S01¶


Research	R0027 — Multilingual prompt engineering challenges
Run	2026-03-26
Query	Q002
Search	S01

WebSearch — Linguistic structure challenges for prompt engineering in SOV, tonal, and inflected languages

Summary¶

Field	Value
Source/Database	WebSearch
Query terms	"prompt engineering challenges SOV word order Japanese Korean tonal languages Mandarin inflected languages Arabic Finnish linguistic structure"
Filters	None
Results returned	10
Results selected	5
Results rejected	5

Selected Results¶

Result	Title	URL	Rationale
S01-R01	Multilingual Prompt Engineering Survey	https://arxiv.org/html/2505.11665v1	Covers linguistic features affecting prompt effectiveness
S01-R02	Addressing the Challenges in Multilingual Prompt Engineering	https://www.comet.com/site/blog/addressing-the-challenges-in-multilingual-prompt-engineering/	Industry perspective on specific linguistic challenges
S01-R03	Native vs Non-Native Language Prompting	https://arxiv.org/html/2409.07054v1	Arabic-specific structural challenges
S01-R04	Multilingual Prompt Engineering for Semantic Alignment	https://latitude-blog.ghost.io/blog/multilingual-prompt-engineering-for-semantic-alignment/	Semantic alignment challenges across language structures
S01-R05	Prompt engineering for low-resource languages	https://portkey.ai/blog/prompt-engineering-for-low-resource-languages/	Practical challenges with morphologically complex languages

Rejected Results¶

Result	Title	URL	Rationale
S01-R06	Prompt Engineering for Language Learning	https://www.promptengineering.ninja/p/prompt-engineering-for-language-learning	About using prompts to learn languages, not about linguistic challenges for prompting
S01-R07	Pangeanic Overcomes Challenges In The Hardest Languages	https://blog.pangeanic.com/pangeanic-overcomes-challenges-in-the-hardest-languages	Commercial translation service marketing
S01-R08	Multilingual Prompt Engineering Survey (ResearchGate duplicate)	https://www.researchgate.net/publication/391878863	Duplicate of S01-R01
S01-R09	Prompt engineering - Wikipedia	https://en.wikipedia.org/wiki/Prompt_engineering	General overview, not focused on linguistic challenges
S01-R10	Prompt Engineering 101 (ACL)	https://aclanthology.org/2024.ccl-1.108.pdf	General prompt engineering tutorial, not multilingual-focused

Notes¶

Direct research on structural linguistic challenges for prompt engineering is limited. Most evidence addresses tokenization and training data rather than linguistic structure per se.