Papers with mention extraction
End-to-end Neural Information Status Classification (2021.findings-emnlp)
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| Challenge: | Existing studies on information status classification and bridging anaphora recognition assume that gold mention or syntactic tree information is given. |
| Approach: | They propose an end-to-end neural approach for information status classification using a mention extraction component and an information status assignment component. |
| Outcome: | The proposed system achieves state-of-the-art on fine-grained IS classification based on gold mentions and better than baselines on ISNotes and SciCorp. |
Modeling Task Interactions in Document-Level Joint Entity and Relation Extraction (2022.naacl-main)
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| Challenge: | Existing work on document-level relation extraction has focused on end-to-end setting that extracts global entities and relations jointly. |
| Approach: | They propose to introduce a two-way interaction between COREF and RE that is specifically designed to leverage task characteristics, bridging decisions of two tasks for direct task interference. |
| Outcome: | The proposed model achieves the best performance by up to 2.3/5.1 F1 over the baseline. |
Interpretable Coreference Resolution Evaluation Using Explicit Semantics (2026.acl-long)
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| Challenge: | Existing evaluation methods for coreference resolution are limited by semantic and contextual information. |
| Approach: | They propose a semantically-enhanced evaluation framework for coreference resolution that assigns semantic labels to nominal mentions and propagates them to entire coreference clusters. |
| Outcome: | The proposed framework uncovers systematic weaknesses obscured by standard metrics. |