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The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
original_conditions_of_access: list<item: string>
child 0, item: string
keywords: list<item: struct<lang: string, original_lang: string, text: string>>
child 0, item: struct<lang: string, original_lang: string, text: string>
child 0, lang: string
child 1, original_lang: string
child 2, text: string
last_modified_timestamp: int64
isbn: list<item: string>
child 0, item: string
original_document_types: list<item: string>
child 0, item: string
date_facets: timestamp[s]
source: list<item: string>
child 0, item: string
conditions_of_access: list<item: string>
child 0, item: string
discarded_authors: list<item: struct<lang: string, fullname: string>>
child 0, item: struct<lang: string, fullname: string>
child 0, lang: string
child 1, fullname: string
datestamp: timestamp[s]
contributor: list<item: string>
child 0, item: string
main_entity_of_page: list<item: string>
child 0, item: string
date_published: string
provider: list<item: string>
child 0, item: string
id: string
headline: list<item: string>
child 0, item: string
knows_about: list<item: struct<uri: string, labels: list<item: struct<lang: string, text: string>>>>
child 0, item: struct<uri: string, labels: list<item: struct<lang: string, text: string>>>
child 0, uri: string
child 1, labels: list<item: struct<lang: string, text: string>>
child 0, item: struct<lang: string, text: string>
child 0, lang: string
child 1, text: st
...
r: list<item: struct<agg: string, fullname: string, id: string>>
child 0, item: struct<agg: string, fullname: string, id: string>
child 0, agg: string
child 1, fullname: string
child 2, id: string
resource_type: list<item: string>
child 0, item: string
additional_type: list<item: string>
child 0, item: string
handle: list<item: string>
child 0, item: string
original_license: list<item: string>
child 0, item: string
abstract: list<item: string>
child 0, item: string
original_source: list<item: string>
child 0, item: string
url: list<item: string>
child 0, item: string
license: list<item: string>
child 0, item: string
issn: list<item: string>
child 0, item: string
producer: list<item: null>
child 0, item: null
publisher: list<item: string>
child 0, item: string
topic: list<item: struct<confidence: double, id: string>>
child 0, item: struct<confidence: double, id: string>
child 0, confidence: double
child 1, id: string
original_languages: list<item: string>
child 0, item: string
doi: list<item: string>
child 0, item: string
vector: list<item: double>
child 0, item: double
_id: string
is_cluster: bool
cluster_children_count: int64
format: list<item: string>
child 0, item: string
temporal_coverage: list<item: null>
child 0, item: null
spatial_coverage: list<item: string>
child 0, item: string
duration: string
original_mentions: list<item: null>
child 0, item: null
mentions: list<item: null>
child 0, item: null
to
{'original_conditions_of_access': List(Value('string')), 'is_cluster': Value('bool'), 'keywords': List({'lang': Value('string'), 'original_lang': Value('string'), 'text': Value('string')}), 'original_document_types': List(Value('string')), 'source': List(Value('string')), 'discarded_authors': List({'lang': Value('string'), 'fullname': Value('string')}), 'datestamp': Value('timestamp[s]'), 'date_published': Value('string'), 'id': Value('string'), 'original_date_published': List(Value('string')), 'identifier': List(Value('string')), 'in_language': List(Value('string')), 'discarded_keywords': List(Json(decode=True)), 'author': List({'agg': Value('string'), 'fullname': Value('string'), 'id': Value('string')}), 'resource_type': List(Value('string')), 'additional_type': List(Value('string')), 'handle': List(Value('string')), 'original_license': List(Value('string')), 'original_source': List(Value('string')), 'license': List(Value('string')), 'issn': List(Value('string')), 'producer': List(Value('null')), 'publisher': List(Value('string')), 'topic': List({'confidence': Value('float64'), 'id': Value('string')}), 'doi': List(Value('string')), 'last_modified_timestamp': Value('int64'), 'isbn': List(Value('string')), 'date_facets': Value('timestamp[s]'), 'conditions_of_access': List(Value('string')), 'contributor': List(Value('string')), 'main_entity_of_page': List(Value('string')), 'provider': List(Value('string')), 'headline': List(Json(decode=True)), 'knows_about': List({'uri': Value('string'), 'labels': List({'lang': Value('string'), 'text': Value('string')})}), 'index_name': Value('string'), 'is_based_on_url': List(Value('string')), 'abstract': List(Json(decode=True)), 'url': List(Value('string')), 'cluster_children_count': Value('int64'), 'original_languages': List(Value('string')), 'vector': List(Value('float64')), '_id': Value('string'), 'format': List(Value('string')), 'original_mentions': List(Value('null')), 'mentions': List(Value('null')), 'temporal_coverage': List(Value('null')), 'spatial_coverage': List(Value('string'))}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
original_conditions_of_access: list<item: string>
child 0, item: string
keywords: list<item: struct<lang: string, original_lang: string, text: string>>
child 0, item: struct<lang: string, original_lang: string, text: string>
child 0, lang: string
child 1, original_lang: string
child 2, text: string
last_modified_timestamp: int64
isbn: list<item: string>
child 0, item: string
original_document_types: list<item: string>
child 0, item: string
date_facets: timestamp[s]
source: list<item: string>
child 0, item: string
conditions_of_access: list<item: string>
child 0, item: string
discarded_authors: list<item: struct<lang: string, fullname: string>>
child 0, item: struct<lang: string, fullname: string>
child 0, lang: string
child 1, fullname: string
datestamp: timestamp[s]
contributor: list<item: string>
child 0, item: string
main_entity_of_page: list<item: string>
child 0, item: string
date_published: string
provider: list<item: string>
child 0, item: string
id: string
headline: list<item: string>
child 0, item: string
knows_about: list<item: struct<uri: string, labels: list<item: struct<lang: string, text: string>>>>
child 0, item: struct<uri: string, labels: list<item: struct<lang: string, text: string>>>
child 0, uri: string
child 1, labels: list<item: struct<lang: string, text: string>>
child 0, item: struct<lang: string, text: string>
child 0, lang: string
child 1, text: st
...
r: list<item: struct<agg: string, fullname: string, id: string>>
child 0, item: struct<agg: string, fullname: string, id: string>
child 0, agg: string
child 1, fullname: string
child 2, id: string
resource_type: list<item: string>
child 0, item: string
additional_type: list<item: string>
child 0, item: string
handle: list<item: string>
child 0, item: string
original_license: list<item: string>
child 0, item: string
abstract: list<item: string>
child 0, item: string
original_source: list<item: string>
child 0, item: string
url: list<item: string>
child 0, item: string
license: list<item: string>
child 0, item: string
issn: list<item: string>
child 0, item: string
producer: list<item: null>
child 0, item: null
publisher: list<item: string>
child 0, item: string
topic: list<item: struct<confidence: double, id: string>>
child 0, item: struct<confidence: double, id: string>
child 0, confidence: double
child 1, id: string
original_languages: list<item: string>
child 0, item: string
doi: list<item: string>
child 0, item: string
vector: list<item: double>
child 0, item: double
_id: string
is_cluster: bool
cluster_children_count: int64
format: list<item: string>
child 0, item: string
temporal_coverage: list<item: null>
child 0, item: null
spatial_coverage: list<item: string>
child 0, item: string
duration: string
original_mentions: list<item: null>
child 0, item: null
mentions: list<item: null>
child 0, item: null
to
{'original_conditions_of_access': List(Value('string')), 'is_cluster': Value('bool'), 'keywords': List({'lang': Value('string'), 'original_lang': Value('string'), 'text': Value('string')}), 'original_document_types': List(Value('string')), 'source': List(Value('string')), 'discarded_authors': List({'lang': Value('string'), 'fullname': Value('string')}), 'datestamp': Value('timestamp[s]'), 'date_published': Value('string'), 'id': Value('string'), 'original_date_published': List(Value('string')), 'identifier': List(Value('string')), 'in_language': List(Value('string')), 'discarded_keywords': List(Json(decode=True)), 'author': List({'agg': Value('string'), 'fullname': Value('string'), 'id': Value('string')}), 'resource_type': List(Value('string')), 'additional_type': List(Value('string')), 'handle': List(Value('string')), 'original_license': List(Value('string')), 'original_source': List(Value('string')), 'license': List(Value('string')), 'issn': List(Value('string')), 'producer': List(Value('null')), 'publisher': List(Value('string')), 'topic': List({'confidence': Value('float64'), 'id': Value('string')}), 'doi': List(Value('string')), 'last_modified_timestamp': Value('int64'), 'isbn': List(Value('string')), 'date_facets': Value('timestamp[s]'), 'conditions_of_access': List(Value('string')), 'contributor': List(Value('string')), 'main_entity_of_page': List(Value('string')), 'provider': List(Value('string')), 'headline': List(Json(decode=True)), 'knows_about': List({'uri': Value('string'), 'labels': List({'lang': Value('string'), 'text': Value('string')})}), 'index_name': Value('string'), 'is_based_on_url': List(Value('string')), 'abstract': List(Json(decode=True)), 'url': List(Value('string')), 'cluster_children_count': Value('int64'), 'original_languages': List(Value('string')), 'vector': List(Value('float64')), '_id': Value('string'), 'format': List(Value('string')), 'original_mentions': List(Value('null')), 'mentions': List(Value('null')), 'temporal_coverage': List(Value('null')), 'spatial_coverage': List(Value('string'))}
because column names don't match
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
original_conditions_of_access list | is_cluster bool | keywords list | original_document_types list | source list | discarded_authors list | datestamp timestamp[s] | date_published string | id string | original_date_published list | identifier list | in_language list | discarded_keywords list | author list | resource_type list | additional_type list | handle list | original_license list | original_source list | license list | issn list | producer list | publisher list | topic list | doi list | last_modified_timestamp int64 | isbn list | date_facets timestamp[s] | conditions_of_access list | contributor list | main_entity_of_page list | provider list | headline list | knows_about list | index_name string | is_based_on_url list | abstract list | url list | cluster_children_count int64 | original_languages list | vector list | _id string | format list | original_mentions list | mentions list | temporal_coverage list | spatial_coverage list |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[
"CC-BY"
] | true | [
{
"lang": "undefined",
"original_lang": "",
"text": "Anne"
},
{
"lang": "undefined",
"original_lang": "",
"text": "Asile"
},
{
"lang": "undefined",
"original_lang": "",
"text": "Bénévolat"
},
{
"lang": "undefined",
"original_lang": "",
"text": "Bénévoles"
... | [
"book",
"info:eu-repo/semantics/book",
"Books"
] | [] | [] | 2026-04-23T13:57:39 | 2026 | -0BKNaYAlXf8GXQpaoY1- | [
"2026"
] | [
"ONIX_20260316T122833_9783034362795_2",
"https://library.oapen.org/handle/20.500.12657/111798",
"10.3726/b23588",
"ISBN: 9783034362795",
"hal-05676153",
"DOI: 10.3726/b23588"
] | [
"fr"
] | [
{
"text": "thema EDItEUR::C Language and Linguistics::CJ Language teaching and learning::CJP Language learning for specific purposes"
},
{
"text": "thema EDItEUR::J Society and Social Sciences::JB Society and culture: general::JBS Social groups, communities and identities::JBSY Social groups: clubs and ... | [
{
"agg": "anne_christel_zeiter_LkfYO8-r4m0o7rw9RK9nR__SEP__Zeiter, Anne-Christel__SEP__zeiter_anne-christel__SEP__anne-christel_zeiter",
"fullname": "Zeiter, Anne-Christel",
"id": "anne_christel_zeiter_LkfYO8-r4m0o7rw9RK9nR"
}
] | [
"document"
] | [
"typ_book"
] | [] | [
"https://creativecommons.org/licenses/by/4.0"
] | [] | [
"lic_creative-commons"
] | [] | [] | [
"Peter Lang International Academic Publishers",
"CCSD",
"Peter Lang Verlag"
] | [] | [
"10.3726/b23588"
] | 1,783,051,841,969 | [
"9783034362795"
] | 2026-01-01T00:00:00 | [
"undefined",
"acr_open-access"
] | [] | [
"https://www.peterlang.com/document/1612365"
] | [
"OapenGotriple",
"HAL"
] | [
{
"original_lang": "",
"is_multi_language": "false",
"translated": "false",
"text": "Langue et intégration\nRequérants d’asile, bénévoles et institutions en Suisse romande : positionnements de la communauté asile",
"lang": [
"fr"
],
"detected_lang": "true"
}
] | [] | triple-documents-prod | [] | [
{
"original_lang": "",
"is_multi_language": "false",
"text": "Comment séjourne-t-on dans un pays auquel on demande l’asile? Comment vit-on dans cette réalité intermédiaire et inconnue? Sur quelles ressources compter pour donner sens à son nouvel environnement et à sa langue, souvent aussi étrange qu’étr... | [
"https://library.oapen.org/bitstream/20.500.12657/111798/1/9783034362795.pdf"
] | 2 | [
"fre"
] | [
0.0102148652,
-0.0622777231,
-0.0120271798,
-0.0281732567,
0.0827074572,
-0.1199422851,
-0.005766456,
-0.0550284646,
-0.0128509589,
0.0352577604,
0.0168050993,
-0.0563465133,
0.0425070189,
-0.0111210225,
-0.0438250639,
0.0682089329,
-0.0599711426,
-0.0015136946,
-0.0140866283,
... | -0BKNaYAlXf8GXQpaoY1- | null | null | null | null | null |
[
"2"
] | true | [
{
"lang": "undefined",
"original_lang": "",
"text": "Pain perception"
},
{
"lang": "undefined",
"original_lang": "",
"text": "Empathy"
},
{
"lang": "undefined",
"original_lang": "",
"text": "Pupil dilation"
},
{
"lang": "undefined",
"original_lang": "",
"t... | [
"14"
] | [] | [] | 2026-07-23T12:53:23 | 2026-03-01 | -0Ored5cuiAfEF3Vxj5V0 | [
"2026-03-01"
] | [] | [
"en"
] | [] | [
{
"agg": "ting_zhang_Fh7jS1dKyLJxYUWqIQXmc__SEP__Zhang, Ting__SEP__zhang_ting__SEP__ting_zhang",
"fullname": "Zhang, Ting",
"id": "ting_zhang_Fh7jS1dKyLJxYUWqIQXmc"
},
{
"agg": "shujia_zhang_MnfwYcItS5ycVlxyN74gt__SEP__Zhang, Shujia__SEP__zhang_shujia__SEP__shujia_zhang",
"fullname": "Zhang,... | [
"document"
] | [
"typ_report"
] | [] | [] | [] | [
"undefined"
] | [] | [] | [
"ELSEVIER"
] | [] | [
"10.1016/j.cognition.2025.106384"
] | 1,786,540,793,810 | [] | 2026-03-01T00:00:00 | [
"other"
] | [] | [
"https://ir.psych.ac.cn/handle/311026/51643"
] | [
"base"
] | [
{
"original_lang": "",
"is_multi_language": "false",
"text": "Automatic pupillary responses to pain perception in adults and children: The influence of race and autistic traits",
"translated": "false",
"lang": [
"en"
],
"detected_lang": "true"
}
] | [] | triple-documents-prod | [] | [
{
"original_lang": "",
"is_multi_language": "false",
"text": "The ability to understand and share others' emotional states (e.g., feeling of pain) plays a fundamental role in survival and prosocial behavior. The current study utilized pupillometry to assess automatic psychophysiological responses to oth... | [] | 2 | [
"eng"
] | [
-0.0217705891,
0.0063193156,
-0.0059175091,
0.1151357368,
0.0911734775,
0.0800690129,
0.0267383754,
-0.0058079259,
0.0438334011,
-0.0219167005,
-0.0165836364,
-0.0549378656,
0.0322906077,
-0.0067941775,
-0.0276150443,
0.0213322565,
-0.076562345,
-0.0447100699,
0.0672112182,
-0.... | -0Ored5cuiAfEF3Vxj5V0 | null | null | null | null | null |
[
"1"
] | true | [
{
"lang": "undefined",
"original_lang": "",
"text": "WISC-IV"
},
{
"lang": "undefined",
"original_lang": "",
"text": "Low and normal IQ groups"
},
{
"lang": "undefined",
"original_lang": "",
"text": "Intellectual disabilities"
},
{
"lang": "undefined",
"origin... | [
"121"
] | [] | [] | 2026-07-23T12:16:42 | 2026 | -0kxtsQdkeHiW-82GYJtj | [
"2026"
] | [] | [
"en"
] | [] | [
{
"agg": "samet_celik_qCFmSg_yFDvUrsL3mRQDV__SEP__Çelik, Samet__SEP__çelik_samet__SEP__samet_çelik",
"fullname": "Çelik, Samet",
"id": "samet_celik_qCFmSg_yFDvUrsL3mRQDV"
},
{
"agg": "figen_eroglu_ada_gmE00qoAbM6c_q0g33SQ7__SEP__Eroglu-Ada, Figen__SEP__eroglu-ada_figen__SEP__figen_eroglu-ada",
... | [
"document"
] | [
"typ_article"
] | [
"11772/26863"
] | [] | [] | [
"undefined"
] | [] | [] | [
"Springernature",
"BMC"
] | [] | [
"10.1186/s40359-025-03927-y"
] | 1,786,535,035,387 | [] | 2026-01-01T00:00:00 | [
"other"
] | [] | [
"https://hdl.handle.net/11772/26863"
] | [
"base"
] | [
{
"original_lang": "",
"is_multi_language": "false",
"text": "Examining the psychometric properties of the WISC-IV in low and normal IQ samples",
"translated": "false",
"lang": [
"en"
],
"detected_lang": "true"
}
] | [] | triple-documents-prod | [] | [
{
"original_lang": "",
"is_multi_language": "false",
"text": "Background The Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is one of the leading instruments in general ability assessments; however, findings regarding its factor structure are still controversial. Methods In this study... | [] | 2 | [
"eng"
] | [
-0.0284040105,
-0.0465342291,
-0.0095939077,
0.0136732068,
0.0229649451,
0.0779599398,
-0.0486494228,
-0.0191878155,
-0.0282529257,
-0.0398864821,
0.0410951637,
-0.0507646129,
0.0673839822,
-0.006647747,
-0.0253823064,
0.0203964971,
-0.0740317255,
-0.0060811779,
-0.0876293927,
... | -0kxtsQdkeHiW-82GYJtj | null | null | null | null | null |
[
"https://creativecommons.org/licenses/by-nc-nd/4.0/",
"info:eu-repo/semantics/OpenAccess"
] | true | [
{
"lang": "en",
"original_lang": "en",
"text": "Economic Policy"
},
{
"lang": "en",
"original_lang": "en",
"text": "Macroeconomic Stabilization"
},
{
"lang": "en",
"original_lang": "en",
"text": "Missing Observations"
},
{
"lang": "en",
"original_lang": "en",
... | [
"info:eu-repo/semantics/preprint",
"Preprints, Working Papers, ...",
"doc-type:workingPaper"
] | [] | [] | 2026-06-09T14:07:42 | 2026-02-10 | -0w1OG4zvKf2HoxwcWqUY | [
"2026-02-10"
] | [
"hal-05506159",
"DOI: 10.13140/RG.2.2.11054.16963",
"doi:10.13140/RG.2.2.11054.16963",
"RePEc:zbw:esprep:336550"
] | [
"en"
] | [] | [
{
"agg": "\"\"",
"fullname": "Levy, Denise",
"id": "dudi_levy_91c_quUv7pdYnKhg0y3VS"
},
{
"agg": "hashem_dezhbakhsh_WhMjkSZjF_qMd00wkNb98__SEP__Dezhbakhsh, Hashem__SEP__dezhbakhsh_hashem__SEP__hashem_dezhbakhsh",
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] | [
"Mémoires, identités, marginalités dans le monde occidental contemporain [UR 15072] (MIMMOC [Poitiers]) ; Université de Poitiers = University of Poitiers (UP)",
"Cette étude a été réalisée dans le cadre du projet « NaNA – la Nature en Nouvelle-Aquitaine,entre innovations gestionnaires et valorisation culturelle ... | [
"https://hal.science/hal-05687498"
] | [
"HAL",
"OpenEdition"
] | [
{
"original_lang": "en",
"is_multi_language": "false",
"text": "Geodiversity and geoheritage in the regional nature parks of Nouvelle-Aquitaine(France): from masks to geoheritage opportunities",
"translated": "false",
"lang": [
"en"
],
"detected_lang": "true"
},
{
"original... | [] | triple-documents-prod | [
"https://hal.science/hal-05687498"
] | [
{
"original_lang": "en",
"is_multi_language": "false",
"translated": "false",
"text": "International audience\nThis article presents a research carried out as part of the regional project \"NaNA - la Nature en Nouvelle-Aquitaine, entre innovations gestionnaires et valorisation culturelle le cas des ... | [] | 2 | [
"fr"
] | [
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0.0175133049,
0.0810481235,
-0.0647128448,
0.0252882708,
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0.062199723,
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0.0929854438,
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0.0530896634,
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-0... | -DSJpi3IihNTw7S5dxOR8 | null | null | null | null | null |
End of preview.
GoTriple 2026 — metadati bibliografici e embedding
75.894 documenti con anno di pubblicazione 2026, estratti da un indice Elasticsearch di GoTriple, il discovery portal per le scienze sociali e umane del progetto OPERAS.
Ogni record contiene i metadati bibliografici aggregati da GoTriple e un embedding denso a 1024 dimensioni del documento.
Contenuto
Un documento per riga, in 8 shard JSONL compressi gzip (575 MB in totale). 54 campi distinti, 37 dei quali presenti in ogni record.
Tipi di documento
Nonostante il nome del dataset, non sono solo articoli:
| Tipo | Documenti | Tipo | Documenti | |
|---|---|---|---|---|
typ_article |
41.224 | typ_report |
1.353 | |
other |
7.568 | typ_thesis |
1.178 | |
typ_book |
7.312 | typ_video |
1.110 | |
typ_conference |
6.360 | typ_dataset |
485 | |
typ_text |
5.842 | typ_audio |
66 | |
typ_review |
2.695 | typ_software |
36 | |
typ_preprint |
1.564 | altri | 63 |
Provider
HAL 31.155 · base 24.664 · OpenEdition 11.712 · econstor 2.233 ·
OapenGotriple 1.639 · Canal-U 1.419 · ucm 1.185 · doaj 872 ·
RECYT 770 · hrcak 286 · altri
Lingue
en 35.266 · fr 25.939 · non dichiarata 7.342 · es 3.358 · de 1.606 ·
it 897 · pt 658 · altre
Il campo vector
Embedding denso a 1024 dimensioni, presente in tutti i 75.894 record. Nell'indice
di origine è un dense_vector Elasticsearch con similarità coseno e indice
int8_hnsw (m: 16, ef_construction: 100).
Il modello che ha prodotto gli embedding non è registrato nell'export e quindi non è dichiarato qui. Va chiesto a chi ha costruito l'indice prima di usare i vettori per confronti con embedding generati altrove.
Come JSON gli embedding pesano circa 22 KB per record, l'84% della taglia del dataset. Chi non ne ha bisogno può scartare il campo in fase di caricamento.
Uso
from datasets import load_dataset
ds = load_dataset("alebertoz/gotriple-articles-2026", split="train")
print(ds[0]["headline"], len(ds[0]["vector"]))
# solo i metadati, senza gli embedding
meta = ds.remove_columns("vector")
Licenze, accesso e provenienza
Il dataset ridistribuisce solo metadati: non contiene testo pieno
(full_text è assente da tutti i record). Licenza e condizioni di accesso sono
dichiarate per singolo record e nella maggior parte dei casi non sono specificate
alla fonte:
license |
Record | conditions_of_access |
Record | |
|---|---|---|---|---|
| non dichiarata | 51.708 | non dichiarate | 29.379 | |
lic_creative-commons |
22.143 | other |
26.173 | |
other |
2.911 | acr_open-access |
18.232 | |
lic_cairn |
168 | acr_all-rights-reserved |
3.431 | |
lic_open-source |
11 | acr_embargoed-access |
932 | |
acr_closed-access |
197 |
La licenza di ciascun record resta quella dichiarata dal provider di origine: va verificata caso per caso prima di riusare i contenuti.
Dati personali
I record contengono nomi di autori, come è normale per metadati bibliografici.
In 520 record compaiono inoltre 426 indirizzi email distinti, quasi sempre
email di corrispondenza incluse dagli autori stessi nel testo dell'abstract
pubblicato; un record ha un campo contact_point con nome, ente ed email di un
referente. Sono dati già pubblici presso gli editori originali e su GoTriple.
Struttura
data/knowledge_base-test-0000{0..7}.jsonl.gz 75.894 documenti, 575 MB
_meta/mapping.json mapping dell'indice di origine
_meta/settings.json settings dell'indice di origine
Come è stato prodotto
Export dell'indice via Point-In-Time + search_after, quindi su una vista
congelata: nessuna scrittura sull'indice di origine. I documenti sono i _source
Elasticsearch così come sono, con l'aggiunta del campo _id. Il file unico
prodotto dall'export è stato poi risuddiviso in 8 shard, con verifica documento per
documento che i 75.894 record fossero identici all'originale.
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