@inproceedings{hauer-kondrak-2022-wic,
title = "{W}i{C} = {TSV} = {WSD}: On the Equivalence of Three Semantic Tasks",
author = "Hauer, Bradley and
Kondrak, Grzegorz",
editor = "Carpuat, Marine and
de Marneffe, Marie-Catherine and
Meza Ruiz, Ivan Vladimir",
booktitle = "Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jul,
year = "2022",
address = "Seattle, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.naacl-main.178",
doi = "10.18653/v1/2022.naacl-main.178",
pages = "2478--2486",
abstract = "The Word-in-Context (WiC) task has attracted considerable attention in the NLP community, as demonstrated by the popularity of the recent MCL-WiC SemEval shared task. Systems and lexical resources from word sense disambiguation (WSD) are often used for the WiC task and WiC dataset construction. In this paper, we establish the exact relationship between WiC and WSD, as well as the related task of target sense verification (TSV). Building upon a novel hypothesis on the equivalence of sense and meaning distinctions, we demonstrate through the application of tools from theoretical computer science that these three semantic classification problems can be pairwise reduced to each other, and therefore are equivalent. The results of experiments that involve systems and datasets for both WiC and WSD provide strong empirical evidence that our problem reductions work in practice.",
}
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%0 Conference Proceedings
%T WiC = TSV = WSD: On the Equivalence of Three Semantic Tasks
%A Hauer, Bradley
%A Kondrak, Grzegorz
%Y Carpuat, Marine
%Y de Marneffe, Marie-Catherine
%Y Meza Ruiz, Ivan Vladimir
%S Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, United States
%F hauer-kondrak-2022-wic
%X The Word-in-Context (WiC) task has attracted considerable attention in the NLP community, as demonstrated by the popularity of the recent MCL-WiC SemEval shared task. Systems and lexical resources from word sense disambiguation (WSD) are often used for the WiC task and WiC dataset construction. In this paper, we establish the exact relationship between WiC and WSD, as well as the related task of target sense verification (TSV). Building upon a novel hypothesis on the equivalence of sense and meaning distinctions, we demonstrate through the application of tools from theoretical computer science that these three semantic classification problems can be pairwise reduced to each other, and therefore are equivalent. The results of experiments that involve systems and datasets for both WiC and WSD provide strong empirical evidence that our problem reductions work in practice.
%R 10.18653/v1/2022.naacl-main.178
%U https://aclanthology.org/2022.naacl-main.178
%U https://doi.org/10.18653/v1/2022.naacl-main.178
%P 2478-2486
Markdown (Informal)
[WiC = TSV = WSD: On the Equivalence of Three Semantic Tasks](https://aclanthology.org/2022.naacl-main.178) (Hauer & Kondrak, NAACL 2022)
ACL
- Bradley Hauer and Grzegorz Kondrak. 2022. WiC = TSV = WSD: On the Equivalence of Three Semantic Tasks. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 2478–2486, Seattle, United States. Association for Computational Linguistics.