Distant supervision has been widely used in relation extraction tasks without hand-labeled datasets recently.
evaluations P@100 P@200 P@300 Automatic@NYT 76.2 73.1 67.4 Manual@NYT 96.0(+19.8) 95.5(+22.4) 91.0(+23.6) Automatic@A-NYT 93.0 89.5 88.0 Manual@A-NYT 96.0(+3.0) 92.5(+3.0) 90.7(+2.7)  To further demonstrate the effectiveness of our training strategies, we compare Generative Adversarial Training (GAT) with other baselines on the partially labeled dataset A-NYT as shown in Figure 4(b).