Comparing Symbolic Models of Language via Bayesian Inference
Annika Heuser and Polina Tsvilodub, 2021
Published in Proceedings of the AAAI Conference on Artificial Intelligence
Abstract: 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.
Recommended citation: Heuser, A., & Tsvilodub, P. (2021). Comparing Symbolic Models of Language via Bayesian Inference (Student Abstract). In Proceedings of the AAAI Conference on Artificial Intelligence.