Kathryn L. Baker

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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(More)
We present an approach to pronominal anaphora resolution using KANT Controlled Language and the KANTOO multilingual MT system. Our algorithm is based on a robust, syntax-based approach that applies a set of restrictions and preferences to select the correct antecedent. We report a success rate of 93.3% on a training corpus with 286 anaphors, and 88.8% on(More)
This paper describes the strategies and techniques used by the English analysis component of the KANT Knowledge-based Machine Translation system to cope with ambiguity. The constraints for elimination of ambiguity are distributed across the various knowledge sources in the ana-lyzer. As a result, efficiency in the analysis component is maintained, and(More)
This paper describes the results of a feasibility study which focused on deriving semantic networks from descriptive texts using controlled language. The KANT system 3, 6] was used to analyze input paragraphs, producing sentence-level interlingua representations. The in-terlinguas were merged to construct a paragraph-level representation, which was used to(More)
This paper presents an overview of the tools provided by KANTOO MT system for controlled source language checking, source text analysis, and terminology management. The steps in each process are described, and screen images are provided to illustrate the system architecture and example tool interfaces.
We describe the automatic resolution of pronominal anaphora using KANT Controlled English (KCE) and the KANTOO English-to-Spanish MT system. Our algorithm is based on a robust, syntax-based approach that applies a set of restrictions and preferences to select the correct antecedent. We report a success rate of 89.6% on a training corpus with 289 anaphors,(More)
Acknowledgements I would like to thank the members of my committee: All have ties to Pitts-burgh, but as we have become separated by time and distance, I appreciate their seeing this project through. Thanks to Rich for bringing me to Pittsburgh in the first place. I am struck by Bob's sharp memory and attention to detail as he has provided numerous(More)
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