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We report results on benchmarking Open Information Extraction (OIE) systemsusing RelVis, a toolkit for benchmarking Open Information Extraction systems.Our comprehensive benchmark contains three data sets from the news domain andone data set from Wikipedia with overall 4522 labeled sentences and 11243binary or n-ary OIE relations. In our analysis on these data sets we comparedthe performance of four popular OIE systems, ClausIE, OpenIE 4.2, StanfordOpenIE and PredPatt. In addition, we evaluated the impact of five common errorclasses on a subset of 749 n-ary tuples. From our deep analysis we unrevealimportant research directions for a next generation of OIE systems.

Analysing Errors of Open Information Extraction Systems