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dc.contributor.authorKarlova-Bourbonus, Natali
dc.date.accessioned2023-03-28T12:43:09Z
dc.date.available2019-04-26T08:41:00Z
dc.date.available2023-03-28T12:43:09Z
dc.date.issued2018
dc.identifier.urihttp://nbn-resolving.de/urn:nbn:de:hebis:26-opus-144470
dc.identifier.urihttps://jlupub.ub.uni-giessen.de//handle/jlupub/15796
dc.identifier.urihttp://dx.doi.org/10.22029/jlupub-15178
dc.description.abstractThe main purpose of news is to inform the reader about the current political, economic, and cultural events in the world. By that, the main requirements for the process of news produc-tion is an objective, uninvolved news reporting and an accurate, i.e. correct and consistent (contradiction-free) use of facts. A violation of the latter leads to the misinformation of the reader and, if detected, to a negative impact on the credibility and trustworthiness of the newspaper. The recognition of contradictions in a (news) text is a challenging task for a human as it presupposes concentrated reading and requires world knowledge and the ability to analyti-cally process the information obtained. Also, the age and mental capability of the reader plays an important role. Further, the task of contradiction recognition becomes even more difficult when dealing with contradictory facts occurring in texts that are separated by space and time. For this reason, the main aim of the present study was to propose a system for the automatic detection of contradictions occurring in news texts written in English.en
dc.language.isoende_DE
dc.rightsIn Copyright*
dc.rights.urihttp://rightsstatements.org/page/InC/1.0/*
dc.subjectcontradictionen
dc.subjectmachine learningen
dc.subjectnatural language processingen
dc.subjecttextual entailmenten
dc.subjectcorpusen
dc.subject.ddcddc:400de_DE
dc.titleAutomatic detection of contradictions in textsen
dc.title.alternativeAutomatische Erkennung von Widersprüchen in Textende_DE
dc.typedoctoralThesisde_DE
dcterms.dateAccepted2019-04-17
local.affiliationFB 05 - Sprache, Literatur, Kulturde_DE
thesis.levelthesis.doctoralde_DE
local.opus.id14447
local.opus.instituteAngewandte Sprachwissenschaft und Computerlinguistikde_DE
local.opus.fachgebietGermanistikde_DE


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