Title
Heuristics and Parse Ranking
Abstract
There are currently two philosophies for building grammars and parsers - Statistically induced grammars and Wide-coverage grammars. One way to combine the strengths of both approaches is to have a wide-coverage grammar with a heuristic component which is domain independent but whose contribution is tuned to particular domains. In this paper, we discuss a three-stage approach to disambiguation in the context of a lexicalized grammar, using a variety of domain independent heuristic techniques. We present a training algorithm which uses hand-bracketed treebank parses to set the weights of these heuristics. We compare the performance of our grammar against the performance of the IBM statistical grammar, using both untrained and trained weights for the heuristics.
Year
Venue
Field
1995
Clinical Orthopaedics and Related Research
Stochastic context-free grammar,Link grammar,L-attributed grammar,Extended Affix Grammar,Regular tree grammar,Computer science,Synchronous context-free grammar,Adaptive grammar,Parsing expression grammar,Natural language processing,Artificial intelligence,Machine learning
DocType
Volume
ISSN
Journal
abs/cmp-lg
International Workshop on Parsing Technologies (IWPT 95)
Citations 
PageRank 
References 
10
2.10
11
Authors
3
Name
Order
Citations
PageRank
Srinivas Bangalore11319157.37
Christine Doran2102.10
Seth Kulick322129.66