Both accuracy metrics show very similar results on three corpora. An interesting fact is that the corpus which was used to create the rules (DROC_red) shows the worst results of all three fictional datasets. Gutenberg contains rather schematic narratives which appear to be easier compared to the other data sets. A more fine grained analysis shows that the best document for DROC_red yields a token level accuracy of 99.7% and the worst document an accuracy of 21.5%. The largest gap can be found in the RW_fict dataset with 0% accuracy for the worst and 100% accuracy for the best document. This shows that while in average the results are promising, there are still phenomena that need to be addressed separately.