Paper: Detecting Verbal Participation in Diathesis Alternations

ACL ID C98-2242
Title Detecting Verbal Participation in Diathesis Alternations
Venue International Conference on Computational Linguistics
Session Main Conference
Year 1998

We present a method for automatically identi- fying verbal participation in diathesis alterna- tions. Automatically acquired subcategoriza- tion fi'ames are compared to a hand-crafted clas- sification for selecting candidate verbs. The minimmn description length principle is then used to produce a model and cost for storing the head noun instances from a training corpus at the relevant argument slots. Alternating sub- categorization fi'ames are identified where the data from corresponding argument slots in the respective frames can be combined to produce a cheaper model than that produced if the data is encoded separately. 1.