Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Languages:
Arabic
Size:
10K - 100K
Tags:
poetry-classification
License:
# coding=utf-8 | |
# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors. | |
# | |
# 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. | |
# Lint as: python3 | |
"""Arabic Poetry Metric dataset.""" | |
import os | |
import datasets | |
_DESCRIPTION = """\ | |
Arabic Poetry Metric Classification. | |
The dataset contains the verses and their corresponding meter classes.\ | |
Meter classes are represented as numbers from 0 to 13. \ | |
The dataset can be highly useful for further research in order to improve the field of Arabic poems’ meter classification.\ | |
The train dataset contains 47,124 records and the test dataset contains 8316 records. | |
""" | |
_CITATION = """\ | |
@article{metrec2020, | |
title={MetRec: A dataset for meter classification of arabic poetry}, | |
author={Al-shaibani, Maged S and Alyafeai, Zaid and Ahmad, Irfan}, | |
journal={Data in Brief}, | |
year={2020}, | |
publisher={Elsevier} | |
} | |
""" | |
_DOWNLOAD_URL = "https://raw.githubusercontent.com/zaidalyafeai/MetRec/master/baits.zip" | |
class MetRecConfig(datasets.BuilderConfig): | |
"""BuilderConfig for MetRec.""" | |
def __init__(self, **kwargs): | |
"""BuilderConfig for MetRec. | |
Args: | |
**kwargs: keyword arguments forwarded to super. | |
""" | |
super(MetRecConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs) | |
class Metrec(datasets.GeneratorBasedBuilder): | |
"""Metrec dataset.""" | |
BUILDER_CONFIGS = [ | |
MetRecConfig( | |
name="plain_text", | |
description="Plain text", | |
) | |
] | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=datasets.Features( | |
{ | |
"text": datasets.Value("string"), | |
"label": datasets.features.ClassLabel( | |
names=[ | |
"saree", | |
"kamel", | |
"mutakareb", | |
"mutadarak", | |
"munsareh", | |
"madeed", | |
"mujtath", | |
"ramal", | |
"baseet", | |
"khafeef", | |
"taweel", | |
"wafer", | |
"hazaj", | |
"rajaz", | |
] | |
), | |
} | |
), | |
supervised_keys=None, | |
homepage="https://github.com/zaidalyafeai/MetRec", | |
citation=_CITATION, | |
) | |
def _vocab_text_gen(self, archive): | |
for _, ex in self._generate_examples(archive, os.path.join("final_baits", "train.txt")): | |
yield ex["text"] | |
def _split_generators(self, dl_manager): | |
arch_path = dl_manager.download_and_extract(_DOWNLOAD_URL) | |
data_dir = os.path.join(arch_path, "final_baits") | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, gen_kwargs={"directory": os.path.join(data_dir, "train.txt")} | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.TEST, gen_kwargs={"directory": os.path.join(data_dir, "test.txt")} | |
), | |
] | |
def _generate_examples(self, directory, labeled=True): | |
"""Generate examples.""" | |
# For labeled examples, extract the label from the path. | |
with open(directory, encoding="UTF-8") as f: | |
for id_, record in enumerate(f.read().splitlines()): | |
label, bait = record.split(" ", 1) | |
yield str(id_), {"text": bait, "label": int(label)} | |