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A wide range of natural language problems can be viewed as disambiguating between a small set of alternatives based upon the string context surrounding the ambiguity site. In this paper we demonstrate that classification accuracy can be improved by invoking a more descriptive feature set than what is typically used. We present a technique that disambiguates by learning regular expressions describing the string contexts in which the ambiguity sites appear.