SPARQL query verbalization for explaining semantic search engine queries
SPARQL query verbalization for explaining semantic search engine queries
In this paper we introduce Spartiqulation, a system that translates SPARQL queries into English text. Our aim is to allow casual end users of semantic applications with limited to no expertise in the SPARQL query language to interact with these applications in a more intuitive way. The verbalization approach exploits domain-independent template-based natural language generation techniques, as well as linguistic cues in labels and URIs.
426-441
Ell, Basil
8d22693c-c5f7-46c5-bd17-3d82b82191b3
Harth, Andreas
87300638-2b12-4b9f-9b6c-b8080aed4b77
Simperl, Elena
40261ae4-c58c-48e4-b78b-5187b10e4f67
2014
Ell, Basil
8d22693c-c5f7-46c5-bd17-3d82b82191b3
Harth, Andreas
87300638-2b12-4b9f-9b6c-b8080aed4b77
Simperl, Elena
40261ae4-c58c-48e4-b78b-5187b10e4f67
Ell, Basil, Harth, Andreas and Simperl, Elena
(2014)
SPARQL query verbalization for explaining semantic search engine queries.
In,
Presutti, Valentina, d'Amato, Claudia, Gandon, Fabien, d'Aquin, Mathieu, Staab, Steffen and Tordai, Anna
(eds.)
The Semantic Web: Trends and Challenges.
Cham, CH.
Springer Cham, .
(doi:10.1007/978-3-319-07443-6_29).
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Abstract
In this paper we introduce Spartiqulation, a system that translates SPARQL queries into English text. Our aim is to allow casual end users of semantic applications with limited to no expertise in the SPARQL query language to interact with these applications in a more intuitive way. The verbalization approach exploits domain-independent template-based natural language generation techniques, as well as linguistic cues in labels and URIs.
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Published date: 2014
Organisations:
Web & Internet Science
Identifiers
Local EPrints ID: 405580
URI: http://eprints.soton.ac.uk/id/eprint/405580
PURE UUID: 072d6399-3374-477f-9d2e-600109faf4fd
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Date deposited: 08 Feb 2017 10:08
Last modified: 15 Mar 2024 04:32
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Contributors
Author:
Basil Ell
Author:
Andreas Harth
Editor:
Valentina Presutti
Editor:
Claudia d'Amato
Editor:
Fabien Gandon
Editor:
Mathieu d'Aquin
Editor:
Steffen Staab
Editor:
Anna Tordai
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