---
title: "Sentence Disambiguation by a Shift-Reduce Parsing Technique"
authors:
  - "Stuart M. Shieber"
doi: ""
url: "https://ijcai.org/proceedings/1983/169"
pdf: "https://ijcai.org/proceedings/1983/0169.pdf"
venue: "Proceedings of the Eighth International Joint Conference on Artificial Intelligence"
year: 1983
pages: "699-702"
track: "Natural Language"
keywords:
---

# Sentence Disambiguation by a Shift-Reduce Parsing Technique

Stuart M. Shieber

*Proceedings of the Eighth International Joint Conference on Artificial Intelligence*, pages 699-702.

## Abstract

Native speakers of English show definite and consistent pr eferences for ce rtain readings of syntactically ambiguous sent e nc e8. A user of a natural-language-processing system would natur ally expe ct it to reflect the same preferences. Thus, such systems must model in some way the lingui8tic performance as we ll as the lingui8tic competence of the native speaker. We ha ve developed a parsing algorithm-a variant of the LALR(1) shift-reduce algorithmthat models the preference behavior of native speakers for a range of syntactic preference phenomena reported in the psycholinguistic literature, including the recent d ata on lexical preferences . The algorithm yields the preferred par se deterministically, without building multiple parse trees and choosing among them. As a side effect, it displays appropria te behavior in processing the much discussed garden-path sente nces. The parsing algorithm has been implemented and has confirmed the feasibility of our approach to the modeling of these phenomena.