Results are shown in Table 2 , where all systems were compared in terms of their performances on "same sentence" edges (both nodes are from the same sentence), "nearby sentence" edges, all edges, and the temporal awareness metric used by the TempEval3 workshop. The first part of Table 2 (Systems 1-5) refers to the baseline method proposed at the beginning of Sec. 3, i.e., simply treating P as F and training on their union. The second part (Systems 6-7) serves as an ablation study showing the effect of bootstrapping only. While System 7 can be regarded as a reproduction of<cite> Ning et al. (2017)</cite> , the original paper of<cite> Ning et al. (2017)</cite> achieved an overall score of P=43.0, R=46.4, F=44.7 and an awareness score of P=42.6, R=44.0, and F=43.3, and the proposed System 9 is also better than<cite> Ning et al. (2017)</cite> on all metrics.