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Computational Fact Checking from Knowledge Networks

Fig 5

Real-world fact-checking scenario.

(a) A document from the ground truth corpus. (b) Statement to fact-check: Did Steve Tesich graduate from Indiana University, Bloomington? This information is not present in the infobox, and thus it is not part of the WKG. (c) Annotations from five human raters. In this case, the majority of raters believe that the statement is true, and thus we consider it as such for classification purposes. (d) Receiver operating characteristic (ROC) curve of the classification for subject-predicate-object statements in which the predicate is “institution” (e.g., “Albert Einstein,” “institution,” “Institute for Advanced Studies”). A true positive rate above the false positive rate (dashed line), and correspondingly an area under the curve (AUC) above 0.5, indicate better than random performance. (e) ROC curve for statements with “degree” predicate (e.g., “Albert Einstein,” “degree,” “University Diploma”).

Fig 5

doi: https://doi.org/10.1371/journal.pone.0128193.g005