Exam AI-102 topic 3 question 24 discussion

B. Named Entity Recognition Named Entity Recognition (NER) is a process in natural language processing that identifies and classifies named entities mentioned in text into predefined categories such as the names of persons, organizations, locations, expressions of times, quantities, monetary values, percentages, etc. Entity Linking typically involves linking entities to knowledge bases. Sentiment Analysis is used to determine the sentiment expressed in the text. Key Phrase Extraction identifies the main points or topics in a text but does not categorize them into entity types like NER does.

B is answer.

Named Entity Recognition a.k.a NER.

NER is OK.

https://learn.microsoft.com/en-us/azure/ai-services/language-service/named-entity-recognition/overview

Title "What is Named Entity Recognition (NER) in Azure AI Language?" at https://learn.microsoft.com/en-us/azure/ai-services/language-service/named-entity-recognition/overview . NER

B is the answer. https://learn.microsoft.com/en-us/azure/cognitive-services/language-service/named-entity-recognition/overview Named Entity Recognition (NER) is one of the features offered by Azure Cognitive Service for Language, a collection of machine learning and AI algorithms in the cloud for developing intelligent applications that involve written language. The NER feature can identify and categorize entities in unstructured text. For example: people, places, organizations, and quantities.

B is correct

From the link in the answer: "The NER feature can identify and categorize entities in unstructured text. For example: people, places, organizations, and quantities."