Paper Info
Title
Non-Local Modeling with a Mixture of PCFGs.
Abstract
While most work on parsing with PCFGs has focused on local correlations between tree configurations, we attempt to model non-local correlations using a finite mixture of PCFGs. A mixture grammar fit with the EM algorithm shows improvement over a single PCFG, both in parsing accuracy and in test data likelihood. We argue that this improvement comes from the learning of specialized grammars that capture non-local correlations.
Year
Venue
Keywords
2006
CoNLL
single pcfg,specialized grammar,parsing accuracy,finite mixture,local correlation,non-local modeling,test data likelihood,mixture grammar fit,capture non-local correlation,non-local correlation,em algorithm
Field
DocType
Citations 
Rule-based machine translation,Expectation–maximization algorithm,Computer science,Grammar,Speech recognition,Artificial intelligence,Test data,Natural language processing,Parsing,Finite mixture,Machine learning
Conference
0
PageRank 
References 
Authors
0.34
11
3
Name
Order
Citations
PageRank
Slav Petrov12405107.56
Leon Barrett252025.02
Dan Klein38083495.21