BIOMRC: A Dataset for Biomedical Machine Reading Comprehension
May 13, 2020 ยท Declared Dead ยท ๐ Workshop on Biomedical Natural Language Processing
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Authors
Petros Stavropoulos, Dimitris Pappas, Ion Androutsopoulos, Ryan McDonald
arXiv ID
2005.06376
Category
cs.CL: Computation & Language
Cross-listed
cs.LG,
stat.ML
Citations
58
Venue
Workshop on Biomedical Natural Language Processing
Last Checked
4 months ago
Abstract
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.
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