| """PHEE: A Dataset for Pharmacovigilance Event Extraction from Text""" | |
| import json | |
| import datasets | |
| from datasets.tasks import LanguageModeling | |
| logger = datasets.logging.get_logger(__name__) | |
| _CITATION = """\ | |
| @misc{sun2022phee, | |
| title={PHEE: A Dataset for Pharmacovigilance Event Extraction from Text}, | |
| author={Zhaoyue Sun and Jiazheng Li and Gabriele Pergola and Byron C. Wallace and Bino John and Nigel Greene and Joseph Kim and Yulan He}, | |
| year={2022}, | |
| eprint={2210.12560}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CL} | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| Data and Code for [``PHEE: A Dataset for Pharmacovigilance Event Extraction from Text``](https://arxiv.org/abs/2210.12560/)\ | |
| """ | |
| _URL = "https://raw.githubusercontent.com/ZhaoyueSun/PHEE/ceea192bc1f1da306980c39e53767176b1f8caec/data/json/" | |
| _URLS = { | |
| "train": _URL + "train.json", | |
| "test": _URL + "test.json", | |
| "dev": _URL + "dev.json", | |
| } | |
| class PHEEConfig(datasets.BuilderConfig): | |
| """BuilderConfig for PHEE.""" | |
| def __init__(self, **kwargs): | |
| """BuilderConfig for PHEE. | |
| Args: | |
| **kwargs: keyword arguments forwarded to super. | |
| """ | |
| super(PHEEConfig, self).__init__(**kwargs) | |
| class PHEE(datasets.GeneratorBasedBuilder): | |
| """PHEE: A Dataset for Pharmacovigilance Event Extraction from Text""" | |
| BUILDER_CONFIGS = [ | |
| PHEEConfig( | |
| name="json", | |
| version=datasets.Version("1.0.0", ""), | |
| description="processed structured data", | |
| ), | |
| ] | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| homepage="https://github.com/ZhaoyueSun/PHEE", | |
| features=datasets.Features( | |
| { | |
| "id": datasets.Value("string"), | |
| "context": datasets.Value("string"), | |
| "is_mult_event": datasets.Value("bool"), | |
| "annotations": [ | |
| { | |
| "events": [ | |
| { | |
| "event_id": datasets.Value("string"), | |
| "event_type": datasets.Value("string"), | |
| "event_data": datasets.Value("string"), | |
| } | |
| ] | |
| } | |
| ], | |
| } | |
| ), | |
| citation=_CITATION, | |
| task_templates=[ | |
| LanguageModeling( | |
| text_column="context", | |
| ) | |
| ], | |
| ) | |
| def _split_generators(self, dl_manager): | |
| downloaded_files = dl_manager.download_and_extract(_URLS) | |
| return [ | |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}), | |
| datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}), | |
| datasets.SplitGenerator(name='dev', gen_kwargs={"filepath": downloaded_files["dev"]}), | |
| ] | |
| def _generate_examples(self, filepath): | |
| """This function returns the examples parsed from json.""" | |
| logger.info("generating examples from = %s", filepath) | |
| with open(filepath, encoding="utf-8") as f: | |
| for key, line in enumerate(f): | |
| obs = json.loads(line) | |
| yield key, { | |
| "id": obs["id"], | |
| "context": obs["context"], | |
| "is_mult_event": obs["is_mult_event"], | |
| "annotations": [ | |
| { | |
| "events": [ | |
| { | |
| "event_id": event["event_id"], | |
| "event_type": event["event_type"], | |
| "event_data": json.dumps(event), | |
| } | |
| for event in annotation["events"]] | |
| } | |
| for annotation in obs["annotations"]], | |
| } | |