OLAC Record oai:www.ldc.upenn.edu:LDC2017T17

Metadata
Title:		TAC KBP Chinese Cross-lingual Entity Linking - Comprehensive Training and Evaluation Data 2011-2014
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 Cross-lingual Entity Linking - Comprehensive Training and Evaluation Data 2011-2014 LDC2017T17. Web Download. Philadelphia: Linguistic Data Consortium, 2017
Contributor:		Ellis, Joe
		Getman, Jeremy
		Strassel, Stephanie
Date (W3CDTF):		2017
Date Issued (W3CDTF):		2017-11-17
Description:		*Introduction* TAC KBP Chinese Cross-lingual Entity Linking - Comprehensive Training and Evaluation Data 2011-2014 was developed by the Linguistic Data Consortium and contains training and evaluation data produced in support of the TAC KBP Chinese Cross-lingual Entity Linking tasks in 2011, 2012, 2013 and 2014. It includes queries and gold standard entity type information, Knowledge Base links, and equivalence class clusters for NIL entities along with the source documents for the queries, specifically, English and Chinese newswire, discussion forum and web data. The corresponding knowledge base is available as TAC KBP Reference Knowledge Base (LDC2014T16). 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. Chinese Cross-lingual Entity Linking was first conducted as part of the 2011 TAC KBP evaluations. The track was an extension of the monolingual English Entity Linking track (EL) whose goal is to measure systems' ability to determine whether an entity, specified by a query, has a matching node in a reference knowledge base (KB) and, if so, to create a link between the two. If there is no matching node for a query entity in the KB, EL systems are required to cluster the mention together with others referencing the same entity. More information about the TAC KBP Entity Linking task and other TAC KBP evaluations can be found on the NIST TAC website. *Data* All source documents were originally released as XML but have been converted to text files for this release. This change was made primarily because the documents were used as text files during data development but also because some fail XML parsing. *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: * Source Sample * Query Sample * Query Response Sample *Updates* None at this time.
Extent:		Corpus size: 141536 KB
Identifier:		LDC2017T17
		https://catalog.ldc.upenn.edu/LDC2017T17
		ISBN: 1-58563-823-4
		ISLRN: 464-261-620-634-2
		DOI: 10.35111/86hk-xg90
Language:		English
		Chinese
		Mandarin Chinese
Language (ISO639):		eng
		zho
		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/LDC2017T17
Rights Holder:		Portions © 2000-2010 Agence France Presse, © 2006-2010 The Associated Press, © 2007-2010 Central News Agency (Taiwan), © 2009-2010 China Military Online, © 2009-2010 Chinanews.com, © 2009-2010 Guangming Daily, © 2007-2009 Los Angeles Times - Washington Post News Service, Inc., © 1997, 2007-2010 New York Times, © 2006-2010 Peoples Daily, © 2010 The Washington Post Service with Bloomberg News, © 1991-2010 Xinhua News Agency, © 2003, 2005, 2007, 2009, 2011, 2016, 2017 Trustees of the University of Pennsylvania
Type (DCMI):		Text
Type (OLAC):		primary_text
OLAC Info
Archive:		The LDC Corpus Catalog
Description:		http://www.language-archives.org/archive/www.ldc.upenn.edu
GetRecord:		OAI-PMH request for OLAC format
GetRecord:		Pre-generated XML file
OAI Info
OaiIdentifier:		oai:www.ldc.upenn.edu:LDC2017T17
DateStamp:		2020-11-30
GetRecord:		OAI-PMH request for simple DC format
Search Info
Citation:		Ellis, Joe; Getman, Jeremy; Strassel, Stephanie. 2017. Linguistic Data Consortium.
Terms:		area_Asia area_Europe country_CN country_GB dcmi_Text iso639_cmn iso639_eng iso639_zho olac_primary_text