11 March 2003

Quantifying Ambiguity Resolution with Information Theory

John Hale

Johns Hopkins University

Ambiguities about grammatical category and syntactic structure permeate natural language. Explaining human comprehenders' performance in the face of such confusion has been called the central problem in sentence processing (Tabor & Tanenhaus, 2001). How is it that human sentence understanders are able to recognize combinatory relationships, from an infinite range of possibilities, to arrive at a meaningful interpretation of a sentence?

This talk argues that an answer lies in formalizing the idea that comprehenders search the space of grammatical analyses in a way constrained by the words they hear. Comprehenders are constantly engaged in ambiguity resolution, and the more ambiguity is resolved, the longer they take.

To make this intuition fully explicit, ambiguity resolution will be given a precise interpretation in terms of information theory.

The general theory is tested using explicit grammar fragments that are probabilistic versions of Generalized Phrase Structure Grammars (Gazdar, Klein & Sag 1985) and Minimalist Grammars (Stabler 1997).

The theory will be shown to derive a range of well-documented processing phenomena including garden-path sentences, center-embedding, and the Accessibility (or Obliqueness) Hierarchy of relativized grammatical functions.