Word Sense Disambiguation Using PolyWordNet

We developed a novel word sense disambiguation algorithm that uses the semantic relations of lexical database PolyWordNet. The PolyWordNet is a lexical database that 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. Our algorithm does not count the overlap of words between the glosses of context and sense bags as in contextual overlap count knowledge-based word sense disambiguation algorithms. Instead, our algorithm searches the paths or links of context words with the senses of the target word. It keeps the track of each path or link that connects a context word and a sense of the target word. If the paths thus obtained connect only one sense of the target word, the algorithm output the linked sense as the correct sense of the target word for the given context. If there are paths that link more than one senses, then the algorithm counts the number of paths or links or connections for each linked sense. Then, the sense for which the number of connection paths is maximum is selected as a correct sense. The accuracy (96.11%) of our algorithm using PolyWordNet is found 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.