Goal-oriented Script Generation is a new task of generating a list of steps that can fulfill the given goal. In this paper, we propose to extend the task from the perspective of cognitive theory. Instead of a simple flat structure, the steps are typically organized hierarchically - Human often decompose a complex task into subgoals, where each subgoal can be further decomposed into steps. To establish the benchmark, we contribute a new dataset, propose several baseline methods, and set up evaluation metrics. Both automatic and human evaluation verify the high-quality of dataset, as well as the effectiveness of incorporating subgoals into hierarchical script generation. Furthermore, We also design and evaluate the model to discover subgoal, and find that it is a bit more difficult to decompose the goals than summarizing from segmented steps.

翻译：目标导向的脚本生成是一项新任务，旨在生成能够实现给定目标的步骤列表。本文从认知理论视角对该任务进行拓展。步骤并非简单的扁平结构，而是通常以层次化方式组织——人类常常将复杂任务分解为子目标，每个子目标可进一步分解为具体步骤。为建立基准，我们贡献了一个新数据集，提出了若干基线方法，并设立了评估指标。自动评估与人工评估均验证了数据集的高质量，以及将子目标融入层次化脚本生成的有效性。此外，我们还设计并评估了子目标发现模型，发现对目标进行分解比从已分段的步骤中归纳更具难度。