Datasets:
caner

@@ -1,122 +0,0 @@
-# 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.
-"""A new corpus of tagged data that can be useful for handling the issues in recognition of Classical Arabic named entities"""
-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"
-# TODO: Add the licence for the dataset here if you can find it
-_LICENSE = ""
-_URL = "https://raw.githubusercontent.com/RamziSalah/Classical-Arabic-Named-Entity-Recognition-Corpus/master/CANERCorpus.csv"
-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=[
-                        "Allah",
-                        "Book",
-                        "Clan",
-                        "Crime",
-                        "Date",
-                        "Day",
-                        "Hell",
-                        "Loc",
-                        "Meas",
-                        "Mon",
-                        "Month",
-                        "NatOb",
-                        "Number",
-                        "O",
-                        "Org",
-                        "Para",
-                        "Pers",
-                        "Prophet",
-                        "Rlig",
-                        "Sect",
-                        "Time",
-                    ]
-                ),
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        data_path = dl_manager.download(_URL)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": data_path,
-                },
-            )
-        ]
-    def _generate_examples(self, filepath):
-        """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],
-                }