NECKAr: A Named Entity Classifier for Wikidata
Johanna Geiß, Andreas Spitz, Michael Gertz · Lecture notes in computer science · 2018
Many Information Extraction tasks such as Named Entity Recognition or Event Detection require background repositories that provide a classification of entities into the basic, predominantly used classes location , person , and organization . Several available knowledge bases offer a very detailed and specific ontology of entities that can be used as a repository. However, due to the mechanisms behind their construction, they are relatively static and of limited use to IE approaches that require up-to-date information. In contrast, Wikidata is a community-edited knowledge base that is kept current by its userbase, but has a constantly evolving and less rigid ontology structure that does not correspond to these basic classes. In this paper we present the tool NECKAr, which assigns Wikidata entities to the three main classes of named entities, as well as the resulting Wikidata NE dataset that consists of over 8 million classified entities. Both are available at http://event.ifi.uni-heidelberg.de/?page_id=532 . These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.