One of the things I am really interested in stories is recognizing patterns and ‘motifs’. Vladímir Propp, a scholar in Russian Folktales, had this awesome theory where he broke down Russian folktales into Proppian functions. Moreover, he also assigned roles (dramatis personae) in the stories and analyzed them in his book, Morphology of a Folktale .
Mark A. Finlayson created an annotated corpus, annotating fifteen of the Russian folktales using Propp’s models. His corpus, ProppBank , was a really interesting starting point for me to go deeper into exploring Propp’s work. For my information extraction class project, I intend to look at learning Propp’s dramatis personae through these annotated stories.
I managed to find a copy of Propp’s book Morphology of the Folktale and I finished reading it over the weekend. In the appendix of the book, Propp has a chart where he lists out all the narrative functions for the 45 stories. He doesn’t annotate the text itself, but it’s possible to go manually into the text for the stories and find the characters.
However, Propp doesn’t consider these characters as strictly in the 45 stories as Finlayson does in the 15 specifically chosen examples: a possible problem is that Propp considers them more as spheres. Multiple characters can have the same dramatis personae, and the same character can have multiple dramatis personae (example: princess can turn into donor, helper, etc.)
Propp also breaks down his stories with the concept of moves, which I found pretty interesting. It is much stronger in definition than story arcs, yet it feels intuitive and fairly objective.
I feel I can go ahead and start annotating the stories referring to Propp’s table. I would basically do the following for each story:
– Find the English-translated story text (they’re not present directly in Propp’s book)
– Refer to Propp’s table and find the characters associated with the dramatic personae
– Create a template file for the story, and fill it out.
 Propp, Vladimir. 1968. Morphology of the Folktale. Austin: University of Texas Press.
 Mark A. Finlayson; ProppLearner: Deeply annotating a corpus of Russian folktales to enable the machine learning of a Russian formalist theory, Digital Scholarship in the Humanities, Volume 32, Issue 2, 1 June 2017, Pages 284–300, https://doi.org/10.1093/llc/fqv067