Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
named-entity-recognition
Languages:
Arabic
Size:
100K - 1M
License:
Commit
•
4749e1d
1
Parent(s):
a64a471
Convert dataset to Parquet (#3)
Browse files- Convert dataset to Parquet (480cf0fa6ee2345e092a0b5e112b4288b1d7bd17)
- Delete loading script (d80ee8d544056c4e52969412df285c2db26a5ef7)
- Delete legacy dataset_infos.json (02b65ac6335eff7d82448471ea7bbac8db4d5aee)
- README.md +8 -3
- caner.py +0 -122
- data/train-00000-of-00001.parquet +3 -0
- dataset_infos.json +0 -1
README.md
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'20': Time
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splits:
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- name: train
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num_bytes:
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num_examples: 258240
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download_size:
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dataset_size:
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---
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# Dataset Card for CANER
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'20': Time
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splits:
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- name: train
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num_bytes: 5095617
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num_examples: 258240
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download_size: 1459014
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dataset_size: 5095617
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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---
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# Dataset Card for CANER
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caner.py
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# coding=utf-8
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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""A new corpus of tagged data that can be useful for handling the issues in recognition of Classical Arabic named entities"""
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import csv
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import os
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import datasets
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_CITATION = """\
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@article{article,
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author = {Salah, Ramzi and Zakaria, Lailatul},
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year = {2018},
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month = {12},
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pages = {},
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title = {BUILDING THE CLASSICAL ARABIC NAMED ENTITY RECOGNITION CORPUS (CANERCORPUS)},
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volume = {96},
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journal = {Journal of Theoretical and Applied Information Technology}
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}
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"""
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_DESCRIPTION = """\
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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.
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"""
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_HOMEPAGE = "https://github.com/RamziSalah/Classical-Arabic-Named-Entity-Recognition-Corpus"
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# TODO: Add the licence for the dataset here if you can find it
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_LICENSE = ""
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_URL = "https://raw.githubusercontent.com/RamziSalah/Classical-Arabic-Named-Entity-Recognition-Corpus/master/CANERCorpus.csv"
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class Caner(datasets.GeneratorBasedBuilder):
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"""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"""
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VERSION = datasets.Version("1.1.0")
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def _info(self):
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features = datasets.Features(
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{
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"token": datasets.Value("string"),
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"ner_tag": datasets.ClassLabel(
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names=[
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"Allah",
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"Book",
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"Clan",
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"Crime",
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"Date",
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"Day",
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"Hell",
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"Loc",
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"Meas",
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"Mon",
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"Month",
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"NatOb",
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"Number",
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"O",
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"Org",
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"Para",
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"Pers",
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"Prophet",
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"Rlig",
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"Sect",
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"Time",
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]
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),
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}
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)
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=features,
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supervised_keys=None,
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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data_path = dl_manager.download(_URL)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={
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"filepath": data_path,
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},
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)
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]
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def _generate_examples(self, filepath):
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"""Yields examples."""
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with open(filepath, encoding="utf-8") as csv_file:
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reader = csv.reader(csv_file, delimiter=",")
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next(reader, None)
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for id_, row in enumerate(reader):
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yield id_, {
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"token": row[0],
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"ner_tag": row[1],
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}
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data/train-00000-of-00001.parquet
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:68d710a709cefb398a3b44ac3d0629975fed8ba489747448c499c65baffc3de2
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size 1459014
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dataset_infos.json
DELETED
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{"default": {"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.\n", "citation": "@article{article,\nauthor = {Salah, Ramzi and Zakaria, Lailatul},\nyear = {2018},\nmonth = {12},\npages = {},\ntitle = {BUILDING THE CLASSICAL ARABIC NAMED ENTITY RECOGNITION CORPUS (CANERCORPUS)},\nvolume = {96},\njournal = {Journal of Theoretical and Applied Information Technology}\n}\n", "homepage": "https://github.com/RamziSalah/Classical-Arabic-Named-Entity-Recognition-Corpus", "license": "", "features": {"token": {"dtype": "string", "id": null, "_type": "Value"}, "ner_tag": {"num_classes": 21, "names": ["Allah", "Book", "Clan", "Crime", "Date", "Day", "Hell", "Loc", "Meas", "Mon", "Month", "NatOb", "Number", "O", "Org", "Para", "Pers", "Prophet", "Rlig", "Sect", "Time"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "caner", "config_name": "default", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 5095721, "num_examples": 258240, "dataset_name": "caner"}}, "download_checksums": {"https://github.com/RamziSalah/Classical-Arabic-Named-Entity-Recognition-Corpus/archive/master.zip": {"num_bytes": 17063406, "checksum": "b4f6bbcc1074dfb9a6cf53fbbd5825a8eafbff842cd89ed20ab33f5b3ef6cddb"}}, "download_size": 17063406, "post_processing_size": null, "dataset_size": 5095721, "size_in_bytes": 22159127}}
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