  Recent advances in reading comprehension have resulted in models that surpass
human performance when the answer is contained in a single, continuous passage
of text. However, complex Question Answering (QA) typically requires multi-hop
reasoning - i.e. the integration of supporting facts from different sources, to
infer the correct answer. This paper proposes Document Graph Network (DGN), a
message passing architecture for the identification of supporting facts over a
graph-structured representation of text. The evaluation on HotpotQA shows that
DGN obtains competitive results when compared to a reading comprehension
baseline operating on raw text, confirming the relevance of structured
representations for supporting multi-hop reasoning.
