SensEmBERT System
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A SensEmBERT System is a Sense Embedding System that is a knowledge-based learning system that produces sense embeddings in multiple languages.
- Example(s):
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- Counter-Example(s):
- See: Word Similarity Task, Word Analogy Task, Distributional Co-Occurrence Word Vector, Term Vector Space, Sentiment Analysis, Natural Language Processing, Language Model, Sequence Tagging, Deep Contextualized Word Representation System, Contextual Word Vector.
References
2020
- (Scarlini et al., 2020) ⇒ Bianca Scarlini, Tommaso Pasini, and Roberto Navigli. (2020). “SensEmBERT: Context-Enhanced Sense Embeddings for Multilingual Word Sense Disambiguation.” In: Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020); Proceedings of the Thirty-Second Innovative Applications of Artificial Intelligence Conference (IAAI 2020); Proceedings of the Tenth AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI 2020).