update native document support sections

Author: laujan

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

@@ -6,7 +6,7 @@ ms.topic: how-to
 manager: nitinme
 ms.author: lajanuar
 author: laujan
-ms.date: 11/21/2024
+ms.date: 03/05/2025
 ---
 
 

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

@@ -6,7 +6,7 @@ ms.topic: how-to
 manager: nitinme
 ms.author: lajanuar
 author: laujan
-ms.date: 11/21/2024
+ms.date: 03/05/2025
 ---
 
 # SAS tokens for your storage containers
@@ -19,17 +19,15 @@ Learn to create user delegation, shared access signature (SAS) tokens, using the
 >
 > [Role-based access control (managed identities)](../concepts/role-based-access-control.md) provide an alternate method for granting access to your storage data without the need to include SAS tokens with your HTTP requests.
 >
-> * You can use managed identities to grant access to any resource that supports Microsoft Entra authentication, including your own applications.
+> * Using managed identities grants access to any resource that supports Microsoft Entra authentication, including your own applications.
 > * Using managed identities replaces the requirement for you to include shared access signature tokens (SAS) with your source and target URLs.
-> * There's no added cost to use managed identities in Azure.
+> * Using managed identities doesn't require an added cost in Azure.
 
 At a high level, here's how SAS tokens work:
 
 * Your application submits the SAS token to Azure Storage as part of a REST API request.
 
-* If the storage service verifies that the SAS is valid, the request is authorized.
-
-* If the SAS token is deemed invalid, the request is declined, and the error code 403 (Forbidden) is returned.
+* The storage service verifies that the SAS is valid and then the request is authorized. If the SAS token is deemed invalid, the request is declined, and the error code 403 (Forbidden) is returned.
 
 Azure Blob Storage offers three resource types:
 
@@ -41,7 +39,7 @@ Azure Blob Storage offers three resource types:
 >
 > * SAS tokens are used to grant permissions to storage resources, and should be protected in the same manner as an account key.
 >
-> * Operations that use SAS tokens should be performed only over an HTTPS connection, and SAS URIs should only be distributed on a secure connection such as HTTPS.
+> * Operations that use SAS tokens should be performed only over an HTTPS connection, and `SAS URI`s should only be distributed on a secure connection such as HTTPS.
 
 ## Prerequisites
 
@@ -80,9 +78,9 @@ Workflow: **Your storage account** → **containers** → **your container** →
     * Consider setting a longer duration period for the time you're using your storage account for Language Service operations.
     * The value of the expiry time is determined by whether you're using an **Account key** or **User delegation key** **Signing method**:
        * **Account key**: No imposed maximum time limit; however, best practices recommended that you configure an expiration policy to limit the interval and minimize compromise. [Configure an expiration policy for shared access signatures](/azure/storage/common/sas-expiration-policy).
-       * **User delegation key**: The value for the expiry time is a maximum of seven days from the creation of the SAS token. The SAS is invalid after the user delegation key expires, so a SAS with an expiry time of greater than seven days will still only be valid for seven days. For more information,*see* [Use Microsoft Entra credentials to secure a SAS](/azure/storage/blobs/storage-blob-user-delegation-sas-create-cli#use-azure-ad-credentials-to-secure-a-sas).
+       * **User delegation key**: The value for the expiry time is a maximum of seven days from the creation of the SAS token. The SAS is invalid after the user delegation key expires, so a SAS with an expiry time of greater than seven days will still only be valid for seven days. For more information, *see* [Use Microsoft Entra credentials to secure a SAS](/azure/storage/blobs/storage-blob-user-delegation-sas-create-cli#use-azure-ad-credentials-to-secure-a-sas).
 
-1. The **Allowed IP addresses** field is optional and specifies an IP address or a range of IP addresses from which to accept requests. If the request IP address doesn't match the IP address or address range specified on the SAS token, authorization fails. The IP address or a range of IP addresses must be public IPs, not private. For more information,*see*, [**Specify an IP address or IP range**](/rest/api/storageservices/create-account-sas#specify-an-ip-address-or-ip-range).
+1. The **Allowed IP addresses** field is optional and specifies an IP address or a range of IP addresses from which to accept requests. If the request IP address doesn't match the IP address or address range specified on the SAS token, authorization fails. The IP address or a range of IP addresses must be public IPs, not private. For more information, *see*, [**Specify an IP address or IP range**](/rest/api/storageservices/create-account-sas#specify-an-ip-address-or-ip-range).
 
 1. The **Allowed protocols** field is optional and specifies the protocol permitted for a request made with the SAS. The default value is HTTPS.
 

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

@@ -27,21 +27,21 @@ The Language service also provides several new features as well, which can eithe
 > [!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.
 
-[**Azure AI Foundry**](https://ai.azure.com) enables you to use most of the below service features without needing to write code.
+[**Azure AI Foundry**](https://ai.azure.com) enables you to use most of the following service features without needing to write code.
 
 ### Named Entity Recognition (NER)
 
 :::row:::
    :::column span="":::
-      :::image type="content" source="media/overview/named-entity-recognition.png" alt-text="A screenshot of named entity recognition in Azure AI Foundry."  lightbox="media/overview/named-entity-recognition.png":::
+      :::image type="content" source="media/overview/named-entity-recognition.png" alt-text="A screenshot of named entity recognition in Azure AI Foundry."lightbox="media/overview/named-entity-recognition.png":::
    :::column-end:::
    :::column span="":::
-      [Named entity recognition](./named-entity-recognition/overview.md) identifies different entries in text and categorizes them into pre-defined types.
+      [Named entity recognition](./named-entity-recognition/overview.md) identifies different entries in text and categorizes them into predefined types.
 
    :::column-end:::
 :::row-end:::
 
-### Personally identifying (PII) and health (PHI) information detection
+### Personal and health data information detection
 
 :::row:::
    :::column span="":::
@@ -73,7 +73,7 @@ The Language service also provides several new features as well, which can eithe
       :::image type="content" source="media/overview/sentiment-analysis.png" alt-text="A screenshot of sentiment analysis in Azure AI Foundry." lightbox="media/overview/sentiment-analysis.png":::
    :::column-end:::
    :::column span="":::
-      [Sentiment analysis and opinion mining](./sentiment-opinion-mining/overview.md) are preconfigured features that help you find out what people think of your brand or topic by mining text for clues about positive or negative sentiment, and can associate them with specific aspects of the text.
+      [Sentiment analysis and opinion mining](./sentiment-opinion-mining/overview.md) preconfigured features that help you understand public perception of your brand or topic. These features analyze text to identify positive or negative sentiments and can link them to specific elements within the text.
 
    :::column-end:::
 :::row-end:::
@@ -88,7 +88,7 @@ The Language service also provides several new features as well, which can eithe
    :::column-end:::
    :::column span="":::
       [Summarization](./summarization/overview.md) condenses information for text and conversations (chat and transcripts).
-      Text summarization generates a summary, supporting two approaches: Extractive summarization produces a summary by extracting salient sentences within the document along with the positioning information of these sentences, and abstractive summarization, which generates a summary with concise, coherent sentences or words that aren't verbatim extract sentences from the original document.
+      Text summarization generates a summary, supporting two approaches: Extractive summarization creates a summary by selecting key sentences from the document and preserving their original positions. In contrast, abstractive summarization generates a summary by producing new, concise, and coherent sentences or phrases that aren't directly copied from the original document.
 Conversation summarization recaps and segments long meetings into timestamped chapters. Call center summarization summarizes customer issues and resolution.
    :::column-end:::
 :::row-end:::
@@ -180,7 +180,7 @@ Conversation summarization recaps and segments long meetings into timestamped ch
       :::image type="content" source="media/studio-examples/question-answering.png" alt-text="A screenshot of a question answering example." lightbox="media/studio-examples/question-answering.png":::
    :::column-end:::
    :::column span="":::
-      [Question answering](./question-answering/overview.md) is a custom feature that finds the most appropriate answer for inputs from your users, and is commonly used to build conversational client applications, such as social media applications, chat bots, and speech-enabled desktop applications.
+      [Question answering](./question-answering/overview.md) is a custom feature that identifies the most suitable answer for user inputs. This feature is typically utilized to develop conversational client applications, including social media platforms, chat bots, and speech-enabled desktop applications.
 
    :::column-end:::
 :::row-end:::
@@ -191,7 +191,7 @@ This section helps you decide which Language service feature you should use for
 
 |What do you want to do?  |Document format  |Your best solution  | Is this solution customizable?* |
 |---------|---------|---------|---------|
-| Detect and/or redact sensitive information such as PII and PHI. | Unstructured text, <br> transcribed conversations | [PII detection](./personally-identifiable-information/overview.md) | |
+| Detect and/or redact sensitive information such as `PII` and `PHI`. | Unstructured text, <br> transcribed conversations | [PII detection](./personally-identifiable-information/overview.md) | |
 | Extract categories of information without creating a custom model.     | Unstructured text         | The [preconfigured NER feature](./named-entity-recognition/overview.md) |       |
 | Extract categories of information using a model specific to your data. | Unstructured text | [Custom NER](./custom-named-entity-recognition/overview.md) | ✓ |
 |Extract main topics and important phrases.     | Unstructured text        | [Key phrase extraction](./key-phrase-extraction/overview.md) |   |

articles/ai-services/language-service/personally-identifiable-information/how-to/redact-conversation-pii.md

@@ -24,23 +24,23 @@ By default, this feature uses the latest available AI model on your input. You c
 
 ### Language support
 
-See the [PII Language Support page](../language-support.md) for more details. Currently the conversational PII GA model only supports the English language. The preview model and API support the [same list languages](../../concepts/language-support.md) as the other Language services.
+For more information, *see* the [PII Language Support page](../language-support.md). Currently the conversational PII GA model only supports the English language. The preview model and API support the [same list languages](../../concepts/language-support.md) as the other Language services.
 
 ### Region support
 
 The conversational PII API supports all Azure regions supported by the Language service.
 
 ## Submitting data
 
-You can submit the input to the API as list of conversation items. Analysis is performed upon receipt of the request. Because the API is asynchronous, there may be a delay between sending an API request, and receiving the results. For information on the size and number of requests you can send per minute and second, see the data limits below.
+You can submit the input to the API as list of conversation items. Analysis is performed upon receipt of the request. Because the API is asynchronous, there may be a delay between sending an API request, and receiving the results. For information on the size and number of requests you can send per minute and second, see the following data limits.
 
-When using the async feature, the API results are available for 24 hours from the time the request was ingested, and is indicated in the response. After this time period, the results are purged and are no longer available for retrieval.
+When you use the async feature, the API results are available for 24 hours from the time the request was ingested, and is indicated in the response. After this time period, the results are purged and are no longer available for retrieval.
 
 When you submit data to conversational PII, you can send one conversation (chat or spoken) per request.
 
 The API attempts to detect all the [defined entity categories](../concepts/conversations-entity-categories.md) for a given conversation input. If you want to specify which entities are detected and returned, use the optional `piiCategories` parameter with the appropriate entity categories.
 
-For spoken transcripts, the entities detected are returned on the `redactionSource` parameter value provided. Currently, the supported values for `redactionSource` are `text`, `lexical`, `itn`, and `maskedItn` (which maps to Speech to text REST API's `display`\\`displayText`, `lexical`, `itn` and `maskedItn` format respectively). Additionally, for the spoken transcript input, this API also provides audio timing information to empower audio redaction. For using the audioRedaction feature, use the optional `includeAudioRedaction` flag with `true` value. The audio redaction is performed based on the lexical input format.
+For spoken transcripts, the entities detected are returned on the `redactionSource` parameter value provided. Currently, the supported values for `redactionSource` are `text`, `lexical`, `itn`, and `maskedItn` (which maps to Speech to text REST API's `display`\\`displayText`, `lexical`, `itn`, and `maskedItn` format respectively). Additionally, for the spoken transcript input, this API also provides audio timing information to empower audio redaction. For using the audioRedaction feature, use the optional `includeAudioRedaction` flag with `true` value. The audio redaction is performed based on the lexical input format.
 
 > [!NOTE]
 > Conversation PII now supports 40,000 characters as document size.
@@ -56,7 +56,7 @@ When you get results from PII detection, you can stream the results to an applic
 
 1. Go to your resource overview page in the [Azure portal](https://portal.azure.com/#home)
 
-2. From the menu on the left side, select **Keys and Endpoint**. You'll need one of the keys and the endpoint to authenticate your API requests.
+2. From the menu on the left side, select **Keys and Endpoint**. You need one of the keys and the endpoint to authenticate your API requests.
 
 3. Download and install the client library package for your language of choice:
 
@@ -65,7 +65,7 @@ When you get results from PII detection, you can stream the results to an applic
     |.NET     | [1.0.0](https://www.nuget.org/packages/Azure.AI.Language.Conversations/1.0.0)        |
     |Python     | [1.0.0](https://pypi.org/project/azure-ai-language-conversations/1.1.0b2)         |
 
-4. See the following reference documentation for more information on the client, and return object:
+4. For more information on the client and return object, *see* the following reference documentation:
 
     * [C#](/dotnet/api/azure.ai.language.conversations)
     * [Python](/python/api/azure-ai-language-conversations/azure.ai.language.conversations.aio)
@@ -74,17 +74,17 @@ When you get results from PII detection, you can stream the results to an applic
 
 ## Redaction Policy (version 2024-11-15-preview only)
 
-In version 2024-11-15-preview, you're able to define the `redactionPolicy` parameter to reflect the redaction policy to be used when redacting the document in the response. The policy field supports 3 policy types:
+In version 2024-11-15-preview, you're able to define the `redactionPolicy` parameter to reflect the redaction policy to be used when redacting the document in the response. The policy field supports three policy types:
 
 - `noMask`
 - `characterMask` (default)
 - `entityMask`
 
 The `noMask` policy allows the user to return the response without the `redactedText` field.
 
-The `characterMask` policy allows the `redactedText` to be masked with a character, preserving the length and offset of the original text. This is the existing behavior.
+The `characterMask` policy allows the `redactedText` to be masked with a character, preserving the length and offset of the original text. This behavior is the existing expectation.
 
-There is also an optional field called `redactionCharacter` where you can input the character to be used in redaction if you're using the `characterMask` policy
+There's also an optional field called `redactionCharacter` where you can input the character to be used in redaction if you're using the `characterMask` policy
 
 The `entityMask` policy allows you to mask the detected PII entity text with the detected entity type
 

articles/ai-services/language-service/personally-identifiable-information/how-to/redact-document-pii.md

@@ -7,7 +7,7 @@ author: jboback
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: how-to
-ms.date: 01/31/2025
+ms.date: 03/05/2025
 ms.author: lajanuar
 ms.custom: language-service-pii
 ---
@@ -17,7 +17,7 @@ ms.custom: language-service-pii
 > [!IMPORTANT]
 >
 > * Azure AI Language public preview releases provide early access to features that are in active development.
-> * Features, approaches, and processes may change, prior to General Availability (GA), based on user feedback.
+> * Features, approaches, and processes may 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.
 
@@ -61,7 +61,7 @@ A native document refers to the file format used to create the original document
 * For this project, we use the cURL command line tool to make REST API calls.
 
     > [!NOTE]
-    > The cURL package is pre-installed on most Windows 10 and Windows 11 and most macOS and Linux distributions. You can check the package version with the following commands:
+    > The cURL package is preinstalled on most Windows 10 and Windows 11 and most macOS and Linux distributions. You can check the package version with the following commands:
     > Windows: `curl.exe -V`
     > macOS `curl -V`
     > Linux: `curl --version`
@@ -84,9 +84,9 @@ A native document refers to the file format used to create the original document
 
   1. **Subscription**. Select one of your available Azure subscriptions.
 
-  1. **Resource Group**. You can create a new resource group or add your resource to a pre-existing resource group that shares the same lifecycle, permissions, and policies.
+  1. **Resource Group**. You can create a new resource group or add your resource to a preexisting resource group that shares the same lifecycle, permissions, and policies.
 
-  1. **Resource Region**. Choose **Global** unless your business or application requires a specific region. If you're planning on using a [system-assigned managed identity (RBAC)](../../concepts/role-based-access-control.md) for authentication, choose a **geographic** region like **West US**.
+  1. **Resource Region**. Choose **Global** unless your business or application requires a specific region. If you're planning on using a [system-assigned managed identity](../../concepts/role-based-access-control.md) for authentication, choose a **geographic** region like **West US**.
 
   1. **Name**. Enter the name you chose for your resource. The name you choose must be unique within Azure.