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

Mokanarangan Thayaparan, Marco Valentino, Viktor Schlegel, André Freitas


Abstract
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.
Anthology ID:
D19-5306
Volume:
Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-13)
Month:
November
Year:
2019
Address:
Hong Kong
Venues:
EMNLP | TextGraphs | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
42–51
Language:
URL:
https://www.aclweb.org/anthology/D19-5306
DOI:
10.18653/v1/D19-5306
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PDF:
http://aclanthology.lst.uni-saarland.de/D19-5306.pdf