Creating subsets of Wikidata
10-30, 20:00–20:10 (UTC), Room 1

In many use cases, projects want to reuse a subset of Wikidata focused on project-specific topics, combining the Wikidata data with project-specific data. Extracting a subgraph of Wikidata is difficult because Wikidata is very large, and it is difficult to specify what to keep and what to discard. This talk presents Knowledge Graph Toolkit (KGTK,, a toolkit that can process the full Wikidata on a laptop, and provides a rich suite of commands for query and path following that can be used to flexibly extract topic specific subgraphs.

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What will the participants take away from this session?

Participants will learn about KGTK, a sophisticated toolkit that provides commands to query Wikidata, perform network analytics and create graph embeddings. KGTK is scalable and efficient: KGTK queries run many times faster on a laptop than equivalent queries on SPARQL running on a large server. Participants will get a preview of how KGTK can be used to create topic-oriented subgraphs of Wikidata.





Dr. Pedro Szekely is a Principal Scientist and Director of the AI division at the USC Information Sciences Institute (ISI. His research focuses on table understanding, knowledge graphs and applications of knowledge graphs. He teaches a graduate course at USC on Building Knowledge Graphs, and has given tutorials on knowledge graph construction at KDD, ISWC, AAAI and WWW.