Representing Translations on the Semantic Web
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This document proposes representing translations of natural language descriptions associated with ontology elements and linked data on the Semantic Web. It discusses current mechanisms like RDFS, SKOS and SKOS-XL that allow some representation of multilingual labels but have limitations. It then introduces the lemon model, an RDF-based ontology-lexicon model, as a basis for the proposal. A typology of translation relations is presented, distinguishing between literal and cultural equivalence translations. The proposal is a lemon module that represents translation relations as well as metadata like translation type and confidence. Examples demonstrate representing literal and cultural equivalence translations between lexicons. The approach aims to directly and explicitly represent translations while maintaining moderate complexity.
Representing Translations on the Semantic Web
- 1. 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
- 2. 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 used 1 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
- 3. The (Multilingual) Web of Data data.bnf.fr – Bibliothèque national de France GeoLinkedData.es – Spanish geospatial data p g p Rechtspraak.nl – Netherlands Council of the Judiciary FAO geopolitical ontology – with labels in en, fr, es, ar, zh, ru, it AGROVOC Linked Open Data – AGROVOC agricultural thesaurus 3
- 5. 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
- 6. Outline 1. Current mechanisms for translation relations 2. lemon 3. Typology of translation relations 4. 4 Proposed lemon module for translations Examples of use 5. Conclusions 6
- 7. Outline 1. Current mechanisms for translation relations 2. lemon 3. Typology of translation relations 4. 4 Proposed lemon module for translations Examples of use 5. Conclusions 7
- 8. RDFS, SKOS RDF(S), OWL RDF(S), OWL ifrs:FinancialAssets rdfs:label “financial assets”@en rdfs:SubPropertyOf SKOS ifrs:FinancialAssets skos:prefLabel “financial assets”@en SKOS labels: prefLabel, altLabel & hiddenLabel. p , 8
- 9. 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
- 10. SKOS-XL class SKOS‐XL SKOS XL skosxl:Label rdf:type ifrs:FinancialAssets ifrs:FinancialAssetsLabel skosxl:prefLabel skosxl:literalForm “financial assets”@en 10
- 11. SKOS-XL skosxl:Label SKOS‐XL rdf:type ifrs: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
- 12. LIR EN River FR 12
- 13. Limitations These 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
- 14. Outline 1. Current mechanisms for translation relations 2. lemon 3. Typology of translation relations 4. 4 Proposed lemon module for translations Examples of use 5. Conclusions 14
- 15. The lemon model An RDF‐based ontology‐lexicon model for ontologies An RDF‐based ontology‐lexicon model for ontologies Main 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
- 16. The lemon model But this is also quite Not so much… remember its complex, isn’t it? modular nature 16
- 18. Outline 1. Current mechanisms for translation relations 2. lemon 3. Typology of translation relations 4. 4 Proposed lemon module for translations Examples of use 5. Conclusions 18
- 19. Typology of translation relations Ontology Localization Multilingual Ontology (an ontololgy in which labels are documented in multiple NLs) but… b t Does a 1 to 1 correspondence between always exist? 19
- 20. 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 mismatches languages represented between cultures and in the ontology languages 20
- 21. Literal vs. Cultural equivalence Translation Ontology A Ontology B (German) (English) Concept A p Concept B p Sparkasse German savings institution Savings bank Literal translation Cultural equivalence translation 21
- 22. Outline 1. Current mechanisms for translation relations 2. lemon 3. Typology of translation relations 4. 4 Proposed lemon module for translations Examples of use 5. Conclusions 22
- 23. lemon module for translations Lexicon language:String entry isSenseOf reference LexicalEntry LexicalSense Ontology term lexicalForm sourceLexicalSense targetLexicalSense Form Translation translationOrigin Resource representation:String confidenceLevel:double LiteralTranslation CulturalEquivalenceTranslation q 23
- 24. Example of literal translation LEXICONEN LexicalEntry LexicalSense ONTOLOGY “payment method” p y http://purl.org/goodrelations/v1#PaymentMethods Translation LexicalEntry LexicalSense “medio de pago” medio pago LEXICONES
- 25. Example of literal translation LEXICONEN LexicalEntry LexicalSense ONTOLOGY “Cabinet of Spain” p http://dbpedia.org/page/Consejo_de_Ministros LiteralTranslation LexicalEntry LexicalSense “Consejo de Ministros” Consejo Ministros LEXICONES
- 26. Example of cultural equivalence translation LEXICONEN ONTOLOGY LexicalEntry LexicalSense http://www.oegov.us/democracy/us/core/owl/usgov#CABINET “Cabinet” CulturalEquivalenceTranslation http://dbpedia.org/page/Cabinet_of_Spain LexicalEntry LexicalSense “Consejo de Ministros” Consejo Ministros ONTOLOGY LEXICONES
- 27. Outline 1. Current mechanisms for translation relations 2. lemon 3. Typology of translation relations 4. 4 Proposed lemon module for translations Examples of use 5. Conclusions 27
- 28. Conclusions Benefits 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 separate Future work: Test this with more real examples Algorithms to distinguish literal/culturally equivalent translations 28
- 29. Thanks for your attention! 29