Language Modelling Makes Sense: Propagating Representations through WordNet for Full-Coverage Word Sense Disambiguation

@article{Loureiro2019LanguageMM,
  title={Language Modelling Makes Sense: Propagating Representations through WordNet for Full-Coverage Word Sense Disambiguation},
  author={Daniel Loureiro and A. Jorge},
  journal={ArXiv},
  year={2019},
  volume={abs/1906.10007}
}
Contextual embeddings represent a new generation of semantic representations learned from Neural Language Modelling (NLM) that addresses the issue of meaning conflation hampering traditional word embeddings. [...] Key Method As a result, a simple Nearest Neighbors (k-NN) method using our representations is able to consistently surpass the performance of previous systems using powerful neural sequencing models. We also analyse the robustness of our approach when ignoring part-of-speech and lemma features…Expand
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