add dybe pr updates

Author: laujan

articles/ai-services/content-understanding/glossary.md

@@ -24,7 +24,7 @@ ms.author: lajanuar
 | **Field schema** | A formal description of the fields to extract from the input. It specifies the name, description, value type, generation method, and more for each field. |
 | **Generation method** | The process of determining the extracted value of a specified field. Content Understanding supports: <br/> &bullet; **Extract**: Directly extract values from the input content, such as dates from receipts or item details from invoices. <br/> &bullet; **Classify**: Classify content into predefined categories, such as call sentiment or chart type. <br/> &bullet; **Generate**: Generate values from input data, such as summarizing an audio conversation or generating scene descriptions from videos. |
 | **Span** | A reference indicating the location of an element (for example, field, word) within the extracted Markdown content. A character offset and length represent a span. Different programming languages use various character encodings, which can affect the exact offset and length values for Unicode text. To avoid confusion, spans are only returned if the desired encoding is explicitly specified in the request. Some elements can map to multiple spans if they aren't contiguous in the markdown (for example, page). |
-| **Processing Location** | An API request parameter that defines the geographic region where your data is analyzed by Azure AI services. You can choose from three options: `geography`, `dataZone`, and `global` to control where processing occurs. This setting helps meet data residency requirements and optimize performance or scalability based on your needs. For more details, see the [API reference documentation](/rest/api/contentunderstanding/content-analyzers/analyze?view=rest-contentunderstanding-2025-05-01-preview&tabs=HTTP#uri-parameters).
+| **Processing Location** | An API request parameter that defines the geographic region where Azure AI Services analyzes your data. You can choose from three options: `geography`, `dataZone`, and `global` to control where processing occurs. This setting helps meet data residency requirements and optimize performance or scalability based on your needs. For more information, *see* the Content Understanding API reference documentation.
 | **Grounding source** | The specific regions in content where a value was generated. It has different representations depending on the file type: <br>&bullet; **Image** - A polygon in the image, often an axis-aligned rectangle (bounding box). <br>&bullet; **PDF/TIFF** - A polygon on a specific page, often a quadrilateral. <br>&bullet; **Audio** - A start and end time range. <br>&bullet; **Video** - A start and end time range with an optional polygon in each frame, often a bounding box.|
 | **Person directory** | A structured way to store face data for recognition tasks. You can add individual faces to the directory and later search for visually similar faces. You can also create person profiles, associate faces to them, and match new face images to known individuals. This setup supports both flexible face matching and identity recognition across images and videos. |
 | **Confidence score** | The level of certainty that the extracted data is accurate. |

articles/ai-services/content-understanding/image/overview.md

@@ -55,7 +55,7 @@ Get started with processing images with Content Understanding by following our [
 
 ## Next steps
 
-* For guidance on optimizing your Content Understanding implementations, including schema design tips, see our detailed [Best practices guide](best-practices.md).
+* For guidance on optimizing your Content Understanding implementations, including schema design tips, see our detailed [Best practices guide](../concepts/best-practices.md).
 * For detailed information on supported input image formats, refer to our [Service quotas and limits](../service-limits.md) page.
 * Review code sample: [**analyzer templates**](https://github.com/Azure-Samples/azure-ai-content-understanding-python/tree/main/analyzer_templates).
 * Refer to our [Data, protection, and privacy policy](https://www.microsoft.com/trust-center/privacy) to learn more about how we handle your data.

articles/ai-services/content-understanding/overview.md

@@ -70,12 +70,11 @@ See [Quickstart](quickstart/use-ai-foundry.md) for more examples.
 |Grounding source| Content Understanding identifies the specific regions in the content where the value was generated from. Source grounding allows users in automation scenarios to quickly verify the correctness of the field values, leading to higher confidence in the extracted data. |
 |Confidence score | Content Understanding provides confidence scores from 0 to 1 to estimate the reliability of the results. High scores indicate accurate data extraction, enabling straight-through processing in automation workflows.|
 
-
 ## Responsible AI
 
  Azure AI Content Understanding is designed to guard against processing harmful content, such as graphic violence and gore, hateful speech and bullying, exploitation, abuse, and more. For more information and a full list of prohibited content, *see* our [**Transparency note**](/legal/cognitive-services/content-understanding/transparency-note?toc=/azure/ai-services/content-understanding/toc.json&bc=/azure/ai-services/content-understanding/breadcrumb/toc.json) and our [**Code of Conduct**](https://aka.ms/AI-CoC).
 
-### Modified Content Filtering
+### Modified content filtering
 
 Content Understanding now supports modified content filtering for approved customers. The subscription IDs with approved modified content filtering impacts Content Understanding output. By default, Content Understanding employs a content filtering system that identifies specific risk categories for potentially harmful content in both submitted prompts and generated outputs. Modified content filtering allows the system to annotate rather than block potentially harmful output, giving you the ability to determine how to handle potentially harmful content. For more information on content filter types, *see* [Content filtering: filter types](../openai/concepts/content-filter.md#content-filter-types).
 
@@ -93,6 +92,7 @@ Developers using the Content Understanding service should review Microsoft's pol
 > If you're using Microsoft products or services to process Biometric Data, you're responsible for: (i) providing notice to data subjects, including with respect to retention periods and destruction; (ii) obtaining consent from data subjects; and (iii) deleting the Biometric Data, all as appropriate, and required under applicable Data Protection Requirements. "Biometric Data" has the meaning articulated in Article 4 of the GDPR and, if applicable, equivalent terms in other data protection requirements. For related information, see [Data and Privacy for Face](/legal/cognitive-services/face/data-privacy-security).
 
 ## Getting started
+
 Our quickstart guides help you quickly start using the Content Understanding service:
 
 * [**Azure AI Foundry portal Quickstart**](quickstart/use-ai-foundry.md)

articles/ai-services/content-understanding/quickstart/use-rest-api.md

@@ -12,13 +12,13 @@ ms.date: 05/19/2025
 
 # Quickstart: Azure AI Content Understanding REST APIs
 
-* This quickstart shows you how to use the [Content Understanding REST API](/rest/api/contentunderstanding/operation-groups?view=rest-contentunderstanding-2025-05-01-preview&preserve-view=true) to get structured data from multimodal content in document, image, audio, and video files.
+* This quickstart shows you how to use the Content Understanding REST API to get structured data from multimodal content in document, image, audio, and video files.
 
 * Try [Content Understanding with no code on Azure AI Foundry](https://ai.azure.com/explore/aiservices/vision/contentunderstanding)
 
 ## Prerequisites
 
-To get started, you need **An Active Azure Subscription**. If you don't have an Azure Account, [create one for free](https://azure.microsoft.com/free/).
+To get started, you need **an active Azure subscription**. If you don't have an Azure account, [create one for free](https://azure.microsoft.com/free/).
 
 * Once you have your Azure subscription, create an [Azure AI Services resource](https://portal.azure.com/#create/Microsoft.CognitiveServicesAIServices) in the Azure portal. This multi-service resource enables access to multiple Azure AI services with a single set of credentials.
 
@@ -36,8 +36,8 @@ To get started, you need **An Active Azure Subscription**. If you don't have an
 
 
 ## Get Started with a prebuilt analyzer
-Analyzers define how your content will be processed and the insights that will be extracted. We offer [pre-built analyzers](link to pre-built analyzer page) for common use cases. You can [customize pre-built analyzers](/how-to/create-a-custom-analyzer) to better fit your specific needs and use cases. 
-This quickstart uses pre-built document, image, audio, and video analyzers to help you get started. 
+Analyzers define how your content is processed and the insights that are extracted. We offer [prebuilt analyzers](../concepts/prebuilt-analyzers.md) for common use cases. You can [customize prebuilt analyzers](/how-to/create-a-custom-analyzer.md) to better fit your specific needs and use cases. 
+This quickstart uses prebuilt document, image, audio, and video analyzers to help you get started. 
 
 ### Send file for analysis
 #### POST request
@@ -52,7 +52,7 @@ Before running the cURL command, make the following changes to the HTTP request:
 # [Document](#tab/document)
 
 1. Replace `{endpoint}` and `{key}` with the corresponding values from your Azure AI Services instance in the Azure portal.
-2. Replace `{analyzerId}` with  `prebuilt-documentAnalyzer`. This analyzer extracts text and layout elements such as paragraphs, sections, and tables from a document.. 
+2. Replace `{analyzerId}` with  `prebuilt-documentAnalyzer`. This analyzer extracts text and layout elements such as paragraphs, sections, and tables from a document. 
 3. Replace `{fileUrl}` with a publicly accessible URL of the file to analyze—such as a path to an Azure Storage Blob with a shared access signature (SAS), or use the sample URL: `https://github.com/Azure-Samples/azure-ai-content-understanding-python/raw/refs/heads/main/data/invoice.pdf`.
 
 # [Image](#tab/image)
@@ -95,7 +95,7 @@ The response returns `resultId` that you can use to track the status of this asy
 
 ### Get analyze result
 
-Use the `resultId` from the `POST` response above and retrieve the result of the analysis.
+Use the `resultId` from the [`POST` response](#post-response) and retrieve the result of the analysis.
 
 1. Replace `{endpoint}` and `{key}` with the endpoint and key values from your Azure portal Azure AI Services instance.
 2. Replace `{resultId}` with the `resultId` from the `POST` response.
@@ -108,7 +108,7 @@ curl -i -X GET "{endpoint}/contentunderstanding/analyzerResults/{resultId}?api-v
 
 #### GET response
 
-The 200 (`OK`) JSON response includes a `status` field indicating the status of the operation. If the operation isn't complete, the value of `status` is `running` or `notStarted`. In such cases, you should send the GET request again, either manually or through a script. Wait an interval of one second or more between calls.
+The 200 (`OK`) JSON response includes a `status` field indicating the status of the operation. If the operation isn't complete, the value of `status` is `running` or `notStarted`. In such cases, you should send the `GET` request again, either manually or through a script. Wait an interval of one second or more between calls.
 
 # [Document](#tab/document)
 
@@ -349,6 +349,6 @@ The 200 (`OK`) JSON response includes a `status` field indicating the status of
 
 ## Next steps
 
-* In this quickstart, you learned how to call the [REST API](/rest/api/contentunderstanding/content-analyzers/analyze?view=rest-contentunderstanding-2025-05-01-preview) using a pre-built analyzer. See how you can [create a custom analyzer](/how-to/create-a-custom-analyzer) to better fit your use case.
+* In this quickstart, you learned how to call the [REST API](/rest/api/contentunderstanding/content-analyzers/analyze?view=rest-contentunderstanding-2025-05-01-preview) using a prebuilt analyzer. See how you can [create a custom analyzer](/how-to/create-a-custom-analyzer) to better fit your use case.