Automatic Verb Classification Using Distributions of Grammatical Features

We apply machine learning techniques to classify automatically a set of verbs into lexical semantic classes, based on distributional approximations of diathe-ses, extracted from a very large annotated corpus. Distributions of four grammatical features are sufficient to reduce error rate by 50% over chance. We conclude that corpus data is a usable repository of verb class information, and that corpus-driven extraction of grammatical features is a promising methodology for automatic lexical acquisition.