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.
@article{arxiv.1910.00290,
title = {Identifying Supporting Facts for Multi-hop Question Answering with Document Graph Networks},
author = {Mokanarangan Thayaparan and Marco Valentino and Viktor Schlegel and Andre Freitas},
journal= {arXiv preprint arXiv:1910.00290},
year = {2019}
}