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Timely YAGO: harvesting, querying, and visualizing temporal knowledge from Wikipedia
Abstract
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.
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A few recent works have explored temporal information for the automatic development of temporal knowledge bases.
“A few recent works [Wang et al. 2010, Hoffart et al. 2011, Wang et al. 2011, Wang et al. 2012, Talukdar et al. 2012, and Kuzey and Weikum 2012] have explored such temporal information for the automatic development of temporal knowledge bases.”
From Survey of Temporal Information Retrieval and Related Applications (2015) · cites this paper as Wang et al. 2010
T-YAGO uses regular expressions to extract temporal facts from semi-structured data attached to Wikipedia articles, such as infoboxes.
“T-YAGO uses regular expressions to extract temporal facts from semi-structured data attached to Wikipedia articles, such as infoboxes.”
From Survey of Temporal Information Retrieval and Related Applications (2015) · cites this paper as Wang et al. 2010
Wang et al. 2010 developed the T-YAGO knowledge base, which is an extension of YAGO.
“One of the first works addressing this problem was developed by [Wang et al. 2010] with the T-YAGO knowledge base, which is an extension of YAGO [Suchanek et al. 2007].”
From Survey of Temporal Information Retrieval and Related Applications (2015) · cites this paper as Wang et al. 2010
Citations
Cites
No references could be resolved yet.
Research works printed but not linked: 12
- D. Ahn , S. F. Adafre and M. d. Rijke. Towards Task-Based Temporal Extraction and Recognition. In Proceedings of the Dagstuhl Seminar. 2005 . D. Ahn, S. F. Adafre and M. d. Rijke. Towards Task-Based Temporal Extraction and Recognition. In Proceedings of the Dagstuhl Seminar. 2005.
- D. Ahn , J. V. Rantwijk and M. d. Rijke . A Cascaded Machine Learning Approach to Interpreting Temporal Expressions . In Proceedings NAACL-HLT 2007 . D. Ahn, J. V. Rantwijk and M. d. Rijke. A Cascaded Machine Learning Approach to Interpreting Temporal Expressions. In Proceedings NAACL-HLT 2007.
- 10.1145/1328964.1328968 · DOI
- S. Auer , C. Bizer , G. Kobilarov , J. Lehmann , R. Cyganiak and Z. Ives . DBpedia: A nucleus for a Web of open data ., In Proceedings of the Sixth International Semantic Web Conference (Pusan, Korea, Nov. 11--15) . Springer , Berlin/ Heidelberg , 2007 . S. Auer, C. Bizer, G. Kobilarov, J. Lehmann, R. Cyganiak and Z. Ives. DBpedia: A nucleus for a Web of open data., In Proceedings of the Sixth International Semantic Web Conference (Pusan, Korea, Nov. 11--15). Springer, Berlin/Heidelberg, 2007.
- M. Banko , M. Cafarella , S. Soderland , M. Broadhead , O. Etzioni : Open Information Extraction from the Web . IJCAI 2007 . M. Banko, M. Cafarella, S. Soderland, M. Broadhead, O. Etzioni: Open Information Extraction from the Web. IJCAI 2007.
- 10.1145/988672.988687 · DOI
- O. Koomiyets , M. Moeans . Meeting TempEval-2: Shallow Approach for Temporal Tagger. In Proceedings of the NAACL HLT Workshop on Semantic Evaluations: Recent Achievements and Future Directions , pages 52 -- 57 , Boulder, Colorado , June 2009 . O. Koomiyets, M. Moeans. Meeting TempEval-2: Shallow Approach for Temporal Tagger. In Proceedings of the NAACL HLT Workshop on Semantic Evaluations: Recent Achievements and Future Directions, pages 52--57, Boulder, Colorado, June 2009.
- 10.5555/1621474.1621520 · DOI
- J. Pustejovsky , J. Castano , R. Ingria and R. Sauri . TimeML: Robust Specification of Event and Temporal Expressions in Text . In Proceedings of the 5th International Workshop on Computational Semantics. 2003 . J. Pustejovsky, J. Castano, R. Ingria and R. Sauri. TimeML: Robust Specification of Event and Temporal Expressions in Text. In Proceedings of the 5th International Workshop on Computational Semantics. 2003.
- 10.1145/1242572.1242667 · DOI · Paper page
- 10.1145/1321440.1321449 · DOI
- Q. Zhang , F. M. Suchanek , L. Yue , and G. Weikum . TOB: Timely ontologies for business relations . In Proceedings of the International Workshop on the Web and Databases (WebDB) , 2008 . Q. Zhang, F. M. Suchanek, L. Yue, and G. Weikum. TOB: Timely ontologies for business relations. In Proceedings of the International Workshop on the Web and Databases (WebDB), 2008.
Cited by
Sorted by citations
Survey of Temporal Information Retrieval and Related Applications
Campos, R., Dias, G., Jorge, A. M., & Jatowt, A. (2015) · ACM Computing Surveys · doi:10.1145/2619088 · Cited by 262
Metadata
- Authors
- Wang, Y., Zhu, M., Qu, L., Spaniol, M., & Weikum, G.
- Affiliations
- Max-Planck-Institut für Informatik, Saarbrücken, Germany
- Venue
- Proceedings of the 13th International Conference on Extending Database Technology
- Publisher
- ACM
- Published
- 2010-03-22
- Pages
- 697-700
- Cited by
- 54
- References
- 0
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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