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。
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。
So researches on Chinese complex sentence semantics facilitate the NLP from the characters and words level to the sentence or even the paragraph level.
因此对复句语义进行研究为中文信息处理从字、词处理级提升到句处理级及句处理级以上的研究提供了基础。
The Chinese FrameNet project is producing a lexicon of Chinese for both human use and NLP applications, based on the principles of Fillmore s Frame Semantics.
汉语框架网络工程是以框架语义学为理论基础的基于语料库的计算词典编纂工程，用于语言学、计算语言学研究及自然语言处理研究。
The Chinese FrameNet project is producing a lexicon of Chinese for both human use and NLP applications, based on the principles of Fillmore s Frame Semantics.
汉语框架网络工程是以框架语义学为理论基础的基于语料库的计算词典编纂工程，用于语言学、计算语言学研究及自然语言处理研究。
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