AI-102 Practice Question: Implement knowledge mining and information extraction solutions
You are using Azure AI Search to index a set of contracts. You need to extract named entities such as organizations, people, and dates from the contract text and store them as separate fields in the index. Which skill should you add to the skillset?
⚠ Common exam trap
Many exam-takers confuse Key Phrases, which returns a flat list of salient phrases, with Entity Recognition, which returns categorized entities with type information.
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 Recognition skill
Entity Recognition is the built-in Azure AI Search skill that calls Azure AI Language to detect named entities with type and subtype metadata. Its output includes categorized entities such as organizations, people, and dates, which can be projected into separate index fields. The other language skills perform different functions and do not produce typed entity output.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Text Translation skill
Why it's wrong here
The Text Translation skill translates text from one language to another using Azure AI Translator. It does not perform entity extraction and would not populate organization, person, or date fields. Using it here would add translated content but leave the required entity fields empty, failing the stated requirement.
- ✗
Language Detection skill
Why it's wrong here
The Language Detection skill identifies the language of the text and returns a language code and name. It does not extract entities or any domain-specific information. While useful for routing documents to the correct language analyzer, it cannot produce organization, person, or date fields from contract content.
- ✗
Key Phrases skill
Why it's wrong here
The Key Phrases skill identifies main talking points in text but does not classify them into entity types such as organizations, people, or dates. It returns a flat list of phrases, which cannot be mapped to separate typed fields. For typed entity extraction, a different skill is required that returns categorized entities with types and subtypes.
- ✓
Entity Recognition skill
Why this is correct
The Entity Recognition skill uses Azure AI Language to detect named entities in text and returns them with type and subtype information, such as Organization, Person, and DateTime. This allows each entity category to be mapped to its own index field. It is the correct skill for extracting typed entities from contract text.
Go deeper
Related to this question
About these practice questions
This AI-102 question is part of Courseiva's 761-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam 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 September 2026 · checked against the official Microsoft exam blueprint
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.