AI-102 Practice Question: Implement natural language processing solutions
You are building an Azure AI Language solution that must extract named entities from support tickets and classify each entity as a person, organization, or location. The tickets are stored as UTF-8 text files. You need to call the REST API for Named Entity Recognition (NER) and ensure the response includes entity categories. Which request should you send?
⚠ Common exam trap
The trap here is assuming that any endpoint under the cognitive services domain will work, when only the unified analyze-text endpoint with the correct task kind returns categorized entities.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
POST to https://<resource>.cognitiveservices.azure.com/language/:analyze-text?api-version=2023-04-01 with a JSON body containing "kind": "EntityRecognition" and the documents array.
The correct request uses the unified Language service analyze-text endpoint with the EntityRecognition task, which returns entities with categories such as Person, Organization, and Location. The older Text Analytics endpoint is deprecated, and other task types like KeyPhraseExtraction do not provide entity categorization. Using POST with a JSON body is mandatory for analyze-text.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
POST to https://<resource>.cognitiveservices.azure.com/text/analytics/v3.1/entities/recognition/general with the documents array.
Why it's wrong here
This endpoint belongs to the older Text Analytics API, which is being deprecated in favor of the unified Language service. While it may still work for some resources, it does not reflect the current recommended approach for Azure AI Language and may not be available for new resources. The scenario calls for the modern analyze-text endpoint.
- ✗
POST to https://<resource>.cognitiveservices.azure.com/language/:analyze-text?api-version=2023-04-01 with a JSON body containing "kind": "KeyPhraseExtraction" and the documents array.
Why it's wrong here
Setting the kind to KeyPhraseExtraction invokes key phrase extraction, not named entity recognition. Key phrase extraction returns a list of important phrases but does not classify entities into categories like person, organization, or location. This does not meet the requirement to categorize entities.
- ✗
GET to https://<resource>.cognitiveservices.azure.com/language/:analyze-text?api-version=2023-04-01 with the text as a query parameter.
Why it's wrong here
The analyze-text endpoint requires a POST request with a JSON body containing the documents. A GET request with text as a query parameter is not supported and will result in an error. The service expects the input documents in the request body, not as URL parameters.
- ✓
POST to https://<resource>.cognitiveservices.azure.com/language/:analyze-text?api-version=2023-04-01 with a JSON body containing "kind": "EntityRecognition" and the documents array.
Why this is correct
The Azure AI Language analyze-text endpoint accepts a POST request with the kind parameter set to EntityRecognition. The api-version 2023-04-01 is a valid version that returns entity categories such as Person, Organization, and Location. This matches the requirement to extract and categorize named entities from support tickets.
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Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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