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# coding=utf-8 | ||
# Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor. | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
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""" | ||
A dataset loader for the n2c2 community-annotated Why Questions dataset. | ||
https://portal.dbmi.hms.harvard.edu/projects/n2c2-nlp/ | ||
The dataset consists of a single archive (no splits) and it is available | ||
as a JSON file and as an XLSX file: | ||
- relations_whyqa_ann-v7-share.json (in SQUAD 2.0 format) | ||
- relations_whyqa_ann-v7-share.xlsx | ||
The dataset also includes TXT files with the full texts of the | ||
clinical notes. | ||
The files comprising this dataset must be on the users local machine | ||
in a single directory that is passed to `datasets.load_dataset` via | ||
the `data_dir` kwarg. This loader script will read the archive files | ||
directly (i.e. the user should not uncompress, untar or unzip any of | ||
the files). | ||
Registration AND submission of DUA is required to access the dataset. | ||
[bigbio_schema_name] = qa | ||
""" | ||
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import os | ||
import zipfile | ||
import json | ||
from collections import defaultdict | ||
from typing import List, Tuple, Dict | ||
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import datasets | ||
from utils import schemas | ||
from utils.configs import BigBioConfig | ||
from utils.constants import Tasks | ||
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# TODO: Add BibTeX citation | ||
_CITATION = """\ | ||
@inproceedings{, | ||
author = {Annotating and Characterizing Clinical Sentences with Explicit Why-{QA} Cues}, | ||
title = {Fan, Jungwei}, | ||
booktitle = {Proceedings of the 2nd Clinical Natural Language Processing Workshop}, | ||
month = {jun}, | ||
year = {2019}, | ||
address = {Minneapolis, Minnesota, USA}, | ||
publisher = {Association for Computational Linguistics}, | ||
url = {https://aclanthology.org/W19-1913}, | ||
doi = {10.18653/v1/W19-1913} | ||
} | ||
} | ||
""" | ||
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_DATASETNAME = "[why_qa]" | ||
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# TODO: Add description of the dataset here | ||
# You can copy an official description | ||
_DESCRIPTION = """\ | ||
This dataset is a collection of why-questions and their answers generated | ||
from a corpus of clincal notes. The corpus is the 2010 i2b2/VA NLP | ||
challenge and consists of 426 discharge summaries from Partners | ||
Healthcare and Beth Israel Deaconess Medical Center. | ||
""" | ||
_HOMEPAGE = "https://portal.dbmi.hms.harvard.edu/projects/n2c2-nlp/" | ||
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_LICENSE = "External Data User Agreement" | ||
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_SUPPORTED_TASKS = [Tasks.QUESTION_ANSWERING] | ||
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_SOURCE_VERSION = "1.0.0" | ||
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_BIGBIO_VERSION = "1.0.0" | ||
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def read_zip_file(file_path): | ||
with zipfile.ZipFile(file_path) as zf: | ||
with zf.open("n2c2-community-annotations_2010-fan-why-QA/relations_whyqa_ann-v7-share.json") as f: | ||
dataset = json.load(f) | ||
return dataset | ||
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def _get_samples(dataset): | ||
samples = dataset['data'][0]['paragraphs'] | ||
return samples | ||
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# TODO: Name the dataset class to match the script name using CamelCase instead of snake_case | ||
# Append "Dataset" to the class name: BioASQ --> BioasqDataset | ||
class WhyQaDataset(datasets.GeneratorBasedBuilder): | ||
"""n2c2 community-annotated Why Questions dataset.""" | ||
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SOURCE_VERSION = datasets.Version(_SOURCE_VERSION) | ||
BIGBIO_VERSION = datasets.Version(_BIGBIO_VERSION) | ||
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BUILDER_CONFIGS = [ | ||
BigBioConfig( | ||
name="why_qa_source", | ||
version=SOURCE_VERSION, | ||
description="why_qa source schema", | ||
schema="source", | ||
subset_id="why_qa", | ||
), | ||
BigBioConfig( | ||
name="why_qa_bigbio_qa", | ||
version=BIGBIO_VERSION, | ||
description="why_wa BigBio schema", | ||
schema="bigbio_qa", | ||
subset_id="why_qa", | ||
), | ||
] | ||
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DEFAULT_CONFIG_NAME = "why_qa_source" | ||
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def _info(self) -> datasets.DatasetInfo: | ||
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if self.config.schema == "source": | ||
features = datasets.Features( | ||
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{ | ||
"note_id": datasets.Value("string"), | ||
"qas": [ | ||
{"question_template": datasets.Value("string"), | ||
"question": datasets.Value("string"), | ||
"id": datasets.Value("string"), | ||
"answers": [ | ||
{"text": datasets.Value("string"), | ||
"answer_start": datasets.Value("int32"), | ||
}, | ||
], | ||
"is_impossible": datasets.Value("bool"), | ||
}, | ||
], | ||
"context": datasets.Value("string"), | ||
}, | ||
) | ||
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elif self.config.schema == "bigbio_qa": | ||
features = schemas.qa_features | ||
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return datasets.DatasetInfo( | ||
description=_DESCRIPTION, | ||
features=features, | ||
homepage=_HOMEPAGE, | ||
license=_LICENSE, | ||
citation=_CITATION, | ||
) | ||
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def _split_generators(self, dl_manager) -> List[datasets.SplitGenerator]: | ||
"""Returns SplitGenerators.""" | ||
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if self.config.data_dir is None: | ||
raise ValueError("This is a local dataset. Please pass the data_dir kwarg to load_dataset.") | ||
else: | ||
data_dir = self.config.data_dir | ||
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return [ | ||
datasets.SplitGenerator( | ||
name=datasets.Split.TRAIN, | ||
# Whatever you put in gen_kwargs will be passed to _generate_examples | ||
gen_kwargs={ | ||
"data_dir": data_dir, | ||
"split": "train", | ||
}, | ||
), | ||
] | ||
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def _generate_examples(self, data_dir, split: str) -> Tuple[int, Dict]: | ||
"""Yields examples as (key, example) tuples.""" | ||
dataset = read_zip_file(data_dir) | ||
samples = _get_samples(dataset) | ||
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if self.config.schema == "source": | ||
_id = 0 | ||
for sample in samples: | ||
yield _id, sample | ||
_id += 1 | ||
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elif self.config.schema == "bigbio_[bigbio_schema_name]": | ||
_id = 0 | ||
for sample in samples: | ||
for qa in sample['qas']: | ||
ans_list = [] | ||
for answer in qa["answer"]: | ||
ans = answer["text"] | ||
ans_list.append(ans) | ||
bigbio_sample = { | ||
"id" : qa["note_id"], | ||
"question_id" : qa["id"], | ||
"document_id" : sample["note_id"], | ||
"question" : qa["question"], | ||
"type" : qa["question_template"], | ||
"choices" : [], | ||
"context" : sample["context"], | ||
"answer" : ans_list, | ||
} | ||
yield _id, bigbio_sample | ||
_id += 1 | ||
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# This template is based on the following template from the datasets package: | ||
# https://github.com/huggingface/datasets/blob/master/templates/new_dataset_script.py |