Handling structural divergences and recovering dropped arguments in a Korean/English machine translation system

被引：0

作者：

Han, CH

Lavoie, B

Palmer, M

Rambow, O

Kittredge, R

Korelsky, T

Kim, N

Kim, M

机构：

[1] Univ Penn, Dept Comp & Informat Sci, IRCS, Philadelphia, PA 19104 USA

[2] CoGenTex Inc, Ithaca, NY 14850 USA

[3] AT&T Labs Res, Florham Pk, NJ 07932 USA

[4] Konan Technol Inc, Seoul 135090, South Korea

来源：

ENVISIONING MACHINE TRANSLATION IN THE INFORMATION FUTURE, PROCEEDINGS | 2000年 / 1934卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：40 / 53

页数：14

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