AI-102 Practice Question: Implement natural language processing solutions
Which TWO Azure AI Language features can you use to extract structured data from unstructured text?
⚠ Common exam trap
Watch out — candidates often confuse Key Phrase Extraction (D) with extracting structured data, but key phrases are merely unstructured text snippets, not categorized or linked entities, which is the core requirement for structured data extraction.
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
✓
Entity Linking
Entity Linking (C) and Named Entity Recognition (E) are both Azure AI Language features designed to extract structured data from unstructured text. Entity Linking disambiguates entities by linking them to a knowledge base (e.g., Wikipedia), providing a unique identifier and structured metadata. Named Entity Recognition identifies and categorizes entities (e.g., person, organization, location) directly from text, enabling extraction of structured information.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Sentiment Analysis
Why it's wrong here
Sentiment Analysis returns sentiment scores, not structured entities.
- ✗
Language Detection
Why it's wrong here
Language Detection returns a language code, not structured data from the text content.
- ✓
Entity Linking
Why this is correct
Entity Linking provides structured links to known entities.
- ✗
Key Phrase Extraction
Why it's wrong here
Key Phrase Extraction provides phrases, not structured data.
- ✓
Named Entity Recognition
Why this is correct
NER extracts structured entities from text.
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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.