Abstract
In this paper, we focus on a definition of polysemy in terms of distributional behaviour of words in monolingual texts and propose a method for disambiguating word-senses in sentences containing occurrences of polysemous verbs. We first discuss existing work on some corpus-related approaches on word-sense disambiguation and show the significance of our approach by comparing it with other related work. Then we give a definition of polysemy from the viewpoint of clustering and propose a clustering method which automatically recognises polysemous words. Finally the information extracted by the clustering method is shown to contribute to disambiguating word-senses in sentences containing occurrences of polysemous verbs. We report the results of two experiments. The first experiment, Disambiguation Experiment, is conducted in order to see how the extracted polysemy information can be used to disambiguate word-senses in actual texts. The second, Comparative Experiment, is conducted in order to see how our disambiguation technique is effective than other related approach, Niwa's technique. The results of experiments demonstrate the applicability of our proposed method.
