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CONTOR: Benchmarking strategies for completing ontologies with plausible missing rules

Na, Li, Bailleux, Thomas, Bouraoui, Zied and Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881 2024. CONTOR: Benchmarking strategies for completing ontologies with plausible missing rules. Presented at: Findings of EMNLP, Miami, Florida, 12-16 November 2024. Published in: Al-Onaizan, Yaser, Bansal, Mohit and Chen, Yun-Nung eds. Findings of the Association for Computational Linguistics: EMNLP 2024. Association for Computational Linguistics, pp. 8316-8334. 10.18653/v1/2024.findings-emnlp.488

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Abstract

We consider the problem of finding plausible rules that are missing from a given ontology. A number of strategies for this problem have already been considered in the literature. Little is known about the relative performance of these strategies, however, as they have thus far been evaluated on different ontologies. Moreover, existing evaluations have focused on distinguishing held-out ontology rules from randomly corrupted ones, which often makes the task unrealistically easy and leads to the presence of incorrectly labelled negative examples. To address these concerns, we introduce a benchmark with manually annotated hard negatives and use this benchmark to evaluate ontology completion models. In addition to previously proposed models, we test the effectiveness of several approaches that have not yet been considered for this task, including LLMs and simple but effective hybrid strategies.

Item Type: Conference or Workshop Item - published (Paper)
Date Type: Published Online
Status: Published
Schools: Schools > Computer Science & Informatics
Publisher: Association for Computational Linguistics
Date of First Compliant Deposit: 25 October 2024
Date of Acceptance: 20 September 2024
Last Modified: 26 Mar 2026 16:27
URI: https://orca.cardiff.ac.uk/id/eprint/173139

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