Resolving Lexical Ambiguity in Tensor Regression Models of Meaning

  title={Resolving Lexical Ambiguity in Tensor Regression Models of Meaning},
  author={Dimitri Kartsaklis and Nal Kalchbrenner and Mehrnoosh Sadrzadeh},
This paper provides a method for improving tensor-based compositional distributional models of meaning by the addition of an explicit disambiguation step prior to composition. In contrast with previous research where this hypothesis has been successfully tested against relatively simple compositional models, in our work we use a robust model trained with linear regression. The results we get in two experiments show the superiority of the prior disambiguation method and suggest that the… CONTINUE READING

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