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TAC 2019
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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 2019 hosts evaluations in three tracks:

  1. Entity Discovery and Linking (EDL)
    The goal of the EDL track is to extract mentions of pre-defined entity types from any language, and link (disambiguate and ground) them to the entities in an English knowledge base (KB).

  2. Streaming Multimedia Knowledge Base Population (SM-KBP)
    The goal of the SM-KBP track is to develop and evaluate technologies that extract structured Knowledge Elements (KEs) from a variety of unstructured sources in order to generate explicit alternative interpretations of events, situations, and trends in noisy, conflicting, and potentially deceptive information environments.

  3. Drug-Drug Interaction Extraction from Drug Labels (DDI)
    The purpose of the DDI track is to test various natural language processing (NLP) approaches for their information extraction (IE) performance on drug-drug interactions in Structured Product Labeling (SPL) documents.

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Last updated: Wednesday, 29-May-2019 08:12:23 EDT
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