Forgetting Exceptions is Harmful in Language Learning
Machine Learning - Special issue on natural language learning
Memory-Based Language Processing (Studies in Natural Language Processing)
Memory-Based Language Processing (Studies in Natural Language Processing)
Inductive Dependency Parsing (Text, Speech and Language Technology)
Inductive Dependency Parsing (Text, Speech and Language Technology)
Semantic role labeling using dependency trees
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Labeled pseudo-projective dependency parsing with support vector machines
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
The CoNLL-2008 shared task on joint parsing of syntactic and semantic dependencies
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
ILK2: semantic role labelling for Catalan and Spanish using TiMBL
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Applying spelling error correction techniques for improving semantic role labelling
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
A memory-based learning approach to event extraction in biomedical texts
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing: Shared Task
Joint memory-based learning of syntactic and semantic dependencies in multiple languages
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning: Shared Task
Learning the scope of negation in biomedical texts
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Semantic role labeling for structured information extraction
Proceedings of the fourth workshop on Exploiting semantic annotations in information retrieval
| Hi-index | 0.00 |
We describe the system submitted to the closed challenge of the CoNLL-2008 shared task on joint parsing of syntactic and semantic dependencies. Syntactic dependencies are processed with the Malt-Parser 0.4. Semantic dependencies are processed with a combination of memory-based classifiers. The system achieves 78.43 labeled macro F1 for the complete problem, 86.07 labeled attachment score for syntactic dependencies, and 70.51 labeled F1 for semantic dependencies.