Automatic verb classification based on statistical distributions of argument structure
Computational Linguistics
Semi-supervised verb class discovery using noisy features
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
CoNLL-X shared task on multilingual dependency parsing
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Labeled pseudo-projective dependency parsing with support vector machines
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Linguistic features in data-driven dependency parsing
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
Animacy encoding in English: why and how
DiscAnnotation '04 Proceedings of the 2004 ACL Workshop on Discourse Annotation
NP animacy identification for anaphora resolution
Journal of Artificial Intelligence Research
Climbing the path to grammar: a maximum entropy model of subject/object learning
PMHLA '05 Proceedings of the Workshop on Psychocomputational Models of Human Language Acquisition
Extracting human Spanish nouns
TSD'10 Proceedings of the 13th international conference on Text, speech and dialogue
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This article presents empirical evaluations of aspects of annotation for the linguistic property of animacy in Swedish, ranging from manual human annotation, automatic classification and, finally, an external evaluation in the task of syntactic parsing. We show that a treatment of animacy as a lexical semantic property of noun types enables generalization over distributional properties of these nouns which proves beneficial in automatic classification and furthermore gives significant improvements in terms of parsing accuracy for Swedish, compared to a state-of-the-art baseline parser with gold standard animacy information.