Corpus studies by Schuler et al. (2010), appear to support a model of comprehension taking place in a general-purpose working memory store, by providing an existence proof that a simple probabilistic sequence model over stores of up to four syntactically-contiguous memory elements has the capacity to reconstruct phrase structure trees for over 99.9% of the sentences in the Penn Treebank corpus, in line with capacity estimates for general-purpose working memory, e.g. by Cowan (2001). But capacity predictions of this simple structure-based model ignore non-structural dependencies, such as long-distance filler-gap dependencies, that may place additional demands on working memory. Distinguishing unattached gap fillers from open attachment sites in syntactically-contiguous memory elements requires this contiguity constraint to be strengthened to a constraint that working memory elements be semantically contiguous. This paper presents corpus results showing that this stricter semantic contiguity constraint still predicts working memory requirements in line with capacity estimates.