AI-103 Text Analysis Practice Question
You are processing customer feedback emails that contain both English and Spanish paragraphs within the same message. You need to perform sentiment analysis on each paragraph separately. What should you do?
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
✓
Split the email into individual paragraphs and submit them as separate documents in the request payload.
Because language detection and sentiment analysis operate per document, you should split the multi-lingual email into separate document chunks (or paragraphs) and specify the language parameter for each document if necessary.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use custom text classification instead of sentiment analysis.
Why it's wrong here
Classification categorizes documents; it does not evaluate sentiment.
- ✗
Submit the entire email as a single document with the language set to auto-detect.
Why it's wrong here
Auto-detection on mixed-language single documents can lead to inaccurate sentiment scoring.
- ✓
Split the email into individual paragraphs and submit them as separate documents in the request payload.
Why this is correct
Splitting mixed-language text into distinct documents ensures accurate processing and language association.
- ✗
Translate the entire email to French before calling sentiment analysis.
Why it's wrong here
Translating intermediate text adds latency and can distort sentiment nuances.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Microsoft exam blueprint
This AI-103 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-103 exam.