@inproceedings{wities-etal-2017-consolidated,
    title = "A Consolidated Open Knowledge Representation for Multiple Texts",
    author = "Wities, Rachel  and
      Shwartz, Vered  and
      Stanovsky, Gabriel  and
      Adler, Meni  and
      Shapira, Ori  and
      Upadhyay, Shyam  and
      Roth, Dan  and
      Martinez Camara, Eugenio  and
      Gurevych, Iryna  and
      Dagan, Ido",
    editor = "Roth, Michael  and
      Mostafazadeh, Nasrin  and
      Chambers, Nathanael  and
      Louis, Annie",
    booktitle = "Proceedings of the 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-level Semantics",
    month = apr,
    year = "2017",
    address = "Valencia, Spain",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W17-0902",
    doi = "10.18653/v1/W17-0902",
    pages = "12--24",
    abstract = "We propose to move from Open Information Extraction (OIE) ahead to Open Knowledge Representation (OKR), aiming to represent information conveyed jointly in a set of texts in an open text-based manner. We do so by consolidating OIE extractions using entity and predicate coreference, while modeling information containment between coreferring elements via lexical entailment. We suggest that generating OKR structures can be a useful step in the NLP pipeline, to give semantic applications an easy handle on consolidated information across multiple texts.",
}