Chinese Sentence Generation in a Knowledge-Based Machine Translation System

This paper presents a technique for generating Chinese sentences from the Interlingua expressions used in the KANT knowledge-based machine translation system. Chinese sentences are generated directly from the semantic representation using a unificationbased generation formalization which takes advantage of certain linguistic features of Chinese. Direct generation from the semantic form eliminates the need for an intermediate syntactic structure, thus simplifying the generation procedure. The generation algorithm is top-down, data-driven and recursive. The descriptive nature of the pseudo-unification grammar formalism used in KANT allows the grammar developer to write very straightforward semantic grammar rules. We also discuss some of the crucial problems in Chinese language generation, and describe how they can be dealt with in our framework. This technique has been implemented in a prototype Chinese sentence generation system for KANT. Some implementation details and experimental results concerning the prototype are presented at the end of this paper.