Schema induction builds a graph representation explaining how events unfold in a scenario. Existing approaches have been based on information retrieval (IR) and information extraction(IE), often with limited human curation. We demonstrate a human-in-the-loop schema induction system powered by GPT-3. We first describe the different modules of our system, including prompting to generate schematic elements, manual edit of those elements, and conversion of those into a schema graph. By qualitatively comparing our system to previous ones, we show that our system not only transfers to new domains more easily than previous approaches, but also reduces efforts of human curation thanks to our interactive interface.
翻译:Schema 感应( Schema improduction) 构建了一个图表, 解释事件在情景中如何演化。 现有方法基于信息检索和信息提取( IE), 通常只有有限的人类整理。 我们展示了一个由 GPT-3 驱动的“ 人到人到人到人到人到人到人到人到人到人到人到人到人到人到人到人到。 我们首先描述了我们系统的不同模块, 包括催促生成示性元素, 手工编辑这些元素, 并将这些元素转换成一个系统图。 通过将我们的系统与以前的系统进行定性比较, 我们显示我们的系统不仅比以前的方法更容易传输到新领域, 而且还由于我们的互动界面而减少了人类的整理努力 。</s>