Difference between revisions of "Extracting Context-Rich Entailment Rules from Wikipedia Revision History"

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{{Infobox work
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| title = Extracting Context-Rich Entailment Rules from Wikipedia Revision History
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| date = 2012
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| authors = [[Elena Cabrio]]<br />[[Bernardo Magnini]]<br />[[Angelina Ivanova]]
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| link = https://dl.acm.org/citation.cfm?id=2392799
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}}
 
'''Extracting Context-Rich Entailment Rules from Wikipedia Revision History''' - scientific work related to [[Wikipedia quality]] published in 2012, written by [[Elena Cabrio]], [[Bernardo Magnini]] and [[Angelina Ivanova]].
 
'''Extracting Context-Rich Entailment Rules from Wikipedia Revision History''' - scientific work related to [[Wikipedia quality]] published in 2012, written by [[Elena Cabrio]], [[Bernardo Magnini]] and [[Angelina Ivanova]].
  
 
== Overview ==
 
== Overview ==
 
Recent work on Textual Entailment has shown a crucial role of knowledge to support entailment inferences. However, it has also been demonstrated that currently available entailment rules are still far from being optimal. Authors propose a methodology for the automatic acquisition of large scale context-rich entailment rules from [[Wikipedia]] revisions, taking advantage of the syntactic structure of entailment pairs to define the more appropriate linguistic constraints for the rule to be successfully applicable. Authors report on rule acquisition experiments on Wikipedia, showing that it enables the creation of an innovative (i.e. acquired rules are not present in other available resources) and good quality rule repository.
 
Recent work on Textual Entailment has shown a crucial role of knowledge to support entailment inferences. However, it has also been demonstrated that currently available entailment rules are still far from being optimal. Authors propose a methodology for the automatic acquisition of large scale context-rich entailment rules from [[Wikipedia]] revisions, taking advantage of the syntactic structure of entailment pairs to define the more appropriate linguistic constraints for the rule to be successfully applicable. Authors report on rule acquisition experiments on Wikipedia, showing that it enables the creation of an innovative (i.e. acquired rules are not present in other available resources) and good quality rule repository.

Revision as of 07:13, 17 May 2020


Extracting Context-Rich Entailment Rules from Wikipedia Revision History
Authors
Elena Cabrio
Bernardo Magnini
Angelina Ivanova
Publication date
2012
Links
Original

Extracting Context-Rich Entailment Rules from Wikipedia Revision History - scientific work related to Wikipedia quality published in 2012, written by Elena Cabrio, Bernardo Magnini and Angelina Ivanova.

Overview

Recent work on Textual Entailment has shown a crucial role of knowledge to support entailment inferences. However, it has also been demonstrated that currently available entailment rules are still far from being optimal. Authors propose a methodology for the automatic acquisition of large scale context-rich entailment rules from Wikipedia revisions, taking advantage of the syntactic structure of entailment pairs to define the more appropriate linguistic constraints for the rule to be successfully applicable. Authors report on rule acquisition experiments on Wikipedia, showing that it enables the creation of an innovative (i.e. acquired rules are not present in other available resources) and good quality rule repository.