Paper: Automatic Acquisition Of The Lexical Semantics Of Verbs From Sentence Frames

ACL ID P89-1022
Title Automatic Acquisition Of The Lexical Semantics Of Verbs From Sentence Frames
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1989
Authors

This paper presents a computational model of verb acquisition which uses what we will call the princi- ple of structured overeommitment to eliminate the need for negative evidence. The learner escapes from the need to be told that certain possibili- ties cannot occur (i.e. , are "ungrammatical") by one simple expedient: It assumes that all proper- ties it has observed are either obligatory or for- bidden until it sees otherwise, at which point it decides that what it thought was either obliga- tory or forbidden is merely optional. This model is built upon a classification of verbs based upon a simple three-valued set of features which repre- sents key aspects of a verb's syntactic structure, its predicate/argument structure, and the map- ping between them.