Paper: Detecting Verbal Participation in Diathesis Alternations

ACL ID P98-2247
Title Detecting Verbal Participation in Diathesis Alternations
Venue Annual Meeting of the Association of 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 frames are compared to a hand-crafted clas- sification for selecting candidate verbs. The minimum 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 frames 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.