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Computer Speech and Language
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
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IWPT '09 Proceedings of the 11th International Conference on Parsing Technologies
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EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
Temporal Relations Learning with a Bootstrapped Cross-document Classifier
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Using syntactic-based kernels for classifying temporal relations
Journal of Computer Science and Technology - Special issue on natural language processing
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Journal of Biomedical Informatics
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This paper shows that inference rules with temporal constraints can be acquired by using verb-verb co-occurrences in Japanese coordinated sentences and verb-noun co-occurrences. For example, our unsupervised acquisition method could obtain the inference rule "If someone enforces a law, usually someone enacts the law at the same time as or before the enforcing of the law" since the verbs "enact" and "enforce" frequently co-occurred in coordinated sentences and the verbs also frequently co-occurred with the noun "law". We also show that the accuracy of the acquisition is improved by using the occurrence frequency of a single verb, which we assume indicates how generic the meaning of the verb is.