Domain Adaptation in Japanese Predicate-Argument Structure Analysis considering First and Second Person Exophora

Abstract

This paper proposes introducing domain adaptation into Japanese predicate-argument structure (PAS) analysis. Our investigation of a Japanese balanced-corpus revealed that the distribution of argument types differs across text media. The difference is particularly significant when the argument is exophoric. Previous Japanese PAS analysis research has disregarded this tendency as studies have targeted mono-media corpora. This investigation begins with a PAS analyzer based on a recurrent neural network as its baseline and extends it by introducing three kinds of domain-adaptation techniques and their combinations. Evaluation experiments using a Japanese balanced-corpus (BCCWJ-PAS) confirmed the domain dependency of the PAS analysis. The domain adaptation is effective in improving the performance of the Japanese PAS analysis, especially in the the nominative case. The maximum F1 score in the QA text analysis (0.030) improved in comparison to the baseline.

Resolving Thai zero pronoun using masked language model

“…This study adopted three kinds of domain-adaptation techniques and their combinations fromSango, Nishikawa, and Tokunaga (2019) 12 i.e., the antecedent (or postcedents) of a given zero pronoun…”