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We compare various forms of prompts to represent event types and develop aunified framework to incorporate the event type specific prompts forsupervised, few-shot, and zero-shot event detection. The experimental resultsdemonstrate that a well-defined and comprehensive event type prompt cansignificantly improve the performance of event detection, especially when theannotated data is scarce (few-shot event detection) or not available (zero-shotevent detection). By leveraging the semantics of event types, our unifiedframework shows up to 24.3\% F-score gain over the previous state-of-the-artbaselines.

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