Red Dragon AI at TextGraphs 2019 Shared Task: Language Model Assisted Explanation Generation
This work addresses explanation generation for elementary science questions, but it is incremental as it builds on existing shared task frameworks.
The paper tackled the TextGraphs-13 Shared Task on Explanation Regeneration by developing methods to reconstruct gold explanations for elementary science questions, achieving 3rd place in the competition and presenting three increasingly sophisticated methods that scored higher post-competition.
The TextGraphs-13 Shared Task on Explanation Regeneration 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.