Microsoft Azure AI Fundamentals (AI-900)Describe features of Natural Language Processing (NLP) workloads on AzureMedium
A research institution is developing a system to help medical professionals quickly find specific information within a large repository of medical journals and clinical trial reports. The system needs to be able to accept natural language questions, such as "What are the side effects of Drug X for patients over 60?", and return precise answers extracted directly from the documents, rather than just providing links to relevant papers. Which Azure AI NLP capability is MOST appropriate for this scenario?
- ALanguage Detection
- BSentiment Analysis
- CQuestion Answering (QnA Maker)
- DText Summarization
Show answer & explanationAnswer & explanation
Correct answer: C. Question Answering (QnA Maker)
Question Answering (QnA Maker) is specifically designed to extract and provide precise answers to user questions from a knowledge base of documents. It goes beyond simple search by understanding the intent of the question and pinpointing exact answer spans.
Why the other options are wrong
- A. Language Detection identifies the language of text, which is not relevant to answering questions from documents.
- B. Sentiment Analysis determines the emotional tone of text, not its factual content in response to a question.
- D. Text Summarization condenses documents, it does not answer specific questions.
Question Answering (QnA Maker)
An Azure AI service that creates a conversational Q&A layer over data. It allows users to query information in natural language and receive direct, accurate answers.
- Builds a knowledge base from structured/unstructured content.
- Understands natural language questions.
- Returns precise answers, not just relevant documents.
Memory trick: QnA: Quick, Nifty Answers for all your docs.