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In order to provide an efficient crowdsourcing solution to the problem presented in Definition 1, we applied a variation of the crowdsourcing pattern Find- Fix-Verify [3]. As discussed in Section 3, this crowdsourcing pattern allows for increasing the overall quality of the results while maintaining competitive monetary costs when applying other crowdsourcing approaches. Our implementation of the Find-Fix-Verify pattern is tailored to assess the quality of Linked Data sets that are automatically created from other sources. Such is the case of DBpedia [24], a data set created by extracting knowledge from Wikipedia via declarative mediator/wrapper pattern. The wrappers are the result of a crowdsourced community effort of contributors to the DBpedia project. To crowdsource the assessment of triples of data sets like DBpedia, we devise a two-fold approach including the following stages: Find and Verify. In the Find stage, the crowd was requested to detect LD quality issues in a set of RDF triples, and annotate them with the corresponding issue(s) if applicable. We define the Find Stage as follows:
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