A Supervised Word Sense Disambiguation Method Using Ontology and Context Knowledge

Abstract

Word Sense Disambiguation is one of the basic tasks in Natural language processing. It is the method of selecting the correct sense of the word in the given context. It is applied whenever a semantic understanding of text is needed. In order to disambiguate a word, two resources are necessary: a context in which the word has been used, and some kind of knowledge related to the word. This paper presents a method for word sense disambiguation task using a tree-matching approach. The method requires a context knowledge base containing the corpus of sentences. This paper also gives some preliminary results when a corpus containing the ambiguous words is tested on this system.

Keywords: Natural Language Understanding, Word Sense Disambiguation; Tree-matching; dependent-word matching