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Extracting Hohfeldian relations from text

Wim Peters, Adam Wyner Orcid Logo

Legal Knowledge and Information Systems, Volume: Volume 279, Pages: 189 - 190

Swansea University Author: Adam Wyner Orcid Logo

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DOI (Published version): 10.3233/978-1-61499-609-5-189

Abstract

This paper presents a semi-automatic methodology and application for identifying the Hohfeldian relation Duty in legal text, using the General Architecture for Text Engineering tool for the automated extraction of Duty instances and its associated roles. The method incrementally supports scholars in...

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Published in: Legal Knowledge and Information Systems
ISBN: 978-1-61499-608-8 978-1-61499-609-5
Published: Amsterdam IOS Press 2015
Online Access: https://ebooks.iospress.nl/volumearticle/42000
URI: https://cronfa.swan.ac.uk/Record/cronfa50689
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first_indexed 2019-06-06T20:54:04Z
last_indexed 2022-02-10T04:15:28Z
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spelling 2022-02-09T14:08:04.0755241 v2 50689 2019-06-06 Extracting Hohfeldian relations from text 51fa34a3136b8e81fc273fce73e88099 0000-0002-2958-3428 Adam Wyner Adam Wyner true false 2019-06-06 SCS This paper presents a semi-automatic methodology and application for identifying the Hohfeldian relation Duty in legal text, using the General Architecture for Text Engineering tool for the automated extraction of Duty instances and its associated roles. The method incrementally supports scholars in their interpretation. Book chapter Legal Knowledge and Information Systems Volume 279 189 190 IOS Press Amsterdam 978-1-61499-608-8 978-1-61499-609-5 Hohfeldian ,Text Engineering, Duty instances, roles. 31 12 2015 2015-12-31 10.3233/978-1-61499-609-5-189 https://ebooks.iospress.nl/volumearticle/42000 Book edited by Antonino Rotolo COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2022-02-09T14:08:04.0755241 2019-06-06T17:49:54.2010814 Faculty of Humanities and Social Sciences Hilary Rodham Clinton School of Law Wim Peters 1 Adam Wyner 0000-0002-2958-3428 2
title Extracting Hohfeldian relations from text
spellingShingle Extracting Hohfeldian relations from text
Adam Wyner
title_short Extracting Hohfeldian relations from text
title_full Extracting Hohfeldian relations from text
title_fullStr Extracting Hohfeldian relations from text
title_full_unstemmed Extracting Hohfeldian relations from text
title_sort Extracting Hohfeldian relations from text
author_id_str_mv 51fa34a3136b8e81fc273fce73e88099
author_id_fullname_str_mv 51fa34a3136b8e81fc273fce73e88099_***_Adam Wyner
author Adam Wyner
author2 Wim Peters
Adam Wyner
format Book chapter
container_title Legal Knowledge and Information Systems
container_volume Volume 279
container_start_page 189
publishDate 2015
institution Swansea University
isbn 978-1-61499-608-8
978-1-61499-609-5
doi_str_mv 10.3233/978-1-61499-609-5-189
publisher IOS Press
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str Hilary Rodham Clinton School of Law{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}Hilary Rodham Clinton School of Law
url https://ebooks.iospress.nl/volumearticle/42000
document_store_str 0
active_str 0
description This paper presents a semi-automatic methodology and application for identifying the Hohfeldian relation Duty in legal text, using the General Architecture for Text Engineering tool for the automated extraction of Duty instances and its associated roles. The method incrementally supports scholars in their interpretation.
published_date 2015-12-31T04:02:14Z
_version_ 1763753207966728192
score 11.017797

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