
About TAC
TAC KBP 2012
WEAS 2012
Past Tracks
Past Data
Publications
Contact

|
|
Text Analysis Conference
Task Evaluations: February - October 2012
Workshop: November 5-6, 2012
National Institute of Standards and Technology
Gaithersburg, Maryland USA
Conducted by:
U.S. National Institute of Standards and Technology (NIST)
With support from:
U.S. Department of Defense
The Text Analysis Conference (TAC) is a series of evaluation workshops
organized to encourage research in Natural Language Processing and
related applications, by providing a large test collection, common
evaluation procedures, and a forum for organizations to share their
results. TAC comprises sets of tasks known as "tracks," each of which
focuses on a particular subproblem of NLP. TAC tracks focus on
end-user tasks, but also include component evaluations situated within
the context of end-user tasks.
TAC 2012 focuses on Knowledge Base Population (KBP). The goal of Knowledge Base Population
is to promote research in automated systems that discover information
about named entities as found in a large corpus and incorporate this
information into a knowledge base. TAC 2012 fields tasks in three areas,
all aimed at improving the ability to automatically populate knowledge
bases from text:
- Entity-Linking: Given a name (of a Person, Organization, or
Geopolitical Entity) and a document containing that name,
determine the KB node for the named entity, adding a new node for
the entity if it is not already in the KB. The reference KB is derived from English Wikipedia, while source documents come from a variety of languages, including:
- Slot-Filling: Given a named entity and a pre-defined set of
attributes ("slots") for the entity type, augment a KB node for
that entity by extracting all new learnable slot values for the
entity as found in a large corpus of documents. The reference KB is derived from English Wikipedia, while source documents come from a variety of languages, including:
A diagnostic task, Slot Filler Validation, will be to determine whether a candidate filler in a document is a correct slot-filler for a given entity.
- Cold Start Knowledge Base Population: Given a KB schema with an empty knowledge base, build the KB from scratch by mining a large text collection.
To promote research in populating probabilistic knowledge bases, systems may augment each assertion they make with a confidence score.
Additionally, TAC continues support for tracks in Summarization and Recognizing Textual Entailment (RTE). The next Summarization and RTE evaluations are planned for early 2013. An interim Workshop on Evaluation Metrics and System Comparison for Automatic Summarization (WEAS) will be held at NAACL-HLT on June 8, 2012, in Montreal, Canada.
|