Performing Integrated Syntactic and Semantic Parsing Using Classification
UNIVERSITY OF SOUTHERN CALIFORNIA MARINA DEL REY INFORMATION SCIENCES INST
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This paper describes a particular approach to parsing that utilizes recent advances in unification-based parsing and in classification-based knowledge representation. As unification-based grammatical frameworks are extended to handle richer descriptions of linguistic information, they begin to share many of the properties that have been developed in KL-ONE-like knowledge representation systems. This commonality suggests that some of the classification-based representation techniques can be applied to unification-based linguistic descriptions. This merging supports the integration of semantic and syntactic information into the same system, simultaneously subject to the same types of processes, in an efficient manner. The result is expected to be more efficient parsing due to the increased organization of knowledge. The use of a KL-ONE style representation for parsing and semantic interpretation was first explored in the PSI-KLONE system 2, in which parsing is characterized as an inference process called incremental description refinement. The key idea underlying this process is that a description of an object can become increasingly more specific as additional features are lamed from multiple knowledge sources, which is essentially the same idea that underlies most unification-based approaches. Bobrow and Webber identified four crucial capabilities that a representational system should have in order to support the process of incremental description refinement. These capabilities, not all available to Bobrow and Webber in 1980, have recently been developed in the Loom knowledge representation system 12 and hence enable the practical development of the new parsing method.