Automatic labeling of semantic roles
Computational Linguistics
Semantic Role Parsing: Adding Semantic Structure to Unstructured Text
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
A study on convolution kernels for shallow semantic parsing
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Automatic semantic role labeling for Chinese verbs
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Introduction to the CoNLL-2005 shared task: semantic role labeling
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Hierarchical semantic role labeling
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
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In this paper, we present a system for Arabic semantic role labeling (SRL) based on SVMs and standard features. The system is evaluated on the released SEMEVAL 2007 development and test data. The results show an Fβ=1 score of 94.06 on argument boundary detection and an overall Fβ=1 score of 81.43 on the complete semantic role labeling task using gold parse trees.