Toward Linguistically Grounded Ontologies by Paul Buitelaar, Philipp Cimiano, Peter Haase, and Michael Sintek (Ireland, Netherlands, Germany) presented.

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Presentation transcript:

Toward Linguistically Grounded Ontologies by Paul Buitelaar, Philipp Cimiano, Peter Haase, and Michael Sintek (Ireland, Netherlands, Germany) presented by Thomas Packer 1Toward Linguistically Grounded Ontologies

Recent Research The 6th Annual European Semantic Web Conference (ESWC2009) 31 May - 4 June 2009, Heraklion, Greece 2Toward Linguistically Grounded Ontologies

Ontologies and Language Are ontologies and language related? Should an ontology contain language information? 3Toward Linguistically Grounded Ontologies

Grounding in Natural Language is Needed Human-readable ontologies (e.g. labels). Ontology-based information extraction (parsing). Ontology-based natural language generation. Interlingua-based machine translation. 4Toward Linguistically Grounded Ontologies

Separation between Linguistics and Semantics is Needed There are ontological distinctions that are never lexicalized. There are linguistic distinctions that are ontologically irrelevant. 5Toward Linguistically Grounded Ontologies

Concept-Label Relations RDFS/OWL specifies “n : m” relation between classes and labels. Paradigmatic Relations: – Relations between words according to meaning. – E.g. between synonyms: “cat” and “Katze”. Syntagmatic Relations: – Relations between words in a sentence in sequence. – E.g. between “sleeping cat”. 6Toward Linguistically Grounded Ontologies

Syntagmatic Composition: Models of Schweineschnitzel (pork cutlet) Tie classes to parts of words or whole words. Make a class: Schweineschnitzel Make a composite class: Make only a general class: schnitzel Make two separate classes: schnitzel, pork 7Toward Linguistically Grounded Ontologies

Needed Linguistic Information capital Generate the triple: (Germany, capital, Berlin) “Germany capitals Berlin.” Need POS and inflectional information to do this right. 8Toward Linguistically Grounded Ontologies

Needed Linguistic Information located at/rdfs:label> “The A8 passes by Karlsruhe”, “The A8 connects Karlsruhe”, “The A8 goes through Karlsruhe”. One label can’t handle expressing or extraction all possibilities. Wouldn’t want to label a relation with all possibilities. Subject and object information: order matters. 9Toward Linguistically Grounded Ontologies

Solution: LexInfo 1.Morphological Relations 2.Syntagmatic Decomposition 3.Complex Linguistic Patterns 4.Specify Meaning with Ontology 5.Separate Linguistics and Semantics 10Toward Linguistically Grounded Ontologies

LexInfo Pedigree LingInfo (Internal Structure) LexInfo LexOnto (External Structure) Lexical Markup Framework (LMF) (computational lexicon meta-model) 11Toward Linguistically Grounded Ontologies

1. Morphological Relations Capture morphological relations between terms e.g., through inflection – cat, cats – Schwein, Schweine, Schweins Separate from the domain ontology 12Toward Linguistically Grounded Ontologies

2. Syntagmatic Decomposition Represent the morphological or syntactic decomposition of composite terms Link components to the ontology Schweineschnitzel composed of two LexicalEntry objects: class pork and class cutlet. 13Toward Linguistically Grounded Ontologies

3. Complex Linguistic Patterns Map linguistic patterns to arbitrary ontological structures. Subcategorization frames for specific verbs Intransitive verb “flow”: – Maps to “flowsThrough” predicate. – Subject maps to predicate domain. – Prepositional object maps to predicate range. 14Toward Linguistically Grounded Ontologies

4. Specify Meaning with Ontology Specify the meaning of linguistic constructions with respect to an arbitrary (domain) ontology. (Follows from 3.) 15Toward Linguistically Grounded Ontologies

5. Separate Linguistics and Semantics Clearly separate the linguistic and semantic (ontological) representation levels. (Exemplified above.) 16Toward Linguistically Grounded Ontologies

Conclusion Good – The gap between knowledge research and language research is narrowing. Bad – No evaluation. – No probabilities. Future Work – Can efficient parsers/extractors be based on this? 17Toward Linguistically Grounded Ontologies

Questions 18Toward Linguistically Grounded Ontologies

Current Standards RDFL/OWL allow labels on ontology elements. cat cats Katze Katzen Is this enough? What more could you want? 19Toward Linguistically Grounded Ontologies