Textual Entailment Resource Pool

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Textual entailment systems rely on many different types of NLP resources, including term banks, paraphrase lists, parsers, named-entity recognizers, etc. With so many resources being continuously released and improved, it can be difficult to know which particular resource to use when developing a system.

In response, the Recognizing Textual Entailment (RTE) shared task community initiated a new activity for building this Textual Entailment Resource Pool. RTE participants and any other member of the NLP community are encouraged to contribute to the pool.

In an effort to determine the relative impact of the resources, RTE participants are strongly encouraged to report, whenever possible, the contribution to the overall performance of each utilized resource. Formal qualitative and quantitative results should be included in a separate section of the system report as well as posted on the talk pages of this Textual Entailment Resource Pool.

Adding a new resource is very easy. See how to use existing templates to do this in Help:Using Templates.

Complete RTE Systems

  • VENSES (from Ca' Foscari University of Venice, Italy)
  • Nutcracker (available for download)
  • Entailment Demo (from the University of Illinois at Urbana-Champaign)

RTE data sets

Knowledge Resources



Role Labelling

Entity Recognition Tools

Corpus Readers

  • NLTK provides a corpus reader for the data from RTE Challenges 1, 2, and 3 - see the Corpus Readers Guide for more information.