EuroSense: Automatic Harvesting of Multilingual Sense Annotations from Parallel Text

Claudio Delli Bovi, Jose Camacho-Collados, Alessandro Raganato, Roberto Navigli


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.
Anthology ID:
P17-2094
Volume:
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
Month:
July
Year:
2017
Address:
Vancouver, Canada
Editors:
Regina Barzilay, Min-Yen Kan
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
594–600
Language:
URL:
https://aclanthology.org/P17-2094
DOI:
10.18653/v1/P17-2094
Bibkey:
Cite (ACL):
Claudio Delli Bovi, Jose Camacho-Collados, Alessandro Raganato, and Roberto Navigli. 2017. EuroSense: Automatic Harvesting of Multilingual Sense Annotations from Parallel Text. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 594–600, Vancouver, Canada. Association for Computational Linguistics.
Cite (Informal):
EuroSense: Automatic Harvesting of Multilingual Sense Annotations from Parallel Text (Delli Bovi et al., ACL 2017)
Copy Citation:
PDF:
https://aclanthology.org/P17-2094.pdf
Data
Word Sense Disambiguation: a Unified Evaluation Framework and Empirical Comparison