PEYMA.py

import json
import pandas as pd
import datasets
import requests
import os

_CITATION = """\\
@article{shahshahani2018peyma,
    title={PEYMA: A Tagged Corpus for Persian Named Entities},
    author={Mahsa Sadat Shahshahani and Mahdi Mohseni and Azadeh Shakery and Heshaam Faili},
    year=2018,
    journal={ArXiv},
    volume={abs/1801.09936}
}
"""
_DESCRIPTION = """\\\\\\\\
PEYMA dataset includes 7,145 sentences with a total of 302,530 tokens from which 41,148 tokens are tagged with seven different classes.
"""

_DRIVE_URL = "https://drive.google.com/uc?export=download&id=1WZxpFRtEs5HZWyWQ2Pyg9CCuIBs1Kmvx"

class PEYMAConfig(datasets.BuilderConfig):
    """BuilderConfig for PEYMA."""
    def __init__(self, **kwargs):
        super(PEYMAConfig, self).__init__(**kwargs)
        
class PEYMA(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [
        PEYMAConfig(name="PEYMA", version=datasets.Version("1.0.0"), description="persian ner dataset"),
    ]
    def _info(self):
        return datasets.DatasetInfo(
            # This is the description that will appear on the datasets page.
            description=_DESCRIPTION,
            # datasets.features.FeatureConnectors
            features=datasets.Features(
                {
                    "token": datasets.Value("string"),
                    "label": datasets.Value("string")
                }
            ),
            supervised_keys=None,
            # Homepage of the dataset for documentation
            homepage="https://hooshvare.github.io/docs/datasets/ner#peyma",
            citation=_CITATION,
        )

    def custom_dataset(self, src_url, dest_path):
        response = requests.get(src_url)
        response.raise_for_status()

        with open(dest_path, 'wb') as f:
            f.write(response.content)

        
    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        # dl_manager is a datasets.download.DownloadManager that can be used to
        # download and extract URLs
    
        downloaded_file = dl_manager.download_custom(_DRIVE_URL, self.custom_dataset)
        extracted_file = dl_manager.extract(downloaded_file)
        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(extracted_file, 'peyma/train.txt')}),
            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": os.path.join(extracted_file, 'peyma/test.txt')}),
            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": os.path.join(extracted_file, 'peyma/dev.txt')}),
        ]

    def _generate_examples(self, filepath):
        try:
            df = pd.read_csv(filepath, error_bad_lines=False, engine='python', 
            sep='|', names=["token", "label"])
            for idx, row in enumerate(reader):
                yield idx, {
                    "token": row["token"],
                    "label": row["label"]
                }
        except Exception as e:
            print(e)