Learning to Tell Tales: A Data-driven Approach to Story Generation

Neil McIntyre, Mirella Lapata

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Computational story telling has sparked great interest in artificial intelligence, partly because of its relevance to educational and gaming applications. Traditionally, story generators rely on a large repository of background knowledge containing information about the story plot and its characters. This information is detailed and usually hand crafted. In this paper we propose a data-driven approach for generating short children’s stories that does not require extensive manual involvement. We create an end-to-end system that realizes the various components of the generation pipeline stochastically. Our system follows a generate-and-and-rank approach where the space of multiple candidate stories is pruned by considering whether they are plausible, interesting, and coherent.
Original languageEnglish
Title of host publicationProceedings of the 47th Annual Meeting of the ACL and the 4th IJCNLP of the AFNLP
PublisherAssociation for Computational Linguistics
Number of pages9
Publication statusPublished - 2009


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