Open-domain question answering (QA) has been extensively studied in recent years.
many existing works have followed the 'search-and-answer' strategy and achieved strong performance (Chen et al., 2017;Kwon et al., 2018;Wang et al., 2018b) spanning multiple QA datasets such as TriviaQA (Joshi et al., 2017), SQuAD (Rajpurkar et al., 2016), mS-macro (Nguyen et al., 2016), ARC   open-domain QA tasks become inherently more difficult when (1) dealing with questions with little available evidence; (2) solving questions where the answer type is free-form text (e.g.