Sentence Disambiguation by a Shift-Reduce Parsing Technique

Native speakers of English show definite and consistent preferences for certain readings of syntactically ambiguous sentences. A user of a natural-language processing system would naturally expect it to reflect the same preferences. Thus, such systems must model in some way the linguistic performance as well as the linguistic competence of the native speaker. The authors have developed a parsing algorithm -- a variant of the LALR(1) shift-reduce algorithm -- that models the preference behavior of native speakers for a range of syntactic preference phenomena reported in the psycholinguistic literature, including the recent data on lexical preferences. The algorithm yields the preferred parse deterministically, without building multiple parse trees and choosing among them. As a side effect, it displays appropriate behavior in processing the much discussed garden-path sentences. The parsing algorithm has been implemented and has confirmed the feasibility of this approach to the modeling of these phenomena.
Technical Note 281. Sponsored in part by the Defense Advanced Research Projects Agency (DARPA). Pub. in the Proceedings of the 21st Annual Meeting of the Association for Computational Linguistics, 1983. Presented at the Annual Meeting of the Association for Computational Linguistics (21st) held in Boston, MA in Jun 1983.