Paper: A Parameterized Approach To Integrating Aspect With Lexical-Semantics For Machine Translation

ACL ID P92-1033
Title A Parameterized Approach To Integrating Aspect With Lexical-Semantics For Machine Translation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1992
Authors

This paper discusses how a two-level knowledge rep- resentation model for machine translation integrates as- pectual information with lexical-semantic information by means of parameterization. The integration of aspect with lexical-semantics is especially critical in machine translation because of the lexical selection and aspec- tual realization processes that operate during the pro- duction of the target-language sentence: there are of- ten a large number of lexical and aspectual possibili- ties to choose from in the production of a sentence from a lexical semantic representation. Aspectual informa- tion from the source-language sentence constrains the choice of target-language terms. In turn, the target- language terms limit the possibilities for generation of aspect. Thus, there is a t...