Learning to Distinguish PP Arguments from Adjuncts

Words differ in the subcategorisation frames in which they occur, and there is a strong correlation between the semantic arguments of a given word and its subcategorisation frame, so that all its arguments should be included in its subcategorisation frame. One problem is posed by the ambiguity between locative prepositional phrases as arguments of a verb or adjuncts. As the semantics for the verb is the same in both cases, it is difficult to differentiate them, and to learn the appropriate subcategorisation frame. We propose an approach that uses semantically motivated preposition selection and frequency information to determine if a locative PP is an argument or an adjunct. In order to test this approach, we perform an experiment using a computational learning system that receives as input utterances annotated with logical forms. The results obtained indicate that the learner successfully distinguishes between arguments (obligatory and optional) and adjuncts.