Title
Semantic Dependency Parsing using N-best Semantic Role Sequences and Roleset Information.
Abstract
In this paper, we describe a syntactic and semantic dependency parsing system submitted to the shared task of CoNLL 2008. The proposed system consists of five modules: syntactic dependency parser, predicate identifier, local semantic role labeler, global role sequence candidate generator, and role sequence selector. The syntactic dependency parser is based on Malt Parser and the sequence candidate generator is based on CKY style algorithm. The remaining three modules are implemented by using maximum entropy classifiers. The proposed system achieves 76.90 of labeled F1 for the overall task, 84.82 of labeled attachment, and 68.71 of labeled F1 on the WSJ+Brown test set.
Year
Venue
Keywords
2008
CoNLL
overall task,global role sequence candidate,local semantic role labeler,syntactic dependency parser,roleset information,brown test set,proposed system,shared task,semantic dependency,role sequence selector,sequence candidate generator,n-best semantic role sequence,maximum entropy,semantic role labeling,dependency parsing
Field
DocType
Citations 
Top-down parsing,Identifier,Syntactic predicate,Computer science,Dependency grammar,Natural language processing,Artificial intelligence,Predicate (grammar),Parsing,Parser combinator,Syntax
Conference
0
PageRank 
References 
Authors
0.34
7
3
Name
Order
Citations
PageRank
Joo-Young Lee17712.36
Han-Cheol Cho21427.48
Hae-Chang Rim382889.14