Towards a Machine-Readable Classification System based on Thompson's Motif-Index: A Case Study on South American Indigenous Narratives

Thompson's Motif-Index (TMI) is one of the most important classificatory references within folklore studies. However, leveraging its potential within contemporary digital methodologies presents us with a manifold of problems. The paper explores general issues and operational limits of the TMI, discusses possible solutions, and ultimately presents a proof of concept to reimagine motifs as labeled digraphs. It does so along a subset of 1,969 narratives from Johannes Wilbert and Karin Simoneau's Folk Literature of the South American Indians (1970–1992) as well as their 23,624 individual motif assignments.