Merge pull request #191944 from lgayhardt/azureml-ner-label-0322

Text labeling GA and NER

Author: GitHubber17

articles/machine-learning/how-to-create-text-labeling-projects.md

@@ -7,26 +7,21 @@ ms.author: sgilley
 ms.service: machine-learning
 ms.subservice: mldata
 ms.topic: how-to
-ms.date: 10/21/2021
+ms.date: 03/18/2022
 ms.custom: data4ml, ignite-fall-2021
 ---
 
-# Create a text labeling project and export labels (preview)
+# Create a text labeling project and export labels
 
 Learn how to create and run data labeling projects to label text data in Azure Machine Learning.  Specify either a single label or multiple labels to be applied to each text item.
 
 You can also use the data labeling tool to [create an image labeling project](how-to-create-image-labeling-projects.md).
 
-> [!IMPORTANT]
-> Text labeling is currently in public preview.
-> The preview version is provided without a service level agreement, and it's not recommended for production workloads. Certain features might not be supported or might have constrained capabilities.
-> For more information, see [Supplemental Terms of Use for Microsoft Azure Previews](https://azure.microsoft.com/support/legal/preview-supplemental-terms/).
-
 ## Text labeling capabilities
 
 Azure Machine Learning data labeling is a central place to create, manage, and monitor data labeling projects:
 
-- Coordinate data, labels, and team members to efficiently manage labeling tasks. 
+- Coordinate data, labels, and team members to efficiently manage labeling tasks.
 - Tracks progress and maintains the queue of incomplete labeling tasks.
 - Start and stop the project and control the labeling progress.
 - Review the labeled data and export labeled as an Azure Machine Learning dataset.
@@ -47,22 +42,28 @@ Data formats available for text data:
 
 [!INCLUDE [start](../../includes/machine-learning-data-labeling-start.md)]
 
-1. To create a project, select **Add project**. Give the project an appropriate name. The project name cannot be reused, even if the project is deleted in future.
+1. To create a project, select **Add project**. Give the project an appropriate name. The project name can’t be reused, even if the project is deleted in future.
 
 1. Select **Text** to create a text labeling project.
 
-    :::image type="content" source="media/how-to-create-labeling-projects/text-labeling-creation-wizard.png" alt-text="Labeling project creation for text labeling":::
+    :::image type="content" source="media/how-to-create-text-labeling-projects/text-labeling-creation-wizard.png" alt-text="Labeling project creation for text labeling":::
+
+    * Choose **Text Classification Multi-class** for projects when you want to apply only a *single label* from a set of labels to each piece of text.
+    * Choose **Text Classification Multi-label** for projects when you want to apply *one or more* labels from a set of labels to each piece of text. 
+    * Choose **Text Named Entity Recognition (Preview)** for projects when you want to apply labels to individual or multiple words of text in each entry.
 
-    * Choose **Text Classification Multi-class (Preview)** for projects when you want to apply only a *single label* from a set of labels to each piece of text.
-    * Choose **Text Classification Multi-label (Preview)** for projects when you want to apply *one or more* labels from a set of labels to each piece of text.
+    > [!IMPORTANT]
+    > Text Named Entity Recognition is currently in public preview.
+    > The preview version is provided without a service level agreement, and it's not recommended for production workloads. Certain features might not be supported or might have constrained capabilities.
+    > For more information, see [Supplemental Terms of Use for Microsoft Azure Previews](https://azure.microsoft.com/support/legal/preview-supplemental-terms/).
 
 1. Select **Next** when you're ready to continue.
 
 ## Add workforce (optional)
 
 [!INCLUDE [outsource](../../includes/machine-learning-data-labeling-outsource.md)]
 
-## Specify the data to label
+## Select or create a dataset
 
 If you already created a dataset that contains your data, select it from the **Select an existing dataset** drop-down list. Or, select **Create a dataset** to use an existing Azure datastore or to upload local files.
 
@@ -78,7 +79,7 @@ To create a dataset from data that you've already stored in Azure Blob storage:
 1. Select **Create a dataset** > **From datastore**.
 1. Assign a **Name** to your dataset.
 1. Choose the **Dataset type**:
-    * Select **Tabular** if you're using a .csv or .tsv file, where each row contains a response.
+    * Select **Tabular** if you're using a .csv or .tsv file, where each row contains a response. Tabular isn't available for Text Named Entity Recognition projects.
     * Select **File** if you're using separate .txt files for each response.
 1. (Optional) Provide a description for your dataset.
 1. Select **Next**.
@@ -96,7 +97,7 @@ To directly upload your data:
 1. Select **Create a dataset** > **From local files**.
 1. Assign a **Name** to your dataset.
 1. Choose the **Dataset type**.
-    * Select **Tabular** if you're using a .csv or .tsv file, where each row is a response.
+    * Select **Tabular** if you're using a .csv or .tsv file, where each row is a response. Tabular isn't available for Text Named Entity Recognition projects. 
     * Select **File** if you're using separate .txt files for each response.
 1. (Optional) Provide a description of your dataset.
 1. Select **Next**
@@ -131,7 +132,6 @@ To directly upload your data:
 ## Use ML-assisted data labeling
 
 The **ML-assisted labeling** page lets you trigger automatic machine learning models to accelerate labeling tasks. ML-assisted labeling is available for both file (.txt) and tabular (.csv) text data inputs.
-
 To use **ML-assisted labeling**:
 
 * Select **Enable ML assisted labeling**.
@@ -144,7 +144,7 @@ At the beginning of your labeling project, the items are shuffled into a random
 
 For training the text DNN model used by ML-assist, the input text per training example will be limited to approximately the first 128 words in the document.  For tabular input, all text columns are first concatenated before applying this limit. This is a practical limit imposed to allow for the model training to complete in a timely manner. The actual text in a document (for file input) or set of text columns (for tabular input) can exceed 128 words.  The limit only pertains to what is internally leveraged by the model during the training process.
 
-The exact number of labeled items necessary to start assisted labeling is not a fixed number. This can vary significantly from one labeling project to another, depending on many factors, including the number of labels classes and label distribution.
+The exact number of labeled items necessary to start assisted labeling isn't a fixed number. This can vary significantly from one labeling project to another, depending on many factors, including the number of labels classes and label distribution.
 
 Since the final labels still rely on input from the labeler, this technology is sometimes called *human in the loop* labeling.
 
@@ -167,13 +167,12 @@ Once a machine learning model has been trained on your manually labeled data, th
 
 ### Dashboard
 
-
 The **Dashboard** tab shows the progress of the labeling task.
 
-:::image type="content" source="./media/how-to-create-labeling-projects/text-labeling-dashboard.png" alt-text="Text data labeling dashboard":::
+:::image type="content" source="./media/how-to-create-text-labeling-projects/text-labeling-dashboard.png" alt-text="Text data labeling dashboard":::
 
 
-The progress chart shows how many items have been labeled, skipped, in need of review, or not yet done.  Hover over the chart to see the number of item in each section.
+The progress chart shows how many items have been labeled, skipped, in need of review, or not yet done.  Hover over the chart to see the number of items in each section.
 
 The middle section shows the queue of tasks yet to be assigned. If ML-assisted labeling is on, you'll also see the number of pre-labeled items.
 
@@ -189,7 +188,7 @@ On the **Data** tab, you can see your dataset and review labeled data. Scroll th
 View and change details of your project.  In this tab you can:
 
 * View project details and input datasets
-* Enable or disable **incremental refresh at regular intervals** or request an immediate refresh
+* Enable or disable **incremental refresh at regular intervals**, or request an immediate refresh.
 * View details of the storage container used to store labeled outputs in your project
 * Add labels to your project
 * Edit instructions you give to your labels
@@ -206,11 +205,17 @@ View and change details of your project.  In this tab you can:
 
 Use the **Export** button on the **Project details** page of your labeling project. You can export the label data for Machine Learning experimentation at any time.
 
-You can export:
-
+For all project types other than **Text Named Entity Recognition**, you can export:
 * A CSV file. The CSV file is created in the default blob store of the Azure Machine Learning workspace in a folder within *Labeling/export/csv*. 
 * An [Azure Machine Learning dataset with labels](how-to-use-labeled-dataset.md). 
 
+
+For **Text Named Entity Recognition** projects, you can export:
+* An [Azure Machine Learning dataset with labels](how-to-use-labeled-dataset.md). 
+* A CoNLL file.  For this export, you'll also have to assign a compute resource. The export process runs offline and generates the file as part of an experiment run.  When the file is ready to download, you'll see a notification on the top right.  Select this to open the notification, which includes the link to the file.
+
+    :::image type="content" source="media/how-to-create-text-labeling-projects/notification-bar.png" alt-text="Notification for file download.":::
+
 Access exported Azure Machine Learning datasets in the **Datasets** section of Machine Learning. The dataset details page also provides sample code to access your labels from Python.
 
 ![Exported dataset](./media/how-to-create-labeling-projects/exported-dataset.png)
@@ -219,7 +224,6 @@ Access exported Azure Machine Learning datasets in the **Datasets** section of M
 
 [!INCLUDE [troubleshooting](../../includes/machine-learning-data-labeling-troubleshooting.md)]
 
-
 ## Next steps
 
 * [How to tag text](how-to-label-data.md#label-text)