Merge pull request #7327 from MicrosoftDocs/main

Auto Publish – main to live - 2025-09-28 11:00 UTC

Author: learn-build-service-prod[bot]

articles/ai-services/language-service/custom-text-classification/overview.md

@@ -7,21 +7,21 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: overview
-ms.date: 03/24/2025
+ms.date: 09/27/2025
 ms.author: lajanuar
 ms.custom: language-service-custom-classification
 ---
 
 # What is custom text classification?
 
-Custom text classification is one of the custom features offered by [Azure AI Language](../overview.md). It is a cloud-based API service that applies machine-learning intelligence to enable you to build custom models for text classification tasks. 
+Custom text classification is one of the custom features offered by [Azure AI Language](../overview.md). It's a cloud-based API service that applies machine-learning intelligence to enable you to build custom models for text classification tasks. 
 
-Custom text classification enables users to build custom AI models to classify text into custom classes pre-defined by the user. By creating a custom text classification project, developers can iteratively 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 classification enables users to build custom AI models to classify text into custom classes predefined by the user. By creating a custom text classification project, developers can iteratively 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 classification supports two types of projects: 
 
-* **Single label classification** - you can assign a single class for each document in your dataset. For example, a movie script could only be classified as "Romance" or "Comedy". 
-* **Multi label classification** - you can assign multiple classes for each document in your dataset. For example, a movie script could be classified as "Comedy" or "Romance" and "Comedy".
+* **Single label classification** - you can assign a single class for each document in your dataset. For example, a movie script could only be classified as "Romance" or "Comedy."
+* **Multi label classification** - you can assign multiple classes for each document in your dataset. For example, a movie script could be classified as "Comedy" or "Romance" and "Comedy."
 
 This documentation contains the following article types:
 
@@ -31,11 +31,11 @@ This documentation contains the following article types:
 
 ## Example usage scenarios
 
-Custom text classification can be used in multiple scenarios across a variety of industries:
+Custom text classification can be used in multiple scenarios across various industries:
 
 ### Automatic emails or ticket triage
 
-Support centers of all types receive a high volume of emails or tickets containing unstructured, freeform text and attachments. Timely review, acknowledgment, and routing to subject matter experts within internal teams is critical. Email triage at this scale requires people to review and route to the right departments, which takes time and resources. Custom text classification can be used to analyze incoming text, and triage and categorize the content to be automatically routed to the relevant departments for further action.
+Support centers of all types receive a high volume of emails or tickets containing unstructured, freeform text, and attachments. Timely review, acknowledgment, and routing to subject matter experts within internal teams is critical. Email triage at this scale requires people to review and route to the right departments, which takes time and resources. Custom text classification can be used to analyze incoming text, and triage and categorize the content to be automatically routed to the relevant departments for further action.
 
 ### Knowledge mining to enhance/enrich semantic search
 
@@ -65,18 +65,18 @@ Follow these steps to get the most out of your model:
 
 As you use custom text classification, see the following reference documentation and samples for Azure AI Language:
 
-|Development option / language  |Reference documentation |Samples  |
-|---------|---------|---------|
-|REST APIs (Authoring)   | [REST API documentation](https://aka.ms/ct-authoring-swagger)        |         |
-|REST APIs (Runtime)    | [REST API documentation](https://aka.ms/ct-runtime-swagger)        |         |
-|C#  (Runtime)   | [C# documentation](/dotnet/api/azure.ai.textanalytics?view=azure-dotnet-preview&preserve-view=true)        | [C# samples - Single label classification](https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/textanalytics/Azure.AI.TextAnalytics/samples/Sample9_SingleLabelClassify.md) [C# samples - Multi label classification](https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/textanalytics/Azure.AI.TextAnalytics/samples/Sample10_MultiLabelClassify.md)       |
-| Java   (Runtime)  | [Java documentation](/java/api/overview/azure/ai-textanalytics-readme?view=azure-java-preview&preserve-view=true)        | [Java Samples - Single label classification](https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/lro/SingleLabelClassifyDocument.java) [Java Samples - Multi label classification](https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/lro/MultiLabelClassifyDocument.java) |
-|JavaScript (Runtime)     | [JavaScript documentation](/javascript/api/overview/azure/ai-text-analytics-readme?view=azure-node-preview&preserve-view=true)        | [JavaScript samples - Single label classification](https://github.com/Azure/azure-sdk-for-js/blob/%40azure/ai-text-analytics_6.0.0-beta.1/sdk/textanalytics/ai-text-analytics/samples/v5/javascript/customText.js) [JavaScript samples - Multi label classification](https://github.com/Azure/azure-sdk-for-js/blob/%40azure/ai-text-analytics_6.0.0-beta.1/sdk/textanalytics/ai-text-analytics/samples/v5/javascript/customText.js) |
-|Python (Runtime)| [Python documentation](/python/api/azure-ai-textanalytics/azure.ai.textanalytics?view=azure-python-preview&preserve-view=true)        | [Python samples - Single label classification](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/textanalytics/azure-ai-textanalytics/samples/sample_single_label_classify.py) [Python samples - Multi label classification](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/textanalytics/azure-ai-textanalytics/samples/sample_multi_label_classify.py) |
+| Development option / language | Reference documentation | Samples |
+|--|--|--|
+| REST APIs (Authoring) | [REST API documentation](https://aka.ms/ct-authoring-swagger) |  |
+| REST APIs (Runtime) | [REST API documentation](https://aka.ms/ct-runtime-swagger) |  |
+| C#  (Runtime) | [C# documentation](/dotnet/api/azure.ai.textanalytics?view=azure-dotnet-preview&preserve-view=true) | [C# samples - Single label classification](https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/textanalytics/Azure.AI.TextAnalytics/samples/Sample9_SingleLabelClassify.md) [C# samples - Multi label classification](https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/textanalytics/Azure.AI.TextAnalytics/samples/Sample10_MultiLabelClassify.md) |
+| Java   (Runtime) | [Java documentation](/java/api/overview/azure/ai-textanalytics-readme?view=azure-java-preview&preserve-view=true) | [Java Samples - Single label classification](https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/lro/SingleLabelClassifyDocument.java) [Java Samples - Multi label classification](https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/lro/MultiLabelClassifyDocument.java) |
+| JavaScript (Runtime) | [JavaScript documentation](/javascript/api/overview/azure/ai-text-analytics-readme?view=azure-node-preview&preserve-view=true) | [JavaScript samples - Single label classification](https://github.com/Azure/azure-sdk-for-js/blob/%40azure/ai-text-analytics_6.0.0-beta.1/sdk/textanalytics/ai-text-analytics/samples/v5/javascript/customText.js) [JavaScript samples - Multi label classification](https://github.com/Azure/azure-sdk-for-js/blob/%40azure/ai-text-analytics_6.0.0-beta.1/sdk/textanalytics/ai-text-analytics/samples/v5/javascript/customText.js) |
+| Python (Runtime) | [Python documentation](/python/api/azure-ai-textanalytics/azure.ai.textanalytics?view=azure-python-preview&preserve-view=true) | [Python samples - Single label classification](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/textanalytics/azure-ai-textanalytics/samples/sample_single_label_classify.py) [Python samples - Multi label classification](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/textanalytics/azure-ai-textanalytics/samples/sample_multi_label_classify.py) |
 
 ## Responsible AI 
 
-An AI system includes not only the technology, but also the people who will use it, the people who will be affected by it, and the environment in which it is deployed. Read the [transparency note for custom text classification](/azure/ai-foundry/responsible-ai/language-service/custom-text-classification-transparency-note) to learn about responsible AI use and deployment in your systems. 
+An AI system includes not only the technology, but also the people who use it, the people affected by it, and the deployment environment. Read the [transparency note for custom text classification](/azure/ai-foundry/responsible-ai/language-service/custom-text-classification-transparency-note) to learn about responsible AI use and deployment in your systems. 
 
 [!INCLUDE [Responsible AI links](../includes/overview-responsible-ai-links.md)]
 

articles/ai-services/language-service/index.yml

@@ -12,7 +12,7 @@ metadata:
   manager: nitinme
   ms.service: azure-ai-language
   ms.topic: hub-page
-  ms.date: 03/24/2025
+  ms.date: 09/27/2025
   ms.author: lajanuar
 highlightedContent:
 # itemType: architecture | concept | deploy | download | get-started | how-to-guide | learn | overview | quickstart | reference | tutorial | whats-new
@@ -30,7 +30,7 @@ highlightedContent:
 conceptualContent:
   items:
     - title: Extract information
-      summary: Use Natural Language Understanding (NLU) to extract information from unstructured text. For example, identify key phrases or Personally Identifiable Information (PII), summarize text, recognize and categorize named entities, or customize an entity extraction model on top of your domain set.
+      summary: Use Natural Language Understanding (NLU) to extract information from unstructured text.
       links:
         - itemType: overview
           text: Extract key phrases

articles/ai-services/language-service/language-detection/quickstart.md

@@ -6,7 +6,7 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: quickstart
-ms.date: 09/15/2025
+ms.date: 09/27/2025
 ms.author: lajanuar
 ms.devlang: csharp
 # ms.devlang: csharp, java, javascript, python