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
Venues:
IWPT | WS
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://preview.aclanthology.org/update-css-js/2000.iwpt-1.2.pdf