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 vast amounts of medical literature. They need to extract precise answers to natural language questions, such as 'What are the side effects of Drug X?' Which NLP capability is best suited for this requirement?
- AText Summarization
- BSentiment Analysis
- CLanguage Modeling
- DQuestion Answering
Show answer & explanationAnswer & explanation
Correct answer: D. Question Answering
Question Answering is an NLP capability specifically designed to find and extract precise answers to natural language questions from a given text or corpus of documents. This directly matches the requirement of finding specific information in medical literature.
Why the other options are wrong
- A. Text Summarization condenses text, but doesn't specifically answer questions.
- B. Sentiment Analysis determines emotional tone, not specific factual answers.
- C. Language Modeling predicts the next word in a sequence, foundational but not for direct question answering.
Question Answering (QA)
An NLP task that retrieves direct answers to natural language questions from a collection of documents or a given text.
- Provides precise, factual answers.
- Differs from search by providing answers, not just documents.
- Used in chatbots, virtual assistants, and information retrieval.
Memory trick: Ask a question, get an answer.