1. Ontology Lexicalisation In collaboration with John McCrae, Philipp Cimiano (CITEC, Univ. of Bielefeld) Elena Montiel-Ponsado (Universidad Politecnica Madrid) and other Monnet partners  Copyright 2010 Digital Enterprise Research Institute. All rights reserved, Paul Buitelaar Paul Buitelaar Unit for Natural Language Processing Digital Enterprise Research Institute - National University of Ireland, Galway

2. What is this talk about? Ontology Lexicalisation  Integrating ontologies (knowledge representation about objects) and lexicons (knowledge representation about words that refer to objects)  Enriching ontologies with a lexical layer Defining an Ontology for Lexicons  Defining a formal model (ontology) for representing lexical information relative to independently defined ontological semantics of concepts denoted by this lexicon  Formal model for web-based, modular, distributed lexicons

3. Use Cases of Ontology Lexicalisation Ontology-based Information Extraction from text Ontology Learning from text Lexical methods in Ontology Alignment Ontology Verbalisation Ontology Localisation …

4. Ontology-based Information Extraction >> ontology-text mismatch – is this a good match? (no) Ontology: Recurso-comercial Text: recurso por las licencias comerciales

5. Cross-lingual Ontology-based IE >> cross-lingual meaning mismatch Ontology (es): Recurso-comercial Text (en): Commercial Appeal (of Communism …)

6. SKOS - Multilingual Information

7. Not much uptake yet? from http://data.nytimes.com/http://data.nytimes.com/

8. Ontology-Text Mismatch ‘Edificio-historico’ vs. ‘…edificio, declarado Monumento Histórico…’ >> goes beyond SKOS (monolingual & multilingual term variants) >> requires representation of lexical information to compute linguistic variants, e.g. ‘edificio historico[apposVP[NP[Adj]]]’

9. A Lexicon Model for Ontologies Requirements for ‘ontology-lexicon’ model  Represent linguistic information relative to ontology – Avoid unnecessary ambiguities by representing only lexical features relevant to semantics of underlying application  Keep semantics separate from linguistic info – Separate clearly ‘world’ (properties of objects referred to by words) from ‘word’ (properties of words) knowledge  Modular, minimal design – Provide simple core model that can be easily extended upon need

10. Was there a solution already? - SKOS Simple Knowledge Organization System – SKOS  General model for formalizing thesauri, terminologies and related semantic and knowledge resources  Formalization of terminology in focus - terminology, classification, Semantic Web communities  Does not address linguistic aspects of terminology, or therefore, the lexicon-ontology interface  http://www.w3.org/2004/02/skos/ http://www.w3.org/2004/02/skos/

11. Was there a solution already? - GOLD General Ontology for Linguistic Description – GOLD  Community-based ontology of linguistics  Linguistic study in focus - linguistics community  Formal model of linguistics as an ontology, but not about connecting lexical features to ontological semantics  Other issues: very big, modularity?  http://linguistics-ontology.org/gold/2010 http://linguistics-ontology.org/gold/2010

12. Was there a solution already? - OWN OntoWordNet – OWN  Formal specification of WordNet through extension and axiomatization of its conceptual relations  Formal knowledge representation in focus - logic, knowledge representation, Semantic Web communities  Turns WordNet into an ontology but not about connecting lexical features to ontological semantics  http://wiki.loa-cnr.it/index.php/LoaWiki:OWN http://wiki.loa-cnr.it/index.php/LoaWiki:OWN

13. Was there a solution already? - LMF Lexical Markup Framework – LMF  General model for formalizing and sharing of machine- readable dictionaries  Lexical knowledge representation in focus - lexicography, NLP communities  Very close to ontology-lexicon requirements, but no view on how lexical features link to ontological semantics – semantics is limited to a notion of sense based on synsets  Other issues: incomplete formal model, focus on classes, less on properties/relations  http://www.lexicalmarkupframework.org/ http://www.lexicalmarkupframework.org/

14. lemon lexicon model for ontologies: ‘lemon’  General model for formalizing lexical features relative to independently defined ontological semantics Two-level modelling  Abstract level (meta-model): lemon  Instantiation level (lexicon model): e.g. ‘LexInfo2’  http://lexinfo.net/ http://lexinfo.net/

15. lemon: Overview

16. LexicalEntry can be a Word, Phrase, or Part - such as an Affix lemon: Lexicon

17. lemon: Form LexicalForm can be, e.g., lemma (canonicalForm), plural form (otherForm), stem (abstractForm)

18. lemon: Structure LexicalEntry can be decomposed into one or more Components and compositional structure can be represented

19. lemon: Structure - Example

20. lemon: Meaning & Reference LexicalSense is an underspecified sense that points to a language- external reference, a unique ontological semantic object, depending on conditions and context LexicalSense can have a subsense and senseRelation with other LexicalSense sememe relation between LexicalSense and ontological semantic object can be either of pref/alt/hiddenSem

21. lemon: Meaning & Reference - Examples

22. lemon: Lexical Projection LexicalEntry can introduce a syntactic frame with arguments that are mapped to LexicalSense and indirectly to ontological semantic objects/properties

23. lemon: Lexical Projection - Example

24. lemon in Use Ontology-Lexicon Generator  Generate a lexicon for a given ontology in RDF/OWL format  http://monnetproject.deri.ie/osgi/DemoLexiconGenerator http://monnetproject.deri.ie/osgi/DemoLexiconGenerator @prefix rdf:. @prefix lemon:. @prefix financeV4:. @prefix lexinfo:. @prefix pennbank:. @prefix rdfs:. … lemon:phraseRoot [ lemon:edge [ lemon:edge [ lemon:edge [ lemon:leaf _:n6 ] ; lemon:constituent pennbank:NNP ] ; lemon:constituent pennbank:NP ], [ lemon:edge [ lemon:edge [ lemon:leaf _:n88 ] ; lemon:constituent pennbank:VBD ], [ lemon:edge [ lemon:edge [ lemon:leaf _:n69 ] ; lemon:constituent pennbank:NN ] ; lemon:constituent pennbank:NP ] ; lemon:constituent pennbank:VP ] ; lemon:constituent pennbank:S ] ; lemon:decomposition ( _:n6 _:n88 _:n69 ) ; lemon:sense [ lemon:reference financeV4:AssetBackedDebt ] ; lemon:canonicalForm [ lemon:writtenRep "Asset backed debt"@en ]. … lexinfo:partOfSpeech lexinfo:verb ; lemon:canonicalForm [ lexinfo:tense lexinfo:past ; lexinfo:verbFormMood lexinfo:indicative ; lemon:writtenRep "backed"@en ; lexinfo:aspect lexinfo:perfective ]. _:n88 rdf:type lemon:Component ; lexinfo:tense lexinfo:past ; lemon:element ; lexinfo:verbFormMood lexinfo:indicative ; lexinfo:aspect lexinfo:perfective.

25. Lexical Linked Data lemon is a web-based ontology, i.e., based on Uniform Resource Identifiers (URI)  Therefore all objects described by it are uniquely identifiable on the web  And can therefore be interlinked in a flexible, modular and distributed way  Making lemon-based lexicons part of the Web of Data, as currently defined by the ‘Linked Open Data cloud’

26. Lexical Linked Data – LOD cloud

27. Lexical Linked Data - Implications lemon objects (lexicons, lexical entries, words, phrases, forms, variants, senses, references, etc.) can be maintained uniquely (only one URI for each lemon object) but in a distributed fashion (maintenance by various parties) lemon objects can be interlinked upon need, creating layers of lexical structure defined formally by selected links with growing legacy of collaborative, formal definition of lexical structure (through use in applications), meta-level analysis of lemon objects will become object of study for lexicography and linguistics ontology development can build on and plug-in formal lexical structures in specific application domains collaborative web-based ontological knowledge development and lexicon development will go hand-in-hand …

28. What happens next? lemon  W3C Incubator Group planned  Experimentation, Dissemination  YOUR input/feedback Lexical Linked Data  Develop infrastructures to support/exploit this  Envision drastically novel applications in linguistic study and product development

29. Acknowledgements & Further Info Monnet colleagues  In particular John McCrae of CITEC, University of Bielefeld, Germany who leads the lemon effort in Monnet Grant support  EU FP7 Grant No. 248458 for the Monnet project on Multilingual Ontologies for Networked Knowledge  Science Foundation Ireland Grant No. SFI/08/CE/I1380 for Lion-2 http://nlp.deri.ie/ http://nlp.deri.ie/ Further info  lemon: http://lexinfo.nethttp://lexinfo.net  http://www.monnet-project.eu & http://twitter.com/monnetproject http://www.monnet-project.euhttp://twitter.com/monnetproject  Monnet Community – contact me: paul.buitelaar@deri.orgpaul.buitelaar@deri.org