  Word ambiguity removal is a task of removing ambiguity from a word, i.e.
correct sense of word is identified from ambiguous sentences. This paper
describes a model that uses Part of Speech tagger and three categories for word
sense disambiguation (WSD). Human Computer Interaction is very needful to
improve interactions between users and computers. For this, the Supervised and
Unsupervised methods are combined. The WSD algorithm is used to find the
efficient and accurate sense of a word based on domain information. The
accuracy of this work is evaluated with the aim of finding best suitable domain
of word.
