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.
| Original language | English |
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| Title of host publication | Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 |
| Editors | Ellen Riloff, David Chiang, Julia Hockenmaier, Jun'ichi Tsujii |
| Publisher | Association for Computational Linguistics |
| Pages | 1533-1542 |
| Number of pages | 10 |
| ISBN (Electronic) | 9781948087841 |
| State | Published - 2018 |
| Externally published | Yes |
| Event | 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 - Brussels, Belgium Duration: 31 Oct 2018 → 4 Nov 2018 |
Publication series
| Name | Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 |
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Conference
| Conference | 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 |
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| Country/Territory | Belgium |
| City | Brussels |
| Period | 31/10/18 → 4/11/18 |
Bibliographical note
Publisher Copyright:© 2018 Association for Computational Linguistics