Resolving Ambiguities in Sentence Processing with Domination and Command – Robert Frank (Department of Cognitive Science, The Johns Hopkins University)

October 7, 1997 all-day

Sentence processing is almost always an effortless task. This seemingly banal observation becomes considerably more puzzling when juxtaposed with the somewhat less obvious observation that natural language syntax exhibits rampant (local) ambiguity. That is to say, in the processing of a given sentence there are likely to be many points at which there are multiple analyses compatible with the input seen thus far, but only one of these may turn out to be consistent with the remainder of the utterance. Many traditional models of parsing deal with such ambiguity by exploiting some type of parallelism, carrying a number of partial parses forward from the point of ambiguity for further consideration. Unfortunately, such a proliferation of parses is bound to consume significant time and space resources, rendering this type of approach inappropriate as a model for human processing.An alternative approach to the local ambiguity problem has been suggested by Marcus, Hindle, and Fleck (1983) in their work on D-theory. In this work and in a significant number of papers that have followed in this line of inquiry, the parser constructs an underspecified description of a parse tree by positing domination (as opposed to parent) relations among nodes in a phrase structure tree. In this talk, I will suggest that certain empirical and conceptual shortcomings of the D-theory approach to local ambiguity can be overcome if the descriptive primitive is changed from domination to the more abstract and linguistically ubiquitous relation of c-command. I will illustrate the advantages of c-command over domination with a range of examples from English and Japanese.

Johns Hopkins University

Johns Hopkins University, Whiting School of Engineering

Center for Language and Speech Processing
Hackerman 226
3400 North Charles Street, Baltimore, MD 21218-2680

Center for Language and Speech Processing