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A significant number of neural architectures for reading comprehension haverecently been developed and evaluated on large cloze-style datasets. We presentexperiments supporting the emergence of "predication structure" in the hiddenstate vectors of these readers. More specifically, we provide evidence that thehidden state vectors represent atomic formulas $\Phi[c]$ where $\Phi$ is asemantic property (predicate) and $c$ is a constant symbol entity identifier.

Emergent Predication Structure in Hidden State Vectors of Neural Readers