ACQUISITION OF SEMANTIC LEXICONS

This paper addresses the problem oflarge-scale acquisition of computational-semantic lexicons from machine-readable resources. We describe semantic
filters designed to reduce the number ofincorrect assignments (i.e., improve
precision) made by a purely syntactic technique. We demonstrate that it is
possible to use these filters to build broad-coverage lexicons with minimal
effort, at a depth of knowledge that lies at the syntax-semantics interface.
We report on our results of disambiguating the verbs in the semantic filters
by adding WordNet sense annotations. We then show the results of our
classification on unknown words and we evaluate these results.