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.

The dataset is distributed as a knowledge graph, a corpus, and aliases. We provide both transductive and inductive data splits used in the original paper.

Setting   #Entity #Relation #Triplet
Transductive Train 4,594,485 822 20,614,279
  Valid 4,594,485 822 5,163
  Test 4,594,485 822 5,133
Inductive Train 4,579,609 822 20,496,514
  Valid 7,374 199 6,699
  Test 7,475 201 6,894


For raw knowledge graph, it may also contain entities that do not have corresponding Wikipedia pages.


Wikidata5m follows the identifier system used in Wikidata. Each entity and relation is identified by a unique ID. Entities are prefixed by Q, while relations are prefixed by P.

Knowledge Graph

The knowledge graph is stored in the triplet list format. For example, the following line corresponds to <Donald Trump, position held, President of the United States>.

Q22686	P39	Q11696


Each line in the corpus is a document, indexed by entity ID. The following line shows the description for Donald Trump.

Q22686	Donald John Trump (born June 14, 1946) is the 45th and current president of the United States ...


Each line lists the alias for an entity or relation. The following line shows the aliases of Donald Trump.

Q22686  donnie trump	45th president of the united states     Donald John Trump ...