Event-driven story writing aims to create coherent stories that conform to event content based on limited background and event information.However,existing methods often suffer from semantic incoherence and plot conflicts due to insufficient reasoning about complex event relationships.To address these problems,a method for event-driven story writing based on three-act structural chain-of-thought and semantic self-consistency is proposed in this paper.Before generating the story,diverse story examples are selected to enable the model to learn different storytelling styles.During the story generation,a chain-of-thought is designed based on three-act structure of setup,confrontation and resolution,guiding the model to reasonably plan the story content and avoid plot inconsistencies.After the story is generated,semantic self-consistency is introduced to simulate the writer's deliberation process,selecting the most semantically consistent,coherent and relevant story from multiple generated versions.Experiments show that the proposed method improves BLEU-4 and BERTScore metrics and demonstrates certain advantages in human evaluations as well.
关键词
事件驱动故事生成/大规模语言模型/语义自恰/三幕结构思维链
Key words
Event-Driven Story Writing/Large Language Model/Semantic Self-Consistency/Three-Act Structural Chain-of-Thought
维普
万方数据