Modeling Narrative Structure in Latin Epic Poetry with Automatically Generated Story Grammars

ArXi:2502.12276v2 Announce Type: replace Computational methods for analyzing prose and poetry utilize word embeddings and other abstract representations that sometimes obscure context-rich literary text. Inspired by the psychology of reading, we utilize story structure and elements to simulate human narrative comprehension to produce a comprehensive representation of literary text. We present a method for automatically generating story grammar labels for input texts as a means of analysis that is interpretable and accessible by humanists and technologists alike.