note and edits

Author: aahill

articles/cognitive-services/language-service/conversational-language-understanding/how-to/call-api.md

@@ -20,9 +20,6 @@ You can query the deployment programmatically through the [prediction API](https
 
 ## Test deployed model
 
-> [!Note]
-> You can use your custom model in an [power automate flow](../../tutorials/power-automate.md)
-
 You can use Language Studio to submit an utterance, get predictions and visualize the results.
 
 [!INCLUDE [Test model](../includes/language-studio/test-model.md)]

articles/cognitive-services/language-service/custom-named-entity-recognition/how-to/call-api.md

@@ -21,9 +21,6 @@ You can query the deployment programmatically using the [Prediction API](https:/
 
 ## Test deployed model
 
-> [!Note]
-> You can use your custom model in an [power automate flow](../../tutorials/power-automate.md)
-
 You can use Language Studio to submit the custom entity recognition task and visualize the results. 
 
 [!INCLUDE [Test model](../includes/language-studio/test-model.md)]

articles/cognitive-services/language-service/custom-text-classification/how-to/call-api.md

@@ -21,9 +21,6 @@ You can query the deployment programmatically [Prediction API](https://aka.ms/ct
 
 ## Test deployed model
 
-> [!Note]
-> You can use your custom model in an [power automate flow](../../tutorials/power-automate.md)
-
 You can use Language Studio to submit the custom text classification task and visualize the results. 
 
 [!INCLUDE [Test model](../includes/language-studio/test-model.md)]

articles/cognitive-services/language-service/custom-text-classification/tutorials/triage-email.md

@@ -1,62 +1,70 @@
 ---
-title: Traige incoming emails with power automate
+title: Triage incoming emails with Power Automate
 titleSuffix: Azure Cognitive Services
-description: Traige incoming emails with power automate
+description: Learn how to use custom text classification to categorize and triage incoming emails with Power Automate
 services: cognitive-services
 author: aahill
 manager: nitinme
 ms.service: cognitive-services
 ms.subservice: language-service
 ms.topic: tutorial
-ms.date: 06/03/2022
+ms.date: 01/27/2023
 ms.author: aahi
-ms.custom: 
 ---
 
-# Tutorial: Traige incoming emails with power automate
+# Tutorial: Triage incoming emails with power automate
 
-In this tutorial we will triage incoming email using custom single text classification project type. When a new email is received, the content of the body gets classified and depending on the classificaiton result, a message is sent to the specialized team on Microsoft Teams.
+In this tutorial you will categorize and triage incoming email using custom text classification. Using this [Power Automate](https://learn.microsoft.com/power-automate/getting-started) flow, when a new email is received, its contents will have a classification applied, and depending on the result, a message will be sent to a designated channel on [Microsoft Teams](https://www.microsoft.com/microsoft-teams).
 
 
 ## Prerequisites
-* Azure subscription, <a href="https://portal.azure.com/#create/Microsoft.CognitiveServicesTextAnalytics"  title="Create a Language resource"  target="_blank">create a Language resource </a> in the Azure portal to get your key and endpoint. After it deploys, click **Go to resource**.
-    * You will need the key and endpoint from the resource you created in your power automate flow.
-    * Successfully created and deployed a [single text classification custom model](../quickstart.md).
 
+* Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services)
+* <a href="https://portal.azure.com/#create/Microsoft.CognitiveServicesTextAnalytics"  title="Create a Language resource"  target="_blank">A Language resource </a>
+    * (optional) A trained model if you're using a custom capability such as [custom NER](../custom-named-entity-recognition/overview.md), [custom text classification](../custom-text-classification/overview.md), or [conversational language understanding](../conversational-language-understanding/overview.md).
+    * You will need the key and endpoint from your Language resource to authenticate your Power Automate flow.
+* A successfully created and deployed [single text classification custom model](../quickstart.md)
 
-## Create a power automate flow
 
-1- [Signin to power automate](https://make.powerautomate.com/)
+## Create a Power Automate flow
 
-2- From the left side menu, choose *My flows* and create a *Automated cloud flow*
-:::image type="content" source="../media/create-flow.png" alt-text="A screenshot of the flow creation." lightbox="../media/create-flow.png":::
+1. [Sign in to power automate](https://make.powerautomate.com/)
 
-3- Name your flow as *EmailTriage*, from triggers search for *email* and choose *When a new email arrives* option then click *create*
-:::image type="content" source="../media/email-flow.png" alt-text="A screenshot of the language flow." lightbox="../media/email-flow.png":::
+2. From the left side menu, select **My flows** and create a **Automated cloud flow**
 
-4- Start by adding the right connection to your email. This connection will be used to access the email content.
+    :::image type="content" source="../media/create-flow.png" alt-text="A screenshot of the flow creation screen." lightbox="../media/create-flow.png":::
 
-5- To add a Language connector, search for *Azure Language* 
-:::image type="content" source="../media/language-connector.png" alt-text="A screenshot of azure language connectors." lightbox="../media/language-connector.png":::
+3. Name your flow `EmailTriage`. Below **Choose your flow's triggers**, search for *email* and select **When a new email arrives**. Then click **create**
 
-6- Search for *CustomSingleLabelClassification*
-:::image type="content" source="../media/single-classification.png" alt-text="A screenshot of Classification connector." lightbox="../media/single-classification.png":::
+    :::image type="content" source="../media/email-flow.png" alt-text="A screenshot of the email flow triggers." lightbox="../media/email-flow.png":::
 
-7- Start by adding the right connection to your connector. This connection will be used to access the classification project.
+4. Add the right connection to your email account. This connection will be used to access the email content.
 
-8- In documents id field, add **1**.
+5. To add a Language service connector, search for *Azure Language*.
+  
+    :::image type="content" source="../media/language-connector.png" alt-text="A screenshot of available Azure Language service connectors." lightbox="../media/language-connector.png":::
 
-9- In documents text field add *body* from dynamic content.
+6. Search for *CustomSingleLabelClassification*.
 
-10- Fill in the project name and deployment name of your deployed model
+    :::image type="content" source="../media/single-classification.png" alt-text="A screenshot of Classification connector." lightbox="../media/single-classification.png":::
 
-:::image type="content" source="../media/classification.png" alt-text="A screenshot project details." lightbox="../media/classification.png":::
+7. Start by adding the right connection to your connector. This connection will be used to access the classification project.
 
-11- Add condition to send a Microsoft Teams message to the righ team. Choose *results* from dynamic content and add the condition. For this tutorial, we are looking for *Computer_science* related emails. In the *Yes* condition, choose your desired option to notify the team. In the *No* condition, you can add further condition to check other cases and do alternative actions.
+8. In the documents ID field, add **1**.
 
-:::image type="content" source="../media/email-triage.png" alt-text="A screenshot of email flow." lightbox="../media/email-triage.png":::
+9. In the documents text field, add **body** from **dynamic content**.
+
+10. Fill in the project name and deployment name of your deployed custom text classification model.
+
+    :::image type="content" source="../media/classification.png" alt-text="A screenshot project details." lightbox="../media/classification.png":::
+
+11. Add a condition to send a Microsoft Teams message to the right team by:
+    1. Select **results** from **dynamic content**, and add the condition. For this tutorial, we are looking for `Computer_science` related emails. In the **Yes** condition, choose your desired option to notify a team channel. In the **No** condition, you can add additional conditions to perform alternative actions.
+
+    :::image type="content" source="../media/email-triage.png" alt-text="A screenshot of email flow." lightbox="../media/email-triage.png":::
 
 
 ## Next steps
 
-[Language studio overview](../../language-studio.md)
+* [Use the Language service with Power Automate](../../tutorials/power-automate.md)
+* [Available Language service connectors](/connectors/cognitiveservicestextanalytics)

articles/cognitive-services/language-service/entity-linking/how-to/call-api.md

@@ -22,9 +22,6 @@ The entity linking feature can be used to identify and disambiguate the identity
 
 [!INCLUDE [development-options](../includes/development-options.md)]
 
-> [!Note]
-> You can use this feature in an [power automate flow](../../tutorials/power-automate.md)
-
 ## Determine how to process the data (optional)
 
 ### Specify the entity linking model

articles/cognitive-services/language-service/language-detection/how-to/call-api.md

@@ -25,9 +25,6 @@ The Language Detection feature can detect a wide range of languages, variants, d
 
 [!INCLUDE [development options](../includes/development-options.md)]
 
-> [!Note]
-> You can use this feature in an [power automate flow](../../tutorials/power-automate.md)
-
 ## Determine how to process the data (optional)
 
 ### Specify the language detection model

articles/cognitive-services/language-service/summarization/how-to/conversation-summarization.md

@@ -50,9 +50,6 @@ When you submit data to conversation summarization, we recommend sending one cha
 
 You can use conversation issue and resolution summarization to get summaries as you need. To see an example using text chats, see the [quickstart article](../quickstart.md).
 
-> [!Note]
-> You can use this feature in an [power automate flow](../../tutorials/power-automate.md)
-
 ### Get summaries from speech transcriptions 
 
 Conversation issue and resolution summarization also enables you to get summaries from speech transcripts by using the [Speech service's speech-to-text feature](../../../Speech-Service/call-center-overview.md). The following example shows a short conversation that you might include in your API requests.

articles/cognitive-services/language-service/text-analytics-for-health/how-to/call-api.md

@@ -86,9 +86,6 @@ To receive your result using the **FHIR** structure, you must send the FHIR vers
 
 ## Getting results from the feature
 
-> [!Note]
-> You can use this feature in an [power automate flow](../../tutorials/power-automate.md)
-
 Depending on your API request, and the data you submit to the Text Analytics for health, you will get:
 
 [!INCLUDE [Text Analytics for health features](../includes/features.md)]

articles/cognitive-services/language-service/tutorials/power-automate.md

@@ -26,7 +26,7 @@ You can use [Power Automate](/power-automate/getting-started) flows to automate
 ## Prerequisites
 * Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services)
 * <a href="https://portal.azure.com/#create/Microsoft.CognitiveServicesTextAnalytics"  title="Create a Language resource"  target="_blank">A Language resource </a>
-    * (optional) A trained model if you're using a custom capability such as [custom NER](../custom-named-entity-recognition/overview.md), [custom text classification](../custom-text-classification/), or [conversational language understanding](../conversational-language-understanding/overview.md).
+    * (optional) A trained model if you're using a custom capability such as [custom NER](../custom-named-entity-recognition/overview.md), [custom text classification](../custom-text-classification/overview.md), or [conversational language understanding](../conversational-language-understanding/overview.md).
     * You will need the key and endpoint from your Language resource to authenticate your Power Automate flow.
 
 ## Create a Power Automate flow
@@ -55,11 +55,11 @@ You can use [Power Automate](/power-automate/getting-started) flows to automate
 
 7. Add endpoint and key for your Language resource, which will be used for authentication. You can find your key and endpoint by navigating to your resource in the [Azure portal](https://portal.azure.com), and selecting **Keys and endpoint** from the left navigation menu.
 
-    :::image type="content" source="../media/azure-portal-resource-credentials.png" alt-text="A screenshot of language key and endpoint." lightbox="../media/azure-portal-resource-credentials.png":::
+    :::image type="content" source="../media/azure-portal-resource-credentials.png" alt-text="A screenshot of A language resource key and endpoint in the Azure portal." lightbox="../media/azure-portal-resource-credentials.png":::
 
 8. Once you have your key and endpoint, add it to the connector in Power Automate.
 
-    :::image type="content" source="../media/language-auth.png" alt-text="A screenshot of language key and endpoint." lightbox="../media/language-auth.png":::
+    :::image type="content" source="../media/language-auth.png" alt-text="A screenshot of adding the language key and endpoint to the Power Automate flow." lightbox="../media/language-auth.png":::
 
 9. Add the data in the connector
 :::image type="content" source="../media/ner-connector.png" alt-text="A screenshot of the NER connector." lightbox="../media/ner-connector.png":::