Journal article 1315 views 232 downloads
Recognizing cited facts and principles in legal judgements
Artificial Intelligence and Law, Volume: 25, Issue: 1, Pages: 107 - 126
Swansea University Author: Adam Wyner
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DOI (Published version): 10.1007/s10506-017-9197-6
Abstract
In common law, lawyers cite facts and legal principles from precedent cases for their arguments in support of their current case. Such facts and principles must be identified, though this is a highly time intensive task. We demonstrate that human annotators can agreement on which sentences are facts...
Published in: | Artificial Intelligence and Law |
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ISSN: | 0924-8463 1572-8382 |
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Springer
2017
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URI: | https://cronfa.swan.ac.uk/Record/cronfa40674 |
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2022-09-28T16:54:59.5137661 v2 40674 2018-06-07 Recognizing cited facts and principles in legal judgements 51fa34a3136b8e81fc273fce73e88099 0000-0002-2958-3428 Adam Wyner Adam Wyner true false 2018-06-07 MACS In common law, lawyers cite facts and legal principles from precedent cases for their arguments in support of their current case. Such facts and principles must be identified, though this is a highly time intensive task. We demonstrate that human annotators can agreement on which sentences are facts or principles. A supervised machine learning framework can automatically annotate sentences containing such legal facts and principles based on linguistic features, reporting precision and recall figures of between 0.79 and 0.89 using a Bayesian classifier. Journal Article Artificial Intelligence and Law 25 1 107 126 Springer 0924-8463 1572-8382 law, machine learning, legal facts, legal principles, corpus 31 12 2017 2017-12-31 10.1007/s10506-017-9197-6 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University 2022-09-28T16:54:59.5137661 2018-06-07T15:51:49.5023782 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Olga Shulayeva 1 Advaith Siddharthan 2 Adam Wyner 0000-0002-2958-3428 3 0040674-11062018165158.pdf FactsPrinciplesLaw.pdf 2018-06-11T16:51:58.0330000 Output 441686 application/pdf Version of Record true 2018-06-11T00:00:00.0000000 This article is distributed under the terms of the Creative Commons Attribution 4.0 International License. true eng |
title |
Recognizing cited facts and principles in legal judgements |
spellingShingle |
Recognizing cited facts and principles in legal judgements Adam Wyner |
title_short |
Recognizing cited facts and principles in legal judgements |
title_full |
Recognizing cited facts and principles in legal judgements |
title_fullStr |
Recognizing cited facts and principles in legal judgements |
title_full_unstemmed |
Recognizing cited facts and principles in legal judgements |
title_sort |
Recognizing cited facts and principles in legal judgements |
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51fa34a3136b8e81fc273fce73e88099 |
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51fa34a3136b8e81fc273fce73e88099_***_Adam Wyner |
author |
Adam Wyner |
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Olga Shulayeva Advaith Siddharthan Adam Wyner |
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Artificial Intelligence and Law |
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25 |
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Swansea University |
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0924-8463 1572-8382 |
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In common law, lawyers cite facts and legal principles from precedent cases for their arguments in support of their current case. Such facts and principles must be identified, though this is a highly time intensive task. We demonstrate that human annotators can agreement on which sentences are facts or principles. A supervised machine learning framework can automatically annotate sentences containing such legal facts and principles based on linguistic features, reporting precision and recall figures of between 0.79 and 0.89 using a Bayesian classifier. |
published_date |
2017-12-31T01:26:21Z |
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11.048994 |