You use natural language processing to process text from a Microsoft news story.

The output identifies text values and labels them with entity categories, such as:

now [DateTime]

students [PersonType]

Microsoft [Organization]

175 [Quantity-Number]

Today [DateTime-Date]

This is entity recognition, also known as Named Entity Recognition (NER). NER identifies and categorizes entities in unstructured text, such as people, organizations, locations, dates, quantities, numbers, and other named or structured values.

Why the other options are incorrect:

B. translation would convert text from one language to another.

C. key phrase extraction would return important phrases or main topics, not categorized entity labels.

D. sentiment analysis would return sentiment such as positive, negative, neutral, or mixed.