Automatic Generation and Scoring of Positive Interpretations from Negated Statements

This paper presents a methodology to extract positive interpretations from negated statements. First, we automatically generate plausible interpretations using well-known grammar rules and manipulating semantic roles. Second, we score plausible alternatives according to their likelihood. Manual annotations show that the positive interpretations are intuitive to humans, and experimental results show that the scoring task can be automated.