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| license: other | |
| task_categories: | |
| - visual-question-answering | |
| language: | |
| - en | |
| # svrd_cleaned | |
| The **svrd__x** family of the ElliotVL supervised-fine-tuning pool, **after VLM cleaning**. | |
| | | | | |
| |---|---| | |
| | images | 1,827 | | |
| | QA turns | 11,163 | | |
| | answers rewritten by the cleaning pass | 2,766 | | |
| | QA created by the cleaning pass (`new_qa`) | 7,858 (70.4%) | | |
| | shards | 4 | | |
| ## How this was cleaned | |
| A vision-language model read each image together with its QA and judged the item. The pass is | |
| **not a filter that only removes rows** — it rewrites answers it finds wrong but salvageable, | |
| drops what it cannot salvage, and adds QA where the image supports more than the source provided. | |
| Each row carries the judge's own record in `clean_meta`, including the cleaner identity, the | |
| policy it applied, and its per-item scores for legibility, richness and coverage. | |
| **A large share of the QA here was written by the cleaning pass, not by the original dataset.** | |
| Across the pool that share runs from roughly half to over 80% of a family's turns, and it is | |
| reported in the table above. Those rows have an empty `org_answer` because no pre-clean original | |
| exists. Treat them as model-generated supervision: they were judged against the image, but they | |
| are not human annotation, and model-written QA is where formatting defects are most likely. | |
| The effect on the answers that *were* carried over is substantive rather than cosmetic. In this pool the pass corrects values, not just | |
| wording — a curve's critical point restated from `4.00` to `2.00`, a computed ratio from `1` to | |
| `Approximately 1.33` — and for some families it removed the content entirely, which is why those | |
| families are absent here rather than published empty. | |
| ## `answer` vs `org_answer` | |
| - `answer` — the cleaned answer. **Train on this.** | |
| - `org_answer` — the pre-cleaning answer from the same `(image, question)` in the uncleaned pool. | |
| It is empty for QA the cleaning pass added, which have no original. | |
| Where the two differ, the difference is the correction. Keeping both makes every edit auditable | |
| instead of asking you to take the cleaning on trust. | |
| ## Schema | |
| - `image` — HF `Image()`, renders directly in the dataset viewer | |
| - `image_sha256` — content hash of the image | |
| - `n_qa` — number of turns attached to this image | |
| - `qa` — list of {`question`, `answer`, `org_answer`}, **in source order** | |
| - `family` / `clean_meta` — provenance and the judge's per-row record | |
| A row with more than one entry in `qa` is a **conversation over a single image**, not a set of | |
| independent questions — the turns depend on each other and the image belongs to all of them. | |
| Keep them together and in order when training. | |
| Parquet row groups are written at ~32 MB so the dataset viewer pages without stalling. | |
| ## What is NOT claimed | |
| No rejection sampling was run against this family: there is no accept/reject verdict per row, and | |
| `answer` is the cleaned reference rather than a model generation that a string verifier confirmed. | |
| For that, use the `*_RS_think` / `*_rejected` datasets in [elliot-mllm](https://huggingface.co/elliot-mllm). | |
| ## Examples | |
| 10 rows taken straight from this dataset. Images are the **original files** as stored here - no downscaling, no recompression - and every turn is shown in full. | |
| ### Example 1 — 5 turns on one image | |
|  | |
| | # | question | answer (cleaned) | org_answer (pre-judge) | | |
| |---|---|---|---| | |
| | 1 | \nExtract all key-value pairs and important information from this document. | I can identify the following key information from this document:<br><br>**Key-Value Relationships:**<br>• 报验号: NO.142002015001209<br>• 日期: 2015-12-30<br>• Tel: (0635)8506063<br>• Fax: (0635)8506069<br>• 页数: 第1页 共1页<br>• 地址: 山东省高唐县姜店工业开发区105国道<br>• 委托方: 高唐华特威科技有限公司<br>• 样品数量: 1个(3袋)<br>• 样品名称: 玉米芯颗粒粉<br>• 样品特征与状态: 符合要求 | I can identify the following key information from this document:\n\n**Key-Value Relationships:**\n• 报验号:: N0.142002015001209\n• 日期: 2015-12-30\n• Tel:: (0635)8506063\n• Fax:: (0635)8506069\n• 页数: 第1页 共1页\n• 地: 山东省高唐县姜店工业开发区105国\n• 委托方:: 高唐华特威科技有限公司\n• 样品数量:: 1个(3袋)\n• 样品名称:: 玉米芯颗粒粉\n• 样品特征与状态:: 符合要求 | | |
| | 2 | What is the full name of the issuing organization and the document title? | Issuing Organization: 聊城检验检疫局技术中心 (LIAOCHENG ENTRY-EXIT INSPECTION AND QUARANTINE BUREAU TECHNOLOGY CENTER). Document Title: 检测报告 (TEST REPORT). | _(unchanged)_ | | |
| | 3 | What are the sample number, sample receipt date, and the test result for 'Lead' (铅)? | Sample Number: 142015007939. Sample Receipt Date: 2015-12-24. Lead (铅) Result: 0.17 mg/kg. | _(unchanged)_ | | |
| | 4 | What are the test methods used for 'Total Arsenic' (总砷) and 'Salmonella' (沙门氏菌)? | Total Arsenic: GB/T 5009.11-2003(第一法). Salmonella: GB/T 13091-2002. | _(unchanged)_ | | |
| | 5 | What is the text in the 'Statement' (声明) section at the bottom of the document? | 1. 未经本实验室书面同意,不得部分地复制本报告。 2. 检验结果仅对受检样品有效。 | _(unchanged)_ | | |
| ### Example 2 — 6 turns on one image | |
|  | |
| | # | question | answer | | |
| |---|---|---| | |
| | 1 | \nWhat are the key details and their values in this document? | I can identify the following key information from this document:\n\n**Key-Value Relationships:**\n• 资质有效期至:: 2021.12.13\n• 报告编号:: BMILP-NVTC-2019-033-2\n• 资质认定证书编号: 150121340108\n• 产品名称:: XYG-001阻性管道式消声器\n• 委托方:: 靖江市万春空调设备制造有限公司\n• 委托方地址:: 靖江市斜桥镇江平路夏仕港桥南首50米\n• 检测类别:: 委托\n• 签发日期:: 2019年6月17日\n• 有效日期:: 2022年6月16日\n• 联系电话:: 010-63524194 | | |
| | 2 | What is the code located in the top right corner of the document? | BMILP-4-303 | | |
| | 3 | What is the full title of the report displayed in the center? | 阻性管式消声器 检测报告 | | |
| | 4 | Which organization issued this report, as indicated by the text and stamp at the bottom? | 北京市劳动保护科学研究所 | | |
| | 5 | What is the page number information at the bottom of the document? | 第 1 页 共 5 页 | | |
| | 6 | What are the address, zip code, and email listed in the footer? | Address: 北京市陶然亭路55号, Zip: 100054, Email: lbszjzx@bmlp.com | | |
| ### Example 3 — 4 turns on one image | |
|  | |
| | # | question | answer | | |
| |---|---|---| | |
| | 1 | \nAnalyze this document and identify the structured information and relationships. | I can identify the following key information from this document:\n\n**Key-Value Relationships:**\n• 报告单号:: 2017102034\n• 产品名称: 13X分子筛\n• 生产日期: 2017-10-20\n• 执行标准: HG/T2690-2012\n• 抽样日期: 2017-10-20\n• 产品批量: 100吨\n• 化验日期: 2017-10-20\n• 生产单位:: 巩义市豫润海源净水材料有限公司\n• 型号: 13X分子筛\n• 型号: 13X分子筛 | | |
| | 2 | What are the specific test results and standards for Static Water Adsorption, Packaging Moisture Content, Carbon Dioxide Adsorption Capacity, and Abrasion Rate? | Static Water Adsorption: Standard ≥25%, Result 30%. Packaging Moisture Content: Standard ≤1.5%, Result 1.2%. Carbon Dioxide Adsorption Capacity: Standard ≥18, Result 20%. Abrasion Rate: Standard ≤0.2%, Result 0.18%. | | |
| | 3 | What is the conclusion of the inspection report and what does the red stamp say? | The conclusion is '产品各项合格' (Product items qualified), and the red stamp reads '检验合格' (Inspection Qualified). | | |
| | 4 | What is the English name of the company listed in the header? | Gongyi city embellish sea water purification materials co., LTD | | |
| ### Example 4 — 6 turns on one image | |
|  | |
| | # | question | answer (cleaned) | org_answer (pre-judge) | | |
| |---|---|---|---| | |
| | 1 | \nExtract all key-value pairs and important information from this document. | **Key-Value Relationships:**<br>• 座位号: 23A<br>• 序号: 023<br>• 航班: CA 4498<br>• 舱位: S<br>• 日期: 11JUL<br>• 登机时间: 0900<br>• 登机口: 4<br>• 始发地: JZH 九寨黄龙<br>• 目的地: CTU 成都<br>• 姓名: YANGYI 杨亦<br>• 身份识别: NI3306021999...102X<br>• 票号: 9995283376205/1<br>• 机场: 四川九寨黄龙机场 (Sichuan jiuzhai huanglong airport) | I can identify the following key information from this document:\n\n**Key-Value Relationships:**\n• 座位号: 23A\n• 序号: 023\n• 航班: CA 4498\n• 舱位: S\n• 日期: 11JUL\n• 登机时间: 0900\n• 登机口: 4\n• 始发地: JCH 九寨黄龙\n• 目的地: CTU 成都\n• 身份识别: 102X | | |
| | 2 | What is the ticket number (TKT NO) listed on the boarding pass? | 9995283376205/1 | _(unchanged)_ | | |
| | 3 | What is the passenger's name? | YANGYI / 杨亦 | _(unchanged)_ | | |
| | 4 | What is the full name of the airport at the top of the pass? | 四川九寨黄龙机场 Sichuan jiuzhai huanglong airport | _(unchanged)_ | | |
| | 5 | What is the warning text at the bottom regarding gate closing? | 登机口于起飞前10分钟关闭 GATES CLOSE 10 MINUTES BEFORE DEPARTURE TIME | _(unchanged)_ | | |
| | 6 | What is the watermark text in the bottom right corner? | 7788收藏@S13334-2020.07.10 | _(unchanged)_ | | |
| ### Example 5 — 4 turns on one image | |
|  | |
| | # | question | answer (cleaned) | org_answer (pre-judge) | | |
| |---|---|---|---| | |
| | 1 | \nExtract all key-value pairs and important information from this document. | **Key-Value Relationships:**<br>• 座位号: 8C<br>• 舱位: J<br>• 日期: 26MAY<br>• 序号: 012<br>• 航班: JR1632<br>• 始发地: 铜仁 (TONGREN FENGHUANG)<br>• 目的地: 长沙 (CHANGSHA)<br>• 登机时间: 0930<br>• 登机口: 02<br>• ETKT: 9292093909297/1 | I can identify the following key information from this document:\n\n**Key-Value Relationships:**\n• 座位号: 8C\n• 舱位: J\n• 日期: 26MAY\n• 序号: 012\n• 航班: JR1632\n• 始发地: 铜仁\n• 目的地: 长沙\n• 登机时间: 0930\n• 登机口: 02\n• ETKT: 9292093909297/1 | | |
| | 2 | \nExtract all the named entities and classify them by type. | **Entities Identified:**<br>• Title: 登机牌 BOARDING PASS<br>• Flight Number: JR1632<br>• Date: 26MAY<br>• Class: J<br>• Serial No.: 012<br>• Seat No.: 8C<br>• Destination: 长沙 CHANGSHA<br>• Origin: 铜仁 TONGREN FENGHUANG<br>• Gate: 02<br>• Boarding Time: 0930<br>• Ticket No.: 9292093909297/1 | **Entities Identified:**\n• Title, which describes the type of cards, tickets, bills, papers and so on. It usually locates on the top part of the first row.: PASS, BOARDING, 登机牌 | | |
| | 3 | What are the English names for the destination and origin cities listed on the boarding pass? | Destination: CHANGSHA; Origin: TONGREN FENGHUANG. | _(unchanged)_ | | |
| | 4 | What is the warning text printed at the very bottom of the boarding pass? | 登机口于起飞前15分钟关闭 GATES CLOSE 15 MINUTES BEFORE DEPARTURE TIME | _(unchanged)_ | | |
| ### Example 6 — 6 turns on one image | |
|  | |
| | # | question | answer (cleaned) | org_answer (pre-judge) | | |
| |---|---|---|---| | |
| | 1 | \nWhat are the key details and their values in this document? | I can identify the following key information from this document:<br><br>**Key-Value Relationships:**<br>• 24小时订票热线: 0731-84112222<br>• 航班号: MF8221<br>• 始发站: 长沙<br>• 到达站: 咸阳<br>• ORIGIN: CHANGSHA<br>• DEST: XI AN/XIANYANG<br>• 日期: 10MAR<br>• 登机时间: 1730<br>• 座位号: 15A<br>• 舱位: G<br>• 登机口: 42<br>• ETKT: 7312312246845/1<br>• ID: NI43018119870221504X | I can identify the following key information from this document:\n\n**Key-Value Relationships:**\n• 24小时订票热线:: 0731-84112222\n• 航班号: MF8221\n• 始发站: 长沙\n• 到达站: 咸阳\n• ORIGIN: CHANGSHA\n• DEST: XI AN/XI\n• 日期: 10MAR\n• 登机时间: 1730\n• 座位号: 15A\n• 登机口: 42 | | |
| | 2 | \nAnalyze this document and identify all key entities with their classifications. | **Entities Identified:**<br>• Institution: CHANGSHA HUANGHUA INTERNATIONAL AIRPORT, 长沙黄花国际机场<br>• Flight Number: MF8221<br>• Date: 10MAR<br>• Seat: 15A<br>• Class: G<br>• Gate: 42<br>• ID Number: NI43018119870221504X | **Entities Identified:**\n• Institution, which is the name or appellation of different organization including companies, merchants, business entities, academic community, and so on.: CHANGSHA HUANGHUAINTERNATIONALAIRPORT, 长沙黄花国际机场 | | |
| | 3 | What is the cabin class indicated on the boarding pass? | G | _(unchanged)_ | | |
| | 4 | What is the ETKT number printed at the bottom left? | 7312312246845/1 | _(unchanged)_ | | |
| | 5 | What is the ID number located below the gate number? | NI43018119870221504X | _(unchanged)_ | | |
| | 6 | What is the text inside the red rectangular box on the bottom right? | 登机口可能变更,请注意广播或提示信息。 | _(unchanged)_ | | |
| ### Example 7 — 6 turns on one image | |
|  | |
| | # | question | answer (cleaned) | org_answer (pre-judge) | | |
| |---|---|---|---| | |
| | 1 | \nWhat types of entities can you detect in this document? | **Entities Identified:**<br>• Title: BOARDING PASS, 登机牌<br>• Institution: 四川九寨黄龙机场, Sichuan jiuzhai huanglong airport<br>• Flight: MU 2374<br>• Date: 15JUL<br>• Class: E<br>• Serial No: 071<br>• Seat No: 36L<br>• Destination: XIY 西安咸阳<br>• Origin: JZH 九寨黄龙<br>• Gate: 5<br>• Boarding Time: 1010<br>• Name: WANGYONG / 汪永<br>• Ticket No: 7812483208128/1 | **Entities Identified:**\n• Title, which describes the type of cards, tickets, bills, papers and so on. It usually locates on the top part of the first row.: BOARDING PASS, 登机牌\n• Institution, which is the name or appellation of different organization including companies, merchants, business entities, academic community, and so on.: 四川九寨黄龙机场, Sichuan jiuzhai huanglong aiport | | |
| | 2 | \nExtract all the named entities and classify them by type. | **Entities Identified:**<br>• Title: BOARDING PASS, 登机牌<br>• Institution: 四川九寨黄龙机场, Sichuan jiuzhai huanglong airport<br>• Flight: MU 2374<br>• Date: 15JUL<br>• Class: E<br>• Serial No: 071<br>• Seat No: 36L<br>• Destination: XIY 西安咸阳<br>• Origin: JZH 九寨黄龙<br>• Gate: 5<br>• Boarding Time: 1010<br>• Name: WANGYONG / 汪永<br>• Ticket No: 7812483208128/1 | **Entities Identified:**\n• Title, which describes the type of cards, tickets, bills, papers and so on. It usually locates on the top part of the first row.: BOARDING, BOARDING PASS, 机牌\n• Institution, which is the name or appellation of different organization including companies, merchants, business entities, academic community, and so on.: 四川九寨黄龙机场, Sichuan jiuzhai huanglong ainport | | |
| | 3 | \nPlease extract and organize all the important information from this document. | **Key-Value Relationships:**<br>• 航班 (FLIGHT): MU 2374<br>• 日期 (DATE): 15JUL<br>• 舱位 (CLASS): E<br>• 序号 (SERIAL NO.): 071<br>• 座位号 (SEAT NO.): 36L<br>• 目的地 (TO): XIY 西安咸阳<br>• 始发地 (FROM): JZH 九寨黄龙<br>• 登机口 (GATE): 5<br>• 登机时间 (BDT): 1010<br>• 姓名 (NAME): WANGYONG / 汪永<br>• 票号 (TKT NO.): 7812483208128/1 | I can identify the following key information from this document:\n\n**Key-Value Relationships:**\n• 航班: MU 2374\n• 航班: MU\n• 日期: 15JUL\n• 舱位: E\n• 序号: 071\n• 座位号: 36L\n• 日期: JIL\n• 目的地: 西安咸阳\n• 始发地: JZH九寨黄龙\n• 登机时间: 1010 | | |
| | 4 | What is the gate number and the passenger's name listed on the boarding pass? | Gate: 5, Name: WANGYONG / 汪永 | _(unchanged)_ | | |
| | 5 | What is the ticket number (TKT NO) and the warning text at the bottom of the pass? | TKT NO: 7812483208128/1, Warning: GATES CLOSE 10 MINUTES BEFORE DEPARTURE TIME | _(unchanged)_ | | |
| | 6 | What website watermark is visible in the top right corner of the image? | 7788.com | _(unchanged)_ | | |
| ### Example 8 — 8 turns on one image | |
|  | |
| | # | question | answer (cleaned) | org_answer (pre-judge) | | |
| |---|---|---|---| | |
| | 1 | \nWhat types of entities can you detect in this document? | **Entities Identified:**\n• Title, which describes the type of cards, tickets, bills, papers and so on. It usually locates on the top part of the first row.: 2015年出口日本茶叶推荐使用农药清单 | _(unchanged)_ | | |
| | 2 | \nExtract all key-value pairs and important information from this document. | The document contains a table with 25 rows of pesticide data. Key information includes:<br>1. Bifenthrin (联苯菊酯), Limit: 30, Target: 防治茶黑毒蛾、象甲类、茶尺蠖、茶蝉类害虫<br>2. Lambda-cypermethrin (高效氯氰菊酯), Limit: 20, Target: 防治茶尺蠖、茶毛虫、茶细蛾等鳞翅目害虫,假眼小绿叶蝉、茶叶螨类害虫<br>3. Lambda-Cyhalothrin (高效氯氟氰菊酯、功夫菊酯), Limit: 15, Target: 防治茶尺蠖、茶毛虫、茶细蛾等鳞翅目害虫,假眼小绿叶蝉、茶叶螨类害虫<br>4. Thiacloprid (噻虫啉), Limit: 30, Target: 茶小绿叶蝉、黑粉刺虱等害虫<br>5. Cypermethrin (氯氰菊酯、安绿宝、高宝), Limit: 20, Target: 防治茶尺蠖、茶毛虫、刺蛾类、卷叶蛾类害虫<br>6. Dinotefuran (呋虫胺), Limit: 25, Target: 茶小绿叶蝉<br>7. Flufenoxuron (氟虫脲), Limit: 15, Target: 防治茶小绿叶蝉、茶尺蠖、茶毛虫、茶细蛾<br>8. Buprofezin (噻嗪酮、优乐得、扑虱灵), Limit: 30, Target: 防治叶蝉、蓟马、粉虱、蚧类,兼治茶橙瘿螨类<br>9. Diafenthiuron (丁醚脲), Limit: 20, Target: 茶小绿叶蝉、茶尺蠖等鳞翅目害虫<br>10. Tebufenozide+chlorfenapyr (虫酰肼+虫螨腈、黄药师), Limit: 25+40, Target: 茶小绿叶蝉、茶尺蠖等鳞翅目害虫<br>11. Flonicamid (氟啶虫酰胺), Limit: 40, Target: 茶小绿叶蝉、蓟马、红蜘蛛<br>12. Propargite (克螨特、炔螨特), Limit: 5, Target: 防治茶螨类害虫<br>13. Imidacloprid (吡虫啉、一遍净、大功臣、蚜虱净), Limit: 10, Target: 防治茶蚜、黑粉刺虱、假眼小绿叶蝉、茶叶蛾类害虫<br>14. Pyridaben (哒螨灵、扫螨净), Limit: 10, Target: 防治茶螨类害虫<br>15. Fenpropathrin (甲氰菊酯、灭扫利), Limit: 25, Target: 防治鳞翅目害虫、茶蚜、茶蚧、粉虱类害虫<br>16. Deltamethrin (溴氰菊酯), Limit: 10, Target: 防治毒蛾类、尺蠖、茶蚜、黑刺粉虱类、蚧类害虫<br>17. Tridemorph (十三吗啉), Limit: 20, Target: 炭疽病、茶饼病、白星病、茶云纹叶枯病等叶面病害<br>18. Chlorothalonil (百菌清、达科宁), Limit: 10, Target: 防治炭疽病、茶白星病、茶云纹叶枯病、茶叶斑病<br>19. Thiamethoxam (噻虫嗪), Limit: 20, Target: 茶小绿叶蝉、黑粉刺虱<br>20. Chlorfenapyr (溴虫腈、虫螨腈), Limit: 40, Target: 防治茶小绿叶蝉、茶叶螨类害虫<br>21. Becillus thuringiensis (苏云金杆菌(B·T)), Limit: 豁免物质, Target: 防治茶毛虫、茶黑毒蛾、茶刺蛾等鳞翅目幼虫<br>22. Bordeaux mixture (波尔多液), Limit: 豁免物质, Target: 封园防病虫害(每两年使用一次)<br>23. Calium polysulfides (石硫合剂), Limit: 豁免物质, Target: 封园防病虫害(每两年使用一次)<br>24. Petroleum oil (绿颖), Limit: 豁免物质, Target: 红蜘蛛、青苔、煤烟病<br>25. Copper hydroxide (氢氧化铜), Limit: 豁免物质, Target: 苔藓、地衣 | I can identify the following key information from this document:\n\n**Key-Value Relationships:**\n• 1: 联苯菊酯\n• 1: 30\n• 1: 防治茶黑毒蛾、象甲类、茶尺蠖、茶蝉类害虫\n• 2: 高效氯氰菊酯\n• 2: 20\n• 2: 防治茶尺蠖、茶毛虫、茶细蛾等鳞翅目害虫,假眼小绿叶蝉、茶叶螨类害虫\n• 3: 高效氯氟氰菊酯、功夫菊酯\n• 3: 15\n• 3: 防治茶尺蠖、茶毛虫、茶细蛾等鳞翅目害虫,假眼小绿叶蝉、茶叶螨类害虫\n• 4: 噻虫啉 | | |
| | 3 | What are the column headers of the table? | The column headers are: 序号 (No.), 农药英文名 (Pesticide English Name), 农药中文名 (Pesticide Chinese Name), 日本残留限量标准 (毫克/千克) (Japan Residue Limit Standard (mg/kg)), and 防治对象 (Target Pests/Diseases). | _(unchanged)_ | | |
| | 4 | List the pesticide details for rows 5 through 10. | 5. Cypermethrin (氯氰菊酯、安绿宝、高宝), Limit: 20, Target: 防治茶尺蠖、茶毛虫、刺蛾类、卷叶蛾类害虫<br>6. Dinotefuran (呋虫胺), Limit: 25, Target: 茶小绿叶蝉<br>7. Flufenoxuron (氟虫脲), Limit: 15, Target: 防治茶小绿叶蝉、茶尺蠖、茶毛虫、茶细蛾<br>8. Buprofezin (噻嗪酮、优乐得、扑虱灵), Limit: 30, Target: 防治叶蝉、蓟马、粉虱、蚧类,兼治茶橙瘿螨类<br>9. Diafenthiuron (丁醚脲), Limit: 20, Target: 茶小绿叶蝉、茶尺蠖等鳞翅目害虫<br>10. Tebufenozide+chlorfenapyr (虫酰肼+虫螨腈、黄药师), Limit: 25+40, Target: 茶小绿叶蝉、茶尺蠖等鳞翅目害虫 | _(unchanged)_ | | |
| | 5 | List the pesticide details for rows 11 through 20. | 11. Flonicamid (氟啶虫酰胺), Limit: 40, Target: 茶小绿叶蝉、蓟马、红蜘蛛<br>12. Propargite (克螨特、炔螨特), Limit: 5, Target: 防治茶螨类害虫<br>13. Imidacloprid (吡虫啉、一遍净、大功臣、蚜虱净), Limit: 10, Target: 防治茶蚜、黑粉刺虱、假眼小绿叶蝉、茶叶蛾类害虫<br>14. Pyridaben (哒螨灵、扫螨净), Limit: 10, Target: 防治茶螨类害虫<br>15. Fenpropathrin (甲氰菊酯、灭扫利), Limit: 25, Target: 防治鳞翅目害虫、茶蚜、茶蚧、粉虱类害虫<br>16. Deltamethrin (溴氰菊酯), Limit: 10, Target: 防治毒蛾类、尺蠖、茶蚜、黑刺粉虱类、蚧类害虫<br>17. Tridemorph (十三吗啉), Limit: 20, Target: 炭疽病、茶饼病、白星病、茶云纹叶枯病等叶面病害<br>18. Chlorothalonil (百菌清、达科宁), Limit: 10, Target: 防治炭疽病、茶白星病、茶云纹叶枯病、茶叶斑病<br>19. Thiamethoxam (噻虫嗪), Limit: 20, Target: 茶小绿叶蝉、黑粉刺虱<br>20. Chlorfenapyr (溴虫腈、虫螨腈), Limit: 40, Target: 防治茶小绿叶蝉、茶叶螨类害虫 | _(unchanged)_ | | |
| | 6 | List the pesticide details for rows 21 through 25, noting the special category in the limit column. | Rows 21-25 are categorized as '豁免物质' (Exempt substances) in the limit column.<br>21. Becillus thuringiensis (苏云金杆菌(B·T)), Target: 防治茶毛虫、茶黑毒蛾、茶刺蛾等鳞翅目幼虫<br>22. Bordeaux mixture (波尔多液), Target: 封园防病虫害(每两年使用一次)<br>23. Calium polysulfides (石硫合剂), Target: 封园防病虫害(每两年使用一次)<br>24. Petroleum oil (绿颖), Target: 红蜘蛛、青苔、煤烟病<br>25. Copper hydroxide (氢氧化铜), Target: 苔藓、地衣 | _(unchanged)_ | | |
| | 7 | Which rows are highlighted in yellow and which are highlighted in green? | Rows 2, 6, 9, 10, 11, 24, and 25 are highlighted in yellow. Rows 22 and 23 are highlighted in green. | _(unchanged)_ | | |
| | 8 | What is the watermark text visible at the bottom right of the image? | 知乎 @欧阳林三 | _(unchanged)_ | | |
| ### Example 9 — 6 turns on one image | |
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| | # | question | answer (cleaned) | org_answer (pre-judge) | | |
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| | 1 | \nExtract all the named entities and classify them by type. | **Entities Identified:**<br>• Title: 装修材料清单预算表<br>• Subtitle: 家庭装修材料清单 预算价格表明细 | **Entities Identified:**\n• Title, which describes the type of cards, tickets, bills, papers and so on. It usually locates on the top part of the first row.: 商都县行政事业性收费公示清单\n• Date, which is the date of the special time node such as departure, arriving, issuing, trading, and so on.: 2017年4月5日 | | |
| | 2 | \nWhat are the key details and their values in this document? | **Key-Value Relationships (Partial Extraction):**<br>• Location: 客<br>• Name: 顶面乳胶漆, Quantity: 22, Unit Price: 12, Amount: 264<br>• Name: 客厅吊顶, Quantity: 9, Unit Price: 130, Amount: 1170<br>• Name: 顶面造型吊顶, Quantity: 30.04, Unit Price: 95, Amount: 2853.8 | I can identify the following key information from this document:\n\n**Key-Value Relationships:**\n• 工程量: 22\n• 单价: 12\n• 金额: 264\n• 名称: 顶面乳胶漆\n• 工程量: 9\n• 单价: 130\n• 金额: 1170\n• 名称: 客厅吊顶\n• 名称: 顶面造型吊顶\n• 工程量: 30.04 | | |
| | 3 | What is the main title of the document? | 装修材料清单预算表 | _(unchanged)_ | | |
| | 4 | What are the column headers in the table? | 位置, 名称, 工程量 (平方米), 单价 (元), 金额 (元), 备注 | _(unchanged)_ | | |
| | 5 | List the items and their total amounts for the '厨' (Kitchen) section. | 橱柜地柜: 2800, 吊柜: 800, 洗菜盆及高弯龙头: 360, 抽油烟机: 1200, 炉盘: 420, 吸顶灯: 100, 热水器: 1000 | _(unchanged)_ | | |
| | 6 | What are the items listed under the '主' (Master Bedroom) location? | 顶面基层处理, 顶面乳胶漆, 墙面乳胶漆 | _(unchanged)_ | | |
| ### Example 10 — 7 turns on one image | |
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| | # | question | answer (cleaned) | org_answer (pre-judge) | | |
| |---|---|---|---| | |
| | 1 | \nAnalyze this document and identify the structured information and relationships. | **Key-Value Relationships:**<br>• 招标人及工程名称: 锡林郭勒盟苏尼特左旗2015年公共租赁住房恩格尔小区内配套基础设施建设项目<br>• 招标编号: TQCGGC2016-DS-GKZB-SZ-SG002<br>• 建设地点: 苏尼特左旗满都拉图镇<br>• 资金来源: 申请中央预算内投资<br>• 招标范围: 图纸设计的各工程内容<br>• 计划工期: 2016年9月-2016年12月<br>• 建设规模: 供热管道300米、排水管道300米小区硬化及道路硬化3500㎡<br>• 投标人资质要求: 施工投标人须具备独立的法人资格,具备市政公用工程施工总承包叁级(含暂叁级)及以上资质的企业。(不接受联合体投标)<br>• 报名地点: 网上报名<br>• 招标文件的获取: 1、资格审查合格后方可购买招标文件 2、招标文件每套售价施工1000元,售后不退。<br>• 发布公告媒介: 中国采购与招标网(www.chinabidding.com.cn)、锡林郭勒盟政务服务(公共资源交易)中心网站http://www.xmzwggzy.com、太仆寺旗公共资源交易中心网(http://www.tqzwfw.com/tq/default.aspx)<br>• 招标代理机构名称: 亿诚建设项目管理有限公司<br>• 联系电话: 15249508558 | I can identify the following key information from this document:\n\n**Key-Value Relationships:**\n• 招标人及工程名称: 锡林郭勒盟苏尼特左旗2015年公共租赁住房恩格尔小区内配套基础设施建设\n• 建设地点: 苏尼特左旗满都拉图镇\n• 资金: 申请中央预算内投资\n• 招标范围: 图纸设计的各工程内容\n• 计划: 2016年9月-2016年12月\n• 建设规模: 供热管道300米、排水管道300米小区硬化及道路硬化3500㎡\n• 投标人资质要求: 施工投标人须具各独立的法人资格,具备市政公用工程施工总承包叁级(含\n• 报名地点: 网上报名\n• 招标文件的获取: 1、资格审查合格后方可购买招标文件\n• 发布公告: 中国采购与招标网(www.chinabidding.com.cn)、锡林郭勒盟政务服务 | | |
| | 2 | What is the main title of the document at the top? | 招标公告审核备案表 | _(unchanged)_ | | |
| | 3 | What is the bidding number (招标编号) listed in the first row? | TQCGGC2016-DS-GKZB-SZ-SG002 | _(unchanged)_ | | |
| | 4 | What is the name of the bidding agency (招标代理机构名称)? | 亿诚建设项目管理有限公司 | _(unchanged)_ | | |
| | 5 | What is the contact phone number (联系电话) provided in the table? | 15249508558 | _(unchanged)_ | | |
| | 6 | What is the price for each set of bidding documents (招标文件每套售价)? | 1000元 | _(unchanged)_ | | |
| | 7 | What is the handwritten date visible at the bottom of the form? | 2016年8月26日 | _(unchanged)_ | | |