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

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

doi:10.1145/1739041.1739130

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

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

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

79 Citations (Scopus)

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.

Original language	English
Title of host publication	Advances in Database Technology - EDBT 2010 - 13th International Conference on Extending Database Technology, Proceedings
Pages	697-700
Number of pages	4
DOIs	https://doi.org/10.1145/1739041.1739130
Publication status	Published - 2010
Externally published	Yes
Event	Extending Database Technology 2010 - Lausanne, Switzerland Duration: 22 Mar 2010 → 26 Mar 2010 Conference number: 13th

Conference

Conference	Extending Database Technology 2010
Abbreviated title	EDBT 2010
Country/Territory	Switzerland
City	Lausanne
Period	22/03/10 → 26/03/10

Keywords

Knowledge harvesting
Knowledge management
Ontology
Temporal fact extraction
Temporal queries
Wikipedia

Access to Document

10.1145/1739041.1739130

Cite this

@inproceedings{265d77e38a4940198cd3744d1cc5952d,

title = "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.",

keywords = "Knowledge harvesting, Knowledge management, Ontology, Temporal fact extraction, Temporal queries, Wikipedia",

author = "Yafang Wang and Mingjie Zhu and Lizhen Qu and Marc Spaniol and Gerhard Weikum",

year = "2010",

doi = "10.1145/1739041.1739130",

language = "English",

isbn = "9781605589459",

pages = "697--700",

booktitle = "Advances in Database Technology - EDBT 2010 - 13th International Conference on Extending Database Technology, Proceedings",

note = "Extending Database Technology 2010, EDBT 2010 ; Conference date: 22-03-2010 Through 26-03-2010",

}

Wang, Y, Zhu, M, Qu, L, Spaniol, M & Weikum, G 2010, Timely YAGO: harvesting, querying, and visualizing temporal knowledge from Wikipedia. in Advances in Database Technology - EDBT 2010 - 13th International Conference on Extending Database Technology, Proceedings. pp. 697-700, Extending Database Technology 2010, Lausanne, Switzerland, 22/03/10. https://doi.org/10.1145/1739041.1739130

Timely YAGO: harvesting, querying, and visualizing temporal knowledge from Wikipedia. / Wang, Yafang; Zhu, Mingjie; Qu, Lizhen et al.
Advances in Database Technology - EDBT 2010 - 13th International Conference on Extending Database Technology, Proceedings. 2010. p. 697-700.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

T1 - Timely YAGO

T2 - Extending Database Technology 2010

AU - Wang, Yafang

AU - Zhu, Mingjie

AU - Qu, Lizhen

AU - Spaniol, Marc

AU - Weikum, Gerhard

N1 - Conference code: 13th

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

KW - Knowledge harvesting

KW - Knowledge management

KW - Ontology

KW - Temporal fact extraction

KW - Temporal queries

KW - Wikipedia

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DO - 10.1145/1739041.1739130

M3 - Conference Paper

AN - SCOPUS:77952262853

SN - 9781605589459

SP - 697

EP - 700

BT - Advances in Database Technology - EDBT 2010 - 13th International Conference on Extending Database Technology, Proceedings

Y2 - 22 March 2010 through 26 March 2010

ER -

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

Abstract

Conference

Keywords

Access to Document

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