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A graph partitioning approach to entity disambiguation using uncertain information

Author
Sapena, E.; Padro, L.; Turmo, J.
Type of activity
Presentation of work at congresses
Name of edition
6th International Conference Advances in Natural Language Processing
Date of publication
2008
Presentation's date
2008
Book of congress proceedings
Proceedings of the 6th International Conference Advances in Natural Language Processing
First page
428
Last page
439
Publisher
Springer
Repository
http://hdl.handle.net/2117/7552 Open in new window
URL
http://www.springerlink.com/content/43380w0237021327/fulltext.pdf Open in new window
Abstract
This paper presents a method for Entity Disambiguation in Information Extraction from different sources in the web. Once entities and relations between them are extracted, it is needed to determine which ones are referring to the same real-world entity. We model the problem as a graph partitioning problem in order to combine the available information more accurately than a pairwise classifier. Moreover, our method handle uncertain information which turns out to be quite helpful. Two algorithms a...
Citation
Sapena, E.; Padró, L.; Turmo, J. A graph partitioning approach to entity disambiguation using uncertain information. A: 6th International Conference Advances in Natural Language Processing. "6th International Conference Advances in Natural Language Processing". Springer, 2008, p. 428-439.
Group of research
GPLN - Natural Language Processing Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
TALP - Centre for Language and Speech Technologies and Applications

Participants