The Data Extraction Scope activity provides a scope for extractor activities, enabling you to configure them according to the document types defined in your taxonomy. The output of the activity is stored in an ExtractionResult variable, containing all automatically extracted data, and can be used as input for the Export Extraction Results activity. This activity also features a Configure Extractors wizard, which lets you specify exactly what fields from the document types defined in the taxonomy you want to extract1.

The extractors that can be used for Data Extraction Scope activity are:

Regex Based Extractor: This extractor enables you to use regular expressions to extract data from text documents. You can define your own expressions or use the predefined ones from the Regex Based Extractor Configuration wizard2.

Form Extractor: This extractor enables you to extract data from semi-structured documents, such as invoices, receipts, or purchase orders, based on the position and relative distance of the fields. You can define the templates for each document type using the Form Extractor Configuration wizard3.

Intelligent Form Extractor: This extractor enables you to extract data from semi-structured documents, such as invoices, receipts, or purchase orders, based on the labels and values of the fields. You can define the fields for each document type using the Intelligent Form Extractor Configuration wizard.

Machine Learning Extractor: This extractor enables you to extract data from any type of document, using a machine learning model that is trained on your data. You can use the predefined models from UiPath or your own custom models hosted on AI Center or other platforms. You can configure the fields and the model for each document type using the Machine Learning Extractor Configuration wizard.

References: 1: Data Extraction Scope 2: Regex Based Extractor 3: Form Extractor : Intelligent Form Extractor : Machine Learning Extractor

UiPath provides out-of-the-box pre-trained models that are ready for use and cover a wide variety of document types. These models can be used as-is for common use cases or fine-tuned based on specific requirements, making them versatile for different projects

When setting up a classification label in UiPath's Out Of the Box (OOB) labeling templates, you need to provide several key details: the name of the label, the classification type (which defines the kind of label), the input to be labeled, the attribute name that describes the label's context, a shortcut for quick access, and a color for visual distinction. These fields ensure the label is fully defined and easy to manage in workflows.

(Source: UiPath Document Understanding documentation)