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| Research on Chinese Event Extraction |
| ZHAO Yan-yan, QIN Bing, CHE Wan-xiang, LIU Ting |
Information Retrieval Laboratory, School of Computer Science and Technology,
Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
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Abstract Event Extraction is an important research point in the area of Information Extraction. This paper makes an intensive study of the two stages of Chinese event extraction, namely event type recognition and event argument recognition. A novel method combining event trigger expansion and a binary classifier is presented in the step of event type recognition while in the step of argument recognition, one with multi-class classification based on maximum entropy is introduced. The above methods solved the data unbalanced problem in training model and the data sparseness problem brought by the small set of training data effectively, and finally our event extraction system achieved a better performance.
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Received: 31 May 2007
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2008, Vol. 22 
