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        <title>CONTOR: Benchmarking Strategies for Completing Ontologies with Plausible Missing Rules</title>
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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.</abstract>
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%0 Conference Proceedings
%T CONTOR: Benchmarking Strategies for Completing Ontologies with Plausible Missing Rules
%A Li, Na
%A Bailleux, Thomas
%A Bouraoui, Zied
%A Schockaert, Steven
%Y Al-Onaizan, Yaser
%Y Bansal, Mohit
%Y Chen, Yun-Nung
%S Findings of the Association for Computational Linguistics: EMNLP 2024
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F li-etal-2024-contor
%X 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.
%U https://aclanthology.org/2024.findings-emnlp.488
%P 8316-8334

Markdown (Informal)

[CONTOR: Benchmarking Strategies for Completing Ontologies with Plausible Missing Rules](https://aclanthology.org/2024.findings-emnlp.488) (Li et al., Findings 2024)

• CONTOR: Benchmarking Strategies for Completing Ontologies with Plausible Missing Rules (Li et al., Findings 2024)

ACL

• Na Li, Thomas Bailleux, Zied Bouraoui, and Steven Schockaert. 2024. CONTOR: Benchmarking Strategies for Completing Ontologies with Plausible Missing Rules. In Findings of the Association for Computational Linguistics: EMNLP 2024, pages 8316–8334, Miami, Florida, USA. Association for Computational Linguistics.