A Class-based approach to learn appropriate selectional restrictions from a parsed corpus

Abstract

We present a methodology to extract Selectional Restrictions at a variable level of abstraction from phrasally analyzed corpora. The method relays in the use of a wide-coverage noun taxonomy and a statistical measure of the co-occurrence of linguistic items. Some experimental results about the performance of the method are provided

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