Questions For Optimal Use of the OpenAI Plugin in Trados Studio 2022 (AIPE / MTPE)

Question

Hello, 
 
 My name is Miha and I am a Project manager at a Slovenia-based LSP, Translat d.o.o. 
 
 We have recently started using your OpenAI plugin (with gpt-4o-mini model) in Trados Studio 2022 in combination with MT (primarily DeepL). While we understand the basic functionality, we would like to make more effective and structured use of the plugin and integrate it properly into our AIPE / MTPE workflows. 
 
 To that end, we would appreciate your clarification on the questions below. 
 1.) Workflow: After MT and AI processing, we see some segments labelled with DEEPL and others with AI; What does this mean in practice?

Does the AI only post-edit the DeepL output where it detects issues? 
 Does it partially retranslate segments? 
 Is the focus mainly stylistic and semantic optimization? 
 
 Is there any way to review or compare DeepL-only output vs. AI‑modified output? 
 
 2.) Context: Does the AI process each segment in isolation, or with access to broader context (paragraph or document level)? 
 
 If processing is segment-based: How is terminological and stylistic consistency ensured across the document? Is there any document-level or batch-context functionality available? 
 
 3.) Prompt Management and Learning: Does the AI learn from: confirmed segments, translator edits, or only from prompts? 
 
 Can the AI remember client-specific preferences, terminology, or style (e.g. on project or profile level) after several usages? Is this predetermined by using an identical (or upgraded) prompt? 
 Are regular updates to prompts recommended, and do you have any best-practice guidance? 
 Based on your experience, what is the most effective way to manage prompts: globally, per client, per project, per language pair...? 
 Is the prompt applied at every AI call or only initially? Are there recommended limits regarding prompt length or complexity? 
 
 5.) Terminology, TM, and QA: To what extent does the AI respect Trados Termbases and Translation Memory? 
 
 In case of conflicts, which has priority: TM/TB or AI output? 
 Can AI also assist with: terminological consistency, style harmonization, fixing typical QA issues (numbers, units, formatting) 
 
 6.) Quality Control and Risk Management: How do you recommend using the plugin for regulated or sensitive content (EU texts, legal, life sciences, technical documentation)? Are there settings for a more conservative output? 
 
 How can the risk of over-paraphrasing or hallucinations be minimized? For which content types would you not recommend using the plugin? 
 
 Thank you very much in advance for your insights. We would also be happy to review any documentation, best-practice examples, or to discuss these topics during a short call or workshop if available.

RWS Community AI · Accepted Answer

Probability score: 0.8 
 Question improvement suggestion: To enhance clarity, consider breaking down your questions into more specific sub-questions or providing examples for each point to facilitate more targeted responses. 
 In the meantime, based on the information you have provided, here is a suggested answer to your question: 
 Hello Miha, 
 Thank you for your detailed inquiry regarding the optimal use of the OpenAI plugin in Trados Studio 2022. Below, I will address your questions step-by-step: 
 **1. Workflow:** 
 - The segments labeled with "DEEPL" indicate that the text was translated using DeepL, while those labeled "AI" suggest that the AI has modified or enhanced the DeepL output. 
 - The AI typically post-edits the DeepL output where it detects issues, focusing on stylistic and semantic optimization. It may also partially retranslate segments if necessary. 
 - To compare DeepL-only output versus AI-modified output, you can use the PostEdit Compare tool, which reports translation modifications during the post-editing phase. 
 **2. Context:** 
 - The AI processes segments in isolation, but it can access broader context if configured to do so. 
 - To ensure terminological and stylistic consistency across the document, you can utilize your termbase and translation memory effectively. Document-level or batch-context functionality may be limited, but you can manage consistency through careful project settings. 
 **3. Prompt Management and Learning:** 
 - The AI learns from confirmed segments and translator edits, allowing it to remember client-specific preferences and terminology. Using consistent prompts can help maintain this learning. 
 - Regular updates to prompts are recommended, and managing prompts can be done globally, per client, or per project, depending on your workflow needs. 
 - The prompt is typically applied at every AI call, and it's advisable to keep prompts concise to ensure effective processing. 
 **4. Terminology, TM, and QA:** 
 - The AI respects Trados Termbases and Translation Memory, but in case of conflicts, the priority may depend on your project settings. 
 - The AI can assist with terminological consistency, style harmonization, and fixing typical QA issues, but you should verify its output against your TM and TB. 
 **5. Quality Control and Risk Management:** 
 - For regulated or sensitive content, it is advisable to use the plugin with caution. You can adjust settings for more conservative output and minimize risks of over-paraphrasing or hallucinations by closely monitoring the AI's suggestions. 
 - It is generally recommended to avoid using the plugin for highly sensitive or critical content types unless you have established robust quality control measures. 
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Questions For Optimal Use of the OpenAI Plugin in Trados Studio 2022 (AIPE / MTPE)