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dc.contributor.authorArcan, Mihael
dc.contributor.authorMontiel-Ponsoda, Elena
dc.contributor.authorMcCrae, John P.
dc.contributor.authorBuitelaar, Paul
dc.identifier.citationArcan, Mihael, Montiel-Ponsoda, Elena, McCrae, John P., & Buitelaar, Paul. (2018). Automatic Enrichment of Terminological Resources: the IATE RDF Example. Paper presented at the LREC 2018, Eleventh International Conference on Language Resources and Evaluation, Miyazaki, Japan, 7-12 May.en_IE
dc.description.abstractTerminological resources have proven necessary in many organizations and institutions to ensure communication between experts. However, the maintenance of these resources is a very time-consuming and expensive process. Therefore, the work described in this contribution aims to automate the maintenance process of such resources. As an example, we demonstrate enriching the RDF version of IATE with new terms in the languages for which no translation was available, as well as with domain-disambiguated sentences and information about usage frequency. This is achieved by relying on machine translation trained on parallel corpora that contains the terms in question and multilingual word sense disambiguation performed on the context provided by the sentences. Our results show that for most languages translating the terms within a disambiguated context significantly outperforms the approach with randomly selected sentences.en_IE
dc.description.sponsorshipThis publication is supported by a research grant from Science Foundation Ireland, SFI/12/RC/2289 (Insight), a research visit grant from Universidad Politecnica de Madrid, ´ by the Spanish Datos4.0 project (TIN2016-78011-C4-4-R) and by the EU’s Lynx project (H2020 Research and Innovation Programme under GA num 780602).en_IE
dc.publisherEuropean Language Resources Associationen_IE
dc.relation.ispartofLanguage Resources and Evaluation Conference (LREC 2018)en
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Ireland
dc.subjectKnowledge basesen_IE
dc.subjectMachine translationen_IE
dc.titleAutomatic enrichment of terminological resources: the IATE RDF exampleen_IE
dc.typeConference Paperen_IE
dc.contributor.funderScience Foundation Irelanden_IE
dc.contributor.funderHorizon 2020en_IE
dc.local.contactMihael Arcan. Email:
dcterms.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/en_IE
dcterms.projectinfo:eu-repo/grantAgreement/EC/H2020::IA/780602/EU/Building the Legal Knowledge Graph for Smart Compliance Services in Multilingual Europe/Lynxen_IE

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