Coping With Ambiguity in a Large-Scale Machine Translation System

Coping With Ambiguity in a Large-Scale Machine Translation System Kathryn L. Baker, Alexander M. Franz, Pamela W. Jordan, Teruko Mitamura, Eric H. Nyberg, 3rd Center for Machine Translation Carnegie Mellon University Pittsburgh, PA 15213 Topical Paper: machine translation, parsing Abstract In an interlingual knowledge-based machine trans- lation system, ambiguity arises when the source 1.qn- guage analyzer produces more than one interlingua expression for a source sentence. This can have a negative impact on translation quality, since a tar- get sentence may be produced from an unintended meaning. In this paper we describe the ,nethods nsed in the KANT machine translation system to reduce or eliminate ambiguity in a large-scale ap- plication domain. We also test these methods on a large corpus of test sentences, in order to illustrate how the different disambiguation methods redtuce the average number of parses per sentence, 1 Introduction The KANT system [Mitamura etal., 1991] is a system for Knowledge-basexl, Accurate Natural-language Translation. The system is used in focused technical domains for multi- lingual translation of controlled source language documents. KANT is an interlingua-based system: the sonrce language analyzer produces an interlingua expression for each source sentence, and this interlingua is processed to produce the corresponding target sentence. The problen3 el' ambiguity arises when the system produces more that~ ()tie interlingua representation for a single input sentence. If the goal is to automate translation and produce output that does not require post-editing, then the presence of ambiguity has a negative impact on translation quality, since a target sentence may he produced from an unintended meaning. When it is possible to limit tile interpretations of a sentence to just those that are coherent in the translation domain, then the accuracy of the MT system is enhanced. Ambiguity can occnr at different levels of processing in source analysis. In this paper, we describe how we cope with ambiguity in the KANT controlled lexicon, grammar, and semantic domain model, and how these :ire designed to reduce or eliminate ambiguity in a given translation domain. 2 Constraining the Source Text The KANT domain lexicon and grammar are a constrained subset of the general source language lexicon and gra,nmar. The strategy of constraining the source text has three main I I l-:igurc 1: The KANT System goals. First, it encourages clear and direct writing, which is beneficial to both the reader of tile source text and to the translation process. Second, it facilitates consistent writing among tile many authors who use the system and across all document types. And third, the selection of unambiguous words :111(I constructions to be used during authoring reduces the necessity for ambiguity resolution during the auto,natic stages of processing. It is important to reduce the processing overhead associaled wilh amhiguity resolution in order tokeep tile system fast enough for on-line use. 2.1 The l)omain Lexicml The domain lexicon is built using corpt, s analysis. Lists of terms, arranged by part of speech, are automatically ex- tracted from the corpus [Mitamura etal., 1993]. "File lexicon consists of …

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