In this paper, we introduce the task of modeling interpersonal relationships
for story generation. For addressing this task, we propose Relationships as
Latent Variables for Story Generation, (ReLiSt). ReLiSt generates stories
sentence by sentence and has two major components - a relationship selector and
a story continuer. The relationship selector specifies a latent variable to
pick the relationship to exhibit in the next sentence and the story continuer
generates the next sentence while expressing the selected relationship in a
coherent way. Our automatic and human evaluations demonstrate that ReLiSt is
able to generate stories with relationships that are more faithful to desired
relationships while maintaining the content quality. The relationship
assignments to sentences during inference bring interpretability to ReLiSt.

该论文介绍了一项关于人际关系建模的任务，提出了一种基于关系选择器和故事继续器两个主要组成部分的故事生成算法 ReLiSt，在自动和人工评估中展示出了其生成的故事能够更加忠实于期望的关系而不影响内容质量，推断过程中的关系分配带来了 ReLiSt 的可解释性。