Datasets › COPEN
COPEN (COnceptual knowledge Probing bENchmark)
COPEN is a COnceptual knowledge Probing benchmark that aims to analyze the conceptual understanding capabilities of Pre-trained Language Models (PLMs). Specifically, COPEN consists of three tasks:
- Conceptual Similarity Judgment (CSJ). Given a query entity and several candidate entities, the CSJ task requires selecting the most conceptually similar candidate entity to the query entity.
- Conceptual Property Judgment (CPJ). Given a statement describing a property of a concept, PLMs need to judge whether the statement is true.
- Conceptualization in Contexts (CiC). Given a sentence, an entity mentioned in the sentence, and several concept chains of the entity, PLMs need to select the most appropriate concept according to the context of the entity.
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 3 papers for it but never published that list.
Dataset loaders archive 2025-07-28
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Tasks archive 2025-07-28
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License archive 2025-07-28
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Modalities archive 2025-07-28
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Languages archive 2025-07-28
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Variants archive 2025-07-28
- COPEN
1 variant name, as the archive lists them.
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