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This paper investigates the effects of stemming, stop word removal and size of context window on Hindi word sense disambiguation. The evaluation has been made on a manually created sense tagged corpus consisting of Hindi words (nouns). The sense definition has been obtained from Hindi WordNet, which is an important lexical resource for Hindi language developed at IIT Bombay. The maximum observed precision of 54.81% on 1248 test instances corresponds to the case when both stemming and stop words elimination has been performed. The % improvement in precision and recall is 9.24% and 12.68% over the baseline performance.