Clustering polysemic subcategorization frame distributions semantically

  • Authors:
  • Anna Korhonen;Yuval Krymolowski;Zvika Marx

  • Affiliations:
  • University of Cambridge, Cambridge, UK;University of Edinburgh, Edinburgh, Scotland, UK;The Hebrew University, Jerusalem, Israel

  • Venue:
  • ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
  • Year:
  • 2003

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Abstract

Previous research has demonstrated the utility of clustering in inducing semantic verb classes from undisambiguated corpus data. We describe a new approach which involves clustering subcategorization frame (SCF) distributions using the Information Bottleneck and nearest neighbour methods. In contrast to previous work, we particularly focus on clustering polysemic verbs. A novel evaluation scheme is proposed which accounts for the effect of polysemy on the clusters, offering us a good insight into the potential and limitations of semantically classifying undisambiguated SCF data.