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Datasets:
iahlt
/
arabic_ner_mafat

Tasks:
Token Classification
Languages:
Arabic
Size:
10K<n<100K
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Arabic NER

Sample of the Arabic NER data

Usage 

pip install datasets

Login:

huggingface-cli login

from datasets import load_dataset


ds = load_dataset("iahlt/arabic_ner_mafat")

Sample 

{'id': '42',
 'ner_tags': [32,
              32,
              32,
              32,
              32,
              32,
              32,
              32,
              32,
              32,
              32,
              32,
              32,
              32,
              32,
              32,
              32,
              30,
              28,
              28,
              31],
 'raw_tags': ['O',
              'O',
              'O',
              'O',
              'O',
              'O',
              'O',
              'O',
              'O',
              'O',
              'O',
              'O',
              'O',
              'O',
              'O',
              'O',
              'O',
              'B-MISC',
              'I-MISC',
              'I-MISC',
              'L-MISC'],
 'record': '{"metadata": {"doc_id": '
           '"0142895c6cdb030b10c8cc2e5c9639f9422bf22ef45a1b314d7a366fc6489938", '
           '"url": "https://www.alarab.com//Article/1004953", "source": '
           '"AlArab", "title": "فوائد غير متوقعة للعلكة الخالية من السكر.. '
           'اكتشفوها معنا!", "authors": "كل العرب (تصوير: iStockphoto)", '
           '"date": "2021-08-30 13:25:01", "domains": "التغذية الصحيحة:فوائد '
           'العلكة الخالية من السكر", "parnumber": "36", "sentnumber": "1", '
           '"manually_qa-ed": "Yes"}, "text": "يجب عليك الامتناع عن مضغ العلكة '
           'إذا كنت تعاني من أي نوع من الام الفك أو اضطراب الصدغي الفكي.", '
           '"label": [[75, 94, "MISC"]], "user": "nlhowell", "timestamp": '
           '1685356359.342268, "flatten": {"tokens": ["يجب", "علي", "ك", '
           '"الامتناع", "عن", "مضغ", "العلكة", "إذا", "كنت", "تعاني", "من", '
           '"أي", "نوع", "من", "الام", "الفك", "أو", "اضطراب", "الصدغي", '
           '"الفكي", "."], "ner_tags": ["O", "O", "O", "O", "O", "O", "O", '
           '"O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", '
           '"I-MISC", "I-MISC", "L-MISC"]}}',
 'tokens': ['يجب',
            'علي',
            'ك',
            'الامتناع',
            'عن',
            'مضغ',
            'العلكة',
            'إذا',
            'كنت',
            'تعاني',
            'من',
            'أي',
            'نوع',
            'من',
            'الام',
            'الفك',
            'أو',
            'اضطراب',
            'الصدغي',
            'الفكي',
            '.']}

Visualization 

pip install spacy ipython -q

import json
from spacy.training import offsets_to_biluo_tags, biluo_tags_to_spans

record = ds[676]
record["record"] = json.loads(record["record"])

ner_tags = record["raw_tags"]
tokens = record["tokens"]


doc = spacy.tokens.Doc(spacy.blank("ar").vocab, words=tokens)
doc.ents = biluo_tags_to_spans(doc, ner_tags)

print(record["record"]["text"])
spacy.displacy.render(doc, style="ent", jupyter=True)
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