Document AI uses Enterprise Knowledge Graph to normalize and
enrich entity extraction results (for supported fields). For example, the addresses
123 Main St Apt 1 and 123 Main street # 1 could be normalized to the same
standardized address.
For each supported field, Document AI also returns a normalizedValue
in addition to the raw extracted field, normalizing the literal text.
This contains the data in a standardized format to reduce post-processing.
Most data belongs to one of the following categories:
- Money
 - Date
 - Timestamp
 - Address
 - Boolean
 - Integer
 - Float
 
Sample response
The enriched values can be found in the
entities.normalizedValue
field as shown in the following truncated sample:
{
  "entities": [
    {
      "textAnchor": {
        "textSegments": [ ... ],
        "content": "Google Singapore"
      },
      "type": "employer_name",
      "mentionText": "Google Singapore",
      "confidence": 0.69933707,
      "pageAnchor": {
        "pageRefs": [
          {
            "boundingPoly": {
              "normalizedVertices": [ ... ]
            }
          }
        ]
      },
      "id": "9",
      "normalizedValue": {
        "text": "Google Asia Pacific, Singapore"
      }
    }
  ]
}
In the sample, the original employer_name "Google Singapore" has been
normalized to "Google Asia Pacific, Singapore".
In the Google Cloud console, the enriched and normalized fields are annotated with G. For example:
  Supported processors
Here are the processors and fields that support entity enrichment.
| Processors | Enriched fields | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
      Bank Statement Parser
  | 
    
      
  | 
  ||||||||||||
      W2 Parser
  | 
    
      
  | 
  ||||||||||||
      Pay Slip Parser
  | 
    
      
  | 
  ||||||||||||
      Expense Parser
  | 
    
      
  | 
  ||||||||||||
      Invoice Parser
  | 
    
      
  |