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 2018 hosts evaluations in four tracks:
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).
- 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.
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.
- Systematic Review Information Extraction (SRIE)
The purpose of the SRIE track is to develop and evaluate Information Extraction (IE) approaches that can assist in the systematic reviews of environmental agents. This track will focus on IE of study design factors found in the Methods and Materials section of published studies of experimental animals exposed to environmental chemicals.
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Last updated: Monday, 14-May-2018 09:49:19 MDT
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