Verb Sense Disambiguation Using Support Vector Machines: Impact of WordNet-Extracted Features (original) (raw)

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.

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References

  1. Girju, R., Roth, D., Sammons, M.: Token-level Disambiguation of VerbNet classes. In: Proc. of the Interdisciplinary Workshop on Verb Features and Verb Classes, Saarbruckem, Germany (2005)
    Google Scholar
  2. Joachims, T.: Making large-scale SVM Learning Practical. In: Advances in Kernel Methods. MIT-press, Cambridge (1999)
    Google Scholar
  3. Lee, Y.K., Ng, H.T.: Supervised Word Sense Disambiguation with Support Vector Machines and Multiple Knowledge Sources. In: Proc. of the SENSEVAL-3 workshop, Barcelona, Spain (2004)
    Google Scholar
  4. Mihalcea, R., Moldovan, D.I.: A Method for Word Sense Disambiguation of Unrestricted Text. In: Proc. of the ACL 1999 Conference, Maryland, NY, U.S.A (1999)
    Google Scholar
  5. Miller, G.: WordNet: a lexical database for english. CACM 38(11), 39–41 (1995)
    Google Scholar
  6. Vapnik, V.N.: The Nature of Statistical Learning Theory. Springer, New York (1995)
    MATH Google Scholar

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Authors and Affiliations

  1. Dpto. Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Valencia, Spain
    Davide Buscaldi, Paolo Rosso, Ferran Pla, Encarna Segarra & Emilio Sanchis Arnal

Authors

  1. Davide Buscaldi
  2. Paolo Rosso
  3. Ferran Pla
  4. Encarna Segarra
  5. Emilio Sanchis Arnal

Editor information

Editors and Affiliations

  1. National Polytechnic Institute, Center for Computing Research, 07738, Mexico City, México
    Alexander Gelbukh

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© 2006 Springer-Verlag Berlin Heidelberg

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Buscaldi, D., Rosso, P., Pla, F., Segarra, E., Arnal, E.S. (2006). Verb Sense Disambiguation Using Support Vector Machines: Impact of WordNet-Extracted Features. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2006. Lecture Notes in Computer Science, vol 3878. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11671299\_21

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