@inproceedings{stanovsky-hopkins-2018-spot,
title = "Spot the Odd Man Out: Exploring the Associative Power of Lexical Resources",
author = "Stanovsky, Gabriel and
Hopkins, Mark",
editor = "Riloff, Ellen and
Chiang, David and
Hockenmaier, Julia and
Tsujii, Jun{'}ichi",
booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing",
month = oct # "-" # nov,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D18-1182",
doi = "10.18653/v1/D18-1182",
pages = "1533--1542",
abstract = "We propose Odd-Man-Out, a novel task which aims to test different properties of word representations. An Odd-Man-Out puzzle is composed of 5 (or more) words, and requires the system to choose the one which does not belong with the others. We show that this simple setup is capable of teasing out various properties of different popular lexical resources (like WordNet and pre-trained word embeddings), while being intuitive enough to annotate on a large scale. In addition, we propose a novel technique for training multi-prototype word representations, based on unsupervised clustering of ELMo embeddings, and show that it surpasses all other representations on all Odd-Man-Out collections.",
}
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%0 Conference Proceedings
%T Spot the Odd Man Out: Exploring the Associative Power of Lexical Resources
%A Stanovsky, Gabriel
%A Hopkins, Mark
%Y Riloff, Ellen
%Y Chiang, David
%Y Hockenmaier, Julia
%Y Tsujii, Jun’ichi
%S Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
%D 2018
%8 oct nov
%I Association for Computational Linguistics
%C Brussels, Belgium
%F stanovsky-hopkins-2018-spot
%X We propose Odd-Man-Out, a novel task which aims to test different properties of word representations. An Odd-Man-Out puzzle is composed of 5 (or more) words, and requires the system to choose the one which does not belong with the others. We show that this simple setup is capable of teasing out various properties of different popular lexical resources (like WordNet and pre-trained word embeddings), while being intuitive enough to annotate on a large scale. In addition, we propose a novel technique for training multi-prototype word representations, based on unsupervised clustering of ELMo embeddings, and show that it surpasses all other representations on all Odd-Man-Out collections.
%R 10.18653/v1/D18-1182
%U https://aclanthology.org/D18-1182
%U https://doi.org/10.18653/v1/D18-1182
%P 1533-1542
Markdown (Informal)
[Spot the Odd Man Out: Exploring the Associative Power of Lexical Resources](https://aclanthology.org/D18-1182) (Stanovsky & Hopkins, EMNLP 2018)
ACL