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Create a learning instance in Document Automation

  • Updated: 2022/09/22
    • Automation 360 v.x
    • IQ Bot
    • Digitize

Create a learning instance in Document Automation

Begin processing documents by creating a learning instance to extract data from invoices, utility bills, or receipts. A learning instance is a structure that holds information such as document type, language, and the fields to be extracted.

Prerequisites

  • To create a learning instance, you must be a Learning instance creator user. See Document Automation users.
  • To create a learning instance that uses a Google Document AI model, you must purchase Google Document AI licenses. Contact your Customer Support Manager (CSM) to obtain the licenses.

Watch this video for the complete end-to-end process of creating a learning instance:

Procedure

  1. From the Control Room home page, navigate to Manage > Learning Instances > Create Learning Instance.
  2. 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.
  3. Select the document type: Invoice , Utility Bill, or Receipt
  4. Select the language.
    Document Automation supports English, Dutch, French, German, and Spanish.
    Note: Extraction for French, German, and Spanish language documents is currently in preview. Extraction results will improve in future releases.
  5. If you selected Invoice: Select the provider.
    If you selected the English language in step 4, Automation Anywhere (Pre-trained) is auto-selected.
  6. 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.

Note:
  • 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.

  1. 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.
    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:
    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.
  2. To add a field, click Add a field and complete the following fields:
    OptionDescription
    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 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 variations of the date format.
    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.
    Note: 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.

    Starts With and Ends With | Pattern | Lists | Formulas

  3. Click Create.
When a new learning instance is created, the Control Room creates a folder with the same name as the learning instance in the Automation > Document Workspace folder. The folder contains two bots (extraction and download), a process, and a form.Example screenshot of learning instance assets
  • Process: Manages the process using if/else scenarios through which Document Automation extracts data from uploaded documents, assigns documents to users for validation, and downloads the extracted data. To learn more, see About the AARI process in Document Automation
  • Extraction bot: Extracts data from defined fields in the uploaded documents.
  • Download bot: Downloads the extracted data to a specific folder on the device or shared network.
  • Form: Defines the input parameters that are sent to the process. Input parameters include the learning instance name, uploaded file, and output file path.

Next steps

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

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