A Breadth-First Parsing Model
Proceedings of the Eighth International Joint Conference on Artificial Intelligence. Natural Language. Pages 696-697.
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.
John Bear. 1983. A Breadth-First Parsing Model. In Proceedings of the Eighth International Joint Conference on Artificial Intelligence, IJCAI-83. IJCAI, 696–697. https://ijcai.org/proceedings/1983/168
Bear, J. (1983). A Breadth-First Parsing Model. In Proceedings of the Eighth International Joint Conference on Artificial Intelligence, IJCAI-83 (pp. 696–697). IJCAI. https://ijcai.org/proceedings/1983/168
@inproceedings{ijcai1983p168,
title = {A Breadth-First Parsing Model},
author = {Bear, John},
booktitle = {Proceedings of the Eighth International Joint Conference on
Artificial Intelligence, {IJCAI-83}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Alan Bundy},
pages = {696--697},
year = {1983},
note = {Natural Language},
url = {https://ijcai.org/proceedings/1983/168},
}
TY - CPAPER TI - A Breadth-First Parsing Model AU - Bear, John T2 - Proceedings of the Eighth International Joint Conference on Artificial Intelligence, IJCAI-83 PB - International Joint Conferences on Artificial Intelligence PY - 1983 SP - 696 EP - 697 UR - https://ijcai.org/proceedings/1983/168 ER -Copied
Machine-readable versions of this paper, for tools and AI agents:
