论文标题
提示艺术：基于类型特定提示的事件检测
The Art of Prompting: Event Detection based on Type Specific Prompts
论文作者
论文摘要
我们比较各种形式的提示，以表示事件类型并开发一个统一的框架，以合并事件类型的特定提示，以进行监督，很少射击和零照片事件检测。实验结果表明，定义明确且全面的事件类型提示可以显着改善事件检测的性能，尤其是当稀缺的注释数据（少数事件检测）或不可用时（零照片事件检测）。通过利用事件类型的语义，我们的统一框架比以前的最新基线显示高达24.3 \％的F分数增益。
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.
