Timely YAGO: harvesting, querying, and visualizing temporal knowledge from Wikipedia

Yafang Wang, Mingjie Zhu, Lizhen Qu, Marc Spaniol, Gerhard Weikum

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77 Citations (Scopus)


Recent progress in information extraction has shown how to automatically build large ontologies from high-quality sources like Wikipedia. But knowledge evolves over time; facts have associated validity intervals. Therefore, ontologies should include time as a first-class dimension. In this paper, we introduce Timely YAGO, which extends our previously built knowledge base YAGO with temporal aspects. This prototype system extracts temporal facts from Wikipedia infoboxes, categories, and lists in articles, and integrates these into the Timely YAGO knowledge base. We also support querying temporal facts, by temporal predicates in a SPARQL-style language. Visualization of query results is provided in order to better understand of the dynamic nature of knowledge.

Original languageEnglish
Title of host publicationAdvances in Database Technology - EDBT 2010 - 13th International Conference on Extending Database Technology, Proceedings
Number of pages4
Publication statusPublished - 2010
Externally publishedYes
EventExtending Database Technology 2010 - Lausanne, Switzerland
Duration: 22 Mar 201026 Mar 2010
Conference number: 13th


ConferenceExtending Database Technology 2010
Abbreviated titleEDBT 2010


  • Knowledge harvesting
  • Knowledge management
  • Ontology
  • Temporal fact extraction
  • Temporal queries
  • Wikipedia

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