Context-Aware Embeddings of Senses (ARES) System

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):
  • SensEmBERT System,
  • BERT Embedding System.
• 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.

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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).

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