Abstract
A usage-based Construction Grammar (CxG) posits that slot-constraints generalize from common exemplar constructions. But what is the best model of constraint generalization? This paper evaluates competing frequency-based and association-based models across eight languages using a metric derived from the Minimum Description Length paradigm. The experiments show that association-based models produce better generalizations across all languages by a significant margin.- Anthology ID:
- W19-2913
- Volume:
- Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics
- Month:
- June
- Year:
- 2019
- Address:
- Minneapolis, Minnesota
- Editors:
- Emmanuele Chersoni, Cassandra Jacobs, Alessandro Lenci, Tal Linzen, Laurent Prévot, Enrico Santus
- Venue:
- CMCL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 117–128
- Language:
- URL:
- https://aclanthology.org/W19-2913
- DOI:
- 10.18653/v1/W19-2913
- Cite (ACL):
- Jonathan Dunn. 2019. Frequency vs. Association for Constraint Selection in Usage-Based Construction Grammar. In Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics, pages 117–128, Minneapolis, Minnesota. Association for Computational Linguistics.
- Cite (Informal):
- Frequency vs. Association for Constraint Selection in Usage-Based Construction Grammar (Dunn, CMCL 2019)
- PDF:
- https://preview.aclanthology.org/teach-a-man-to-fish/W19-2913.pdf