Merge pull request #234579 from aahill/ta4h-article-fixes

Ta4h article fixes

Author: American-Dipper

articles/cognitive-services/language-service/custom-text-analytics-for-health/how-to/create-project.md

@@ -25,7 +25,7 @@ Before you start using custom text analytics for health, you need:
 
 ## Create a Language resource 
 
-Before you start using custom text analytics for health, you'll need an Azure Language resource. It's recommended to create your Language resource and connect a storage account to it in the Azure portal. Creating a resource in the Azure portal lets you create an Azure storage account at the same time, with all of the required permissions preconfigured. You can also read further in the article to learn how to use a pre-existing resource, and configure it to work with custom named entity recognition.
+Before you start using custom text analytics for health, you'll need an Azure Language resource. It's recommended to create your Language resource and connect a storage account to it in the Azure portal. Creating a resource in the Azure portal lets you create an Azure storage account at the same time, with all of the required permissions preconfigured. You can also read further in the article to learn how to use a pre-existing resource, and configure it to work with custom text analytics for health.
 
 You also will need an Azure storage account where you will upload your `.txt` documents that will be used to train a model to extract entities.
 
@@ -113,6 +113,6 @@ If you have already labeled data, you can use it to get started with the service
 
 ## Next steps
 
-<!--* You should have an idea of the [project schema](design-schema.md) you will use to label your data.-->
+* You should have an idea of the [project schema](design-schema.md) you will use to label your data.
 
 * After you define your schema, you can start [labeling your data](label-data.md), which will be used for model training, evaluation, and finally making predictions.

articles/cognitive-services/language-service/custom-text-analytics-for-health/includes/language-studio/import-project.md

@@ -13,7 +13,7 @@ ms.author: aahi
 
 1. Sign into the [Language Studio](https://aka.ms/languageStudio). A window will appear to let you select your subscription and Language resource. Select your Language resource. 
 
-2. Under the **Extract information** section of Language Studio, select **Custom named entity recognition**.
+2. Under the **Extract information** section of Language Studio, select **Custom text analytics for health**.
 
     <!--:::image type="content" source="../../media/select-custom-ner.png" alt-text="A screenshot showing the location of the custom NER feature in the Language Studio landing page." lightbox="../../media/select-custom-ner.png":::-->
         

articles/cognitive-services/language-service/custom-text-analytics-for-health/includes/use-pre-existing-resource.md

@@ -20,7 +20,7 @@ You can use an existing Language resource to get started with custom NER as long
 |Pricing tier     | The pricing tier for your resource. <!--Learn more about [supported pricing tiers](../service-limits.md#language-resource-limits).-->        |
 |Managed identity     | Make sure that the resource's managed identity setting is enabled. Otherwise, read the next section. |
 
-To use custom named entity recognition, you'll need to [create an Azure storage account](../../../../storage/common/storage-account-create.md) if you don't have one already. 
+To use custom text analytics for health, you'll need to [create an Azure storage account](../../../../storage/common/storage-account-create.md) if you don't have one already. 
 
 ## Enable identity management for your resource
 
@@ -42,13 +42,13 @@ Your Language resource must have identity management, to enable it using [Langua
 
 ---
 
-### Enable custom named entity recognition feature
+### Enable custom text analytics for health
 
-Make sure to enable **Custom text classification / Custom Named Entity Recognition** feature from Azure portal.
+Make sure to enable **Custom text classification / Custom Named Entity Recognition / Custom text analytics for health** feature from Azure portal.
 
 1. Go to your Language resource in [Azure portal](https://portal.azure.com/)
 2. From the left side menu, under **Resource Management** section, select **Features**
-3. Enable **Custom text classification / Custom Named Entity Recognition** feature
+3. Enable the **Custom text classification / Custom Named Entity Recognition / Custom text analytics** feature
 4. Connect your storage account
 5. Click **Apply**
 

articles/cognitive-services/language-service/custom-text-analytics-for-health/overview.md

@@ -15,17 +15,16 @@ ms.custom: language-service-custom-ta4h, ignite-fall-2021, event-tier1-build-202
 
 # What is custom Text Analytics for health? 
 
-Custom Text Analytics for health is one of the custom features offered by [Azure Cognitive Service for Language](../overview.md). It is a cloud-based API service that applies machine-learning intelligence to enable you to build custom models on top of [Text Analytics for health)(../text-analytics-for-health/overview.md) for custom healthcare entity recognition tasks.
+Custom Text Analytics for health is one of the custom features offered by [Azure Cognitive Service for Language](../overview.md). It is a cloud-based API service that applies machine-learning intelligence to enable you to build custom models on top of [Text Analytics for health](../text-analytics-for-health/overview.md) for custom healthcare entity recognition tasks.
 
-Custom Text Analytics for health enables users to build custom AI models to extract healthcare specific entities from unstructured text, such as clinical notes and reports. By creating a custom Text Analytics for health project, developers can iteratively define new vocabulary, label data, train, evaluate, and improve model performance before making it available for consumption. The quality of the labeled data greatly impacts model performance. To simplify building and customizing your model, the service offers a custom web portal that can be accessed through the [Language studio](https://aka.ms/languageStudio). You can easily get started with the service by following the steps in this [quickstart](quickstart.md). 
+Custom Text Analytics for health enables users to build custom AI models to extract healthcare specific entities from unstructured text, such as clinical notes and reports. By creating a custom Text Analytics for health project, developers can iteratively define new vocabulary, label data, train, evaluate, and improve model performance before making it available for consumption. The quality of the labeled data greatly impacts model performance. To simplify building and customizing your model, the service offers a web portal that can be accessed through the [Language studio](https://aka.ms/languageStudio). You can easily get started with the service by following the steps in this [quickstart](quickstart.md). 
 
 This documentation contains the following article types:
 
 * [Quickstarts](quickstart.md) are getting-started instructions to guide you through creating making requests to the service.
-<!--
 * [Concepts](concepts/evaluation-metrics.md) provide explanations of the service functionality and features.
-* [How-to guides](how-to/tag-data.md) contain instructions for using the service in more specific or customized ways.
--->
+* [How-to guides](how-to/label-data.md) contain instructions for using the service in more specific or customized ways.
+
 ## Example usage scenarios
 
 Similarly to Text Analytics for health, custom Text Analytics for health can be used in multiple [scenarios](../text-analytics-for-health/overview.md#example-use-cases) across a variety of healthcare industries. However, the main usage of this feature is to provide a layer of customization on top of Text Analytics for health to extend its existing entity map.
@@ -48,7 +47,7 @@ Using custom Text Analytics for health typically involves several different step
 
 * **View the model's performance**: After training is completed, view the model's evaluation details, its performance and guidance on how to improve it. 
 
-* **Deploy the model**: Deploying a model makes it available for use via the [Analyze API](https://aka.ms/ct-runtime-swagger).
+* **Deploy the model**: Deploying a model makes it available for use via an API.
 
 * **Extract entities**: Use your custom models for entity extraction tasks.
 
@@ -74,6 +73,5 @@ An AI system includes not only the technology, but also the people who will use
 * Use the [quickstart article](quickstart.md) to start using custom Text Analytics for health.  
 
 * As you go through the project development lifecycle, review the glossary to learn more about the terms used throughout the documentation for this feature. 
-<!--
+
 * Remember to view the [service limits](reference/service-limits.md) for information such as [regional availability](reference/service-limits.md#regional-availability).
--->

articles/cognitive-services/language-service/custom-text-analytics-for-health/quickstart.md

@@ -36,14 +36,14 @@ In this article, we use Language Studio to demonstrate key concepts of custom Te
 
 * [Text analytics for health overview](./overview.md)
 
-<!--After you've created entity extraction model, you can:
+After you've created entity extraction model, you can:
 
 * [Use the runtime API to extract entities](how-to/call-api.md)
 
 When you start to create your own custom Text Analytics for health projects, use the how-to articles to learn more about data labeling, training and consuming your model in greater detail:
 
 * [Data selection and schema design](how-to/design-schema.md)
-* [Tag data](how-to/tag-data.md)
+* [Tag data](how-to/label-data.md)
 * [Train a model](how-to/train-model.md)
 * [Model evaluation](how-to/view-model-evaluation.md)
--->
+

articles/cognitive-services/language-service/includes/custom/resource-creation-language-studio.md

@@ -30,4 +30,4 @@ Create a Language resource with following details.
 > * Make sure to to enable **Managed Identity** when you create a Language resource. 
 > * Read and confirm Responsible AI notice
 
-To use custom named entity recognition, you'll need to [create an Azure storage account](../../../../storage/common/storage-account-create.md) if you don't have one already. 
+To use custom text analytics for health, you'll need to [create an Azure storage account](../../../../storage/common/storage-account-create.md) if you don't have one already.