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The Universal Parser Architecture for Knowledge-Based Machine Translation

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journal contribution
posted on 01.02.2008 by Masaru Tomita, Jaime G. Carbonell
Machine translation should be semanticalty-accurate, linguisticallyprincipled, user-interactive, and extensible to multiple languages and domains. This paper presents the universal parser architecture that strives to meet these objectives. In essence, linguistic knowledge bases (syntactic, semantic, lexical, pragmatic), encoded in theoretically-motivated formalisms such as lexical-functional grammars, are unified and precompiled into fast run-time grammars for parsing and generation. Thus, the universal parser provides principled run-time integration of syntax and semantics, while preserving the generality of domain-independent syntactic grammars, and language-independent domain knowledge bases; the optimized cross product is generated automatically in the precornpllation phase. Initial results for bi-directional English-Japanese translation show considerable promise both in terms of demonstrating the theoretical feasibillty of the approach and in terms of subsequent practical utility.