Reconcile the Results

When you run through your document extraction process, most of the work occurs in the background. It's only after the Start Doc Extraction Smart Service extracts data from a document that the Reconcile Doc Extraction Smart Service generates a task for a user to validate the data.

The reconciliation task plays an important role in making auto-mappings smarter. As you complete reconciliation tasks, Appian learns how to map the data in your documents to the proper fields in your data type. Over time, this will make auto-extraction more accurate and reconciliation easier and less frequent.

Note that learned mappings are dependent on the data type's fields, so if you change the fields or make a new data type, it will not use the learned mappings. Learning also happens independently in each environment. When deploying your application to another environment, you may see different behavior for auto-extraction depending on which documents have been processed and how they have been reconciled by users.

Complete the reconciliation task

The reconciliation task is auto-generated by the Reconcile Doc Extraction Smart Service.

To complete the reconciliation task, users will compare the data that was extracted to an image of the uploaded document. They can use the information that displays in the document preview to update any incorrect or missing information.

To complete the reconciliation task:

  1. On the left side of the page, review the information in the fields. Use the document preview on the right to verify the accuracy of the data.
    • Note: To see where the information in the fields came from, select the field and the value is automatically highlighted in the document preview.

  2. If any information is missing, you can populate the information in three ways:

    Values selected from the document preview will improve data extraction results. Values entered manually will not. For example, if you select the value for a PO number from the document preview in two different documents, it can learn that PO No. and PO # both mean PO Number. If you have the option, you should select correctly labeled values from the document preview instead of entering them manually.

    • Place your cursor in the field, then click the box that surrounds the desired value.

    • Click the box that surrounds the desired value in the document preview on the right, then click the arrow next to the field to populate the field.

    • To select text that was not automatically extracted, press and hold the Shift key while dragging the mouse.

  3. Perform additional reconciliation for tables, if they appear in the document preview.

  4. After all fields are verified and populated, click RECONCILE.

While you are reconciling the data, icons indicate how the information was entered for each field:

  • No icon: Value was entered manually
  • Magic wand icon : Value was entered automatically during data extraction.
  • Link icon : Value was selected from the document preview.

user_guide_reconciliation_icons

Reconcile table data

  1. Under the relevant field in the left-pane, click Select Table.
  2. Select your table and identify the header row.
  3. Choose which field in each column header corresponds to the column in the table.
  4. Remove rows that don't contain actual table data, described below.
  5. Verify your data is correct.
  6. Click OK.

As users submit document extraction tasks, Appian will learn the aliases for your tables' column headers. It can then use the learnings to automatically extract table values, reducing the need for human reconciliation.

Table actions

When manually extracting table data, users can take a variety of actions by clicking on the menu icon next to a column or row.

For columns, users can:

  • Duplicate a column
  • Insert a column to the left
  • Insert a column to the right
  • Remove a column

For rows, users can:

  • Duplicate a row
  • Insert a row above
  • Insert a row below

Users can also remove individual rows by clicking the close icon on the right side of each row

Open in Github Built: Fri, Nov 04, 2022 (07:10:52 PM)

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