Abstract
Generally, verbs are polysemous in any language as their number is lesser than other categories including nouns. Mostly, the meaning of a verb is decided by the words with which it collocates. The contextual dependency of the verbs reduces the number of verbs in most of the languages or all languages. So by default, verbs become highly polysemous. In textual context or spoken context, the polysemy will not create problems as one can infer the correct meaning of a verb by the context of its occurrence. But in computational context, polysemy will be a problem. As machine does not have the knowledge which human brain has, it must be given knowledge by some means to interpret the meaning of a verb correctly. Polysemy is a problem in the interpretation of Malayalam verbs too. Resolving polysemy in Malayalam verb is needed for any NLP activity in Malayalam including machine translation. In machine translation, ambiguity due to polysemy is a crucial problem. This chapter explores all sorts of ambiguity focusing mainly on ambiguity due to polysemy in verbs. It will also explore resolving polysemy in Malayalam verbs using context similarity.
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Mohan Raj, S.N., Sachin Kumar, S., Rajendran, S., Soman, K.P. (2021). Resolving Polysemy in Malayalam Verbs Using Context Similarity. In: Kumar, R., Paiva, S. (eds) Applications in Ubiquitous Computing. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-35280-6_7
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