edits

Author: diberry

articles/cognitive-services/LUIS/luis-tutorial-composite-entity.md

@@ -1,16 +1,8 @@
 ---
 title: "Tutorial: Composite entity tutorial - LUIS"
-titleSuffix: Azure Cognitive Services
 description: In this tutorial, add a composite entity to bundle extracted data of various types into a single containing entity. By bundling the data, the client application can easily extract related data in different data types.
-services: cognitive-services
-author: diberry
-manager: nitinme
-ms.custom: seodec18
-ms.service: cognitive-services
-ms.subservice: language-understanding
 ms.topic: tutorial
-ms.date: 12/17/2019
-ms.author: diberry
+ms.date: 03/31/2020
 ---
 
 # Tutorial: Group and extract related data
@@ -103,11 +95,11 @@ LUIS provides several prebuilt entities for common data extraction.
 
 ## Train the app so the changes to the intent can be tested
 
-[!INCLUDE [LUIS How to Train steps](../../../includes/cognitive-services-luis-tutorial-how-to-train.md)]
+To train the app, select **Train**. Training applies the changes, such as the new entities and the labeled utterances, to the active model.
 
-## Publish the app so the trained model is queryable from the endpoint
+## Publish the app to access it from the HTTP endpoint
 
-[!INCLUDE [LUIS How to Publish steps](../../../includes/cognitive-services-luis-tutorial-how-to-publish.md)]
+[!INCLUDE [LUIS How to Publish steps](includes/howto-publish.md)]
 
 ## Get intent and entity prediction from endpoint
 
@@ -183,7 +175,7 @@ LUIS provides several prebuilt entities for common data extraction.
 
 ## Clean up resources
 
-[!INCLUDE [LUIS How to clean up resources](../../../includes/cognitive-services-luis-tutorial-how-to-clean-up-resources.md)]
+[!INCLUDE [LUIS How to clean up resources](includes/quickstart-tutorial-cleanup-resources.md)]
 
 ## Related information
 

articles/cognitive-services/LUIS/tutorial-entity-roles.md

@@ -85,14 +85,19 @@ The prebuilt entity, **geographyV2**, extracts location information, including c
     > ![Add geographyV2 prebuilt entity to app](media/tutorial-entity-roles/add-geographyV2-prebuilt-entity.png)
 
 1. Select the checkbox and select **Done**.
+
+## Add roles to prebuilt entity
+
 1. In the **Entities** list, select the **geographyV2** to open the new entity.
-1. To add a role, select Add two roles, `Origin`, and `Destination`.
+1. To add a role, select **+** and add the following two roles: `Origin`, and `Destination`.
 
     > [!div class="mx-imgBorder"]
     > ![Add roles to prebuilt entity](media/tutorial-entity-roles/add-roles-to-prebuilt-entity.png)
 
+## Label entity roles in example utterances
+
 1. Select **Intents** from the left-side navigation, then select the **MoveEmployeeToCity** intent. Notice the city names are labeled with the prebuilt entity **geographyV2**.
-1. In the context toolbar, select the **Entity palette**.
+1. In the context toolbar, select the **Entity palette** with the _pencil icon_.
 
     > [!div class="mx-imgBorder"]
     > ![Select Entity Palette from content toolbar](media/tutorial-entity-roles/intent-detail-context-toolbar-select-entity-palette.png)
@@ -112,18 +117,21 @@ The prebuilt entity, **geographyV2**, extracts location information, including c
 
 ## Train the app so the changes to the intent can be tested
 
-[!INCLUDE [LUIS How to Train steps](../../../includes/cognitive-services-luis-tutorial-how-to-train.md)]
+To train the app, select **Train**. Training applies the changes, such as the new entities and the labeled utterances, to the active model.
 
-## Publish the app so the trained model is queryable from the endpoint
+## Publish the app to access it from the HTTP endpoint
+
+[!INCLUDE [LUIS How to Publish steps](includes/howto-publish.md)]
 
-[!INCLUDE [LUIS How to Publish steps](../../../includes/cognitive-services-luis-tutorial-how-to-publish.md)]
 
 ## Get intent and entity prediction from endpoint
 
-1. [!INCLUDE [LUIS How to get endpoint first step](../../../includes/cognitive-services-luis-tutorial-how-to-get-endpoint.md)]
+1. [!INCLUDE [LUIS How to get endpoint first step](includes/howto-get-endpoint.md)]
+
 
+1. Go to the end of the URL in the address bar and replace _YOUR_QUERY_HERE_ with `Please move Carl Chamerlin from Tampa to Portland`.
 
-1. Go to the end of the URL in the address bar and enter `Please move Carl Chamerlin from Tampa to Portland`. The last querystring parameter is `q`, the utterance **query**. This utterance is not the same as any of the labeled utterances so it is a good test and should return the `MoveEmployee` intent with the entity extracted.
+This utterance is not the same as any of the labeled utterances so it is a good test and should return the `MoveEmployee` intent with the entity extracted.
 
     ```json
     {
@@ -165,7 +173,7 @@ The prebuilt entity, **geographyV2**, extracts location information, including c
 
 ## Clean up resources
 
-[!INCLUDE [LUIS How to clean up resources](../../../includes/cognitive-services-luis-tutorial-how-to-clean-up-resources.md)]
+[!INCLUDE [LUIS How to clean up resources](includes/quickstart-tutorial-cleanup-resources.md)]
 
 ## Related information
 

articles/cognitive-services/LUIS/tutorial-machine-learned-entity.md

@@ -1,16 +1,8 @@
 ---
 title: "Tutorial: extract structured data with machine-learned entity - LUIS"
-titleSuffix: Azure Cognitive Services
 description: Extract structured data from an utterance using the machine-learned entity. To increase the extraction accuracy, add subcomponents with descriptors and constraints.
-services: cognitive-services
-author: diberry
-manager: nitinme
-ms.custom: seodec18
-ms.service: cognitive-services
-ms.subservice: language-understanding
 ms.topic: tutorial
-ms.date: 12/17/2019
-ms.author: diberry
+ms.date: 03/31/2020
 #Customer intent: As a new user, I want to understand how to extract complex data contained in a user utterance.
 ---
 
@@ -219,7 +211,7 @@ Test the app using the interactive **Test** panel. This process lets you enter a
 
 1. [!INCLUDE [LUIS How to get endpoint first step](includes/howto-get-endpoint.md)]
 
-1. Go to the end of the URL in the address and enter the same query as you entered in the interactive test panel.
+1. Go to the end of the URL in the address and replace _YOUR_QUERY_HERE_ with the same query as you entered in the interactive test panel.
 
     `deliver a medium veggie pizza`