This means we would assign labels to 74% of instances in the dataset (excluding those discarded during argument identification) and attain a role classification with 79.4% precision (purity).
5 instead of labeling all 165, 662 instances contained in these clusters individually we would only have to assign labels to 2, 869 clusters.