Document flags

aiR for Data Breach Response applies document flags during Ingestion and Data Analysis to communicate the processing status of individual documents. Use document flags to identify documents that encountered errors, understand why an issue occurred, and determine the next step to resolve it.

A document can have multiple reasons for failure. However, the error log records only the first issue encountered and produces a flag for that issue. Analysis stops at that point, so any additional issues with the document are not evaluated until you correct the initial error and resubmit the document.

For example, if a document has both an unsupported file type and an excessive file size, the error field displays only the file type issue. The file size issue does not appear because analysis halts at the first error. If you then convert the document to a supported file type and resubmit it, the file size error surfaces.

System flags

The application logic creates system flags during an Ingestion or Data Analysis run and users cannot remove them. System flags denote documents for which the application has issues processing. The presence of a system flag may prevent that document from processing in certain pipeline stages.

System default flag types

The following table describes default flag types:

Flag name	Description	Solution
A regex in the required detector(s) previously timed out, so it was skipped for this document	Regex that was previously timing out was used again and is skipping processing this time.	Try adjusting your regex.
Bad request: Cannot perform operation	Infrastructure of network issues occurring more broadly in RelativityOne	Contact support.
Detection process not complete due to timeout	A timeout error occurred.	Try rerunning Data Analysis. If you continue to encounter an error, contact support.
Detector regex timed out	The regex you are using may be too generic or too complex.	Try restructuring your regex.
Error running token level detectors	There was an error during detection stage.	Try rerunning Data Analysis. If you continue to encounter an error, contact support.
Excel annotations did not generate correctly	Occurs after a failure during Structured Detection.	There is no way to clear the flag. Contact support for more details.
Excel detection process not complete due to timeout	A timeout error occurred.	Try rerunning Data Analysis. If you continue to encounter an error, contact support.
Excel header assignment did not complete on this document	Occurs when the pipeline fails to change the assignment of the header on a document. Spreadsheet QC is used to set a header to a different PI type. If data analysis encounters an error it will apply this flag to the problem documents.	Try rerunning the Structured Detection substage of Data Analysis. If you continue to encounter an error, contact support.
Excel header detection did not complete on this document	Occurs after a failure during Structured Detection. Applied when a failure occurs during the Header Detection sub stage of Structured Detection.	Try reviewing the document and applying new header classifications manually. Contact support for more details.
Exception in PI Detection Manager while processing request	The document was not fully processed.	Contact support for more details.
Header values excluded from Spreadsheet QC table	A header containing multiple PI types was identified.	Manually review the document header to designate the correct PI type. The analysis process determined multiple types were potentially contained in that header and a manual decision is needed.
System Technical Issue	A file has been impacted by a technical issue that has prevented the document from being processed for review and reporting.	Try rerunning Data Analysis. If you continue to encounter an error, contact support.
The document statistics could not be updated. The reported count of PI may be incorrect	Something went wrong while calculating or updating document statistics.	Statistics on reports may be wrong, which includes document dashboard data possibly being outdated.