@inproceedings{delli-bovi-etal-2017-eurosense,
title = "{E}uro{S}ense: Automatic Harvesting of Multilingual Sense Annotations from Parallel Text",
author = "Delli Bovi, Claudio and
Camacho-Collados, Jose and
Raganato, Alessandro and
Navigli, Roberto",
editor = "Barzilay, Regina and
Kan, Min-Yen",
booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
month = jul,
year = "2017",
address = "Vancouver, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P17-2094",
doi = "10.18653/v1/P17-2094",
pages = "594--600",
abstract = "Parallel corpora are widely used in a variety of Natural Language Processing tasks, from Machine Translation to cross-lingual Word Sense Disambiguation, where parallel sentences can be exploited to automatically generate high-quality sense annotations on a large scale. In this paper we present EuroSense, a multilingual sense-annotated resource based on the joint disambiguation of the Europarl parallel corpus, with almost 123 million sense annotations for over 155 thousand distinct concepts and entities from a language-independent unified sense inventory. We evaluate the quality of our sense annotations intrinsically and extrinsically, showing their effectiveness as training data for Word Sense Disambiguation.",
}
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%0 Conference Proceedings
%T EuroSense: Automatic Harvesting of Multilingual Sense Annotations from Parallel Text
%A Delli Bovi, Claudio
%A Camacho-Collados, Jose
%A Raganato, Alessandro
%A Navigli, Roberto
%Y Barzilay, Regina
%Y Kan, Min-Yen
%S Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2017
%8 July
%I Association for Computational Linguistics
%C Vancouver, Canada
%F delli-bovi-etal-2017-eurosense
%X Parallel corpora are widely used in a variety of Natural Language Processing tasks, from Machine Translation to cross-lingual Word Sense Disambiguation, where parallel sentences can be exploited to automatically generate high-quality sense annotations on a large scale. In this paper we present EuroSense, a multilingual sense-annotated resource based on the joint disambiguation of the Europarl parallel corpus, with almost 123 million sense annotations for over 155 thousand distinct concepts and entities from a language-independent unified sense inventory. We evaluate the quality of our sense annotations intrinsically and extrinsically, showing their effectiveness as training data for Word Sense Disambiguation.
%R 10.18653/v1/P17-2094
%U https://aclanthology.org/P17-2094
%U https://doi.org/10.18653/v1/P17-2094
%P 594-600
Markdown (Informal)
[EuroSense: Automatic Harvesting of Multilingual Sense Annotations from Parallel Text](https://aclanthology.org/P17-2094) (Delli Bovi et al., ACL 2017)
ACL