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A word having multiple senses in a text introduces the lexical semantic taskto find out which particular sense is appropriate for the given context. Onesuch task is Word sense disambiguation which refers to the identification ofthe most appropriate meaning of the polysemous word in a given context usingcomputational algorithms. The language processing research in Hindi, theofficial language of India, and other Indian languages is restricted byunavailability of the standard corpus. For Hindi word sense disambiguationalso, the large corpus is not available. In this work, we prepared the textcontaining new senses of certain words leading to the enrichment of thesense-tagged Hindi corpus of sixty polysemous words. Furthermore, we analyzedtwo novel lexical associations for Hindi word sense disambiguation based on thecontextual features of the polysemous word. The evaluation of these methods iscarried out over learning algorithms and favorable results are achieved.

Context based Analysis of Lexical Semantics for Hindi Language