Example-Based Word-Sense Disambiguation (Special Issue on Natural Language Processing and Understanding)

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概要

• 論文の詳細を見る

• This paper presents a new method for resolving lexical (word sense) ambiguities ingerent in natural language sentences. The Sentence Analyzer (SENA) was developed to resolve such ambiguities by using constraints and example-based preferences. The ambiguities are packed into a single dependency structure, and grammatical and lexical constraints are applied to it in order to reduce the degree of ambiguity. The application of constraints is realized by a very effective constraint-satisfaction technique. Remaining ambiguities are resolved by the use of preferences calculated from an examplebase, which is a set of fully parsed word-to-word dependencies acquired semi-automatically from on-line dictionaries.

• 一般社団法人電子情報通信学会の論文
• 1994-02-25

著者

• Uramoto Naohiko

  Ibm Research Tokyo Research Laboratory

関連論文

• Example-Based Word-Sense Disambiguation (Special Issue on Natural Language Processing and Understanding)

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