Papers with informative argument extraction

1 papers
Document-Level Event Argument Extraction by Conditional Generation (2021.naacl-main)

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Challenge: Existing event extraction models have been limited to the sentence level . this formulation signifies a misalignment between the information seeking behavior and the informative seeking behavior.
Approach: They propose a document-level neural event argument extraction model by formulating the task as conditional generation following event templates.
Outcome: The proposed model achieves 7.6% F1 and 5.7% F1 over the best baseline on the document-level event extraction dataset WikiEvents and 9.3% F1 on the informative argument extraction task.

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