Share via

Azure Content Understanding Citations and Confidence Score for Generate Fields.

Siddharth Mehta 1 Reputation point Microsoft Employee
2026-03-17T04:22:10.36+00:00

In Azure Content Understanding, we can extract fields based on Schemas and specify the generation methods by Explicitly setting the method (extract, generate, or classify) for each field based on its purpose.

For Extract fields we can get the Confidence Score, Citation links based on bounded box regions mapping to the document Source

Is the same Now, also Available for Generate fields i.e. getting Confidence Score and Citations for Generate Fields?

Also do we have any code samples for following:

  1. Get confidence score and citations for generate fields using C# SDK
  2. How to Open a PDF and show bounded box regions and highlight Extract (or Generate) fields. Which NuGet package to use for suchPDF operations?

Thanks In Advance!

Foundry Tools
Foundry Tools

Formerly known as Azure AI Services or Azure Cognitive Services is a unified collection of prebuilt AI capabilities within the Microsoft Foundry platform


1 answer

Sort by: Most helpful
  1. Q&A Assist
    2026-03-17T04:22:25.6233333+00:00
    AI generated content. This question contains an answer created with AI from Q&A Assist. Learn more

    Confidence scores and citations (grounding) for generate fields:

    • Confidence scores are available for all field extraction methods for documents, including generate. This is explicitly called out as a recent enhancement: “Confidence scores are now consistently available across all extraction methods for documents—whether you use extract, generative, or classify.”
    • Grounding (citations to source regions) is supported for extract and generate methods when enabled. Grounding is defined as the “specific regions in content where a value was extracted or generated,” and is available when confidence/grounding is opted in.
    • To enable confidence and grounding for field extraction in a document analyzer, set:
      • estimateFieldSourceAndConfidence = true in the analyzer config (for all fields), or
      • estimateSourceAndConfidence = true on a specific field.

    This applies equally to generate fields in document analyzers, so generate fields can return both confidence scores and grounded source regions.

    C# SDK sample for confidence and citations on generate fields:

    The context describes the API behavior and configuration flags but does not include a C# SDK code sample. The key configuration needed in any client (including C#) is:

    • In the analyzer schema/configuration for documents:
      • Set estimateFieldSourceAndConfidence = true to opt in to confidence and grounding for all fields, or
      • On individual fields, set estimateSourceAndConfidence = true.

    Once enabled, the JSON response for analyzed documents will include, for each field (including generate fields):

    • The field value
    • Confidence score (0–1)
    • Grounding/source spans (page numbers, bounding boxes, etc.)

    The C# SDK would need to deserialize these properties from the service’s JSON response according to the SDK’s model types, but the exact C# types and usage are not provided in the context.

    Opening a PDF and showing bounding boxes / highlights:

    • Content Understanding provides grounding source information for document fields, including page numbers and bounding boxes for extracted values. This is intended to “aid the user experience by highlighting locations for human review and correction.”
    • The service itself does not perform PDF rendering or visual highlighting. It only returns metadata (page numbers, bounding boxes, spans) that can be used by a client application.
    • The context does not specify any particular .NET or NuGet package for opening PDFs and drawing bounding boxes/highlights. Any PDF rendering library that allows drawing rectangles at given coordinates could be used, but no specific package recommendation is provided in the available documentation.

    References:

    Was this answer helpful?

Your answer

Answers can be marked as 'Accepted' by the question author and 'Recommended' by moderators, which helps users know the answer solved the author's problem.