@InProceedings{wang-EtAl:2017:RepL4NLP,
  author    = {Wang, Hai  and  Onishi, Takeshi  and  Gimpel, Kevin  and  McAllester, David},
  title     = {Emergent Predication Structure in Hidden State Vectors of Neural Readers},
  booktitle = {Proceedings of the 2nd Workshop on Representation Learning for NLP},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {26--36},
  abstract  = {A significant number of neural architectures for reading comprehension have
	recently been developed and evaluated on large cloze-style datasets.
	  We present experiments supporting the emergence of "predication structure" in
	the hidden state vectors of these readers.  More specifically, we provide
	evidence that the hidden state vectors represent atomic formulas $\Phi[c]$
	where $\Phi$ is a semantic property (predicate) and $c$ is a constant symbol
	entity identifier.},
  url       = {http://www.aclweb.org/anthology/W17-2604}
}