Three machine learning algorithms for lexical ambiguity resolution
Three machine learning algorithms for lexical ambiguity resolution
Maximum entropy models for natural language ambiguity resolution
Maximum entropy models for natural language ambiguity resolution
Combining Classifiers for word sense disambiguation
Natural Language Engineering
Nymble: a high-performance learning name-finder
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Three generative, lexicalised models for statistical parsing
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
An algorithm for aspects of semantic interpretation using an enhanced WordNet
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
An empirical evaluation of knowledge sources and learning algorithms for word sense disambiguation
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
English tasks: all-words and verb lexical sample
SENSEVAL '01 The Proceedings of the Second International Workshop on Evaluating Word Sense Disambiguation Systems
Aligning features with sense distinction dimensions
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Word domain disambiguation via word sense disambiguation
NAACL-Short '06 Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers
PNNL: a supervised maximum entropy approach to word sense disambiguation
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Automatic event-level textual emotion sensing using mutual action histogram between entities
Expert Systems with Applications: An International Journal
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Joint learning of preposition senses and semantic roles of prepositional phrases
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Jointly modeling WSD and SRL with Markov logic
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Extensive study on automatic verb sense disambiguation in czech
TSD'06 Proceedings of the 9th international conference on Text, Speech and Dialogue
Event-Level textual emotion sensing based on common action distributions between event participants
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
Integrative semantic dependency parsing via efficient large-scale feature selection
Journal of Artificial Intelligence Research
Composition of semantic relations: Theoretical framework and case study
ACM Transactions on Speech and Language Processing (TSLP)
Hi-index | 0.00 |
We describe an automatic Word Sense Disambiguation (WSD) system that disambiguates verb senses using syntactic and semantic features that encode information about predicate arguments and semantic classes. Our system performs at the best published accuracy on the English verbs of Senseval-2. We also experiment with using the gold-standard predicate-argument labels from PropBank for disambiguating fine-grained WordNet senses and course-grained PropBank framesets, and show that disambiguation of verb senses can be further improved with better extraction of semantic roles.