Conundrums in Entity Coreference Resolution: Making Sense of the State of the Art (2020.emnlp-main)
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| Challenge: | despite significant progress on entity coreference resolution, there is a general lack of understanding of what has been improved. |
| Approach: | They present an empirical analysis of entity coreference resolvers to provide an understanding of what has been improved. |
| Outcome: | The proposed model improves the performance of entity coreference resolvers. |
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| Challenge: | Recent years have seen the successful application of span-based neural models to entity-based information extraction tasks such as entity coreference resolution (CR) Existing event coreference resolvers focused on feature engineering are few and far between, let alone event corefers. |
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| Challenge: | bridging resolution is an anaphora resolution task that is less studied than entity coreference resolution. |
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| Challenge: | state-of-the-art resolvers for bridging resolution are weaker than entity coreference resolution. |
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| Challenge: | a new study examines the current state of knowledge about the BERT model . the model is a stack of transformer encoder layers that are based on multiple self-attention ''heads'' |
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| Challenge: | Existing joint models for event coreference resolution are understudied and underexploited . current models only learn trigger detection and event coreference from annotated training data . |
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| Challenge: | Unlike singular mentions each of which represents one entity, plural mentions stand for multiple entities. |
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The Coreference under Transformation Labeling Dataset: Entity Tracking in Procedural Texts Using Event Models (2023.findings-acl)
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| Challenge: | et al., 2023) show that entity coreference resolution is improved when events bring about changes in entities that are not reflected in text mentions. |
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| Challenge: | a pretrained language model is used in state-of-the-art coreference resolution models. |
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Evaluating the Impact of a Hierarchical Discourse Representation on Entity Coreference Resolution Performance (2021.naacl-main)
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| Challenge: | Recent work on entity coreference resolution (CR) follows current trends in Deep Learning . traditional approaches do not make use of hierarchical representations of discourse structure . |
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End-to-End Neural Discourse Deixis Resolution in Dialogue (2022.emnlp-main)
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| Challenge: | Lexical overlap is a strong indicator of entity coreference, both among names and in the resolution of nominals. |
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