Describe features of Natural Language Processing workloads on Azure →mediumMultiple ChoiceObjective-mapped
What is Named Entity Recognition (NER) in Azure AI Language?
Which Azure AI service can identify and extract named entities (people, organizations, locations, dates) from text?
Quick Answer
The correct answer is Azure AI Language, specifically its Named Entity Recognition (NER) capability, because this service is purpose-built to identify and extract categories like people, organizations, locations, and dates from unstructured text. NER functions as a core component of Azure’s Natural Language Processing (NLP) workload, analyzing text to label entities with predefined types. On the AI-900 exam, this question tests your understanding of which Azure service handles entity extraction versus other tasks like sentiment analysis or translation—a common trap is confusing Azure AI Language with Azure AI Translator or Azure Bot Service. Remember that NER is about “who, what, where, and when” in text, so if you see a scenario asking for extracting names, places, or dates, think Azure AI Language. A helpful memory tip: NER stands for “Name Entity Recognition,” and the “N” in NER can remind you of “Names” as the primary output.
⚠ Common exam trap
Many candidates confuse Azure AI Language's NER with Azure AI Vision's OCR (Optical Character Recognition), mistakenly thinking that 'extracting entities from text' includes extracting text from images, but NER specifically operates on already-digitized text, not images.
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
✓
Azure AI Language (Named Entity Recognition)
Azure AI Language's Named Entity Recognition (NER) capability is specifically designed to identify and categorize named entities such as people, organizations, locations, and dates from unstructured text. This is a core feature of the Natural Language Processing (NLP) workload within Azure AI Language, making option B the correct choice.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Azure AI Vision
Why it's wrong here
Azure AI Vision analyzes images — named entity recognition operates on text.
- ✓
Azure AI Language (Named Entity Recognition)
Why this is correct
Azure AI Language's NER feature extracts and categorizes entities like people, organizations, and locations from text.
- ✗
Azure AI Translator
Why it's wrong here
Azure AI Translator converts text between languages — NER is a feature of Azure AI Language.
- ✗
Azure AI Speech
Why it's wrong here
Azure AI Speech handles audio — named entity recognition is a text analytics feature.
Go deeper
Related to this question
Learn chapter
Machine Learning Core Concepts
Key term
Feature
A feature is a distinct unit of functionality that delivers value to the user, often managed and tracked throughout the software development lifecycle.
Key term
NLP
NLP (Natural Language Processing) is a branch of artificial intelligence that enables computers to understand, interpret, and generate human language in a way that is meaningful and useful.
About these practice questions
One of 985 original AI-900 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
1 more way this is tested on AI-900
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. What is 'named entity recognition' (NER) in Azure AI Language?
easy- A.Renaming database fields to follow a consistent naming convention
- ✓ B.Identifying and classifying real-world entities (people, organisations, locations) mentioned in text
- C.Recognising the named author of a document for copyright purposes
- D.Detecting when a user provides their name in a chatbot conversation
Why B: Named entity recognition (NER) is a feature of Azure AI Language that identifies and categorizes real-world entities such as people, organizations, locations, dates, and quantities within unstructured text. It uses pre-trained machine learning models to extract these entities, enabling downstream tasks like information retrieval and content summarization. Option B correctly describes this core functionality.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-900 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-900 exam.