---
title: "YAGO2: A Spatially and Temporally Enhanced Knowledge Base from Wikipedia: Extended Abstract"
authors:
  - "Johannes Hoffart"
  - "Fabian M. Suchanek"
  - "Klaus Berberich"
  - "Gerhard Weikum"
doi: ""
url: "https://ijcai.org/proceedings/2013/478"
pdf: "https://ijcai.org/proceedings/2013/0478.pdf"
venue: "Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence"
year: 2013
pages: "3161-3164"
track: ""
keywords:
---

# YAGO2: A Spatially and Temporally Enhanced Knowledge Base from Wikipedia: Extended Abstract

Johannes Hoffart, Fabian M. Suchanek, Klaus Berberich, Gerhard Weikum

*Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence*, pages 3161-3164.

## Abstract

We present YAGO2, an extension of the YAGO knowledge base, in which entities, facts, and events are anchored in both time and space. YAGO2 is built automatically from Wikipedia, GeoNames, and WordNet. It contains 447 million facts about 9.8 million entities. Human evaluation confirmed an accuracy of 95% of the facts in YAGO2. In this paper, we present the extraction methodology and the integration of the spatio-temporal dimension.