From Show Programmes to Data: Designing a Workflow to Make Performing Arts Ephemera Accessible Through Language Models

Clarisse Bardiot; Pierre-Carl Langlais; Bernard Jacquemin; Jacob Hart; Antonios Lagarias; Nicolas Foucault; Aurélie Lemaître-Legargeant; Jeanne Fras

arXiv · 2512.07452

From Show Programmes to Data: Designing a Workflow to Make Performing Arts Ephemera Accessible Through Language Models

Clarisse Bardiot·Pierre-Carl Langlais·Bernard Jacquemin·Jacob Hart·Antonios Lagarias·Nicolas Foucault·Aurélie Lemaître-Legargeant·Jeanne Fras

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Abstract

Many heritage institutions hold extensive collections of theatre programmes, which remain largely underused due to their complex layouts and lack of structured metadata. In this paper, we present a workflow for transforming such documents into structured data using a combination of multimodal large language models (LLMs), an ontology-based reasoning model, and a custom extension of the Linked Art framework. We show how vision-language models can accurately parse and transcribe born-digital and digitised programmes, achieving over 98% of correct extraction. To overcome the challenges of semantic annotation, we train a reasoning model (POntAvignon) using reinforcement learning with both formal and semantic rewards. This approach enables automated RDF triple generation and supports alignment with existing knowledge graphs. Through a case study based on the Festival d'Avignon corpus, we demonstrate the potential for large-scale, ontology-driven analysis of performing arts data. Our results open new possibilities for interoperable, explainable, and sustainable computational theatre historiography.

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Clarisse Bardiot, Pierre-Carl Langlais, Bernard Jacquemin, Jacob Hart, Antonios Lagarias, Nicolas Foucault, Aurélie Lemaître-Legargeant, Jeanne Fras. 2025-12-08. From Show Programmes to Data: Designing a Workflow to Make Performing Arts Ephemera Accessible Through Language Models. https://arxiv.org/abs/2512.07452

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