Thai Universal Dependency Treebank

TL;DR

This paper introduces the Thai Universal Dependency Treebank, the largest Thai dependency treebank, and evaluates transformer-based dependency parsers trained on it, demonstrating improved performance and providing resources for future research.

Contribution

The creation of the largest Thai dependency treebank aligned with UD standards and systematic benchmarking of transformer-based parsers on Thai data.

Findings

Most models outperform previous results

Insights into optimal parser components for Thai

Resources made publicly available

Abstract

Automatic dependency parsing of Thai sentences has been underexplored, as evidenced by the lack of large Thai dependency treebanks with complete dependency structures and the lack of a published systematic evaluation of state-of-the-art models, especially transformer-based parsers. In this work, we address these problems by introducing Thai Universal Dependency Treebank (TUD), a new largest Thai treebank consisting of 3,627 trees annotated in accordance with the Universal Dependencies (UD) framework. We then benchmark dependency parsing models that incorporate pretrained transformers as encoders and train them on Thai-PUD and our TUD. The evaluation results show that most of our models can outperform other models reported in previous papers and provide insight into the optimal choices of components to include in Thai dependency parsers. The new treebank and every model's full prediction generated in our experiment are made available on a GitHub repository for further study.