Topic Models for Word Sense Disambiguation and Token-Based Idiom Detection

  title={Topic Models for Word Sense Disambiguation and Token-Based Idiom Detection},
  author={Linlin Li and Benjamin Roth and Caroline Sporleder},
This paper presents a probabilistic model for sense disambiguation which chooses the best sense based on the conditional probability of sense paraphrases given a context. We use a topic model to decompose this conditional probability into two conditional probabilities with latent variables. We propose three different instantiations of the model for solving sense disambiguation problems with different degrees of resource availability. The proposed models are tested on three different tasks… CONTINUE READING
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