Dunn, J. (2019). “Frequency vs. Association for Constraint Selection in Usage-Based Construction Grammar.” In Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics (NAACL 19). Association for Computational Linguistics. 117-128.
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.
[Poster]
[Datasets: https://labbcat.canterbury.ac.nz/download/?jonathandunn/CxG_Data_FixedSize]
Dr. Jonathan Dunn 