OLAC Record
oai:www.ldc.upenn.edu:LDC2018T24

Metadata
Title:TAC Relation Extraction Dataset
Access Rights:Licensing Instructions for Subscription & Standard Members, and Non-Members: http://www.ldc.upenn.edu/language-resources/data/obtaining
Bibliographic Citation:Zhong, Victor, et al. TAC Relation Extraction Dataset LDC2018T24. Web Download. Philadelphia: Linguistic Data Consortium, 2018
Contributor:Zhong, Victor
Zhang, Yuhao
Chen, Danqi
Angeli, Gabor
Manning, Christopher
Date (W3CDTF):2018
Date Issued (W3CDTF):2018-12-15
Description:*Introduction* TAC Relation Extraction Dataset (TACRED) was developed by The Stanford NLP Group and is a large-scale relation extraction dataset with 106,264 examples built over English newswire and web text used in the NIST TAC KBP English slot filling evaluations during the period 2009-2014. The annotations were derived from TAC KBP relation types (see the guidelines), from human annotations developed by the Linguistic Data Consortium and from crowdsourcing using Mechanical Turk. *Data* In each year of the slot filling evaluation, 100 entities (people or organizations) were given as queries (i.e., subjects), for which participating systems should find associated relations and object entities. All sentences judged in the TAC KBP evaluation and a sampling of other sentences that contain the query entities in the evaluation corpus form TACRED. Each sentence was crowd-annotated using Mechanical Turk, where each turk annotator was asked to annotate the subject and object entity spans and the corresponding relation. Data is presented in both CoNLL and JSON format, both encoded in UTF-8. Scoring tools and gold relation labels are also included. Source corpora used for this dataset were TAC KBP Comprehensive English Source Corpora 2009-2014 (LDC2018T03) and TAC KBP English Regular Slot Filling - Comprehensive Training and Evaluation Data 2009-2014 (LDC2018T22). For detailed information about the dataset and benchmark results, please refer to the TACRED paper. *Samples* Please view this CoNLL sample and JSON sample. *Updates* None at this time.
Extent:Corpus size: 295320 KB
Identifier:LDC2018T24
https://catalog.ldc.upenn.edu/LDC2018T24
ISBN: 1-58563-869-2
ISLRN: 927-859-759-915-2
DOI: 10.35111/m0kp-4w25
Language:English
Language (ISO639):eng
License:LDC User Agreement for Non-Members: https://catalog.ldc.upenn.edu/license/ldc-non-members-agreement.pdf
Medium:Distribution: Web Download
Publisher:Linguistic Data Consortium
Publisher (URI):https://www.ldc.upenn.edu
Relation (URI):https://catalog.ldc.upenn.edu/docs/LDC2018T24
Rights Holder:Portions © 1994-1997, 2001-2010 Agence France Presse, © 2005 Aljazeera, © 1996-1997 American Broadcasting Corporation, © 1994-2010 The Associated Press, © 1994-1997 Cable News Network, LP, LLLP, © 1997-1999, 2001, 2003-2010 Central News Agency (Taiwan), © 2005 Dubai TV, © 2005-2006 National Broadcasting Company, Inc., © 1996-1997 National Cable Satellite Corporation, © 1994-1998, 2003-2009 Los Angeles Times - Washington Post News Service, Inc., © 1994-2010 New York Times, © 1996-1997 Public Radio International, © 1994-1995 Reuters America, Inc., © 1996 The University of California, USC Radio and Marketplace, © 2010 The Washington Post Service with Bloomberg News, © 1995-2010 Xinhua News Agency, © 2018 The Board of Trustees of the Leland Stanford Junior University, © 1996-1998, 2007, 2008, 2009, 2011, 2014, 2018 Trustees of the University of Pennsylvania
Type (DCMI):Text
Type (OLAC):primary_text

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OaiIdentifier:  oai:www.ldc.upenn.edu:LDC2018T24
DateStamp:  2020-11-30
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Citation: Zhong, Victor; Zhang, Yuhao; Chen, Danqi; Angeli, Gabor; Manning, Christopher. 2018. Linguistic Data Consortium.
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