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Copy file name to clipboardExpand all lines: articles/ai-services/language-service/named-entity-recognition/overview.md
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manager: nitinme
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ms.service: azure-ai-language
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ms.topic: overview
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ms.date: 02/15/2025
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ms.date: 07/14/2025
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ms.author: lajanuar
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ms.custom: language-service-ner
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---
@@ -19,31 +19,29 @@ Named Entity Recognition (NER) is one of the features offered by [Azure AI Langu
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*[**How-to guides**](how-to-call.md) contain instructions for using the service in more specific or customized ways.
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* The [**conceptual articles**](concepts/named-entity-categories.md) provide in-depth explanations of the service's functionality and features.
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> [!NOTE]
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> [Entity Resolution](concepts/entity-resolutions.md) was upgraded to the [Entity Metadata](concepts/entity-metadata.md) starting in API version 2023-04-15-preview. If you're calling the preview version of the API equal or newer than 2023-04-15-preview, check out the [Entity Metadata](concepts/entity-metadata.md) article to use the resolution feature.
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[!INCLUDE [Typical workflow for pre-configured language features](../includes/overview-typical-workflow.md)]
An AI system includes not only the technology, but also the people who use it, the people who are affected by it, and the environment in which it's deployed. Read the [transparency note for NER](/azure/ai-foundry/responsible-ai/language-service/transparency-note-named-entity-recognition) to learn about responsible AI use and deployment in your systems. You can also see the following articles for more information:
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An AI system consists of more than just its core technology. It also includes the people who operate it, the people its use affects, and the broader deployment context.
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All these interconnected elements shape the effectiveness and outcomes of AI. Read the [transparency note for NER](/azure/ai-foundry/responsible-ai/language-service/transparency-note-named-entity-recognition) to learn about responsible AI use and deployment in your systems. For more information, *see* the following articles:
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[!INCLUDE [Responsible AI links](../includes/overview-responsible-ai-links.md)]
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## Scenarios
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*Enhance search capabilities and search indexing - Customers can build knowledge graphs based on entities detected in documents to enhance document search as tags.
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*Automate business processes - For example, when reviewing insurance claims, recognized entities like name and location could be highlighted to facilitate the review. Or a support ticket could be generated with a customer's name and company automatically from an email.
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* Customer analysis – Determine the most popular information conveyed by customers in reviews, emails, and calls to determine the most relevant topics that get brought up and determine trends over time.
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***Enhance search capabilities and search indexing**. Customers can build knowledge graphs based on entities detected in documents to enhance document search as tags.
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***Automate business processes** - Insurance claims, recognized entities like name and location can be highlighted to facilitate review. Support tickets can be automatically generated with customer name and company from an email.
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***In-depth customer analysis**. Determine the most popular information conveyed by customers in reviews, emails, and calls to determine relevant topics and trends over time.
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## Next steps
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There are two ways to get started using the Named Entity Recognition (NER) feature:
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*[Azure AI Foundry](../../../ai-foundry/what-is-azure-ai-foundry.md) is a web-based platform that lets you use several Language service features without needing to write code.
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* The [quickstart article](quickstart.md) for instructions on making requests to the service using the REST API and client library SDK.
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* The [quickstart article](quickstart.md) for instructions on making requests to the service using the REST API and client library SDK.
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