The role of semantics, pre-emption and skew in linguistic distributions: the case of the un-construction

We use the Google Ngram database, a corpus of 5,195,769 digitized books containing ~4% of all books ever published, to test three ideas that are hypothesized to account for linguistic generalizations: verbal semantics, pre-emption and skew. Using 828,813 tokens of un-forms as a test case for these mechanisms, we found verbal semantics was a good predictor of the frequency of un-forms in the English language over the past 200 years—both in terms of how the frequency changed over time and their frequency rank. We did not find strong evidence for the direct competition of un-forms and their top pre-emptors, however the skew of the un-construction competitors was inversely correlated with the acceptability of the un-form. We suggest a cognitive explanation for this, namely, that the more the set of relevant pre-emptors is skewed then the more easily it is retrieved from memory. This suggests that it is not just the frequency of pre-emptive forms that must be taken into account when trying to explain usage patterns but their skew as well.