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The aim in supervised disambiguation is to build a classifier which correctly classifies new cases based on their context of use.
The basic inference in thesaurus-based disambiguation is that semantic categories of the words in a context determine the semantic category of that context as a whole.
Disambiguation is done by computing the semantic similarity between words and applying the heuristic rules based on this similarity.