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TAC 2017
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Text Analysis Conference

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 hosts evaluations in two areas of research:

  1. Knowledge Base Population (KBP)
    The goal of Knowledge Base Population is to promote research in automated systems that discover information about entities as found in a large corpus and incorporate this information into a knowledge base.

  2. 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.

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Last updated: Tuesday, 18-Apr-2017 10:04:00 MDT
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