In this work, we revisit Shared Task 1 from the 2012 *SEM Conference: the au-tomated analysis of negation. Unlike the vast majority of participating systems in 2012, our approach works over explicit and formal representations of proposi-tional semantics, i.e. derives the notion of negation scope assumed in this task from the structure of logical-form meaning rep-resentations. We relate the task-specific interpretation of (negation) scope to the concept of (quantifier and operator) scope in mainstream underspecified semantics. With reference to an explicit encoding of semantic predicate-argument structure, we can operationalize the annotation deci-sions made for the 2012 *SEM task, and demonstrate how a comparatively simple system for negation scope resolution can be built from an off-the-shelf deep parsing system. In a system combination setting, our approach improves over the best pub-lished results on this task to date. 1

A precise syntacto-semantic analysis of English requires a large detailed lexicon with the possibility of treating multiple tokens as a single meaning-bearing unit, a word-with-spaces.However parsing with such a lexicon, as included in the English Resource Grammar, can be very slow.We show that we can apply supertagging techniques over an ambiguous token lattice without resorting to previously used heuristics, a process we call ubertagging.Our model achieves an ubertagging accuracy that can lead to a four to eight fold speed up while improving parser accuracy.