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Create README.md
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README.md
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| 1 |
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---
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| 2 |
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task_categories:
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- token-classification
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| 4 |
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language:
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- ar
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size_categories:
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- 10K<n<100K
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---
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## Arabic NER
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| 11 |
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Sample of the Arabic NER data
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## Usage
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```bash
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pip install datasets
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```
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| 20 |
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Login:
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```
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huggingface-cli login
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```
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```python
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from datasets import load_dataset
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ds = load_dataset("iahlt/arabic_ner_mafat")
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```
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## Sample
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```json
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{'id': '42',
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'ner_tags': [32,
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32,
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32,
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32,
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32,
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32,
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32,
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32,
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32,
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32,
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32,
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32,
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32,
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32,
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32,
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32,
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32,
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30,
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28,
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28,
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31],
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'raw_tags': ['O',
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| 59 |
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'O',
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| 60 |
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'O',
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| 61 |
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'O',
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'O',
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| 63 |
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'O',
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| 64 |
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'O',
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| 65 |
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'O',
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| 66 |
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'O',
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| 67 |
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'O',
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| 68 |
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'O',
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| 69 |
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'O',
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'O',
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| 71 |
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'O',
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'O',
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'O',
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'O',
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'B-MISC',
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'I-MISC',
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'I-MISC',
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'L-MISC'],
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'record': '{"metadata": {"doc_id": '
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| 80 |
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'"0142895c6cdb030b10c8cc2e5c9639f9422bf22ef45a1b314d7a366fc6489938", '
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| 81 |
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'"url": "https://www.alarab.com//Article/1004953", "source": '
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| 82 |
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'"AlArab", "title": "فوائد غير متوقعة للعلكة الخالية من السكر.. '
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| 83 |
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'اكتشفوها معنا!", "authors": "كل العرب (تصوير: iStockphoto)", '
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| 84 |
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'"date": "2021-08-30 13:25:01", "domains": "التغذية الصحيحة:فوائد '
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| 85 |
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'العلكة الخالية من السكر", "parnumber": "36", "sentnumber": "1", '
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| 86 |
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'"manually_qa-ed": "Yes"}, "text": "يجب عليك الامتناع عن مضغ العلكة '
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| 87 |
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'إذا كنت تعاني من أي نوع من الام الفك أو اضطراب الصدغي الفكي.", '
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| 88 |
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'"label": [[75, 94, "MISC"]], "user": "nlhowell", "timestamp": '
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| 89 |
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'1685356359.342268, "flatten": {"tokens": ["يجب", "علي", "ك", '
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| 90 |
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'"الامتناع", "عن", "مضغ", "العلكة", "إذا", "كنت", "تعاني", "من", '
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| 91 |
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'"أي", "نوع", "من", "الام", "الفك", "أو", "اضطراب", "الصدغي", '
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'"الفكي", "."], "ner_tags": ["O", "O", "O", "O", "O", "O", "O", '
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'"O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-MISC", '
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'"I-MISC", "I-MISC", "L-MISC"]}}',
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'tokens': ['يجب',
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'علي',
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'ك',
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'الامتناع',
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'عن',
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'مضغ',
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'العلكة',
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'إذا',
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'كنت',
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'تعاني',
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'من',
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'أي',
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'نوع',
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'من',
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'الام',
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'الفك',
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'أو',
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'اضطراب',
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'الصدغي',
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'الفكي',
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'.']}
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```
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## Visualization
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| 119 |
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```bash
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| 122 |
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pip install spacy ipython -q
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| 123 |
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```
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| 124 |
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| 125 |
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```python
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| 126 |
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import json
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| 127 |
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from spacy.training import offsets_to_biluo_tags, biluo_tags_to_spans
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| 128 |
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| 129 |
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record = ds[676]
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| 130 |
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record["record"] = json.loads(record["record"])
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| 131 |
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| 132 |
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ner_tags = record["raw_tags"]
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| 133 |
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tokens = record["tokens"]
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| 134 |
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| 135 |
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| 136 |
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doc = spacy.tokens.Doc(spacy.blank("ar").vocab, words=tokens)
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| 137 |
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doc.ents = biluo_tags_to_spans(doc, ner_tags)
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| 138 |
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| 139 |
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print(record["record"]["text"])
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| 140 |
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spacy.displacy.render(doc, style="ent", jupyter=True)
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| 141 |
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```
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| 142 |
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