To combat the noisy training data produced by heuristic labeling in distant supervision, researchers (Bunescu and Mooney, 2007; Riedel et al., 2010; <cite>Hoffmann et al., 2011</cite>; Surdeanu et al., 2012) exploited multi-instance learning models.