Verb sense disambiguation using support vector machines: impact of wordnet-extracted features

  • Authors:
  • Davide Buscaldi;Paolo Rosso;Ferran Pla;Encarna Segarra;Emilio Sanchis Arnal

  • Affiliations:
  • Dpto. Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Valencia, Spain;Dpto. Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Valencia, Spain;Dpto. Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Valencia, Spain;Dpto. Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Valencia, Spain;Dpto. Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Valencia, Spain

  • Venue:
  • CICLing'06 Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing
  • Year:
  • 2006

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Abstract

The disambiguation of verbs is usually considered to be more difficult with respect to other part-of-speech categories. This is due both to the high polysemy of verbs compared with the other categories, and to the lack of lexical resources providing relations between verbs and nouns. One of such resources is WordNet, which provides plenty of information and relationships for nouns, whereas it is less comprehensive with respect to verbs. In this paper we focus on the disambiguation of verbs by means of Support Vector Machines and the use of WordNet-extracted features, based on the hyperonyms of context nouns.