Microsoft Certified: Azure AI Engineer AssociateImplement natural language processing solutionsEasy
A construction company wants to automate the process of extracting specific details from project proposals, such as project names, client names, and proposed budgets. These details are consistently formatted within the documents. Which Azure AI Language feature is best suited for this task?
- ANamed Entity Recognition (NER)
- BSentiment Analysis
- CKey Phrase Extraction
- DAbstractive Summarization
Show answer & explanationAnswer & explanation
Correct answer: A. Named Entity Recognition (NER)
Named Entity Recognition (NER) is specifically designed to identify and extract predefined categories of entities like names, organizations, and numerical values from unstructured text. This aligns perfectly with the requirement to extract specific, consistently formatted details from project proposals.
Why the other options are wrong
- B. Sentiment Analysis determines the emotional tone of text, which is not the goal here.
- C. Key Phrase Extraction identifies important concepts, but not specific entity types like names or budgets.
- D. Abstractive Summarization generates a concise summary of the text, not specific data points.
Named Entity Recognition (NER)
A natural language processing (NLP) task that identifies and classifies named entities in text into predefined categories such as person names, organizations, locations, medical codes, and numerical expressions.
- Automatically identifies specific entities in text.
- Categorizes entities into predefined types (e.g., person, organization, location).
- Useful for information extraction and structuring unstructured data.
Memory trick: NER is for Naming and Extracting Records.