TAC KBP Reference Knowledge Base
|Item Name:||TAC KBP Reference Knowledge Base|
|Author(s):||Heather Simpson, Joe Ellis, Robert Parker, Stephanie Strassel|
|LDC Catalog No.:||LDC2014T16|
|Release Date:||August 15, 2014|
|Data Source(s):||web collection|
|Application(s):||information extraction, knowledge base population, knowledge representation|
LDC User Agreement for Non-Members
|Online Documentation:||LDC2014T16 Documents|
|Licensing Instructions:||Subscription & Standard Members, and Non-Members|
|Citation:||Simpson, Heather, et al. TAC KBP Reference Knowledge Base LDC2014T16. Web Download. Philadelphia: Linguistic Data Consortium, 2014.|
TAC KBP Reference Knowledge Base was developed by the Linguistic Data Consortium (LDC) in support of the NIST-sponsored TAC-KBP evaluation series. It is a knowledge base built from English Wikipedia articles and their associated infoboxes and covers over 800,000 entities. LDC also released TAC KBP Spanish Cross-lingual Entity Linking - Comprehensive Training and Evaluation Data 2012-2014 (LDC2016T26.)
TAC (Text Analysis Conference) is a series of workshops organized by NIST (the National Institute of Standards and Technology) 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. TAC's KBP track (Knowledge Base Population) 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.
Consult the LDC TAC-KBP project page for further information about LDC's resource development for the TAC-KBP program.
The source data (Wikipedia infoboxes and articles) was taken from an October 2008 snapshot of Wikipedia.
TAC KBP Reference Knowledge Base contains a set of entities, each with a canonical name and title for the Wikipedia page, an entity type, an automatically parsed version of the data from the infobox in the entity's Wikipedia article, and a stripped version of the text of the Wiki article. Each entity is assigned one of four types: PER (person), ORG (organization), GPE (geo-political entity) and UKN (unknown).
All data files are presented as UTF-8 encoded XML.
Please view the following sample.
None at this time.