Microsoft Azure AI Fundamentals (AI-900)Describe features of Natural Language Processing (NLP) workloads on AzureMedium
A school district wants to create a system that can automatically answer common questions from parents and students based on their extensive knowledge base of school policies, FAQs, and handbooks. The system needs to provide direct, concise answers to specific questions posed in natural language. Which Azure AI NLP capability is most suitable for this purpose?
- AQuestion Answering (QA)
- BText Summarization
- CSentiment Analysis
- DNamed Entity Recognition (NER)
Show answer & explanationAnswer & explanation
Correct answer: A. Question Answering (QA)
Question Answering (QA) is specifically designed to understand natural language questions and find precise answers within a given body of text or knowledge base. This perfectly matches the school district's need to answer parent and student questions from their policy documents.
Why the other options are wrong
- B. Text Summarization condenses text, but doesn't answer specific questions.
- C. Sentiment Analysis determines emotional tone, not direct answers to questions.
- D. NER extracts specific entities, but doesn't provide direct answers to questions.
Question Answering (QA)
An NLP capability that enables systems to understand questions posed in natural language and retrieve or generate accurate answers from a given text or knowledge base.
- Understands user questions in natural language.
- Extracts precise answers from documents.
- Powers chatbots and intelligent search systems.
Memory trick: QA Quells Queries Accurately