Implement natural language processing solutions →easyMultiple Choice

AI-102 Practice Question: Implement natural language processing solutions

Exhibit

{
  "parameters": {
    "api-version": "2023-04-01",
    "deployment-id": "myDeployment",
    "document": {
      "id": "1",
      "language": "en",
      "text": "The quick brown fox jumps over the lazy dog."
    }
  },
  "endpoint": "https://mytextanalytics.cognitiveservices.azure.com/text/analytics/v3.1/entities/recognition/general"
}

Refer to the exhibit. You are calling the Azure AI Language NER API. The response returns no entities. What is the most likely reason?

⚠ Common exam trap

Azure often tests the misconception that a missing or incorrect parameter (like API version, language, or region) would silently return empty results, when in reality those errors manifest as HTTP status codes or error messages, not a successful empty response.

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

✓

The text does not contain any recognized entities

The NER API returns entities only if the input text contains recognized entity types (e.g., Person, Location, Organization, DateTime, etc.). If no entities are found, the API returns an empty entities array. This is the most straightforward and common reason for a zero-entity response, assuming the request is otherwise valid.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✓
The text does not contain any recognized entities
Why this is correct
The NER API returns entities only when it recognises spans matching its trained entity categories. Empty results mean the submitted text contained no such recognisable entities, not a request failure, so the most likely cause is simply that no entities were present.
✗
The API version is incorrect
Why it's wrong here
An invalid API version produces an error status such as 400 or 404, not a 200 response with an empty entities collection. The exhibit returns success, so version negotiation succeeded. Pinning the API version is what you would check when the service rejects requests outright after a deprecation.
✗
The document language should be 'es' for Spanish
Why it's wrong here
Specifying 'es' only sets the language hint for analysis; it does not cause an empty entity list. The exhibit's request already targets the correct language, so entities should still be detected. Language selection matters when text is genuinely Spanish and the default 'en' model misreads it.
✗
The endpoint URL is for the wrong region
Why it's wrong here
A wrong-region endpoint returns an authorisation or 404 error, not a successful 200 response containing an empty entities array. The exhibit shows a valid response, so routing is fine. Region choice matters when provisioning the resource near your data to cut latency and meet residency rules.

Go deeper

AI-102 Practice Question: Implement natural language processing solutions

Exhibit

Why each option matters

Option-by-option breakdown

Related to this question