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RE traditionally takes as input a finite set R of relations and a document d, and induces assertions in the form rel(subj, obj), where rel represent binary relations between a subject entity subj and an object entity obj mentioned in d. Hence, it may be viewed as a closed-domain paradigm. Recent efforts [3,2,30] have focused on alleviating the cost of full supervision via distant supervision. Distant supervision leverages available KBs to automatically annotate training data in the input documents. This is in contrast to our work, since we aim at enriching the target KB with external data, rather than using it as a source. Furthermore, our relatively cheap crowdsourcing technique serves as a substitute to distant supervision, while ensuring full supervision. Other approaches such as [7,33] instead leverage text that is not covered by the target KB, like we do.
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