| 摘要: |
| 本文提出并实现了一种基于定量统计分析优先的统计和规则并举的汉语词性自动标注算法.本算法引入置信区间的概念,优先采用高准确率的定量统计分析技术,然后利用规则标注剩余语料和校正部分统计标注错误.封闭和开放测试表明,在未考虑生词和汉语词错误切分的情况下,本算法的准确率为98.9%和98.1%. |
| 关键词: 汉语,词性标注,隐马尔可夫模型,规则,置信区间. |
| DOI： |
| 分类号: |
| 基金项目:本文研究得到国家863高科技项目基金资助. |
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| Part of Speech Tagging Chinese Corpus Based on Statistics and Rules |
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ZHANG Min,LI Sheng,ZHAO Tie-jun,ZHANG Yan-feng
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| Abstract: |
| This paper proposes an algorithm of automaticallytagging the POS(part of speech) of Chinese words which is based on integration of the statistical technique and the rule technique with the priority of the quantitative statistical analysis. The confidence intervals in the estimation of parameters is employed in the algorithm, and this makes the high-accuracy quantitative statistical technique as the top priority of tagging a corpus. Then the untagging part of the corpus is tagged in terms of rules, and some errors by statistics can be corrected by rules. Both closed and opened tests indicated that the accuracies of the algorithm are 98.9% and 98.1% respectively without consideration of both unknown words and segmentation errors. |
| Key words: Chinese, part of speech tagging, hidden Markov model, rule, confidence intervals. |
