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Effective Attention Modeling for Neural Relation Extraction

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Figure

Figure 1: Architecture of our attention model with m = 1. We have not shown the CNN-based global featureextraction here
Figure 2: An example dependency tree. The two num-bers indicate the distance of the word from the headtoken of the two entities respectively along the depen-dency tree path.
Table 1: Statistics of the NYT10 and NYT11 dataset.
Table 2: Performance comparison of different models on the two datasets. * denotes a statistically significantimprovement over the previous best state-of-the-art model with p < 0.01 under the bootstrap paired t-test.†denotes the previous best state-of-the-art model.
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