词义排歧的精确率依赖于排歧知识的完备性。
The precision rate of word sense disambiguation depends on the completeness of disambiguation knowledge.
词义排歧在自然语言处理领域占有重要地位。
Word sense disambiguation has always been important in natural language processing.
提出了一种机器翻译中多义词词义排歧的新方法。
A new method of polysemant meaning disambiguation is provided.
测试评价标准分别采用了词性标注准确率和兼类词排歧准确率。
Test evaluation criteria were used in POS tagging accuracy and part-category words disambiguation accuracy.
量词和含量词短语的分析排歧是汉语文本自动分析中的难点之一。
One of the most difficult points in Chinese text automatic analysis is to analyse and disambiguate classifier and phrase containing classifier.
实验结果表明语义范畴的引入有助于提高算法的学习效率和词义排歧的正确率。
Experimental results show that the semantic categorization knowledge is useful for improving the learning efficiency of the algorithm and accuracy of disambiguation.
词义排歧在机器翻译、信息检索、句子分析和语音识别等许多领域有重要的作用。
Word sense disambiguation (WSD) plays an important role in many areas of natural language processing such as machine translation, information retrieval, sentence analysis, speech recognition.
兼类词的词类排歧是汉语语料词性标注中的难点问题，它严重影响语料的词性标注质量。
The disambiguation of multi-category words is one of the difficulties in part-of-speech tagging of Chinese text, which affects the processing quality of corpora greatly.
本文的主要工作是研究获取支持词义排歧的知识的方法，并在此基础上建立一个面向真实文本中实词的汉语词义排歧系统。
The main work in the dissertation is to study how to acquire the knowledge that is supporting WSD from different language resources and build a WSD system about Chinese real text .
提出了一种基于贝叶斯分类与机读词典的多义词排歧方法，通过小规模语料库的训练和歧义词在机读词典中的语义定义来完成歧义的消除。
A method based on the bayes and machine readable dictionary was proposed, which could disambiguate by the training of a small-scale corpus and the definition of semantic in machine dictionary.
提出了一种基于贝叶斯分类与机读词典的多义词排歧方法，通过小规模语料库的训练和歧义词在机读词典中的语义定义来完成歧义的消除。
A method based on the bayes and machine readable dictionary was proposed, which could disambiguate by the training of a small-scale corpus and the definition of semantic in machine dictionary.
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