A maximum entropy approach to natural language processing
Computational Linguistics
A stochastic finite-state word-segmentation algorithm for Chinese
Computational Linguistics
Maximum entropy models for natural language ambiguity resolution
Maximum entropy models for natural language ambiguity resolution
Introduction to the special issue on word sense disambiguation: the state of the art
Computational Linguistics - Special issue on word sense disambiguation
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
Two statistical parsing models applied to the Chinese Treebank
CLPW '00 Proceedings of the second workshop on Chinese language processing: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 12
Combining contextual features for word sense disambiguation
WSD '02 Proceedings of the ACL-02 workshop on Word sense disambiguation: recent successes and future directions - Volume 8
SENSEVAL '01 The Proceedings of the Second International Workshop on Evaluating Word Sense Disambiguation Systems
English tasks: all-words and verb lexical sample
SENSEVAL '01 The Proceedings of the Second International Workshop on Evaluating Word Sense Disambiguation Systems
The Penn Chinese TreeBank: Phrase structure annotation of a large corpus
Natural Language Engineering
Combining contextual features for word sense disambiguation
WSD '02 Proceedings of the ACL-02 workshop on Word sense disambiguation: recent successes and future directions - Volume 8
Chinese verb sense discrimination using an EM clustering model with rich linguistic features
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Aligning features with sense distinction dimensions
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Word Clustering for Collocation-Based Word Sense Disambiguation
CICLing '07 Proceedings of the 8th International Conference on Computational Linguistics and Intelligent Text Processing
A novel machine learning approach for the identification of named entity relations
FeatureEng '05 Proceedings of the ACL Workshop on Feature Engineering for Machine Learning in Natural Language Processing
Automatic construction of an English-Chinese bilingual FrameNet
HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers
SRCB-WSD: supervised Chinese word sense disambiguation with key features
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Combining knowledge- and corpus-based word-sense-disambiguation methods
Journal of Artificial Intelligence Research
Identifying semantic relations between named entities from chinese texts
Proceedings of the 2005 joint Chinese-German conference on Cognitive systems
A collocation-based WSD model: RFR-SUM
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Using a smoothing maximum entropy model for chinese nominal entity tagging
IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
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In this paper we report on our experiments on automatic Word Sense Disambiguation using a maximum entropy approach for both English and Chinese verbs. We compare the difficulty of the sense-tagging tasks in the two languages and investigate the types of contextual features that are useful for each language. Our experimental results suggest that while richer linguistic features are useful for English WSD, they may not be as beneficial for Chinese.