A Structure-Based Model for Chinese Organization Name Translation
A Structure-Based Model for Chinese Organization Name Translation
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DOI：
10.1145/1330291.1330292
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发表时间：
2008-02
期刊：
影响因子：
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通讯作者：
Yufeng Chen;Chengqing Zong
中科院分区：
文献类型：
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作者：
Yufeng Chen;Chengqing Zong
命名实体翻译是多语言自然语言处理中的一项基本任务。机器翻译系统的性能在很大程度上取决于包含性内斯的精确翻译。此外，组织名称（ON）是所有内斯中翻译最复杂的网元。本文研究了Ons的结构形式，提出了一种基于层次结构的Ons翻译模型。该模型首先进行ON组块，然后通过同步上下文无关语法（CFG）实现组块内单词的翻译和组块的重新排序。在训练程序中，从双语ON对中提取CFG规则。本文的主要贡献是：（1）定义了合适的组块单元，用于分析汉语ON的内部结构;（2）通过层次化的CFG推导，使得基于组块的ON翻译变得可行和灵活;（3）提出了一种自动学习同步CFG的训练架构，用于从对齐的双语ON对中构造具有组块单元的ON。实验结果表明，该方法将中文ON翻译成英文的准确率为93.75%，并显着提高了基线统计机器翻译（SMT）系统的性能。
Named entity (NE) translation is a fundamental task in multilingual natural language processing. The performance of a machine translation system depends heavily on precise translation of the inclusive NEs. Furthermore, organization name (ON) is the most complex NE for translation among all the NEs. In this article, the structure formulation of ONs is investigated and a hierarchical structure-based ON translation model for Chinese-to-English translation system is presented. First, the model performs ON chunking; then both the translation of words within chunks and the process of chunk-reordering are achieved by synchronous context-free grammar (CFG). The CFG rules are extracted from bilingual ON pairs in a training program. The main contributions of this article are: (1) defining appropriate chunk-units for analyzing the internal structure of Chinese ONs; (2) making the chunk-based ON translation feasible and flexible via a hierarchical CFG derivation; and (3) proposing a training architecture to automatically learn the synchronous CFG for constructing ONs with chunk-units from aligned bilingual ON pairs. The experiments show that the proposed approach translates the Chinese ONs into English with an accuracy of 93.75% and significantly improves the performance of a baseline statistical machine translation (SMT) system.