A Preferential Constraint Satisfaction Technique for Natural Language Analysis

Katashi NAGAO  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E77-D   No.2   pp.161-170
Publication Date: 1994/02/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Issue on Natural Language Processing and Understanding)
Category: 
Keyword: 
disambiguation,  constraint satisfaction,  preference,  dependency structure,  delayed semantic somposition,  

Full Text: PDF>>
Buy this Article




Summary: 
In this paper, we present a new technique for the semantic analysis of sentences, including an ambiguity-packing method that generates a packed representation of individual syntactic and semantic structures. This representation is based on a dependency structure with constraints that must be satisfied in the syntax-semantics mapping phase. Complete syntax-semantics mapping is not performed until all ambiguities have been resolved, thus avoiding the combinatorial explosions that sometimes occur when unpacking locally packed ambiguities. A constraint satisfaction technique makes it possible to resolve ambiguities efficiently without unpacking. Disambiguation is the process of applying syntactic and semantic constraints to the possible candidate solutions (such as modifiees, cases, and wordsenses) and removing unsatisfactory condidates. Since several candidates often remain after applying constraints, another kind of knowledge to enable selection of the most plausible candidate solution is required. We call this new knowledge a preference. Both constraints and preferences must be applied to coordination for disambiguation. Either of them alone is insufficient for the purpose, and the interactions between them are important. We also present an algorithm for controlling the interaction between the constraints and the preferences in the disambiguation process. By allowing the preferences to control the application of the constraints, ambiguities can be efficiently resolved, thus avoiding combinatorial explosions.