GisPy: A Tool for Measuring Gist Inference Score in Text
Pedram Hosseini, Christopher Wolfe, Mona Diab, David Broniatowski
Abstract
Decision making theories such as Fuzzy-Trace Theory (FTT) suggest that individuals tend to rely on gist, or bottom-line meaning, in the text when making decisions. In this work, we delineate the process of developing GisPy, an opensource tool in Python for measuring the Gist Inference Score (GIS) in text. Evaluation of GisPy on documents in three benchmarks from the news and scientific text domains demonstrates that scores generated by our tool significantly distinguish low vs. high gist documents. Our tool is publicly available to use at: https: //github.com/phosseini/GisPy.- Anthology ID:
- 2022.wnu-1.5
- Volume:
- Proceedings of the 4th Workshop of Narrative Understanding (WNU2022)
- Month:
- July
- Year:
- 2022
- Address:
- Seattle, United States
- Venue:
- WNU
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 38–46
- Language:
- URL:
- https://aclanthology.org/2022.wnu-1.5
- DOI:
- 10.18653/v1/2022.wnu-1.5
- Cite (ACL):
- Pedram Hosseini, Christopher Wolfe, Mona Diab, and David Broniatowski. 2022. GisPy: A Tool for Measuring Gist Inference Score in Text. In Proceedings of the 4th Workshop of Narrative Understanding (WNU2022), pages 38–46, Seattle, United States. Association for Computational Linguistics.
- Cite (Informal):
- GisPy: A Tool for Measuring Gist Inference Score in Text (Hosseini et al., WNU 2022)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/2022.wnu-1.5.pdf
- Code
- phosseini/GisPy