Representing Translations on the Semantic Web
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Representing Translations on the Semantic Web

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Representing Translations on the Semantic Web. Elena Montiel-Ponsoda. ISWC2011

Representing Translations on the Semantic Web. Elena Montiel-Ponsoda. ISWC2011

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    Representing Translations on the Semantic Web Representing Translations on the Semantic Web Presentation Transcript

    • Representing Translations on the Semantic Web Elena Montiel-Ponsoda, Jorge Gracia, Guadalupe Aguado-de-Cea, Asunción Gómez-Pérez Ontology Engineering Group (OEG) Facultad de Informática Universidad Politécnica de Madrid http://www.oeg-upm.net {emontiel, j { ti l jgracia, l i lupe, asun}@fi.upm.es }@fi
    • The (Multilingual) Web of Data• We know that the Web is multilingual….• Is the Web of Data also multilingual?• Ell, B., Vrandecic, D., and Simperl, E. (2011). Labels in the Web of Data English: 44.72% Most used1 language specified: 2.2% language tags: German: 5.22 %Nl languages specified: 0 7% ifi d 0.7% French: 5.11% F h 11% 2
    • The (Multilingual) Web of Datadata.bnf.fr – Bibliothèque national de FranceGeoLinkedData.es – Spanish geospatial data p g pRechtspraak.nl – Netherlands Council of the JudiciaryFAO geopolitical ontology – with labels in en, fr, es, ar, zh, ru, itAGROVOC Linked Open Data – AGROVOC agricultural thesaurus 3
    • The problem4
    • Our proposal• To propose a representation mechanism for explicit p p p p translation relations between natural language descriptions associated to ontology elements and data.• To implement it as a metamodel in OWL offered as a module of the lemon model, lexicon-ontology model to account for the linguistic descriptions associated to g p ontologies and linked data. 5
    • Outline1. Current mechanisms for translation relations2. lemon3. Typology of translation relations4.4 Proposed lemon module for translations  Examples of use5. Conclusions 6
    • Outline1. Current mechanisms for translation relations2. lemon3. Typology of translation relations4.4 Proposed lemon module for translations  Examples of use5. Conclusions 7
    • RDFS, SKOSRDF(S), OWLRDF(S), OWL ifrs:FinancialAssets rdfs:label “financial assets”@en rdfs:SubPropertyOfSKOS ifrs:FinancialAssets skos:prefLabel “financial assets”@enSKOS labels:  prefLabel, altLabel & hiddenLabel.  p , 8
    • SKOS SKOS enables a simple form of multilingual labeling:ifrs:FinancialAssets skos:prefLabel p “financial assets”@en skos:prefLabel “activos financieros”@es What happens when we have more than one label per language? Food and Agriculture Organization and FAO? How can we create explicit links between labels? Say that one is translation, acronym of the other? 9
    • SKOS-XL classSKOS‐XLSKOS XL skosxl:Label rdf:typeifrs:FinancialAssets ifrs:FinancialAssetsLabel skosxl:prefLabel skosxl:literalForm “financial assets”@en 10
    • SKOS-XL skosxl:Label SKOS‐XL rdf:typeifrs:FinancialAssets ifrs:FinancialAssetsLabel1 skosxl:prefLabel skosxl:literalForm “financial assets”@en skosxl:labelRelation ex:isTranslationOf rdfs:subPropertyOf ex:isTranslationOf “activos financieros”@es skosxl:literalForm ifrs:FinancialAssetsLabel2 skosxl:prefLabel rdf:type skosxl:Label 11
    • LIREN River FR 12
    • LimitationsThese solutions work! …Th l ti k!  …but with some limitations   Rigid models  Simple translation relation insufficient for: p  original vs. target label  type of translation relation  source of the translation  adequacy or reliability of translations 13
    • Outline1. Current mechanisms for translation relations2. lemon3. Typology of translation relations4.4 Proposed lemon module for translations  Examples of use5. Conclusions 14
    • The lemon modelAn RDF‐based ontology‐lexicon model for ontologiesAn RDF‐based ontology‐lexicon model for ontologiesMain features: • Semantics by reference • Rich lexical and terminological description of ontology elements • Concise (i.e., trade off between complexity and expressivity) • Descriptive not prescriptive (i.e., uses data categories) • Modular and extensible 15
    • The lemon model But this is also quiteNot so much… remember its complex, isn’t it?modular nature 16
    • The lemon model17
    • Outline1. Current mechanisms for translation relations2. lemon3. Typology of translation relations4.4 Proposed lemon module for translations  Examples of use5. Conclusions 18
    • Typology of translation relations Ontology Localization Multilingual Ontology(an ontololgy in which labels aredocumented in multiple NLs) but… b t Does a 1 to 1 correspondence between always exist? 19
    • Typology of translation relations Types of domains Internationalized Culturally C or standardized influenced domains domains Types of conceptualizations Conceptualizations Conceptualizations that shared among the represent mismatcheslanguages represented between cultures and in the ontology languages 20
    • Literal vs. Cultural equivalence TranslationOntology A Ontology B(German) (English) Concept A p Concept B p Sparkasse German savings institution Savings bankLiteral translation Cultural equivalence translation 21
    • Outline1. Current mechanisms for translation relations2. lemon3. Typology of translation relations4.4 Proposed lemon module for translations  Examples of use5. Conclusions 22
    • lemon module for translations Lexicon language:String entry isSenseOf reference LexicalEntry LexicalSense Ontology termlexicalForm sourceLexicalSense targetLexicalSense Form Translation translationOrigin Resource representation:String confidenceLevel:double LiteralTranslation CulturalEquivalenceTranslation q 23
    • Example of literal translationLEXICONENLexicalEntry LexicalSense ONTOLOGY“payment method” p y http://purl.org/goodrelations/v1#PaymentMethods TranslationLexicalEntry LexicalSense“medio de pago” medio pago LEXICONES
    • Example of literal translationLEXICONENLexicalEntry LexicalSense ONTOLOGY“Cabinet of Spain” p http://dbpedia.org/page/Consejo_de_Ministros LiteralTranslationLexicalEntry LexicalSense“Consejo de Ministros” Consejo Ministros LEXICONES
    • Example of cultural equivalence translationLEXICONEN ONTOLOGYLexicalEntry LexicalSense http://www.oegov.us/democracy/us/core/owl/usgov#CABINET“Cabinet” CulturalEquivalenceTranslation http://dbpedia.org/page/Cabinet_of_SpainLexicalEntry LexicalSense“Consejo de Ministros” Consejo Ministros ONTOLOGY LEXICONES
    • Outline1. Current mechanisms for translation relations2. lemon3. Typology of translation relations4.4 Proposed lemon module for translations  Examples of use5. Conclusions 27
    • ConclusionsBenefits of the approach:  Direct, Direct explicit translations can be represented  Distinction between literal/culturally equivalent translation  Translation metadata can be accounted for  Moderate complexity  Expressivity of lemon model  Conceptual/lexical layers remain separateFuture work:  Test this with more real examples  Algorithms to distinguish literal/culturally equivalent translations 28
    • Thanks for your attention! 29