Semi-supervised Relation Extraction with Label Propagation.
NAACL-Short '06 Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers（2006）
Abstract
To overcome the problem of not having enough manually labeled relation instances for supervised relation extraction methods, in this paper we propose a label propagation (LP) based semi-supervised learning algorithm for relation extraction task to learn from both labeled and unlabeled data. Evaluation on the ACE corpus showed when only a few labeled examples are available, our LP based relation extraction can achieve better performance than SVM and another bootstrapping method.
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Key words
relation extraction,relation extraction task,relation instance,supervised relation extraction method,ACE corpus,better performance,bootstrapping method,label propagation,unlabeled data,Semi-supervised relation extraction
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