Abstract
Word sense disambiguation (WSD) means finding the correct sense of a word in a specific context. Ambiguity is an open problem of natural language processing and ontology. It is crucial to minimize the ambiguity for the applications: machine translation, information extraction, knowledge acquisition, question answering system and sentiment analysis. Many researchers have worked on automatic WSD for the English language, but the work carried out on Marathi language requires more attention. This paper focuses on word sense disambiguation using WordNet and the Lesk algorithm for Marathi Language. It uses the WordNet for Marathi, developed at IIT Mumbai, which is a very important lexical knowledge base for Marathi. The basic idea is to compare the context of the word in a sentence with the contexts constructed from the WordNet and choosing the correct sense. The algorithm has been implemented and tested on a set of sentences containing ambiguous words, and for majority of the sentences, the correct meaning has been inferred by the synset.
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Kharate, N.G., Patil, V.H. (2021). Word Sense Disambiguation for Marathi Language Using WordNet and the Lesk Approach. In: Patil, V.H., Dey, N., N. Mahalle, P., Shafi Pathan, M., Kimbahune, V.V. (eds) Proceeding of First Doctoral Symposium on Natural Computing Research. Lecture Notes in Networks and Systems, vol 169. Springer, Singapore. https://doi.org/10.1007/978-981-33-4073-2_5
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DOI: https://doi.org/10.1007/978-981-33-4073-2_5
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