TAC 2017 Tracks
KBP Tracks
ADR Track
Call for Participation
Track Registration
Reporting Guidelines
TAC 2017 Workshop
|
|
Text Analysis Conference (TAC) 2017
Evaluation: February-November, 2017
Workshop: November 13-14, 2017
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 2017 has six tracks in two major areas:
- Adverse
Drug Reaction Extraction from Drug Labels (ADR)
The
purpose of this track is to test various natural language
approaches for their information extraction performance on adverse
drug reactions (ADR). Participants will be provided with
mention-, relation-, and document-level annotations in order to
extract structured ADR information from the Food and Drug
Administration's (FDA) official pharmaceutical knowledge
base.
Track coordinator: Kirk Roberts (Kirk.Roberts@uth.tmc.edu)
Home page: https://bionlp.nlm.nih.gov/tac2017adversereactions/
Mailing list: tac-adr@googlegroups.com
- Knowledge Base Population
(KBP)
KBP tracks develop technologies for building and
populating knowledge bases (KBs) from unstructured text. In
addition to the main end-to-end KB construction task in the Cold
Start KB track, component tasks are offered in 4 tracks that
focus on specific components of the KB:
- Cold Start KB (CSKB): The Cold Start KB track builds a
knowledge base from scratch using a given document collection and
knowledge base schema. The KB schema includes entities, events, and
relations involving entities and events, including entity attributes
(aka slots), event arguments, and sentiment between entities.
- Entity Discovery and Linking (EDL): The Entity Discovery
and Linking track aims to extract entity mentions from a source
collection of textual documents and link them to a reference KB; an
EDL system is also required to cluster mentions for those entities
that don't have corresponding KB entries.
- Slot Filling (SF): The Slot Filling task is to search a
document collection to fill in values for predefined slots
(attributes) for a given entity.
- Event: The goal of the Event track is to extract
information about events such that the information would be suitable
as input to a knowledge base. The track includes Event Nugget
(EN) tasks to detect and link events, and Event Argument
(EAL) tasks to extract event arguments and link arguments that
belong to the same event.
- Belief and Sentiment (BeSt): The Belief and Sentiment track
detects belief and sentiment of an entity toward another entity,
relation, or event.
Home page: tac.nist.gov/2017/KBP/
Mailing list: tac-kbp@nist.gov
TAC 2017 Schedule |
February 20 | Track registration opens |
June 15 | Deadline for registration for track participation |
June - October | Track evaluation windows (varies by track) |
By mid October | Release of individual evaluated results to participants (most tracks) |
October 15 | Deadline for short system descriptions |
October 15 | Deadline for workshop presentation proposals |
October 20 | Notification of acceptance of presentation proposals |
November 1 | Deadline for system reports (workshop notebook version) |
November 13-14 | TAC 2017 workshop in Gaithersburg, Maryland, USA |
February 28, 2018 | Deadline for system reports (final proceedings version) |
|