Safwat, Hazem and Zarrouk, Manel and Davis, Brian (2018) Rewriting Simplified Text into a Controlled Natural Language. In: Controlled Natural Language. Frontiers in Artificial Intelligence and Applications . IOS Press. ISBN 9781614999041

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Abstract

While machine processable Controlled Natural Languages (CNLs) as a natural language interface have proven a popular, unambiguous and user friendly method for non experts to engineer formal knowledge-bases, human-oriented CNLs however remain under-researched despite having found favor within industry over many years. Whether such human orientated CNLs like the machine processable counterparts can be captured automatically as formal knowledge remains an open question. In addition, rewriting all or most of a human-oriented CNL into a machine-oriented CNL could unlock significant silos of general purpose domain knowledge, contained within existing human-oriented CNL content for exploitation by knowledge based systems. This paper explores the feasibility of rewriting a human-orientated CNL represented in Simplified English into a well know machine-oriented CNL represented in ACE CNL and describes preliminary results

Item Type:	Book Section
Additional Information:	This work has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289 and in part by the SSIX Horizon 2020 project (grant agreement No 645425). This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). https://creativecommons.org/licenses/by-nc/4.0/
Keywords:	Controlled Natural Language; Natural Language Processing; Knowledge Extraction; Semantic Web;
Academic Unit:	Faculty of Science and Engineering > Computer Science
Item ID:	13420
Identification Number:	https://doi.org/10.3233/978-1-61499-904-1-85
Depositing User:	Brian Davis
Date Deposited:	07 Oct 2020 15:28
Publisher:	IOS Press
Refereed:	Yes
Funders:	European Union Horizon 2020 programme
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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