Difference between revisions of "Exploiting Semantic Role Labeling, Wordnet and Wikipedia for Coreference Resolution"

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{{Infobox work
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| title = Exploiting Semantic Role Labeling, Wordnet and Wikipedia for Coreference Resolution
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| date = 2006
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| authors = [[Simone Paolo Ponzetto]]<br />[[Michael Strube]]
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| doi = 10.3115/1220835.1220860
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| link = http://dl.acm.org/citation.cfm?id=1220860
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}}
 
'''Exploiting Semantic Role Labeling, Wordnet and Wikipedia for Coreference Resolution''' - scientific work related to [[Wikipedia quality]] published in 2006, written by [[Simone Paolo Ponzetto]] and [[Michael Strube]].
 
'''Exploiting Semantic Role Labeling, Wordnet and Wikipedia for Coreference Resolution''' - scientific work related to [[Wikipedia quality]] published in 2006, written by [[Simone Paolo Ponzetto]] and [[Michael Strube]].
  
 
== Overview ==
 
== Overview ==
 
In this paper authors present an extension of a machine learning based coreference resolution system which uses [[features]] induced from different [[semantic knowledge]] sources. These features represent knowledge mined from [[WordNet]] and [[Wikipedia]], as well as information about semantic role labels. Authors show that semantic features indeed improve the performance on different referring expression types such as pronouns and common nouns.
 
In this paper authors present an extension of a machine learning based coreference resolution system which uses [[features]] induced from different [[semantic knowledge]] sources. These features represent knowledge mined from [[WordNet]] and [[Wikipedia]], as well as information about semantic role labels. Authors show that semantic features indeed improve the performance on different referring expression types such as pronouns and common nouns.

Revision as of 07:33, 22 June 2020


Exploiting Semantic Role Labeling, Wordnet and Wikipedia for Coreference Resolution
Authors
Simone Paolo Ponzetto
Michael Strube
Publication date
2006
DOI
10.3115/1220835.1220860
Links
Original

Exploiting Semantic Role Labeling, Wordnet and Wikipedia for Coreference Resolution - scientific work related to Wikipedia quality published in 2006, written by Simone Paolo Ponzetto and Michael Strube.

Overview

In this paper authors present an extension of a machine learning based coreference resolution system which uses features induced from different semantic knowledge sources. These features represent knowledge mined from WordNet and Wikipedia, as well as information about semantic role labels. Authors show that semantic features indeed improve the performance on different referring expression types such as pronouns and common nouns.