Huge Automatically Extracted Training Sets for Multilingual Word Sense Disambiguation
Computation and Language
2018-05-15 v1
Abstract
We release to the community six large-scale sense-annotated datasets in multiple language to pave the way for supervised multilingual Word Sense Disambiguation. Our datasets cover all the nouns in the English WordNet and their translations in other languages for a total of millions of sense-tagged sentences. Experiments prove that these corpora can be effectively used as training sets for supervised WSD systems, surpassing the state of the art for low-resourced languages and providing competitive results for English, where manually annotated training sets are accessible. The data is available at trainomatic.org.
Cite
@article{arxiv.1805.04685,
title = {Huge Automatically Extracted Training Sets for Multilingual Word Sense Disambiguation},
author = {Tommaso Pasini and Francesco Maria Elia and Roberto Navigli},
journal= {arXiv preprint arXiv:1805.04685},
year = {2018}
}