Learning Disentangled Representations of Negation and Uncertainty
Learning Disentangled Representations of Negation and Uncertainty
Negation and uncertainty modeling are long-standing tasks in natural language processing. Linguistic theory postulates that expressions of negation and uncertainty are semantically independent from each other and the content they modify. However, previous works on representation learning do not explicitly model this independence. We therefore attempt to disentangle the representations …