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        <title>Automatic Identification of Basic-Level Categories</title>
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        <namePart type="given">Gina-Anne</namePart>
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    <abstract>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 basic-level category research.</abstract>
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%0 Conference Proceedings
%T Automatic Identification of Basic-Level Categories
%A Mills, Chad
%A Bond, Francis
%A Levow, Gina-Anne
%Y Bond, Francis
%Y Vossen, Piek
%Y Fellbaum, Christiane
%S Proceedings of the 9th Global Wordnet Conference
%D 2018
%8 January
%I Global Wordnet Association
%C Nanyang Technological University (NTU), Singapore
%F mills-etal-2018-automatic
%X 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 basic-level category research.
%U https://aclanthology.org/2018.gwc-1.35/
%P 298-305

Markdown (Informal)

[Automatic Identification of Basic-Level Categories](https://aclanthology.org/2018.gwc-1.35/) (Mills et al., GWC 2018)

• Automatic Identification of Basic-Level Categories (Mills et al., GWC 2018)

ACL

• Chad Mills, Francis Bond, and Gina-Anne Levow. 2018. Automatic Identification of Basic-Level Categories. In Proceedings of the 9th Global Wordnet Conference, pages 298–305, Nanyang Technological University (NTU), Singapore. Global Wordnet Association.