Corpus ID: 7856415

Learning 5000 Relational Extractors

@inproceedings{Hoffmann2010Learning5R,
  title={Learning 5000 Relational Extractors},
  author={R. Hoffmann and Congle Zhang and Daniel S. Weld},
  booktitle={ACL},
  year={2010}
}
  • R. Hoffmann, Congle Zhang, Daniel S. Weld
  • Published in ACL 2010
  • Computer Science
  • Many researchers are trying to use information extraction (IE) to create large-scale knowledge bases from natural language text on the Web. However, the primary approach (supervised learning of relation-specific extractors) requires manually-labeled training data for each relation and doesn't scale to the thousands of relations encoded in Web text. This paper presents LUCHS, a self-supervised, relation-specific IE system which learns 5025 relations --- more than an order of magnitude greater… CONTINUE READING
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