OLAC Record

Title:TAC KBP Chinese Regular Slot Filling - Comprehensive Training and Evaluation Data 2014
Access Rights:Licensing Instructions for Subscription & Standard Members, and Non-Members: http://www.ldc.upenn.edu/language-resources/data/obtaining
Bibliographic Citation:Ellis, Joe, Jeremy Getman, and Stephanie Strassel. TAC KBP Chinese Regular Slot Filling - Comprehensive Training and Evaluation Data 2014 LDC2019T08. Web Download. Philadelphia: Linguistic Data Consortium, 2019
Contributor:Ellis, Joe
Getman, Jeremy
Strassel, Stephanie
Date (W3CDTF):2019
Date Issued (W3CDTF):2019-05-15
Description:*Introduction* TAC KBP Chinese Regular Slot Filling - Comprehensive Training and Evaluation Data 2014 was developed by the Linguistic Data Consortium (LDC) and contains training and evaluation data produced in support of the TAC KBP Chinese Regular Slot Filling evaluation track conducted in 2014. Text Analysis Conference (TAC) is a series of workshops organized by the National Institute of Standards and Technology (NIST). TAC was developed to encourage research in natural language processing and related applications by providing a large test collection, common evaluation procedures, and a forum for researchers to share their results. Through its various evaluations, the Knowledge Base Population (KBP) track of TAC encourages the development of systems that can match entities mentioned in natural texts with those appearing in a knowledge base and extract novel information about entities from a document collection and add it to a new or existing knowledge base. The regular Chinese Slot Filling evaluation track involved mining information about entities from text. Slot Filling can be viewed as more traditional Information Extraction, or alternatively, as a Question Answering task, in which the questions are static but the targets change. In completing the task, participating systems and LDC annotators searched a corpus for information on certain attributes (slots) of person and organization entities and attempted to return all valid answers (slot fillers) in the source collection. For more information about Chinese Slot Filling, please refer to the 2014 track home page. *Data* This release contains all evaluation and training data developed in support of TAC KBP Chinese Regular Slot Filling. This includes queries, the 'manual runs' (human-produced responses to the queries), the final rounds of assessment results and the complete set of Chinese source documents. All text data is encoded as UTF-8. *Acknowledgement* This material is based on research sponsored by Air Force Research Laboratory and Defense Advance Research Projects Agency under agreement number FA8750-13-2-0045. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of Air Force Research Laboratory and Defense Advanced Research Projects Agency or the U.S. Government. *Samples* Please view the following samples. * Query * Manual Run * Assessment * Source Doc *Updates* None at this time.
Extent:Corpus size: 3947928 KB
ISBN: 1-58563-886-2
ISLRN: 228-911-774-662-0
DOI: 10.35111/thcb-cn24
Language:Mandarin Chinese
Language (ISO639):cmn
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/LDC2019T08
Rights Holder:Portions © 2000-2010 Agence France Presse, © 2009-2010 Central News Agency (Taiwan), © 2009-2010 China Military Online, © 2009-2010 Chinanews.com, © 2009-2010 Guangming Daily, © 2009 New York Times, © 2006-2010 Peoples Daily, © 2010 The Washington Post News Service with Bloomberg News, ©1991-2010 Xinhua News Agency, © 2003, 2005, 2007, 2009, 2011, 2019 Trustees of the University of Pennsylvania
Type (DCMI):Text
Type (OLAC):primary_text


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Citation: Ellis, Joe; Getman, Jeremy; Strassel, Stephanie. 2019. Linguistic Data Consortium.
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