Automatic Identification of Basic-Level Categories
Date of Issue2018
The 9th Global WordNet Conference (GWC 2018)
School of Humanities and Social Sciences
Basic-level categories have been shown to be both psychologically significant and useful in a wide range of practical applications. We build a rule-based system to identify basic-level categories in WordNet, achieving 77% accuracy on a test set derived from prior psychological experiments. With additional annotations we found our system also has low precision, in part due to the existence of many categories that do not fit into the three classes (superordinate, basic-level, and subordinate) relied on in basiclevel category research.
© 2018 The author(s). This is the author created version of a work that has been peer reviewed and accepted for publication by The 9th Global WordNet Conference (GWC 2018). It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The full-text is available at: [http://compling.hss.ntu.edu.sg/events/2018-gwc/pdfs/GWC2018_paper_5.pdf].