TAC KBP Spanish Cross-lingual Entity Linking - Comprehensive Training and Evaluation Data 2012-2014

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Ellis, Joe; Getman, Jeremy; Strassel, Stephanie, 2016, "TAC KBP Spanish Cross-lingual Entity Linking - Comprehensive Training and Evaluation Data 2012-2014", https://hdl.handle.net/11272.1/AB2/HL83QO, Abacus Data Network, V1

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Description	Introduction TAC KBP Spanish Cross-Lingual Entity Linking - Comprehensive Training and Evaluation Data 2012-2014 was developed by the Linguistic Data Consortium (LDC) and contains training and evaluation data produced in support of the TAC KBP Spanish Cross-lingual Entity Linking tasks in 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 Spanish 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. Spanish cross-lingual entity linking was first conducted as part of the 2012 TAC KBP evaluations. The track was an extension of the monolingual English Entity Linking track (EL) whose goal was to measure systems’ ability to determine whether an entity, specified by a query, had a matching node in a reference knowledge base (KB) and, if so, to create a link between the two. If there was no matching node for a query entity in the KB, EL systems were 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.
Subject	Other
Keyword	Linguistics

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Citation Metadata

Dataset Persistent ID	hdl:11272.1/AB2/HL83QO
Publication Date	2016-12-15
Citation Date
Title	TAC KBP Spanish Cross-lingual Entity Linking - Comprehensive Training and Evaluation Data 2012-2014
Other ID	Linguistic Data Consortium: LDC2016T26 ISBN: 1-58563-780-7 ISLRN: 546-386-811-027-3
Author	Ellis, Joe Getman, Jeremy Strassel, Stephanie
Contact	Use email button above to contact. Abacus support
Description	Introduction TAC KBP Spanish Cross-Lingual Entity Linking - Comprehensive Training and Evaluation Data 2012-2014 was developed by the Linguistic Data Consortium (LDC) and contains training and evaluation data produced in support of the TAC KBP Spanish Cross-lingual Entity Linking tasks in 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 Spanish 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. Spanish cross-lingual entity linking was first conducted as part of the 2012 TAC KBP evaluations. The track was an extension of the monolingual English Entity Linking track (EL) whose goal was to measure systems’ ability to determine whether an entity, specified by a query, had a matching node in a reference knowledge base (KB) and, if so, to create a link between the two. If there was no matching node for a query entity in the KB, EL systems were 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.
Subject	Other
Keyword	Linguistics (ACV)
Producer	Linguistic Data Consortium (University of Pennsylvania) (LDC) https://www.ldc.upenn.edu/
Production Date	2016-12-15
Production Place	Philadelphia
Grant Information	Air Force Research Laboratory and Defense Advance Research Projects Agency: FA8750-13-2-0045
Distributor	Linguistic Data Consortium (University of Pennsylvania) (LDC) https://www.ldc.upenn.edu/
Deposit Date	2017-01-12
Time Period Covered	Start: 2011 ; End: 2011
Date of Collection	Start: 2011 ; End: 2011
Kind of Data	Linguistic data
Series	LDC: Linguistic Data Consortium
Data Sources	Newswire, discussion forum, web collection

Geospatial Metadata

Geographic Coverage	China France Taiwan, Province of China United States

Social Science and Humanities Metadata

Study Level Error Notes

DCMI type: TextProject: TACApplication: Knowledge base populationApplication: Entity extractionApplication: Information extractionApplication: Knowledge representationLanguage: Spanish, EnglishLanguage ID: spa, engMisc: 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. Previous handle https://hdl.handle.net/11272/NMNR4 has been deprecated

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