Comparing Symbolic Models of Language via Bayesian Inference (Student Abstract)
Annika Heuser, Polina Tsvilodub · Proceedings of the AAAI Conference on Artificial Intelligence · 2021
Given recurring interest in structured representations in computational cognitive models, we extend a Bayesian scoring procedure for comparing symbolic models of language grammar. We conduct a case-study of modeling syntactic principles in German, providing preliminary results consistent with linguistic theory. We also note that dataset and part-of-speech (POS) tagger quality should not be taken for granted.