Structure Modeling Approach for UD Parsing of Historical Modern Japanese

AbstractThis study shows the effectiveness of structure modeling for transfer ability in diachronic syntactic parsing. The syntactic parsing for historical languages is significant from a humanities and quantitative linguistics perspective to enable annotation support and analysis on unannotated documents.We compared the zero-shot transfer ability between Transformer-based Biaffine UD parsers and our structure modeling approach. The structure modeling approach is a pipeline method consisting with dictionary-based morphological analysis (MeCab), a deep learning-based phrase (bunsetsu) analysis (Monaka), SVM-based phrase dependency parsing (CaboCha) and a rule-based conversion from phrase dependencies to UD.This pipeline closely follows the methodology used in constructing Japanese UD corpora.Experimental results showed that the structure modeling approach outperformed zero-shot transfer from the contemporary to the modern Japanese. Moreover, the structure modeling approach outperformed several existing UD parsers in contemporary Japanese. To this end, the structure modeling approach outperformed in the diachronic transfer of Japanese by a wide margin and was useful to those applications for digital humanities and quantitative linguistics.