{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T14:32:49Z","timestamp":1772375569759,"version":"3.50.1"},"reference-count":61,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2016,5,12]],"date-time":"2016-05-12T00:00:00Z","timestamp":1463011200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Argument &amp; Computation"],"published-print":{"date-parts":[[2016,7,5]]},"abstract":"<jats:p> In many domains of public discourse such as arguments about public policy, there is an abundance of knowledge to store, query, and reason with. To use this knowledge, we must address two key general problems: first, the problem of the knowledge acquisition bottleneck between forms in which the knowledge is usually expressed, e.g., natural language, and forms which can be automatically processed; second, reasoning with the uncertainties and inconsistencies of the knowledge. Given such complexities, it is labour and knowledge intensive to conduct policy consultations, where participants contribute statements to the policy discourse. Yet, from such a consultation, we want to derive policy positions, where each position is a set of consistent statements, but where positions may be mutually inconsistent. To address these problems and support policy-making consultations, we consider recent automated techniques in natural language processing, instantiating arguments, and reasoning with the arguments in argumentation frameworks. We discuss application and \u201cbridge\u201d issues between these techniques, outlining a pipeline of technologies whereby: expressions in a controlled natural language are parsed and translated into a logic (a literals and rules knowledge base), from which we generate instantiated arguments and their relationships using a logic-based formalism (an argument knowledge base), which is then input to an implemented argumentation framework that calculates extensions of arguments (an argument extensions knowledge base), and finally, we extract consistent sets of expressions (policy positions). The paper reports progress towards reasoning with web-based, distributed, collaborative, incomplete, and inconsistent knowledge bases expressed in natural language. <\/jats:p>","DOI":"10.3233\/aac-160002","type":"journal-article","created":{"date-parts":[[2019,11,9]],"date-time":"2019-11-09T22:19:45Z","timestamp":1573337985000},"page":"69-89","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":6,"title":["Working on the argument pipeline: Through\u00a0flow issues between natural           language argument, instantiated arguments, and argumentation frameworks"],"prefix":"10.1177","volume":"7","author":[{"given":"Adam","family":"Wyner","sequence":"first","affiliation":[{"name":"Department of Computing Science, University of Aberdeen, Aberdeen, United Kingdom.\r            E-mail:\u00a0"}]},{"given":"Tom","family":"van Engers","sequence":"additional","affiliation":[{"name":"Leibniz Centre for Law, University of Amsterdam, Amsterdam, The Netherlands.\r            E-mail:\u00a0"}]},{"given":"Anthony","family":"Hunter","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University College London, London, United Kingdom.\r            E-mail:\u00a0"}]}],"member":"179","published-online":{"date-parts":[[2016,5,12]]},"reference":[{"key":"ref001","unstructured":"L.\u00a0Amgoud, M.\u00a0Caminada, C.\u00a0Cayrol, M.C.\u00a0Lagasquie and             H.\u00a0Prakken, Towards a           consensual formal model: Inference part, Technical report, ASPIC project, 2004."},{"key":"ref002","doi-asserted-by":"publisher","DOI":"10.1007\/BF00350139"},{"key":"ref003","unstructured":"V.\u00a0Basile, J.\u00a0Bos,             K.\u00a0Evang and N.\u00a0Venhuizen,             Negation detection with discourse representation             structures, in: The First Joint Conference on Lexical and             Computational Semantics (SEM 2012), Montreal, Canada,             2012, 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