{"type":"ScholarlyArticle","title":"A Breadth-First Parsing Model","authors":[{"name":"John Bear","slug":"john-bear","given":"John","family":"Bear","affiliation":""}],"abstract":"Recent attempts at modeling humans' abilitiesat processing natural language have centered around depth first parsing algorithms, and control strategies for making the best choices for disambiguation and attachment. This paper proposes a breadth-first algor ithrn as a model. The algorithm avoids sane of the carrnon pitfalls of depth-first approaches regarding ambiguity, and by using more pre-canputed information about the grammar, avoids sane of the usual proolans of parallel parsing algorithms as well.","doi":null,"url":"https://ijcai.org/proceedings/1983/168","pdf":"https://ijcai.org/proceedings/1983/0168.pdf","markdown":"https://ijcai.org/proceedings/1983/168.md","bibtex":"https://ijcai.org/proceedings/1983/bibtex/168","volume":{"slug":"1983","title":"Proceedings of the Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1983","url":"https://ijcai.org/proceedings/1983/","year":1983,"location":"Karlsruhe, West Germany","dates":"","editors":"Alan Bundy","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Natural Language","track":"Natural Language","number":168,"pages":{"first":696,"last":697},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}