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README.md

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+---
+language:
+- ace
+- bg
+- da
+- fur
+- ilo
+- lij
+- mzn
+- qu
+- su
+- vi
+- af
+- bh
+- de
+- fy
+- io
+- lmo
+- nap
+- rm
+- sv
+- vls
+- als
+- bn
+- diq
+- ga
+- is
+- ln
+- nds
+- ro
+- sw
+- vo
+- am
+- bo
+- dv
+- gan
+- it
+- lt
+- ne
+- ru
+- szl
+- wa
+- an
+- br
+- el
+- gd
+- ja
+- lv
+- nl
+- rw
+- ta
+- war
+- ang
+- bs
+- eml
+- gl
+- jbo
+- nn
+- sa
+- te
+- wuu
+- ar
+- ca
+- en
+- gn
+- jv
+- mg
+- no
+- sah
+- tg
+- xmf
+- arc
+- eo
+- gu
+- ka
+- mhr
+- nov
+- scn
+- th
+- yi
+- arz
+- cdo
+- es
+- hak
+- kk
+- mi
+- oc
+- sco
+- tk
+- yo
+- as
+- ce
+- et
+- he
+- km
+- min
+- or
+- sd
+- tl
+- zea
+- ast
+- ceb
+- eu
+- hi
+- kn
+- mk
+- os
+- sh
+- tr
+- ay
+- ckb
+- ext
+- hr
+- ko
+- ml
+- pa
+- si
+- tt
+- az
+- co
+- fa
+- hsb
+- ksh
+- mn
+- pdc
+- ug
+- ba
+- crh
+- fi
+- hu
+- ku
+- mr
+- pl
+- sk
+- uk
+- zh
+- bar
+- cs
+- hy
+- ky
+- ms
+- pms
+- sl
+- ur
+- csb
+- fo
+- ia
+- la
+- mt
+- pnb
+- so
+- uz
+- cv
+- fr
+- id
+- lb
+- mwl
+- ps
+- sq
+- vec
+- be
+- cy
+- frr
+- ig
+- li
+- my
+- pt
+- sr
+multilinguality:
+- multilingual
+size_categories:
+- 10K<100k
+task_categories:
+- token-classification
+task_ids:
+- named-entity-recognition
+pretty_name: WikiAnn
+---
+
+# Dataset Card for "tner/wikiann"
+
+## Dataset Description
+
+- **Repository:** [T-NER](https://github.com/asahi417/tner)
+- **Paper:** [https://aclanthology.org/P17-1178/](https://aclanthology.org/P17-1178/)
+- **Dataset:** WikiAnn
+- **Domain:** Wikipedia
+- **Number of Entity:** 3
+
+
+### Dataset Summary
+WikiAnn NER dataset formatted in a part of [TNER](https://github.com/asahi417/tner) project.
+- Entity Types: `LOC`, `ORG`, `PER`
+
+## Dataset Structure
+
+### Data Instances
+An example of `train` looks as follows.
+
+```
+{
+    'tokens': ['I', 'hate', 'the', 'words', 'chunder', ',', 'vomit', 'and', 'puke', '.', 'BUUH', '.'],
+    'tags': [6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6]
+}
+```
+
+### Label ID
+The label2id dictionary can be found at [here](https://huggingface.co/datasets/tner/btc/raw/main/dataset/label.json).
+```python
+{
+    "B-LOC": 0,
+    "B-ORG": 1,
+    "B-PER": 2,
+    "I-LOC": 3,
+    "I-ORG": 4,
+    "I-PER": 5,
+    "O": 6
+}
+```
+
+### Data Splits
+
+|  name   |train|validation|test|
+|---------|----:|---------:|---:|
+|btc      | 6338|      1001|2000|
+
+### Citation Information
+
+```
+@inproceedings{pan-etal-2017-cross,
+    title = "Cross-lingual Name Tagging and Linking for 282 Languages",
+    author = "Pan, Xiaoman  and
+      Zhang, Boliang  and
+      May, Jonathan  and
+      Nothman, Joel  and
+      Knight, Kevin  and
+      Ji, Heng",
+    booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
+    month = jul,
+    year = "2017",
+    address = "Vancouver, Canada",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/P17-1178",
+    doi = "10.18653/v1/P17-1178",
+    pages = "1946--1958",
+    abstract = "The ambitious goal of this work is to develop a cross-lingual name tagging and linking framework for 282 languages that exist in Wikipedia. Given a document in any of these languages, our framework is able to identify name mentions, assign a coarse-grained or fine-grained type to each mention, and link it to an English Knowledge Base (KB) if it is linkable. We achieve this goal by performing a series of new KB mining methods: generating {``}silver-standard{''} annotations by transferring annotations from English to other languages through cross-lingual links and KB properties, refining annotations through self-training and topic selection, deriving language-specific morphology features from anchor links, and mining word translation pairs from cross-lingual links. Both name tagging and linking results for 282 languages are promising on Wikipedia data and on-Wikipedia data.",
+}
+```