We introduce BIOMRC, a large-scale cloze-style biomedical MRC dataset. Care
was taken to reduce noise, compared to the previous BIOREAD dataset of Pappas
et al. (2018). Experiments show that simple heuristics do not perform well on
the new dataset, and that two neural MRC models that had been tested on BIOREAD
perform much better on BIOMRC, indicating that the new dataset is indeed less
noisy or at least that its task is more feasible. Non-expert human performance
is also higher on the new dataset compared to BIOREAD, and biomedical experts
perform even better. We also introduce a new BERT-based MRC model, the best
version of which substantially outperforms all other methods tested, reaching
or surpassing the accuracy of biomedical experts in some experiments. We make
the new dataset available in three different sizes, also releasing our code,
and providing a leaderboard.

介绍了 BIOMRC 大规模填空式生物医学 MRC 数据集及相关实验结果，新数据集噪声更小，任务也更可行，比以前的 BIOREAD 数据集表现更好。同时，介绍了一个基于 BERT 的最佳 MRC 模型，其准确率在某些实验中甚至超过了生物医学专家，并释放了三种规模的数据集和代码。