Papers with event coreference
Cross-document Event Coreference Search: Task, Dataset and Modeling (2022.emnlp-main)
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| Challenge: | Cross-document Event Coreference resolution is the task of identifying clusters of text mentions that refer to the same event, whether within a single document or across a document collection. |
| Approach: | They propose a cross-document coreference search task that searches for all coreferring mentions for a query event in a large document collection. |
| Outcome: | The proposed model integrates a powerful coreference scoring scheme into the DPR architecture, yielding improved performance. |
Event Coreference Resolution with Non-Local Information (2020.aacl-main)
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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 . |
| Approach: | They propose to add a topic-based trigger detection module and a preprocessing module to improve event coreference. |
| Outcome: | The proposed model yields the best results on the KBP 2017 English and Chinese datasets. |
Event Coreference Resolution with their Paraphrases and Argument-aware Embeddings (2020.coling-main)
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| Challenge: | Existing methods for event coreference resolution do not identify paraphrase relations between events. |
| Approach: | They propose a new event-specific paraphrase and argument-aware semantic Embedding model for event coreference resolution based on event-related paraphrases and argument embeddings . EPASE recognizes deep paraphrase relations in an event- specific context of sentences and can cover event paraphrase of more situations . |
| Outcome: | Experiments on within- and cross-document event coreference show it is superior compared to existing methods. |
Constrained Multi-Task Learning for Event Coreference Resolution (2021.naacl-main)
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| Challenge: | a neural event coreference model is based on a task of determining whether two event mentions refer to the same event . event coreferent tasks require nontrivial tasks such as identifying potential arguments and linking arguments to their event mention. |
| Approach: | They propose a neural event coreference model in which event coreference is jointly trained with five tasks. |
| Outcome: | The proposed model achieves state-of-the-art on the KBP 2017 event coreference dataset. |
Temporal Common Sense Acquisition with Minimal Supervision (2020.acl-main)
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| Challenge: | Temporal common sense is crucial for understanding natural language, but its acquisition is challenging . human annotation on such concepts is costly and often not made explicit in text . |
| Approach: | They propose a method that exploits explicit and implicit mentions of temporal common sense to build a temporal similarity language model. |
| Outcome: | The proposed model gives better predictions of various dimensions of temporal common sense than the standard BERT. |