This paper presents a two-step procedure to extract positive meaning from verbal negation. We first generate potential positive interpretations manipulating syntactic dependencies. Then, we score them according to their likelihood. Manual annotations show that positive interpretations are ubiquitous and intuitive to humans. Experimental results show that dependencies are better suited than semantic roles for this task, and automation is possible.