Hugging Face's logo

Datasets:
iahlt
/
arabic_ner_mafat

Tasks:
Token Classification
Languages:
Arabic
Size:
10K<n<100K
Dataset card Files Community
Dataset Viewer
Full Screen

The viewer is disabled because this dataset repo requires arbitrary Python code execution. Please consider removing the loading script and relying on automated data support (you can use convert_to_parquet from the datasets library). If this is not possible, please open a discussion for direct help.

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)
Downloads last month
32
Edit dataset card