Datasets:
Tasks:
Question Answering
Sub-tasks:
closed-domain-qa
Languages:
Russian
Multilinguality:
monolingual
Size Categories:
100K<n<1M
Source Datasets:
original
Tags:
License:
| # coding=utf-8 | |
| # Copyright 2020 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. | |
| """Russian Q&A posts from a medical related forum""" | |
| import csv | |
| import datasets | |
| _DESCRIPTION = """\ | |
| This dataset contains 190,335 Russian Q&A posts from a medical related forum. | |
| """ | |
| class MedicalQARuData(datasets.GeneratorBasedBuilder): | |
| def _info(self): | |
| features = datasets.Features( | |
| { | |
| "date": datasets.Value("string"), | |
| "categ": datasets.Value("string"), | |
| "theme": datasets.Value("string"), | |
| "desc": datasets.Value("string"), | |
| "ans": datasets.Value("string"), | |
| "spec10": datasets.Value("string"), | |
| } | |
| ) | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=features, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| urls_to_download = { | |
| "train": "medical_qa_ru_data.csv" | |
| } | |
| downloaded_files = dl_manager.download_and_extract(urls_to_download) | |
| return [ | |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}) | |
| ] | |
| #data_file = dl_manager.download_and_extract(_URL) | |
| #return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_file})] | |
| def _generate_examples(self, filepath): | |
| """Yields examples.""" | |
| with open(filepath, encoding="utf-8") as f: | |
| data = csv.reader(f) | |
| for id_, row in enumerate(data): | |
| if id_>0: | |
| yield id_, { | |
| "date": row[0], | |
| "categ": row[1], | |
| "theme": row[2], | |
| "desc": row[3], | |
| "ans": row[4], | |
| "spec10": row[5], | |
| } |