Commit
•
8c2e675
1
Parent(s):
63c373d
Host data files (#2)
Browse files- Add data files in JSON Lines (96fe571ae68c0b714555fe29333b8c0ba0514943)
- Use hosted data files in JSON Lines format (83429ebe1a3f8b76896d83aa77708c27f1db7133)
- biomrc.py +21 -24
- data/biomrc_large/dataset_test.jsonl.gz +3 -0
- data/biomrc_large/dataset_test_B.jsonl.gz +3 -0
- data/biomrc_large/dataset_train.jsonl.gz +3 -0
- data/biomrc_large/dataset_train_B.jsonl.gz +3 -0
- data/biomrc_large/dataset_val.jsonl.gz +3 -0
- data/biomrc_large/dataset_val_B.jsonl.gz +3 -0
- data/biomrc_small/dataset_test_small.jsonl.gz +3 -0
- data/biomrc_small/dataset_test_small_B.jsonl.gz +3 -0
- data/biomrc_small/dataset_train_small.jsonl.gz +3 -0
- data/biomrc_small/dataset_train_small_B.jsonl.gz +3 -0
- data/biomrc_small/dataset_val_small.jsonl.gz +3 -0
- data/biomrc_small/dataset_val_small_B.jsonl.gz +3 -0
- data/biomrc_tiny/dataset_tiny.jsonl.gz +3 -0
- data/biomrc_tiny/dataset_tiny_B.jsonl.gz +3 -0
biomrc.py
CHANGED
@@ -21,7 +21,6 @@ import json
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import datasets
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logger = datasets.logging.get_logger(__name__)
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@@ -47,6 +46,22 @@ _DESCRIPTION = """\
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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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class BiomrcConfig(datasets.BuilderConfig):
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"""BuilderConfig for BioMRC."""
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@@ -143,23 +158,9 @@ class Biomrc(datasets.GeneratorBasedBuilder):
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def _split_generators(self, dl_manager):
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setting = "" if self.config.biomrc_setting == "A" else "_B"
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"val": f"https://archive.org/download/biomrc_dataset/biomrc_large/dataset_val{setting}.json.gz",
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"test": f"https://archive.org/download/biomrc_dataset/biomrc_large/dataset_test{setting}.json.gz",
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}
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elif self.config.biomrc_version == "small":
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urls_to_download = {
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"train": f"https://archive.org/download/biomrc_dataset/biomrc_small/dataset_train_small{setting}.json.gz",
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"val": f"https://archive.org/download/biomrc_dataset/biomrc_small/dataset_val_small{setting}.json.gz",
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"test": f"https://archive.org/download/biomrc_dataset/biomrc_small/dataset_test_small{setting}.json.gz",
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}
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else:
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urls_to_download = {
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"test": f"https://archive.org/download/biomrc_dataset/biomrc_tiny/dataset_tiny{setting}.json.gz"
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}
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downloaded_files = dl_manager.download_and_extract(urls_to_download)
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if self.config.biomrc_version == "tiny":
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@@ -178,10 +179,6 @@ class Biomrc(datasets.GeneratorBasedBuilder):
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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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zip(biomrc["abstracts"], biomrc["titles"], biomrc["entities_list"], biomrc["answers"])
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):
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yield _id, {"abstract": ab, "title": ti, "entities_list": el, "answer": an}
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import datasets
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logger = datasets.logging.get_logger(__name__)
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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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_URLS = {
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"large": {
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"train": "data/biomrc_large/dataset_train{setting}.jsonl.gz",
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"val": "data/biomrc_large/dataset_val{setting}.jsonl.gz",
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"test": "data/biomrc_large/dataset_test{setting}.jsonl.gz",
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},
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"small": {
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"train": "data/biomrc_small/dataset_train_small{setting}.jsonl.gz",
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"val": "data/biomrc_small/dataset_val_small{setting}.jsonl.gz",
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"test": "data/biomrc_small/dataset_test_small{setting}.jsonl.gz",
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},
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"tiny": {
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"test": "data/biomrc_tiny/dataset_tiny{setting}.jsonl.gz",
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},
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}
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class BiomrcConfig(datasets.BuilderConfig):
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"""BuilderConfig for BioMRC."""
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def _split_generators(self, dl_manager):
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setting = "" if self.config.biomrc_setting == "A" else "_B"
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urls_to_download = {
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split: url.format(setting=setting) for split, url in _URLS[self.config.biomrc_version].items()
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}
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downloaded_files = dl_manager.download_and_extract(urls_to_download)
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if self.config.biomrc_version == "tiny":
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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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with open(filepath, encoding="utf-8") as fp:
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for idx, example in enumerate(fp):
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yield idx, json.loads(example)
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data/biomrc_large/dataset_test.jsonl.gz
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:f745d3c0dd4cc6a2f795ef06ab8156d09555b6d9987b723db9ca845dd428a21c
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size 33922627
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data/biomrc_large/dataset_test_B.jsonl.gz
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:9e0cc7821972a394b65ce95a4082ba265553bcdcb74c6fd8eef9bc927a563717
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size 27883744
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data/biomrc_large/dataset_train.jsonl.gz
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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size 377220119
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data/biomrc_large/dataset_train_B.jsonl.gz
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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size 309771578
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data/biomrc_large/dataset_val.jsonl.gz
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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size 27416109
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data/biomrc_large/dataset_val_B.jsonl.gz
ADDED
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version https://git-lfs.github.com/spec/v1
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size 22591623
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data/biomrc_small/dataset_test_small.jsonl.gz
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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data/biomrc_small/dataset_test_small_B.jsonl.gz
ADDED
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version https://git-lfs.github.com/spec/v1
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data/biomrc_small/dataset_train_small.jsonl.gz
ADDED
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version https://git-lfs.github.com/spec/v1
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data/biomrc_small/dataset_train_small_B.jsonl.gz
ADDED
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data/biomrc_small/dataset_val_small.jsonl.gz
ADDED
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data/biomrc_small/dataset_val_small_B.jsonl.gz
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data/biomrc_tiny/dataset_tiny.jsonl.gz
ADDED
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data/biomrc_tiny/dataset_tiny_B.jsonl.gz
ADDED
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