Neural Sequence Learning Models for Word Sense Disambiguation

@inproceedings{Raganato2017NeuralSL,
  title={Neural Sequence Learning Models for Word Sense Disambiguation},
  author={Alessandro Raganato and Claudio Delli Bovi and R. Navigli},
  booktitle={EMNLP},
  year={2017}
}
Word Sense Disambiguation models exist in many flavors. Even though supervised ones tend to perform best in terms of accuracy, they often lose ground to more flexible knowledge-based solutions, which do not require training by a word expert for every disambiguation target. To bridge this gap we adopt a different perspective and rely on sequence learning to frame the disambiguation problem: we propose and study in depth a series of end-to-end neural architectures directly tailored to the task… Expand
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References

SHOWING 1-10 OF 77 REFERENCES
Word Sense Disambiguation using a Bidirectional LSTM
  • 79
  • PDF
Word Sense Disambiguation: A Unified Evaluation Framework and Empirical Comparison
  • 175
  • PDF
Embeddings for Word Sense Disambiguation: An Evaluation Study
  • 203
  • PDF
Semi-supervised Word Sense Disambiguation with Neural Models
  • 104
  • Highly Influential
  • PDF
One Million Sense-Tagged Instances for Word Sense Disambiguation and Induction
  • 61
  • Highly Influential
  • PDF
context2vec: Learning Generic Context Embedding with Bidirectional LSTM
  • 304
  • Highly Influential
  • PDF
Semi-Supervised Word Sense Disambiguation Using Word Embeddings in General and Specific Domains
  • 98
  • PDF
Semi-supervised Learning with Induced Word Senses for State of the Art Word Sense Disambiguation
  • 14
  • PDF
It Makes Sense: A Wide-Coverage Word Sense Disambiguation System for Free Text
  • 287
  • PDF
...
1
2
3
4
5
...