update latest steps

Author: eric-urban

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

@@ -8,7 +8,7 @@ manager: nitinme
 ms.service: cognitive-services
 ms.subservice: language-service
 ms.topic: tutorial
-ms.date: 01/26/2023
+ms.date: 03/02/2023
 ms.author: aahi
 ms.custom: cogserv-non-critical-language
 ---
@@ -27,52 +27,57 @@ In this tutorial, you'll create a Power Automate flow to extract entities found
 
 ## 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/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.
+* Once you have your 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, select **Go to resource**.
+    * You will need the key and endpoint from the resource you create to connect your application to the API. You'll paste your key and endpoint into the code below later in the quickstart.
+    * You can use the free pricing tier (`Free F0`) to try the service, and upgrade later to a paid tier for production.
+* Optional for this tutorial: A trained model is required 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).
 
 ## Create a Power Automate flow
 
+For this tutorial, you will create a flow that extracts named entities from text.
+
 1. [Sign in to power automate](https://make.powerautomate.com/)
 
-2. From the left side menu, select **My flows** and create a **Automated cloud flow**
+1. From the left side menu, select **My flows**. Then select **New flow** > **Automated cloud flow**.
 
     :::image type="content" source="../media/create-flow.png" alt-text="A screenshot of the menu for creating an automated cloud flow." lightbox="../media/create-flow.png":::
 
-3. Enter a name your flow. For example `Languageflow`.
+1. Enter a name for your flow such as `LanguageFlow`. Then select **Skip** to continue without choosing a trigger.
 
     :::image type="content" source="../media/language-flow.png" alt-text="A screenshot of automated cloud flow screen." lightbox="../media/language-flow.png":::
 
-4. Start by selecting **Manually trigger flow**.
+1. Under **Triggers** select **Manually trigger a flow**.
 
     :::image type="content" source="../media/trigger-flow.png" alt-text="A screenshot of how to manually trigger a flow." lightbox="../media/trigger-flow.png":::
 
-5. To add a Language service connector, search for **Azure Language**.
+1. Select **+ New step** to begin adding a Language service connector. 
+
+1. Under **Choose an operation** search for **Azure Language**. Then select **Azure Cognitive Service for Language**. This will narrow down the list of actions to only those that are available for Language.
 
     :::image type="content" source="../media/language-connector.png" alt-text="A screenshot of An Azure language connector." lightbox="../media/language-connector.png":::
 
-6. For this tutorial, you will create a flow that extracts named entities from text. Search for **Named entity recognition**, and select the connector.
+1. Under **Actions** search for **Named Entity Recognition**, and select the connector. 
 
     :::image type="content" source="../media/entity-connector.png" alt-text="A screenshot of a named entity recognition connector." lightbox="../media/entity-connector.png":::
 
-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.
+1. Get the 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 side menu.
 
     :::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.
+1. 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 adding the language key and endpoint to the Power Automate flow." lightbox="../media/language-auth.png":::
 
-9. Add the data in the connector
+1. Add the data in the connector
 :::image type="content" source="../media/connector-data.png" alt-text="A screenshot of data being added to the connector." lightbox="../media/connector-data.png":::
 
     > [!NOTE]
     > You will need deployment name and project name if you are using custom language capability.
 
-9. From the top navigation menu, save the flow and select **Test the flow**. In the window that appears, select **Test**. 
+1. From the top navigation menu, save the flow and select **Test the flow**. In the window that appears, select **Test**. 
 :::image type="content" source="../media/test-connector.png" alt-text="A screenshot of how to run the flow." lightbox="../media/test-connector.png":::
 
-10. After the flow runs, you will see the response in the **outputs** field.
+1. After the flow runs, you will see the response in the **outputs** field.
 
     :::image type="content" source="../media/response-connector.png" alt-text="A screenshot of flow response." lightbox="../media/response-connector.png":::