Towards Harnessing the Most of ChatGPT for Korean Grammatical Error Correction

Chanjun Park; Seonmin Koo; Gyeongmin Kim; Heuiseok Lim

doi:10.3390/app14083195

Towards Harnessing the Most of ChatGPT for Korean Grammatical Error Correction

Chanjun Park, Seonmin Koo, Gyeongmin Kim, Heuiseok Lim

Research output: Contribution to journal › Article › peer-review

Abstract

In this study, we conduct a pioneering and comprehensive examination of ChatGPT’s (GPT-3.5 Turbo) capabilities within the realm of Korean Grammatical Error Correction (K-GEC). Given the Korean language’s agglutinative nature and its rich linguistic intricacies, the task of accurately correcting errors while preserving Korean-specific sentiments is notably challenging. Utilizing a systematic categorization of Korean grammatical errors, we delve into a meticulous, case-specific analysis to identify the strengths and limitations of a ChatGPT-based correction system. We also critically assess influential parameters like temperature and specific error criteria, illuminating potential strategies to enhance ChatGPT’s efficacy in K-GEC tasks. Our findings offer valuable contributions to the expanding domain of NLP research centered on the Korean language.

Original language	English
Article number	3195
Journal	Applied Sciences (Switzerland)
Volume	14
Issue number	8
DOIs	https://doi.org/10.3390/app14083195
Publication status	Published - 2024 Apr

Bibliographical note

Publisher Copyright:
© 2024 by the authors.

Keywords

ChatGPT
K-NCT
Korean grammatical error correction
large language model

ASJC Scopus subject areas

General Materials Science
Instrumentation
General Engineering
Process Chemistry and Technology
Computer Science Applications
Fluid Flow and Transfer Processes

Access to Document

10.3390/app14083195

Cite this

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abstract = "In this study, we conduct a pioneering and comprehensive examination of ChatGPT{\textquoteright}s (GPT-3.5 Turbo) capabilities within the realm of Korean Grammatical Error Correction (K-GEC). Given the Korean language{\textquoteright}s agglutinative nature and its rich linguistic intricacies, the task of accurately correcting errors while preserving Korean-specific sentiments is notably challenging. Utilizing a systematic categorization of Korean grammatical errors, we delve into a meticulous, case-specific analysis to identify the strengths and limitations of a ChatGPT-based correction system. We also critically assess influential parameters like temperature and specific error criteria, illuminating potential strategies to enhance ChatGPT{\textquoteright}s efficacy in K-GEC tasks. Our findings offer valuable contributions to the expanding domain of NLP research centered on the Korean language.",

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Towards Harnessing the Most of ChatGPT for Korean Grammatical Error Correction

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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