Capturing Language Specific Constraints on Lexical Selection with Feature-Based Lexicalized Tree-Adjoining Grammars

摘要

The success of a Machine Translation (MT) application depends on its ability to perform lexical selection, that is, to choose lexical items in the target language that most closely match the lexical items in the input source. This task is particularly difficult in cases, such as those which arise in translating from English to Chinese and Korean, where the target language imposes lexical constraints which are non-existent or completely different in the source. We present an implementation of an English-Korean MT system using Feature-Based, Lexicalized Tree-Adjoining Grammar (FB-LTAG), and demonstrate its ability to handle difficulties involving lexical selection between those two languages. We also describe the applicability of this approach to similar issues which arise in English-Chinese translation. By building language-dependent FB-LTAGs for each language and then linking them via a Synchronous Tree-Adjoining Grammar (STAG), we are able to elegantly model the specific and language-dependent syntactic and semantic distinctions necessary to filter the choice of target lexical items.