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Coreference in Wikipedia: Main Concept Resolution

Abbas Ghaddar,P. Langlais

Published 2016 in Conference on Computational Natural Language Learning

ABSTRACT

Wikipedia is a resource of choice exploited in many NLP applications, yet we are not aware of recent attempts to adapt coreference resolution to this resource. In this work, we revisit a seldom studied task which consists in identifying in a Wikipedia article all the mentions of the main concept being described. We show that by exploiting the Wikipedia markup of a document, as well as links to external knowledge bases such as Freebase, we can acquire useful information on entities that helps to classify mentions as coreferent or not. We designed a classifier which drastically outperforms fair baselines built on top of state-of-the-art coreference resolution systems. We also measure the benefits of this classifier in a full coreference resolution pipeline applied to Wikipedia texts.

PUBLICATION RECORD

  • Publication year

    2016

  • Venue

    Conference on Computational Natural Language Learning

  • Publication date

    2016-08-01

  • Fields of study

    Linguistics, Computer Science

  • Identifiers
    DOI 10.18653/v1/K16-1023
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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