Summary of the paper

Title BioRead: A New Dataset for Biomedical Reading Comprehension
Authors Dimitris Pappas, Ion Androutsopoulos and Haris Papageorgiou
Abstract We present BioRead, a new publicly available cloze-style biomedical machine reading comprehension (MRC) dataset with approximately 16.4 million passage-question instances. BioRead was constructed in the same way as the widely used Children’s Book Test and its extension BookTest, but using biomedical journal articles and employing MetaMap to identify UMLS concepts. BioRead is one of the largest MRC datasets, and currently the largest one in the biomedical domain. We also provide a subset of BioRead, BioReadLite, for research groups with fewer computational resources. We re-implemented and tested on BioReadLite two well-known MRC methods, AS Reader and AOA Reader, along with four baselines, as a first step towards a BioRead (and BioReadLite) leaderboard. AOA Reader is currently the best method on BioReadLite, with 51.19% test accuracy. Both AOA Reader and AS Reader outperform the baselines by a wide margin on the test subset of BioReadLite. Our re-implementations of the two MRC methods are also publicly available.
Topics Question Answering, Statistical And Machine Learning Methods, Corpus (Creation, Annotation, Etc.)
Full paper BioRead: A New Dataset for Biomedical Reading Comprehension
Bibtex @InProceedings{PAPPAS18.795,
  author = {Dimitris Pappas and Ion Androutsopoulos and Haris Papageorgiou},
  title = "{BioRead: A New Dataset for Biomedical Reading Comprehension}",
  booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)},
  year = {2018},
  month = {May 7-12, 2018},
  address = {Miyazaki, Japan},
  editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {979-10-95546-00-9},
  language = {english}
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