Generalizing automatically generated selectional patterns
Ralph Grishman, John Sterling · 1994
Frequency information on co-occurrence patterns can be automatically collected from a syntactically analyzed corpus; this information can then serve as the basis for selectional constraints when analyzing new text from the same domain. This information, however, is necessarily incomplete. We report on measurements of the degree of selectional coverage obtained with different sizes of corpora. We then describe a technique for using the corpus to identify selectionally similar terms, and for using this similarity to broaden the selectional coverage for a fixed corpus size.