Word sense disambiguation using fuzzy semantic relations

The natural languages are an integral part of the day to day communications. But the fact remains that they are full of ambiguity. Humans can differentiate between the “pen” of a dog and the “pen” used by a student but the machine/computer systems cannot resolve this ambiguity on their own. Hence Word Sense Disambiguation remains one of the most common real life problems that are related to natural language processing which needs to be resolved efficiently. In this paper we have explained an extended version of WordNet by fuzzyfying the semantic relationships that were previously defined in it. We have explained these fuzzy semantic relations with examples and discussed the method to disambiguate a word effectively and efficiently using these fuzzy semantic relations, which will in turn be useful in many natural language processing applications.