W e present a method for automatically identifying verbal participation in diathesis alternations. Automatically acquired subcategorization frames are compared to a hand-crafted classification for selecting candidate verbs. The m i n i m u m description length principle is then used to produce a model and cost for storing the head noun instances from a training corpus at the relevant argument slots.