bigscience-workshop / bigscience-workshop/data_tooling

Create dataset s2orc_the_semantic_scholar_open_research_corpus

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#127 コメント 10 件 リアクション 0 件 担当者 2 名 @lvwerra が担当を希望しています GitHub で見る
data catalog language modeling script
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説明

- uid: s2orc_the_semantic_scholar_open_research_corpus
- type: primary
- description:
- name: S2ORC: The Semantic Scholar Open Research Corpus
- description: Largest collection of machine-readable English-language open-access scientific literature formatted to support NLP research. 136M papers with titles and abstracts, including 12.7M papers with full text. Unifies popular resources like PubMed Central (Biomedicine) and arXiv (Physics, Math, CS) with papers sourced across many different academic disciplines. Maintained by the Semantic Scholar Research team at AI2. https://aclanthology.org/2020.acl-main.447/
- homepage: https://github.com/allenai/s2orc
- validated: True
- languages:
- language_names:
- English
- language_comments:
- language_locations:
- World-Wide
- validated: False
- custodian:
- name: Semantic Scholar / Allen Institute for AI
- in_catalogue:
- type: A nonprofit/NGO (other)
- location: United States of America
- contact_name: Kyle Lo
- contact_email: kylel@allenai.org
- contact_submitter: True
- additional: http://allenai.org/
- validated: False
- availability:
- procurement:
- for_download: Yes - after signing a user agreement
- download_url: https://docs.google.com/forms/d/1fUqUw68dDMnzFt58WgMi-FI33MPcVFpflN2G3Yjfn9c/edit
- download_email:
- licensing:
- has_licenses: Yes
- license_text:
- license_properties:
- non-commercial use
- license_list:
- cc-by-nc-2.0: Creative Commons Attribution Non Commercial 2.0 Generic
- pii:
- has_pii: Yes
- generic_pii_likely: very likely
- generic_pii_list:
- names
- email addresses
- physical addresses
- URLs
- website account name or handle
- numeric_pii_likely: somewhat likely
- numeric_pii_list:
- telephone numbers
- sensitive_pii_likely: unlikely
- sensitive_pii_list:
- no_pii_justification_class:
- no_pii_justification_text:
- validated: False
- source_category:
- category_type: collection
- category_web:
- category_media: scientific articles/journal
- validated: False
- media:
- category:
- text
- text_format:
- .XHTML
- .TXT
- .CSV
- .TEX
- other
- .JSON
- audiovisual_format:
- image_format:
- other
- .PDF
- database_format:
- .TAR
- .JSON
- .GZIP
- .TGZ
- text_is_transcribed: Yes - image
- instance_type: article
- instance_count: 1M

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