Papers with DEE
Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction (D19-1)
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| Challenge: | Existing event extraction methods are limited to extract event arguments within the sentence scope. |
| Approach: | They propose a model which generates an entity-based directed acyclic graph to fulfill document-level EE effectively. |
| Outcome: | The proposed model can generate entity-based directed acyclic graph to fulfill document-level EE effectively. |
CLIO: Role-interactive Multi-event Head Attention Network for Document-level Event Extraction (2022.coling-1)
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| Challenge: | Existing methods for document-level event extraction struggle due to two intrinsic challenges: nested arguments and multiple events. |
| Approach: | They propose a role-interactive multi-event head attention network to solve two challenges . they map different events to multiple subspaces and then determine whether the current event exists . |
| Outcome: | The proposed model improves on two widely used DEE datasets on the Internet. |
RAAT: Relation-Augmented Attention Transformer for Relation Modeling in Document-Level Event Extraction (2022.naacl-main)
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| Challenge: | Existing methods focus on sentencelevel event extraction (SEE), but they are inconsistent with actual situations. |
| Approach: | They propose a document-level event extraction framework which can model relation dependencies by a relation-augmented Attention Transformer. |
| Outcome: | The proposed framework can achieve state-of-the-art performance on two public datasets. |
Document-Level Event Extraction via Information Interaction Based on Event Relation and Argument Correlation (2024.lrec-main)
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| Challenge: | Document-level Event Extraction (DEE) is a vital task in NLP . current approaches overlook intricate relationships among events and subtle correlations among arguments within a document . |
| Approach: | They propose a document-level event extraction tool that integrates event relationships and argument correlation graphs to model the relationship among events. |
| Outcome: | The proposed network outperforms existing models and large language models in terms of F1-score across two benchmark datasets. |
Document-level Event Extraction via Parallel Prediction Networks (2021.acl-long)
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| Challenge: | Document-level event extraction (DEE) is indispensable when events are described throughout a document. |
| Approach: | They propose a document-level event extraction model that can extract structured events from a text in parallel. |
| Outcome: | The proposed model outperforms current state-of-the-art methods on a document-level event extraction task. |
An Iteratively Parallel Generation Method with the Pre-Filling Strategy for Document-level Event Extraction (2023.emnlp-main)
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| Challenge: | Existing methods to generate event roles require a given generation order . parallel methods suffer from inadequate training and manifest zero accuracies on some event roles. |
| Approach: | They propose an iteratively parallel generation method with the Pre-Filling strategy to generate event roles in parallel to avoid order selection. |
| Outcome: | The proposed method outperforms other entity-enhanced models and achieves state-of-the-art performance on two public datasets. |