A Semi-Complete Disambiguation Algorithm for Open Text

Rada Mihalcea, Southern Methodist University

In this paper, we present an iterative algorithm for Word Sense Disambiguation. It combines two sources of information: WordNet and a semantic tagged corpus, for the purpose of identifying the correct sense of the words in a given text. It differs from other standard approaches in that the disambiguation process is performed in an iterative manner: starting from free text, a set of disambiguated words is built, using various methods; new words are sense tagged based on their relation to the already disambiguated words, and then added to the set. This iterative process allows us to identify, in the original text, a set of words which can be disambiguated with high precision; 55% of the verbs and nouns are disambiguated with an accuracy of 92%.

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