Nari Kim


2000

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Handling structural divergences and recovering dropped arguments in a Korean/English machine translation system
Chung-hye Han | Benoit Lavoie | Martha Palmer | Owen Rambow | Richard Kittredge | Tanya Korelsky | Nari Kim | Myunghee Kim
Proceedings of the Fourth Conference of the Association for Machine Translation in the Americas: Technical Papers

This paper describes an approach for handling structural divergences and recovering dropped arguments in an implemented Korean to English machine translation system. The approach relies on canonical predicate-argument structures (or dependency structures), which provide a suitable pivot representation for the handling of structural divergences and the recovery of dropped arguments. It can also be converted to and from the interface representations of many off-the-shelf parsers and generators.

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Towards Translingual Information Access using Portable Information Extraction
Michael White | Claire Cardie | Chung-hye Han | Nari Kim | Benoit Lavoie | Martha Palmer | Owen Rainbow | Juntae Yoon
ANLP-NAACL 2000 Workshop: Embedded Machine Translation Systems

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Customizing the XTAG system for efficient grammar development for Korean
Juntae Yoon | Chung-hye Han | Nari Kim | Meesook Kim
Proceedings of the Fifth International Workshop on Tree Adjoining Grammar and Related Frameworks (TAG+5)

1998

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Statistical approach for Korean analysis
Nari Kim
Proceedings of the Third Conference of the Association for Machine Translation in the Americas: Technical Papers

In conventional approaches to Korean analysis, verb subcategorization has generally been used as lexical knowledge. A problem arises, however, when we are given long sentences in which two or more verbs of the same subcategorization are involved. In those sentences, a noun phrase may be taken as the constituent of more than one verb and cause an ambiguity. This paper presents an approach to solving this problem by using structural patterns acquired by a statistical method from corpora. Structural patterns can be the processing units for syntactic analysis and for translation into other languages as well. We have collected 10,686 unique structural patterns from a Korean corpus of 1.27 million words. We have analyzed 2,672 sentences and shown that structural patterns can improve the accuracy of Korean analysis.