A Comparison of Selectional Preference Models for Automatic Verb Classification

We present a comparison of different selec-tional preference models and evaluate them on an automatic verb classification task in German. We find that all the models we compare are effective for verb clustering; the best-performing model uses syntactic information to induce nouns classes from unlabelled data in an unsupervised man-ner. A very simple model based on lexical preferences is also found to perform well.