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dc.date.accessioned2014-09-22T17:13:16Z
dc.date.available2014-09-22T17:13:16Z
dc.date.created2014-09-21T16:22:49Z
dc.date.issued2014
dc.identifier.urihttp://hdl.handle.net/10852/41223
dc.description.abstractIn this paper we present our participation in the Semeval 2014 task “Evaluation of compositional distributional semantic models on full sentences through semantic relatedness and textual entailment”. Our results demonstrate that using generic tools for semantic analysis is a viable option for a system that recognizes textual entailment. The invested effort in developing such tools allows us to build systems for reasoning that do not require training. Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014), 2014, Pages 699-703.en_US
dc.languageEN
dc.language.isoenen_US
dc.titleUIO-Lien: Entailment Recognition using Minimal Recursion Semanticsen_US
dc.typeChapteren_US
dc.creator.authorLien, Elisabeth
dc.creator.authorKouylekov, Milen
cristin.unitcode185,15,0,0
cristin.unitnameDet matematisk-naturvitenskapelige fakultet
cristin.ispublishedtrue
cristin.fulltextoriginal
dc.identifier.cristin1156381
dc.identifier.startpage699
dc.identifier.endpage703
dc.identifier.urnURN:NBN:no-45793
dc.type.documentBokkapittelen_US
dc.type.peerreviewedPeer reviewed
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/41223/2/SemEval125.pdf
dc.type.versionPublishedVersion
cristin.btitleProceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)


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