Employing Discourse Coherence Enhancement to Improve Cross-Document Event and Entity Coreference Resolution
Xinyu Chen, Peifeng Li, Qiaoming Zhu
Abstract
Cross-Document Coreference Resolution (CDCR) aims to identify and group together mentions of a specific event or entity that occur across multiple documents. In contrast to the within-document tasks, in which event and entity mentions are linked by rich and coherent contexts, cross-document mentions lack such critical contexts, which presents a significant challenge in establishing connections among them. To address this issue, we introduce a novel task Cross-Document Discourse Coherence Enhancement (CD-DCE) to enhance the discourse coherence between two cross-document event or entity mentions. Specifically, CD-DCE first selects coherent texts and then adds them between two cross-document mentions to form a new coherent document. Subsequently, the coherent text is employed to represent the event or entity mentions and to resolve any coreferent mentions. Experimental results on the three popular datasets demonstrate that our proposed method 1 outperforms several state-of-the-art baselines.
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Builds on10
- Span-Based Event Coreference ResolutionJing Lu, Vincent NgAAAI 2021 · 17 citations
- Synergetic Event Understanding: A Collaborative Approach to Cross-Document Event Coreference Resolution with Large Language ModelsQingkai Min, Qipeng Guo, Xiangkun Hu, Songfang Huang et al.ACL 2024 · 11 citations
- CorefPrompt: Prompt-based Event Coreference Resolution by Measuring Event Type and Argument CompatibilitiesSheng Xu, Peifeng Li, Qiaoming ZhuEMNLP 2023 · 11 citations
- Focus on what matters: Applying Discourse Coherence Theory to Cross Document CoreferenceWilliam Barr Held, Dan Iter, Dan JurafskyEMNLP 2021 · 11 citations
- Improving Event Coreference Resolution Using Document-level and Topic-level InformationSheng Xu, Peifeng Li, Qiaoming ZhuEMNLP 2022 · 10 citations
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