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The Art of Prompting: Event Detection based on Type Specific Prompts

About

We compare various forms of prompts to represent event types and develop a unified framework to incorporate the event type specific prompts for supervised, few-shot, and zero-shot event detection. The experimental results demonstrate that a well-defined and comprehensive event type prompt can significantly improve the performance of event detection, especially when the annotated data is scarce (few-shot event detection) or not available (zero-shot event detection). By leveraging the semantics of event types, our unified framework shows up to 24.3\% F-score gain over the previous state-of-the-art baselines.

Sijia Wang, Mo Yu, Lifu Huang• 2022

Related benchmarks

TaskDatasetResultRank
Event DetectionMAVEN (test)
F1 Score68.8
26
Event DetectionERE
F1 Score63.4
23
Event DetectionACE05-E+ (Evaluation)
F1 Score74.9
23
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