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DSGAN: Generative Adversarial Training for Distant Supervision Relation Extraction

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Figure

Figure 1: Illustration of the distant supervisiontraining data distribution for one relation type.
Figure 2:An overview of the DSGAN training pipeline. The generator (denoted by G) calculates theprobability distribution over a bag of DS positive samples, and then samples according to this probabilitydistribution
Table 1: Hyperparameter settings of the generatorand the discriminator.
Figure 3: The convergence of the DSGAN training process for 3 relation types and the performance oftheir corresponding generators
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