This paper proposes that the set of frequencies that the human language processor keeps track of are those that are useful to it in learning. In a computational experimental setting, we investigate four liguistically motivated features which distinguish subclasses of intransitive verbs, and suggest that those features that are the most useful to automatically classify verbs into lexical semantic classes are related to mechanisms used in adult processing to resolve structural ambiguity.
