Latent variable models of selectional preference

  • Authors:
  • Diarmuid Ó. Séaghdha

  • Affiliations:
  • University of Cambridge, United Kingdom

  • Venue:
  • ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
  • Year:
  • 2010

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Abstract

This paper describes the application of so-called topic models to selectional preference induction. Three models related to Latent Dirichlet Allocation, a proven method for modelling document-word cooccurrences, are presented and evaluated on datasets of human plausibility judgements. Compared to previously proposed techniques, these models perform very competitively, especially for infrequent predicate-argument combinations where they exceed the quality of Web-scale predictions while using relatively little data.