Abstract
Recently, online news has become one of the most important resources from which people get useful information. Linking named entities in news articles to existing knowledge bases is a critical task to facilitate readers to understand the news well. In this paper, we propose an approach for linking entities in Chinese news articles to Chinese knowledge bases. Our approach first recognizes three types of named entities (i.e., person, location, and organization) and then uses a disambiguation method to link entities occurring in news articles to entities in knowledge bases. In the disambiguation process, co-mentioned entities are used as features to compute the context similarities between entities in news and entities in knowledge bases; the disambiguation results are decided by a threshold-filtering method on the context similarities. Experiments on linking entities in Sina news to Hudong knowledge base validate the effectiveness of our approach; it achieves 84.39%, 84.02%, and 86.16% F1-scores in the task of linking person entities, location entities, and organization entities, respectively.
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Acknowledgements
The work is supported by the Natural Science Foundation of China (No. 61035004, No. 60973102), 863 High Technology Program (2011AA01A207), European Union 7th Framework Project FP7-288342, and THU-NUS NExT Co-Lab and the project cooperated with Chongqing research institute of science and technology.
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Zheng, Q., Li, J., Wang, Z., Hou, L. (2013). Co-mention and Context-Based Entity Linking. In: Li, J., Qi, G., Zhao, D., Nejdl, W., Zheng, HT. (eds) Semantic Web and Web Science. Springer Proceedings in Complexity. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6880-6_10
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DOI: https://doi.org/10.1007/978-1-4614-6880-6_10
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