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From Simplified Text to Knowledge Representation using Controlled Natural Language

Publication Type: 
Refereed Conference Meeting Proceeding
Knowledge based systems provide means to store data and perform reasoning on top of it. Thus numerous knowledge bases were built using Controlled Natural Language (CNL) which is considered as an engineered subset of natural language. CNLs aim to abstract the complexity level of natural languages and reduce/abolish the characterizing ambiguity of these languages. Two major types of CNLs exist. The one aiming to improve human-human communication is called Simplified Language or human CNL. The second type is a machine-readable CNL, which is a formal language used mainly as an Abstract Knowledge Representation (AKR) Language. In this paper, we present an approach to translating the Medline summaries of diseases presented in a Simplified English to a machine readable CNL Knowledge Base. This approach will result in a formal Knowledge Base enabling machine processing, querying and reasoning all with avoiding the usual main obstacle which is natural language ambiguity. This approach will provide an attractive alternative to non-expert users to read and query over the knowledge base easily. We tested the approach on a sample corpus of the Anemia disease and presented the concluded hypothesis.
Conference Name: 
International Conference on Intelligent Text Processing and Computational Linguistics
18th International Conference on Intelligent Text Processing and Computational Linguistics (CICLING 2017)
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Research Group: 
National University of Ireland, Galway (NUIG)
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