ASUBMITTED APARTLYSUBMITTED ADECLINED WAfhandelenleads [EOC] ASUBMITTED APARTLYSUBMITTED APREACCEPTED WAfhandelenleads WCompleterenaanvraag WCompleterenaanvraag WCompleterenaanvraag AACCEPTED AFINALIZED OSELECTED OCREATED OSENT WCompleterenaanvraag WNabellenoffertes WNabellenoffertes WNabellenoffertes OSENTBACK WNabellenoffertes WValiderenaanvraag WValiderenaanvraag WValiderenaanvraag WNabellenincompletedossiers OCANCELLED OSELECTED OCREATED OSENT WNabellenincompletedossiers WNabellenincompletedossiers WNabellenincompletedossiers WNabellenincompletedossiers WNabellenincompletedossiers ACANCELLED OCANCELLED WNabellenincompletedossiers [EOC] ASUBMITTED APARTLYSUBMITTED WAfhandelenleads ADECLINED WAfhandelenleads [EOC] ASUBMITTED APARTLYSUBMITTED ADECLINED [EOC] ASUBMITTED APARTLYSUBMITTED APREACCEPTED AACCEPTED OSELECTED AFINALIZED OCREATED OSENT WCompleterenaanvraag WNabellenoffertes WNabellenoffertes ADECLINED ODECLINED WNabellenoffertes [EOC] Figure 9: Example hallucinations for the BPI2012 dataset (probabilistic output sampling, ”[EOC]” designates end-of-case) Table 7: Hallucination characteristics for BPI2012 (completion events only) dataset fitness of the hallucinations similar to that of the original model is a strong indication that the generated traces are realistic. We also examine whether the frequency distribution of events in the generated hallucinations matches that in the original dataset, using the Kolmogorov-Smirnov test. A non-signifant test (p-value > 0 . 05) indicates the frequency distributions come from the same underlying population. Table 7 shows the results for the BPI2012 dataset. Probabilistic output sampling produces more realistic results than choosing the output with the highest probability; the latter produces many long uniform event sequences that are uncharacteristic of the input logs. Results for the other event logs are similar. In summary, the generated hallucinations show that the neural networks learn the relevant features of the input event logs. Hallucinations can also be used to predict the remainder of a case. For this, the 26 full log prob. sampling top-p output Mean trace length 13 12 21 Max trace length 96 56 194 Replay fitness .586 .582 .350 KS test p-value — .878 .000