Difference between revisions of "Open Information Extraction Using Wikipedia"
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| − | '''Open Information Extraction Using Wikipedia''' - scientific work related to Wikipedia quality published in 2010, written by Fei Wu and Daniel S. Weld. | + | '''Open Information Extraction Using Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2010, written by [[Fei Wu]] and [[Daniel S. Weld]]. |
== Overview == | == Overview == | ||
Information-extraction (IE) systems seek to distill semantic relations from natural-language text, but most systems use supervised learning of relation-specific examples and are thus limited by the availability of training data. Open IE systems such as TextRunner, on the other hand, aim to handle the unbounded number of relations found on the Web. But how well can these open systems perform? | Information-extraction (IE) systems seek to distill semantic relations from natural-language text, but most systems use supervised learning of relation-specific examples and are thus limited by the availability of training data. Open IE systems such as TextRunner, on the other hand, aim to handle the unbounded number of relations found on the Web. But how well can these open systems perform? | ||
Revision as of 16:53, 21 June 2020
Open Information Extraction Using Wikipedia - scientific work related to Wikipedia quality published in 2010, written by Fei Wu and Daniel S. Weld.
Overview
Information-extraction (IE) systems seek to distill semantic relations from natural-language text, but most systems use supervised learning of relation-specific examples and are thus limited by the availability of training data. Open IE systems such as TextRunner, on the other hand, aim to handle the unbounded number of relations found on the Web. But how well can these open systems perform?
