> ## Documentation Index
> Fetch the complete documentation index at: https://futureagi.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Create Dynamic Column by Extracting Entities

> This feature allows users to create column dynamically by extract information from already existing column by defining extraction rules.

## **1. Select a Dataset**

Before configuring retrieval, ensure you have selected a dataset. If no dataset is available, follow the steps to **Add Dataset** on the Future AGI platform.

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## **2. Access the Extract Entities**

* Navigate to your dataset under Build.
* Click on the **Add Columns** button (+) in the top-right menu.
* Select column type
* Under **Dynamic Columns**, select **Extract Entities.**

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## 3. Configure Extract Entities

* **Name**: Assign a **name** to the newly column created using this method
* **Column**: Select the **column** which you want to use to extract information to create this new column
* **Enter Instructions**: Define what specific information you want to extract from the text. The instructions should be **clear and specific** to ensure accurate entity extraction.
* **Model:** Select an AI model for entity extraction. If you're using it for the first time, a pop-up will prompt you to enter and save your API key for authentication. If you've already provided an API key, you can simply choose from the available models.
* **Concurrency**: Set the number of rows to process simultaneously.

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After configuring the settings, click **Test** to preview the extracted entities. If the results look correct, click **Create New Column** to apply the extraction process. The extracted entities will be stored in a separate column in the dataset.

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