Clustering Algorithms
Automatic labeling of semantic roles
Computational Linguistics
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Statistical Models for Co-occurrence Data
Statistical Models for Co-occurrence Data
The Proposition Bank: An Annotated Corpus of Semantic Roles
Computational Linguistics
A dual coordinate descent method for large-scale linear SVM
Proceedings of the 25th international conference on Machine learning
Towards robust semantic role labeling
Computational Linguistics
Algorithms for deterministic incremental dependency parsing
Computational Linguistics
A latent variable model of synchronous parsing for syntactic and semantic dependencies
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
The CoNLL-2009 shared task: syntactic and semantic dependencies in multiple languages
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning: Shared Task
Dependency-based semantic role labeling of PropBank
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Hardware/Software Codesign of Resource Constrained Real-Time Systems
IAS '09 Proceedings of the 2009 Fifth International Conference on Information Assurance and Security - Volume 01
Online graph planarisation for synchronous parsing of semantic and syntactic dependencies
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Introduction to the CoNLL-2005 shared task: semantic role labeling
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Dynamic programming for linear-time incremental parsing
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Retrieving correct semantic boundaries in dependency structure
LAW IV '10 Proceedings of the Fourth Linguistic Annotation Workshop
Semantic role features for machine translation
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Getting the most out of transition-based dependency parsing
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
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This paper suggests two ways of improving semantic role labeling (SRL). First, we introduce a novel transition-based SRL algorithm that gives a quite different approach to SRL. Our algorithm is inspired by shift-reduce parsing and brings the advantages of the transition-based approach to SRL. Second, we present a self-learning clustering technique that effectively improves labeling accuracy in the test domain. For better generalization of the statistical models, we cluster verb predicates by comparing their predicate argument structures and apply the clustering information to the final labeling decisions. All approaches are evaluated on the CoNLL'09 English data. The new algorithm shows comparable results to another state-of-the-art system. The clustering technique improves labeling accuracy for both in-domain and out-of-domain tasks.