Improving Word Sense Disambiguation with Translations
Full Text: 2020.emnlp-main.332.pdf
It has been conjectured that multilingual information can help monolingual word sense disambiguation (WSD). However, existing WSD systems rarely consider multilingual information, and no effective method has been proposed for improving WSD by generating translations. In this paper, we present a novel approach that improves the performance of a base WSD system using machine translation. Since our approach is language independent, we perform WSD experiments on several languages. The results demonstrate that our methods can consistently improve the performance of WSD systems, and obtain state-ofthe-art results in both English and multilingual WSD. To facilitate the use of lexical translation information, we also propose BABALIGN, an precise bitext alignment algorithm which is guided by multilingual lexical correspondences from BabelNet.
Citation
Y. Luan, B. Hauer, L. Mou, G. Kondrak. "Improving Word Sense Disambiguation with Translations ". EMNLP - Conference on Empirical Methods in Natural Language Processing, pp 4055-4065, November 2020.| Keywords: | |
| Category: | In Conference |
| Web Links: | doi |
| ACL |
BibTeX
@incollection{Luan+al:(EMNLP)20,
author = {Yixing Luan and Bradley Hauer and Lili Mou and Grzegorz Kondrak},
title = {Improving Word Sense Disambiguation with Translations },
Pages = {4055-4065},
booktitle = {EMNLP - Conference on Empirical Methods in Natural Language
Processing},
year = 2020,
}Last Updated: February 01, 2021Submitted by Sabina P
