Abstract
People can identify correspondences between narratives in everyday life. For example, an analogy with the Cinderella story may be made in describing the unexpected success of an underdog in seemingly different stories. We present a new task and dataset for story understanding: identifying instances of similar narratives from a collection of narrative texts. We present an initial approach for this problem, which finds correspondences between narratives in terms of plot events, and resemblances between characters and their social relationships. Our approach yields an 8% absolute improvement in performance over a competitive information-retrieval baseline on a novel dataset of plot summaries of 577 movie remakes from Wikipedia.- Anthology ID:
- N18-2106
- Volume:
- Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana
- Editors:
- Marilyn Walker, Heng Ji, Amanda Stent
- Venue:
- NAACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 673–678
- Language:
- URL:
- https://aclanthology.org/N18-2106
- DOI:
- 10.18653/v1/N18-2106
- Cite (ACL):
- Snigdha Chaturvedi, Shashank Srivastava, and Dan Roth. 2018. Where Have I Heard This Story Before? Identifying Narrative Similarity in Movie Remakes. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), pages 673–678, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- Where Have I Heard This Story Before? Identifying Narrative Similarity in Movie Remakes (Chaturvedi et al., NAACL 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/N18-2106.pdf