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| Classifying Named Entities on Chinese Wikipedia |
| XU Zhihao1,2,HUI Haotian1,2,QIAN Longhua1,2,ZHU Qiaoming1,2 |
1.Natural Language Processing Lab of Soochow University,Suzhou,Jiangsu 215006,China;
2. School of Computer Science & Technology,Soochow University,Suzhou,Jiangsu 215006,China |
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Abstract Classifying Wikipedia Entities is of great significance to NLP and machine learning. This paper presents a machine learning based method to classify the Chinese Wikipedia articles. Besides using semi-structured data and non-structured text as basic features, we also extend to use Chinese-oriented features and semantic features in order to improve the classification performance. The experimental results on a manually tagged corpus show that the additional features significantly boost the entity classification performance with the overall F1-measure as high as 96% on the ACE entity type hierarchy and 95% on the extended entity type hierarchy.
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Received: 08 July 2015
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2015, Vol. 29 
