document-understanding
latest
false
- Overview
- Getting started
- Activities
- Insights dashboards
- Document Understanding Process
- Quickstart tutorials
- Framework components
- ML packages
- Overview
- Document Understanding - ML package
- DocumentClassifier - ML package
- ML packages with OCR capabilities
- 1040 - ML package
- 1040 Schedule C - ML package
- 1040 Schedule D - ML package
- 1040 Schedule E - ML package
- 1040x - ML package
- 3949a - ML package
- 4506T - ML package
- 709 - ML package
- 941x - ML package
- 9465 - ML package
- ACORD125 - ML package
- ACORD126 - ML package
- ACORD131 - ML package
- ACORD140 - ML package
- ACORD25 - ML package
- Bank Statements - ML package
- Bills Of Lading - ML package
- Certificate of Incorporation - ML package
- Certificate of Origin - ML package
- Checks - ML package
- Children Product Certificate - ML package
- CMS 1500 - ML package
- EU Declaration of Conformity - ML package
- Financial Statements - ML package
- FM1003 - ML package
- I9 - ML package
- ID Cards - ML package
- Invoices - ML package
- Invoices Australia - ML package
- Invoices China - ML package
- Invoices Hebrew - ML package
- Invoices India - ML package
- Invoices Japan - ML package
- Invoices Shipping - ML package
- Packing Lists - ML package
- Payslips - ML package
- Passports - ML package
- Purchase Orders - ML package
- Receipts - ML package
- Remittance Advices - ML package
- UB04 - ML package
- Utility Bills - ML package
- Vehicle Titles - ML package
- W2 - ML package
- W9 - ML package
- Other Out-of-the-box ML Packages
- Public endpoints
- Traffic limitations
- OCR Configuration
- Pipelines
- OCR services
- Supported languages
- Deep Learning
- Data and security
- Licensing
Important :
La localisation du contenu nouvellement publié peut prendre 1 à 2 semaines avant d’être disponible.
Document Understanding User Guide
Dernière mise à jour 24 nov. 2025
Acord 140 is most commonly known as the Property Section and it's used to record specific property information including the insured’s business locations/ buildings, property values and other property details.
This model is trained to extract up to 73 fields plus items.
The model automatically detects data such as:
- Date, Effective Date,
- Premises Information: Address, Description, Subject of Insurance, Amount, Coins%,
- Additional Coverages, Options, Restrictions, Endorsements and Rating Information: Spoiled Coverage, Limit, Deductible Amount, Construction Type, Fire District, BLDG Code Grade, Occupancies, Building Improvements.
