Structure Modeling Approach for UD Parsing of Historical Modern Japanese

This study shows the effectiveness of structure modeling for transferability 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 of dictionary-based morphological analysis (MeCab), a deep learning-based phrase (bunsetsu) analysis (Monaka), SVMbased 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.

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.18653/v1/2025.xllm-1.12
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Structure Modeling Approach for UD Parsing of Historical Modern Japanese

Masayuki Asahara, Kanako Komiya, Mai Omura, Toshinobu Ogiso et al.
Natural Language Processing Techniques
article

Structure Modeling Approach for UD Parsing of Historical Modern Japanese

Masayuki Asahara, Kanako Komiya, Mai Omura, Toshinobu Ogiso, Hiroaki Ozaki
article en

Abstract

This study shows the effectiveness of structure modeling for transferability 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 of dictionary-based morphological analysis (MeCab), a deep learning-based phrase (bunsetsu) analysis (Monaka), SVMbased 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.

National Institute for Japanese Language and Linguistics, Japan Society for the Promotion of Science
Openalex Percentile: Top 90%
Natural Language Processing Techniques
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