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COLING
1994

Coping With Ambiguity in a Large-Scale Machine Translation System

10 years 5 months ago
Coping With Ambiguity in a Large-Scale Machine Translation System
In an interlingual knowledge-based machine translation system, ambiguity arises when the source language analyzer produces more than one interlingua expression for a source sentence. This can have a negative impact on translation quality, since a target sentence may be produced from an unintended meaning. In this paper we describe the methods used in the KANT machine translation system to reduce or eliminate ambiguity in a large-scale application domain. We also test these methods on a large corpus of test sentences, in order to illustrate how the different disambiguation methods reduce the average number of parses per sentence.
Kathryn L. Baker, Alexander Franz, Pamela W. Jorda
Added 02 Nov 2010
Updated 02 Nov 2010
Type Conference
Year 1994
Where COLING
Authors Kathryn L. Baker, Alexander Franz, Pamela W. Jordan, Teruko Mitamura, Eric Nyberg
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