If we don't apply the filter before the classifier, the recall results increase by about 20% (with no loss in precision).
the filter plays a very important role in keeping the extraction pipeline robust and efficient (as shown in Figure 7, the filter discards 99% of the candidate pairs), so this loss of recall is a price worth paying.