Word Sense Disambiguation: A review

Natural Language Processing

Word Sense Disambiguation (WSD) is the task of removing ambiguity in different senses of words. It is a core research field in computational linguistics dealing with the automatic assignment of senses to words occurring in a given context. Humans are inherently good at WSD and distinguish senses used in words through spoken language. Computers on the other hand have difficulties identifying correct senses of words. Various advancements have been made in the task of disambiguation using mainly four approaches: Knowledge based, Supervised, Semi-Supervised, and Unsupervised. Better understanding of the human language will help computer’s performance in various applications such as search engines, assistant software, and voice command interpretation. The objective of this work is to increase the accuracy of existing system to improve communication between computers and humans. Our hypothetical model uses supervised approach to create database using WordNet dictionary upon which we use a two-level algorithm. First level uses our improvised system, whereas second level uses Lesk algorithm together providing accurate sense detection

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