Can ChatGPT recognize impoliteness? An exploratory study of the pragmatic awareness of a large language model

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3APLQ7NVRF" target="_blank" >RIV/00216208:11320/26:PLQ7NVRF - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S0378216625000323" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0378216625000323</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.pragma.2025.02.001" target="_blank" >10.1016/j.pragma.2025.02.001</a>

Result language

angličtina

Original language name

Can ChatGPT recognize impoliteness? An exploratory study of the pragmatic awareness of a large language model

Original language description

The practical potential of Large Language Models (LLMs) depends in part on their ability to accurately interpret pragmatic functions. In this article, we assess ChatGPT 3.5’s ability to identify and interpret linguistic impoliteness across a series of text examples. We provided ChatGPT 3.5 with instances of implicational, metalinguistic, and explicit impoliteness, alongside sarcasm, unpalatable questions, erotic talk, and unmarked impolite linguistic behavior, asking (i) whether impoliteness was present, and (ii) its source. We then further tested the bot’s ability to identify impoliteness by asking it to remove it from a series of text examples. ChatGPT 3.5 generally performed well, recognizing both conventionalized lexicogrammatical forms and context-sensitive cases. However, it struggled to account for all impoliteness. In some cases, the model was more sensitive to potentially offensive expressions than humans are, as a result of its design, training and/or inability to sufficiently determine the situational context of the examples. We also found that the model had difficulties sometimes in interpreting impoliteness generated through implicature. Given that impoliteness is a complex and multi-functional phenomenon, we consider our findings to contribute to increasing public awareness not only about the use of AI technologies but also about improving their safety, transparency, and reliability.

Czech name

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Czech description

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Type

J_ost - Miscellaneous article in a specialist periodical

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Journal of Pragmatics

ISSN

0378-2166

e-ISSN

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Volume of the periodical

239

Issue of the periodical within the volume

2025-04-01

Country of publishing house

US - UNITED STATES

Number of pages

21

Pages from-to

16-36

UT code for WoS article

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EID of the result in the Scopus database

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