Acquisition Of Selectional Patterns

1 The Problem For most natural language analysis systems, one of the major hurdles in porting the system to a new domain is the development of an appropriate set of semantic patterns. Such patterns are typically needed to guide syntactic analysis (as selectional constraints) and to control the translation into a predicate-argument representation. As systems are ported to more complex domains, the set of patterns grows and the task of accumulating them manually becomes more formidable. There has therefore been increasing interest in acquiring such patterns automatically froin a sample of text in the domain, through an analysis of word co-occurrence patterns either in raw text (word sequences) or in parsed text. We briefly review some of this work later in the article. We have been specificaily concerned about the prac-ticality of using such techniques in place of manual encoding to develop the selectional patterns for new domains. In the experiments reported here, we have therefore been particularly concerned with the evaluation of our automatically generated patterns, in terms of their complete-hess and accuracy and in terms of their efficacy in performing selection during parsing. In principle, the semantic patterns could be stated in terms of individual words-this verb can meaningfully occur with this subject, etc. In practice, however, this would produce an unmanageable number of patterns for even a small domain. We therefore need to define semantic word classes for the domain and state our patterns in terms of these classes. Ideally, then, a discovery proeednre for semantic patterns would acquire both the word classes and the patterns from an analysis of the word co-occurrence patterns. In order to simplify the task, however, while we are exploring different strategies, we have divided it into separate tasks, that of acquiring word classes and that of acquiring semantic patterns (given a set of word classes). We have previously described [1] some experiments in which the principal word classes for a sublanguge were obtained through the clustering of words based on the contexts in which they occurred, and we expect to renew such experiments using the larger corpora now available. However, the experiments we report below are limited to the acquisition of semantic patterns given a set of manually prepared word classes. The basic mechanism of pattern acquisition is straightforward. A sample of text in a new domain is parsed using a broad-coverage grammar (but without any semantic constraints). The resulting parse …