ML Anthology

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

Dawid Wisniewski, Jedrzej Potoniec, Agnieszka Lawrynowicz
AAAI 2022 pp. 13079-13080
doi:10.1609/AAAI.V36I11.21676 /aaai/2022/wisniewski2022aaai-bigcq/

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.

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Cite

Text

Wisniewski et al. "BigCQ: Generating a Synthetic Set of Competency Questions Formalized into SPARQL-OWL (Student Abstract)." AAAI Conference on Artificial Intelligence, 2022. doi:10.1609/AAAI.V36I11.21676

Markdown

[Wisniewski et al. "BigCQ: Generating a Synthetic Set of Competency Questions Formalized into SPARQL-OWL (Student Abstract)." AAAI Conference on Artificial Intelligence, 2022.](https://mlanthology.org/aaai/2022/wisniewski2022aaai-bigcq/) doi:10.1609/AAAI.V36I11.21676

BibTeX

@inproceedings{wisniewski2022aaai-bigcq,
  title     = {{BigCQ: Generating a Synthetic Set of Competency Questions Formalized into SPARQL-OWL (Student Abstract)}},
  author    = {Wisniewski, Dawid and Potoniec, Jedrzej and Lawrynowicz, Agnieszka},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2022},
  pages     = {13079-13080},
  doi       = {10.1609/AAAI.V36I11.21676},
  url       = {https://mlanthology.org/aaai/2022/wisniewski2022aaai-bigcq/}
}