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lemon: An Ontology-Lexicon model for the
Multilingual Semantic Web
MONNET Project Consortium, represented by
Thierry Declerck (DFKI GmbH), Paul Buitelaar & Tobias Wunner (DERI), John
McCrae (CITEC), Elena Montiel-Ponsoda & Guadalupe Aguado de Cea (UPM)
http://www.monnet-project.eu
http://twitter.com/monnetproject
W3C Workshop:
The Multilingual Web - Where Are We?
26-27 October 2010, Madrid
Presentation Overview
• Monnet Project
• Partners
• Objectives
• Financial Use Case
• Introduction to lemon
• Why lemon?
• Design of the lemon model
• Relations to other projects and to standardisation bodies
• Conclusion
Project Partners
Industrial Organizations
 SAP, Germany (http://www.sap.com/index.epx)
 BeInformed, The Netherlands (/http://www.beinformed.nl)
 XBRL-EUROPE, Belgium (http://www.xbrl.org/eu/)
Research Institutes
 DERI, Ireland (http://www.deri.ie/), coordinator
 DFKI, Germany (www.dfki.de)
 UPM, Spain (http://www.upm.es/institucional)
 UniBi-CITEC, Germany (http://www.uni-bielefeld.de)
Monnet: Main Objectives
• Monnet addresses some of the topics identified by the
“MultilingualWeb” project, http://www.multilingualweb.eu/:
„The MultilingualWeb project is exploring standards and best practices that
support the creation, localization and use of multilingual web-based information“.
• With: Multilingual Ontologies for Networked Knowledge
• Linguistically enriched knowledge representation
• Multilingual access to structured/networked knowledge: ontologies, knowledge
bases, linked data
• How: Handling Information at the Semantic Level
• Ontology-Based Cross-lingual information Extraction, Storage and Presentation
• Localization/Translation of information abstracting from language & layout
Monnet Financial Use Case
• Objective: multilingual access to financial reports for sharing
business knowledge across Europe
• Semantic-level analysis of business reports of companies
• Search for financial information and financial report creation in the
language of choice of the users
• Outcome: A prototype that will allow a financial analyst to
search for information by filling in structured search forms
localized to his/her own language
• The results will be presented in terms of charts, diagrams, results lists
etc. localized to the preferred language of the user
Knowledge Sources
 XBRL (eXtensible Business Reporting Language): an XML-based mark-up
language for the exchange of business information, including financial
reporting. Available taxonomies ecoded in XBRL:
 IFRS (International Financial Reporting Standards): a standard
developed by the International Accounting Standards Board (IASB).
IFRS Terminology is translated in many languages.
 GAAP (Generally Accepted Accounting Principles), taxonomies
reflecting national and regional legislations on financial reporting.
Terms in GAAP taxonomies are available in the national/regional
languages, and maybe in English.
IFRS-XBRL Example
XBRL – Semantic Analysis
“Enhance semantics to
facilitate label translation and
information extraction.”
Upgrading XBRL into an Ontology
lexicon
Application of STL
• Localization of domain terms
• Ontology-based Information Extraction
ifrs:Revenue
ifrs:ProfitLossBeforeTax
ifrs:MinimumFinanceLeasePaymentsPayable
ontology
ifrs:ProfitLossBeforeTax(Tesco,3176))
ifrs:Revenue(Tesco,56910)
ifrs:ProfitLossBeforeTax(SAP,676)
ifrs:Revenue(SAP,2894)
XBRL-Ontology as the basis
for Localization and OBIE
Application in Machine Translation
Domain Terms Localization:
“minimum finance lease payments receivable”
Google-Translate: Minimum finance lease payments receivable
minimum finance lease payments receivable
decompose IFRS, sapTerm, googleDefine
mindest Finanzierungsleasing Zahlungen Forderungen
translate parts multilingual domain ontologies, IATE, DBPedia, leo
reconstruct
Mindestfinanzierungsleasingzahlungsforderungen
Google-Translate: Minimum Leasingzahlungen Forderungen
Official IFRS: Im Rahmen von Finanzierungs-Leasingverhältnissen zu erhaltende Mindestzahlungen
relying on lexical information, but compounding
language issues!!
…The fair value of the Group’s
finance lease receivables at
23 February 2008 was £5m…
..As at December 31, 2008,
the future minimum lease
payments expected to be
received was €16 million…
Application in Information Extraction (IE)
Application in OBIE
linguistic analysis payments
received
receivabl
es
:MinimumFinanceLeasePaymentsReceivable
rdfs:subClassOf xbrli:monetaryItemType ;
rdfs:label “Minimum finance lease payments receivable”@en .
semantically lifted
Minimum finance lease payments receivableterm analysis
Monnet Components to address the issues
Lexicalization Component
• Taxonomies and ontologies have labels that contain NL
expressions (terms), which need to be linguistically enriched for
supporting both, the localization of labels and the multilingual
OBIE task
• For this purpose, we define lemon as a ontology-lexicon model
• RDF(S)
• Minimalist (i.e., a hub for connecting lexical and terminological
description elements with ontologies)
• Not prescriptive (i.e., uses data categories)
• Relational semantics (i.e., uses ontologies)
• Modular and extensible
lemon's origins
• Lexical Markup Framework (ISO 24613)
• Standard for representing lexicons
• XML/UML
• LexInfo, LIR
• Represent lexical information relative to an ontology
• OWL
• SKOS (W3C Standard)
• Designed for Taxonomy/Vocabulary representation
• RDF
The model
The model provides a
principled chain
between the semantic
representation and its
linguistic realization
The core path
 Lexicon: Represents the lexicon. Marked
with a single language tag (ISO-639)
 Lexical Entry: An entry in a lexicon. Syntax-
invariant
 Lexical Sense: The relationship between
the entry and its ontology reference.
 Reference: The ontology entity
 Form: A form of an entry. Orthography-
invariant
 Representation: The string. IETF lang-
tagged
Relations to other Projects
Monnet has a clear link to MultilingualWeb, proposing
a semantic approach for extracting, storing and
presenting information across languages.
Monnet has a clear link to META-NET (formal
collaboration agreement being discussed).
 A possible application would be to offer a localization of
the terminology in use in the ontology underlying the
META-NET portal, and to apply OBIE to documents in
the field of Human Language Technology
Relation to Standards
• lemon is drawing on existing standards in both the
W3C (RDF, OWL, SKOS, ...) and the ISO framework
(LMF, TMF, ISOCat, ...).
• lemon can contribute also to both:
• W3C: on how to represent lexicalised ontologies and to put
them into relation with other semantic resources on the web
• ISO: on guidelines for linguistic driven lexicalization of
ontologies
• Adjusting the role played by LMF and other ISO standards on
language resource management
Conclusions
• Monnet aims at providing a novel combination of
semantic web solutions and localization technologies
for semantically structured information
• 1st step in this direction has been the development of
an ontology-lexicon model, lemon, for supporting the
• Localization of ontology labels
• Ontology-based multilingual IE
• Future work will be dedicated to ontology-based, cross-
lingual information access and presentation
Thanks for your attention
Contact:
http://www.monnet-project.eu &
http://twitter.com/monnetproject

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Lemon at-mlw3

  • 1. lemon: An Ontology-Lexicon model for the Multilingual Semantic Web MONNET Project Consortium, represented by Thierry Declerck (DFKI GmbH), Paul Buitelaar & Tobias Wunner (DERI), John McCrae (CITEC), Elena Montiel-Ponsoda & Guadalupe Aguado de Cea (UPM) http://www.monnet-project.eu http://twitter.com/monnetproject W3C Workshop: The Multilingual Web - Where Are We? 26-27 October 2010, Madrid
  • 2. Presentation Overview • Monnet Project • Partners • Objectives • Financial Use Case • Introduction to lemon • Why lemon? • Design of the lemon model • Relations to other projects and to standardisation bodies • Conclusion
  • 3. Project Partners Industrial Organizations  SAP, Germany (http://www.sap.com/index.epx)  BeInformed, The Netherlands (/http://www.beinformed.nl)  XBRL-EUROPE, Belgium (http://www.xbrl.org/eu/) Research Institutes  DERI, Ireland (http://www.deri.ie/), coordinator  DFKI, Germany (www.dfki.de)  UPM, Spain (http://www.upm.es/institucional)  UniBi-CITEC, Germany (http://www.uni-bielefeld.de)
  • 4. Monnet: Main Objectives • Monnet addresses some of the topics identified by the “MultilingualWeb” project, http://www.multilingualweb.eu/: „The MultilingualWeb project is exploring standards and best practices that support the creation, localization and use of multilingual web-based information“. • With: Multilingual Ontologies for Networked Knowledge • Linguistically enriched knowledge representation • Multilingual access to structured/networked knowledge: ontologies, knowledge bases, linked data • How: Handling Information at the Semantic Level • Ontology-Based Cross-lingual information Extraction, Storage and Presentation • Localization/Translation of information abstracting from language & layout
  • 5. Monnet Financial Use Case • Objective: multilingual access to financial reports for sharing business knowledge across Europe • Semantic-level analysis of business reports of companies • Search for financial information and financial report creation in the language of choice of the users • Outcome: A prototype that will allow a financial analyst to search for information by filling in structured search forms localized to his/her own language • The results will be presented in terms of charts, diagrams, results lists etc. localized to the preferred language of the user
  • 6. Knowledge Sources  XBRL (eXtensible Business Reporting Language): an XML-based mark-up language for the exchange of business information, including financial reporting. Available taxonomies ecoded in XBRL:  IFRS (International Financial Reporting Standards): a standard developed by the International Accounting Standards Board (IASB). IFRS Terminology is translated in many languages.  GAAP (Generally Accepted Accounting Principles), taxonomies reflecting national and regional legislations on financial reporting. Terms in GAAP taxonomies are available in the national/regional languages, and maybe in English.
  • 8. XBRL – Semantic Analysis “Enhance semantics to facilitate label translation and information extraction.” Upgrading XBRL into an Ontology
  • 9. lexicon Application of STL • Localization of domain terms • Ontology-based Information Extraction ifrs:Revenue ifrs:ProfitLossBeforeTax ifrs:MinimumFinanceLeasePaymentsPayable ontology ifrs:ProfitLossBeforeTax(Tesco,3176)) ifrs:Revenue(Tesco,56910) ifrs:ProfitLossBeforeTax(SAP,676) ifrs:Revenue(SAP,2894) XBRL-Ontology as the basis for Localization and OBIE
  • 10. Application in Machine Translation Domain Terms Localization: “minimum finance lease payments receivable” Google-Translate: Minimum finance lease payments receivable minimum finance lease payments receivable decompose IFRS, sapTerm, googleDefine mindest Finanzierungsleasing Zahlungen Forderungen translate parts multilingual domain ontologies, IATE, DBPedia, leo reconstruct Mindestfinanzierungsleasingzahlungsforderungen Google-Translate: Minimum Leasingzahlungen Forderungen Official IFRS: Im Rahmen von Finanzierungs-Leasingverhältnissen zu erhaltende Mindestzahlungen relying on lexical information, but compounding language issues!!
  • 11. …The fair value of the Group’s finance lease receivables at 23 February 2008 was £5m… ..As at December 31, 2008, the future minimum lease payments expected to be received was €16 million… Application in Information Extraction (IE) Application in OBIE linguistic analysis payments received receivabl es :MinimumFinanceLeasePaymentsReceivable rdfs:subClassOf xbrli:monetaryItemType ; rdfs:label “Minimum finance lease payments receivable”@en . semantically lifted Minimum finance lease payments receivableterm analysis
  • 12. Monnet Components to address the issues
  • 13. Lexicalization Component • Taxonomies and ontologies have labels that contain NL expressions (terms), which need to be linguistically enriched for supporting both, the localization of labels and the multilingual OBIE task • For this purpose, we define lemon as a ontology-lexicon model • RDF(S) • Minimalist (i.e., a hub for connecting lexical and terminological description elements with ontologies) • Not prescriptive (i.e., uses data categories) • Relational semantics (i.e., uses ontologies) • Modular and extensible
  • 14. lemon's origins • Lexical Markup Framework (ISO 24613) • Standard for representing lexicons • XML/UML • LexInfo, LIR • Represent lexical information relative to an ontology • OWL • SKOS (W3C Standard) • Designed for Taxonomy/Vocabulary representation • RDF
  • 15. The model The model provides a principled chain between the semantic representation and its linguistic realization
  • 16. The core path  Lexicon: Represents the lexicon. Marked with a single language tag (ISO-639)  Lexical Entry: An entry in a lexicon. Syntax- invariant  Lexical Sense: The relationship between the entry and its ontology reference.  Reference: The ontology entity  Form: A form of an entry. Orthography- invariant  Representation: The string. IETF lang- tagged
  • 17. Relations to other Projects Monnet has a clear link to MultilingualWeb, proposing a semantic approach for extracting, storing and presenting information across languages. Monnet has a clear link to META-NET (formal collaboration agreement being discussed).  A possible application would be to offer a localization of the terminology in use in the ontology underlying the META-NET portal, and to apply OBIE to documents in the field of Human Language Technology
  • 18. Relation to Standards • lemon is drawing on existing standards in both the W3C (RDF, OWL, SKOS, ...) and the ISO framework (LMF, TMF, ISOCat, ...). • lemon can contribute also to both: • W3C: on how to represent lexicalised ontologies and to put them into relation with other semantic resources on the web • ISO: on guidelines for linguistic driven lexicalization of ontologies • Adjusting the role played by LMF and other ISO standards on language resource management
  • 19. Conclusions • Monnet aims at providing a novel combination of semantic web solutions and localization technologies for semantically structured information • 1st step in this direction has been the development of an ontology-lexicon model, lemon, for supporting the • Localization of ontology labels • Ontology-based multilingual IE • Future work will be dedicated to ontology-based, cross- lingual information access and presentation
  • 20. Thanks for your attention Contact: http://www.monnet-project.eu & http://twitter.com/monnetproject

Editor's Notes

  1. you will not find this term but sub terms
  2. Internet Engineering Task Force