TAC KBP Evaluation Source Corpora 2016-2017
|Item Name:||TAC KBP Evaluation Source Corpora 2016-2017|
|Author(s):||Joe Ellis, Jeremy Getman, Stephanie Strassel|
|LDC Catalog No.:||LDC2019T12|
|Release Date:||August 15, 2019|
|Data Source(s):||discussion forum, newswire|
|Application(s):||information extraction, knowledge base population, knowledge representation|
|Language(s):||English, Mandarin Chinese, Spanish|
|Language ID(s):||eng, cmn, spa|
LDC User Agreement for Non-Members
|Online Documentation:||LDC2019T12 Documents|
|Licensing Instructions:||Subscription & Standard Members, and Non-Members|
|Citation:||Ellis, Joe, Jeremy Getman, and Stephanie Strassel. TAC KBP Evaluation Source Corpora 2016-2017 LDC2019T12. Web Download. Philadelphia: Linguistic Data Consortium, 2019.|
TAC KBP Evaluation Source Corpora 2016-2017 was developed by the Linguistic Data Consortium (LDC) and contains the 180,003 Chinese, English and Spanish source documents used in support of all TAC KBP evaluation tracks conducted in 2016 and 2017.
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 source data consists of Chinese, English and Spanish discussion forum and newswire text collected by LDC. Documents are released as UTF-8 encoded XML with corresponding DTDs. Also provided are a series of lists and tables to aid in the recreation of specific test sets. See the included documentation for more information.
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.
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