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"""Arabic Billion Words Corpus""" |
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from __future__ import absolute_import, division, print_function |
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import os |
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import re |
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import datasets |
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_CITATION = """\ |
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@article{el20161, |
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title={1.5 billion words arabic corpus}, |
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author={El-Khair, Ibrahim Abu}, |
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journal={arXiv preprint arXiv:1611.04033}, |
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year={2016} |
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} |
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""" |
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_DESCRIPTION = """\ |
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Abu El-Khair Corpus is an Arabic text corpus, that includes more than five million newspaper articles. |
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It contains over a billion and a half words in total, out of which, there are about three million unique words. |
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The corpus is encoded with two types of encoding, namely: UTF-8, and Windows CP-1256. |
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Also it was marked with two mark-up languages, namely: SGML, and XML. |
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""" |
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_HOMEPAGE = "http://abuelkhair.net/index.php/en/arabic/abu-el-khair-corpus" |
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_URL = "http://abuelkhair.net/corpus/" |
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_URLs = { |
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"Alittihad": _URL + "Alittihad_XML_utf_8.rar", |
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"Almasryalyoum": _URL + "Almasryalyoum_XML_utf_8.rar", |
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"Almustaqbal": _URL + "Almustaqbal_XML_utf_8.rar", |
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"Alqabas": _URL + "Alqabas_XML_utf_8.rar", |
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"Echoroukonline": _URL + "Echoroukonline_XML_utf_8.rar", |
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"Ryiadh": _URL + "Ryiadh_XML_utf_8.rar", |
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"Sabanews": _URL + "Sabanews_XML_utf_8.rar", |
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"SaudiYoum": _URL + "SaudiYoum_XML_utf_8.rar", |
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"Techreen": _URL + "Techreen_XML_utf_8.rar", |
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"Youm7": _URL + "Youm7_XML_utf_8.rar", |
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} |
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MISS_SPELLED_TAGS = { |
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"Dateline": ["Dateline", "dateline"], |
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"Headline": ["Headline", "Healine"], |
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"Text": ["Text"], |
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"URL": ["URL"], |
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} |
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class ArabicBillionWords(datasets.GeneratorBasedBuilder): |
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"""Arabic Billion Words Corpus""" |
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VERSION = datasets.Version("1.1.0") |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig( |
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name="Alittihad", version=VERSION, description="This part of dataset covers Alittihad news paper" |
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), |
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datasets.BuilderConfig( |
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name="Almasryalyoum", version=VERSION, description="This part of dataset covers Almasryalyoum news paper" |
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), |
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datasets.BuilderConfig( |
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name="Almustaqbal", version=VERSION, description="This part of dataset covers Almustaqbal news paper" |
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), |
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datasets.BuilderConfig( |
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name="Alqabas", version=VERSION, description="This part of dataset covers Alqabas news paper" |
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), |
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datasets.BuilderConfig( |
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name="Echoroukonline", version=VERSION, description="This part of dataset covers Echoroukonline news paper" |
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), |
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datasets.BuilderConfig( |
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name="Ryiadh", version=VERSION, description="This part of dataset covers Ryiadh news paper" |
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), |
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datasets.BuilderConfig( |
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name="Sabanews", version=VERSION, description="This part of dataset covers Sabanews news paper" |
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), |
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datasets.BuilderConfig( |
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name="SaudiYoum", version=VERSION, description="This part of dataset covers SaudiYoum news paper" |
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), |
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datasets.BuilderConfig( |
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name="Techreen", version=VERSION, description="This part of dataset covers Techreen news paper" |
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), |
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datasets.BuilderConfig( |
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name="Youm7", version=VERSION, description="This part of dataset covers Youm7 news paper" |
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), |
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] |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"url": datasets.Value("string"), |
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"head_line": datasets.Value("string"), |
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"date": datasets.Value("string"), |
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"text": datasets.Value("string"), |
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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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homepage=_HOMEPAGE, |
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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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my_urls = _URLs[self.config.name] |
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data_dir = dl_manager.download_and_extract(my_urls) |
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my_file_name = f"{self.config.name}_utf_8.xml" |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"filepath": os.path.join(data_dir, my_file_name), |
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}, |
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), |
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] |
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def _extract_tags(self, sample, tag): |
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for tg in MISS_SPELLED_TAGS[tag]: |
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pattern = f"<{tg}>(.*?)</{tg}>" |
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out = re.findall(r"" + pattern, sample.group(0), re.MULTILINE | re.DOTALL) |
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if len(out) > 0: |
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break |
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return out[0] |
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def _clean_text(self, text): |
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return text.replace("?", "") |
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def _generate_examples(self, filepath): |
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""" Yields examples. """ |
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current_multi_line = "" |
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_idx = 0 |
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data_tag = self.config.name |
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with open(filepath, mode="r", encoding="utf-8") as f: |
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for i, line in enumerate(f): |
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if i == 0: |
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continue |
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current_multi_line += line |
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if i % 8 == 0: |
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pattern = f"<{data_tag}(.*?)</{data_tag}>" |
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data = re.finditer(r"" + pattern, current_multi_line, re.MULTILINE | re.DOTALL) |
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text, url, head_line, date = ["", "", "", ""] |
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for _, record in enumerate(data): |
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try: |
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text = self._clean_text(self._extract_tags(record, "Text")) |
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url = self._extract_tags(record, "URL") |
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head_line = self._clean_text(self._extract_tags(record, "Headline")) |
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date = self._extract_tags(record, "Dateline") |
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except ValueError: |
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pass |
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yield str(_idx), {"url": url, "head_line": head_line, "date": date, "text": text} |
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_idx += 1 |
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current_multi_line = "" |
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