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| Research on the Extraction of Synonymous Representation Patterns for Coreference Event Recognition |
| Wang Junze1,2, Song Xiaojiong1,2, Du Hongtao3 |
1.School of Public Administration, Huazhong University of Science and Technology, Wuhan 430074
2.Non-traditional Security Center, Huazhong University of Science and Technology, Wuhan 430074
3.China Industrial Control Systems Cyber Emergency Response Team, Beijing 100040 |
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Abstract In the field of coreference resolution, many studies have focused on the issue of entity coreference resolution, while papers about event coreference resolution are fewer. The flexibility of event representation means that one of the key points of event coreference resolution tasks is constructing a model for computing the similarity between events representation. Similar representations of the same event include not only synonymous representations at a word level but also synonymous representations at a sentence level. In this paper, based on the characteristics of the news corpus, we designed a strategy which can construct a synonym knowledge base automatically, and account for the processing of abbreviations and appositives. Conversely, on the basis of synonym expression patterns at the word level, we also designed a strategy for identifying synonym expression instances at a sentence level so as to extract synonymous representation patterns at this level and eliminate redundant components in patterns. Experiments on real data sets show the effectiveness of the proposed strategy. Based on the extracted synonymous representation pattern pairs at the word and sentence levels, we can effectively improve the effect of event coreference resolution. Our study can be regarded as a supplement to existing research on event coreference resolution.
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Received: 11 March 2019
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