Corpus ID: 171268

Global Learning of Typed Entailment Rules

@inproceedings{Berant2011GlobalLO,
  title={Global Learning of Typed Entailment Rules},
  author={Jonathan Berant and I. Dagan and J. Goldberger},
  booktitle={ACL},
  year={2011}
}
  • Jonathan Berant, I. Dagan, J. Goldberger
  • Published in ACL 2011
  • Computer Science
  • Extensive knowledge bases of entailment rules between predicates are crucial for applied semantic inference. [...] Key Method We apply the algorithm over a large data set of extracted predicate instances, from which a resource of typed entailment rules has been recently released (Schoenmackers et al., 2010). Our results show that using global transitivity information substantially improves performance over this resource and several baselines, and that our scaling methods allow us to increase the scope of global…Expand Abstract

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 33 REFERENCES
    Automatic Acquisition of Hyponyms from Large Text Corpora
    • 3,364
    • PDF
    Global Learning of Focused Entailment Graphs
    • 58
    • PDF
    Discovery of inference rules for question-answering
    • 592
    • Highly Influential
    • PDF
    Open Information Extraction from the Web
    • 2,059
    • Highly Influential
    • PDF
    Semantic Taxonomy Induction from Heterogenous Evidence
    • 505
    • PDF
    Learning Entailment Rules for Unary Templates
    • 112
    • PDF
    Scaling Web-based Acquisition of Entailment Relations
    • 196
    Recognizing textual entailment : Rational , evaluation and approaches
    • I D O D A G A N, O. A.N, B E R N A R D O M A G N I N I
    • 2009
    • 144
    • PDF
    The Berkeley FrameNet Project
    • 2,575
    • PDF
    Learning First-Order Horn Clauses from Web Text
    • 171
    • Highly Influential
    • PDF