Unlocking Korean Verbs: A User-Friendly Exploration into the Verb Lexicon
Seohyun Song, Eunkyul Leah Jo, Yige Chen, Jeen-Pyo Hong, Kyuwon Kim, Jin Wee, Kang Miyoung, KyungTae Lim
Abstract
The Sejong dictionary dataset offers a valuable resource, providing extensive coverage of morphology, syntax, and semantic representation. This dataset can be utilized to explore linguistic information in greater depth.The labeled linguistic structures within this dataset form the basis for uncovering relationships between words and phrases and their associations with target verbs. This paper introduces a user-friendly web interface designed for the collection and consolidation of verb-related information, with a particular focus on subcategorization frames. Additionally, it outlines our efforts in mapping this information by aligning subcategorization frames with corresponding illustrative sentence examples.Furthermore, we provide a Python library that would simplify syntactic parsing and semantic role labeling. These tools are intended to assist individuals interested in harnessing the Sejong dictionary dataset to develop applications for Korean language processing.
BibTeX
@inproceedings{song-etal-2025-unlocking,
title = "Unlocking {K}orean Verbs: A User-Friendly Exploration into the Verb Lexicon",
author = "Song, Seohyun and
Jo, Eunkyul Leah and
Chen, Yige and
Hong, Jeen-Pyo and
Kim, Kyuwon and
Wee, Jin and
Miyoung, Kang and
Lim, KyungTae and
Park, Jungyeul and
Park, Chulwoo",
editor = "Dziri, Nouha and
Ren, Sean (Xiang) and
Diao, Shizhe",
booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (System Demonstrations)",
month = apr,
year = "2025",
address = "Albuquerque, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.naacl-demo.24/",
pages = "287--294",
ISBN = "979-8-89176-191-9"
}