Enhancing Lemmatization for Mongolian and its Application to Statistical Machine Translation

机译：加强蒙古人的合法化及其在统计机器翻译中的应用

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摘要

Lemmatization is crucial in natural language processing and information retrieval especially for highly inflected languages, such as Finnish and Mongolian. The state-of-the-art method of lemmatization for Mongolian does not need a noun dictionary and is scalable, but errors of this method are mainly caused by problems related to part of speech (POS) information. To resolve this problem, we integrate POS tagging and lemmatization for Mongolian. We evaluate the effectiveness of our method and its contribution to statistical machine translation.

机译：合法化在自然语言处理和信息检索中至关重要，特别是对于芬兰语和蒙古语等高语种而言。蒙古语的最新词法归类化方法不需要名词词典并且可扩展，但是该方法的错误主要是由与词性（POS）信息有关的问题引起的。为了解决这个问题，我们集成了POS标记和蒙古语的词形化。我们评估了我们方法的有效性及其对统计机器翻译的贡献。

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来源
《10th workshop on Asian language resources》|2012年|115-123|共9页
会议地点 Mumbai(IN)
作者
Odbayar Chimeddorj Atsushi Fujii;
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作者单位

Graduate School of Information Science and Engineering, Tokyo Institute of Technology 2-12-1 Ookayama, 152-8552, Japan;

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会议组织
原文格式 PDF
正文语种 eng
中图分类
关键词
Morphological segmentation; Lemmatization; Mongolian language; Statistical Machine Translation;

机译：形态分割合法化；蒙古语；统计机器翻译;

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4. Enhancing Lemmatization for Mongolian and its Application to Statistical Machine Translation [C] . Odbayar Chimeddorj Atsushi Fujii International conference on computational linguistics . 2012

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Enhancing Lemmatization for Mongolian and its Application to Statistical Machine Translation

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