A Methodological Framework for Ontology and Multilingual Termontological Database Co-evolution
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Transcript of A Methodological Framework for Ontology and Multilingual Termontological Database Co-evolution
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A METHODOLOGICAL FRAMEWORK FOR ONTOLOGY
AND MULTILINGUAL TERMONTOLOGICAL DATABASE
CO-EVOLUTION
CHRISTOPHE DEBRUYNE
CRISTIAN VÁSQUEZ
KOEN KERREMANS
ANDRÉS DOMÍNGUEZ BURGOS
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INTRODUCTION
Ontologies. Computer-based, shared, agreed, formal conceptualizations for – amongst others – semantic interoperability between autonomously developed and maintained information systems.
Multilingual Terminology Bases (MTBs) are language resources that contain - in several languages - terms (including variants) referring to concepts in specialized domains. Several other types of information can be added to MTBs in order to describe specific properties of a term, its meaning or its use in specific communicative contexts.
Ontologies are meant for a specific purpose whereas MTBs are more general purpose
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PROBLEM
Ontologies and MTBs have different purposes. How and what are the benefits of combining these two artifacts and their methods of construction?
At two levels
• Level of the respective artifacts• Level of the construction methods
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METHOD: ONTOLOGY ENGINEERING
Hybrid Ontology Engineering
• Method Grounding Ontologies in Social Processes and Natural Language (GOSPL)
• Community grounded agreements on formal and informal concept descriptions
• Formal descriptions by means of fact-orientation• Informal descriptions by means of an artifact called glossary
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METHOD: TERMINOLOGY ENGINEERING
Multilingual Termontological Database
• MTB in which some ontological relations are made explicit• Hierarchical relationships as well as non-hierarchical (*)
• Method Termontography• Explicitly distinguishes the linguistic level from the
semantic level
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METHOD: HYBRID ONTOLOGY & MTB CO-EVOLUTION
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METHOD: HYBRID ONTOLOGY & MTB CO-EVOLUTION
From MTB to Hybrid Ontology
• Retrieval of generic “pre-fact types” • Retrieval of informal descriptions
From Hybrid Ontology to MTB
• Social interactions lead the mining process• Alignment with the hybrid ontology enables natural
language querying• Structuring the query with NLP, generating a first structure
then annotated with the ontology
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TOOL
First, eating our own dog food: creation of an MTB (termontography) ontology
Annotation of the MTB to expose data as RDF
• Creation of a SPARQL endpoint
Connection GOSPL Tool with endpoint
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TOOL
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USE CASE
Used in the context of the cultural domain
• Retrieval of information on cultural events in Brussels• Three languages: NL, FR, EN
• Motivation of Multilingual Termontological Databases
• Different data sources motivate the need of Ω
• Application
• Natural language querying. Query is first parsed to a structure, and alignment with Ω facilitates the translation of that structure into query
• Multilingual interfaces• User comprehension of the results
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CONCLUSIONS
Conclusions
• Ontologies and MTBs are two different artifacts, with distinct construction processes
• We examined how these two processes and artifacts can be combined and presented a proposal
• Ideas were implemented in a tool, which will be part of a greater set up
• Used the tool in the context of a project in the cultural domain.
Future work
• Implementation and integration of the natural language query interface
• More testing and user evaluation
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THANK YOU!
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