Abstract
This paper presents the Character Decision Points Detection (CHADPOD) task, a task of identification of points within narratives where characters make decisions that may significantly influence the story’s direction. We propose a novel dataset based on Choose Your Own Adventure (a registered trademark of Chooseco LLC) games graphs to be used as a benchmark for such a task. We provide a comparative analysis of different models’ performance on this task, including a couple of LLMs and several MLMs as baselines, achieving up to 89% accuracy. This underscores the complexity of narrative analysis, showing the challenges associated with understanding character-driven story dynamics. Additionally, we show how such a model can be applied to the existing text to produce linear segments divided by potential branching points, demonstrating the practical application of our findings in narrative analysis.- Anthology ID:
- 2024.games-1.8
- Volume:
- Proceedings of the 10th Workshop on Games and Natural Language Processing @ LREC-COLING 2024
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Chris Madge, Jon Chamberlain, Karen Fort, Udo Kruschwitz, Stephanie Lukin
- Venues:
- games | WS
- SIG:
- Publisher:
- ELRA and ICCL
- Note:
- Pages:
- 70–75
- Language:
- URL:
- https://aclanthology.org/2024.games-1.8
- DOI:
- Cite (ACL):
- Alexey Tikhonov. 2024. Branching Narratives: Character Decision Points Detection. In Proceedings of the 10th Workshop on Games and Natural Language Processing @ LREC-COLING 2024, pages 70–75, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- Branching Narratives: Character Decision Points Detection (Tikhonov, games-WS 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.games-1.8.pdf