Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Summary

There has been a growing recognition of the importance of community-wide evaluations for research in information technologies. The Text Analysis Conference is a series of workshops that provides the infrastructure for large-scale evaluation of Natural Language Processing technology.

Description

Mission

TAC's mission is to support research within the Natural Language Processing community by providing the infrastructure necessary for large-scale evaluation of NLP methodologies. TAC's primary purpose is not competitive benchmarking; the emphasis is on advancing the state of the art through evaluation results. In particular, the TAC workshop series has the following goals:

  • to promote research in NLP based on large common test collections;
  • to improve evaluation methodologies and measures for NLP;
  • to build a series of test collections that evolve to anticipate the evaluation needs of modern NLP systems;
  • to increase communication among industry, academia, and government by creating an open forum for the exchange of research ideas;
  • to speed the transfer of technology from research labs into commercial products by demonstrating substantial improvements in NLP methodologies on real-world problems.

TAC Cycle

A TAC cycle consists of a set tracks, areas of focus in which particular NLP tasks are defined. The tracks serve several purposes. First, tracks act as incubators to experiment with new research areas; the first running of a track often defines what the problem really is, and a track creates the necessary infrastructure (test collections, evaluation methodology, etc.) to support research on its tasks. The tracks also demonstrate the robustness of core NLP technology in that the same techniques are frequently appropriate for a variety of tasks. Finally, the tracks make TAC attractive to a broader community by providing tasks that match the research interests of more groups. The TAC advisory committee selects the set of tracks that will be run in a given year of TAC based on track proposals.

General Information

Comments to: tac-web [at] nist.gov (tac-web[at]nist[dot]gov)

Created February 25, 2021, Updated March 2, 2021