@inproceedings{boleda-etal-2017-instances,
    title = "Instances and concepts in distributional space",
    author = "Boleda, Gemma  and
      Gupta, Abhijeet  and
      Pad{\'o}, Sebastian",
    editor = "Lapata, Mirella  and
      Blunsom, Phil  and
      Koller, Alexander",
    booktitle = "Proceedings of the 15th Conference of the {E}uropean Chapter of the Association for Computational Linguistics: Volume 2, Short Papers",
    month = apr,
    year = "2017",
    address = "Valencia, Spain",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/E17-2013/",
    pages = "79--85",
    abstract = "Instances ({\textquotedblleft}Mozart{\textquotedblright}) are ontologically distinct from concepts or classes ({\textquotedblleft}composer{\textquotedblright}). 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 ({\textquotedblleft}Mozart {--} composer{\textquotedblright}) is generally easier than hypernymy detection ({\textquotedblleft}chemist {--} scientist{\textquotedblright}), and that results on the influence of input representation do not transfer from hyponymy to instantiation."
}