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@@ -20,17 +20,16 @@ pretty_name: relbert/t_rex
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  This is the T-REX dataset proposed in [https://aclanthology.org/L18-1544/](https://aclanthology.org/L18-1544/).
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  The test split is universal across different version, which is manually checked by the author of [relbert/t_rex](https://huggingface.co/datasets/relbert/t_rex),
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  and the test split contains predicates that is not included in the train/validation split.
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- The train/validation splits are created for each configuration by the ratio of 9:1.
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  The number of triples in each split is summarized in the table below.
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  ***Note:*** To make it consistent with other datasets ([nell](https://huggingface.co/datasets/relbert/nell) and [conceptnet](https://huggingface.co/datasets/relbert/conceptnet)), we rename predicate/subject/object as relation/head/tail.
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- - Number of instances (`filter_unified.min_entity_4_max_predicate_10`)
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  | | train | validation | test |
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  |:--------------------------------|--------:|-------------:|-------:|
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- | number of triples | 33812 | 8454 | 122 |
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- | number of unique relation types (predicate) | 169 | 135 | 34 |
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  ### Filtering to Remove Noise
 
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  This is the T-REX dataset proposed in [https://aclanthology.org/L18-1544/](https://aclanthology.org/L18-1544/).
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  The test split is universal across different version, which is manually checked by the author of [relbert/t_rex](https://huggingface.co/datasets/relbert/t_rex),
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  and the test split contains predicates that is not included in the train/validation split.
 
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  The number of triples in each split is summarized in the table below.
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  ***Note:*** To make it consistent with other datasets ([nell](https://huggingface.co/datasets/relbert/nell) and [conceptnet](https://huggingface.co/datasets/relbert/conceptnet)), we rename predicate/subject/object as relation/head/tail.
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+ - Number of instances
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  | | train | validation | test |
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  |:--------------------------------|--------:|-------------:|-------:|
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+ | number of triples | 1,274,264 | 318,566 | 122 |
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+ | number of unique relation types (predicate) | 759 | 676 | 34 |
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  ### Filtering to Remove Noise