ready for review

Author: laujan

articles/ai-services/.openpublishing.redirection.ai-services.json

@@ -814,6 +814,21 @@
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       "redirect_url": "/azure/ai-services/what-are-ai-services",
       "redirect_document_id": false
+    },
+    {
+      "source_path_from_root": "/articles/ai-services/language-service/personally-identifiable-information/how-to-call.md",
+      "redirect_url": "/azure/ai-services/language-service/personally-identifiable-information/how-to/redact-text-pii",
+      "redirect_document_id": true
+    },
+    {
+      "source_path_from_root": "/articles/ai-services/language-service/personally-identifiable-information/how-to-call-for-conversations.md",
+      "redirect_url": "/azure/ai-services/language-service/personally-identifiable-information/how-to/redact-conversation-pii",
+      "redirect_document_id": true
+    },
+    {
+      "source_path_from_root": "/articles/ai-services/language-service/native-document-support/use-native-documents.md",
+      "redirect_url": "/azure/ai-services/language-service/native-document-support/overview",
+      "redirect_document_id": true
     }
   ]
 }

articles/ai-services/language-service/native-document-support/managed-identities.md

@@ -12,7 +12,7 @@ ms.date: 11/21/2024
 
 # Managed identities for Language resources
 
-Managed identities for Azure resources are service principals that create a Microsoft Entra identity and specific permissions for Azure managed resources. Managed identities are a safer way to grant access to storage data and replace the requirement for you to include shared access signature tokens (SAS) with your [source and target container URLs](use-native-documents.md#create-azure-blob-storage-containers).
+Managed identities for Azure resources are service principals that create a Microsoft Entra identity and specific permissions for Azure managed resources. Managed identities are a safer way to grant access to storage data and replace the requirement for you to include shared access signature tokens (SAS) with your [source and target container URLs](overview.md#create-azure-blob-storage-containers).
 
    :::image type="content" source="media/managed-identity-flow.png" alt-text="Screenshot of managed identity flow (RBAC).":::
 
@@ -24,7 +24,7 @@ Managed identities for Azure resources are service principals that create a Micr
 
 > [!IMPORTANT]
 >
-> * When using managed identities, don't include a SAS token URL with your HTTP requests—your requests will fail. Using managed identities replaces the requirement for you to include shared access signature tokens (SAS) with your [source and target container URLs](use-native-documents.md#create-azure-blob-storage-containers).
+> * When using managed identities, don't include a SAS token URL with your HTTP requests—your requests will fail. Using managed identities replaces the requirement for you to include shared access signature tokens (SAS) with your [source and target container URLs](overview.md#create-azure-blob-storage-containers).
 >
 > * To use managed identities for Language operations, you must [create your Language resource](https://ms.portal.azure.com/#create/Microsoft.CognitiveServicesTextAnalytics) in a specific geographic Azure region such as **East US**. If your Language resource region is set to **Global**, then you can't use managed identity authentication. You can, however, still use [Shared Access Signature (SAS) tokens](shared-access-signatures.md).
 >
@@ -135,4 +135,4 @@ You must grant the Language resource access to your storage account before it ca
 ## Next steps
 
 > [!div class="nextstepaction"]
-> [Get started with native document support](use-native-documents.md#include-native-documents-with-an-http-request)
+> [Get started with native document support](overview.md#include-native-documents-with-an-http-request)

articles/ai-services/language-service/native-document-support/overview.md

@@ -0,0 +1,76 @@
+---
+title: Native document support for Azure AI Language (preview)
+titleSuffix: Azure AI services
+description: How to use native document with Azure AI Languages Personally Identifiable Information and Summarization capabilities.
+author: laujan
+manager: nitinme
+ms.service: azure-ai-language
+ms.custom:
+  - ignite-2024
+ms.topic: how-to
+ms.date: 02/19/2025
+ms.author: lajanuar
+---
+
+<!-- markdownlint-disable MD033 -->
+<!-- markdownlint-disable MD051 -->
+<!-- markdownlint-disable MD024 -->
+<!-- markdownlint-disable MD036 -->
+<!-- markdownlint-disable MD049 -->
+<!-- markdownlint-disable MD001 -->
+
+# Native document support for Azure AI Language (preview)
+
+> [!IMPORTANT]
+>
+> * Azure AI Language public preview releases provide early access to features that are in active development.
+> * Features, approaches, and processes can change, before General Availability (GA), based on user feedback.
+
+Azure AI Language is a cloud-based service that applies Natural Language Processing (NLP) features to text-based data. The native document support capability enables you to send API requests asynchronously, using an HTTP POST request body to send your data and HTTP GET request query string to retrieve the status results. Your processed documents are located in your Azure Blob Storage target container.
+
+A native document refers to the file format used to create the original document such as Microsoft Word (docx) or a portable document file (pdf). Native document support eliminates the need for text preprocessing before using Azure AI Language resource capabilities. Currently, native document support is available for the following capabilities:
+
+* [Personally Identifiable Information (PII)](../personally-identifiable-information/overview.md). The PII detection feature can identify, categorize, and redact sensitive information in unstructured text. The `PiiEntityRecognition` API supports native document processing.
+
+* [Document summarization](../summarization/overview.md). Document summarization uses natural language processing to generate extractive (salient sentence extraction) or abstractive (contextual word extraction) summaries for documents. Both `AbstractiveSummarization` and `ExtractiveSummarization` APIs support native document processing.
+
+## Supported document formats
+
+ Applications use native file formats to create, save, or open native documents. Currently **PII** and **Document summarization** capabilities supports the following native document formats:
+
+|File type|File extension|Description|
+|---------|--------------|-----------|
+|Text| `.txt`|An unformatted text document.|
+|Adobe PDF| `.pdf`|A portable document file formatted document.|
+|Microsoft Word| `.docx`|A Microsoft Word document file.|
+
+## Input guidelines
+
+***Supported file formats***
+
+|Type|support and limitations|
+|---|---|
+|**PDFs**| Fully scanned PDFs aren't supported.|
+|**Text within images**| Digital images with embedded text aren't supported.|
+|**Digital tables**| Tables in scanned documents aren't supported.|
+
+***Document Size***
+
+|Attribute|Input limit|
+|---|---|
+|**Total number of documents per request** |**≤ 20**|
+|**Total content size per request**| **≤ 10 MB**|
+
+## Request headers and parameters
+
+|parameter  |Description  |
+|---------|---------|
+|`-X POST <endpoint>`     | Specifies your Language resource endpoint for accessing the API.        |
+|`--header Content-Type: application/json`     | The content type for sending JSON data.          |
+|`--header "Ocp-Apim-Subscription-Key:<key>`    | Specifies the Language resource key for accessing the API.        |
+|`-data`     | The JSON file containing the data you want to pass with your request.         |
+
+## Related content
+
+> [!div class="nextstepaction"]
+> [PII detection overview](../personally-identifiable-information/overview.md "Learn more about Personally Identifiable Information detection.") [Document Summarization overview](../summarization/overview.md "Learn more about automatic document summarization.")

articles/ai-services/language-service/native-document-support/shared-access-signatures.md

@@ -130,5 +130,5 @@ That's it! You learned how to create SAS tokens to authorize how clients access
 ## Next steps
 
 > [!div class="nextstepaction"]
-> [Learn more about native document support](use-native-documents.md "Learn how to process and analyze native documents.") [Learn more about granting access with SAS ](/azure/storage/common/storage-sas-overview "Grant limited access to Azure Storage resources using shared access SAS.")
+> [Learn more about native document support](overview.md "Learn how to process and analyze native documents.") [Learn more about granting access with SAS ](/azure/storage/common/storage-sas-overview "Grant limited access to Azure Storage resources using shared access SAS.")
 >

articles/ai-services/language-service/overview.md

@@ -17,23 +17,23 @@ Azure AI Language is a cloud-based service that provides Natural Language Proces
 
 ## Available features
 
-This Language service unifies the following previously available Azure AI services: Text Analytics, QnA Maker, and LUIS. If you need to migrate from these services, see [the migration section](#migrate-from-text-analytics-qna-maker-or-language-understanding-luis) below.
+This Language service unifies the following previously available Azure AI services: Text Analytics, QnA Maker, and LUIS. If you need to migrate from these services, see [the migration section](#migrate-from-text-analytics-qna-maker-or-language-understanding-luis).
 
 The Language service also provides several new features as well, which can either be:
 
-* Preconfigured, which means the AI models that the feature uses are not customizable. You just send your data, and use the feature's output in your applications.
-* Customizable, which means you'll train an AI model using our tools to fit your data specifically.
+* Preconfigured, which means the AI models that the feature uses aren't customizable. You just send your data, and use the feature's output in your applications.
+* Customizable, which means you train an AI model using our tools to fit your data specifically.
 
 > [!TIP]
-> Unsure which feature to use? See [Which Language service feature should I use?](#which-language-service-feature-should-i-use) to help you decide.
+> Unsure which feature to use? See [Which Language service feature should I use](#which-language-service-feature-should-i-use) to help you decide.
 
-[**Language Studio**](./language-studio.md) enables you to use the below service features without needing to write code.
+[**Language Studio**](./language-studio.md) enables you to use the following service features without needing to write code.
 
 ### Named Entity Recognition (NER)
 
 :::row:::
    :::column span="":::
-      :::image type="content" source="media/studio-examples/named-entity-recognition.png" alt-text="A screenshot of a named entity recognition example."  lightbox="media/studio-examples/named-entity-recognition.png":::
+      :::image type="content" source="media/studio-examples/named-entity-recognition.png" alt-text="A screenshot of a named entity recognition example." lightbox="media/studio-examples/named-entity-recognition.png":::
    :::column-end:::
    :::column span="":::
       [Named entity recognition](./named-entity-recognition/overview.md) is a preconfigured feature that categorizes entities (words or phrases) in unstructured text across several predefined category groups. For example: people, events, places, dates, [and more](./named-entity-recognition/concepts/named-entity-categories.md).
@@ -48,7 +48,7 @@ The Language service also provides several new features as well, which can eithe
       :::image type="content" source="media/studio-examples/personal-information-detection.png" alt-text="A screenshot of a PII detection example." lightbox="media/studio-examples/personal-information-detection.png":::
    :::column-end:::
    :::column span="":::
-      [PII detection](./personally-identifiable-information/overview.md) is a preconfigured feature that identifies, categorizes, and redacts sensitive information in both [unstructured text documents](./personally-identifiable-information/how-to-call.md), and [conversation transcripts](./personally-identifiable-information/how-to-call-for-conversations.md). For example: phone numbers, email addresses, forms of identification, [and more](./personally-identifiable-information/concepts/entity-categories.md).
+      [PII detection](./personally-identifiable-information/overview.md) is a preconfigured feature that identifies, categorizes, and redacts sensitive information in [unstructured text documents](./personally-identifiable-information/how-to/redact-text-pii.md), [conversation transcripts](./personally-identifiable-information/how-to/redact-conversation-pii.md), and [native documents](./personally-identifiable-information/how-to/redact-document-pii.md). PII includes phone numbers, email addresses, forms of identification, [and more](./personally-identifiable-information/concepts/entity-categories.md).
 
    :::column-end:::
 :::row-end:::
@@ -182,7 +182,7 @@ The Language service also provides several new features as well, which can eithe
 
 ## Which Language service feature should I use?
 
-This section will help you decide which Language service feature you should use for your application:
+This section helps you decide which Language service feature you should use for your application:
 
 |What do you want to do?  |Document format  |Your best solution  | Is this solution customizable?* |
 |---------|---------|---------|---------|
@@ -200,23 +200,23 @@ This section will help you decide which Language service feature you should use
 | Predict the intention of user inputs and extract information from them. | Unstructured user inputs | [Conversational language understanding](./conversational-language-understanding/overview.md) | ✓ |
 | Connect apps from conversational language understanding, LUIS, and question answering. | Unstructured user inputs | [Orchestration workflow](./orchestration-workflow/overview.md) | ✓ | 
 
-\* If a feature is customizable, you can train an AI model using our tools to fit your data specifically. Otherwise a feature is preconfigured, meaning the AI models it uses cannot be changed. You just send your data, and use the feature's output in your applications.
+\* If a feature is customizable, you can train an AI model using our tools to fit your data specifically. Otherwise a feature is preconfigured, meaning the AI models it uses can't be changed. You just send your data, and use the feature's output in your applications.
 
 ## Migrate from Text Analytics, QnA Maker, or Language Understanding (LUIS)
 
 Azure AI Language unifies three individual language services in Azure AI services - Text Analytics, QnA Maker, and Language Understanding (LUIS). If you have been using these three services, you can easily migrate to the new Azure AI Language. For instructions see [Migrating to Azure AI Language](concepts/migrate.md).  
 
 ## Tutorials
 
-After you've had a chance to get started with the Language service, try our tutorials that show you how to solve various scenarios.
+After you get started with the Language service quickstarts, try our tutorials that show you how to solve various scenarios.
 
 * [Extract key phrases from text stored in Power BI](key-phrase-extraction/tutorials/integrate-power-bi.md)
 * [Use Power Automate to sort information in Microsoft Excel](named-entity-recognition/tutorials/extract-excel-information.md) 
 * [Use Flask to translate text, analyze sentiment, and synthesize speech](/training/modules/python-flask-build-ai-web-app/)
 * [Use Azure AI services in canvas apps](/powerapps/maker/canvas-apps/cognitive-services-api?context=/azure/ai-services/language-service/context/context)
-* [Create a FAQ Bot](question-answering/tutorials/bot-service.md)
+* [Create an FAQ Bot](question-answering/tutorials/bot-service.md)
 
-## Additional code samples
+## Code samples
 
 You can find more code samples on GitHub for the following languages:
 
@@ -237,7 +237,7 @@ Use Language service containers to deploy API features on-premises. These Docker
 
 ## Responsible AI 
 
-An AI system includes not only the technology, but also the people who will use it, the people who will be affected by it, and the environment in which it is deployed. Read the following articles to learn about responsible AI use and deployment in your systems:
+An AI system includes not only the technology, but also the people who use it, the people affected by it, and the deployment environment. Read the following articles to learn about responsible AI use and deployment in your systems:
 
 * [Transparency note for the Language service](/legal/cognitive-services/text-analytics/transparency-note)
 * [Integration and responsible use](/legal/cognitive-services/text-analytics/guidance-integration-responsible-use)