A Sequential Truncation Parsing Algorithm Based on the Score Function

Keh-Yih Su, Jong-Nae Wang, Mei-Hui Su, Jing-Shin Chang


Abstract
In a natural language processing system, a large amount of ambiguity and a large branching factor are hindering factors in obtaining the desired analysis for a given sentence in a short time. In this paper, we are proposing a sequential truncation parsing algorithm to reduce the searching space and thus lowering the parsing time. The algorithm is based on a score function which takes the advantages of probabilistic characteristics of syntactic information in the sentences. A preliminary test on this algorithm was conducted with a special version of our machine translation system, the ARCHTRAN, and an encouraging result was observed.
Anthology ID:
W89-0210
Volume:
Proceedings of the First International Workshop on Parsing Technologies
Month:
August
Year:
1989
Address:
Pittsburgh, Pennsylvania, USA
Editor:
Masaru Tomita
Venue:
IWPT
SIG:
SIGPARSE
Publisher:
Carnegy Mellon University
Note:
Pages:
95–104
Language:
URL:
https://aclanthology.org/W89-0210
DOI:
Bibkey:
Cite (ACL):
Keh-Yih Su, Jong-Nae Wang, Mei-Hui Su, and Jing-Shin Chang. 1989. A Sequential Truncation Parsing Algorithm Based on the Score Function. In Proceedings of the First International Workshop on Parsing Technologies, pages 95–104, Pittsburgh, Pennsylvania, USA. Carnegy Mellon University.
Cite (Informal):
A Sequential Truncation Parsing Algorithm Based on the Score Function (Su et al., IWPT 1989)
Copy Citation:
PDF:
https://preview.aclanthology.org/naacl-24-ws-corrections/W89-0210.pdf