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

• URL: http://arxiv.org/abs/2204.07241v1
• Date: Thu, 14 Apr 2022 21:28:50 GMT
• Title: The Art of Prompting: Event Detection based on Type Specific Prompts
• Authors: Sijia Wang, Mo Yu, Lifu Huang
• Abstract summary: We develop a unified framework to incorporate the event type specific prompts for supervised, few-shot, and zero-shot event detection. Our framework shows up to 24.3% F-score gain over the previous state-of-the-art baselines.
• Score: 28.878630198163556
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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