Merge pull request #222958 from aahill/rena-prs

Rena PRs

Author: 19BMG00

articles/cognitive-services/language-service/custom-text-classification/includes/language-studio/create-project.md

@@ -42,6 +42,8 @@ ms.custom: ignite-fall-2021, event-tier1-build-2022
 6. Select the container where you have uploaded your dataset. 
 
     >[!Note]
-    > If you have already labeled your data make sure it follows the [supported format](../../concepts/data-formats.md) and click on **Yes, my documents are already labeled and I have formatted JSON labels file** and select the labels file from the drop-down menu below. Click **Next**.
+    > If you have already labeled your data make sure it follows the [supported format](../../concepts/data-formats.md) and click on **Yes, my documents are already labeled and I have formatted JSON labels file** and select the labels file from the drop-down menu below. 
+ 
+    > If you’re using one of the example datasets, use the included `webOfScience_labelsFile` or `movieLabels` json file. Then click **Next**.
     
 7. Review the data you entered and select **Create Project**.

articles/cognitive-services/language-service/custom-text-classification/includes/language-studio/test-model.md

@@ -20,7 +20,7 @@ To test your deployed models within [Language Studio](https://aka.ms/LanguageStu
 
 4. Select the deployment you want to query/test from the dropdown.
 
-5. Enter the text you want to submit in the request, or upload a `.txt` document to use.
+5. Enter the text you want to submit in the request, or upload a `.txt` document to use. If you’re using one of the example datasets, you can use one of the included .txt files.
 
 6. Click on **Run the test** from the top menu.
 

articles/cognitive-services/language-service/custom-text-classification/includes/language-studio/train-model.md

@@ -28,5 +28,5 @@ To start training your model from within the [Language Studio](https://aka.ms/La
 
     > [!NOTE]
     > * Only successfully completed training jobs will generate models.
-    > * Training can take some time between a couple of minutes and several hours based on the size of your labeled data.
+    > * The time to train the model can take anywhere between a few minutes to several hours based on the size of your labeled data.
     > * You can only have one training job running at a time. You can't start other training job within the same project until the running job is completed.

articles/cognitive-services/language-service/custom-text-classification/includes/quickstarts/blob-storage-upload.md

@@ -43,7 +43,9 @@ The provided sample dataset contains about 210 documents, each of which is an ab
 
 ---
 
-2. In the [Azure portal](https://portal.azure.com), navigate to the storage account you created, and select it.
+2. In the [Azure portal](https://portal.azure.com), navigate to the storage account you created, and select it. You can do this by clicking **Storage accounts** and typing your storage account name into **Filter for any field**.
+
+    if your resource group does not show up, make sure the **Subscription equals** filter is set to **All**.
 
 3. In your storage account, select **Containers** from the left menu, located below **Data storage**. On the screen that appears, select **+ Container**. Give the container the name **example-data** and leave the default **Public access level**.
 

articles/cognitive-services/language-service/custom-text-classification/includes/resource-creation-azure-portal.md

@@ -29,8 +29,12 @@ ms.custom: language-service-custom-classification, event-tier1-build-2022
     | Name | A name for your resource. |
     |Pricing tier     | One of the [supported pricing tiers](../service-limits.md#pricing-tiers). You can use the Free (F0) tier to try the service.       |
 
-    > [!NOTE]
-    > If you get a message saying "*your login account is not an owner of the selected storage account's resource group*", your account needs to have an owner role assigned on the resource group before you can create a Language resource. Contact your Azure subscription owner for assistance.
+    If you get a message saying "*your login account is not an owner of the selected storage account's resource group*", your account needs to have an owner role assigned on the resource group before you can create a Language resource. Contact your Azure subscription owner for assistance. 
+	
+	You can determine your Azure subscription owner by [searching your resource group](https://ms.portal.azure.com/#view/HubsExtension/BrowseResourceGroups) and following the link to its associated subscription. Then: 
+	1. Select the **Access Control (IAM)** tab
+	2. Select **Role assignments** 
+	3. Filter by **Role:Owner**.
 
 1. In the **Custom text classification & custom named entity recognition** section, select an existing storage account or select **New storage account**. Note that these values are to help you get started, and not necessarily the [storage account values](../../../../storage/common/storage-account-overview.md) you’ll want to use in production environments. To avoid latency during building your project connect to storage accounts in the same region as your Language resource.
 
@@ -39,4 +43,4 @@ ms.custom: language-service-custom-classification, event-tier1-build-2022
     | Storage account name | Any name |
     | Storage account type | Standard LRS |
 
-1. Make sure the **Responsible AI Notice** is checked. Select **Review + create** at the bottom of the page, then select.
+1. Make sure the **Responsible AI Notice** is checked. Select **Review + create** at the bottom of the page.

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

@@ -19,7 +19,9 @@ Azure Cognitive Service for Language is a cloud-based service that provides Natu
 
 ## Available features
 
-This Language service unifies Text Analytics, QnA Maker, and LUIS and provides several new features as well. These features can either be:
+This Language service unifies the following previously available Cognitive 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.
+
+The Language service also provides several new features as well, which can either be:
 
 * Pre-configured, 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.
@@ -36,7 +38,7 @@ This Language service unifies Text Analytics, QnA Maker, and LUIS and provides s
       :::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 pre-configured feature that identifies entities in unstructured text across several pre-defined categories. For example: people, events, places, dates, [and more](./named-entity-recognition/concepts/named-entity-categories.md).
+      [Named entity recognition](./named-entity-recognition/overview.md) is a pre-configured feature that categorizes entities (words or phrases) in unstructured text across several pre-defined category groups. For example: people, events, places, dates, [and more](./named-entity-recognition/concepts/named-entity-categories.md).
 
    :::column-end:::
 :::row-end:::
@@ -106,7 +108,7 @@ This Language service unifies Text Analytics, QnA Maker, and LUIS and provides s
       :::image type="content" source="media/studio-examples/entity-linking.png" alt-text="A screenshot of an entity linking example." lightbox="media/studio-examples/entity-linking.png":::
    :::column-end:::
    :::column span="":::
-      [Entity linking](./entity-linking/overview.md) is a pre-configured feature that disambiguates the identity of entities found in unstructured text and returns links to Wikipedia. 
+      [Entity linking](./entity-linking/overview.md) is a pre-configured feature that disambiguates the identity of entities (words or phrases) found in unstructured text and returns links to Wikipedia. 
    :::column-end:::
 :::row-end:::
 
@@ -128,7 +130,7 @@ This Language service unifies Text Analytics, QnA Maker, and LUIS and provides s
       :::image type="content" source="media/studio-examples/single-classification.png" alt-text="A screenshot of a custom text classification example." lightbox="media/studio-examples/single-classification.png":::
    :::column-end:::
    :::column span="":::
-      [Custom text classification](./custom-text-classification/overview.md) enables you to build custom AI models to classify text into custom classes you define.
+      [Custom text classification](./custom-text-classification/overview.md) enables you to build custom AI models to classify unstructured text documents into custom classes you define.
    :::column-end:::
 :::row-end:::
 
@@ -140,7 +142,7 @@ This Language service unifies Text Analytics, QnA Maker, and LUIS and provides s
       :::image type="content" source="media/studio-examples/custom-named-entity-recognition.png" alt-text="A screenshot of a custom NER example." lightbox="media/studio-examples/custom-named-entity-recognition.png":::
    :::column-end:::
    :::column span="":::
-      [Custom NER](custom-named-entity-recognition/overview.md) enables you to build custom AI models to extract custom entity categories, using unstructured text that you provide. 
+      [Custom NER](custom-named-entity-recognition/overview.md) enables you to build custom AI models to extract custom entity categories (labels for words or phrases), using unstructured text that you provide. 
    :::column-end:::
 :::row-end:::