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Harnessing Historical Corrections to Build Test Collections for Named Entity Disambiguation
[chapter]
2018
Lecture Notes in Computer Science
Matching mentions of persons to the actual persons (the name disambiguation problem) is central for several digital library applications. Scientists have been working on algorithms to create this matching for decades without finding a universal solution. One problem is that test collections for this problem are often small and specific to a certain collection. In this work, we present an approach that can create large test collections from historical metadata with minimal extra cost. We apply
doi:10.1007/978-3-030-00066-0_4
fatcat:jcqoka6ajnhpvndkw5exeyltyi