Microsoft Azure AI Fundamentals (AI-900)Describe features of Natural Language Processing (NLP) workloads on AzureMedium
A compliance officer needs to monitor internal company documents for specific jargon, project names, and policy terms that are unique to their organization. The standard Named Entity Recognition (NER) models do not adequately identify these custom terms. Which Azure NLP tool allows for the recognition of these organization-specific entities?
- AQnA Maker
- BAzure Translator
- CCustom Named Entity Recognition (Custom NER)
- DLanguage Understanding (LUIS)
Show answer & explanationAnswer & explanation
Correct answer: C. Custom Named Entity Recognition (Custom NER)
Custom Named Entity Recognition (Custom NER) in Azure Cognitive Service for Language allows users to train models to identify and extract entities that are specific to their domain, industry, or organization, which is precisely what's needed for unique company jargon and policy terms.
Why the other options are wrong
- A. QnA Maker creates a knowledge base for answering questions, not for extracting custom entities.
- B. Azure Translator translates text between languages, not for custom entity extraction.
- D. LUIS is for understanding user intent and entities in conversational AI, not for batch document entity extraction.
Custom Named Entity Recognition (Custom NER)
An NLP capability that allows users to train models to identify and extract domain-specific or organization-specific entities from text.
- Extends standard NER for unique terms.
- Requires labeled training data.
- Useful for specialized industries (medical, legal, finance).
Memory trick: Custom NER for custom names.