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The evaluation of the results showed that it is feasible to crowdsource the detection of flaws in LD sets; in particular, the experiments revealed that (i) lay workers are in fact able to detect certain quality issues with satisfactory precision; that (ii) experts perform well in identifying triples with ‘object value’ or ‘datatype’ issues, and lastly, (iii) the two approaches reveal complementary strengths.
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