AI-102 Plan and manage an Azure AI solution Practice Question
A company is using Azure Form Recognizer to extract data from invoices. The prebuilt model does not correctly extract a custom field that is specific to the company's invoices. What is the most appropriate action to improve extraction accuracy for this field?
⚠ Common exam trap
Watch out — candidates often think prebuilt models can be customized via mapping or retraining, but Azure Form Recognizer prebuilt models are immutable and only custom models can be trained to recognize new fields.
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
✓
Train a custom model using labeled invoices that include the custom field.
The prebuilt Form Recognizer model is designed for common invoice layouts and may not recognize company-specific fields. Training a custom model with labeled invoices that include the custom field allows the model to learn the field's location and semantics, significantly improving extraction accuracy for that specific field.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use the prebuilt model with a custom field mapping.
Why it's wrong here
Prebuilt models do not support custom field mapping.
- ✓
Train a custom model using labeled invoices that include the custom field.
Why this is correct
A custom model with labeled examples can learn the custom field.
- ✗
Adjust the confidence threshold for the prebuilt model.
Why it's wrong here
Confidence thresholds affect rejection criteria, not extraction accuracy.
- ✗
Retrain the prebuilt model with additional invoices.
Why it's wrong here
Prebuilt models are not retrainable.
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