A class-based probabilistic approach to structural disambiguation
Stephen Charles Clark, David James Weir · 2000
Knowledge of which words are able to fill particular argument slots of a predicate can be used for structural disambiguation. This paper describes a proposal for acquiring such knowledge, and in line with much of the recent work in this area, a probabilistic approach is taken. We develop a novel way of using a semantic hierarchy to estimate the probabilities, and demonstrate the general approach using a prepositional phrase attachment experiment.