Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution (P19-1)
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| Challenge: | Recognizing that various textual spans across multiple texts refer to the same entity or event is an important NLP task. |
| Approach: | They propose a neural architecture for cross-document coreference resolution by representing an event mention using its lexical span, surrounding context, and relation to other mentions via predicate-arguments structures. |
| Outcome: | The proposed model outperforms the state-of-the-art event coreference model on ECB+ while providing the first entity coreference results on this corpus. |
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| Challenge: | Existing models for event coreference resolution are based on entity-level tasks, but event coreferent resolution is a challenge. |
| Approach: | They propose a model that learns and integrates multiple representations from event alone and event pair on the basis of event but not entity as before. |
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Enhancing Cross-Document Event Coreference Resolution by Discourse Structure and Semantic Information (2024.lrec-main)
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| Challenge: | Existing cross-document event coreference resolution models lack the ability to capture long-distance dependencies. |
| Approach: | They propose to construct document-level Rhetorical Structure Theory trees and cross-document Lexical Chains to model structural and semantic information of documents. |
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Cross-document Coreference Resolution over Predicted Mentions (2021.findings-acl)
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| Challenge: | Cross-document coreference resolution has been under-explored in recent years . however, the challenge of cross-document resolution remains relatively under-studied . |
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Contrastive Representation Learning for Cross-Document Coreference Resolution of Events and Entities (2022.naacl-main)
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| Challenge: | Identifying related entities and events within and across documents is fundamental to natural language understanding. |
| Approach: | They propose an approach to entity and event coreference resolution using contrastive representation learning. |
| Outcome: | The proposed method achieves state-of-the-art results on key metrics on the ECB+ corpus and is competitive on others. |
Cross-Document Event Coreference Resolution on Discourse Structure (2023.emnlp-main)
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| Challenge: | Experimental results show that our proposed model outperforms several baselines and achieves the competitive performance with the start-of-the-art baselines. |
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Sequential Cross-Document Coreference Resolution (2021.emnlp-main)
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| Challenge: | Existing models for cross-document coreference resolution have been used for within-document entity coreference but have been relatively limited. |
| Approach: | They propose a model that extends the efficient sequential prediction paradigm for coreference resolution to cross-document settings and achieves competitive results for both entity and event coreference. |
| Outcome: | The proposed model achieves competitive results for entity and event coreference while minimizing error propagation in complex reasoning tasks. |
Multimodal Cross-Document Event Coreference Resolution Using Linear Semantic Transfer and Mixed-Modality Ensembles (2024.lrec-main)
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Abhijnan Nath, Huma Jamil, Shafiuddin Rehan Ahmed, George Arthur Baker, Rahul Ghosh, James H. Martin, Nathaniel Blanchard, Nikhil Krishnaswamy
| Challenge: | Existing methods for cross-document coreference resolution do not provide images for all mentions of events. |
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Exploiting Document Structures and Cluster Consistencies for Event Coreference Resolution (2021.acl-long)
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| Challenge: | Existing deep learning models for event coreference resolution are limited in that they cannot exploit important interactions between relevant objects for ECR. |
| Approach: | They propose a deep learning model that groups coreferent event mentions into the same clusters . they use document structures to capture relevant objects for ECR . |
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Neural Cross-Lingual Coreference Resolution And Its Application To Entity Linking (P18-2)
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| Challenge: | a cross-lingual coreference model is based on multi-lingual embeddings and language independent features. |
| Approach: | They propose a crosslingual coreference model that builds on multi-lingual embeddings and language independent features. |
| Outcome: | The proposed model outperforms the existing models on Chinese and Spanish test sets. |
Towards Consistent Document-level Entity Linking: Joint Models for Entity Linking and Coreference Resolution (2022.acl-short)
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| Challenge: | Existing approaches to solve entity linking (EL) jointly with coreference resolution (coref) a coreferenced cluster can only be linked to a single entity or NIL (i.e., a nonlinkable entity) |
| Approach: | They propose to join entity linking and coreference resolution in a single structured prediction task over directed trees and use a globally normalized model to solve it. |
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