In this paper, we will introduce a corpus-based Chinese parsing system.
在这篇文章中，我们将介绍一种基于语料库的汉语句法分析系统。
Then according to the idea of chunk parsing, the Chinese parsing system based on semantic analysis is designed and is implemented.
接着本文运用组块分析的思想，提出并实现了一个基于语义的汉语句法分析系统。
It is for the first time in China that the researcher introduces automatic Chinese parsing with CTT and its application in Chinese teaching.
本文是国内第一篇介绍用CTT做汉语自动句法分析及应用于汉语教学的文章。
The phrase database is a powerful language knowledge resource and will be some help to phrase structure study, Chinese parsing and Chinese-English machine translation.
短语库是综合型语言知识库的有机组成部分，它的建设将为短语结构研究、句法分析和机器翻译提供强大的语言知识支撑。
Software experiments about the Chinese sentence parsing show the model presented in this paper has higher efficiency and robustness.
将该模型用于汉语句子分析的软件实验中表明：模型具有较高的计算效率和鲁棒性。
In this paper, a trainable and fast partial parsing method for Chinese is presented.
提出一种可训练的快速汉语部分句法分析方法。
The former includes Chinese word segmentation, part - of - speech tagging, pinyin tagging, named entity recognition, new word detection, syntactic parsing, word sense disambiguation, etc.
前者涉及到词法、句法、语义分析，包括汉语分词、词性标注、注音、命名实体识别、新词发现、句法分析、词义消歧等。
It is a temporal relation between the event time and the speech time or another reference time, and can be obtained by time phrase parsing of Chinese text.
时制是时间信息的重要组成部分，需要在篇章中通过时间短语的语义分析获得。
We investigated dependency parsing based algorithm and keyword matching based algorithm for feature-based opinion mining. We construct a product features library and a Chinese polarity Dictionary.
设计并实现了基于依存句法分析的细颗粒意见挖掘算法和基于关键字匹配的细颗粒意见挖掘算法，并构建产品特征库和中文极性词典。
The experiment results show that the maximum entropy model has a very good effect on semantic chunk parsing to Chinese question sentence.
实验结果说明最大熵模型应用于汉语问句语义组块分析具有较好的效果。
To improve the computer's processing capacity on Chinese information, and do better shallow parsing, this paper presents a recognition method of Chinese phrase structure based on Maximum Entropy(ME).
为提高计算机对汉语信息的处理能力，更好地进行浅层句法分析，提出一种基于最大熵的汉语短语结构识别方法。
A method of skeleton parsing for domain specific Chinese text is put forward in this paper.
本文提出了一种面向特定领域的汉语句法主干分析方法。
The former includes Chinese word segmentation, part-of-speech tagging, pinyin tagging, named entity recognition, new word detection, syntactic parsing, word sense disambiguation, etc .
前者涉及到词法、句法、语义分析，包括汉语分词、词性标注、注音、命名实体识别、新词发现、句法分析、词义消歧等。
This dissertation also discusses applying Conditional Random Fields to Chinese Chunk Parsing and our future works.
提出了未来关于应用条件随机场构建汉语词法语块分析模型的初步构想。
In Chinese-English machine translation, temporal information parsing of Chinese text is very important, because it is the basis to generate the correct tenses of English verbs.
汉英机器翻译中，汉语篇章的时间信息是生成正确英语动词时态的基础。
This paper proposes to use Maximum Entropy (ME) model to conduct Chinese chunk parsing.
采用最大熵模型实现中文组块分析的任务。
This paper proposes to use Maximum Entropy (ME) model to conduct Chinese chunk parsing.
采用最大熵模型实现中文组块分析的任务。
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