Automatic Grammar Induction: Combining, Reducing and Doing Nothing

Eric Brill, John C. Henderson, Grace Ngai


Abstract
This paper surveys three research directions in parsing. First, we look at methods for both automatically generating a set of diverse parsers and combining the outputs of different parsers into a single parse. Next, we will discuss a parsing method known as transformation-based parsing. This method, though less accurate than the best current corpus-derived parsers, is able to parse quite accurately while learning only a small set of easily understood rules, as opposed to the many-megabyte parameter files learned by other techniques. Finally, we review a recent study exploring how people and machines compare at the task of creating a program to automatically annotate noun phrases.
Anthology ID:
2000.iwpt-1.2
Volume:
Proceedings of the Sixth International Workshop on Parsing Technologies
Month:
February 23-25
Year:
2000
Address:
Trento, Italy
Editors:
Alberto Lavelli, John Carroll, Robert C. Berwick, Harry C. Bunt, Bob Carpenter, John Carroll, Ken Church, Mark Johnson, Aravind Joshi, Ronald Kaplan, Martin Kay, Bernard Lang, Alon Lavie, Anton Nijholt, Christer Samuelsson, Mark Steedman, Oliviero Stock, Hozumi Tanaka, Masaru Tomita, Hans Uszkoreit, K. Vijay-Shanker, David Weir, Mats Wiren
Venue:
IWPT
SIG:
SIGPARSE
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–5
Language:
URL:
https://aclanthology.org/2000.iwpt-1.2
DOI:
Bibkey:
Cite (ACL):
Eric Brill, John C. Henderson, and Grace Ngai. 2000. Automatic Grammar Induction: Combining, Reducing and Doing Nothing. In Proceedings of the Sixth International Workshop on Parsing Technologies, pages 1–5, Trento, Italy. Association for Computational Linguistics.
Cite (Informal):
Automatic Grammar Induction: Combining, Reducing and Doing Nothing (Brill et al., IWPT 2000)
Copy Citation:
PDF:
https://aclanthology.org/2000.iwpt-1.2.pdf