2 papers
cs.CL2020
Word Sense Disambiguation for 158 Languages using Word Embeddings Only
Varvara Logacheva, Denis Teslenko, Artem Shelmanov +7
Disambiguation of word senses in context is easy for humans, but is a major challenge for automatic approaches. Sophisticated supervised and knowledge-based models were developed t…
cs.CL2018
An Unsupervised Word Sense Disambiguation System for Under-Resourced Languages
Dmitry Ustalov, Denis Teslenko, Alexander Panchenko +3
In this paper, we present Watasense, an unsupervised system for word sense disambiguation. Given a sentence, the system chooses the most relevant sense of each input word with resp…