  Selectional preference learning methods have usually focused on word-to-class
relations, e.g., a verb selects as its subject a given nominal class. This
papers extends previous statistical models to class-to-class preferences, and
presents a model that learns selectional preferences for classes of verbs. The
motivation is twofold: different senses of a verb may have different
preferences, and some classes of verbs can share preferences. The model is
tested on a word sense disambiguation task which uses subject-verb and
object-verb relationships extracted from a small sense-disambiguated corpus.
