Automatically Generated Noun Lexicons for Event Extraction

  • Béatrice Arnulphy
  • Xavier Tannier
  • Anne Vilnat
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7182)

Abstract

In this paper, we propose a method for creating automatically weighted lexicons of event names. Almost all names of events are ambiguous in context (i.e., they can be interpreted in an eventive or non-eventive reading). Therefore, weights representing the relative “eventiveness” of a noun can help for disambiguating event detection in texts.

We applied our method on both French and English corpora. Our method has been applied to both French and English corpora. We performed an evaluation based upon a machine-learning approach that shows that using weighted lexicons can be a good way to improve event extraction. We also propose a study concerning the necessary size of corpus to be used for creating a valuable lexicon.

Keywords

Noun Phrase Extraction Rule Event Extraction Eventive Reading Semantic Role Labelling 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Béatrice Arnulphy
    • 1
  • Xavier Tannier
    • 1
  • Anne Vilnat
    • 1
  1. 1.LIMSI-CNRS, Univ. Paris-SudOrsayFrance

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