@inproceedings{thayaparan-etal-2019-identifying,
title = "Identifying Supporting Facts for Multi-hop Question Answering with Document Graph Networks",
author = "Thayaparan, Mokanarangan and
Valentino, Marco and
Schlegel, Viktor and
Freitas, Andr{\'e}",
editor = "Ustalov, Dmitry and
Somasundaran, Swapna and
Jansen, Peter and
Glava{\v{s}}, Goran and
Riedl, Martin and
Surdeanu, Mihai and
Vazirgiannis, Michalis",
booktitle = "Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-13)",
month = nov,
year = "2019",
address = "Hong Kong",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-5306",
doi = "10.18653/v1/D19-5306",
pages = "42--51",
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.",
}
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%0 Conference Proceedings
%T Identifying Supporting Facts for Multi-hop Question Answering with Document Graph Networks
%A Thayaparan, Mokanarangan
%A Valentino, Marco
%A Schlegel, Viktor
%A Freitas, André
%Y Ustalov, Dmitry
%Y Somasundaran, Swapna
%Y Jansen, Peter
%Y Glavaš, Goran
%Y Riedl, Martin
%Y Surdeanu, Mihai
%Y Vazirgiannis, Michalis
%S Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-13)
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong
%F thayaparan-etal-2019-identifying
%X 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.
%R 10.18653/v1/D19-5306
%U https://aclanthology.org/D19-5306
%U https://doi.org/10.18653/v1/D19-5306
%P 42-51
Markdown (Informal)
[Identifying Supporting Facts for Multi-hop Question Answering with Document Graph Networks](https://aclanthology.org/D19-5306) (Thayaparan et al., TextGraphs 2019)
ACL