4.2.2 Transaction Log

This topic describes the systematic instructions to view all the uploaded transactions that are interpreted by the NLP models.

The user can filter the displayed transactions based on the Document Type and Status.
Specify User ID and Password, and login to Home screen.
  1. On Home screen, click Machine Learning. Under Machine Learning, click Operation.
  2. Under Operation, click Transaction Log.
    The Transaction Log screen displays.
  3. Specify the fields on Transaction Log screen.
    For more information on fields, refer to the field description table.

    Table 4-7 Transaction Log – Field Description

    Field Description
    Document Type Select the document type from drop-down list.
    Status Select the type of status from drop-down list.
    Document ID Displays the Document Management System Unique Identifier.
    Document Type Displays the document type - Use Case Definition.
    Model Ref Displays the Unique Model Version Identifier.
    Processing Date Displays the document processed date.
    Status Displays the status of the transaction.
    Failure Reason Displays the reason for failed status.
    Train. Reqd Displays train required status.
    Tag Values Displays the tag values for the processed transactions and allow the correction for transactions with errors.
  4. To check the execution flow, click on Document ID to view details and flow.
    The Process Log screen displays.
  5. To check the processed status, select Processed in Status drop-down list.
    The document ID page displays that contains model tag values used to process the transactions.

    Figure 4-24 Processed Status

    The displayed information reflects both the original retrieved values by the model from the document and also the values which are corrected manually.

  6. To check the error status, select Error in Status drop-down list.
    All the failed transactions displays.
  7. For the failed transactions, click on the Tag Value(s) to invoke the toolkit annotator in the error correction mode to create a new annotated training file for future model training.
    The Annotator screen displays.