title: Verb subcategorization frequencies: American English corpus data, methodological studies, and cross-corpus comparisons.
abstract: Verb subcategorization frequencies (verb biases) have been widely studied in psycholinguistics and play an important role in human sentence processing. Yet available resources on subcategorization frequencies suffer from limited coverage, limited ecological validity, and divergent coding criteria. Prior estimates of verb transitivity, for example, vary widely with corpus size, coverage, and coding criteria This article provides norming data for 281 verbs of interest to psycholinguistic research, sampled from a corpus of American English, along with a detailed coding manual. We examine the effect on transitivity bias of various coding decisions and methods of computing verb biases.
authors.affiliation: University of Illinois at Urbana-Champaign, Urbana, Illinois, USA. gahl@icsi.berkeley.edu
authors.forename: Susanne
authors.initials: S
authors.lastname: Gahl
authors.forename: Dan
authors.initials: D
authors.lastname: Jurafsky
authors.forename: Douglas
authors.initials: D
authors.lastname: Roland
mesh_terms: D006801:Humans; D007802:Language; D008037:Linguistics / Q000379:methods / Q000706:statistics & numerical data; D010507:Periodicity; D010700:Phonetics; D014825:Vocabulary