Recent work on Textual Entailment has shown a crucial role of knowledge to support entail- ment inferences. However, it has also been demonstrated that currently available entail- ment rules are still far from being optimal. We propose a methodology for the automatic ac- quisition of large scale context-rich entailment rules from Wikipedia revisions, taking advan- tage of the syntactic structure of entailment pairs to define the more appropriate linguis- tic constraints for the rule to be successfully applicable. We report on rule acquisition ex- periments on Wikipedia, showing that it en- ables the creation of an innovative (i.e. ac- quired rules are not present in other available resources) and good quality rule repository.

Extracting Context-Rich Entailment Rules from Wikipedia Revision History

Magnini, Bernardo;
2012

Abstract

Recent work on Textual Entailment has shown a crucial role of knowledge to support entail- ment inferences. However, it has also been demonstrated that currently available entail- ment rules are still far from being optimal. We propose a methodology for the automatic ac- quisition of large scale context-rich entailment rules from Wikipedia revisions, taking advan- tage of the syntactic structure of entailment pairs to define the more appropriate linguis- tic constraints for the rule to be successfully applicable. We report on rule acquisition ex- periments on Wikipedia, showing that it en- ables the creation of an innovative (i.e. ac- quired rules are not present in other available resources) and good quality rule repository.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11582/104212
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