Coherent Story Generation with Structured Knowledge

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Abstract

The emergence of pre-trained language models has taken story generation, which is the task of automatically generating a comprehensible story from limited information, to a new stage. Although generated stories from the language models are fluent and grammatically correct, the lack of coherence affects their quality. We propose a knowledge-based multi-stage model that incorporates the schema, a kind of structured knowledge, to guide coherent story generation. Our framework includes a schema acquisition module, a plot generation module, and a surface realization module. In the schema acquisition module, high-relevant structured knowledge pieces are selected as a schema. In the plot generation module, a coherent plot plan is navigated by the schema. In the surface realization module, conditioned by the generated plot, a story is generated. Evaluations show that our methods can generate more comprehensible stories than strong baselines, especially with higher global coherence and less repetition.

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APA

Ma, C., Funakoshi, K., Shirai, K., & Okumura, M. (2023). Coherent Story Generation with Structured Knowledge. In International Conference Recent Advances in Natural Language Processing, RANLP (pp. 681–690). Incoma Ltd. https://doi.org/10.26615/978-954-452-092-2_074

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