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Machine comprehension of text using combinatory categorial grammar and answer set programs

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Title: Machine comprehension of text using combinatory categorial grammar and answer set programs
Authors: Chabierski, P
Russo, A
Law, M
Broda, K
Item Type: Conference Paper
Abstract: We present an automated method for generating Answer Set Programs from narratives written in English and demonstrate how such a representation can be used to answer questions about text. The proposed approach relies on a transparent interface between the syntax and semantics of natural language provided by Combinatory Categorial Grammars to translate text into Answer Set Programs, hence creating a knowledge base that, together with background knowledge, can be queried.
Issue Date: 6-Nov-2017
Date of Acceptance: 8-Sep-2017
URI: http://hdl.handle.net/10044/1/64301
ISSN: 1613-0073
Publisher: CEUR Workshop Proceedings
Journal / Book Title: CEUR Workshop Proceedings
Volume: 2052
Copyright Statement: © 2017 The Author(s).
Conference Name: COMMONSENSE 2017
Publication Status: Published
Start Date: 2017-11-06
Finish Date: 2017-11-08
Conference Place: London, UK
Online Publication Date: 2017-11-06
Appears in Collections:Computing
Faculty of Engineering