Claims

Prompting experiments show LLMs perform badly at generating non-US national standard varieties and conflate Nigerian English with Nigerian Pidgin

Claim · All claims
Evidence · 1 study (2 entries) · qualitative r2 · q1
Currency · newest study 2025 · not yet checked against its sources · not reviewed by a person · recheck by 2028: tool and model accuracy changes quickly

Subclaims

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q1 i? In the contributors' prompting experiments, LLMs performed very badly at generating national standard varieties of English other than US English, even failing to implement British spelling consistently. → Ugwuanyi 2025 q1 i? ChatGPT's one-shot rewrite in 'Nigerian English' produced text with exaggerated Nigerian Pidgin features that would no longer be considered academic, indicating minoritised varieties are underrepresented in pre-training data. → Ugwuanyi 2025 (2)

Evidence

Ugwuanyi 2025

Ugwuanyi, K., Mair, C., Dovchin, S., Erdocia, I., Kuteeva, M., & Airemionkhale, E. (2025). Generative AI and linguistic diversity in academic writing and publishing: Perspectives from World Englishes. https://arxiv.org/abs/2607.28505 doi:10.48550/arxiv.2607.28505

q1 · i? · theoretical · r2

Self-reported prompting experiments by a World Englishes scholar, reported in the dialogue: LLMs "perform very badly" at generating non-US national standard varieties, including inconsistent British spelling over more than a few paragraphs. Informal, unreported methodology.

"I have carried out prompting experiments to generate text in national standard varieties of English other than the US one and found LLMs to perform very badly at this task."

Ugwuanyi 2025 (2)

Ugwuanyi, K., Mair, C., Dovchin, S., Erdocia, I., Kuteeva, M., & Airemionkhale, E. (2025). Generative AI and linguistic diversity in academic writing and publishing: Perspectives from World Englishes. https://arxiv.org/abs/2607.28505. doi:10.48550/arxiv.2607.28505

q1 · i? · qualitative · r2

Analysis of a ChatGPT-4 one-shot prompt rewriting an abstract in Nigerian English: the output exaggerated enregistered Pidgin-style features, showing minoritised varieties are "underrepresented in the pre-training data". Single-prompt demonstration, not a systematic evaluation.

"the above text generated by ChatGPT confirms that the voices of scholars using minoriti sed varieties of World Englishes are clearly underrepresented in the pre-training data."

Discussion

Page metadata
Field Value
type claim
id llms-perform-badly-non-us-standard-varieties
title Prompting experiments show LLMs perform badly at generating non-US national standard varieties and conflate Nigerian English with Nigerian Pidgin
description Prompting experiments show LLMs perform badly at generating non-US national standard varieties and conflate Nigerian English with Nigerian Pidgin
status review
evidence_strength weak
newest_evidence 2025
recheck_by 2028
generated by process:wiki-ingest on 2026-10-10
trust unverified — no one has confirmed this page's content
sources 2 — ugwuanyi-2025, ugwuanyi-2025-2

Frontmatter is the page's machine-readable record — see the Schema & Guide.