Microsoft Azure AI Fundamentals (AI-900)Describe features of Natural Language Processing (NLP) workloads on AzureEasy
A developer is building a system to automatically generate short, concise summaries of news articles to display in a mobile app. Which Azure NLP capability is designed for this purpose?
- AKey Phrase Extraction
- BNamed Entity Recognition (NER)
- CText Summarization
- DLanguage Detection
Show answer & explanationAnswer & explanation
Correct answer: C. Text Summarization
Text Summarization is the NLP capability specifically designed to create a concise and coherent summary of a longer text document, which is exactly what's needed for news articles.
Why the other options are wrong
- A. Key Phrase Extraction pulls out important terms, but not a full summary.
- B. NER identifies specific entities, it doesn't summarize the entire text.
- D. Language Detection identifies the language of the text, not its summary.
Text Summarization
Text Summarization is an NLP task that condenses a longer text document into a shorter version, while preserving its core meaning and key information.
- Can be extractive (pulls sentences directly) or abstractive (generates new sentences).
- Useful for quickly grasping content, news feeds, document review.
- Available as a feature in Azure Cognitive Service for Language.
Memory trick: Summaries Condense Text Superbly.