Multi-Agent System for AI-Assisted Extraction of Narrative Arcs in TV Series

Roberto Balestri, Guglielmo Pescatore

2025

Abstract

Serialized TV shows are built on complex storylines that can be hard to track and evolve in ways that defy straightforward analysis. This paper introduces a multi-agent system designed to extract and analyze these narrative arcs. Tested on the first season of Grey’s Anatomy (ABC 2005-), the system identifies three types of arcs: Anthology (self-contained), Soap (relationship-focused), and Genre-Specific (strictly related to the series’ genre). Episodic progressions of these arcs are stored in both relational and semantic (vectorial) databases, enabling structured analysis and comparison. To bridge the gap between automation and critical interpretation, the system is paired with a graphical interface that allows for human refinement using tools to enhance and visualize the data. The system performed strongly in identifying Anthology Arcs and character entities, but its reliance on textual paratexts (such as episode summaries) revealed limitations in recognizing overlapping arcs and subtler dynamics. This approach highlights the potential of combining computational and human expertise in narrative analysis. Beyond television, it offers promise for serialized written formats, where the narrative resides entirely in the text. Future work will explore the integration of multimodal inputs, such as dialogue and visuals, and expand testing across a wider range of genres to refine the system further.

Paper Citation

in Harvard Style

Balestri R. and Pescatore G. (2025). Multi-Agent System for AI-Assisted Extraction of Narrative Arcs in TV Series. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 663-670. DOI: 10.5220/0013369600003890

in Bibtex Style

@conference{icaart25,
author={Roberto Balestri and Guglielmo Pescatore},
title={Multi-Agent System for AI-Assisted Extraction of Narrative Arcs in TV Series},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2025},
pages={663-670},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013369600003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Multi-Agent System for AI-Assisted Extraction of Narrative Arcs in TV Series
SN - 978-989-758-737-5
AU - Balestri R.
AU - Pescatore G.
PY - 2025
SP - 663
EP - 670
DO - 10.5220/0013369600003890
PB - SciTePress