README.md

metadata

language: fa
pretty_name: Clinical Question Answering Dataset II (Farsi)
tags:
  - Farsi
  - Persian
  - clinic
  - QA
  - question
  - answer
task_categories:
  - question-answering
license: cc

Clinical Question Answering Dataset II (Farsi)

This dataset contains more than 211k questions and more than 700k answers, all produced in written form. The questions were posed by ordinary Persian speakers (Iranians), and the responses were provided by doctors from various specialties.

Dataset Description

Question records without corresponding answers have been excluded from the dataset. This dataset is NOT a part of Clinical Question Answering I dataset and is a whole different dataset.

This dataset will be updated periodically with new records.

The reference for this dataset is drhast.com website.

Usage

Huggingface datasets library:

from datasets import load_dataset
dataset = load_dataset('PerSets/clinical-persian-qa-ii')

Pandas library:

import pandas
import os

data_files = [file for file in os.listdir() if file.startswith("train") and file.endswith(".jsonl")]
df = pd.DataFrame()
for file in data_files:
    df = pd.concat([df, pd.read_json(file, lines=True)], ignore_index=True)

Vanilla Python:
(very slow - not recommended)

import json
import os

data_files = [file for file in os.listdir() if file.startswith("train") and file.endswith(".jsonl")]

train = []
for file in data_files:
    with open(file, encoding="utf-8") as f:
        for line in f:
            obj = json.loads(line)
            train.append(obj)

License

CC0