Using Language Models to Improve Rule-based Linguistic Annotation of Modern Historical Japanese Corpora

1 code implementation • LaTeCHCLfL (COLING) 2022 • Jerry Bonnell, Mitsunori Ogihara

To address both points for the case of Modern Historical Japanese text, this paper proposes the use of unsupervised domain adaptation methods to develop a domain-adapted language model (LM) that can flag instances of inaccurate UD output from a pretrained LM and the use of these instances to form rules that, when applied, improves pretrained annotation accuracy.

Dependency Parsing Language Modelling +1