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Relation Extraction from Environmental Law Text Using Natural Language Understanding

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dc.contributor.authorThimm, Heiko
dc.contributor.authorSchneider, Phil
dc.contributor.editorWohlgemuth, Volker
dc.contributor.editorNaumann, Stefan
dc.contributor.editorArndt, Hans-Knud
dc.contributor.editorBehrens, Grit
dc.contributor.editorHöb, Maximilian
dc.date.accessioned2022-09-19T09:20:47Z
dc.date.available2022-09-19T09:20:47Z
dc.date.issued2022
dc.description.abstractIn the last decades the highly active area of environmental legislation has produced a vast amount of text documents that contain laws and regulations enacted by various types of rule setters. This large body of legal text documents is still growing with an increasing speed. In order to assure compliance with the regulations, today, corporate specialist spend a lot of time with the reviewing and assessment of these documents. It seems that through the use of text processing assistance tools these important corporate environmental compliance management tasks can be completed in less time. To develop corresponding assistance tools has been the broader goal of this work in which initial text processing experiments with a common Natural Language Understanding pipeline are described. The obtained results confirm that in order to extract meaningful relations from text documents of the environmental legislation area, domain-specific processing techniques that are tailored to the specific language and format of legal text are required.en
dc.identifier.isbn978-3-88579-722-7
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/39400
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofEnviroInfo 2022
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-328
dc.subjectEnvironmental legislation
dc.subjectlegal text
dc.subjectNatural Language Processing
dc.subjectNatural Language Understanding
dc.subjectRelation Extraction
dc.subjectText Processing Pipeline.
dc.titleRelation Extraction from Environmental Law Text Using Natural Language Understandingen
dc.typeText/Conference Paper
gi.citation.publisherPlaceBonn
gi.citation.startPage43
gi.conference.date26.-30- September 2022
gi.conference.locationHamburg

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P328 - EnviroInfo 2022
Environmental Informatics 2022