We present a method for making decisions as to whether an entity in a knowledge base should be a class or an instance based on external evidence in the form of corresponding textual corpora such as Wikipedia articles. The approach, based on machine classification of the text, avoids the need for feature engineering and provides valuable guidance when building or refining large knowledge bases. The approach works well over different domains and outperforms a variety of other state-of-the-art approaches.
CITATION STYLE
Padia, A., Martin, D., & Patel-Schneider, P. F. (2018). Automating class/instance representational choices in knowledge bases. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11313, pp. 273–288). Springer Verlag. https://doi.org/10.1007/978-3-030-03667-6_18
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