The speed of Chinese word segmentation is very important for many Chinese NLP systems, such as web search engines based on words.
对于基于词的搜索引擎等中文处理系统，分词速度要求较高。
Chinese word segmentation is a basic research issue on Chinese NLP areas such as information retrieval, machine translation, text correction, and so on.
汉语分词是信息检索、机器翻译、文本校对等中文信息处理重要领域的基础。
Automatic word segmentation is the basis of NLP.
自动分词技术是自然语言处理的基础工程。
Chinese word segmentation is the foundation of NLP.
汉语自动分词是中文信息处理的重要基石。
The results of this study indicate that the SKCC is effective for word sense disambiguation in MT system and are likely to be important for general Chinese NLP.
初步的实验结果表明，该方法可以有效地进行汉语名词、动词、形容词的词义消歧。
Word alignment is a basic problem of Cross-lingual Natural Language Processing. Many NLP tasks based on bilingual corpus such as SBMT, EBMT, WSD, Automated Dictionary Extraction need to align words.
词语对齐是跨语言自然语言处理领域的一个基本问题，许多基于双语语料库的应用(如sbmt、EBMT、WSD、词典编纂)都需要词汇级别的对齐。
WTD and its similar task - word sense disambiguation (WSD) in mono-lingual category are important and hard in the research of nature language processing (NLP) and are always the basis of it.
译文消歧及与之相似的在单语范畴内的词义消歧一直是自然语言处理领域基础研究课题，它也是自然语言处理技术的重点和难点之一。
WTD and its similar task - word sense disambiguation (WSD) in mono-lingual category are important and hard in the research of nature language processing (NLP) and are always the basis of it.
译文消歧及与之相似的在单语范畴内的词义消歧一直是自然语言处理领域基础研究课题，它也是自然语言处理技术的重点和难点之一。
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