Predicting Proppian Narrative Functions from Stories in Natural Language. Valls-Vargas, J., Zhu, J., & Ontañón, S. In Proceedings of the Twelfth Artificial Intelligence and Interactive Digital Entertainment Conference, 2016. ![Predicting Proppian Narrative Functions from Stories in Natural Language [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper abstract bibtex Computational narrative systems usually require knowledge about the story world and narrative theory to be encoded in some form of structured knowledge representation formalism, a notoriously time-consuming task requiring expertise in both storytelling and knowledge engineering. In this paper we present an approach that combines supervised machine learning with narrative domain knowledge toward automatically extracting such knowledge from natural language stories, focusing specifically on predicting Proppian narrative functions. Our experiments on a dataset of Russian fairy tales show that our system outperforms an informed baseline and that combining top-down narrative theory and bottom-up statistical models inferred from an annotated dataset increases prediction accuracy with respect to using them in isolation.
@inproceedings{valls2016predicting,
Abstract = {Computational narrative systems usually require knowledge about the story world and narrative theory to be encoded in some form of structured knowledge representation formalism, a notoriously time-consuming task requiring expertise in both storytelling and knowledge engineering. In this paper we present an approach that combines supervised machine learning with narrative domain knowledge toward automatically extracting such knowledge from natural language stories, focusing specifically on predicting Proppian narrative functions. Our experiments on a dataset of Russian fairy tales show that our system outperforms an informed baseline and that combining top-down narrative theory and bottom-up statistical models inferred from an annotated dataset increases prediction accuracy with respect to using them in isolation.},
Author = {Valls-Vargas, Josep and Zhu, Jichen and Onta{\~n}{\'o}n, Santiago},
Booktitle = {Proceedings of the Twelfth Artificial Intelligence and Interactive Digital Entertainment Conference},
Keywords = {computational narrative, information extraction, NLP, Propp},
Title = {Predicting Proppian Narrative Functions from Stories in Natural Language},
Url = {http://www.aaai.org/ocs/index.php/AIIDE/AIIDE16/paper/view/13989/13602},
Year = {2016},
JV-Q = {Automatically identifying Proppian functions from text segments.}
}
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