Abstract
Expectation-based theories of sentence processing posit that processing difficulty is determined by predictability in context. While predictability quantified via surprisal has gained empirical support, this representation-agnostic measure leaves open the question of how to best approximate the human comprehender’s latent probability model. This work presents an incremental left-corner parser that incorporates information about both propositional content and syntactic categories into a single probability model. This parser can be trained to make parsing decisions conditioning on only one source of information, thus allowing a clean ablation of the relative contribution of propositional content and syntactic category information. Regression analyses show that surprisal estimates calculated from the full parser make a significant contribution to predicting self-paced reading times over those from the parser without syntactic category information, as well as a significant contribution to predicting eye-gaze durations over those from the parser without propositional content information. Taken together, these results suggest a role for propositional content and syntactic category information in incremental sentence processing.- Anthology ID:
- 2021.cmcl-1.28
- Volume:
- Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics
- Month:
- June
- Year:
- 2021
- Address:
- Online
- Editors:
- Emmanuele Chersoni, Nora Hollenstein, Cassandra Jacobs, Yohei Oseki, Laurent Prévot, Enrico Santus
- Venue:
- CMCL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 241–250
- Language:
- URL:
- https://aclanthology.org/2021.cmcl-1.28
- DOI:
- 10.18653/v1/2021.cmcl-1.28
- Cite (ACL):
- Byung-Doh Oh and William Schuler. 2021. Contributions of Propositional Content and Syntactic Category Information in Sentence Processing. In Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics, pages 241–250, Online. Association for Computational Linguistics.
- Cite (Informal):
- Contributions of Propositional Content and Syntactic Category Information in Sentence Processing (Oh & Schuler, CMCL 2021)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2021.cmcl-1.28.pdf
- Data
- Natural Stories