The Universal Parser Architecture for Knowledge-Based Machine Translation

Abstract

Machine translation should be semanticalty-accurate, linguistically-principled, user-interactive, and extensible to multiple languages and domains. This paper presents the<em> universal parser</em> 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<em> parser</em> 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.