2020/04/08 by Aaron Steven White, White, Aaron Steven, Kyle Rawlins +1 · 2 citations
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Speech and dialogue systems #Topic Modeling
paper · pdf · doi:10.48550/arxiv.2004.04106
openalex publication_date 2020/04/08 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28
We investigate the relationship between the frequency with which verbs are\nfound in particular subcategorization frames and the acceptability of those\nverbs in those frames, focusing in particular on subordinate clause-taking\nverbs, such as "think", "want", and "tell". We show that verbs'\nsubcategorization frame frequency distributions are poor predictors of their\nacceptability in those frames---explaining, at best, less than 1/3 of the total\ninformation about acceptability across the lexicon---and, further, that common\nmatrix factorization techniques used to model the acquisition of verbs'\nacceptability in subcategorization frames fare only marginally better. All data\nand code are available at http://megaattitude.io.\n