AI-102 Practice Question: Implement natural language processing solutions
You are a developer at a global e-commerce company. You are building a multilingual chatbot using Azure AI Language that supports English, French, German, and Spanish. The chatbot must answer frequently asked questions about order status, returns, and shipping. You plan to use Custom Question Answering with a single project containing questions and answers in all four languages. However, during testing, you notice that queries in French and German often return incorrect answers or no answer, while English and Spanish work well. You need to ensure accurate answers across all four languages. What should you do?
⚠ Common exam trap
Many exam-takers assume a single Custom Question Answering project can handle multiple languages by simply adding translated QnA pairs, overlooking that the underlying NLP pipeline is language-specific and cannot correctly process queries in languages other than the project's configured primary language.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Create a separate Custom Question Answering project for each language and route user queries to the appropriate project based on language detection.
Custom Question Answering (CQA) projects are language-specific; a single project cannot reliably handle multiple languages due to differences in tokenization, stemming, and stop-word handling. By creating a separate project per language and routing queries based on language detection (e.g., using Azure AI Language's language detection API), you ensure that each project's model is optimized for its respective language, improving answer accuracy for French and German.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Create a separate Custom Question Answering project for each language and route user queries to the appropriate project based on language detection.
Why this is correct
Separate projects ensure optimal language-specific models and accurate answers.
- ✗
Use Azure Cognitive Search with semantic ranking to index the QnA pairs.
Why it's wrong here
Cognitive Search is a different service; it does not provide the same question-answering capabilities as Custom Question Answering.
- ✗
Add synonyms in the project for French and German terms to improve matching.
Why it's wrong here
Synonyms help within a language but do not address the core issue of mixing languages.
- ✗
Deploy the same project to multiple regions and use traffic manager.
Why it's wrong here
Regional deployment does not improve language accuracy within a single project.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-102 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-102 exam.