@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."
}
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%0 Conference Proceedings
%T A Consolidated Open Knowledge Representation for Multiple Texts
%A Wities, Rachel
%A Shwartz, Vered
%A Stanovsky, Gabriel
%A Adler, Meni
%A Shapira, Ori
%A Upadhyay, Shyam
%A Roth, Dan
%A Martinez Camara, Eugenio
%A Gurevych, Iryna
%A Dagan, Ido
%Y Roth, Michael
%Y Mostafazadeh, Nasrin
%Y Chambers, Nathanael
%Y Louis, Annie
%S Proceedings of the 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-level Semantics
%D 2017
%8 April
%I Association for Computational Linguistics
%C Valencia, Spain
%F wities-etal-2017-consolidated
%X 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.
%R 10.18653/v1/W17-0902
%U https://aclanthology.org/W17-0902/
%U https://doi.org/10.18653/v1/W17-0902
%P 12-24
Markdown (Informal)
[A Consolidated Open Knowledge Representation for Multiple Texts](https://aclanthology.org/W17-0902/) (Wities et al., LSDSem 2017)
ACL
- Rachel Wities, Vered Shwartz, Gabriel Stanovsky, Meni Adler, Ori Shapira, Shyam Upadhyay, Dan Roth, Eugenio Martinez Camara, Iryna Gurevych, and Ido Dagan. 2017. A Consolidated Open Knowledge Representation for Multiple Texts. In Proceedings of the 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-level Semantics, pages 12–24, Valencia, Spain. Association for Computational Linguistics.