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import csv |
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import json |
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import os |
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import datasets |
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_CITATION = """\ |
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@inproceedings{devaraj-etal-2021-paragraph, |
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title = "Paragraph-level Simplification of Medical Texts", |
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author = "Devaraj, Ashwin and |
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Marshall, Iain and |
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Wallace, Byron and |
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Li, Junyi Jessy", |
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booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies", |
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month = jun, |
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year = "2021", |
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address = "Online", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/2021.naacl-main.395", |
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doi = "10.18653/v1/2021.naacl-main.395", |
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pages = "4972--4984", |
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} |
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""" |
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_DESCRIPTION = """\ |
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This dataset measures the ability for a model to simplify paragraphs of medical text through the omission non-salient information and simplification of medical jargon. |
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""" |
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_URLs = { |
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"train": "train.json", |
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"validation": "validation.json", |
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"test": "test.json", |
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} |
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class Cochrane(datasets.GeneratorBasedBuilder): |
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VERSION = datasets.Version("1.0.0") |
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DEFAULT_CONFIG_NAME = "cochrane-simplification" |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"gem_id": datasets.Value("string"), |
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"gem_parent_id": datasets.Value("string"), |
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"source": datasets.Value("string"), |
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"target": datasets.Value("string"), |
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"doi": datasets.Value("string"), |
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"references": [datasets.Value("string")], |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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supervised_keys=datasets.info.SupervisedKeysData( |
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input="source", output="target" |
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), |
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homepage="https://github.com/AshOlogn/Paragraph-level-Simplification-of-Medical-Texts ", |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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dl_dir = dl_manager.download_and_extract(_URLs) |
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return [ |
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datasets.SplitGenerator( |
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name=spl, gen_kwargs={"filepath": dl_dir[spl], "split": spl} |
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) |
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for spl in ["train", "validation", "test"] |
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] |
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def _generate_examples(self, filepath, split): |
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"""Yields examples.""" |
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with open(filepath, encoding="utf-8") as f: |
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reader = json.load(f) |
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for id_, example in enumerate(reader): |
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yield id_, { |
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"gem_id": f"cochrane-simplification-{split}-{id_}", |
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"gem_parent_id": f"cochrane-simplification-{split}-{id_}", |
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"source": example["source"], |
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"target": example["target"], |
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"doi": example["doi"], |
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"references": [example["target"]], |
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} |
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