Learning to Predict Denotational Probabilities For Modeling Entailment

Autor: Julia Hockenmaier, Alice Lai
Rok vydání: 2017
Předmět:
Zdroj: EACL (1)
DOI: 10.18653/v1/e17-1068
Popis: We propose a framework that captures the denotational probabilities of words and phrases by embedding them in a vector space, and present a method to induce such an embedding from a dataset of denotational probabilities. We show that our model successfully predicts denotational probabilities for unseen phrases, and that its predictions are useful for textual entailment datasets such as SICK and SNLI.
Databáze: OpenAIRE