Table extraction tips
This Sensible Instruct method extracts a table in a document based on your description of the table title and each of its column headers.
Tips
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Try extracting all columns to get the best results. If you describe only a few of the columns, your results may be less accurate.
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Try using the table titles or table column headers in the document as descriptions.
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For more information about how to write descriptions, or "prompts", Query extraction tips.
Examples
Example 1
The following example shows using the Table method to extract data from an auto insurance document:
To try out this example in the Sensible app, take the following steps:
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Download the following example PDF:
Example PDF Download link -
Create a test document type in the Sensible app, then click the document type you created to edit it. In the document type's Reference documents tab, upload the example PDF you downloaded in a previous step.
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Click the document type's Configurations tab, create a new test configuration, and click the configuration you created to edit it.
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Click Sensible Instruct and create fields to extract data using the following table:
Field name | Method | Overall table description | Column IDs and descriptions |
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insured_vehicles_table | Table | "insured vehicles" | manufacturer - "vehicle make (not model)" year - "year of manufacture" |
transactions_table | Table | "transactions for insurance account" | transaction_date - "transaction date." transaction_description - "transaction description" |
For example, use the following screenshot as a guide for configuring the insured_vehicles_table
field:
Notes
For the full reference for this method in SenseML, see NLP Table.
Updated 1 day ago