Global Learning of Typed Entailment Rules

@inproceedings{Berant2011GlobalLO,
  title={Global Learning of Typed Entailment Rules},
  author={Jonathan Berant and Ido Dagan and Jacob Goldberger},
  booktitle={ACL},
  year={2011}
}
Extensive knowledge bases of entailment rules between predicates are crucial for applied semantic inference. In this paper we propose an algorithm that utilizes transitivity constraints to learn a globally-optimal set of entailment rules for typed predicates. We model the task as a graph learning problem and suggest methods that scale the algorithm to larger graphs. We apply the algorithm over a large data set of extracted predicate instances, from which a resource of typed entailment rules has… CONTINUE READING

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