On the limited memory BFGS method for large scale optimization
Mathematical Programming: Series A and B
A machine learning approach to coreference resolution of noun phrases
Computational Linguistics - Special issue on computational anaphora resolution
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
A comparison of algorithms for maximum entropy parameter estimation
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Specialized models and ranking for coreference resolution
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A ranking approach to pronoun resolution
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
TectoMT: highly modular MT system with tectogrammatics used as transfer layer
StatMT '08 Proceedings of the Third Workshop on Statistical Machine Translation
Supervised models for coreference resolution
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Simple coreference resolution with rich syntactic and semantic features
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
Comparison of classification and ranking approaches to pronominal anaphora resolution in Czech
SIGDIAL '09 Proceedings of the SIGDIAL 2009 Conference: The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Coreference resolution in a modular, entity-centered model
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Supervised noun phrase coreference research: the first fifteen years
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
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In this work, we present first results on noun phrase coreference resolution on Czech data. As the data resource for our experiments, we employed yet unfinished and unpublished extension of Prague Dependency Treebank 2.0, which captures noun phrase coreference and bridging relations. Incompleteness of the data influenced one of our motivations --- to aid annotators with automatic pre-annotation of the data. Although we introduced several novel tree features and tried different machine learning approaches, results on a growing amount of data shows that the selected feature set and learning methods are not able to sufficiently exploit the data.