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title description titleSuffix author manager ms.service ms.topic ms.date ms.author ms.devlang ms.custom
Send a Named Entity Recognition (NER) request to your custom model
Learn how to send requests for custom NER.
Azure AI services
jboback
nitinme
azure-ai-language
how-to
12/19/2023
jboback
csharp
language-service-custom-ner

Query your custom model

After the deployment is added successfully, you can query the deployment to extract entities from your text based on the model you assigned to the deployment. You can query the deployment programmatically using the Prediction API or through the client libraries (Azure SDK).

Test deployed model

You can use Language Studio to submit the custom entity recognition task and visualize the results.

[!INCLUDE Test model]

:::image type="content" source="../media/test-model-results.png" alt-text="A screenshot showing the model test results." lightbox="../media/test-model-results.png":::

Send an entity recognition request to your model

Language Studio

[!INCLUDE Get prediction URL]

REST API

First you need to get your resource key and endpoint:

[!INCLUDE Get keys and endpoint Azure Portal]

Submit a custom NER task

[!INCLUDE submit a custom NER task using the REST API]

Get task results

[!INCLUDE get custom NER task results]

Client libraries (Azure SDK)

First you need to get your resource key and endpoint:

[!INCLUDE Get keys and endpoint Azure Portal]

  1. Download and install the client library package for your language of choice:

    Language Package version
    .NET 5.2.0-beta.3
    Java 5.2.0-beta.3
    JavaScript 6.0.0-beta.1
    Python 5.2.0b4

  2. After you've installed the client library, use the following samples on GitHub to start calling the API.

  3. See the following reference documentation for more information on the client, and return object:

Next steps