pythainlp/thainer-corpus-v2-base-model
Token Classification
•
Updated
•
1.97k
•
10
words
sequencelengths 1
282
| ner
sequencelengths 1
282
|
|---|---|
[
"ทักษิณ",
" ",
"ชินวัตร",
" ",
"ทวีต",
"ไม่",
"แปลกใจ",
"ศาลปกครอง",
"สูงสุด",
" ",
"ยก",
"ฟ้องคดี",
"ถอน",
"พาสปอร์ต",
" ",
"ชี้",
" ",
"กระบวนการยุติธรรม",
"ไทย",
"ถูก",
"ใช้",
"เป็น",
"เครื่องมือ",
"การเมือง"
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[
"ทุกคน",
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"ว่า",
"พระ",
"ลูกชาย",
"ของ",
"ตน",
"ทำ",
"ไป",
"ไม่",
"ได้",
"เจตนา",
"จะ",
"หา",
"เงินทอง",
"เข้าตัว",
"แต่",
"อย่างไร"
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[
"“",
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"โซ",
"ตัส",
"”",
" ",
"หวั่น",
"รับน้อง",
"ลาม",
"มัธยม",
" ",
"ชี้",
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"“",
"มหา",
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"”",
" ",
"ใช้",
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"“",
"ชั่วโมง",
"กิจกรรม",
"”",
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"สร้าง",
"ชอบธรรม",
"บังคับ",
"คน",
"ร่วม"
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[
"ป.ป.ช.",
"สรุป",
"ผลสอบ",
" ",
"10",
" ",
"คน",
"เอี่ยว",
"ทุจริต",
"งบ",
" ",
"“",
"อาหารกลางวัน",
"”"
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[
"ฟีฟ่า",
"พอใจ",
"กรรมการตัดสิน",
"ฟุตบอล",
"โลก",
"2010"
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[
"สุเทพ",
"โยน",
"สื่อ",
"เสี้ยม",
"ขัดแย้ง",
"เติ้ง"
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[
"รัฐบาล",
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"ยกระดับ",
"การคมนาคม",
"ขนส่ง",
"ให้",
"ทันสมัย",
" ",
"โดย",
"จับมือ",
"กับ",
"ประเทศ",
"ญี่ปุ่น",
"ซึ่ง",
"มี",
"ความก้าวหน้า",
"ทางเทคโนโลยี",
"สูง",
"เพื่อ",
"ร่วมกัน",
"พัฒนา",
"โครงการ",
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[
"สถานเอกอัครราชทูต",
"บราซิล",
" ",
"กรุงเทพฯ",
" ",
"ร่วมกับ",
" ",
"สยามพารากอน",
" ",
"มูลนิธิ",
"ช่วย",
"คนตาบอด",
"แห่ง",
"ประเทศ",
"ไทย",
"ใน",
"พระ",
"บรม",
"ราชินูปถัมภ์",
" ",
"และ",
"สมาคมคนตาบอดแห่งประเทศไทย",
" ",
"จัด",
"นิทรรศการ",
" ",
"สีสัน",
"แห่ง",
"ความ",
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" ",
"(",
"Colours",
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"of",
" ",
"Silence",
")",
" ",
"แสดงผล",
"งานศิลปะ",
"ชุด",
"พิเศษ",
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"ชาว",
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" ",
"ค",
"ริ",
"สติ",
"น่า",
" ",
"ปอร์แตล",
"ล่า",
" ",
"(",
"Cristina",
" ",
"Portella",
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"ที่",
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"ฮอลล์",
" ",
"ออฟ",
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"มิ",
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[
"รายงาน",
"ข่าว",
"จาก",
"สำนักงานการตรวจเงินแผ่นดิน",
" ",
"(",
"สตง.",
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"แจ้ง",
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"ลี",
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"ได้",
"ส่ง",
"หนังสือ",
"ลับ",
"ด่วน",
"ที่สุด",
"ถึง",
"พล",
".",
"ร.อ.",
"ธีระ",
" ",
"ห้าว",
"เจริญ",
"รมว.",
"คมนาคม",
"เมื่อ",
"วันที่",
"29",
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"เพื่อ",
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"ข้อเท็จจริง",
"กรณี",
"โครง",
"การสอน",
"ฝึก",
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[
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"รณรงค์",
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"แอลกอฮอล์",
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"ได้",
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"ความเข้มแข็ง",
"ของ",
"สถาบันครอบครัว",
" ",
"จัด",
"ทํา",
"โครงการ",
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"“",
"ค้น",
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"ค้นหา",
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"การ",
"ดื่มเหล้า",
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[
"วันนี้",
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"(",
"13",
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"61",
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"ข้อมูล",
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[
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End of preview. Expand
in Dataset Viewer.
Dataset Card for "thainer-corpus-v2"
News!!!
Thai NER v2.2 is released! Please use Thai NER 2.2 instead This corpus. Thai NER v2.2: https://huggingface.co/datasets/pythainlp/thainer-corpus-v2.2
Thai Named Entity Recognition Corpus
Home Page: https://pythainlp.github.io/Thai-NER/version/2
Training script and split data: https://zenodo.org/record/7761354
You can download .conll to train named entity model in https://zenodo.org/record/7761354.
Size
- Train: 3,938 docs
- Validation: 1,313 docs
- Test: 1,313 Docs
Some data come from crowdsourcing between Dec 2018 - Nov 2019. https://github.com/wannaphong/thai-ner
Domain
- News (It, politics, economy, social)
- PR (KKU news)
- general
Source
- I use sone data from Nutcha’s theses (http://pioneer.chula.ac.th/~awirote/Data-Nutcha.zip) and improve data by rechecking and adding more tagging.
- Blognone.com - It news
- thaigov.go.th
- kku.ac.th
And more (the lists are lost.)
Tag
- DATA - date
- TIME - time
- EMAIL - email
- LEN - length
- LOCATION - Location
- ORGANIZATION - Company / Organization
- PERSON - Person name
- PHONE - phone number
- TEMPERATURE - temperature
- URL - URL
- ZIP - Zip code
- MONEY - the amount
- LAW - legislation
- PERCENT - PERCENT
Download: HuggingFace Hub
Cite
Wannaphong Phatthiyaphaibun. (2022). Thai NER 2.0 (2.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7761354
or BibTeX
@dataset{wannaphong_phatthiyaphaibun_2022_7761354,
author = {Wannaphong Phatthiyaphaibun},
title = {Thai NER 2.0},
month = sep,
year = 2022,
publisher = {Zenodo},
version = {2.0},
doi = {10.5281/zenodo.7761354},
url = {https://doi.org/10.5281/zenodo.7761354}
}
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