Abstract
Instances ("Mozart") are ontologically distinct from concepts or classes ("composer"). Natural language encompasses both, but instances have received comparatively little attention in distributional semantics. Our results show that instances and concepts differ in their distributional properties. We also establish that instantiation detection ("Mozart - composer") is generally easier than hypernymy detection ("chemist - scientist"), and that results on the influence of input representation do not transfer from hyponymy to instantiation.
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CITATION STYLE
Boleda, G., Gupta, A., & Padó, S. (2017). Instances and concepts in distributional space. In 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Proceedings of Conference (Vol. 2, pp. 79–85). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/e17-2013
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