Towards Harnessing the Most of ChatGPT for Korean Grammatical Error Correction

  • Chanjun Park
  • , Seonmin Koo
  • , Gyeongmin Kim
  • , Heuiseok Lim*
  • *Corresponding author for this work

    Research output: Contribution to journalArticlepeer-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 languageEnglish
    Article number3195
    JournalApplied Sciences (Switzerland)
    Volume14
    Issue number8
    DOIs
    Publication statusPublished - 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

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