Zero anaphora resolution in Chinese and its application in Chinese-English machine translation

被引：0

作者：

Peng, Jing ^{[1
]}

Araki, Kenji ^{[1
]}

机构：

[1] Hokkaido Univ, Language Media Lab, Kita Ku, Kita 14,Nishi 9, Sapporo, Hokkaido, Japan

来源：

NATURAL LANGUAGE PROCESSING AND INFORMATION SYSTEMS, PROCEEDINGS | 2007年 / 4592卷

关键词：

zero anaphora resolution; Web-based features; ME-based classifier; machine translation;

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：

In this paper, we propose a learning classifier based on maximum entropy (ME) for resolving ZA in Chinese. Besides regular grammatical, lexical, positional and semantic features, we develop two innovative Web-based features for extracting additional semantic information of ZA from the Web. Our study shows the Web as a knowledge source can be incorporated effectively in the learning framework and significantly improves its performance. In the application of ZA resolution in MT, it is viewed as a pre-processing module that is detachable and MT-independent. The experiment results demonstrate a significant improvement on BLEU/NIST scores after the ZA resolution is employed.

引用

页码：364 / +

页数：2

共 15 条

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