caner_replicate.py

# -*- coding: utf-8 -*-
"""caner_replicate.ipynb

Automatically generated by Colaboratory.

Original file is located at
    https://colab.research.google.com/drive/1QgToSf5_B5l43oRCKwI2vGEB0YcRUtHe
"""

import csv
import os

import datasets


_CITATION = """\
@article{article,
author = {Salah, Ramzi and Zakaria, Lailatul},
year = {2018},
month = {12},
pages = {},
title = {BUILDING THE CLASSICAL ARABIC NAMED ENTITY RECOGNITION CORPUS (CANERCORPUS)},
volume = {96},
journal = {Journal of Theoretical and Applied Information Technology}
}
"""

_DESCRIPTION = """\
Classical Arabic Named Entity Recognition corpus as a new corpus of tagged data that can be useful for handling the issues in recognition of Arabic named entities.
"""

_HOMEPAGE = "https://github.com/RamziSalah/Classical-Arabic-Named-Entity-Recognition-Corpus"
_HOMEPAGE = "https://github.com/omarmohamed2011/caner_data_copy"
# TODO: Add the licence for the dataset here if you can find it
_LICENSE = ""

#_URL = "https://github.com/RamziSalah/Classical-Arabic-Named-Entity-Recognition-Corpus/archive/master.zip"
_URL  = 'https://github.com/omarmohamed2011/caner_data_copy/blob/main/df_caner.zip'

class Caner(datasets.GeneratorBasedBuilder):
    """Classical Arabic Named Entity Recognition corpus as a new corpus of tagged data that can be useful for handling the issues in recognition of Arabic named entities"""

    VERSION = datasets.Version("1.1.0")

    def _info(self):

        features = datasets.Features(
            {
                "token": datasets.Value("string"),
                "ner_tag": datasets.ClassLabel(
                names =['MalikIbnAnas',
                         'Sibawayh',
                         'IbnHisham',
                         'IbnSulaymanKufi',
                         'Bukhari',
                         'KhalilFarahidi',
                         'FathIbnKhaqan',
                         'IbnHamzaKisai',
                         'IbnTayfur',
                         'MuhammadBarjlani',
                         'ImamCaskari',
                         'AbdAllahIbnCabbas',
                         'IbnAyyubRazi',
                         'IbnWaddahQurtubi',
                         'HasanBasri',
                         'IbnAbiKhaythama',
                         'YahyaIbnHusayn',
                         'SufyanThawri',
                         'IbnQuraybAsmaci',
                         'IbnIsmacilKirmani',
                         'IbnCimranMawsili',
                         'Mubarrad',
                         'MuhammadShaybani',
                         'AbuZurcaDimashqi',
                         'IbnWahbQurashi',
                         'MacmarIbnMuthanna',
                         'YahyaIbnSalam',
                         'AbuHasanSacdi',
                         'IbnIbrahimBursi',
                         'IbnSirin',
                         'Baladhuri',
                         'CaliIbnAbiTalib',
                         'IbnZiyadFarra',
                         'AbuYusufYacqub',
                         'IbnHanbal',
                         'ZubayrIbnBakkar',
                         'AbuBakrBazzar',
                         'Fakihi',
                         'IbnMuzahimMinqari',
                         'AbyZurca',
                         'AkhfashAwsat',
                         'AhmadBarqi',
                         'IbnAhmadIbnHanbal',
                         'IbnCabdHakam',
                         'CabdRazzakSancani',
                         'AbuHatimSijistani',
                         'IbnSacd',
                         'IbnHammadKhuzaci',
                         'IbnCaliMarwazi',
                         'MujahidIbnJabr',
                         'Bahshal',
                         'IbnHasanSaffar']

                ),
            }
        )

        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            supervised_keys=None,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""

        my_urls = _URL
        data_dir = dl_manager.download_and_extract(my_urls)
        
        data_dir = '/content/df_caner.csv'
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                # These kwargs will be passed to _generate_examples
               
                gen_kwargs={
                    "filepath": data_dir,
                    #os.path.join(   data_dir, "/df_caner.csv"),
                    "split": "train",
                },
            )
        ]

    def _generate_examples(self, filepath, split):
        """Yields examples."""

        with open(filepath, encoding="utf-8") as csv_file:
            reader = csv.reader(csv_file, delimiter=",")
            next(reader, None)

            for id_, row in enumerate(reader):

                yield id_, {
                    "token": row[0],
                    "ner_tag": row[1],
                }