Buitelaar P, Cimiano P, McCrae J, Montiel-Ponsoda E, Declerck T. Ontology Lexicalization: The lemon perspective. In:  Proceedings of the Workshops - 9th International Conference on Terminology and Artificial Intelligence (TIA 2011). 2011: 33-36

Buitelaar, Paul

Cimiano, Philipp 

Declerck, Thierry

McCrae, John 

Montiel-Ponsoda, Elena

English

Publications at Bielefeld University

Ontology Lexicalisation: The lemon PerspectivePaul Buitelaar•, Philipp Cimiano?, John McCrae?, Elena Montiel-Ponsoda†, Thierry Declerck‡•Unit for Natural Language Processing, DERI, National University of Ireland, Galway?Semantic Computing Group, CITEC, University of Bielefeld, Germany,†Ontology Engineering Group, Universidad Polite´cnica de Madrid, Spain,‡Language Technology Lab, DFKI, Germany1 IntroductionOntologies (Guarino1998) capture knowledge butfail to capture the structure and use of terms inexpressing and referring to this knowledge in nat-ural language. The structure and use of termsis the concern of terminology as well as lexicol-ogy. In recent years, the relevance of terminologyin knowledge representation has been recognizedagain (for example the advent of SKOS1) but lessconsideration has been given to lexical and lin-guistic issues in knowledge representation (Buite-laar2010).2 Use Cases of Ontology LexicalisationNatural language is often the medium of choice forknowledge representation and transfer betweenhumans. However, ambiguity is widespread innatural language. Words have multiple meaningsand grammar can be ambiguous in structure andtherefore in interpretation. However, such ambi-guities appear to provide little issue to people, whocan with little effort resolve these ambiguities innearly all situations. Machines, on the other hand,have significant issues in resolving these ambigu-ities and this can lead to difficulties in definingprecise interpretations in technical domains. Toillustrate this we will now briefly explore someof the use cases of ontology lexicalisation, i.e. inknowledge acquisition from text and multilingualknowledge access.2.1 Knowledge Acquisition from TextIn the case of knowledge acquisition from text weaim to identify relevant text segments and align1http://www.w3.org/2009/08/skos-reference/skos.htmlthese with formally defined knowledge structures,such as facts and axioms. Let us focus onontology-based information extraction, that is, theextraction of facts from text relative to a givenontology. Consider for example an ontology ontourism with ontology labels (terms) in Spanish.The ontology defines concepts of relevance totourism such as historical buildings, which will bedefined by use of the Spanish term (ontology la-bel) “edificio histo´rico”. For instance, in the fol-lowing sentence there is a specification of a setof facts concerning a historical building (Univer-sidad de Barcelona), its architect (Elies Rogent),and building period (1863-1882):• “El edificio histo´rico de la Universidad deBarcelona es obra de Elies Rogent, se inicio´su construccio´n en 1863, pero no se concluyo´hasta 1882.” (The historical building of theUniversity of Barcelona is the work of EliesRogent, its construction began in 1863, butwas not completed until 1882.)Observe that the match between ontology labeland text is straightforward, as they are identical.However, this is not the case in the following ex-ample:• “El Cabildo de Buenos Aires, ... El edi-ficio, declarado Monumento Histo´rico Na-cional desde el an˜o 1933, fue objeto de suce-sivas alteraciones, ... ” (The Cabildo ofBuenos Aires, ... The building, declared aNational Historic Landmark in the year 1933,underwent successive alterations, ...)In this case, the text segment again specifies aset of facts on a historical building (El Cabildo),its location (Buenos Aires), and dedication date(1933), but the match between ontology label andtext is not straightforward and requires the rep-resentation of linguistic information to computemorphological and syntactic variants.2.2 Multilingual Knowledge AccessOntology lexicalisation can be extended to mul-tiple languages, enabling applications such asmultilingual ontology-based question answering.Consider the following question in English,Dutch, German and Spanish:• “Who painted the Mona Lisa?”• “Wie schilderde de Mona Lisa?”• “Wer malte die Mona Lisa?”• “¿Quie´n pinto´ la Mona Lisa?”Intuitively, the answer to these questions shouldbe the same and thus independent of the specificlanguage the question is expressed in. Accord-ing to our main hypothesis, we claim that thesequestions could be translated into a normalizedlanguage-independent representation that can beevaluated with respect to semantically structureddata. For example, we could use a formal query inthe SPARQL language to express these questionsin a way that abstracts from the original language:PREFIX rdf: .../22-rdf-syntax-ns#select ?who where {<http://dbpedia.org/.../Mona_Lisa><http://dbpedia.org/.../artist>?who}The strings enclosed in angle brackets representURIs (Uniform Resource Identifiers) that uniquelyidentify a certain entity (Mona Lisa) and a prop-erty (artist). The fact that the label of the prop-erty artist is English should not mislead; the URIrepresents a real-world relation between paintingsand their creators and just happens to be labeledwith an English string for the sake of human read-ability. The existence of such a relation is how-ever independent of a specific language. In anycase, in order to map the above question into a nor-malized and language-independent representation,i.e. the SPARQL query above, we require knowl-edge about the fact that the verb “schilderen” inDutch, “malen” in German, “pintar” in Spanishand “paint” in English all refer to the propertyartist.3 A Lexicon Model for OntologiesGiven the motivations for ontology lexicalisationgiven by the use cases outlined above and the factthat a solution for this seems missing in currentstate of the art research and best practices, we pro-pose a formal model for the proper representationof the continuum between: i) ontology semantics;ii) terminology that is used to convey this in nat-ural language; and iii) linguistic information onthese terms and their constituent lexical units. Asthis model in essence enables the creation of a lex-icon for a given ontology, we call this a lexiconmodel for ontologies.3.1 RequirementsThe requirements for a lexicon model for ontolo-gies address several different goals. In particu-lar, the model should: i) represent linguistic in-formation relative to the semantics given by theontology, thereby avoiding the representation ofunnecessary lexical features that may lead to over-generation of term variants; ii) strict separationof ’world knowledge’ (describing domain objectsthat are referenced by lexical objects) from ’wordknowledge’ (describing lexical objects); iii) en-able easy uptake of the model by providing a sim-ple core model, supplemented with a set of mod-ules that can be used, extended or ignored uponneed.3.2 lemon: lexicon model for ontologiesThe proposed lexicon model for ontologies(’lemon’) is described in detail in the ’lemon cook-book’2. Here we provide a summary of its mostprominent features, starting with the lemon core,which is organized around a core path as follows:• Ontology Entity: URI of an ontology ele-ment to which a Lexical Sense points, pro-viding a possible linguistic realisation forthat Ontology Entity• Lexical Sense: functional object that links aLexical Entry to an Ontology Entity, pro-viding a sense-disambiguated interpretationof that Lexical Entry2http://lexinfo.net/lemon-cookbook.pdf• Lexical Entry: morphosyntactic normalisa-tion of one or more Lexical Form• Lexical Form: morphosyntactic variant of aLexical Entry, including inflection, declina-tion and syntactic variation• Representation: standard written or pho-netic representation for a Lexical FormIn addition, lemon has a number of modules thatallow for further modeling:• The linguistic description module is con-cerned with the use of data categories suchas ISOcat for describing lemon elements.Although lemon itself is a meta-model andtherefore agnostic as regards the specific datacategory set used, specific data categories canbe used in particular instances of the lemonmodel.• The morphology module is concerned withthe analysis and representation of inflectionaland agglutinative morphology. The moduleallows the specification of regular inflectionsof words by use of Perl-like regular expres-sions.• The phrase structure module is concernedwith the modeling of lexical entries that aresyntactically complex, such as phrases andclauses, to enable representation of the syn-tactic structure of such lexical entries.• The syntax and mapping module is con-cerned with a description of lexical ’predi-cates’ (sub-categorisation frames with syn-tactic arguments) and semantic predicates(properties with subject/object) on the ontol-ogy side and the mapping between them.• The variation module is concerned with adescription of the relationships between el-ements of a lemon lexicon: sense relations(e.g. translation) require a semantic context,lexical variations (e.g. plural) require a mor-phosyntactic context, form variations (e.g.homographs) include all other variations.4 ConclusionsIn this paper we presented a motivation for ontol-ogy lexicalisation that builds on use cases, amongothers, in knowledge acquisition from text andmultilingual knowledge access. We argued thatthe representation of a lexical level in ontologies,beyond the semantic and terminological level, isneeded for a proper use of ontologies in applica-tions and also serves in integrating the terminol-ogy level with the ontology level. No previouslyavailable model (e.g. (Gangemi et al.2003), (Far-rar and Langendoen2003), (Reymonet et al.2007))fulfills all the requirements for an ontology lexi-calisation model. We therefore developed a model(lemon) for this purpose, of which we discussedsome of its main features and directions in whichit is currently used. Full details of the modeland details of its use are described in other pa-pers to which we refer the interested reader (Buite-laar et al.2009), (McCrae et al.2011), (McCrae etal.forthcoming).AcknowledgementsThis work is supported in part by the EuropeanUnion under Grant No. 248458 for the Monnetproject as well as by the Science Foundation Ire-land under Grant No. SFI/08/CE/I1380 (Lion2)and the CITEC excellence initiative funded by theEU and the DFG.ReferencesBuitelaar P. (2010) Ontology-based Semantic Lexi-cons: Mapping between Terms and Object De-scriptions In: Chu-Ren Huang, Nicoletta Calzolari,Aldo Gangemi, Alessandro Oltramari, AlessandroLenci, Laurent Prevot (eds.) Ontology and the Lex-icon: A Natural Language Processing PerspectiveCambridge Studies in Natural Language Processing,Cambridge University Press.Buitelaar P., P. Cimiano, P. Haase, M. Sintek(2009) Towards Linguistically Grounded Ontolo-gies Proceedings of the 6th European Semantic WebConference. Lecture Notes in Computer Science,Springer.Farrar S., D. Terence Langendoen (2003) A linguis-tic ontology for the Semantic Web GLOT Interna-tional. 7 (3), pp.97-100.Gangemi A,, R. Navigli, P. Velardi (2003) The On-toWordNet Project: extension and axiomatiza-tion of conceptual relations in WordNet Proceed-ings of ODBASE, Springer.Guarino, N. (1998). Formal Ontology in Informa-tion Systems In: N. Guarino (ed.) Formal Ontologyin Information Systems. Proceedings of FOIS’98,Trento, Italy, 6-8 June 1998. IOS Press, pp.3-15.McCrae J., D. Spohr, P. Cimiano (2011) Linking Lex-ical Resources and Ontologies on the SemanticWeb with Lemon Proceedings of the 8th EuropeanSemantic Web Conference, Lecture Notes in Com-puter Science, Springer, Volume 6643, pp.245-259.McCrae J., G. Aguado-de-Cea, P. Buitelaar, P. Cimi-ano, T. Declerck, A. Gomez-Perez, J. Gracia, L.Hollink, E. Montiel-Ponsoda, D. Spohr, T. Wunner(forthcoming) Interchanging lexical resources onthe SemanticWeb Accepted for publication in Lan-guage Resources and Evaluation, Springer.Reymonet A., J. Thomas, N. Aussenac-Gilles (2007)Modelling ontological and terminological re-sources in OWL-DL Proceedings of the ISWC07workshop From Text to Knowledge: The Lexi-con/Ontology Interface (OntoLex ’07).

A linguistic ontology for the Semantic Web

Aussenac-Gilles

Formal Ontology in Information Systems In:

Ontology-based Semantic Lexicons: Mapping between Terms and Object Descriptions In:

The OntoWordNet Project: extension and axiomatization of conceptual relations

Towards Linguistically Grounded Ontologies

Ontology Lexicalization: The lemon perspective

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Ontology Lexicalization: The lemon perspective

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