Title
Semantic and syntactic features for dutch coreference resolution
Abstract
We investigate the effect of encoding additional semantic and syntactic information sources in a classification-based machine learning approach to the task of coreference resolution for Dutch. We experiment both with a memory-based learning approach and a maximum entropy modeling method. As an alternative to using external lexical resources, such as the lowcoverage Dutch EuroWordNet, we evaluate the effect of automatically generated semantic clusters as information source. We compare these clusters, which group together semantically similar nouns, to two semantic features based on EuroWordNet encoding synonym and hypernym relations between nouns. The syntactic function of the anaphor and antecedent in the sentence can be an important clue for resolving coreferential relations. As baseline approach, we encode syntactic information as predicted by a memorybased shallow parser in a set of features. We contrast these shallow parse based features with features encoding richer syntactic information from a dependency parser. We show that using both the additional semantic information and syntactic information lead to small but significant performance improvement of our coreference resolution approach.
Year
DOI
Venue
2008
10.1007/978-3-540-78135-6_30
CICLing
Keywords
Field
DocType
information source,syntactic information,baseline approach,dutch coreference resolution,coreference resolution approach,additional semantic,syntactic information source,syntactic feature,richer syntactic information,syntactic information lead,additional semantic information,syntactic function,machine learning,semantic similarity,maximum entropy model,noun
Noun phrase,Coreference,Syntactic predicate,Pattern recognition,Computer science,Dependency grammar,Natural language processing,Artificial intelligence,Parsing,Semantic feature,Syntax,EuroWordNet
Conference
Volume
ISSN
ISBN
4919
0302-9743
3-540-78134-X
Citations 
PageRank 
References 
2
0.36
23
Authors
3
Name
Order
Citations
PageRank
Iris Hendrickx128530.91
Veronique Hoste213816.92
Walter Daelemans32019269.73