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Main Authors: Sung, Hakyung, Shin, Gyu-Ho
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2503.14718
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author Sung, Hakyung
Shin, Gyu-Ho
author_facet Sung, Hakyung
Shin, Gyu-Ho
contents We expand the second language (L2) Korean Universal Dependencies (UD) treebank with 5,454 manually annotated sentences. The annotation guidelines are also revised to better align with the UD framework. Using this enhanced treebank, we fine-tune three Korean language models and evaluate their performance on in-domain and out-of-domain L2-Korean datasets. The results show that fine-tuning significantly improves their performance across various metrics, thus highlighting the importance of using well-tailored L2 datasets for fine-tuning first-language-based, general-purpose language models for the morphosyntactic analysis of L2 data.
format Preprint
id arxiv_https___arxiv_org_abs_2503_14718
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Second language Korean Universal Dependency treebank v1.2: Focus on data augmentation and annotation scheme refinement
Sung, Hakyung
Shin, Gyu-Ho
Computation and Language
We expand the second language (L2) Korean Universal Dependencies (UD) treebank with 5,454 manually annotated sentences. The annotation guidelines are also revised to better align with the UD framework. Using this enhanced treebank, we fine-tune three Korean language models and evaluate their performance on in-domain and out-of-domain L2-Korean datasets. The results show that fine-tuning significantly improves their performance across various metrics, thus highlighting the importance of using well-tailored L2 datasets for fine-tuning first-language-based, general-purpose language models for the morphosyntactic analysis of L2 data.
title Second language Korean Universal Dependency treebank v1.2: Focus on data augmentation and annotation scheme refinement
topic Computation and Language
url https://arxiv.org/abs/2503.14718