Context-Aware Embeddings of Senses (ARES) System
(Redirected from ARES representation)
Jump to navigation
Jump to search
A Context-Aware Embeddings of Senses (ARES) System is a Sense Embedding System that is a semi-supervised learning system for producing sense embeddings from lexical meanings within a lexical knowledge base.
- Example(s):
- …
- 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). “With More Contexts Comes Better Performance: Contextualized Sense Embeddings for All-Round Word Sense Disambiguation.” In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020).