Create literal and natural translations for different audiences

Auteur: AILesson6 min de préparationTesté avec:ChatGPTRévisé: 2026-08-28

Réponse rapide

Compare a source-close rendering with an audience-ready version without hiding meaning changes. Fournir: Source text, Target language, audience, and use, Meaning and style constraints. Résultat attendu: Two aligned translations with adaptation notes and a recommendation.

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Create two translations of the source for the stated target language and use.

Source:
[source]

Target locale, audience, channel, reading level, and purpose:
[audience]

Fixed facts, terms, tone boundaries, length, and forbidden adaptations:
[constraints]

Version A must stay close to the source's syntax and wording so a reviewer can trace meaning. Version B may reorganize phrasing, idiom, explicitness, and sentence length for the audience, but must preserve facts, conditions, requests, certainty, tone boundary, and practical effect. Do not add cultural references, promises, benefits, or explanations unsupported by the source. Return: source-aligned version; natural audience-ready version; sentence-level adaptation notes; any meaning that cannot be preserved cleanly; and a recommendation for which version to use.
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De l'entrée au résultat

Un exemple détaillé

Voyez comment un contexte concret transforme cette recette en résultat utilisable.

Entrée réelle

Source text
Before you hit the road, give the backup a quick once-over. If anything looks off, pause the migration and contact the service desk; do not try to power through.
Target language, audience, and use
Simplified Chinese for first-time users in an in-app migration checklist. Friendly, plain language, short sentences.
Meaning and style constraints
Preserve the sequence: inspect backup, pause migration if abnormal, contact service desk. ‘Do not try to power through’ means do not continue despite the problem. Do not promise support response time.

Exemple de sortie

Version A — source-close: 在开始操作前,请快速检查一下备份。如果发现任何异常,请暂停迁移并联系服务台;不要勉强继续。

Version B — audience-ready: 开始迁移前,请先检查备份。发现异常时,请立即暂停迁移并联系服务台。问题确认前不要继续。

Adaptation notes: “hit the road” was rendered as 开始操作/开始迁移 rather than a travel image; “quick once-over” became 快速检查/先检查; “power through” became 勉强继续 in A and the explicit action boundary 问题确认前不要继续 in B. B splits the source into three checklist actions but preserves their order and adds no response-time promise. Recommendation: use B in the interface; retain A for bilingual review.

Pourquoi cela fonctionne

  1. 1

    Parallel versions expose the trade-off between auditability and natural reading.

  2. 2

    Adaptation notes make audience changes reviewable instead of silently treating them as translation.

Vérifier le résultat

  • Can every material idea in both versions be traced to the source?

  • Does the natural version fit the audience without adding promises or deleting conditions?

  • Do the notes identify every material departure from source order, idiom, or explicitness?

Utilisez-la en toute confiance

Questions fréquentes

Des réponses pratiques sur le bon moment pour utiliser cette recette, ce qu’il faut fournir et les cas où une vérification humaine reste nécessaire.

What should I prepare before using “Create literal and natural translations for different audiences”?

For “Create literal and natural translations for different audiences,” prepare Source text, Target language, audience, and use, and Meaning and style constraints. Replace placeholders only with information you can verify. If a detail is unknown, preserve that uncertainty explicitly instead of asking the model to infer it.

When is the “Create literal and natural translations for different audiences” result not ready to use?

The result is not ready if it does not yet deliver the stated outcome—Two aligned translations with adaptation notes and a recommendation—from the supplied evidence, or if it relies on unresolved assumptions, missing approvals, or invented details. Use the checks as release gates: revise the source inputs or assign a named, authorized reviewer instead of polishing an unsupported output.

Which AI tools have recorded tests for “Create literal and natural translations for different audiences”?

The published test record for “Create literal and natural translations for different audiences” lists ChatGPT as of 2026-08-28. This confirms recorded runs, not guaranteed compatibility or identical results in later product versions. For another tool or version, keep every constraint visible and repeat the result checks before use.

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