Datasets › OLPBENCH
OLPBENCH
OLPBENCH is a large Open Link Prediction benchmark, which was derived from the state-of-the-art Open Information Extraction corpus OPIEC (Gashteovski et al., 2019). OLPBENCH contains 30M open triples, 1M distinct open relations and 2.5M distinct mentions of approximately 800K entities.
Open Link Prediction is defined as follows: Given an Open Knowledge Graph and a question consisting of an entity mention and an open relation, predict mentions as answers. A predicted mention is correct if it is a mention of the correct answer entity. For example, given the question (“NBC-TV”, “has office in”, ?), correct answers include “NYC” and “New York”.
Source: OLPBENCH
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 4 papers for it but never published that list.
Dataset loaders archive 2025-07-28
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Tasks archive 2025-07-28
License archive 2025-07-28
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Modalities archive 2025-07-28
Languages archive 2025-07-28
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Variants archive 2025-07-28
- OLPBENCH
1 variant name, as the archive lists them.
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