In many NLP applications such as machine translation, content analysis, and information retrieval, Word Sense Disambiguation (WSD) is an important technique. Word sense disambiguation is the essence of communication in a natural language. WSD process is useful for automatically identifying the correct meaning of an ambiguous word in the sentence or the query when it has multiple meanings. So, this system proposes as the Tanimoto coefficient based word sense disambiguation system to increase the precision of the NLP application. This system provides additional semantic as conceptually related words with the help of glosses to each keyword in the inputted sentence by disambiguating their meanings. This system uses the WordNet as the lexical resource that encodes concepts of each term.