EuroSense: Automatic Harvesting of Multilingual Sense Annotations from Parallel Text
Claudio Delli Bovi, José Camacho-Collados, Alessandro Raganato, Roberto Navigli · 2017
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 languageindependent unified sense inventory.We evaluate the quality of our sense annotations intrinsically and extrinsically, showing their effectiveness as training data for Word Sense Disambiguation.