CHINERS: a Chinese named entity recognition system for the sports domain
SIGHAN '03 Proceedings of the second SIGHAN workshop on Chinese language processing - Volume 17
A novel machine learning approach for the identification of named entity relations
FeatureEng '05 Proceedings of the ACL Workshop on Feature Engineering for Machine Learning in Natural Language Processing
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In this interactive presentation, a Chinese named entity and relation identification system is demonstrated. The domain-specific system has a three-stage pipeline architecture which includes word segmentation and part-of-speech (POS) tagging, named entity recognition, and named entity relation identitfication. The experimental results have shown that the average F-measure for word segmentation and POS tagging after correcting errors achieves 92.86 and 90.01 separately. Moreover, the overall average F-measure for 6 kinds of name entities and 14 kinds of named entity relations is 83.08% and 70.46% respectively.