Update files from the datasets library (from 1.4.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.4.0
README.md
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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##
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- **Homepage:** [http://nlp.cs.aueb.gr/](http://nlp.cs.aueb.gr/)
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- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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- **Size of the generated dataset:** 5539.64 MB
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- **Total amount of disk used:** 6765.92 MB
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###
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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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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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##
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We show detailed information for up to 5 configurations of the dataset.
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###
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#### biomrc_large_A
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}
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```
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###
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The data fields are the same among all splits.
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- `entities_list`: a `list` of `string` features.
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- `answer`: a `string` feature.
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###
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#### biomrc_large_A
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|-------------|---:|
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|biomrc_tiny_A| 30|
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##
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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##
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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##
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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###
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```
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@inproceedings{pappas-etal-2020-biomrc,
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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## Dataset Description
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- **Homepage:** [http://nlp.cs.aueb.gr/](http://nlp.cs.aueb.gr/)
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- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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- **Size of the generated dataset:** 5539.64 MB
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- **Total amount of disk used:** 6765.92 MB
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### Dataset Summary
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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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### Supported Tasks
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Languages
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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## Dataset Structure
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We show detailed information for up to 5 configurations of the dataset.
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### Data Instances
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#### biomrc_large_A
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}
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```
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### Data Fields
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The data fields are the same among all splits.
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- `entities_list`: a `list` of `string` features.
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- `answer`: a `string` feature.
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### Data Splits Sample Size
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#### biomrc_large_A
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|-------------|---:|
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|biomrc_tiny_A| 30|
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## Dataset Creation
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### Curation Rationale
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Source Data
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Annotations
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Personal and Sensitive Information
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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## Considerations for Using the Data
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### Social Impact of Dataset
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Discussion of Biases
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Other Known Limitations
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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## Additional Information
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### Dataset Curators
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Licensing Information
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Citation Information
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```
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@inproceedings{pappas-etal-2020-biomrc,
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biomrc.py
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from __future__ import absolute_import, division, print_function
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import json
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import logging
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import datasets
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_CITATION = """\
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@inproceedings{pappas-etal-2020-biomrc,
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title = "{B}io{MRC}: A Dataset for Biomedical Machine Reading Comprehension",
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self.biomrc_setting = "B"
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else:
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if biomrc_setting.lower() != "a":
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self.biomrc_setting = "A"
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if biomrc_version.lower() == "small":
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self.biomrc_version = "tiny"
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else:
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if biomrc_version.lower() != "large":
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self.biomrc_version = "large"
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super(BiomrcConfig, self).__init__(**kwargs)
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def _generate_examples(self, filepath):
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"""This function returns the examples in the raw (text) form."""
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# Id for the biomrc dataset
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with open(filepath, encoding="utf-8") as fp:
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biomrc = json.load(fp)
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from __future__ import absolute_import, division, print_function
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import json
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import datasets
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logger = datasets.logging.get_logger(__name__)
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_CITATION = """\
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@inproceedings{pappas-etal-2020-biomrc,
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title = "{B}io{MRC}: A Dataset for Biomedical Machine Reading Comprehension",
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self.biomrc_setting = "B"
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else:
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if biomrc_setting.lower() != "a":
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logger.warning("Wrong Setting for BioMRC, using Setting A instead.")
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self.biomrc_setting = "A"
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if biomrc_version.lower() == "small":
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self.biomrc_version = "tiny"
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else:
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if biomrc_version.lower() != "large":
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logger.warning("Wrong version for BioMRC, using BioMRC Large instead.")
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self.biomrc_version = "large"
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super(BiomrcConfig, self).__init__(**kwargs)
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def _generate_examples(self, filepath):
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"""This function returns the examples in the raw (text) form."""
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logger.info("generating examples from = %s", filepath)
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# Id for the biomrc dataset
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with open(filepath, encoding="utf-8") as fp:
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biomrc = json.load(fp)
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