Field configuration settings allow users to customize how data is extracted, processed, and displayed in Affinda’s platform. These settings ensure the extracted data meets specific requirements and can be easily integrated into downstream workflows. Field configuration options can be accessed by Workspace Owners and Admins by clicking ‘Configure Fields’ in the top right corner of the document validation view.Documentation Index
Fetch the complete documentation index at: https://docs.affinda.com/llms.txt
Use this file to discover all available pages before exploring further.
Detailed guide for Schema Design
Schema Design
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Basic Configuration
Field Name
The field name represents the label for the extracted data in the validation UI. It is user-defined and helps the model in extracting the field from documents; as such, it is important to have clear and relevant field names.Field Description
Users may optionally enhance the model’s predictions by providing additional context, such as how the data is typically labelled and where it appears on the page.Data Types
Your field’s data type determines how extracted values are processed and standardized. Different data types are available to ensure that structured and unstructured data is correctly categorized. The selected data type influences the structure of the data and the post-processing logic applied to extracted values, ensuring consistency and accuracy.Standard Data Types
Text, Numbers, Dates, Location, Phone Number, URLs
Structures
Groups and Tables
Picklists
Options and Data Source
Checkboxes
Labels and True/False
Image Fields
Signatures, Seals, and Headshots
Basic Field Settings
Enabling Fields
This setting determines whether the field should be predicted and visible in the extracted output. Users can toggle this option depending on whether they want the model to extract and display the field. Disabling a field instead of deleting it lets the model keep all previously validated annotations and automatically restores them when the field is re‑enabled.
Multiple Values
Enable multiple predictions only when a field can have multiple distinct values within a single document. Examples include:- Line item tables on an Invoice
- Parties or Signatories in a Legal Contract
- Transactions in a Bank Statement
