LawStats – Large-scale German court decision evaluation using web service classifiers

LawStats provides quantitative insights into court decisions from the Bundesgerichtshof - Federal Court of Justice (BGH), the Federal Court of Justice in Germany. Using Watson Web Services and approaches from Sentiment Analysis (SA), we can automatically classify the revision outcome and offer stati...

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Main Authors: RUPPERT, Eugen, HARTUNG, Dirk, SITTIG, Phillip, GSCHWANDER, Tjorben, RÖNNEBURG, Lennart, KILLING, Tobias, BIEMANN, Chris
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Language:English
Published: Institutional Knowledge at Singapore Management University 2018
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Online Access:https://ink.library.smu.edu.sg/sol_research/4525
https://ink.library.smu.edu.sg/context/sol_research/article/6483/viewcontent/472936_1_En_14_Chapter.pdf
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spelling sg-smu-ink.sol_research-64832024-10-17T03:28:50Z LawStats – Large-scale German court decision evaluation using web service classifiers RUPPERT, Eugen HARTUNG, Dirk SITTIG, Phillip GSCHWANDER, Tjorben RÖNNEBURG, Lennart KILLING, Tobias BIEMANN, Chris LawStats provides quantitative insights into court decisions from the Bundesgerichtshof - Federal Court of Justice (BGH), the Federal Court of Justice in Germany. Using Watson Web Services and approaches from Sentiment Analysis (SA), we can automatically classify the revision outcome and offer statistics on judges, senates, previous instances etc. via faceted search. These statistics are accessible through a open web interface to aid law professionals. With a clear focus on interpretability, users can not only explore statistics, but can also understand, which sentences in the decision are responsible for the machine’s decision; links to the original texts provide more context. This is the first large-scale application of Machine Learning (ML) based Natural Language Processing (NLP) for German in the analysis of ordinary court decisions in Germany that we are aware of. We have analyzed over 50,000 court decisions and extracted the outcomes and relevant entities. The modular architecture of the application allows continuous improvements of the ML model as more annotations become available over time. The tool can provide a critical foundation for further quantitative research in the legal domain and can be used as a proof-of-concept for similar efforts. 2018-08-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sol_research/4525 info:doi/10.1007/978-3-319-99740-7_14 https://ink.library.smu.edu.sg/context/sol_research/article/6483/viewcontent/472936_1_En_14_Chapter.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection Yong Pung How School Of Law eng Institutional Knowledge at Singapore Management University Cognitive services Faceted search Law domain Text classification Web APIs Internet Law Science and Technology Law
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Cognitive services
Faceted search
Law domain
Text classification
Web APIs
Internet Law
Science and Technology Law
spellingShingle Cognitive services
Faceted search
Law domain
Text classification
Web APIs
Internet Law
Science and Technology Law
RUPPERT, Eugen
HARTUNG, Dirk
SITTIG, Phillip
GSCHWANDER, Tjorben
RÖNNEBURG, Lennart
KILLING, Tobias
BIEMANN, Chris
LawStats – Large-scale German court decision evaluation using web service classifiers
description LawStats provides quantitative insights into court decisions from the Bundesgerichtshof - Federal Court of Justice (BGH), the Federal Court of Justice in Germany. Using Watson Web Services and approaches from Sentiment Analysis (SA), we can automatically classify the revision outcome and offer statistics on judges, senates, previous instances etc. via faceted search. These statistics are accessible through a open web interface to aid law professionals. With a clear focus on interpretability, users can not only explore statistics, but can also understand, which sentences in the decision are responsible for the machine’s decision; links to the original texts provide more context. This is the first large-scale application of Machine Learning (ML) based Natural Language Processing (NLP) for German in the analysis of ordinary court decisions in Germany that we are aware of. We have analyzed over 50,000 court decisions and extracted the outcomes and relevant entities. The modular architecture of the application allows continuous improvements of the ML model as more annotations become available over time. The tool can provide a critical foundation for further quantitative research in the legal domain and can be used as a proof-of-concept for similar efforts.
format text
author RUPPERT, Eugen
HARTUNG, Dirk
SITTIG, Phillip
GSCHWANDER, Tjorben
RÖNNEBURG, Lennart
KILLING, Tobias
BIEMANN, Chris
author_facet RUPPERT, Eugen
HARTUNG, Dirk
SITTIG, Phillip
GSCHWANDER, Tjorben
RÖNNEBURG, Lennart
KILLING, Tobias
BIEMANN, Chris
author_sort RUPPERT, Eugen
title LawStats – Large-scale German court decision evaluation using web service classifiers
title_short LawStats – Large-scale German court decision evaluation using web service classifiers
title_full LawStats – Large-scale German court decision evaluation using web service classifiers
title_fullStr LawStats – Large-scale German court decision evaluation using web service classifiers
title_full_unstemmed LawStats – Large-scale German court decision evaluation using web service classifiers
title_sort lawstats – large-scale german court decision evaluation using web service classifiers
publisher Institutional Knowledge at Singapore Management University
publishDate 2018
url https://ink.library.smu.edu.sg/sol_research/4525
https://ink.library.smu.edu.sg/context/sol_research/article/6483/viewcontent/472936_1_En_14_Chapter.pdf
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