Can ChatGPT Understand Malapropism Correctly? Challenges to Davidson's Passing Theory in Generative AI

Tsukasa Yamanaka

English Language Teaching, 2024, vol. 17, issue 9, 48

Abstract: This study examines ChatGPT's performance in understanding Japanese malapropisms, aiming to explore its capacity for linguistic inference compared to humans. Despite its remarkable fluency in conversation, ChatGPT shows significant limitations in comprehending malapropisms, particularly in handling phonetic, lexical, and contextual errors. Using a specialized dataset, the research highlights these gaps, suggesting that while ChatGPT excels in fluency, its understanding of nuanced language phenomena remains distinct from human comprehension. The findings contribute to the discourse on the potential and limitations of generative AI, advocating for a reevaluation of linguistic-philosophical theories in light of AI advancements.

Date: 2024
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://ccsenet.org/journal/index.php/elt/article/download/0/0/50549/54763 (application/pdf)
https://ccsenet.org/journal/index.php/elt/article/view/0/50549 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ibn:eltjnl:v:17:y:2024:i:9:p:48

Access Statistics for this article

More articles in English Language Teaching from Canadian Center of Science and Education Contact information at EDIRC.
Bibliographic data for series maintained by Canadian Center of Science and Education ().