Datasetpublic

PerSets/iran-legal-persian-qa

Iranian Legal Question Answering Dataset (Farsi) This dataset includes over 600K questions and 2M answers, all in written form. The questions were posed by ordinary Persian speakers (Iranians), while the responses were provided by attorneys from various specialties. Dataset Description Question records without corresponding answers have been excluded from the dataset. This dataset will be updated periodically with new records. The reference for this dataset is… See the full description on the dataset page: https://huggingface.co/datasets/PerSets/iran-legal-persian-qa.

sourceHugging Faceccupdated 1y agoView on Hugging Face

7likes591downloads

Dataset Card

Iranian Legal Question Answering Dataset (Farsi)

This dataset includes over 600K questions and 2M answers, all in written form. The questions were posed by ordinary Persian speakers (Iranians), while the responses were provided by attorneys from various specialties.

Dataset Description

Question records without corresponding answers have been excluded from the dataset.

This dataset will be updated periodically with new records.

The reference for this dataset is dadrah.ir website.

Usage

Huggingface datasets library:

python

from datasets import load_dataset
dataset = load_dataset('PerSets/iran-legal-persian-qa')

Pandas library:

python

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: <br> (very slow - not recommended)

python

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)

</details>

License

CC0