Unlocking Korean Verbs: A User-Friendly Exploration into the Verb Lexicon

TL;DR

This paper presents a user-friendly web interface and Python tools for exploring and utilizing the Sejong dictionary dataset to enhance Korean verb processing and linguistic analysis.

Contribution

It introduces a web interface and Python library for collecting, mapping, and analyzing Korean verb information from the Sejong dataset, facilitating language processing applications.

Findings

Developed a web interface for verb information collection

Created a Python library for syntactic parsing and semantic role labeling

Mapped subcategorization frames with illustrative sentence examples

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.