Modelling Protagonist Goals and Desires in First-Person Narrative
Elahe Rahimtoroghi, Jiaqi Wu, Ruimin Wang, Pranav Anand, Marilyn Walker
Abstract
Many genres of natural language text are narratively structured, a testament to our predilection for organizing our experiences as narratives. There is broad consensus that understanding a narrative requires identifying and tracking the goals and desires of the characters and their narrative outcomes. However, to date, there has been limited work on computational models for this problem. We introduce a new dataset, DesireDB, which includes gold-standard labels for identifying statements of desire, textual evidence for desire fulfillment, and annotations for whether the stated desire is fulfilled given the evidence in the narrative context. We report experiments on tracking desire fulfillment using different methods, and show that LSTM Skip-Thought model achieves F-measure of 0.7 on our corpus.- Anthology ID:
- W17-5543
- Volume:
- Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue
- Month:
- August
- Year:
- 2017
- Address:
- Saarbrücken, Germany
- Editors:
- Kristiina Jokinen, Manfred Stede, David DeVault, Annie Louis
- Venue:
- SIGDIAL
- SIG:
- SIGDIAL
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 360–369
- Language:
- URL:
- https://aclanthology.org/W17-5543
- DOI:
- 10.18653/v1/W17-5543
- Cite (ACL):
- Elahe Rahimtoroghi, Jiaqi Wu, Ruimin Wang, Pranav Anand, and Marilyn Walker. 2017. Modelling Protagonist Goals and Desires in First-Person Narrative. In Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue, pages 360–369, Saarbrücken, Germany. Association for Computational Linguistics.
- Cite (Informal):
- Modelling Protagonist Goals and Desires in First-Person Narrative (Rahimtoroghi et al., SIGDIAL 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/W17-5543.pdf
- Data
- DesireDB, MCTest