The answer is to provide a dictionary with the terms and their translations set to the same word. Azure AI Translator’s dictionary feature allows you to specify a source term and its forced translation; by setting the translation to the identical word, you effectively prevent translation of that specific term while the rest of the document processes normally. On the AI-102 exam, this scenario tests your understanding of the Translator’s built-in dictionary functionality versus common misconceptions—many candidates mistakenly look for an ‘includeUntranslated’ parameter, which does not exist, or suggest post-editing, which is inefficient for large volumes. A common trap is assuming custom models are needed, but they require training data and are overkill for simple term preservation. Remember the memory tip: “Same word, same meaning” — if you want a term to stay as-is, map it to itself in the dictionary.
AI-102 Practice Question: Implement natural language processing solutions
This AI-102 practice question tests your understanding of implement natural language processing solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are using Azure AI Translator to translate documents from English to French. Some technical terms must remain untranslated. How should you handle this?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Provide a dictionary with the terms and their translations set to the same word
Azure AI Translator supports a dictionary to specify words that should not be translated. The 'includeUntranslated' parameter does not exist. Post-editing is inefficient. Using a custom model requires training data.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Set the includeUntranslated parameter to true
Why it's wrong here
No such parameter exists in Translator API.
✗
Train a custom translation model that ignores those terms
Why it's wrong here
Overkill; dictionary is simpler and sufficient.
✗
Post-process the output to revert translations of those terms
Why it's wrong here
Manual post-processing is error-prone and inefficient.
✓
Provide a dictionary with the terms and their translations set to the same word
Why this is correct
The dictionary allows forcing a specific translation; setting the target same as source prevents translation.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Implement natural language processing solutions — This question tests Implement natural language processing solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Provide a dictionary with the terms and their translations set to the same word — Azure AI Translator supports a dictionary to specify words that should not be translated. The 'includeUntranslated' parameter does not exist. Post-editing is inefficient. Using a custom model requires training data.
What should I do if I get this AI-102 question wrong?
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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