Datasets:

GEM
/

cochrane-simplification

	import csv
	import json
	import os
	import datasets

	_CITATION = """\
	@inproceedings{devaraj-etal-2021-paragraph,
	title = "Paragraph-level Simplification of Medical Texts",
	author = "Devaraj, Ashwin and
	Marshall, Iain and
	Wallace, Byron and
	Li, Junyi Jessy",
	booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
	month = jun,
	year = "2021",
	address = "Online",
	publisher = "Association for Computational Linguistics",
	url = "https://aclanthology.org/2021.naacl-main.395",
	doi = "10.18653/v1/2021.naacl-main.395",
	pages = "4972--4984",
	}
	"""

	_DESCRIPTION = """\
	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.
	"""

	_URLs = {
	"train": "train.json",
	"validation": "validation.json",
	"test": "test.json",
	}


	class Cochrane(datasets.GeneratorBasedBuilder):
	VERSION = datasets.Version("1.0.0")
	DEFAULT_CONFIG_NAME = "cochrane-simplification"

	def _info(self):
	features = datasets.Features(
	{
	"gem_id": datasets.Value("string"),
	"gem_parent_id": datasets.Value("string"),
	"source": datasets.Value("string"),
	"target": datasets.Value("string"),
	"doi": datasets.Value("string"),
	"references": [datasets.Value("string")],
	}
	)
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	supervised_keys=datasets.info.SupervisedKeysData(
	input="source", output="target"
	),
	homepage="https://github.com/AshOlogn/Paragraph-level-Simplification-of-Medical-Texts ",
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	dl_dir = dl_manager.download_and_extract(_URLs)
	return [
	datasets.SplitGenerator(
	name=spl, gen_kwargs={"filepath": dl_dir[spl], "split": spl}
	)
	for spl in ["train", "validation", "test"]
	]

	def _generate_examples(self, filepath, split):
	"""Yields examples."""
	with open(filepath, encoding="utf-8") as f:
	reader = json.load(f)
	for id_, example in enumerate(reader):
	yield id_, {
	"gem_id": f"cochrane-simplification-{split}-{id_}",
	"gem_parent_id": f"cochrane-simplification-{split}-{id_}",
	"source": example["source"],
	"target": example["target"],
	"doi": example["doi"],
	"references": [example["target"]],
	}