AI-103 Text Analysis Practice Question
Your enterprise customer service department receives thousands of support emails daily. Management wants a system that ingests long support tickets and automatically outputs a concise summary highlighting the most critical issues. Which Azure AI Language service feature should you implement?
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
✓
Text summarization (Abstractive or Extractive)
Extractive or abstractive text summarization is designed to process long documents and generate concise summaries.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Named Entity Recognition (NER)
Why it's wrong here
NER identifies entities such as people, locations, and organizations, which does not synthesize a summary.
- ✓
Text summarization (Abstractive or Extractive)
Why this is correct
Text summarization analyzes the content and condenses long documents into summaries using either extractive or abstractive methods.
- ✗
Key phrase extraction
Why it's wrong here
Key phrase extraction returns a list of important semantic concepts in the text, not a coherent summary.
- ✗
Opinion mining
Why it's wrong here
Opinion mining breaks down sentiments associated with specific product features or aspects, not overall text summarization.
About these practice questions
Courseiva writes every AI-103 question from scratch — 510 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
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.