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.

本文从认知理论的角度扩展了目标导向脚本生成的任务，并提出了基于子目标的层次化组织方法。研究者们贡献了一个新的数据集，并提出了几种基线方法和评估指标，表明了子目标与层次化脚本生成的有效性。此外，研究者们还设计和评估了发现子目标的模型，并发现此过程比从分段步骤中进行摘要更加困难。