Abstract
Recognition and disambiguation of named entities in text is a knowledge-intensive task. Systems are typically bound by the resources and coverage of a single target knowledge base (KB). In place of a fixed knowledge base, we attempt to infer a set of endpoints which reliably disambiguate entity mentions on the web. We propose a method for discovering web KBs and our preliminary results suggest that web KBs allow linking to entities that can be found on the web, but may not merit a major KB entry.
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CITATION STYLE
Chisholm, A., Radford, W., & Hachey, B. (2016). Discovering entity knowledge bases on the web. In Proceedings of the 5th Workshop on Automated Knowledge Base Construction, AKBC 2016 at the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2016 (pp. 7–11). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w16-1302
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