@inproceedings{1b1e31c76b3844cbac99448cc9cab3b4,
title = "Do supervised distributional methods really learn lexical inference relations?",
abstract = "Distributional representations of words have been recently used in supervised settings for recognizing lexical inference relations between word pairs, such as hypernymy and entailment. We investigate a collection of these state-of-the-art methods, and show that they do not actually learn a relation between two words. Instead, they learn an independent property of a single word in the pair: whether that word is a {"}prototypical hypernym{"}.",
author = "Omer Levy and Steffen Remus and Chris Biemann and Ido Dagan",
note = "Publisher Copyright: {\textcopyright} 2015 Association for Computational Linguistics.; Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2015 ; Conference date: 31-05-2015 Through 05-06-2015",
year = "2015",
doi = "https://doi.org/10.3115/v1/n15-1098",
language = "الإنجليزيّة",
series = "NAACL HLT 2015 - 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference",
publisher = "Association for Computational Linguistics (ACL)",
pages = "970--976",
booktitle = "NAACL HLT 2015 - 2015 Conference of the North American Chapter of the Association for Computational Linguistics",
address = "الولايات المتّحدة",
}