PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Global Learning of Focused Entailment Graphs
Jonathan Berant, Ido Dagan and Jacob Goldberger
In: ACL 2010, 11-16 July 2010, Uppsala, Sweden.


We propose a global algorithm for learning entailment relations between predicates. We define a graph structure over predicates that represents entailment relations as directed edges, and use a global transitivity constraint on the graph to learn the optimal set of edges, by formulating the optimization problem as an Integer Linear Program. We motivate this graph with an application that provides a hierarchical summary for a set of propositions that focus on a target concept, and show that our global algorithm improves performance by more than 10% over baseline algorithms

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
ID Code:7661
Deposited By:Jonathan Berant
Deposited On:17 March 2011