C4.5: programs for machine learning
C4.5: programs for machine learning
Assessing agreement on classification tasks: the kappa statistic
Computational Linguistics
Robustness beyond shallowness: incremental deep parsing
Natural Language Engineering
Message Understanding Conference-6: a brief history
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Evita: a robust event recognizer for QA systems
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Automatically extracting nominal mentions of events with a bootstrapped probabilistic classifier
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Automatic detection of non-deverbal event nouns for quick lexicon production
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
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In this paper, we propose a method for creating automatically weighted lexicons of event names. Almost all names of events are ambiguous in context (i.e., they can be interpreted in an eventive or non-eventive reading). Therefore, weights representing the relative "eventiveness" of a noun can help for disambiguating event detection in texts. We applied our method on both French and English corpora. Our method has been applied to both French and English corpora. We performed an evaluation based upon a machine-learning approach that shows that using weighted lexicons can be a good way to improve event extraction. We also propose a study concerning the necessary size of corpus to be used for creating a valuable lexicon.