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A Hybrid Neural Network Model for Commonsense Reasoning

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Figure

Figure 1: Architecture of the hybrid model for commonsense reasoning. The model consists of two componentmodels, a masked language model (MLM) and a semantic similarity model (SSM)
Table 2in our experiments. Since the WSC and PDP60datasets do not contain any training instances, fol-lowing (dataset (ing and selection
Table 4: Test results
Figure 3: Comparison of different task formulation onWNLI.

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