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 Word Net-extracted features, based on the hyperonyms of context nouns. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3878 LNCS, pp. 192–195). https://doi.org/10.1007/11671299_21
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