MIS<br>which hosts<br>beneficiary<br>registration<br>and payment<br>data<br>|The implementing<br>partner will collect<br>beneficiary data during<br>targeting and<br>registration. The<br>payment service<br>provider will document<br>payment data and<br>share with the<br>implementing partner<br>|Implementing Partner<br>|\n|Beneficiaries of social safety net<br>programs - Female||This indicator<br>will be<br>measured at<br>least on a<br>quarterly<br>basis during<br>missions and<br>ISRs<br>|SNSOP MIS<br>which hosts<br>beneficiary<br>registration<br>and payment<br>data<br>|The implementing<", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["beneficiary data", "payment data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000153", "page": 55, "chunk": 0, "title": "South Sudan - Productive Safety Net for Socioeconomic Opportunities Project", "pdf_url": "http://documents1.worldbank.org/curated/en/889471654610458548/pdf/South-Sudan-Productive-Safety-Net-for-Socioeconomic-Opportunities-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "beneficiary data", "label": "VAGUE_DATA", "score": 0.5927293300628662, "start": 655, "end": 671, "probe_score": 0.0877, "gold": "NON_MENTION", "gold_tier": "v1"}, {"text": "payment data", "label": "VAGUE_DATA", "score": 0.5629788041114807, "start": 765, "end": 777, "probe_score": 0.0486, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Box 2.** Labour productivity of refugees in relation to the rest of population\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nTo gauge the labour productivity of Ukrainian refugees in relation to the rest of the population we **Chart 14.** Distribution of workers (refugees from Ukraine vs. natives and other immigrants) by average earnings in a poviat\nperformed back-of-the-envelope calculations. Unfortunately, publicly available data for the refugee and _Persons registered for social security on 30.09.2023_\ngeneral populations is gathered differently and for different time periods. Assuming that such results\n\nUkrainian refugees\n\nare broadly correct – educational attainment and geographical distribution imply higher earnings (a\nproxy for labour productivity) of refugees than the general population, while their employer firm sizes, 10%\n\n\n9%\n\n\n\nUkrainian refugees\n\n\n\n10%\n\n\n\n9%\n\n\n\n\n|Col1|Col2|Col3|Col4|Warszaw|a|Col7|Col8|\n|---|---|---|---|---|---|---|---|\n|||Nearly**10% of re**<br>work in Warsaw|**  fugees**|||||\n|||||||||\n||||Wrocław|||||\n|||||||||\n|||||Kraków||||\n|||Łodź|Poznań||||R² = 0,20|\n|||Szczecin<br>||Gdańsk||||\n||Poznański|Bydgoszcz||~~Katowice~~||||\n|||||Łęczy", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["publicly available data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 16, "chunk": 0, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "publicly available data", "label": "VAGUE_DATA", "score": 0.7299280762672424, "start": 522, "end": 545, "probe_score": 0.9864, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " will also borrow elements from other approaches used for service\ndelivery in fragile and displacement contexts, including strong engagement with communities to\nencourage participation in and ownership of project activities.\n\n51. **Lessons from safety net projects around the world suggest the need for transparent**\n**and objective targeting criteria,** **particularly in fragile settings, to avoid overlapping of**\n**interventions and elite capture and to improve overall efficiency** . The project will rely on\nseveral methods for targeting (described in Supplemental Attachments, Targeting Methodology\navailable in the project file), and will ensure that its objectives, intended beneficiaries, and the\nselection process are clearly communicated. The project also builds on early lessons on targeting\nfrom the PFS, as well as lessons on the establishment of the Unified Social Registry, methods for\nregistration, payment systems, and grievance redress mechanisms. Finally, the project draws on\nglobal evidence suggesting that the combination of cash plus accompanying measures tends to be\nthe most effective way to incentivize the use of services while smoothing consumption and\nimproving livelihoods.\n\n52. **The project builds on a recent World Bank analysis of the dynamics of refugee**\n**inclusion to understand potential areas of tension with host communities** . <sup>27</sup> Though there is\nscant global evidence on successful approaches to promote social cohesion among forcibly\n\n\n26 Republic of Chad, Additional Financing Education Sector Reform Project Phase II (P163740), Project Appraisal Document, June\n2, 2017.\n27 Watson et al., Refugee and Host Communities in Chad: Dynamics of Economic and Social Inclusion, May 2018. The World\nBank.\n\n\nPage 25", "output": {"entities": {"named_data": ["Unified Social Registry"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000035", "page": 29, "chunk": 1, "title": "Chad - Refugees and Host Communities Support Project", "pdf_url": "http://documents.worldbank.org/curated/en/658761536982256019/pdf/PAD2809-PAD-PUBLIC-disclosed-9-12-2018-IDA-R2018-0286-1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Unified Social Registry", "label": "NAMED_DATA", "score": 0.7479856610298157, "start": 866, "end": 889, "probe_score": 0.0224, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "<br>re Results|Post|Request for Quota<br>tions|Limited|Single Stage - One E<br>nvelope||7,200.00|0.00|Pending Impl<br>ementation|||||||2019-01-10||||||||2019-03-08||2019-05-15||\n|KE-VIHIGA COUNTY-86425-G<br>O-RFQ / Print and laminate 1<br>000 copies of Intergrated Ma<br>nagement of Childhood Illne<br>sss recording forms for distri<br>bution in all facilities|IDA / 58360|Improving Primary Health Ca<br>re Results|Post|Request for Quota<br>tions|Limited|Single Stage - One E<br>nvelope||500.00|0.00|Pending Impl<br>ementation|||||||2018-12-15||||||||2019-02-09||2019-06-10||\n|KE-VIHIGA COUNTY-85172-G<br>O-RFQ / Print 3000 No. of eac<br>h of the following health data<br>reporting tools for all 94 Heal<br>th Facilities MPDSR,EPI REG,A<br>NC REG,MATERNITY REG,MO<br>THER TO CHILD BOOKLETS|IDA / 58360|Improving Primary Health Ca<br>re Results|Post|Request for Quota<br>tions|Limited|Single Stage - One E<br>nvelope||16,500.00|25,755.64|Signed|||||||2018-11", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["health data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:007532", "page": 6, "chunk": 4, "title": "Kenya - EASTERN AND SOUTHERN AFRICA- P152394- Transforming Health Systems for Universal Care - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099810001182319612/pdf/P1523940b59a430a10a33e0335cc5522ea9.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "health data", "label": "VAGUE_DATA", "score": 0.6698057651519775, "start": 657, "end": 668, "probe_score": 0.267, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\n**I.** **STRATEGIC CONTEXT**\n\n\n**A. Country Context**\n\n\n1. **South Sudan was beset by decades of armed conflicts even prior to its independence in 2011,**\n**and these have only become increasingly complex in the years since.** Southern Sudan, as the region was\ncalled before independence, has been marred by conflict since 1955, just a year before Sudan attained its\nindependence from British colonial rule. The region experienced systematic marginalization and\nunderdevelopment under both British and Sudanese rule, inhibiting it from developing its physical and\nhuman capital. Consequently, at its independence in July 2011, South Sudan ranked almost at the bottom\nof the global development indicators with little infrastructure, basic services provided almost entirely\nthrough humanitarian aid, and an economy completely dependent on oil. Renewed civil conflict broke out\nin December 2013 and has only recently subsided with the formation of a new government in February\n2020, pursuant to the terms of the September 2018 Revitalized Peace Agreement. <mark>As a result of decades</mark>\n<mark>of violence, nearly 7.5 million people of the estimated 14 million total population rely on some type of</mark>\n<mark>humanitarian assistance or protection.</mark> <sup>1</sup> [^1: UNOCHA (United Nations Office for Coordination of Humanitarian Affairs). 2020. _Humanitarian Needs Overview 2020_, p. 3]\n\n\n2. **The country is highly vulnerable to climate change and natural disasters, and increased stress**\n**on natural resources is fueling local conflicts** . The Global Climate Risk Index ranked the country 125 out\nof 171 between 1998 and 2018. <sup>2</sup> [^2: Germanwatch. 2019. _Global Climate Risk Index 2020_, p. 42.] With a strong reliance on subsistence farming and", "output": {"entities": {"named_data": ["Global Climate Risk Index"], "descriptive_data": ["global development indicators"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 14, "chunk": 0, "title": "South Sudan - Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/824121596765983121/pdf/South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "global development indicators", "label": "DESCRIPTIVE_DATA", "score": 0.6543789505958557, "start": 777, "end": 806, "probe_score": 0.9799, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Global Climate Risk Index", "label": "NAMED_DATA", "score": 0.7685593962669373, "start": 1663, "end": 1688, "probe_score": 0.9976, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " refugees is for persons with PESEL UKR registered for social security on 30th September 2023. It\nis then compared to the general population by nine main occupational groups from GUS LFS in Q2 2023 and earnings from GUS (2023) “Structure\nof wages and salaries by occupation in October 2022”, and by detailed occupations workers and earnings from GUS (2022) “Structure of wages and\nsalaries by occupations in October 2020”.\n\n\n\n**Note:** Earnings in poviat Lubiński are so high, as it is the site of KGHM, state-owned copper mining corporation.\n\n\n**Source:** Deloitte own elaboration based on ZUS, and Statistics Poland data.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n32\n\n\n\n33", "output": {"entities": {"named_data": ["ZUS", "Statistics Poland data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 16, "chunk": 4, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "ZUS", "label": "NAMED_DATA", "score": 0.6988366842269897, "start": 591, "end": 594, "probe_score": 0.0002, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Statistics Poland data", "label": "NAMED_DATA", "score": 0.7343977093696594, "start": 600, "end": 622, "probe_score": 0.9696, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " approach to its reconstruction and recovery priorities. The\nproposed project will support the medium-term recovery and reconstruction planning of the areas of Beirut affected\nby the blast through technical assistance (LFF funded, bank-executed Advisory Services and Analytics (ASA) to local\nand national government institutions to strengthen their planning, coordination, and citizen outreach capacity, and\nprovide a platform for in-depth consultations with government, civil society, and donors. This will support the\npreparation of plans for scaling up the recovery and reconstruction of housing, public buildings, urban infrastructure,\nand critical municipal services in the blast area, which would be critical for the overall recovery of Beirut. This TA will\nsupport PCH and sectoral stakeholders in the development of plans and options to close the financing gap for the\nrecovery of the housing sector. This technical assistance is critical to ensure that the emergency activities that will be\nimplemented through the proposed project offer the opportunity to the local government to: i) plan medium to long\nterm reconstruction and recovery of Beirut; ii) monitor current rehabilitation activities led by NGOs and international\nactors; and iii) reposition itself as a key actor in urban regeneration and planning vis-à-vis citizens.\n\n**20.** **A Bank-Executed Technical Assistance (TA) will ensure institutional sustainability by supporting the**\n**Governorate on the setting up of a Planning and Coordinating Unit (PCU) and a “One Stop Shop” to coordinate,**\n**communicate, and facilitate financing, for the city’s medium to the long-term recovery strategy.** A PCU will be\nestablished at the governorate of Beirut. The TA will support the PCU to i) manage the coordination of reconstruction\nand recovery efforts in the affected areas, ii) define a vision for the reconstruction and recovery for the city (Port-city\nintegration, housing, urban transport, integrated municipal services, public and green spaces, cultural heritage, etc.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000012", "page": 17, "chunk": 1, "title": "Lebanon - Beirut Housing Rehabilitation and Cultural and Creative Industries Recovery", "pdf_url": "http://documents.worldbank.org/curated/en/270591648016658758/pdf/Lebanon-Beirut-Housing-Rehabilitation-and-Cultural-and-Creative-Industries-Recovery.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " Annex 6). The new latrines will also prevent fecal\ncontamination of groundwater by offering the local communities an alternative to open defecation.\n\nb) **Water, Sanitation and Hygiene (WASH) awareness raising campaigns**\n\n25. This activity will support awareness raising campaigns targeting schools, health centers and public market\nplaces. NGOs will undertake the campaigns before latrine construction so that managers of the facilities and endusers are sensitized about the correct usage of the latrines and water systems and about good hygiene practices\nonce the facilities are in service. The campaigns will be tailored to specific sub-groups.\n\n**Component 2: Improving sustainable access to safe water and sanitation for refugees and host communities in**\n**Hodh Echargui and Hodh El Gharbi** ( **Cost: US$12.7 million equivalent of which 11.2 million IDA, US$1.5 million**\n**counterpart funding** )\n\n**2.1 Improvement of access to safe and reliable water through:**\n\n\na) **Construction of 74 mini-water systems and six regular water systems in Hodh El Gharbi and Hodh Echargui**\n\n26. These activities are similar to those proposed under Component 1.1a) except the geographic scope is\ndifferent. The water systems will be constructed in the two hodhs, which are host community regions. As with\nComponent 1.1a), the new water systems will be equipped to operate on solar energy.\n\nb) **Rehabilitation of the existing 43 piped water systems in Hodh Echargui**\n\n27. The project will rehabilitate rural water systems in Hodh Echargui, a host community, in order to improve\nwater supply to beneficiary residents. Forty-one of these systems are currently operated by ONSER and two by\n\n\n20 The centers include: Monguel and Maghama (Gorgol); Ould", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000106", "page": 18, "chunk": 1, "title": "Mauritania - Water and Sanitation Sectoral Project", "pdf_url": "http://documents1.worldbank.org/curated/en/605151585879430844/pdf/Mauritania-Water-and-Sanitation-Sectoral-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nresources, are among key challenges\nfaced by the majority of the sectors.\n\n\nDespite ongoing assistance programmes\nbeing implemented in urban peri-urban\nand rural areas, the needs of refugees\nliving in these areas increased due\nthe deepening economic situation and\nreduced livelihood opportunities. This\nwas evident in:\n\n\n- an increasing number of refugees in\nthese areas requested relocation to\ncamps, resulting in long waiting lists\nand negative coping mechanisms;\n\n\n- insufficient rehabilitation and provision\nof medical equipment to public health\nfacilities and limited access to mental\n\n\n\nhealth and psychosocial support (PSS)\nservices; and,\n\n\n- shelter needs and care and\nmaintenance of infrastructure being\ninsufficiently addressed.\n\n\nThe massive internal displacement of over\n3.3 million Iraqis has caused a shift in the\nfocus of humanitarian actors and has left\na subsequent gap in funding, resulting in:\n\n\n- insufficient support to create permanent\nand more formal employment\nopportunities: the Livelihoods sector\nreceived the smallest financial\ncontribution (3 per cent of the total\nrequired as of June 2017), <sup>17</sup> although\nsustainable livelihoods is crucial to the\nwell-being and resilience of refugees in\nprotracted stay.\n\n\n- competition for labour and increased\npressure on local food production:\n\n\n\n17 Latest available sector funding breakdowns are as of 30 June 2017.\n\n<mark>42</mark>", "output": {"entities": {"named_data": [], "descriptive_data": ["sector funding breakdowns"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001347", "page": 41, "chunk": 1, "title": "(3RP) Regional Refugee and Resilience Plan 2017 - 2018 in response to the Syria Crisis | 2017 Progress Report", "pdf_url": "https://reliefweb.int/attachments/cfc40205-10a1-3332-8346-eba007ada788/3RP-Progress-Report-17102017-final.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "sector funding breakdowns", "label": "DESCRIPTIVE_DATA", "score": 0.6411240696907043, "start": 1343, "end": 1368, "probe_score": 0.4281, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".\n\n\n     - **MOSA** SDCs are responsible for: (i) receiving household applications and interface\nwith applicant; (ii) data entry into program application; (iii) conducting household\nvisits; (iv) checking possible data errors in application forms against provided\nofficial documents; (v) transmitting households' application data to **MOSA** central\nunit; and (vi) handling appeals and claims received **by** households..\n\n\n**8.** With respect to the institutional setup of the **NPTP,** the progam has been managed **by** the\n**MOSA** and the Presidency of the Council of Ministers (PCM). <sup>6</sup> This was deemed the best\noption at the time of appraisal of the **ESPISP** II project, which supported the creation of the\n**NPTP.** <sup>**3 7**</sup> The present institutional setup will be retained during the implementation of the SPPP,\nthough the **GOL** has started discussing the possibility of consolidating the **NPTP** under **MOSA**\nand institutionalizing it as an independent program with its own budgetary allocations.\n\n\n**36** **A** central management unit at the PCM and a central unit in **MOSA** manage the program. The former is responsible for: (i) comanaging the central **NPTP** database; (ii) validating data and cross-checking with national databases; (iii) processing household\ndata and generating scores and ranks according to the proxy-means testing (PMT) formula; (iv) maintaining the PMT formula;\n(v) analyzing national data and reporting findings to the Social Inter-Ministerial Committee (Social-IMC); (vi", "output": {"entities": {"named_data": [], "descriptive_data": ["national databases"], "vague_data": ["household\ndata"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000109", "page": 51, "chunk": 1, "title": "Lebanon - Social Promotion and Protection Project", "pdf_url": "http://documents1.worldbank.org/curated/en/643811468055144236/pdf/749060PAD0P124010Box374388B00OUO090.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "national databases", "label": "DESCRIPTIVE_DATA", "score": 0.6342385411262512, "start": 1256, "end": 1274, "probe_score": 0.025, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "household\ndata", "label": "VAGUE_DATA", "score": 0.7039326429367065, "start": 1293, "end": 1307, "probe_score": 0.0, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nUganda Digital Acceleration Project – GovNet (P171305)\n\n\nGlobal Findex data of 50 percent of adults owning mobile money accounts in Uganda. <sup>23</sup> The take-up of mobile\nservices has also increased women’s rates of financial inclusion over time.\n\n\n**8.** **The digital divide persists in Uganda and is driven by a range of socio-economic barriers.** To ensure that the\ntransformative potential of digital services reaches all, including the most vulnerable population, there is a need\nto address barriers defined by gender, geography, residency status, disabilities, and income levels. Only 16\npercent of the total number of mobile phone users have smartphones. <sup>24</sup> Geographically, the wide gap between\nthe 19.5 percent Internet penetration rate in urban areas and the mere 7.1 percent in rural areas also raises\nconcerns around the urban-rural divide. <sup>25</sup> A gender gap also persists. Only 53.7 percent of women own phones\ncompared with 74.5 percent of men. In addition, women account for the largest share (66 percent) of people who\ndo not use mobile phones. <sup>26</sup> The gender gap in Internet use is estimated at 25 percent between men and women,\ninfluenced by the lower socioeconomic position and education levels of women. Skills are also an issue as 75\npercent of Ugandans who do not use the Internet report that they lack the skills to do so. <sup>27</sup> Skills gaps are\nparticularly stark between men and women. Even among the employed population, fewer women than men\npossess a formal education: 4.4 percent versus 6.2 percent; and two-thirds of young women in employment lack\na trade, technical skills, or specialization.\n\n\n**9.*", "output": {"entities": {"named_data": ["Findex data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000023", "page": 16, "chunk": 0, "title": "Uganda - Digital Acceleration Project", "pdf_url": "http://documents.worldbank.org/curated/en/473041622944887337/pdf/Uganda-Digital-Acceleration-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Findex data", "label": "NAMED_DATA", "score": 0.7894632816314697, "start": 83, "end": 94, "probe_score": 0.9664, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "output": {"entities": {"named_data": [], "descriptive_data": ["household expenditure survey data", "data from the Household Survey"], "vague_data": ["survey data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:012749", "page": 38, "chunk": 1, "title": "Uganda - Agricultural Extension Project", "pdf_url": "https://documents.worldbank.org/curated/en/420021468309309527/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "household expenditure survey data", "label": "DESCRIPTIVE_DATA", "score": 0.8699104189872742, "start": 565, "end": 598, "probe_score": 0.7323, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "survey data", "label": "VAGUE_DATA", "score": 0.5808603167533875, "start": 870, "end": 881, "probe_score": 0.1461, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "data from the Household Survey", "label": "DESCRIPTIVE_DATA", "score": 0.5346028804779053, "start": 1978, "end": 2008, "probe_score": 0.1121, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " additionally a positive\nimpact on labour productivity that cannot\nbe accounted for using the available data.\nThese effects could stem from the growth\nin specialisation due to additional workers\nwith different skillsets appearing on the\nlabour market, e.g., occupational upgrading\nof native workers.\n\n\n\n**Immigrants could possess complementary skills that**\n**make native workers more productive as they specialise.**\nThese skills do not even need to be advanced to be\ncomplementary. Natives are likely to deal better with\ncommunications-intensive tasks and have better networking, all\nof which may be better paid and not easily transferable between\ncountries. OECD (2016) gives an example of a native carpenter,\nwho employs an immigrant to do his previous manual tasks\nand himself focuses on marketing and business development.\nSuch occupational upgrading has been first shown in a seminal\npaper by Peri and Sparber (2009) in the USA data, but has been\nquickly extended to other countries. From this perspective\nFoged and Peri (2016) look at refugees in Denmark in the 19912008 period. They find that inflow of low-skill refugees caused\nless educated native workers to pursue less manual-intensive\ntasks - improving their wages, employment, and occupational\nmobility. These effects are causal, as the authors exploit the\nrefugee dispersal system, which is orthogonal to economic\nopportunities.\n\n\n**Immigrants could enter childcare, elderly care, and**\n**housekeeping services, allowing highly educated and**\n**productive native women to increase their labour supply.**\nA caveat in the case of refugees from Ukraine is that this could\nmean working below their qualifications or in the informal\nsector, making the overall effect for productivity unclear.\nNevertheless, as availability of care and housework services\nincreases, it becomes easier for women mainly to combine\nfamily and professional lives and increase labour supply.\nSuch effects may be stronger for countries with less accessible\nchildcare. Furtado (2015) reviews this literature, finding evidence\nfrom Australia, Hong", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["USA data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 20, "chunk": 1, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "USA data", "label": "VAGUE_DATA", "score": 0.674831211566925, "start": 931, "end": 939, "probe_score": 0.8086, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "# 2. DISPLACEMENT AND DISASTER RISK\n\n\n### 2.1 APPROACHING DISPLACEMENT FROM THE PERSPECTIVE OF DISASTER RISK\n\nThis paper brings together data from several disparate\nsources in order to better quantify human displacement\nrisk in South Asia. The goal is to look beyond historic\ndisplacement figures and to estimate future displacement risk within each country. As the last of five regional analyses based on a displacement risk methodology\nunder development by IDMC, it:\n\n- advances several considerations for modelling of\ndisplacement risk\n\n- elaborates a new assessment methodology which is\nbeing refined for each of the five regional analyses\n\n- seeks to yield results that are as accurate and certain\nas possible with available data\n\n- brings to light the main sources of uncertainty and\nerror\n\n- informs continuing policy discussions related to\nthe Nansen Initiative consultations on cross-border\ndisplacement in the context of disasters and climate\nchange.\n\nThe findings presented here have benefitted from initial\ntesting of the displacement risk methodology in Central\nAmerica and the South Pacific. In each case, we have\nused the best available spatial and temporal evidence\nto generate displacement risk estimates. In the light\nof future economic, demographic and climate-related\nchanges, these displacement risk estimates provide a\nlook at potential, rather than historic, displacement in\norder to improve understanding of the implications of\ndisaster-induced human displacement trends.\n\n\n\nThe results contained in this paper should be considered\nprovisional. IDMC will continue to improve the probabilistic risk model methodology and incorporate more\nhistorical data as it becomes available. A complete explanation of the methodology used in the analysis has been\nincluded in IDMC’s global assessment of disaster-related\ndisplacement risk. <sup>11</sup> [^11: IDMC, 2015. _Disaster-related displacement risk: Measuring the risk and assessing its drivers._ (http://goo.gl/VQkOwQ)]\n\n### 2.2 STRENGTHS AND WEAKNESSES OF THE ‘RISK’ APPROACH\n\n\nThe objective of this project is to generate probabilistic\nrisk information that quantifies expected displacement\nbased on both annual averages as well as the effect of\ndisaster events of different return periods (", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["historical data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000444", "page": 9, "chunk": 0, "title": "The risk of disaster-induced displacement in South Asia", "pdf_url": "https://reliefweb.int/attachments/3ecb2db8-0bcd-36bf-a3ca-bddb57680d53/201504-ap-south-asia-disaster-induced-displacement-risk-en.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "historical data", "label": "VAGUE_DATA", "score": 0.7494626641273499, "start": 1661, "end": 1676, "probe_score": 0.1307, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "and also allows us to measure the responses of major macroeconomic variables.\n\n\nOur results confirm that the impact of a negative shock to Chinese real GDP on the\n\n\nAsian countries has significantly increased under the recent trade structures of 2005 and\n\n\n2013 compared to the earlier trade structures of 1985 and 1995. This confirms the common\n\n\nunderstanding of Asia’s increased dependency on China. The GIRFs are significantly nega\n\ntive with the exception of the Philippines and New Zealand. All remaining Asian countries\n\n\nare negatively impacted by a real GDP shock to the Chinese economy at the 68% interval.\n\n\nChina’s slowdown also curbs its demand for commodities, and we investigated whether this\n\n\ntranslates into commodity price drops. Our GIRFs show that a negative shock to the real\n\n\nGDP of China not only reduces crude oil prices, as some previous studies have shown, but\n\n\nalso metals and agricultural prices. We also ran our model to test the impact of a poten\n\ntial US real GDP shock, and confirms that although the US has a stronger influence on\n\n\nAsian economies than China, these countries are more exposed to China than ever through\n\n\nincreased economic ties.\n\n\nThe rest of the paper is organized as follows. In Section 2, we analyze the historical\n\n\ntransition of the Chinese trade volume using trade data. In Section 3, we explain the\n\n\nstandard GVAR model following past studies, and introduce several modifications, such as\n\n\nthe time-varying trade weights, increasing the number of commodities, and inclusion of the\n\n\n“shift in intercepts” dummy variables to control the outliers. In Section 4, we estimate the\n\n\nmodel. In Section 5, we calculate the GIRFs, and investigate the effect of a Chinese economic\n\n\nshock on the Asian countries by comparing the shapes of the GIRFs with various settings.\n\n\nSection 6 summarizes our conclusions.\n\n#### **2 The transition of China’s trade share**\n\n\nChina’s membership of the World Trade Organization in 2001 dramatically altered the\n\n\noutlook for global trade", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["trade data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:006492", "page": 6, "chunk": 0, "title": "wps7442", "pdf_url": "https://local/prwp/wps7442.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "trade data", "label": "VAGUE_DATA", "score": 0.6635658144950867, "start": 1320, "end": 1330, "probe_score": 0.9087, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "\nhealth, nutrition, and livelihoods. Access to sufficient fuel for cooking is a major challenge, and the\nconsumption of firewood is a driver of environmental degradation and a major source of protection risk,\nespecially for women and children who are mostly tasked with gathering firewood. Shortage of fuel for\ncooking causes competition for these resources and tensions between refugees and nearby host\ncommunities. Alleviating energy deprivation can provide significant benefits associated with better\nlighting, protection, gender equality, food security, water, sanitation and health, education, livelihoods,\nconnectivity, and environmental protection.\n\n6. The project aims to alleviate energy deprivation of about 400,000 refugees from 20 refugee camps\nand a city and 740,000 people from host communities located within 25 km from refugee camps, including\nboth rural areas and cities. In addition, it will provide electricity access for 150 medical centers and 200\nschools that are located in areas comprising refugee camps and host communities, as well as for 500 PUEs.\nThe eligibility criteria of 25 km for host communities was replicated from the ongoing PARCA that aims to\n(a) improve access of refugees and host communities to basic services, livelihoods, and safety nets in\nseven provinces and (b) strengthen country systems to support refugees. Synergies will be exploited\nbetween the project and PARCA. The activities of the project will align with preexisting and ongoing\ninitiatives from the UNHCR and implementing partners toward better energy access for refugees. In\nparticular, targeting of refugees will be coordinated with them through already available data, and\ncapacity building of refugees in implementation and maintenance could be provided by the UNHCR. The\nproject will adapt as needed to changing circumstances during implementation with respect to focus\nsites/areas, including the ability to serve new refugee camps and nearby host communities.\n\n\nPage 68 of 87", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["already available data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000051", "page": 73, "chunk": 1, "title": "Chad - Energy Access Scale Up Project", "pdf_url": "http://documents.worldbank.org/curated/en/860701648216750651/pdf/Chad-Energy-Access-Scale-Up-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "already available data", "label": "VAGUE_DATA", "score": 0.7487351298332214, "start": 1655, "end": 1677, "probe_score": 0.8822, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\nand Yei. <sup>16</sup> [^16: International Organization for Migration (IOM), Displacement Tracking Matrix (DTM), Round 6 (op cit.)] A recent study estimates that 80,000 people died between December 2013 and April 2018. <sup>17</sup> [^17: Checchi, F., et. al. 2018. _Estimates of Crisis-attributable Mortality in South Sudan, December 2013–April 2018: A Statistical Analysis._ London\nSchool of Hygiene and Tropical Medicine.]\nAbout <mark>6.4 million people (54</mark> percent <mark>of the population)</mark> <mark>are in ‘Crisis’ (IPC</mark> <sup>18</sup> [^18: IPC = Integrated Food Security Phase Classification.] <mark>Phase 3) or worse acute food</mark>\n<mark>insecurity.</mark> <sup>19</sup> [^19: IPC. 2019. _<mark>South Sudan: Acute Food Insecurity and Acute Malnutrition Situation (August 2019–April 2020).</mark>_\n[20 Johns Hopkins University and Medicine Coronavirus Resource Center: https://coronavirus.jhu.edu/map.html](https://coronavirus.jhu.edu/map.html) _._] These populations are among the least resilient and are the most vulnerable to climate\nshocks, compounding the twin shocks of conflict and natural disasters.\n\n\n6. **The risk of spread of Coronavirus Disease (COVID-19) is high.** The pandemic could push the\npeople, especially the vulnerable poor and the displaced, deeper into destitution and the country faces\nthe risk of further destabilization. [As of July 14, 2020, South Sudan recorded 2,148c4295ef41ba34682ab0b08d826b1d07d", "output": {"entities": {"named_data": ["Displacement Tracking Matrix"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000049", "page": 16, "chunk": 0, "title": "South Sudan - Enhancing Community Resilience and Local Governance Project", "pdf_url": "http://documents.worldbank.org/curated/en/824121596765983121/pdf/South-Sudan-Enhancing-Community-Resilience-and-Local-Governance-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Displacement Tracking Matrix", "label": "NAMED_DATA", "score": 0.8637825846672058, "start": 180, "end": 208, "probe_score": 0.9453, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " levels undermine the transformative potential of digital services while\nexcluding the most vulnerable from the associated benefits. Only 16 percent of the total number of mobile\nphone users have smartphones. <sup>28</sup> Geographically, the wide gap between the 19.5 percent Internet\n\n\n22 Uganda Economic Update, 15th Edition Digital Solutions in a Time of Crisis July 2020\n23 National Information Technology Survey 2017/18 Report. NITA Uganda, March 2018\n24 National Information Technology Survey 2017/18 Report. NITA Uganda, March 2018\n25 Women’s Economic Empowerment in Uganda: Inequalities and Implications. Policy Brief No. 110, November 2019. Kampala:\nEconomic Policy Research Centre. Available at: https://eprcug.org/all-publications/614-women-s-economic-empowerment-inuganda-inequalities-and-implications\n26 National Information Technology Survey 2017/18 Report. NITA Uganda, March 2018\n27 Global Findex Database. World Bank Group, 2017. https://globalfindex.worldbank.org/sites/globalfindex/files/201804/2017%20Findex%20full%20report_0.pdf\n28 National Information Technology Survey 2017/18 Report. NITA Uganda, March 2018\n\n\nJan 15, 2021 Page 6 of 26", "output": {"entities": {"named_data": ["Global Findex Database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000033", "page": 5, "chunk": 2, "title": "Project Information Document - Uganda Digital Acceleration Program - P171305", "pdf_url": "http://documents.worldbank.org/curated/en/630051615474731857/pdf/Project-Information-Document-Uganda-Digital-Acceleration-Program-P171305.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Global Findex Database", "label": "NAMED_DATA", "score": 0.7362959384918213, "start": 900, "end": 922, "probe_score": 0.9941, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ".\nTo maximise the positive impact\nof refugees on economy, policies\nhelping their integration into the\nlabour market that both allow\ntheir maximal employment as\nwell minimise market mismatch\nbetween demand for specific\nskills and their abilities are\ncrucial. The second part of this\nrecommendation, achieved\neither through improvements\nin utilisation of skills of refugees\nor trainings giving them abilities\ndemanded by the labour market,\nis integral as it should lower\ncosts for the local labour force.\n\n\n\n45  Based on number of economically active people in III quarter of 2023 according to labour market survey.\n46  E.g. vice-president of Polish Development Found Bartosz Marczuk estimated it at around 16 billion PLN, but this estimation also included spending of NGOs\nwhich was combined with spendings of local governments Polska pomoc dla Ukrainy 2022 - ile kosztowała? - Infor.pl.\n47  Excluding spending of private households estimated as further 10 billion PLN.\n48  Model treats general government sector as a whole, as such cost and income internal structure may differ creating institutions with financial loses while\nother may have disproportionate increase of income.", "output": {"entities": {"named_data": [], "descriptive_data": ["labour market survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 18, "chunk": 2, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "labour market survey", "label": "DESCRIPTIVE_DATA", "score": 0.8775113224983215, "start": 592, "end": 612, "probe_score": 0.7997, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ").|The number of women who have access to impact-based flood early warning services.<br>This figure will be estimated by a user survey conducted at least three times during the<br>life of the project (at the beginning, mid-term and towards the end of the project).|\n\n\n33\n\n\nOfficial Use Only", "output": {"entities": {"named_data": [], "descriptive_data": ["user survey"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:005282", "page": 32, "chunk": 4, "title": "Ethiopia - Flood Management Project (EFMP) : Implementation Support Mission - September 29 to October 7, 2025", "pdf_url": "https://documents.worldbank.org/curated/en/099112625112524670/pdf/P176327-f2b0081b-4e37-482f-8a68-6a8bac98eae5.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "user survey", "label": "DESCRIPTIVE_DATA", "score": 0.8564802408218384, "start": 123, "end": 134, "probe_score": 0.2406, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n© UNHCR / Anna Liminowicz\n# **3.** Economic impact modelling\n\n\n\nSimple back-of-the-envelope calculations\ngive the intuition behind how additional\nworkers help to grow the economy.\nThe simplest estimate would be to assume\nthat an increase of employment by 1.4-2.2%\nwill grow the Gross Domestic Product by\nan equal percentage. In such a case, we\nwould need to assume that labour is the\nonly production factor, and thus all of GDP\ncan be equally divided between workers.\nHowever, this is not the case, as GDP is not\njust a function of labour, but also of capital\nthat workers have at their disposal – all the\nmachines, computer programs, offices, and\nthe like. As displacement is unexpected and\nrefugee status (both legal and intent to stay\nlong term) at first is uncertain, companies\ntake time to increase their stocks of capital\nto the new workers. A more elaborate\nestimate would account for the part of GDP\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\nthat is produced by labour alone. This can\nbe estimated by assuming that it is equal\nto the labour compensation share of GDP\n(GDP can be divided into compensation of\nlabour and capital), which in 2022 and 2023\nstood in Poland at 48% according to the\nEuropean Commission’s AMECO database.\nAccounting for that, gives a lower estimate\nof 0.7-1.0% GDP. Such calculations are\nvery abstract, and do not account for other\nphenomena developing simultaneously\nin the economy, like the various effects of\nthe war and energy shock. For this reason,\nwe turn next to formal general equilibrium\nmodelling, where equations of the model\nstate explicitly every assumption about\nthe workings of the economy and allow for\na credible estimation of counter-factual\nscenarios.\n\n\n\nRefugees’ impact on the economy manifests\nin a multi-layered fashion. An influx of\nrefugees means", "output": {"entities": {"named_data": ["AMECO database"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 15, "chunk": 0, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "AMECO database", "label": "NAMED_DATA", "score": 0.9460641741752625, "start": 1333, "end": 1347, "probe_score": 0.9688, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\n© UNHCR / Anna Liminowicz\n\n\nDispersing refugees to weaker labour\nmarkets can also have negative social\noutcomes. Albarosa and Elsner (2022) report\nmore anti-immigrant incidents during the\nEuropean refugee crisis (2015/2016) in areas\nof Germany with high unemployment rates\nand shares of right-wing voters. Damm and\nDustmann (2014) show that immigrant men\ndispersed to areas of Denmark with more\nconvicted criminals, experience higher future\ncrime conviction probabilities, but not overall\nneighbourhood crime rate.\n\n\nThe estimated employment rate of refugees\nfrom Ukraine in Poland is above 60% and\nwas among the highest in the OECD <sup>27</sup> [^27: Deloitte elaboration based on the aggregation in OECD International Migration Outlook 2023] .\nAlthough there is uncertainty around\nemployment rate in different countries due\nto uncertainty regarding refugee numbers\n\nwhile MSNA Poland 2023 gives a slightly\nlower figure of 61%. In comparison, the\nemployment rate equalled 61% in the United\n\n\n\nBy refraining from any refugee dispersal\npolicies, Poland and other EU Member\nStates may have improved labour market\ninclusion. In many European countries\nrefugees are geographically dispersed after\narrival to spread the cost of hosting them,\nease the stress on the housing market\nand public services, and to avoid creating\nethnic enclaves. The effects, however, can\nbe detrimental to labour market inclusion\nand may be contrary to other aims of the\npolicy. Dispersal pushes at least some of\nthe refugees into regions with weak labour\nmarkets and few co-nationals already\nsettled, who otherwise could transmit\nimportant information about employment\nopportunities. Fasani, Frattini, and Minale\n(2022) conducted the first cross-country\nstudy of refugee dispersal policies.\nTheir LFS sample covers refugees who\nexperienced dispersal policies in Finland,\nGermany, Ireland, Netherlands, Norway,\nSweden, Switzerland and the UK (no data\nfor Denmark). They find that non-EU15\nrefugees aged 25-64 who arrived when a\ndispersal policy was in place experience\n4.5", "output": {"entities": {"named_data": ["OECD International Migration Outlook 2023", "MSNA Poland 2023"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 12, "chunk": 0, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "OECD International Migration Outlook 2023", "label": "NAMED_DATA", "score": 0.7534892559051514, "start": 778, "end": 819, "probe_score": 0.9998, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "MSNA Poland 2023", "label": "NAMED_DATA", "score": 0.6530247330665588, "start": 951, "end": 967, "probe_score": 0.9984, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Annex 1\nPage 3 **of** 3\n\n\n**Key Performance**\n**Hierarchy of Objectives** **Indicators** **Monitoring &** **Critical Assumptions**\n**Evaluation**\n**Project Components / Sub-** **Inputs: (budget for each** **Project reports:** **(from Components to**\n**components:** **component)** **Outputs)**\n\n\nImprove Access: provision of US$5.8 million MOE monitoring Capacity within the\nclassrooms. Number of schools reports construction sector to handle\nconstructed per year; the volume of school\nimproved design and construction.\nefficiency.\nCreate Conditions for Quality US$1.1 million School surveys; student Good textbook distribution;\nImprovement: access to Number of textbooks per learning achievement management training\neducational materials; student; autonomous school reports (MOE effectiveness; Government\nimproved school management; salaries paid on monitoring reports). commitment to paying\nmanagement; teacher a timely basis teacher salaries.\nmotivation.\n\n\nImprove Government's US$4.1 million Project monitoring Purpose and integrity\nCapacity to Manage Sector: Project effectively reports; study reports. maintained within project\ncapacity building within the implemented and management; stakeholder\nMOE and its related services; management improved; participation in pilot studies.\npilot studies. reports with implementable\nresults.\n\n\n**Annexe 1 Attachment: Program and Project Monitorin** **Tar** **ets**\n**_Year_** _2001-02 2002-03_ **_2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10_**\nPrimary Enrollment Boys 19,125 21,506 24,300 26,627 29,867 31,696 34,457 37,217 40,129\nPrimary Enrollment Girls 14,875 17,994 20,", "output": {"entities": {"named_data": [], "descriptive_data": ["School surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000049", "page": 31, "chunk": 0, "title": "Croatia - Reconstruction Project for Eastern Slavonia, Baranja and Western Srijem", "pdf_url": "http://documents1.worldbank.org/curated/en/347691468746725804/pdf/multi-page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "School surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8726161122322083, "start": 577, "end": 591, "probe_score": 0.0853, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**8.3. Suggested Further Action**\nMore detailed mapping should be done for IDP camps located near parks as a basis for\nassessing the impact of these camps on park resources. See Section 12, below.\n\n### **9. Humanitarian Response Environmental Impact Assessments**\n\n**9.1. Rapid Assessment Process and Report**\nThe DRC Shelter Cluster conducted a strategic/programmatic-level environment impact\nassessment using the Rapid Environment Impact Assessment in Disaster (REA) methodology.\nThe process involved an online assessment of critical environmental issues followed by a\nranking of these issues, a review of results and development of an Environmental Management\n& Monitoring Plans, as described in Section 10, below.\n\nThe key issues noted in the assessment are summarized in the table below. Two questions on\ngender were included in the survey:\n\n  - Are activities of men, women, girls or boys linked to the environment potentially\nsubjecting them to physical harm, and\n\n  - Who might be affected?\nOf eleven respondents, one indicated that harm could occur “In some cases” while ten\nindicated that harm could occur “In most cases”.\n\nIn terms of who could be most at risk of harm, the nine respondents indicated the following:\n\n\n\n\n  - Women: 11\n\n  - Girls: 11\n\n\nLinks to the report can be found in Annex 23.5\n\n\n\n\n- Boys: 9\n\n- Men: 9\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|DRC Online REA Issues Ranking|Col2|Col3|\n|---|---|---|\n|**Issue**|**Response**|**Rank (12**<br>**is**<br>**maximum)**|\n|Expectations of the affected<br>populations in terms of external<br>assistance?|High the affected population expect<br>most of their needs to be met from<br>external assistance.|10|\n|Availability of natural resources to<br", "output": {"entities": {"named_data": ["DRC Online REA Issues Ranking"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:001100", "page": 23, "chunk": 0, "title": "Democratic Republic of Congo: Environmental Country Profile for Shelter and Settlements - 1st edition, September 2023", "pdf_url": "https://reliefweb.int/attachments/a65403d8-05db-412f-9a94-867473b3d3bb/DRC%20Environmental%20Shelter%20Country%20Profile.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "DRC Online REA Issues Ranking", "label": "NAMED_DATA", "score": 0.6879273653030396, "start": 1366, "end": 1395, "probe_score": 0.5111, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "000|\n|**Support to schools for pandemic**<br>**recovery**|Distribution of materials|1|1,000,000|1,000,000|\n|**Community support for school**<br>**cleanliness.**|Development of guidelines|140,000|1|140,000|\n|**Community support for school**<br>**cleanliness.**|Dissemination of guidelines|8|100,000|800,000|\n\n\n**Component 3: System-level resilience and project coordination**\n\n\n|Emergency helpdesk.|Staffing and telecoms, per month|10,000|10|100,000|\n|---|---|---|---|---|\n|**Support to regional and local**<br>**supervision capacity.**||200,000|1|200,000|\n|**Learning from Evidence**|Bimonthly surveys and end-of-<br>project evaluation|100,000|1|100,000|\n|**Project coordination**||100,000|1|100,000|\n\n\n\n\n\n\n\n\n\nPage 40 of 46", "output": {"entities": {"named_data": [], "descriptive_data": ["Bimonthly surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:014783", "page": 44, "chunk": 1, "title": "Ethiopia - Covid-19 Education Response Project", "pdf_url": "https://documents.worldbank.org/curated/en/559941617295228500/pdf/Ethiopia-Covid-19-Education-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Bimonthly surveys", "label": "DESCRIPTIVE_DATA", "score": 0.6009364128112793, "start": 584, "end": 601, "probe_score": 0.006, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nIntegrated Community Resilience Project (P506969) PROJECT APPRAISAL DOCUMENT\n\n|Frequency|Every six months|\n|---|---|\n|Data source|** MASS regular monitoring reports submittted to the bank per semester**|\n|Methodology for Data<br>Collection|** The MASS will develop a work plan to operationalize the project M&E. The work plan will include collection of data at**<br>**the point of implementation and its agregation to provide updates on the indicator. Data collected will be**<br>**disagregated by regions – including Djibouti ville.**|\n|Responsibility for Data<br>Collection|** MASS in collaboration with the regional administrations**|\n|**Beneficiaries of cash-based interventions - Female (Number of people)CRI**|**Beneficiaries of cash-based interventions - Female (Number of people)CRI**|\n|Description|Indicator measures female beneficiaries of the C4N intervention under the social safety net system supported by the<br>project.|\n|Frequency|** Six months**|\n|Data source|** MASS regular monitoring reports**|\n|Methodology for Data<br>Collection|** The MASS will develop a work plan to operationalize the project M&E. The work plan will include collection of data at**<br>**the point of implementation and its agregation to provide updates on the indicator. Data collected will be**<br>**disagregated by regions – including Djibouti ville.**|\n|Responsibility for Data<br>Collection|** MASS in collaboration with the regional administrations**|\n|**Beneficiaries of cash-", "output": {"entities": {"named_data": ["MASS regular monitoring reports"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "refugee_pads", "corpus_id": "refugee_pads:000180", "page": 42, "chunk": 0, "title": "Djibouti - Integrated Community Resilience Project", "pdf_url": "https://documents1.worldbank.org/curated/en/099022525185016955/pdf/BOSIB-87c444de-4797-4bf9-b654-4932a7fb0112.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "MASS regular monitoring reports", "label": "NAMED_DATA", "score": 0.6495404839515686, "start": 152, "end": 183, "probe_score": 0.1353, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nThe influx of refugees into Poland after the\nRussian invasion of Ukraine was large, with\nnearly 16 million border crossings <sup>18</sup> [^18: UNHCR data, <u>[https://data2.unhcr.org/en/situations/ukraine](https://data2.unhcr.org/en/situations/ukraine)</u>] from\nUkraine until the end of September 2023 and\ncumulatively 1.7 million PESEL registrations.\nIt must be noted that such a rapid population\nmovement of that scale was not seen in\nEurope since World War II. Not everyone\n\n\n\nstayed in Poland, however. A large number of\nthese refugees later returned to Ukraine or\nmoved to other European countries.\nBy October 2023, the remaining active PESEL\nUKR numbers stood at less than 1 million,\nwhile the border movement balance between\nPoland and Ukraine at 2.5 million.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 4.** Age and gender structure of refugees based with active PESEL numbers in\nOctober 2023\n\n\n|Col1|Col2|Col3|Col4|Col5|Col6|Col7|Col8|Col9|The s<br>imple<br>of for|udden<br>menta<br>eigner|drop in<br>tion of t<br>status a|registe<br>he 30-d<br>fter a r|red num<br>ay dead<br>egistere|bers is<br>line for<br>d depa|due to<br>revoca<br>rture fro|the<br>tion<br>m|Col18|\n|---|---|---|---|---|---|---|---|---|---|---|", "output": {"entities": {"named_data": ["UNHCR data"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jad_paddy_docs", "corpus_id": "jad_paddy_docs:000007", "page": 7, "chunk": 0, "title": "Poland Analysis of the impact of refugees from Ukraine on the economy of Poland – March 2024", "pdf_url": "https://local/jad_paddy_docs/poland analysis of the impact of refugees from ukraine on the economy of poland – march 2024.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "UNHCR data", "label": "NAMED_DATA", "score": 0.8377419114112854, "start": 220, "end": 230, "probe_score": 0.9964, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["data on social development issues"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:008156", "page": 24, "chunk": 0, "title": "Ethiopia - Seed Systems Development Project", "pdf_url": "https://documents.worldbank.org/curated/en/116821468744299057/pdf/multi0page.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data on social development issues", "label": "VAGUE_DATA", "score": 0.581004798412323, "start": 1670, "end": 1703, "probe_score": 0.333, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " do not require cutting edge\nR&D to improve their competitive standing. For these firms, assistance in honing\nskills related to technology acquisition and use may be much more relevant than\nadditional public R&D funding.\n\nPut differently, the current R&D system is simply not a viable or effective instrument for\ncreating a modern, innovative economy. For example:\n\n\n  - The Latvian innovation system shrank dramatically since the early days of\ntransition. With 17,000 researchers, Latvia was a major center of R&D in the\nformer Soviet Union. Most of these scientists and engineers were engaged in\ndefense related activities. But as defense orders dried up, the number of research\npersonnel declined dramatically. Unfortunately, shrinkage is not the same as\nstructural reform.\n\n**Table 7 Changes in R&D Personnel in Latvia, 1989-1999**\n\n|Employed in Science|1990|1993|1996|1999|2000|\n|---|---|---|---|---|---|\n|Total number of employed persons<br>Total number of researchers<br>Researchers with degrees|30,700<br>17,700<br>3,710|8,536<br>3,999<br>1,977|4,744<br>2,839<br>1,491|4,301<br>2,626<br>1,492|4,280<br>2,590<br>1,495|\n\n\n\n_Source:_ European Trend Chart on Innovation, 2001\n\n\n  - Latvia’s remaining innovation system is small, with only about 4000 personnel.\nTherefore, to generate a critical mass of R&D with this small base, Latvia will\nneed to focus its R&D efforts in a few key areas.\n\n  - R&D personnel are ageing and not being replaced by new, younger cadres. This\nis true both", "output": {"entities": {"named_data": ["European Trend Chart on Innovation"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "prwp", "origin": "general_prwp", "corpus_id": "prwp:002704", "page": 42, "chunk": 1, "title": "wps3457", "pdf_url": "https://local/prwp/wps3457.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "European Trend Chart on Innovation", "label": "NAMED_DATA", "score": 0.8439323306083679, "start": 1139, "end": 1173, "probe_score": 0.482, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "|KE-MOH-07-2023/2024-GO-<br>RFQ / Procurement of Access<br>ories for PCR Machine in Kak<br>amega Referral Hospital|IDA / 65980|Medical supplies and equip<br>ment|Post|Request for Quot<br>ations|Limited|Single Stage - One<br>Envelope|Col8|39,710.00|0.00|Completed|Col12|Col13|Col14|Col15|Col16|Col17|2023-11-05|2023-11-20|Col20|Col21|Col22|Col23|Col24|Col25|2023-12-08|2024-01-16|2024-03-31|2024-06-28|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n|KE-MOH-08-2023/2024-GO-<br>RFQ / Procurement of One La<br>boratory Freeze and one refr<br>igerator for Lodwar County R<br>eferral Hospital|IDA / 65980|Medical supplies and equip<br>ment|Post|Request for Quot<br>ations|Limited|Single Stage - One<br>Envelope||60,000.00|0.00|Complete", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:000494", "page": 12, "chunk": 0, "title": "Kenya - EASTERN AND SOUTHERN AFRICA- P173820- KENYA COVID-19 HEALTH EMERGENCY RESPONSE PROJECT - Procurement Plan", "pdf_url": "https://documents.worldbank.org/curated/en/099020325053517288/pdf/P173820-b5fa0dad-47c4-40b1-b5e5-a786f5da3e7f.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 0.0, "split": "holdout", "spans": [], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " is better<br>than making a wild guesstimate. Through the FAFSA4caster tool,<br>an anticipating high school student or parent can obtain better<br>estimates of the COA and EFC.<br>**How does the FAFSA4caster Work?**<br>The FAFSA4caster displays a worksheet that must be flled with<br>the Cost of Attendance (COA), such as tuition fees, other<br>educational expenses and living costs of the student’s chosen<br>school. To get the information you need, go to the College<br>Scorecard page of the U.S. DepEd.<br>A household’s potential fnancial contribution, on the other hand,<br>can be estimated by providing answers to the FAFSA4caster<br>questionnaire that determines fnancial capability of a potential<br>college student. Here, it is important that all questions will be given<br>answers even if based on near-enough guesses or estimates. Be<br>ready with some personal records as some questions need<br>answers based on personal documents such as bank statements<br>or federal tax returns.<br>After which, the tool will display several sources of college funds,<br>whilst indicating eligibility for **federal fnancial aid** like Pell Grant,<br>Direct Subsidized or Direct Unsubsidized Loan, or Federal Work-<br>Study program. If there are any state aid or college fnancial<br>assistance that a student or parent considers as potential source of<br>college funding, fll in the appropriate worksheet felds with the<br>amounts.<br>Hitting the “Calculate” button will summarize the total anticipated<br>College Attendance Cost, and the total", "output": {"entities": {"named_data": [], "descriptive_data": ["federal tax returns"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000022", "page": 0, "chunk": 56, "title": "RD Congo : Camps de Kilimani, Kalinga, Bihito et Luchebere (Groupement de Biiri, Collectivité de Osso, Territorire de Masisi)", "pdf_url": "http://www.rdc-humanitaire.net/IMG/pdf/Data_Masisi_Camps_070609_v1.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "federal tax returns", "label": "DESCRIPTIVE_DATA", "score": 0.5488535761833191, "start": 972, "end": 991, "probe_score": 0.6577, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**ALTERNATIVES TO THE APPROACH TAKEN IN REGARD TO THE**\n**SHREDDING TENDER**\n\n\nThe water hyacinth is a reflection of the wider problem of eutrophication of Lake Victoria.\nWater hyacinth can be found in most African Great Lakes. For example, one can see individual\nhyacinth plants in Lake Malawi, and it is likely that the hyacinth has been present in Lake\nMalawi at least as long as it has in Lake Victoria. Yet there are no mats of hyacinth in Lake\nMalawi, and it is not a major problem there. The difference is in the quality of lake water. Lake\nVictoria is eutrophic and Lake Malawi is oligotrophic. If the water hyacinth were not present in\nLake Victoria, then the nutrient bound in the hyacinth mats would, in all likelihood be tied up in\nphytoplankton or other plants living in the Lake. **_<u>The hyacinth do not ADD nutrients as implied</u>_**\n**_<u>in the complaints, they only make use of the nutrients already in the water. The sources of the</u>_**\n**_<u>nutrients in the Lake are surface runoff from the catchment and atmospheric deposition.</u>_**\n**_<u>Control of the eutrophication process has little or nothing to do with water hyacinths, which</u>_**\n**_<u>are really only a symptom of the “illness” (i.e. nutrient enrichment of the Lake) rather than</u>_**\n**_<u>the “illness” itself.</u>_** .\n\n\nGiven that it would be impossible to do a thorough EA in anything less than 3-5 years or\nmore (the time it would take to collect the minimum amount of baseline data, assuming that the\nLVEMP suffers from no", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["baseline data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:020447", "page": 33, "chunk": 0, "title": "Kenya - Lake Victoria Environmental Management Project : Inspection Panel Report and Recommendation : Kenya - Lake Victoria Environmental Management Project : Inpection Panel Report and Recommendation", "pdf_url": "https://documents.worldbank.org/curated/en/941631468774530549/pdf/21933.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "baseline data", "label": "VAGUE_DATA", "score": 0.7969512343406677, "start": 1466, "end": 1479, "probe_score": 0.2009, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": ". However, this report – like the previous reports published within the Displaced and\nDisconnected workstream – focuses on proof of identity barriers. To that end, particular focus is placed on\nthe legal and regulatory frameworks governing SIM registration and Know Your Customer (KYC)/Customer\nDue Diligence (CDD) requirements for financial institutions and mobile money.\n\n\nRefugees, asylum-seekers, and stateless persons, in particular, face challenges meeting proof of identity\nrequirements required for inter alia registering a SIM card, opening a bank account or obtaining a loan\nunder KYC/CDD regulatory frameworks that do not include the ID documents issued to these populations\namong the forms of identification that satisfy KYC/CDD procedures. <sup>11</sup> Meanwhile, use of only informal\nfinancial instruments limits vulnerable populations – including refugees and other FDPs – “in their ability\nto save, repay debts, and manage risk responsibly.” <sup>12</sup>\n\n\nThe report concludes with recommendations for government actors and humanitarian/development\norganizations intended to guide efforts toward more inclusive regulatory environments that grant\nrefugees, asylum-seekers, and other FDPs access to digital and financial services through open-loop\nsystems.\n\n\n## **2. Research Methodology** **and Limitations**\n\nResearch for this report was conducted between October 2021 and January 2022. It consisted of a\nliterature review on digital and financial inclusion of displaced persons in Burundi, Ethiopia, Kenya,\nRwanda, Somalia, South Sudan, Sudan, Tanzania, and Uganda, and a comprehensive desk review and\nlegal analysis of the relevant laws and regulations governing the telecommunications and financial sectors\nin Somalia, Sudan, and South Sudan.\n\n\nIt also included qualitative data collection in the form of key informant interviews (KIIs) conducted remotely\nwith stakeholders in Somalia, Sudan, and South Sudan, and consultations with UNHCR staff in all nine\nfocus countries. The primary data collected does not serve as a representative set of data", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["primary data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000137", "page": 5, "chunk": 1, "title": "Displaced and Disconnected: East and Horn of Africa and Great Lakes Region (July 2022)", "pdf_url": "https://reliefweb.int/attachments/09a75838-e186-4ff7-8fb4-300bda077a55/Displaced%20and%20Disconnected%20-%20East%20and%20Horn%20of%20Africa%20and%20Great%20Lakes%20Region.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "primary data", "label": "VAGUE_DATA", "score": 0.5802139639854431, "start": 2000, "end": 2012, "probe_score": 0.6245, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "** All three will benefit from the increased access to markets and an improved economic\nenabling environment. The host community members and refugees living outside of settlements will benefit\nfrom the increased access to social services along the KYM road corridor. Refugees in the camps – who\n\n\n48 World Bank 2019, Informing the Refugee Policy Response in Uganda, Results from the Uganda Refugee and Host Communities\n2018 Household Survey.\n[49 www.koboko.go.ug](http://www.koboko.go.ug/) _,_ [www.yumbe.go.ug](http://www.yumbe.go.ug/) _,_ [www.moyo.go.ug, Koboko, Yumbe and Moyo are prime investment sites based on their](http://www.moyo.go.ug/)\nstrategic location within a large market of the population in South Sudan, North and Eastern DRC and Uganda of approximately 71\nmillion people.\n50 Koboko District Investment Profile – Uganda Investment Authority.\n51 Yumbe District Investment Profile – Uganda Investment Authority.\n52 Moyo District Investment Profile – Uganda Investment Authority.\n\n\nPage 24 of 80", "output": {"entities": {"named_data": ["Uganda Refugee and Host Communities\n2018 Household Survey"], "descriptive_data": [], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 28, "chunk": 2, "title": "Uganda - Roads and Bridges in the Refugee Hosting Districts/Koboko-Yumbe-Moyo Road Corridor Project", "pdf_url": "http://documents.worldbank.org/curated/en/834931600048847296/pdf/Uganda-Roads-and-Bridges-in-the-Refugee-Hosting-Districts-Koboko-Yumbe-Moyo-Road-Corridor-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Uganda Refugee and Host Communities\n2018 Household Survey", "label": "NAMED_DATA", "score": 0.9001392126083374, "start": 383, "end": 440, "probe_score": 0.9989, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": " for trade, thereby making the cost of travel cheaper.\n\n94. The cost-benefit analysis indicates that the Economic Internal Rate of Return (EIRR) for the upgrading option\nof Asphalt Concrete pavement (with 50 mm Asphalt Concrete, 200 mm of Aggregate Base Course, and 250\nmm of Granular Subbase) is 19.7 percent when a discount rate of 12 percent is used. A sensitivity analysis\nhas been carried out by increasing or decreasing the critical factors. For the scenario with a 20 percent\nincrease in construction costs, the EIRR is 16.3 percent. For the scenario with a 20 percent decrease in traffic\nvolume, the EIRR is 14 percent. However, if both scenarios are combined, the EIRR is 9.9 percent.\n\n\n95. Reduced travel time and reduced congestion is expected to lower carbon emissions. Based on current and\nfuture traffic forecasts, upgrading of the KYM road corridor is expected to reduce GHG emissions by 42,884\ntons CO2, for the 30 years of operation.\n\n\n**B. Fiduciary**\n\n\n**(i)  Financial Management**\n\n\n96. The project’s financial and other resources will be managed through the existing financial management\narrangements in UNRA as established under the Directorate of Corporate Services in the Finance/Accounts\ndepartment regarding record keeping, accounts, reporting and disbursements. The project planning and\nbudgeting process is mainstreamed into the UNRA procedures. The UNRA Board of Directors has the\nresponsibility of approval of policy, work plans and budget of the entity operations while Bank project\nbudgets are approved in liaison with the World Bank. UNRA will dedicate a project accountant to oversee\nday-to-day financial transactions and ensure proper reporting and controls are in place for the project using\nPastel Accounting System while the GoU IFMIS is used for counterpart funding. The Executive Director of\nUNRA will be the Accounting Officer assuming the overall responsibility for accounting for the project funds.\nDuring the assessment, some risks have", "output": {"entities": {"named_data": ["GoU IFMIS"], "descriptive_data": ["current and\nfuture traffic forecasts"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000050", "page": 41, "chunk": 1, "title": "Uganda - Roads and Bridges in the Refugee Hosting Districts/Koboko-Yumbe-Moyo Road Corridor Project", "pdf_url": "http://documents.worldbank.org/curated/en/834931600048847296/pdf/Uganda-Roads-and-Bridges-in-the-Refugee-Hosting-Districts-Koboko-Yumbe-Moyo-Road-Corridor-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "current and\nfuture traffic forecasts", "label": "DESCRIPTIVE_DATA", "score": 0.5127171874046326, "start": 791, "end": 827, "probe_score": 0.0016, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "GoU IFMIS", "label": "NAMED_DATA", "score": 0.5424190163612366, "start": 1764, "end": 1773, "probe_score": 0.0, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "**The World Bank**\nLebanon: Wheat supply emergency response project (P178866)\n\n\n5. **Monetary and financial turmoil, along with surging inflation, continue to drive crisis conditions.** The\nexchange rate further deteriorated in 2021, with the US dollar banknote rate depreciating by 211 percent year on\nyear (yoy) over the first 11 months of 2021, repeatedly breaching the LBP 22,000/US$ threshold. This situation\noccurred within a multiple-exchange-rate system that also includes the official rate of LBP 1,507.5/US$, and the\nCentral Bank of Lebanon ( _Banque du Liban_, BdL) administered lower rates. Overall, the World Bank Average\nExchange Rate depreciated by 219 percent yoy over 11 months of 2021. Exchange rate pass-through effects have\nimplied surging inflation, which is estimated to average 150 percent in 2021— the third highest globally after\nVenezuela and Sudan (Lebanon Economic Monitor [LEM], Fall 2021). After falling to 101 percent yoy by June 2021,\ninflation rose again to 174 percent yoy in October 2021. The surge since June 2021 is linked to the steady removal\nof the foreign exchange subsidy on imported goods and inflation recorded a further spike at 240 percent yoy in\nJanuary 2022.\n\n6. **While the average annual inflation rose to 85 percent in 2020, the average food inflation alone grew by**\n**a record 250 percent over 2019.** Between January 2021 and January 2022, the average yoy inflation rate reached\n157 percent, with a corresponding food inflation rate of 328 percent. Since the removal of foreign exchange\nsubsidies, yoy food inflation has increased sharply, reaching 483 percent in January 2022. This situation has dire\nconsequences for the poor because food consumption forms a larger proportion of household expenses in poorer\nhouseholds. Phone surveys in May and July 2021 found that 46 percent of households reported challenges in\naccessing food and", "output": {"entities": {"named_data": ["Lebanon Economic Monitor"], "descriptive_data": ["Phone surveys"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "jdc_operational", "corpus_id": "jdc_operational:000019", "page": 12, "chunk": 0, "title": "Lebanon - Wheat Supply Emergency Response Project", "pdf_url": "http://documents.worldbank.org/curated/en/408131653327258940/pdf/Lebanon-Wheat-Supply-Emergency-Response-Project.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "Lebanon Economic Monitor", "label": "NAMED_DATA", "score": 0.8052637577056885, "start": 876, "end": 900, "probe_score": 0.9936, "gold": "DATA_MENTION", "gold_tier": "v1"}, {"text": "Phone surveys", "label": "DESCRIPTIVE_DATA", "score": 0.8143156170845032, "start": 1777, "end": 1790, "probe_score": 0.9783, "gold": "DATA_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "Covering all 44 asylum countries which provided monthly data to UNHCR.<br>Top-20 ranking of countries based on applications lodged in all countries. An asterisk (*) denotes between 1 and 4 applications.|**Table 6. Applications submitted by country of asylum and origin, 2008**<br>Covering all 44 asylum countries which provided monthly data to UNHCR.<br>Top-20 ranking of countries based on applications lodged in all countries. An asterisk (*) denotes between 1 and 4 applications.|**Table 6. Applications submitted by country of asylum and origin, 2008**<br>Covering all 44 asylum countries which provided monthly data to UNHCR.<br>Top-20 ranking of countries based on applications lodged in all countries. An asterisk (*) denotes between 1 and 4 applications.|**Table 6. Applications submitted by country of asylum and origin, 2008**<br>Covering all 44 asylum countries which provided monthly data to UNHCR.<br>Top-20 ranking of countries based on applications lodged in all countries. An asterisk (*) denotes between 1 and 4 applications.|**Table 6. Applications submitted by country of asylum and origin, 2008**<br>Covering all 44 asylum countries which provided monthly data to UNHCR.<br>Top-20 ranking of countries based on applications lodged in all countries. An asterisk (*) denotes between 1 and 4 applications.|**Table 6. Applications submitted by country of asylum and origin, 2008**<br>Covering all 44 asylum countries which provided monthly data to UNHCR.<br>Top-20 ranking of countries based on applications lodged in all countries. An asterisk (*) denotes between 1 and 4 applications.|**Table 6. Applications submitted by country of asylum and origin, 2008**<br>Covering all 44 asylum countries", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": ["monthly data"]}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "reliefweb", "corpus_id": "reliefweb:000427", "page": 18, "chunk": 1, "title": "Asylum Levels and Trends in Industrialized Countries 2008 - Statistical Overview of Asylum Applications Lodged in Europe and selected Non-European Countries", "pdf_url": "https://reliefweb.int/attachments/3ab13bab-8d4b-3f86-b90a-e2540078aef7/2F800689DD12C5A78525758300561F85-unhcr-asylumtrends-mar2009.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "monthly data", "label": "VAGUE_DATA", "score": 0.5557720065116882, "start": 48, "end": 60, "probe_score": 0.7977, "gold": "NON_MENTION", "gold_tier": "v1"}], "probe_model": "rafmacalaba/gliner_datause_probe"}
{"input": "24. _Implementation_ : The assessment revealed gaps between the actual implementation and plans\nparticularly with regard to timelines and cost. In most cases, activities are not implemented as per the\nplanned time frame and there is huge difference observed between the actual contract amount and the cost\nestimate as indicated in the procurement plan. This is due to inadequate preparation, lack of collaboration\nwith the relevant stakeholders and in adequate market assessment and also due to the limited practice in\nupdating procurement plans to respond to changes in the market, requirement, timeframe, cost etc., It is\nalso noted that procurement plans are usually prepared as a formality for budget processing purpose rather\nthan to use them as a management tool useful to strategize and monitor procurement activities. For program\nimplementation, the gaps shall be addressed through training and skill development during the proposed\nannual fiduciary forum.\n\n\n**3.1.3. Procurement profile of the program**\n25. _General Procurement profile in the IAs_ **:** Based on the data collected from all the visited\nImplementing agencies, the assessment revealed that, in the last two years, on average close to 60% of the\ntotal expenditure was spent through procurement. The share of procurement expenditure from the total\nexpenditure is much higher in the federal IAs as compared to regional or local expenditure. In the MoA,\nthe average share of procurement expenditure for the last two years was 75% of the total expenditure while\nit was 52% in the Ethiopian Agriculture Research Institute (EIAR). (Figure 1) The average procurement\nexpenditure in 2016/17 and 2017/18 budget years for all of the visited IAs was USD 60 million and USD\n55 million respectively. The volume of procurement in the Ministry of Agriculture is the largest amounting\nto two third of the aggregate procurement carried out in all the visited IA. In terms of category, the\nprocurement of Goods assumes the largest share amounting to 73% and 77% in 2016/17 and", "output": {"entities": {"named_data": [], "descriptive_data": ["data collected from all the visited\nImplementing agencies"], "vague_data": []}, "entity_descriptions": {"named_data": "A data mention with a proper name: dataset, survey, database, index, census, registry, or information system.", "descriptive_data": "A data mention described by its characteristics or producer rather than a proper name.", "vague_data": "A data mention that only generally references data, information, or statistics."}}, "corpus": "fcv", "origin": "fcv_pads_east_africa", "corpus_id": "fcv_pads_east_africa:016090", "page": 14, "chunk": 0, "title": "Final Fiduciary Systems Assessment - ETHIOPIA CLIMATE ACTION THROUGH LANDSCAPE MANAGEMENT PROGRAM FOR RESULTS - P170384", "pdf_url": "https://documents.worldbank.org/curated/en/647141558461409065/pdf/Final-Fiduciary-Systems-Assessment-ETHIOPIA-CLIMATE-ACTION-THROUGH-LANDSCAPE-MANAGEMENT-PROGRAM-FOR-RESULTS-P170384.pdf", "extractor": "rafmacalaba/gliner_datause", "footnote_link": true, "dedupe_overlap": true, "has_data_score": 1.0, "split": "holdout", "spans": [{"text": "data collected from all the visited\nImplementing agencies", "label": "DESCRIPTIVE_DATA", "score": 0.8955267071723938, "start": 1077, "end": 1134, "probe_score": 0.3457, "gold": "DATA_MENTION", "gold_tier": "human-final"}], "probe_model": "rafmacalaba/gliner_datause_probe"}