Automated Storytelling via Causal, Commonsense Plot Ordering

TL;DR

This paper introduces C2PO, a novel approach for automated story generation that leverages soft causal relations inferred from commonsense reasoning to improve story coherence and quality.

Contribution

It proposes the concept of soft causal relations for narrative generation and demonstrates their effectiveness through human evaluations across different storytelling genres.

Findings

Soft causal relations enhance perceived story coherence.

C2PO outperforms baseline systems in human evaluations.

Genre influences perceptions of story quality.

Abstract

Automated story plot generation is the task of generating a coherent sequence of plot events. Causal relations between plot events are believed to increase the perception of story and plot coherence. In this work, we introduce the concept of soft causal relations as causal relations inferred from commonsense reasoning. We demonstrate C2PO, an approach to narrative generation that operationalizes this concept through Causal, Commonsense Plot Ordering. Using human-participant protocols, we evaluate our system against baseline systems with different commonsense reasoning reasoning and inductive biases to determine the role of soft causal relations in perceived story quality. Through these studies we also probe the interplay of how changes in commonsense norms across storytelling genres affect perceptions of story quality.