Part of Speech Tagging Chinese Corpus Based on Statistics and Rules
统计与规则并举的汉语词性自动标注算法

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.