Zhe Zuo, Gjergji Kasneci, Toni Gruetze, and Felix Naumann

CoNLL-YAGO: The subset of the CoNLL-YAGO dataset that we used in the experiments contains 76 articles that were carefully manually (re-)annotated by our team members.

CUCERZAN: This dataset consists of 350 Wikipedia articles that were randomly selected by Silviu Cucerzan [1].  The original annotations can be found here. Since some of the original Wikipedia articles are missing, we have recovered 339 out of 350 articles. In this version of the articles, the mentions were annotated with entities from YAGO instead of the original Wikipedia pages. 

KORE: This dataset contains 50 short hand-crafted articles including highly ambiguous mentions of named entities. It was produced in the realm of the AIDA project [3], which is available here.  

[1] S. Cucerzan. Large-scale named entity disambiguation based on Wikipedia data. In Proceedings of the Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), pages 708–716, 2007.

[2] J. Hoffart, M. A. Yosef, I. Bordino, H. Fürstenau, M. Pinkal, M. Spaniol, B. Taneva, S. Thater, and G. Weikum. Robust disambiguation of named entities in text. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 782–792, 2011.

[3] J. Hoffart, S. Seufert, D. B. Nguyen, M. Theobald, and G. Weikum. KORE: keyphrase overlap relatedness for entity disambiguation. In Proceedings of the International Conference on Information and Knowledge Management (CIKM), pages 545–554, 2012.