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.

翻译：我们比较了各种形式的事件提示,以代表事件类型,并制定一个统一框架,将事件类型特定提示纳入监督、少发和零发事件的检测。 实验结果表明,定义明确和全面的事件类型快速可以显著改善事件检测的性能,特别是当附加说明的数据稀缺(零发事件检测)或无法获得(零发事件检测)时。 通过利用事件类型的语义,我们的统一框架显示比以往最先进的基线收益高达24.3-F-核心。