A Computational Model of Syntactic Processing: Ambiguity Resolution from Interpretation

A Computational Model of Syntactic Processing Ambiguity Resolution from Interpretation Michael Niv Mark J Steedman Supervisor Syntactic ambiguity abounds in natural language yet humans have no di culty coping with it In fact the process of ambiguity resolution is almost always unconscious But it is not infallible however as example demonstrates The horse raced past the barn fell This sentence is perfectly grammatical as is evident when it appears in the following context Two horses were being shown o to a prospective buyer One was raced past a meadow and the other was raced past a barn Grammatical yet unprocessable sentences such as are called garden path sentences Their existence provides an opportunity to investigate the human sentence processing mechanism by studying how and when it fails The aim of this thesis is to construct a computational model of language understanding which can predict processing di culty The data to be modeled are known examples of garden path and non garden path sentences and other results from psycholinguistics It is widely believed that there are two distinct loci of computation in sentence processing syntactic parsing and semantic interpretation One longstanding controversy is which of these two modules bears responsibility for the immediate resolution of ambiguity My claim is that it is the latter and that the syntactic processing module is a very simple device which blindly and faithfully constructs all possible analyses for the sentence up to the current point of processing The interpretive module serves as a lter occasionally discarding certain of these analyses which it deems less appropriate for the ongoing discourse than their competitors This document is divided into three parts The rst is introductory and reviews a selection of proposals from the sentence processing literature The second part explores a body of data which has been adduced in support of a theory of structural preferences one that is inconsistent with the present claim I show how the current proposal can be speci ed to account for the available data and moreover to predict where structural preference theories will go wrong The third part is a theoretical investigation of how well the proposed architecture can be realized using current conceptions of linguistic competence In it I present a parsing algorithm and a meaning based ambiguity resolution method