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Báo cáo khoa học: "SOLVING THEMATIC DIVERGENCES TRANSLATIONIN MACHINE"

Though most translation systems have some mechanism for translating certain types of divergent predicate-argument structures, they do not provide a genera] procedure that takes advantage of the relationship between lexical-semantic structure and syntactic structure. A divergent predicate-argument structure is one in which the predicate (e.g., the main verb) or its arguments (e.g., the subject and object) do not have the same syntactic ordering properties for both the source and target language. . | SOLVING THEMATIC DIVERGENCES IN MACHINE TRANSLATION Bonnie Dorr M.LT. Artificial Intelligence Laboratory 545 Technology Square Room 810 Cambridge MA 02139 USA internet bonnie@reagan.ai.mit.edu ABSTRACT Though most translation systems have some mechanism for translating certain types of divergent predicate-argument structures they do not provide a general procedure that takes advantage of the relationship between lexical-semantic structure and syntactic structure. A divergent predicate-argument structure is one in which the predicate e.jf. the main verb or its arguments e.g. the subject and object do not have the same syntactic ordering properties for both the source and target language. To account for such ordering differences a machine translator must consider language-specific syntactic idiosyncrasies that distinguish a target language from a source language while making use of lexical-semantic uniformities that tie the two languages together. This paper describes the mechanisms used by the UNITRAN machine translation system for mapping an underlying lexical-conceptual structure to a syntactic structure and vice versa and it shows how these mechanisms coupled with a set of general linking routines solve the problem of thematic divergence in machine translation. 1 INTRODUCTION There are a number of different divergence types that arise during the translation of a source language to a target language. Figure 1 shows some of these divergences with respect to Spanish English and German.1 We will look at each of these traditionally difficult divergence types in turn. The first divergence type is a structural divergence in that the verbal object is realized as a noun phrase John in English and as a prepositional phrase a Juan in Spanish. The second diver- This paper describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for this research has been provided by NSF Grant DCR-85552543 under a Presidential .