Class-based probability estimation using a semantic hierarchy.

This paper concerns the acquisition of a particular kind of lexical knowledge, namely the knowledge of which noun senses can fill argument slots of predicates. Probabilities are used to represent the knowledge, and classes from a semantic hierarchy are used to estimate the probabilities. There is a particular focus on the problem of how to determine a suitable class, or level of generalisation, in the hierarchy. A pseudo disambiguation task is used to compare different class-based estimation methods.