@inproceedings{wang-etal-2017-emergent,
    title = "Emergent Predication Structure in Hidden State Vectors of Neural Readers",
    author = "Wang, Hai  and
      Onishi, Takeshi  and
      Gimpel, Kevin  and
      McAllester, David",
    editor = "Blunsom, Phil  and
      Bordes, Antoine  and
      Cho, Kyunghyun  and
      Cohen, Shay  and
      Dyer, Chris  and
      Grefenstette, Edward  and
      Hermann, Karl Moritz  and
      Rimell, Laura  and
      Weston, Jason  and
      Yih, Scott",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/W17-2604/",
    doi = "10.18653/v1/W17-2604",
    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."
}