Word sense disambiguation in Nepali language

This paper presents a modified Adapted Lesk algorithm for word sense disambiguation in Nepali language. We included the synset, gloss, example and hypernym of the context words to form the final collection of context words. The context window contains all the words from the whole sentence except articles, prepositions and pronouns. The collection of words for each sense of a target word is also formed by including their synset, gloss, example and hypernym. Each word in the collection of context words is compared with every word in the collection of words for each sense of a target word to count the overlaps. Moreover, the numbers of examples for each word in our sample Nepali WordNet have been increased to four in average. The experiments performed on 348 words including 59 polysemy words shows the accuracy level of our algorithm to be 88.05%.