Paper Info
Title
Automated extraction of Tree-Adjoining Grammars from treebanks
Abstract
There has been a contemporary surge of interest in the application of stochastic models of parsing. The use of tree-adjoining grammar (TAG) in this domain has been relatively limited due in part to the unavailability, until recently, of large-scale corpora hand-annotated with TAG structures. Our goals are to develop inexpensive means of generating such corpora and to demonstrate their applicability to stochastic modeling. We present a method for automatically extracting a linguistically plausible TAG from the Penn Treebank. Furthermore, we also introduce labor-inexpensive methods for inducing higher-level organization of TAGs. Empirically, we perform an evaluation of various automatically extracted TAGs and also demonstrate how our induced higher-level organization of TAGs can be used for smoothing stochastic TAG models.
Year
DOI
Venue
2006
10.1017/S1351324905003943
Natural Language Engineering
Keywords
Field
DocType
higher-level organization,penn treebank,linguistically plausible tag,automated extraction,contemporary surge,tag structure,induced higher-level organization,stochastic tag model,labor-inexpensive method,stochastic model,inexpensive mean,tree-adjoining grammars,tree adjoining grammar
Rule-based machine translation,Computer science,Grammar,Smoothing,Unavailability,Natural language processing,Artificial intelligence,Treebank,Stochastic modelling,Parsing
Journal
Volume
Issue
Citations 
12
3
15
PageRank 
References 
Authors
0.90
32
3
Name
Order
Citations
PageRank
john chen119726.31
Srinivas Bangalore21319157.37
K. Vijay-Shanker32057192.47