Unlocking Medical Ontologies for Non-Ontology Experts

S F Liang, D Scott, R Stevens, A Rector

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    Ontology authoring is a specialised task requiring amongst other things a deep knowledge of the ontology language being used. Understanding and reusing ontologies can thus be difficult for domain experts, who tend not to be ontology experts. To address this problem, we have developed a Natural Language Generation system for transforming the axioms that form the definitions of ontology classes into Natural Language paragraphs. Our method relies on deploying ontology axioms into a top-level Rhetorical Structure Theory schema. Axioms are ordered and structured with specific rhetorical relations under rhetorical structure trees. We describe here an implementation that focuses on a sub-module of SNOMED CT. With some refinements on articles and layout, the resulting paragraphs are fluent and coherent, offering a way for subject specialists to understand an ontology's content without need to understand its logical representation.
    Original languageEnglish
    Title of host publicationProceedings of the 2011 Workshop on Biomedical Natural Language Processing, BioNLP'11
    PublisherAssociation for Computational Linguistics
    Pages174-181
    Number of pages8
    ISBN (Print)978-1-932432-91-6
    Publication statusPublished - 2011

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