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Identifying Supporting Facts for Multi hop Question Answering with Document Graph Networks

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Figure 1: Is structure important for complex, multi-hop Question Answering (QA) over unstructured textpassages? To answer this question we explore the taskof identifying supporting facts (rounded rectangles) bytransforming a corpus of documents (1) into an undi-rected graph (2) connecting sentence nodes (rectan-gles) and document nodes (hexagons).
Figure 2: Overview of the approach for the identification of supporting facts in a multi-hop QA pipeline
Table 2: Supporting facts identification: Harmonicmean (F1), Precision and Recall
Table 3: Precision, Recall and F1 score of the DGNmodel with different values of k assigned to the pre-filtering algorithm

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