OLAC Record oai:www.ldc.upenn.edu:LDC2020T03

Metadata
Title:		TAC KBP English Event Argument - Training and Evaluation Data 2014-2015
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 English Event Argument - Training and Evaluation Data 2014-2015 LDC2020T03. Web Download. Philadelphia: Linguistic Data Consortium, 2020
Contributor:		Ellis, Joe
		Getman, Jeremy
		Strassel, Stephanie
Date (W3CDTF):		2020
Date Issued (W3CDTF):		2020-02-17
Description:		*Introduction* TAC KBP English Event Argument - Training and Evaluation Data 2014-2015 was developed by the Linguistic Data Consortium (LDC) and contains training and evaluation data produced in support of the 2014 TAC KBP English Event Argument Extraction Pilot and Evaluation tasks and the 2015 English Event Argument Extraction and Linking Training and Evaluation tasks. 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 Event Argument Extraction and Linking task required systems to extract event arguments (entities or attributes playing a role in an event) from unstructured text, indicate the role they play in an event, and link the arguments appearing in the same event to each other. Since the extracted information must be suitable as input to a knowledge base, systems constructed tuples indicating the event type, the role played by the entity in the event, and the most canonical mention of the entity from the source document. The event types and roles were drawn from an externally-specified ontology of 31 event types, which included financial transactions, communication events, and attacks. For more information about Event Argument Extraction and Linking, refer to the track home page on the NIST TAC website. *Data* Source data for the annotations in this corpus was English newswire and discussion forum text collected by LDC. Source and annotation files are presented as UTF-8 encoded tab delimited or plain text files. A summary of the data is below: Year Set Source Docs Manual Responses Assessments Event Hoppers 2014 pilot 60 0 32,054 n/a 2014 evaluation 528 5,947 57,599 n/a 2015 training 55* 0 0 599 2015 evaluation 500 5,207 45,391 1,608 *NOTE: the 2015 training source documents are a subset of the 2014 evaluation source corpus *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 * Assessment * Manual Run *Updates* None at this time.
Extent:		Corpus size: 52522 KB
Identifier:		LDC2020T03
		https://catalog.ldc.upenn.edu/LDC2020T03
		ISBN: 1-58563-918-4
		ISLRN: 505-557-960-269-8
		DOI: 10.35111/th16-k019
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/LDC2020T03
Rights Holder:		Portions © 2003, 2009, 2010 Agence France Presse, © 2009, 2010 The Associated Press, © 2010 Central News Agency (Taiwan), © 2009, 2010, 2013 New York Times, © 2010 The Washington Post News Service with Bloomberg News, © 2009, 2010 Xinhua News Agency, © 2003, 2009, 2010, 2013, 2014, 2015, 2016, 2020 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:LDC2020T03
DateStamp:		2021-01-01
GetRecord:		OAI-PMH request for simple DC format
Search Info
Citation:		Ellis, Joe; Getman, Jeremy; Strassel, Stephanie. 2020. Linguistic Data Consortium.
Terms:		area_Europe country_GB dcmi_Text iso639_eng olac_primary_text