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BigCQ: Generating a Synthetic Set of Competency Questions Formalized into SPARQL-OWL (Student Abstract)

Authors

Dawid Wiśniewski

Faculty of Computing and Telecommunications, Poznan University of Technology, Piotrowo 3A, Poznan, Poland 60-965


Jędrzej Potoniec

Faculty of Computing and Telecommunications, Poznan University of Technology, Piotrowo 3A, Poznan, Poland 60-965 CAMIL Center for Artificial Intelligence and Machine Learning, Piotrowo 3A, Poznan, Poland 60-965


Agnieszka Ławrynowicz

Faculty of Computing and Telecommunications, Poznan University of Technology, Piotrowo 3A, Poznan, Poland 60-965 CAMIL Center for Artificial Intelligence and Machine Learning, Piotrowo 3A, Poznan, Poland 60-965


Proceedings:

No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations

Volume

Issue:

Proceedings of the AAAI Conference on Artificial Intelligence, 36

Track:

AAAI Student Abstract and Poster Program

Downloads:

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Abstract:

We present a method for constructing synthetic datasets of Competency Questions translated into SPARQL-OWL queries. This method is used to generate BigCQ, the largest set of CQ patterns and SPARQL-OWL templates that can provide translation examples to automate assessing the completeness and correctness of ontologies.

DOI:

10.1609/aaai.v36i11.21676


AAAI

Proceedings of the AAAI Conference on Artificial Intelligence, 36