Create a learning instance in Community Edition

Create a learning instance to begin processing documents. In Community Edition, you can extract data from invoices in English using the ABBYY OCR provider.

Procedura

From the Control Room home page, navigate to Manage > Learning Instances > Create Learning Instance.
Enter a name and description for the learning instance.
Document Automation does not allow duplicate learning instance names, so the name you provide must be unique.
Click Next.

We recommend that you open a sample document side by side with the Control Room window as you configure the form and table fields.

Nota:

A form field is a type of field that occurs only once in a document.
A table field is a type of field that reoccurs throughout a document, typically in the form of a table.

Configure the form and table fields for extraction.
Document Automation offers a standard set of form and table fields, many of which are not initially visible. You can search for a field by field name, field label, or data type.

To see the full list of fields, click Show unused fields. See the following video for a demonstration:

Click a field to open the fields editor. You can edit most attributes of a field. You cannot edit the name and default aliases. Document Automation assigns default aliases, which are hardcoded keywords, to standard fields to help with extraction. You cannot modify or delete default aliases, but you can add aliases in the Custom aliases field. See the following video for a demonstration of creating a custom alias:
Nota: Custom fields are not available for learning instances that use the Google Document AI provider.

Mouse over the menu icon to the right of a field to access the up/down arrows. Use the arrows to rearrange the order of the fields for a more efficient manual validation. The order of the fields does not impact extraction.

To learn more about the other field attributes, review the table in the next step.

To add a field, click Add a field and complete the following fields:

Option	Description
Field name	Enter a field name that begins with an alphabetical character (A-Z or a-z). In standard fields, the field name is hardcoded and cannot be changed.
Field label	Enter a user-friendly name to help validators. For example, you can rename Organization tax number to a localized name, such as VAT number. The field label does not affect extraction.
Confidence	Set a threshold to reduce potential false positives. At the time of processing, the Document Automation engine assigns a score to each field in a document to indicate the certainty that the data was correctly extracted. If the document contains fields with a score that is lower than the confidence threshold, the document is sent to the validation queue. If you enter a high confidence threshold, more documents will be sent to the validation queue. If you enter a low confidence threshold, fewer documents will be sent to the validation queue. Supports values from zero to 100.
Data type	Choose from Address, Text, Number, and Date. If the data in the field does not match the data type, the document is sent to the validation queue. Document Automation supports date and number format variations. If you are configuring a learning instance with a user-defined document type, the form fields include the address data type, which extracts the entire structure of an address.
Required	Select one of the following: Required: Field cannot be empty. Optional: Field can be empty or not exist in the document.
Default aliases	No action is necessary for this field. Document Automation assigns default aliases, which are hardcoded keywords, to standard fields to help with extraction.
Custom aliases	Additional keywords to help Document Automation locate the field. For example, add country or region-specific names for fields such as VAT number as an alias to an Organization tax number custom field. Nota: Custom aliases must be unique. They cannot duplicate the default alias of another field. Exception: Form fields can have duplicate custom aliases as the table fields and vice versa.
Validation rules	Depending on data type, create rules using patterns, formulas, lists, and statements such as starts or ends with. Formula validation \| Pattern validation

Click Create.

Fasi successive

Upload documents to the learning instance, fix validation errors, and verify the extracted data: Process documents in Community Edition

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