Graphene: Semantically-Linked Propositions in Open Information Extraction
- Submitting institution
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The University of Manchester
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 85361948
- Type
- E - Conference contribution
- DOI
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- Title of conference / published proceedings
- Proceedings of the 27th International Conference on Computational Linguistics
- First page
- 2300
- Volume
- -
- Issue
- -
- ISSN
- -
- Open access status
- -
- Month of publication
- August
- Year of publication
- 2018
- URL
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- Supplementary information
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- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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3
- Research group(s)
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A - Computer Science
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- "This paper addressed a historical problem in open information extraction (Fader et al. 2011 - of uninformative and incoherent extractions).
Keynote at 2018 conference for the Korean national project ""Exobrain"" (2013-2023), aiming to be the ""Korean IBM Watson"". Invited talks (OKBQA2018-Korea, AMW2019-Paraguay, DOING@MADICS2020-France).
Enabled funding:
- Macular Society Grant GBP81,800
- EPSRC iCASE BBC GBP113,000
- Royal Society Grant (IEC\R3\183018) University of Tokyo GBP11,800
- Collaboration with CancerResearchUK GBP600,000
The method was implemented as an open source software (32 Github forks for projects derived from our software, with 82 stars)."
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
