@inproceedings{chia-etal-2019-red,
title = "Red Dragon {AI} at {T}ext{G}raphs 2019 Shared Task: Language Model Assisted Explanation Generation",
author = "Chia, Yew Ken and
Witteveen, Sam and
Andrews, Martin",
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/D19-5311",
doi = "10.18653/v1/D19-5311",
pages = "85--89",
abstract = "The TextGraphs-13 Shared Task on Explanation Regeneration (Jansen and Ustalov, 2019) asked participants to develop methods to reconstruct gold explanations for elementary science questions. Red Dragon AI{'}s entries used the language of the questions and explanation text directly, rather than a constructing a separate graph-like representation. Our leaderboard submission placed us 3rd in the competition, but we present here three methods of increasing sophistication, each of which scored successively higher on the test set after the competition close.",
}
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<abstract>The TextGraphs-13 Shared Task on Explanation Regeneration (Jansen and Ustalov, 2019) asked participants to develop methods to reconstruct gold explanations for elementary science questions. Red Dragon AI’s entries used the language of the questions and explanation text directly, rather than a constructing a separate graph-like representation. Our leaderboard submission placed us 3rd in the competition, but we present here three methods of increasing sophistication, each of which scored successively higher on the test set after the competition close.</abstract>
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%0 Conference Proceedings
%T Red Dragon AI at TextGraphs 2019 Shared Task: Language Model Assisted Explanation Generation
%A Chia, Yew Ken
%A Witteveen, Sam
%A Andrews, Martin
%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 chia-etal-2019-red
%X The TextGraphs-13 Shared Task on Explanation Regeneration (Jansen and Ustalov, 2019) asked participants to develop methods to reconstruct gold explanations for elementary science questions. Red Dragon AI’s entries used the language of the questions and explanation text directly, rather than a constructing a separate graph-like representation. Our leaderboard submission placed us 3rd in the competition, but we present here three methods of increasing sophistication, each of which scored successively higher on the test set after the competition close.
%R 10.18653/v1/D19-5311
%U https://aclanthology.org/D19-5311
%U https://doi.org/10.18653/v1/D19-5311
%P 85-89
Markdown (Informal)
[Red Dragon AI at TextGraphs 2019 Shared Task: Language Model Assisted Explanation Generation](https://aclanthology.org/D19-5311) (Chia et al., TextGraphs 2019)
ACL