NLP 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.

Prompt Tips

• Extract all columns to get the best results. If you describe only a few of the columns, your results may be less accurate.
• Use the table titles or table column headers in the document as descriptions.
• For more information about how to write descriptions, or “prompts”, see Query Group.
• For advanced options, see Advanced prompt configuration.

Examples

Example 1

The following example shows using the NLP Table method to extract data from a bank statement:

To try out this example in the Sensible app, take the following steps:

1. Navigate to the following example document:
   | Example document | https://app.sensible.so/editor/instruct/?d=sensible_instruct_basics&c=bank_statement&g=bank_statement |

2. Create fields to extract data using the following table:

Field name	Method	Overall table description	Column IDs and descriptions
savings_transaction_history	NLP Table	”savings transaction history”	date - “date”description - “description without totals”amount - “amount”

Click the Send icon for each column.

3. To verify the extracted data, scroll down in the right pane and compare the Extracted data section to the document in the left pane:

4. (Optional) To standardize the representation of the extracted dates and dollar amounts, configure date and currency types as shown in the following screenshots:

You should see that the formatting of the extracted data changes according to the types you specified. For example, Sensible reformats the date 04/11/23 to a standardized output format, 2023-04-11:

Example 2

The following example shows using the NLP Table method to extract data from an auto insurance document:

To try out this example in the Sensible app, take the following steps:

1. Download the following example document:
   | Example document | Download link |

2. 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 document you downloaded in a previous step.

3. Click the document type’s Configurations tab, create a new test configuration, and click the configuration you created to edit it.

4. Click Sensible Instruct and create prompts to extract data using the following table:

Field name	Method	Overall table description	Column IDs and descriptions
insured_vehicles_table	NLP Table	”insured vehicles”	manufacturer - “vehicle make (not model)“year - “year of manufacture”
transactions_table	NLP 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.