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Inferring Propp’s Functions from Semantically Annotated Text
Abstract
Vladimir Propp’s Morphology of the Folktale is a seminal work in folkloristics and a compelling subject of computational study. I demonstrate a technique for learning Propp’s functions from semantically annotated text. Fifteen folktales from Propp’s corpus were annotated for semantic roles, co-reference, temporal structure, event sentiment, and dramatis personae. I derived a set of merge rules from descriptions given by Propp. These rules, when coupled with a modified version of the model merging learning framework, reproduce Propp’s functions well. Three important function groups--namely A/a (villainy/lack), H/I (struggle and victory), and W (reward)--are identified with high accuracies. This is the first demonstration of a computational system learning a real theory of narrative structure.
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“In 'Inferring Propp's Functions from Semantically Annotated text' (2016) Finlayson demonstrates a technique for learning Propp's functions from semantically annotated texts.”
From The Thirty-One Functions in Vladimir Propp’s Morphology of the Folktale: An Outline and Recent Trends in the Applicability of the Proppian Taxonomic Model (2017) · cites this paper as Finlayson, 2016
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“The Proppian template as a subject of machine learning can be of wider applicability if the morphology could be 'automatically' extracted.”
From The Thirty-One Functions in Vladimir Propp’s Morphology of the Folktale: An Outline and Recent Trends in the Applicability of the Proppian Taxonomic Model (2017) · cites this paper as Finlayson, 2016
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- 2. ---. 1975. Russian Fairy Tales, trans. Norbert Guterman. New York: Pantheon Books.
- 3. Agirre, Eneko, and Philip Edmonds, eds. 2007. Word Sense Disambiguation. Dordrecht: Springer. · DOI
- 4. Bird, Steven, and Mark Liberman. 2001. A Formal Framework for Linguistic Annotation. Speech Communication 33(1-2):23-60. · DOI
- 5. Carletta, Jean. 1996. Assessing Agreement on Classification Tasks: The Kappa Statistic. Computational Linguistics 22(2):249-54.
- 6. Chambers, Nathanael, and Daniel Jurafsky. 2008. Unsupervised Learning of Narrative Event Chains. Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics, pp. 789-97, Columbus, OH.
- 7. ---. 2009. Unsupervised Learning of Narrative Schemas and Their Participants. Proceedings of the 47th Annual Meeting of the Association for Computational Linguistics, pp. 602-10, Suntec. · DOI
- 8. Colby, Benjamin. 1973. A Partial Grammar of Eskimo Folktales. American Anthropologist 75(3):645-62. · DOI
- 9. Díaz-Agudo, Belén, Pablo Gervás, and Federico Peinado. 2004. A Case Based Reasoning Approach to Story Plot Generation. In Proceedings of the European Conference on Case Based Reasoning (ECCBR), pp. 142-56, Madrid. · DOI
- 11. Fellbaum, Christiane, ed. 1998. Wordnet: An Electronic Lexical Database. Cambridge, MA: MIT Press. · DOI
- 12. Finlayson, Mark Alan. 2008. Collecting Semantics in the Wild: The Story Workbench. In Proceedings of the AAAI Fall Symposium on Naturally Inspired Artificial Intelligence, pp. 46-53, Washington, DC.
- 13. ---. 2009. Deriving Narrative Morphologies via Analogical Story Merging. In New Frontiers in Analogy Research (Proceedings of the 2nd International Conference on Analogy), ed. Boris Kokinov, Keith Holyoak, and Dedre Gentner, pp. 127-36. Sofia: New Bulgarian University Press.
- 14. ---. 2010a. Learning Narrative Morphologies from Annotated Folktales. In Proceedings of the 1st Automated Motif Discovery in Cultural Heritage and Scientific Communication Texts (AMICUS) Workshop, pp. 99-102, Vienna.
- 15. ---. 2010b. The Story Workbench: An Extensible Semi-Automatic Text Annotation Tool. In Proceedings of the 4th Workshop on Intelligent Narrative Technologies (INT-4), pp. 21-4, Stanford, CA. · DOI
- 17. Fischer, J. L. 1963. The Sociopsychological Analysis of Folktales. Current Anthropology 4(3):235-95. · DOI
- 18. Gazdar, Gerald, Ewan Klein, Geoffrey K. Pullum, and Ivan A. Sag. 1985. Generalized Phrase Structure Grammar. Oxford: Basil Blackwell.
- 19. Gildea, Daniel, and Daniel Jurafsky. 2002. Automatic Labeling of Semantic Roles. Computational Linguistics 28(3):245-88. · DOI
- 20. Goodman, Joshua. 2000. Probabilistic Feature Grammars. In Advances in Probabilistic and Other Parsing Technologies, ed. Harry Bunt and Anton Nijholt, pp. 63-84. Dordrecht: Springer. · DOI
- 22. Halpin, Harry, Johanna Moore, and Judy Robertson. 2004. Automatic Analysis of Plot for Story Rewriting. In Proceedings of the Conference on Experimental Methods in Natural Language Processing (EMNLP), pp. 127-33, Barcelona.
- 23. Hervás, Raquel, and Mark Alan Finlayson. 2010. The Prevalence of Descriptive Referring Expressions in News and Narrative. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, pp. 49-54, Uppsala.
- 24. Higuera, Colin de la. 2010. Grammatical Inference: Learning Automata and Grammars. Cambridge: University of Cambridge Press.
- 25. Hubert, Lawrence, and Phipps Arabie. 1985. Comparing Partitions. Journal of Classification 2(1):193-218. · DOI · Paper page
- 27. Lehnert, Wendy G. 1981. Plot Units and Narrative Summarization. Cognitive Science 5(4):293-331. · DOI
- 28. Lévi-Strauss, Claude. 1978. Myth and Meaning. New York: Routledge. · DOI
- 29. Omohundro, Stephen M. 1992. Best-First Model Merging for Dynamic Learning and Recognition. In Advances in Neural Information Processing Systems 5, ed. John E. Moody, Stephen J. Hanson, and Richard P. Lippmann, pp. 958-965. San Mateo, CA: Morgan Kaufmann.
- 30. Palmer, Martha, Paul Kingsbury, and Daniel Gildea. 2005. The Proposition Bank: An Annotated Corpus of Semantic Roles. Computational Linguistics 31(1):71-105. · DOI
- 31. Pradhan, Sameer, Kadri Hacioglu, Valerie Krugler, Wayne Ward, James H. Martin, and Daniel Jurky. 2005. Support Vector Learning for Semantic Argument Classification. Machine Learning 60(1-3):11-39. · DOI
- 32. Propp, Vladimir. [1928] 1968. Morphology of the Folktale (2nd edition), trans. Laurence Scott. Austin: University of Texas Press. · DOI
- 33. Pustejovsky, James, Jose Castano, Robert Ingria, Roser Sauri, Robert Gaizauskas, Andrea Setzer, and Graham Katz. 2003. TimeML: Robust Specification of Event and Temporal Expressions in Text. In Proceedings of Fifth International Workshop on Computational Semantics (IWCS-5), p. 193, Tilberg.
- 34. Regneri, Michaela, Alexander Koller, and Manfred Pinkal. 2010. Learning Script Knowledge with Web Experiments. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, pp. 979-88, Uppsala.
- 35. Rota, Gian-Carlo. 1964. The Number of Partitions of a Set. American Mathematical Monthly 71(5):498-504. · DOI
- 37. Stolcke, Andreas, and Stephen Omohundro. 1994. Inducing Probabilistic Grammars by Bayesian Model Merging. In Grammatical Inference and Applications, ed. Rafael C. Carrasco and Jose Oncina, pp. 106-18. Berlin: Springer. · DOI
- 38. van Rijsbergen, C. J. 1979. Evaluation. In Information Retrieval, by C. J. van Rijsbergen, pp. 112-40. London: Butterworths.
- 39. Young-Lai, Matthew. 2009. Grammar Inference. In Encyclopedia of Database Systems, ed. Ling Liu and M. Tamer Ozsu, pp. 1256-60. Berlin: Springer. · DOI
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Jawaharlal Nehru University, & Dogra, S. (2017) · Rupkatha Journal on Interdisciplinary Studies in Humanities · doi:10.21659/rupkatha.v9n2.41 · Cited by 10
Metadata
- Authors
- Finlayson, M. A.
- Corresponding author
- Finlayson, Mark Alan
- ORCID
- Finlayson, Mark Alan
- Venue
- Journal of American Folklore
- Publisher
- University of Illinois Press
- Published
- 2016-01-01
- Volume
- 129
- Issue
- 511
- Pages
- 55-77
- ISSN
- 0021-8715 (ISSN-L)
- 1535-1882
- OpenAlex
- W2332793758
- Cited by
- 31
- References
- 0
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 3 · 2023: 5 · 2022: 3 · 2021: 3 · 2020: 2 · 2019: 3 · 2018: 4 · 2017: 3
- FWCI
- 44.58
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of American Folklore (publishedVersion)
- Project Muse (Johns Hopkins University) (submittedVersion)
- Topics
- Social Sciences › Arts and Humanities › Literature and Literary Theory › Folklore, Mythology, and Literature Studies
- Social Sciences › Arts and Humanities › Literature and Literary Theory › Digital Humanities and Scholarship
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Keywords
- Vladimir Propp, Morphology of the Folktale, folk tales, narrative structure, semantic annotation, thematic roles, coreference, temporal structure, dramatic characters
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