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Dynamic Strategy Selection in Flexible Parsing
Computer Science Department
  • Jaime G. Carbonell, Carnegie Mellon University
  • Philip J Hayes, Carnegie Mellon University
Date of Original Version
Conference Proceeding
Abstract or Description
Robust natural language interpretation requires strong semantic domain models, "fail-soft" recovery heuristics, and very flexible control structures. Although single-strategy parsers have met with a measure of success, a multi.strategy approach is shown to provide a much higher degree of flexibility, redundancy, and ability to bring task-specific domain knowledge (in addition to general linguistic knowledge) to bear on both grammatical and ungrammatical input. A parsing algorithm is presented that integrates several different parsing strategies, with case-frame instantiation dominating. Each of these parsing strategies exploits different types of knowledge; and their combination provides a strong framework in which to process conjunctions, fragmentary input, and ungrammatical structures, as well as less exotic, grammatically correct input. Several specific heuristics for handling ungrammatical input are presented within this multi-strategy framework.
Citation Information
Jaime G. Carbonell and Philip J Hayes. "Dynamic Strategy Selection in Flexible Parsing" (1981)
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