Learning Cooccurrences by using a Parser

Kazunori Matsumoto, Hiroshi Sakaki, Shingo Kuroiwa


Abstract
This paper describes two methods for the acquisition and utilization of lexical cooccurrence relationships. Under these method, cooccurrence relationships are obtained from two kinds of inputs: example sentences and the corresponding correct syntactic structure. The first of the two methods treats a set of governors each element of which is bound to a element of sister nodes set in a syntactic structure under consideration, as a cooccurrence relationship. In the second method, a cooccurrence relationship name and affiliated attribute names are manually given in the description of augmented rewriting rules. Both methods discriminate correctness of cooccurrence by the use of the correct syntactic structure mentioned above. Experiment is made for both methods to find if thus obtained cooccurrence relationship is useful for the correct analysis.
Anthology ID:
W89-0239
Volume:
Proceedings of the First International Workshop on Parsing Technologies
Month:
August
Year:
1989
Address:
Pittsburgh, Pennsylvania, USA
Venue:
IWPT
SIG:
SIGPARSE
Publisher:
Carnegy Mellon University
Note:
Pages:
379–388
Language:
URL:
https://aclanthology.org/W89-0239
DOI:
Bibkey:
Cite (ACL):
Kazunori Matsumoto, Hiroshi Sakaki, and Shingo Kuroiwa. 1989. Learning Cooccurrences by using a Parser. In Proceedings of the First International Workshop on Parsing Technologies, pages 379–388, Pittsburgh, Pennsylvania, USA. Carnegy Mellon University.
Cite (Informal):
Learning Cooccurrences by using a Parser (Matsumoto et al., IWPT 1989)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/W89-0239.pdf