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
- 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)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/P17-2094.pdf
- Data
- Word Sense Disambiguation: a Unified Evaluation Framework and Empirical Comparison