We developed a new lexical database named as ‘PolyWordNet’. The PolyWordNet organizes multiple senses of a polysemy word in such a way that each sense of the polysemy word is linked with its related words by dividing these related words into verbs, nouns, adverbs and adjectives. Each related word in the PolyWordNet is linked only with a single sense of a polysemy word except for the case of bridging related word. This is because such related word will lead to the multiple senses of a polysemy word during the sense disambiguation process if the related word is liked to more than one sense of the same polysemy word introducing the ambiguity in ambiguity as in the case of contextual overlap count WSD approaches that use the Princeton WordNet for sense disambiguation. The PolyWordNet resolves this problem which is produced due to the common information collected from Princeton WordNet. The results obtained from the experiments show exceptionally high accuracy (96.11%) of our Word Sense Disambiguation algorithm that uses our lexical database PolyWordNet. This accuracy is significantly higher than that of the accuracy (58.33%) of the other contextual overlap count Word Sense Disambiguation method that used the Princeton WordNet for sense disambiguation.