C4.5: programs for machine learning
C4.5: programs for machine learning
Machine Learning
Getting Useful Gender Statistics from English Text
Getting Useful Gender Statistics from English Text
A New, Fully Automatic Version of Mitkov's Knowledge-Poor Pronoun Resolution Method
CICLing '02 Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing
Towards robust animacy classification using morphosyntactic distributional features
EACL '06 Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop
Anaphora resolution: to what extent does it help nlp applications?
DAARC'07 Proceedings of the 6th discourse anaphora and anaphor resolution conference on Anaphora: analysis, algorithms and applications
Extracting human Spanish nouns
TSD'10 Proceedings of the 13th international conference on Text, speech and dialogue
Automatic animacy classification
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research Workshop
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Information about the animacy of nouns is important for a wide range of tasks in NLP. In this paper, we present a method for determining the animacy of English nouns using WordNet and machine learning techniques. Our method firstly categorises the senses from WordNet using an annotated corpus and then uses this information in order to classify nouns for which the sense is not known. Our evaluation results show that the accuracy of the classification of a noun is around 97% and that animate entities are more difficult to identify than inanimate ones.