# -*- coding: utf-8 -*-
"""The Wikidata5m dataset from [wang2019]_.
Wikidata5m is a million-scale knowledge graph dataset with aligned corpus.
This dataset integrates the Wikidata knowledge graph and Wikipedia pages.
Each entity in Wikidata5m is described by a corresponding Wikipedia page,
which enables the evaluation of link prediction over unseen entities.
- Website: https://deepgraphlearning.github.io/project/wikidata5m
- Paper: https://arxiv.org/pdf/1911.06136.pdf
Get a summary with ``python -m pykeen.datasets.wikidata5m``,
"""
import pathlib
from docdata import parse_docdata
from .base import TarFileRemoteDataset
__all__ = [
"Wikidata5M",
]
TRANSDUCTIVE_URL = "https://zenodo.org/record/5546383/files/wikidata5m_transductive.tar.gz"
INDUCTIVE_URL = "https://zenodo.org/record/5546387/files/wikidata5m_inductive.tar.gz"
[docs]@parse_docdata
class Wikidata5M(TarFileRemoteDataset):
"""The Wikidata5M dataset from [wang2019]_.
---
name: Wikidata5M
statistics:
entities: 4594149
relations: 822
training: 20614279
testing: 4977
validation: 4983
triples: 20624239
citation:
author: Wang
year: 2019
arxiv: 1911.06136
link: https://arxiv.org/abs/1911.06136
"""
def __init__(self, **kwargs):
"""Initialize the Wikidata5M dataset.
:param kwargs: keyword arguments passed to :class:`pykeen.datasets.base.TarFileRemoteDataset`.
"""
super().__init__(
url=TRANSDUCTIVE_URL,
relative_training_path=pathlib.PurePath("wikidata5m_transductive_train.txt"),
relative_testing_path=pathlib.PurePath("wikidata5m_transductive_test.txt"),
relative_validation_path=pathlib.PurePath("wikidata5m_transductive_valid.txt"),
**kwargs,
)
if __name__ == "__main__":
Wikidata5M.cli()