---
title: "The Universal Parser Architecture for Knowledge-based Machine Translation"
authors:
  - "Masaru Tomita"
  - "Jaime G. Carbonell"
doi: ""
url: "https://ijcai.org/proceedings/1987/143"
pdf: "https://ijcai.org/proceedings/1987/0143.pdf"
venue: "Proceedings of the Tenth International Joint Conference on Artificial Intelligence"
year: 1987
pages: "718-720"
track: "Natural Language"
keywords:
---

# The Universal Parser Architecture for Knowledge-based Machine Translation

Masaru Tomita, Jaime G. Carbonell

*Proceedings of the Tenth International Joint Conference on Artificial Intelligence*, pages 718-720.

## Abstract

Machine translation should be semantically-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 automatlpally in the precompilation phase. Initial results for bi-directional English-Japanese translation show considerable promise both in terms of demonstrating the theoretical feasibility of the approach and in terms of subsequent practical utility.