You are here:
Extraction Using Queries for Intelligent Form Reader
Enable Amazon Textract Queries to extract information using natural language queries.
Required Editions
| Available in: Lightning Experience |
| Available in: Financial Services Cloud, Health Cloud, and Public Sector Solutions |
| Intelligent Form Reader is available for an additional cost with the Intelligent Form Reader add-on license. |
| User Permissions Needed | |
|---|---|
| To create document types: | Customize Application |
Note The Maximum Pages and Confidence Score Threshold fields in the global content
extraction settings are available only in Health Cloud.
- From Setup, in the Quick Find box, enter Intelligent Form Reader, and then select Intelligent Form Reader.
- In the Global Content Extraction Settings section, click Edit Settings.
-
Enter the maximum number of consecutive pages from the first page of a document that you
want to send for content extraction at a time.
The default value for Maximum Pages is 5. If a user selects pages that are already scanned, the pages aren’t counted against the limit.
- Enable Amazon Textract Queries to extract information using natural language queries, with a limit of 200 characters.
- Select the Document Type tab.
- Click New Document Type.
- Enter a name, select the Form Type, and add a description for the document type.
-
In the Queries section, add a new entry containing an alias that serves as a descriptive
label displayed in the template and a natural language query that defines the information you
want to extract from documents.
Each document type supports up to 15 unique queries.
-
Save your changes.
The Edit Global Content Extraction Settings page opens.
-
Click Save.
Tip- For extracting information from a document, the defined queries for that document type and other enabled Textract APIs (such as Forms and Analyze ID) will be used.
- When you create a template by using a document type with associated queries, those queries will be executed during data extraction and display their corresponding aliases as document fields.
- Queries that fail to identify any values within the document will not be displayed as fields in your template.
- After successful query execution, bounding boxes will highlight the extracted values within the document, rather than the associated query labels.
Did this article solve your issue?
Let us know so we can improve!

