load_wn18rr

ampligraph.datasets.datasets.load_wn18rr(check_md5hash=False, clean_unseen=True, add_reciprocal_rels=False)

Load the WN18RR dataset.

The dataset is described in [DMSR18].

Warning

WN18RR’s validation set contains 198 unseen entities over 210 triples. The test set has 209 unseen entities, distributed over 210 triples.

The WN18RR dataset is loaded from file if it exists at the AMPLIGRAPH_DATA_HOME location. If AMPLIGRAPH_DATA_HOME is not set, the default ~/ampligraph_datasets is checked. If the dataset is not found at either location, it is downloaded and placed in AMPLIGRAPH_DATA_HOME or ~/ampligraph_datasets.

This dataset is divided in three splits:

  • train: 86,835 triples

  • valid: 3,034 triples

  • test: 3,134 triples

Dataset

Train

Valid

Test

Entities

Relations

WN18RR

86,835

3,034

3,134

40,943

11
Parameters:

  • clean_unseen (bool) – If True, filters triples in validation and test sets that include entities not present in the training set.

  • check_md5hash (bool) – If True check the md5hash of the datset files (default: False).

  • add_reciprocal_rels (bool) – Flag which specifies whether to add reciprocal relations. For every <s, p, o> in the dataset this creates a corresponding triple with reciprocal relation <o, p_reciprocal, s> (default: False).

Returns:

splits – The dataset splits: {‘train’: train, ‘valid’: valid, ‘test’: test}. Each split is a ndarray of shape (n, 3).

Return type:

dict

Example

>>> from ampligraph.datasets import load_wn18rr
>>> X = load_wn18rr()
>>> X["valid"][0]
array(['02174461', '_hypernym', '02176268'], dtype=object)