Frequency, Acceptability, and Selection: A case study of clause-embedding
This addresses a linguistic modeling problem for researchers in syntax and language acquisition, but it is incremental as it builds on existing techniques without major breakthroughs.
The study tackled the problem of predicting verb acceptability in subcategorization frames based on frequency distributions, finding that frequency explains less than one-third of acceptability information and matrix factorization methods perform only slightly better.
We investigate the relationship between the frequency with which verbs are found in particular subcategorization frames and the acceptability of those verbs in those frames, focusing in particular on subordinate clause-taking verbs, such as "think", "want", and "tell". We show that verbs' subcategorization frame frequency distributions are poor predictors of their acceptability in those frames---explaining, at best, less than 1/3 of the total information about acceptability across the lexicon---and, further, that common matrix factorization techniques used to model the acquisition of verbs' acceptability in subcategorization frames fare only marginally better. All data and code are available at http://megaattitude.io.