{"id":"https://openalex.org/W3008866797","doi":"https://doi.org/10.1109/ssci44817.2019.9003090","title":"Towards Contradiction Detection in German: a Translation-Driven Approach","display_name":"Towards Contradiction Detection in German: a Translation-Driven Approach","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3008866797","doi":"https://doi.org/10.1109/ssci44817.2019.9003090","mag":"3008866797"},"language":"en","primary_location":{"id":"doi:10.1109/ssci44817.2019.9003090","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci44817.2019.9003090","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064201630","display_name":"Rafet Sifa","orcid":"https://orcid.org/0009-0004-6680-8210"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rafet Sifa","raw_affiliation_strings":["Fraunhofer Center for Machine Learning Fraunhofer, IAIS University of Bonn, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer Center for Machine Learning Fraunhofer, IAIS University of Bonn, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054556600","display_name":"Maren Pielka","orcid":"https://orcid.org/0000-0001-9610-6026"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maren Pielka","raw_affiliation_strings":["Fraunhofer Center for Machine Learning Fraunhofer, IAIS University of Bonn, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer Center for Machine Learning Fraunhofer, IAIS University of Bonn, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035886948","display_name":"Rajkumar Ramamurthy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rajkumar Ramamurthy","raw_affiliation_strings":["Fraunhofer Center for Machine Learning Fraunhofer, IAIS University of Bonn, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer Center for Machine Learning Fraunhofer, IAIS University of Bonn, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083948511","display_name":"Anna Ladi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anna Ladi","raw_affiliation_strings":["Fraunhofer Center for Machine Learning Fraunhofer, IAIS University of Bonn, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer Center for Machine Learning Fraunhofer, IAIS University of Bonn, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081939611","display_name":"Lars Hillebrand","orcid":"https://orcid.org/0000-0002-5496-4177"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lars Hillebrand","raw_affiliation_strings":["Fraunhofer Center for Machine Learning Fraunhofer, IAIS University of Bonn, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer Center for Machine Learning Fraunhofer, IAIS University of Bonn, Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003875445","display_name":"Christian Bauckhage","orcid":"https://orcid.org/0000-0001-6615-2128"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Christian Bauckhage","raw_affiliation_strings":["Fraunhofer Center for Machine Learning Fraunhofer, IAIS University of Bonn, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer Center for Machine Learning Fraunhofer, IAIS University of Bonn, Germany","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7353,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.89041694,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"2019","issue":null,"first_page":"2497","last_page":"2505"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13629","display_name":"Text Readability and Simplification","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8728847503662109},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.8400774002075195},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7792282104492188},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7662594318389893},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5523970723152161},{"id":"https://openalex.org/keywords/contradiction","display_name":"Contradiction","score":0.5489828586578369},{"id":"https://openalex.org/keywords/german","display_name":"German","score":0.5358067750930786},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5279133319854736},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.5051200985908508},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4953705072402954},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4450570046901703},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.41853466629981995},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.158354252576828}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8728847503662109},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.8400774002075195},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7792282104492188},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7662594318389893},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5523970723152161},{"id":"https://openalex.org/C2776728590","wikidata":"https://www.wikidata.org/wiki/Q363948","display_name":"Contradiction","level":2,"score":0.5489828586578369},{"id":"https://openalex.org/C154775046","wikidata":"https://www.wikidata.org/wiki/Q188","display_name":"German","level":2,"score":0.5358067750930786},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5279133319854736},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.5051200985908508},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4953705072402954},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4450570046901703},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.41853466629981995},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.158354252576828},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/ssci44817.2019.9003090","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci44817.2019.9003090","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"},{"id":"pmh:oai:fraunhofer.de:N-593089","is_oa":false,"landing_page_url":"http://publica.fraunhofer.de/documents/N-593089.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400801","display_name":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer IAIS","raw_type":"Conference Paper"},{"id":"pmh:oai:publica.fraunhofer.de:publica/408212","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/408212","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"},{"id":"mag:3044343808","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002233298375457","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8500000238418579}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1532325895","https://openalex.org/W1840435438","https://openalex.org/W1924770834","https://openalex.org/W2005708641","https://openalex.org/W2101105183","https://openalex.org/W2118463056","https://openalex.org/W2130359236","https://openalex.org/W2131744502","https://openalex.org/W2133564696","https://openalex.org/W2154474435","https://openalex.org/W2157331557","https://openalex.org/W2250539671","https://openalex.org/W2550821151","https://openalex.org/W2619953528","https://openalex.org/W2754608118","https://openalex.org/W2798459010","https://openalex.org/W2880875857","https://openalex.org/W2907849599","https://openalex.org/W2916132663","https://openalex.org/W2949547296","https://openalex.org/W2962958286","https://openalex.org/W2963440143","https://openalex.org/W2963514026","https://openalex.org/W2963854351","https://openalex.org/W2963918774","https://openalex.org/W2964308564","https://openalex.org/W2973794125","https://openalex.org/W4211148418","https://openalex.org/W4297823153","https://openalex.org/W6637901910","https://openalex.org/W6640212811","https://openalex.org/W6679434410","https://openalex.org/W6679775712","https://openalex.org/W6750737311","https://openalex.org/W6752788575","https://openalex.org/W6757575941","https://openalex.org/W6898505805"],"related_works":["https://openalex.org/W159132833","https://openalex.org/W3093843097","https://openalex.org/W3171566221","https://openalex.org/W3198474835","https://openalex.org/W3167690611","https://openalex.org/W2950819771","https://openalex.org/W2126242092","https://openalex.org/W4298027009","https://openalex.org/W2985347586","https://openalex.org/W4288023470"],"abstract_inverted_index":{"With":[0],"the":[1,31,36,79,98,108,134,137,149,181],"recent":[2],"advancements":[3],"in":[4,67,78,156],"Machine":[5],"Learning":[6],"based":[7],"Natural":[8,111],"Language":[9,112],"Processing":[10],"(NLP),":[11],"language":[12,33],"dependency":[13],"has":[14,62,74],"always":[15],"been":[16,76],"a":[17,21,92,159,165,172],"limiting":[18],"factor":[19],"for":[20,30,52,97,153,190],"majority":[22],"of":[23,38,81,86,94,161,184],"NLP":[24,68],"applications.":[25],"Typically,":[26],"models":[27,51],"are":[28],"trained":[29,189],"English":[32,82,123],"due":[34],"to":[35,48,71,90,124,175],"availability":[37],"very":[39],"large":[40],"labeled":[41],"and":[42,69,128,136,158],"unlabeled":[43],"datasets,":[44],"which":[45],"also":[46,170],"allow":[47],"fine":[49],"tune":[50],"that":[53,61],"language.":[54,83],"Contradiction":[55,99],"Detection":[56,100],"is":[57,89,120,148],"one":[58],"such":[59],"problem":[60,155],"found":[63],"many":[64],"practical":[65],"applications":[66],"up":[70],"this":[72,87,106,154],"point":[73],"only":[75],"studied":[77],"context":[80],"The":[84],"scope":[85],"paper":[88],"examine":[91],"set":[93,116],"baseline":[95],"methods":[96],"task":[101],"on":[102,132],"German":[103],"text.":[104],"For":[105],"purpose,":[107],"well-known":[109],"Stanford":[110],"Inference":[113],"(SNLI)":[114],"data":[115,143,166],"(110,000":[117],"sentence":[118,177],"pairs)":[119],"machine-translated":[121],"from":[122],"German.":[125],"We":[126,169],"train":[127],"evaluate":[129],"four":[130],"classifiers":[131],"both":[133],"original":[135],"translated":[138],"data,":[139],"using":[140],"state-of-the-art":[141],"textual":[142],"representations.":[144],"Our":[145],"main":[146],"contribution":[147],"first":[150],"large-scale":[151],"assessment":[152],"German,":[157],"validation":[160],"machine":[162],"translation":[163],"as":[164],"generation":[167],"method.":[168],"present":[171],"novel":[173],"approach":[174],"learn":[176],"embeddings":[178],"by":[179],"exploiting":[180],"hidden":[182],"states":[183],"an":[185],"encoder-decoder":[186],"Sequence-To-Sequence":[187],"RNN":[188],"autoencoding":[191],"or":[192],"translation.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
