For MIT Restaurant, MIT Movie, CADEC, i2b2 2014 and i2b2 2006 (Figure 2), the neural network approaches have better recall than PRED and PRED-CCA across all dataset sizes; this results in the neural network approaches having a greater F1 score for these datasets in most cases (the exceptions being MIT Restaurant with under 500 sentences, and CADEC with 500 sentences).
for GUM, re3d, NIST IE-ER, MUC 6 ( Figure 4) and Ritter (Figure 3), we observe that initially PRED and PRED-CCA have higher recall than the neural network approaches, but the neural networks' recall surpasses them once the target domain dataset is large enough.