EMIL: Extracting Meaning from Inconsistent Language
- Submitting institution
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Swansea University / Prifysgol Abertawe
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 50680
- Type
- D - Journal article
- DOI
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10.1016/j.ijar.2019.04.010
- Title of journal
- International Journal of Approximate Reasoning
- Article number
- -
- First page
- 55
- Volume
- 112
- Issue
- -
- ISSN
- 0888613X
- Open access status
- Compliant
- Month of publication
- September
- Year of publication
- 2019
- URL
-
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- Supplementary information
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- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
-
- Research group(s)
-
-
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- There is a pressing need for computational approaches to reason with inconsistent knowledge in natural language across domains, e.g., medicine, law, and everyday decision making. The paper describes a novel system which addresses critical gaps in the integration of formal reasoning with inconsistent knowledge expressed in natural language. It is an advance based on the interdisciplinary integration of formal argumentation, computational analysis, and natural language processing, applied to natural language expressions of defeasibility; it provides proofs of logical and complexity properties, advances NLP tools, and was evaluated in a real-world use case.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -