JCSE, vol. 8, no. 3, pp.137-148, 2014

DOI: http://dx.doi.org/10.5626/JCSE.2014.8.3.137

Classifying Articles in Chinese Wikipedia with Fine-Grained Named Entity Type

Jie Zhou, Bicheng Li, and Yongwang Tang
Zhengzhou Information Science and Technology Institute, Zhengzhou, China

Abstract: Named entity classification of Wikipedia articles is a fundamental research area that can be used to automatically build large-scale corpora of named entity recognition or to support other entity processing, such as entity linking, as auxiliary tasks. This paper describes a method of classifying named entities in Chinese Wikipedia with fine-grained types. We considered multi-faceted information in Chinese Wikipedia to construct four feature sets, designed different feature selection methods for each feature, and fused different features with a vector space using different strategies. Experimental results show that the explored feature sets and their combination can effectively improve the performance of named entity classification.

Keyword: Named entity classification; Chinese Wikipedia; Fine-grained; Feature selection; NER corpora

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