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How easy is it to learn a controlled natural language for building a knowledge base?

Williams, Sandra; Power, Richard and Third, Allan (2014). How easy is it to learn a controlled natural language for building a knowledge base? In: Proceedings of the Fourth Workshop on Controlled Natural Language , Lecture Notes in Computer Science, Springer International Publishing AG, pp. 20–32.

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Abstract

Recent developments in controlled natural language editors for knowledge engineering (KE) have given rise to expectations that they will make KE tasks more accessible and perhaps even enable non-engineers to build knowledge bases. This exploratory research focussed on novices and experts in knowledge engineering during their attempts to learn a controlled natural language (CNL) known as OWL Simplified English and use it to build a small knowledge base. Participants' behaviours during the task were observed through eye-tracking and screen recordings. This was an attempt at a more ambitious user study than in previous research because we used a naturally occurring text as the source of domain knowledge, and left them without guidance on which information to select, or how to encode it. We have identified a number of skills (competencies) required for this difficult task and key problems that authors face.

Item Type: Conference or Workshop Item
Copyright Holders: 2014 Springer International Publishing
ISBN: 3-319-10222-2, 978-3-319-10222-1
Project Funding Details:
Funded Project NameProject IDFunding Body
Not SetNot SetThe Open University (OU)
Extra Information: Co-located with COLING 2014
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Research Group: Centre for Research in Computing (CRC)
Related URLs:
Item ID: 40385
Depositing User: Sandra Williams
Date Deposited: 12 Jun 2014 10:42
Last Modified: 19 Dec 2017 10:32
URI: http://oro.open.ac.uk/id/eprint/40385
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