Resolution of ambiguity in Chinese and its application to machine translation

Abstract

In this paper, we present a typology of ambiguity in Chinese, which includes morphological, lexical, syntactic, semantic, and contextual ambiguities. Examples are shown for each type of ambiguity and sometimes for subtypes. Ambiguity resolution strategies used in the ALICE machine translation system are presented in various levels of detail. A disambiguation model, called Four-Step, is proposed for resolving syntactic ambiguities involving serial verb construction and predication. As the name suggests, the model comprises four steps-well-formedness checking, preference for argument readings, precondition checking, and late closure. For resolving semantic ambiguity, we propose a new formalism, called Semantic Functional Grammar (SFG), to deal with the resolution problem. SFG integrates the concept of Semantic Grammar into Lexical-Functional Grammar (LFG) such that the functional structure (f-structures) include semantic functions in addition to grammatical functions. For dealing with lexical and contextual ambiguities, we briefly describe the mechanisms used in the ALICE system. As for morphological ambiguity, the resolution is a problem of word-boundary decision (segmentation) and is beyond the scope of this research. The mechanisms presented in the paper have been successfully applied to the translation of Chinese news headlines in the ALICE system.