
# Dataset Card for WikiANN

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** [Massively Multilingual Transfer for NER](https://github.com/afshinrahimi/mmner)
- **Repository:** [Massively Multilingual Transfer for NER](https://github.com/afshinrahimi/mmner)
- **Paper:** The original datasets come from the _Cross-lingual name tagging and linking for 282 languages_ [paper](https://www.aclweb.org/anthology/P17-1178/) by Xiaoman Pan et al. (2018). This version corresponds to the balanced train, dev, and test splits of the original data from the _Massively Multilingual Transfer for NER_ [paper](https://arxiv.org/abs/1902.00193) by Afshin Rahimi et al. (2019).
- **Leaderboard:**
- **Point of Contact:** [Afshin Rahimi](mailto:afshinrahimi@gmail.com) or [Lewis Tunstall](mailto:lewis.c.tunstall@gmail.com) or [Albert Villanova del Moral](albert@huggingface.co)

### Dataset Summary

WikiANN (sometimes called PAN-X) is a multilingual named entity recognition dataset consisting of Wikipedia articles annotated with LOC (location), PER (person), and ORG (organisation) tags in the IOB2 format. This version corresponds to the balanced train, dev, and test splits of Rahimi et al. (2019), which supports 176 of the 282 languages from the original WikiANN corpus.

### Supported Tasks and Leaderboards

- `named-entity-recognition`: The dataset can be used to train a model for named entity recognition in many languages, or evaluate the zero-shot cross-lingual capabilities of multilingual models.

### Languages

The dataset contains 176 languages, one in each of the configuration subsets. The corresponding BCP 47 language tags
are:

|                    | Language tag   |
|:-------------------|:---------------|
| ace                | ace            |
| af                 | af             |
| als                | als            |
| am                 | am             |
| an                 | an             |
| ang                | ang            |
| ar                 | ar             |
| arc                | arc            |
| arz                | arz            |
| as                 | as             |
| ast                | ast            |
| ay                 | ay             |
| az                 | az             |
| ba                 | ba             |
| bar                | bar            |
| be                 | be             |
| bg                 | bg             |
| bh                 | bh             |
| bn                 | bn             |
| bo                 | bo             |
| br                 | br             |
| bs                 | bs             |
| ca                 | ca             |
| cdo                | cdo            |
| ce                 | ce             |
| ceb                | ceb            |
| ckb                | ckb            |
| co                 | co             |
| crh                | crh            |
| cs                 | cs             |
| csb                | csb            |
| cv                 | cv             |
| cy                 | cy             |
| da                 | da             |
| de                 | de             |
| diq                | diq            |
| dv                 | dv             |
| el                 | el             |
| en                 | en             |
| eo                 | eo             |
| es                 | es             |
| et                 | et             |
| eu                 | eu             |
| ext                | ext            |
| fa                 | fa             |
| fi                 | fi             |
| fo                 | fo             |
| fr                 | fr             |
| frr                | frr            |
| fur                | fur            |
| fy                 | fy             |
| ga                 | ga             |
| gan                | gan            |
| gd                 | gd             |
| gl                 | gl             |
| gn                 | gn             |
| gu                 | gu             |
| hak                | hak            |
| he                 | he             |
| hi                 | hi             |
| hr                 | hr             |
| hsb                | hsb            |
| hu                 | hu             |
| hy                 | hy             |
| ia                 | ia             |
| id                 | id             |
| ig                 | ig             |
| ilo                | ilo            |
| io                 | io             |
| is                 | is             |
| it                 | it             |
| ja                 | ja             |
| jbo                | jbo            |
| jv                 | jv             |
| ka                 | ka             |
| kk                 | kk             |
| km                 | km             |
| kn                 | kn             |
| ko                 | ko             |
| ksh                | ksh            |
| ku                 | ku             |
| ky                 | ky             |
| la                 | la             |
| lb                 | lb             |
| li                 | li             |
| lij                | lij            |
| lmo                | lmo            |
| ln                 | ln             |
| lt                 | lt             |
| lv                 | lv             |
| mg                 | mg             |
| mhr                | mhr            |
| mi                 | mi             |
| min                | min            |
| mk                 | mk             |
| ml                 | ml             |
| mn                 | mn             |
| mr                 | mr             |
| ms                 | ms             |
| mt                 | mt             |
| mwl                | mwl            |
| my                 | my             |
| mzn                | mzn            |
| nap                | nap            |
| nds                | nds            |
| ne                 | ne             |
| nl                 | nl             |
| nn                 | nn             |
| no                 | no             |
| nov                | nov            |
| oc                 | oc             |
| or                 | or             |
| os                 | os             |
| other-bat-smg      | sgs            |
| other-be-x-old     | be-tarask      |
| other-cbk-zam      | cbk            |
| other-eml          | eml            |
| other-fiu-vro      | vro            |
| other-map-bms      | jv-x-bms       |
| other-simple       | en-basiceng    |
| other-zh-classical | lzh            |
| other-zh-min-nan   | nan            |
| other-zh-yue       | yue            |
| pa                 | pa             |
| pdc                | pdc            |
| pl                 | pl             |
| pms                | pms            |
| pnb                | pnb            |
| ps                 | ps             |
| pt                 | pt             |
| qu                 | qu             |
| rm                 | rm             |
| ro                 | ro             |
| ru                 | ru             |
| rw                 | rw             |
| sa                 | sa             |
| sah                | sah            |
| scn                | scn            |
| sco                | sco            |
| sd                 | sd             |
| sh                 | sh             |
| si                 | si             |
| sk                 | sk             |
| sl                 | sl             |
| so                 | so             |
| sq                 | sq             |
| sr                 | sr             |
| su                 | su             |
| sv                 | sv             |
| sw                 | sw             |
| szl                | szl            |
| ta                 | ta             |
| te                 | te             |
| tg                 | tg             |
| th                 | th             |
| tk                 | tk             |
| tl                 | tl             |
| tr                 | tr             |
| tt                 | tt             |
| ug                 | ug             |
| uk                 | uk             |
| ur                 | ur             |
| uz                 | uz             |
| vec                | vec            |
| vep                | vep            |
| vi                 | vi             |
| vls                | vls            |
| vo                 | vo             |
| wa                 | wa             |
| war                | war            |
| wuu                | wuu            |
| xmf                | xmf            |
| yi                 | yi             |
| yo                 | yo             |
| zea                | zea            |
| zh                 | zh             |

## Dataset Structure

### Data Instances

This is an example in the "train" split of the "af" (Afrikaans language) configuration subset:
```python
{
  'tokens': ['Sy', 'ander', 'seun', ',', 'Swjatopolk', ',', 'was', 'die', 'resultaat', 'van', '’n', 'buite-egtelike', 'verhouding', '.'],
  'ner_tags': [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  'langs': ['af', 'af', 'af', 'af', 'af', 'af', 'af', 'af', 'af', 'af', 'af', 'af', 'af', 'af'],
  'spans': ['PER: Swjatopolk']
}
```

### Data Fields

- `tokens`: a `list` of `string` features.
- `langs`: a `list` of `string` features that correspond to the language of each token.
- `ner_tags`: a `list` of classification labels, with possible values including `O` (0), `B-PER` (1), `I-PER` (2), `B-ORG` (3), `I-ORG` (4), `B-LOC` (5), `I-LOC` (6).
- `spans`: a `list` of `string` features, that is the list of named entities in the input text formatted as ``<TAG>: <mention>``

### Data Splits

For each configuration subset, the data is split into "train", "validation" and "test" sets, each containing the
following number of examples:

|              |   Train |   Validation |   Test |
|:-------------|--------:|-------------:|-------:|
| ace          |     100 |          100 |    100 |
| af           |    5000 |         1000 |   1000 |
| als          |     100 |          100 |    100 |
| am           |     100 |          100 |    100 |
| an           |    1000 |         1000 |   1000 |
| ang          |     100 |          100 |    100 |
| ar           |   20000 |        10000 |  10000 |
| arc          |     100 |          100 |    100 |
| arz          |     100 |          100 |    100 |
| as           |     100 |          100 |    100 |
| ast          |    1000 |         1000 |   1000 |
| ay           |     100 |          100 |    100 |
| az           |   10000 |         1000 |   1000 |
| ba           |     100 |          100 |    100 |
| bar          |     100 |          100 |    100 |
| bat-smg      |     100 |          100 |    100 |
| be           |   15000 |         1000 |   1000 |
| be-x-old     |    5000 |         1000 |   1000 |
| bg           |   20000 |        10000 |  10000 |
| bh           |     100 |          100 |    100 |
| bn           |   10000 |         1000 |   1000 |
| bo           |     100 |          100 |    100 |
| br           |    1000 |         1000 |   1000 |
| bs           |   15000 |         1000 |   1000 |
| ca           |   20000 |        10000 |  10000 |
| cbk-zam      |     100 |          100 |    100 |
| cdo          |     100 |          100 |    100 |
| ce           |     100 |          100 |    100 |
| ceb          |     100 |          100 |    100 |
| ckb          |    1000 |         1000 |   1000 |
| co           |     100 |          100 |    100 |
| crh          |     100 |          100 |    100 |
| cs           |   20000 |        10000 |  10000 |
| csb          |     100 |          100 |    100 |
| cv           |     100 |          100 |    100 |
| cy           |   10000 |         1000 |   1000 |
| da           |   20000 |        10000 |  10000 |
| de           |   20000 |        10000 |  10000 |
| diq          |     100 |          100 |    100 |
| dv           |     100 |          100 |    100 |
| el           |   20000 |        10000 |  10000 |
| eml          |     100 |          100 |    100 |
| en           |   20000 |        10000 |  10000 |
| eo           |   15000 |        10000 |  10000 |
| es           |   20000 |        10000 |  10000 |
| et           |   15000 |        10000 |  10000 |
| eu           |   10000 |        10000 |  10000 |
| ext          |     100 |          100 |    100 |
| fa           |   20000 |        10000 |  10000 |
| fi           |   20000 |        10000 |  10000 |
| fiu-vro      |     100 |          100 |    100 |
| fo           |     100 |          100 |    100 |
| fr           |   20000 |        10000 |  10000 |
| frr          |     100 |          100 |    100 |
| fur          |     100 |          100 |    100 |
| fy           |    1000 |         1000 |   1000 |
| ga           |    1000 |         1000 |   1000 |
| gan          |     100 |          100 |    100 |
| gd           |     100 |          100 |    100 |
| gl           |   15000 |        10000 |  10000 |
| gn           |     100 |          100 |    100 |
| gu           |     100 |          100 |    100 |
| hak          |     100 |          100 |    100 |
| he           |   20000 |        10000 |  10000 |
| hi           |    5000 |         1000 |   1000 |
| hr           |   20000 |        10000 |  10000 |
| hsb          |     100 |          100 |    100 |
| hu           |   20000 |        10000 |  10000 |
| hy           |   15000 |         1000 |   1000 |
| ia           |     100 |          100 |    100 |
| id           |   20000 |        10000 |  10000 |
| ig           |     100 |          100 |    100 |
| ilo          |     100 |          100 |    100 |
| io           |     100 |          100 |    100 |
| is           |    1000 |         1000 |   1000 |
| it           |   20000 |        10000 |  10000 |
| ja           |   20000 |        10000 |  10000 |
| jbo          |     100 |          100 |    100 |
| jv           |     100 |          100 |    100 |
| ka           |   10000 |        10000 |  10000 |
| kk           |    1000 |         1000 |   1000 |
| km           |     100 |          100 |    100 |
| kn           |     100 |          100 |    100 |
| ko           |   20000 |        10000 |  10000 |
| ksh          |     100 |          100 |    100 |
| ku           |     100 |          100 |    100 |
| ky           |     100 |          100 |    100 |
| la           |    5000 |         1000 |   1000 |
| lb           |    5000 |         1000 |   1000 |
| li           |     100 |          100 |    100 |
| lij          |     100 |          100 |    100 |
| lmo          |     100 |          100 |    100 |
| ln           |     100 |          100 |    100 |
| lt           |   10000 |        10000 |  10000 |
| lv           |   10000 |        10000 |  10000 |
| map-bms      |     100 |          100 |    100 |
| mg           |     100 |          100 |    100 |
| mhr          |     100 |          100 |    100 |
| mi           |     100 |          100 |    100 |
| min          |     100 |          100 |    100 |
| mk           |   10000 |         1000 |   1000 |
| ml           |   10000 |         1000 |   1000 |
| mn           |     100 |          100 |    100 |
| mr           |    5000 |         1000 |   1000 |
| ms           |   20000 |         1000 |   1000 |
| mt           |     100 |          100 |    100 |
| mwl          |     100 |          100 |    100 |
| my           |     100 |          100 |    100 |
| mzn          |     100 |          100 |    100 |
| nap          |     100 |          100 |    100 |
| nds          |     100 |          100 |    100 |
| ne           |     100 |          100 |    100 |
| nl           |   20000 |        10000 |  10000 |
| nn           |   20000 |         1000 |   1000 |
| no           |   20000 |        10000 |  10000 |
| nov          |     100 |          100 |    100 |
| oc           |     100 |          100 |    100 |
| or           |     100 |          100 |    100 |
| os           |     100 |          100 |    100 |
| pa           |     100 |          100 |    100 |
| pdc          |     100 |          100 |    100 |
| pl           |   20000 |        10000 |  10000 |
| pms          |     100 |          100 |    100 |
| pnb          |     100 |          100 |    100 |
| ps           |     100 |          100 |    100 |
| pt           |   20000 |        10000 |  10000 |
| qu           |     100 |          100 |    100 |
| rm           |     100 |          100 |    100 |
| ro           |   20000 |        10000 |  10000 |
| ru           |   20000 |        10000 |  10000 |
| rw           |     100 |          100 |    100 |
| sa           |     100 |          100 |    100 |
| sah          |     100 |          100 |    100 |
| scn          |     100 |          100 |    100 |
| sco          |     100 |          100 |    100 |
| sd           |     100 |          100 |    100 |
| sh           |   20000 |        10000 |  10000 |
| si           |     100 |          100 |    100 |
| simple       |   20000 |         1000 |   1000 |
| sk           |   20000 |        10000 |  10000 |
| sl           |   15000 |        10000 |  10000 |
| so           |     100 |          100 |    100 |
| sq           |    5000 |         1000 |   1000 |
| sr           |   20000 |        10000 |  10000 |
| su           |     100 |          100 |    100 |
| sv           |   20000 |        10000 |  10000 |
| sw           |    1000 |         1000 |   1000 |
| szl          |     100 |          100 |    100 |
| ta           |   15000 |         1000 |   1000 |
| te           |    1000 |         1000 |   1000 |
| tg           |     100 |          100 |    100 |
| th           |   20000 |        10000 |  10000 |
| tk           |     100 |          100 |    100 |
| tl           |   10000 |         1000 |   1000 |
| tr           |   20000 |        10000 |  10000 |
| tt           |    1000 |         1000 |   1000 |
| ug           |     100 |          100 |    100 |
| uk           |   20000 |        10000 |  10000 |
| ur           |   20000 |         1000 |   1000 |
| uz           |    1000 |         1000 |   1000 |
| vec          |     100 |          100 |    100 |
| vep          |     100 |          100 |    100 |
| vi           |   20000 |        10000 |  10000 |
| vls          |     100 |          100 |    100 |
| vo           |     100 |          100 |    100 |
| wa           |     100 |          100 |    100 |
| war          |     100 |          100 |    100 |
| wuu          |     100 |          100 |    100 |
| xmf          |     100 |          100 |    100 |
| yi           |     100 |          100 |    100 |
| yo           |     100 |          100 |    100 |
| zea          |     100 |          100 |    100 |
| zh           |   20000 |        10000 |  10000 |
| zh-classical |     100 |          100 |    100 |
| zh-min-nan   |     100 |          100 |    100 |
| zh-yue       |   20000 |        10000 |  10000 |

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information

The original 282 datasets are associated with this article

```
@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://www.aclweb.org/anthology/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.",
}
```

while the 176 languages supported in this version are associated with the following article

```
@inproceedings{rahimi-etal-2019-massively,
    title = "Massively Multilingual Transfer for {NER}",
    author = "Rahimi, Afshin  and
      Li, Yuan  and
      Cohn, Trevor",
    booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
    month = jul,
    year = "2019",
    address = "Florence, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/P19-1015",
    pages = "151--164",
}
```


### Contributions

Thanks to [@lewtun](https://github.com/lewtun) and [@rabeehk](https://github.com/rabeehk) for adding this dataset.
task_categories:token-classification task_ids:named-entity-recognition annotations_creators:machine-generated language_creators:crowdsourced multilinguality:multilingual size_categories:n<1K source_datasets:original language:ace language:af language:als language:am language:an language:ang language:ar language:arc language:arz language:as language:ast language:ay language:az language:ba language:bar language:be language:bg language:bh language:bn language:bo language:br language:bs language:ca language:cbk language:cdo language:ce language:ceb language:ckb language:co language:crh language:cs language:csb language:cv language:cy language:da language:de language:diq language:dv language:el language:eml language:en language:eo language:es language:et language:eu language:ext language:fa language:fi language:fo language:fr language:frr language:fur language:fy language:ga language:gan language:gd language:gl language:gn language:gu language:hak language:he language:hi language:hr language:hsb language:hu language:hy language:ia language:id language:ig language:ilo language:io language:is language:it language:ja language:jbo language:jv language:ka language:kk language:km language:kn language:ko language:ksh language:ku language:ky language:la language:lb language:li language:lij language:lmo language:ln language:lt language:lv language:lzh language:mg language:mhr language:mi language:min language:mk language:ml language:mn language:mr language:ms language:mt language:mwl language:my language:mzn language:nan language:nap language:nds language:ne language:nl language:nn language:no language:nov language:oc language:or language:os language:pa language:pdc language:pl language:pms language:pnb language:ps language:pt language:qu language:rm language:ro language:ru language:rw language:sa language:sah language:scn language:sco language:sd language:sgs language:sh language:si language:sk language:sl language:so language:sq language:sr language:su language:sv language:sw language:szl language:ta language:te language:tg language:th language:tk language:tl language:tr language:tt language:ug language:uk language:ur language:uz language:vec language:vep language:vi language:vls language:vo language:vro language:wa language:war language:wuu language:xmf language:yi language:yo language:yue language:zea language:zh license:unknown arxiv:1902.00193 region:us
{"annotations_creators": ["machine-generated"], "language_creators": ["crowdsourced"], "language": ["ace", "af", "als", "am", "an", "ang", "ar", "arc", "arz", "as", "ast", "ay", "az", "ba", "bar", "be", "bg", "bh", "bn", "bo", "br", "bs", "ca", "cbk", "cdo", "ce", "ceb", "ckb", "co", "crh", "cs", "csb", "cv", "cy", "da", "de", "diq", "dv", "el", "eml", "en", "eo", "es", "et", "eu", "ext", "fa", "fi", "fo", "fr", "frr", "fur", "fy", "ga", "gan", "gd", "gl", "gn", "gu", "hak", "he", "hi", "hr", "hsb", "hu", "hy", "ia", "id", "ig", "ilo", "io", "is", "it", "ja", "jbo", "jv", "ka", "kk", "km", "kn", "ko", "ksh", "ku", "ky", "la", "lb", "li", "lij", "lmo", "ln", "lt", "lv", "lzh", "mg", "mhr", "mi", "min", "mk", "ml", "mn", "mr", "ms", "mt", "mwl", "my", "mzn", "nan", "nap", "nds", "ne", "nl", "nn", "no", "nov", "oc", "or", "os", "pa", "pdc", "pl", "pms", "pnb", "ps", "pt", "qu", "rm", "ro", "ru", "rw", "sa", "sah", "scn", "sco", "sd", "sgs", "sh", "si", "sk", "sl", "so", "sq", "sr", "su", "sv", "sw", "szl", "ta", "te", "tg", "th", "tk", "tl", "tr", "tt", "ug", "uk", "ur", "uz", "vec", "vep", "vi", "vls", "vo", "vro", "wa", "war", "wuu", "xmf", "yi", "yo", "yue", "zea", "zh"], "license": ["unknown"], "multilinguality": ["multilingual"], "size_categories": ["n<1K"], "source_datasets": ["original"], "task_categories": ["token-classification"], "task_ids": ["named-entity-recognition"], "paperswithcode_id": "wikiann-1", "pretty_name": "WikiANN", "config_names": ["no", "ace", "af", "als", "am", "an", "ang", "ar", "arc", "arz", "as", "ast", "ay", "az", "ba", "bar", "be", "bg", "bh", "bn", "bo", "br", "bs", "ca", "cdo", "ce", "ceb", "ckb", "co", "crh", "cs", "csb", "cv", "cy", "da", "de", "diq", "dv", "el", "en", "eo", "es", "et", "eu", "ext", "fa", "fi", "fo", "fr", "frr", "fur", "fy", "ga", "gan", "gd", "gl", "gn", "gu", "hak", "he", "hi", "hr", "hsb", "hu", "hy", "ia", "id", "ig", "ilo", "io", "is", "it", "ja", "jbo", "jv", "ka", "kk", "km", "kn", "ko", "ksh", "ku", "ky", "la", "lb", "li", "lij", "lmo", "ln", "lt", "lv", "mg", "mhr", "mi", "min", "mk", "ml", "mn", "mr", "ms", "mt", "mwl", "my", "mzn", "nap", "nds", "ne", "nl", "nn", "nov", "oc", "or", "os", "other-bat-smg", "other-be-x-old", "other-cbk-zam", "other-eml", "other-fiu-vro", "other-map-bms", "other-simple", "other-zh-classical", "other-zh-min-nan", "other-zh-yue", "pa", "pdc", "pl", "pms", "pnb", "ps", "pt", "qu", "rm", "ro", "ru", "rw", "sa", "sah", "scn", "sco", "sd", "sh", "si", "sk", "sl", "so", "sq", "sr", "su", "sv", "sw", "szl", "ta", "te", "tg", "th", "tk", "tl", "tr", "tt", "ug", "uk", "ur", "uz", "vec", "vep", "vi", "vls", "vo", "wa", "war", "wuu", "xmf", "yi", "yo", "zea", "zh"], "language_bcp47": ["be-tarask", "en-basiceng", "jv-x-bms"], "dataset_info": [{"config_name": "ace", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 22453, "num_examples": 100}, {"name": "test", "num_bytes": 25752, "num_examples": 100}, {"name": "train", "num_bytes": 23231, "num_examples": 100}], "download_size": 234008884, "dataset_size": 71436}, {"config_name": "af", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 299137, "num_examples": 1000}, {"name": "test", "num_bytes": 295849, "num_examples": 1000}, {"name": "train", "num_bytes": 1521604, "num_examples": 5000}], "download_size": 234008884, "dataset_size": 2116590}, {"config_name": "als", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 34318, "num_examples": 100}, {"name": "test", "num_bytes": 36345, "num_examples": 100}, {"name": "train", "num_bytes": 34968, "num_examples": 100}], "download_size": 234008884, "dataset_size": 105631}, {"config_name": "am", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 21429, "num_examples": 100}, {"name": "test", "num_bytes": 23811, "num_examples": 100}, {"name": "train", "num_bytes": 22214, "num_examples": 100}], "download_size": 234008884, "dataset_size": 67454}, {"config_name": "an", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 180609, "num_examples": 1000}, {"name": "test", "num_bytes": 174992, "num_examples": 1000}, {"name": "train", "num_bytes": 180967, "num_examples": 1000}], "download_size": 234008884, "dataset_size": 536568}, {"config_name": "ang", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 21925, "num_examples": 100}, {"name": "test", "num_bytes": 24523, "num_examples": 100}, {"name": "train", "num_bytes": 23296, "num_examples": 100}], "download_size": 234008884, "dataset_size": 69744}, {"config_name": "ar", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2325688, "num_examples": 10000}, {"name": "test", "num_bytes": 2334664, "num_examples": 10000}, {"name": "train", "num_bytes": 4671669, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 9332021}, {"config_name": "arc", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 15726, "num_examples": 100}, {"name": "test", "num_bytes": 16641, "num_examples": 100}, {"name": "train", "num_bytes": 18536, "num_examples": 100}], "download_size": 234008884, "dataset_size": 50903}, {"config_name": "arz", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 26609, "num_examples": 100}, {"name": "test", "num_bytes": 25663, "num_examples": 100}, {"name": "train", "num_bytes": 26375, "num_examples": 100}], "download_size": 234008884, "dataset_size": 78647}, {"config_name": "as", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 25736, "num_examples": 100}, {"name": "test", "num_bytes": 23350, "num_examples": 100}, {"name": "train", "num_bytes": 24984, "num_examples": 100}], "download_size": 234008884, "dataset_size": 74070}, {"config_name": "ast", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 217477, "num_examples": 1000}, {"name": "test", "num_bytes": 220874, "num_examples": 1000}, {"name": "train", "num_bytes": 228238, "num_examples": 1000}], "download_size": 234008884, "dataset_size": 666589}, {"config_name": "ay", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 11684, "num_examples": 100}, {"name": "test", "num_bytes": 13379, "num_examples": 100}, {"name": "train", "num_bytes": 12596, "num_examples": 100}], "download_size": 234008884, "dataset_size": 37659}, {"config_name": "az", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 272066, "num_examples": 1000}, {"name": "test", "num_bytes": 267935, "num_examples": 1000}, {"name": "train", "num_bytes": 2645552, "num_examples": 10000}], "download_size": 234008884, "dataset_size": 3185553}, {"config_name": "ba", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 29262, "num_examples": 100}, {"name": "test", "num_bytes": 30502, "num_examples": 100}, {"name": "train", "num_bytes": 31123, "num_examples": 100}], "download_size": 234008884, "dataset_size": 90887}, {"config_name": "bar", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 17374, "num_examples": 100}, {"name": "test", "num_bytes": 17839, "num_examples": 100}, {"name": "train", "num_bytes": 16796, "num_examples": 100}], "download_size": 234008884, "dataset_size": 52009}, {"config_name": "bat-smg", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 26496, "num_examples": 100}, {"name": "test", "num_bytes": 26093, "num_examples": 100}, {"name": "train", "num_bytes": 24677, "num_examples": 100}], "download_size": 234008884, "dataset_size": 77266}, {"config_name": "be", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 262042, "num_examples": 1000}, {"name": "test", "num_bytes": 266104, "num_examples": 1000}, {"name": "train", "num_bytes": 3983322, "num_examples": 15000}], "download_size": 234008884, "dataset_size": 4511468}, {"config_name": "be-x-old", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 342654, "num_examples": 1000}, {"name": "test", "num_bytes": 337599, "num_examples": 1000}, {"name": "train", "num_bytes": 1704256, "num_examples": 5000}], "download_size": 234008884, "dataset_size": 2384509}, {"config_name": "bg", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2840907, "num_examples": 10000}, {"name": "test", "num_bytes": 2830213, "num_examples": 10000}, {"name": "train", "num_bytes": 5665063, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 11336183}, {"config_name": "bh", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 33682, "num_examples": 100}, {"name": "test", "num_bytes": 30692, "num_examples": 100}, {"name": "train", "num_bytes": 36374, "num_examples": 100}], "download_size": 234008884, "dataset_size": 100748}, {"config_name": "bn", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 238446, "num_examples": 1000}, {"name": "test", "num_bytes": 237218, "num_examples": 1000}, {"name": "train", "num_bytes": 2351591, "num_examples": 10000}], "download_size": 234008884, "dataset_size": 2827255}, {"config_name": "bo", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 22688, "num_examples": 100}, {"name": "test", "num_bytes": 15437, "num_examples": 100}, {"name": "train", "num_bytes": 14085, "num_examples": 100}], "download_size": 234008884, "dataset_size": 52210}, {"config_name": "br", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 206839, "num_examples": 1000}, {"name": "test", "num_bytes": 222083, "num_examples": 1000}, {"name": "train", "num_bytes": 221495, "num_examples": 1000}], "download_size": 234008884, "dataset_size": 650417}, {"config_name": "bs", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 246378, "num_examples": 1000}, {"name": "test", "num_bytes": 247331, "num_examples": 1000}, {"name": "train", "num_bytes": 3669346, "num_examples": 15000}], "download_size": 234008884, "dataset_size": 4163055}, {"config_name": "ca", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 1836319, "num_examples": 10000}, {"name": "test", "num_bytes": 1847746, "num_examples": 10000}, {"name": "train", "num_bytes": 3689342, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 7373407}, {"config_name": "cbk-zam", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 47060, "num_examples": 100}, {"name": "test", "num_bytes": 47277, "num_examples": 100}, {"name": "train", "num_bytes": 52545, "num_examples": 100}], "download_size": 234008884, "dataset_size": 146882}, {"config_name": "cdo", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 37479, "num_examples": 100}, {"name": "test", "num_bytes": 34319, "num_examples": 100}, {"name": "train", "num_bytes": 36204, "num_examples": 100}], "download_size": 234008884, "dataset_size": 108002}, {"config_name": "ce", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 40303, "num_examples": 100}, {"name": "test", "num_bytes": 38640, "num_examples": 100}, {"name": "train", "num_bytes": 38284, "num_examples": 100}], "download_size": 234008884, "dataset_size": 117227}, {"config_name": "ceb", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 22789, "num_examples": 100}, {"name": "test", "num_bytes": 23950, "num_examples": 100}, {"name": "train", "num_bytes": 21365, "num_examples": 100}], "download_size": 234008884, "dataset_size": 68104}, {"config_name": "ckb", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 214231, "num_examples": 1000}, {"name": "test", "num_bytes": 211988, "num_examples": 1000}, {"name": "train", "num_bytes": 217066, "num_examples": 1000}], "download_size": 234008884, "dataset_size": 643285}, {"config_name": "co", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 15968, "num_examples": 100}, {"name": "test", "num_bytes": 15880, "num_examples": 100}, {"name": "train", "num_bytes": 18032, "num_examples": 100}], "download_size": 234008884, "dataset_size": 49880}, {"config_name": "crh", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 20230, "num_examples": 100}, {"name": "test", "num_bytes": 23879, "num_examples": 100}, {"name": "train", "num_bytes": 23336, "num_examples": 100}], "download_size": 234008884, "dataset_size": 67445}, {"config_name": "cs", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2456654, "num_examples": 10000}, {"name": "test", "num_bytes": 2458155, "num_examples": 10000}, {"name": "train", "num_bytes": 4944758, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 9859567}, {"config_name": "csb", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 28841, "num_examples": 100}, {"name": "test", "num_bytes": 27840, "num_examples": 100}, {"name": "train", "num_bytes": 31640, "num_examples": 100}], "download_size": 234008884, "dataset_size": 88321}, {"config_name": "cv", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 24787, "num_examples": 100}, {"name": "test", "num_bytes": 26403, "num_examples": 100}, {"name": "train", "num_bytes": 26956, "num_examples": 100}], "download_size": 234008884, "dataset_size": 78146}, {"config_name": "cy", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 228586, "num_examples": 1000}, {"name": "test", "num_bytes": 233869, "num_examples": 1000}, {"name": "train", "num_bytes": 2337116, "num_examples": 10000}], "download_size": 234008884, "dataset_size": 2799571}, {"config_name": "da", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2422976, "num_examples": 10000}, {"name": "test", "num_bytes": 2432324, "num_examples": 10000}, {"name": "train", "num_bytes": 4882222, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 9737522}, {"config_name": "de", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2754550, "num_examples": 10000}, {"name": "test", "num_bytes": 2750996, "num_examples": 10000}, {"name": "train", "num_bytes": 5510641, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 11016187}, {"config_name": "diq", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 24147, "num_examples": 100}, {"name": "test", "num_bytes": 22476, "num_examples": 100}, {"name": "train", "num_bytes": 24131, "num_examples": 100}], "download_size": 234008884, "dataset_size": 70754}, {"config_name": "dv", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 30322, "num_examples": 100}, {"name": "test", "num_bytes": 27279, "num_examples": 100}, {"name": "train", "num_bytes": 31033, "num_examples": 100}], "download_size": 234008884, "dataset_size": 88634}, {"config_name": "el", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 3027962, "num_examples": 10000}, {"name": "test", "num_bytes": 3034329, "num_examples": 10000}, {"name": "train", "num_bytes": 6046638, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 12108929}, {"config_name": "eml", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 30050, "num_examples": 100}, {"name": "test", "num_bytes": 35880, "num_examples": 100}, {"name": "train", "num_bytes": 30792, "num_examples": 100}], "download_size": 234008884, "dataset_size": 96722}, {"config_name": "en", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2336353, "num_examples": 10000}, {"name": "test", "num_bytes": 2330245, "num_examples": 10000}, {"name": "train", "num_bytes": 4649601, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 9316199}, {"config_name": "eo", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 1968690, "num_examples": 10000}, {"name": "test", "num_bytes": 1961486, "num_examples": 10000}, {"name": "train", "num_bytes": 2952610, "num_examples": 15000}], "download_size": 234008884, "dataset_size": 6882786}, {"config_name": "es", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 1976935, "num_examples": 10000}, {"name": "test", "num_bytes": 1986664, "num_examples": 10000}, {"name": "train", "num_bytes": 3972292, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 7935891}, {"config_name": "et", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2403361, "num_examples": 10000}, {"name": "test", "num_bytes": 2392424, "num_examples": 10000}, {"name": "train", "num_bytes": 3579264, "num_examples": 15000}], "download_size": 234008884, "dataset_size": 8375049}, {"config_name": "eu", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2677036, "num_examples": 10000}, {"name": "test", "num_bytes": 2628951, "num_examples": 10000}, {"name": "train", "num_bytes": 2672353, "num_examples": 10000}], "download_size": 234008884, "dataset_size": 7978340}, {"config_name": "ext", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 30821, "num_examples": 100}, {"name": "test", "num_bytes": 29483, "num_examples": 100}, {"name": "train", "num_bytes": 23110, "num_examples": 100}], "download_size": 234008884, "dataset_size": 83414}, {"config_name": "fa", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2328640, "num_examples": 10000}, {"name": "test", "num_bytes": 2314687, "num_examples": 10000}, {"name": "train", "num_bytes": 4618098, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 9261425}, {"config_name": "fi", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2500586, "num_examples": 10000}, {"name": "test", "num_bytes": 2505161, "num_examples": 10000}, {"name": "train", "num_bytes": 5020655, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 10026402}, {"config_name": "fiu-vro", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 27672, "num_examples": 100}, {"name": "test", "num_bytes": 27728, "num_examples": 100}, {"name": "train", "num_bytes": 28689, "num_examples": 100}], "download_size": 234008884, "dataset_size": 84089}, {"config_name": "fo", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 26094, "num_examples": 100}, {"name": "test", "num_bytes": 23531, "num_examples": 100}, {"name": "train", "num_bytes": 26178, "num_examples": 100}], "download_size": 234008884, "dataset_size": 75803}, {"config_name": "fr", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2058004, "num_examples": 10000}, {"name": "test", "num_bytes": 2073593, "num_examples": 10000}, {"name": "train", "num_bytes": 4123995, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 8255592}, {"config_name": "frr", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 15883, "num_examples": 100}, {"name": "test", "num_bytes": 15736, "num_examples": 100}, {"name": "train", "num_bytes": 16654, "num_examples": 100}], "download_size": 234008884, "dataset_size": 48273}, {"config_name": "fur", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 25264, "num_examples": 100}, {"name": "test", "num_bytes": 30562, "num_examples": 100}, {"name": "train", "num_bytes": 33654, "num_examples": 100}], "download_size": 234008884, "dataset_size": 89480}, {"config_name": "fy", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 226436, "num_examples": 1000}, {"name": "test", "num_bytes": 229700, "num_examples": 1000}, {"name": "train", "num_bytes": 223013, "num_examples": 1000}], "download_size": 234008884, "dataset_size": 679149}, {"config_name": "ga", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 234092, "num_examples": 1000}, {"name": "test", "num_bytes": 235083, "num_examples": 1000}, {"name": "train", "num_bytes": 238047, "num_examples": 1000}], "download_size": 234008884, "dataset_size": 707222}, {"config_name": "gan", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 17533, "num_examples": 100}, {"name": "test", "num_bytes": 13879, "num_examples": 100}, {"name": "train", "num_bytes": 14398, "num_examples": 100}], "download_size": 234008884, "dataset_size": 45810}, {"config_name": "gd", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 23230, "num_examples": 100}, {"name": "test", "num_bytes": 20308, "num_examples": 100}, {"name": "train", "num_bytes": 20154, "num_examples": 100}], "download_size": 234008884, "dataset_size": 63692}, {"config_name": "gl", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2029683, "num_examples": 10000}, {"name": "test", "num_bytes": 2031150, "num_examples": 10000}, {"name": "train", "num_bytes": 3030993, "num_examples": 15000}], "download_size": 234008884, "dataset_size": 7091826}, {"config_name": "gn", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 29132, "num_examples": 100}, {"name": "test", "num_bytes": 24263, "num_examples": 100}, {"name": "train", "num_bytes": 28220, "num_examples": 100}], "download_size": 234008884, "dataset_size": 81615}, {"config_name": "gu", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 48009, "num_examples": 100}, {"name": "test", "num_bytes": 45417, "num_examples": 100}, {"name": "train", "num_bytes": 42625, "num_examples": 100}], "download_size": 234008884, "dataset_size": 136051}, {"config_name": "hak", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 17977, "num_examples": 100}, {"name": "test", "num_bytes": 18155, "num_examples": 100}, {"name": "train", "num_bytes": 16208, "num_examples": 100}], "download_size": 234008884, "dataset_size": 52340}, {"config_name": "he", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2801392, "num_examples": 10000}, {"name": "test", "num_bytes": 2785474, "num_examples": 10000}, {"name": "train", "num_bytes": 5600488, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 11187354}, {"config_name": "hi", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 261207, "num_examples": 1000}, {"name": "test", "num_bytes": 267255, "num_examples": 1000}, {"name": "train", "num_bytes": 1315829, "num_examples": 5000}], "download_size": 234008884, "dataset_size": 1844291}, {"config_name": "hr", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2417450, "num_examples": 10000}, {"name": "test", "num_bytes": 2430440, "num_examples": 10000}, {"name": "train", "num_bytes": 4877331, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 9725221}, {"config_name": "hsb", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 24695, "num_examples": 100}, {"name": "test", "num_bytes": 24348, "num_examples": 100}, {"name": "train", "num_bytes": 24228, "num_examples": 100}], "download_size": 234008884, "dataset_size": 73271}, {"config_name": "hu", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2590116, "num_examples": 10000}, {"name": "test", "num_bytes": 2626771, "num_examples": 10000}, {"name": "train", "num_bytes": 5263122, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 10480009}, {"config_name": "hy", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 237560, "num_examples": 1000}, {"name": "test", "num_bytes": 237121, "num_examples": 1000}, {"name": "train", "num_bytes": 3634065, "num_examples": 15000}], "download_size": 234008884, "dataset_size": 4108746}, {"config_name": "ia", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 32064, "num_examples": 100}, {"name": "test", "num_bytes": 37617, "num_examples": 100}, {"name": "train", "num_bytes": 32928, "num_examples": 100}], "download_size": 234008884, "dataset_size": 102609}, {"config_name": "id", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 1901625, "num_examples": 10000}, {"name": "test", "num_bytes": 1902732, "num_examples": 10000}, {"name": "train", "num_bytes": 3814047, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 7618404}, {"config_name": "ig", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 17721, "num_examples": 100}, {"name": "test", "num_bytes": 18432, "num_examples": 100}, {"name": "train", "num_bytes": 15988, "num_examples": 100}], "download_size": 234008884, "dataset_size": 52141}, {"config_name": "ilo", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 16675, "num_examples": 100}, {"name": "test", "num_bytes": 17245, "num_examples": 100}, {"name": "train", "num_bytes": 17152, "num_examples": 100}], "download_size": 234008884, "dataset_size": 51072}, {"config_name": "io", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 19026, "num_examples": 100}, {"name": "test", "num_bytes": 17231, "num_examples": 100}, {"name": "train", "num_bytes": 20781, "num_examples": 100}], "download_size": 234008884, "dataset_size": 57038}, {"config_name": "is", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 243667, "num_examples": 1000}, {"name": "test", "num_bytes": 235946, "num_examples": 1000}, {"name": "train", "num_bytes": 243465, "num_examples": 1000}], "download_size": 234008884, "dataset_size": 723078}, {"config_name": "it", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2282947, "num_examples": 10000}, {"name": "test", "num_bytes": 2307618, "num_examples": 10000}, {"name": "train", "num_bytes": 4633575, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 9224140}, {"config_name": "ja", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 6775608, "num_examples": 10000}, {"name": "test", "num_bytes": 6898538, "num_examples": 10000}, {"name": "train", "num_bytes": 13578325, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 27252471}, {"config_name": "jbo", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 15618, "num_examples": 100}, {"name": "test", "num_bytes": 19586, "num_examples": 100}, {"name": "train", "num_bytes": 15070, "num_examples": 100}], "download_size": 234008884, "dataset_size": 50274}, {"config_name": "jv", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 17691, "num_examples": 100}, {"name": "test", "num_bytes": 20203, "num_examples": 100}, {"name": "train", "num_bytes": 19409, "num_examples": 100}], "download_size": 234008884, "dataset_size": 57303}, {"config_name": "ka", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 3454381, "num_examples": 10000}, {"name": "test", "num_bytes": 3480870, "num_examples": 10000}, {"name": "train", "num_bytes": 3428008, "num_examples": 10000}], "download_size": 234008884, "dataset_size": 10363259}, {"config_name": "kk", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 286502, "num_examples": 1000}, {"name": "test", "num_bytes": 284503, "num_examples": 1000}, {"name": "train", "num_bytes": 287952, "num_examples": 1000}], "download_size": 234008884, "dataset_size": 858957}, {"config_name": "km", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 29310, "num_examples": 100}, {"name": "test", "num_bytes": 36101, "num_examples": 100}, {"name": "train", "num_bytes": 31938, "num_examples": 100}], "download_size": 234008884, "dataset_size": 97349}, {"config_name": "kn", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 36853, "num_examples": 100}, {"name": "test", "num_bytes": 32278, "num_examples": 100}, {"name": "train", "num_bytes": 34346, "num_examples": 100}], "download_size": 234008884, "dataset_size": 103477}, {"config_name": "ko", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2553068, "num_examples": 10000}, {"name": "test", "num_bytes": 2547800, "num_examples": 10000}, {"name": "train", "num_bytes": 5107090, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 10207958}, {"config_name": "ksh", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 26338, "num_examples": 100}, {"name": "test", "num_bytes": 25249, "num_examples": 100}, {"name": "train", "num_bytes": 25941, "num_examples": 100}], "download_size": 234008884, "dataset_size": 77528}, {"config_name": "ku", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 22597, "num_examples": 100}, {"name": "test", "num_bytes": 20795, "num_examples": 100}, {"name": "train", "num_bytes": 22669, "num_examples": 100}], "download_size": 234008884, "dataset_size": 66061}, {"config_name": "ky", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 31010, "num_examples": 100}, {"name": "test", "num_bytes": 31896, "num_examples": 100}, {"name": "train", "num_bytes": 32768, "num_examples": 100}], "download_size": 234008884, "dataset_size": 95674}, {"config_name": "la", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 207205, "num_examples": 1000}, {"name": "test", "num_bytes": 198910, "num_examples": 1000}, {"name": "train", "num_bytes": 999050, "num_examples": 5000}], "download_size": 234008884, "dataset_size": 1405165}, {"config_name": "lb", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 253774, "num_examples": 1000}, {"name": "test", "num_bytes": 249989, "num_examples": 1000}, {"name": "train", "num_bytes": 1260939, "num_examples": 5000}], "download_size": 234008884, "dataset_size": 1764702}, {"config_name": "li", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 20201, "num_examples": 100}, {"name": "test", "num_bytes": 18817, "num_examples": 100}, {"name": "train", "num_bytes": 20211, "num_examples": 100}], "download_size": 234008884, "dataset_size": 59229}, {"config_name": "lij", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 28005, "num_examples": 100}, {"name": "test", "num_bytes": 27882, "num_examples": 100}, {"name": "train", "num_bytes": 30581, "num_examples": 100}], "download_size": 234008884, "dataset_size": 86468}, {"config_name": "lmo", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 26575, "num_examples": 100}, {"name": "test", "num_bytes": 29453, "num_examples": 100}, {"name": "train", "num_bytes": 24161, "num_examples": 100}], "download_size": 234008884, "dataset_size": 80189}, {"config_name": "ln", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 21709, "num_examples": 100}, {"name": "test", "num_bytes": 27003, "num_examples": 100}, {"name": "train", "num_bytes": 22227, "num_examples": 100}], "download_size": 234008884, "dataset_size": 70939}, {"config_name": "lt", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2192874, "num_examples": 10000}, {"name": "test", "num_bytes": 2191269, "num_examples": 10000}, {"name": "train", "num_bytes": 2199946, "num_examples": 10000}], "download_size": 234008884, "dataset_size": 6584089}, {"config_name": "lv", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2173420, "num_examples": 10000}, {"name": "test", "num_bytes": 2190458, "num_examples": 10000}, {"name": "train", "num_bytes": 2206943, "num_examples": 10000}], "download_size": 234008884, "dataset_size": 6570821}, {"config_name": "map-bms", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 19780, "num_examples": 100}, {"name": "test", "num_bytes": 20558, "num_examples": 100}, {"name": "train", "num_bytes": 21639, "num_examples": 100}], "download_size": 234008884, "dataset_size": 61977}, {"config_name": "mg", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 24861, "num_examples": 100}, {"name": "test", "num_bytes": 22570, "num_examples": 100}, {"name": "train", "num_bytes": 25739, "num_examples": 100}], "download_size": 234008884, "dataset_size": 73170}, {"config_name": "mhr", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 23263, "num_examples": 100}, {"name": "test", "num_bytes": 23639, "num_examples": 100}, {"name": "train", "num_bytes": 18648, "num_examples": 100}], "download_size": 234008884, "dataset_size": 65550}, {"config_name": "mi", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 39399, "num_examples": 100}, {"name": "test", "num_bytes": 40147, "num_examples": 100}, {"name": "train", "num_bytes": 37896, "num_examples": 100}], "download_size": 234008884, "dataset_size": 117442}, {"config_name": "min", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 28719, "num_examples": 100}, {"name": "test", "num_bytes": 24741, "num_examples": 100}, {"name": "train", "num_bytes": 26620, "num_examples": 100}], "download_size": 234008884, "dataset_size": 80080}, {"config_name": "mk", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 333193, "num_examples": 1000}, {"name": "test", "num_bytes": 337757, "num_examples": 1000}, {"name": "train", "num_bytes": 3355936, "num_examples": 10000}], "download_size": 234008884, "dataset_size": 4026886}, {"config_name": "ml", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 363008, "num_examples": 1000}, {"name": "test", "num_bytes": 349383, "num_examples": 1000}, {"name": "train", "num_bytes": 3582066, "num_examples": 10000}], "download_size": 234008884, "dataset_size": 4294457}, {"config_name": "mn", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 22006, "num_examples": 100}, {"name": "test", "num_bytes": 23538, "num_examples": 100}, {"name": "train", "num_bytes": 23244, "num_examples": 100}], "download_size": 234008884, "dataset_size": 68788}, {"config_name": "mr", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 314858, "num_examples": 1000}, {"name": "test", "num_bytes": 326290, "num_examples": 1000}, {"name": "train", "num_bytes": 1598804, "num_examples": 5000}], "download_size": 234008884, "dataset_size": 2239952}, {"config_name": "ms", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 183944, "num_examples": 1000}, {"name": "test", "num_bytes": 183539, "num_examples": 1000}, {"name": "train", "num_bytes": 3699238, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 4066721}, {"config_name": "mt", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 24571, "num_examples": 100}, {"name": "test", "num_bytes": 24662, "num_examples": 100}, {"name": "train", "num_bytes": 24956, "num_examples": 100}], "download_size": 234008884, "dataset_size": 74189}, {"config_name": "mwl", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 51987, "num_examples": 100}, {"name": "test", "num_bytes": 43008, "num_examples": 100}, {"name": "train", "num_bytes": 44605, "num_examples": 100}], "download_size": 234008884, "dataset_size": 139600}, {"config_name": "my", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 48953, "num_examples": 100}, {"name": "test", "num_bytes": 45956, "num_examples": 100}, {"name": "train", "num_bytes": 41371, "num_examples": 100}], "download_size": 234008884, "dataset_size": 136280}, {"config_name": "mzn", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 25304, "num_examples": 100}, {"name": "test", "num_bytes": 25947, "num_examples": 100}, {"name": "train", "num_bytes": 24841, "num_examples": 100}], "download_size": 234008884, "dataset_size": 76092}, {"config_name": "nap", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 21546, "num_examples": 100}, {"name": "test", "num_bytes": 24194, "num_examples": 100}, {"name": "train", "num_bytes": 26596, "num_examples": 100}], "download_size": 234008884, "dataset_size": 72336}, {"config_name": "nds", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 28388, "num_examples": 100}, {"name": "test", "num_bytes": 26571, "num_examples": 100}, {"name": "train", "num_bytes": 24679, "num_examples": 100}], "download_size": 234008884, "dataset_size": 79638}, {"config_name": "ne", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 33932, "num_examples": 100}, {"name": "test", "num_bytes": 33227, "num_examples": 100}, {"name": "train", "num_bytes": 36173, "num_examples": 100}], "download_size": 234008884, "dataset_size": 103332}, {"config_name": "nl", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2378080, "num_examples": 10000}, {"name": "test", "num_bytes": 2403076, "num_examples": 10000}, {"name": "train", "num_bytes": 4784289, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 9565445}, {"config_name": "nn", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 274140, "num_examples": 1000}, {"name": "test", "num_bytes": 269631, "num_examples": 1000}, {"name": "train", "num_bytes": 5436185, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 5979956}, {"config_name": "no", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2576669, "num_examples": 10000}, {"name": "test", "num_bytes": 2563559, "num_examples": 10000}, {"name": "train", "num_bytes": 5139548, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 10279776}, {"config_name": "nov", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 14856, "num_examples": 100}, {"name": "test", "num_bytes": 14830, "num_examples": 100}, {"name": "train", "num_bytes": 17270, "num_examples": 100}], "download_size": 234008884, "dataset_size": 46956}, {"config_name": "oc", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 20428, "num_examples": 100}, {"name": "test", "num_bytes": 18600, "num_examples": 100}, {"name": "train", "num_bytes": 19319, "num_examples": 100}], "download_size": 234008884, "dataset_size": 58347}, {"config_name": "or", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 32131, "num_examples": 100}, {"name": "test", "num_bytes": 29508, "num_examples": 100}, {"name": "train", "num_bytes": 27822, "num_examples": 100}], "download_size": 234008884, "dataset_size": 89461}, {"config_name": "os", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 26779, "num_examples": 100}, {"name": "test", "num_bytes": 25995, "num_examples": 100}, {"name": "train", "num_bytes": 26033, "num_examples": 100}], "download_size": 234008884, "dataset_size": 78807}, {"config_name": "pa", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 25230, "num_examples": 100}, {"name": "test", "num_bytes": 23708, "num_examples": 100}, {"name": "train", "num_bytes": 24171, "num_examples": 100}], "download_size": 234008884, "dataset_size": 73109}, {"config_name": "pdc", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 24419, "num_examples": 100}, {"name": "test", "num_bytes": 24674, "num_examples": 100}, {"name": "train", "num_bytes": 23991, "num_examples": 100}], "download_size": 234008884, "dataset_size": 73084}, {"config_name": "pl", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2448324, "num_examples": 10000}, {"name": "test", "num_bytes": 2463783, "num_examples": 10000}, {"name": "train", "num_bytes": 4851527, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 9763634}, {"config_name": "pms", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 28369, "num_examples": 100}, {"name": "test", "num_bytes": 24015, "num_examples": 100}, {"name": "train", "num_bytes": 27429, "num_examples": 100}], "download_size": 234008884, "dataset_size": 79813}, {"config_name": "pnb", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 19070, "num_examples": 100}, {"name": "test", "num_bytes": 21206, "num_examples": 100}, {"name": "train", "num_bytes": 19504, "num_examples": 100}], "download_size": 234008884, "dataset_size": 59780}, {"config_name": "ps", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 49901, "num_examples": 100}, {"name": "test", "num_bytes": 43621, "num_examples": 100}, {"name": "train", "num_bytes": 63501, "num_examples": 100}], "download_size": 234008884, "dataset_size": 157023}, {"config_name": "pt", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 1962145, "num_examples": 10000}, {"name": "test", "num_bytes": 1946729, "num_examples": 10000}, {"name": "train", "num_bytes": 3917453, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 7826327}, {"config_name": "qu", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 18231, "num_examples": 100}, {"name": "test", "num_bytes": 17675, "num_examples": 100}, {"name": "train", "num_bytes": 16989, "num_examples": 100}], "download_size": 234008884, "dataset_size": 52895}, {"config_name": "rm", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 32776, "num_examples": 100}, {"name": "test", "num_bytes": 35880, "num_examples": 100}, {"name": "train", "num_bytes": 30489, "num_examples": 100}], "download_size": 234008884, "dataset_size": 99145}, {"config_name": "ro", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2063860, "num_examples": 10000}, {"name": "test", "num_bytes": 2060933, "num_examples": 10000}, {"name": "train", "num_bytes": 4179869, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 8304662}, {"config_name": "ru", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2574546, "num_examples": 10000}, {"name": "test", "num_bytes": 2597248, "num_examples": 10000}, {"name": "train", "num_bytes": 5175665, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 10347459}, {"config_name": "rw", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 17999, "num_examples": 100}, {"name": "test", "num_bytes": 14445, "num_examples": 100}, {"name": "train", "num_bytes": 16778, "num_examples": 100}], "download_size": 234008884, "dataset_size": 49222}, {"config_name": "sa", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 45721, "num_examples": 100}, {"name": "test", "num_bytes": 49209, "num_examples": 100}, {"name": "train", "num_bytes": 52504, "num_examples": 100}], "download_size": 234008884, "dataset_size": 147434}, {"config_name": "sah", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 27875, "num_examples": 100}, {"name": "test", "num_bytes": 26853, "num_examples": 100}, {"name": "train", "num_bytes": 27041, "num_examples": 100}], "download_size": 234008884, "dataset_size": 81769}, {"config_name": "scn", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 20105, "num_examples": 100}, {"name": "test", "num_bytes": 17384, "num_examples": 100}, {"name": "train", "num_bytes": 21032, "num_examples": 100}], "download_size": 234008884, "dataset_size": 58521}, {"config_name": "sco", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 22215, "num_examples": 100}, {"name": "test", "num_bytes": 21589, "num_examples": 100}, {"name": "train", "num_bytes": 20308, "num_examples": 100}], "download_size": 234008884, "dataset_size": 64112}, {"config_name": "sd", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 51555, "num_examples": 100}, {"name": "test", "num_bytes": 38534, "num_examples": 100}, {"name": "train", "num_bytes": 56925, "num_examples": 100}], "download_size": 234008884, "dataset_size": 147014}, {"config_name": "sh", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 1789918, "num_examples": 10000}, {"name": "test", "num_bytes": 1791491, "num_examples": 10000}, {"name": "train", "num_bytes": 3583633, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 7165042}, {"config_name": "si", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 30845, "num_examples": 100}, {"name": "test", "num_bytes": 29341, "num_examples": 100}, {"name": "train", "num_bytes": 31255, "num_examples": 100}], "download_size": 234008884, "dataset_size": 91441}, {"config_name": "simple", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 247147, "num_examples": 1000}, {"name": "test", "num_bytes": 245358, "num_examples": 1000}, {"name": "train", "num_bytes": 4921916, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 5414421}, {"config_name": "sk", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2342061, "num_examples": 10000}, {"name": "test", "num_bytes": 2335009, "num_examples": 10000}, {"name": "train", "num_bytes": 4701553, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 9378623}, {"config_name": "sl", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2090247, "num_examples": 10000}, {"name": "test", "num_bytes": 2133491, "num_examples": 10000}, {"name": "train", "num_bytes": 3158676, "num_examples": 15000}], "download_size": 234008884, "dataset_size": 7382414}, {"config_name": "so", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 21864, "num_examples": 100}, {"name": "test", "num_bytes": 17219, "num_examples": 100}, {"name": "train", "num_bytes": 23780, "num_examples": 100}], "download_size": 234008884, "dataset_size": 62863}, {"config_name": "sq", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 210888, "num_examples": 1000}, {"name": "test", "num_bytes": 209824, "num_examples": 1000}, {"name": "train", "num_bytes": 1052387, "num_examples": 5000}], "download_size": 234008884, "dataset_size": 1473099}, {"config_name": "sr", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2548390, "num_examples": 10000}, {"name": "test", "num_bytes": 2564831, "num_examples": 10000}, {"name": "train", "num_bytes": 5105569, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 10218790}, {"config_name": "su", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 22605, "num_examples": 100}, {"name": "test", "num_bytes": 21861, "num_examples": 100}, {"name": "train", "num_bytes": 20839, "num_examples": 100}], "download_size": 234008884, "dataset_size": 65305}, {"config_name": "sv", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2678672, "num_examples": 10000}, {"name": "test", "num_bytes": 2719077, "num_examples": 10000}, {"name": "train", "num_bytes": 5395722, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 10793471}, {"config_name": "sw", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 168819, "num_examples": 1000}, {"name": "test", "num_bytes": 172693, "num_examples": 1000}, {"name": "train", "num_bytes": 168749, "num_examples": 1000}], "download_size": 234008884, "dataset_size": 510261}, {"config_name": "szl", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 19397, "num_examples": 100}, {"name": "test", "num_bytes": 18967, "num_examples": 100}, {"name": "train", "num_bytes": 17646, "num_examples": 100}], "download_size": 234008884, "dataset_size": 56010}, {"config_name": "ta", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 354957, "num_examples": 1000}, {"name": "test", "num_bytes": 357667, "num_examples": 1000}, {"name": "train", "num_bytes": 5275759, "num_examples": 15000}], "download_size": 234008884, "dataset_size": 5988383}, {"config_name": "te", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 356189, "num_examples": 1000}, {"name": "test", "num_bytes": 359780, "num_examples": 1000}, {"name": "train", "num_bytes": 358792, "num_examples": 1000}], "download_size": 234008884, "dataset_size": 1074761}, {"config_name": "tg", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 27130, "num_examples": 100}, {"name": "test", "num_bytes": 28821, "num_examples": 100}, {"name": "train", "num_bytes": 27200, "num_examples": 100}], "download_size": 234008884, "dataset_size": 83151}, {"config_name": "th", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 14189743, "num_examples": 10000}, {"name": "test", "num_bytes": 14505054, "num_examples": 10000}, {"name": "train", "num_bytes": 28968916, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 57663713}, {"config_name": "tk", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 21611, "num_examples": 100}, {"name": "test", "num_bytes": 20302, "num_examples": 100}, {"name": "train", "num_bytes": 19521, "num_examples": 100}], "download_size": 234008884, "dataset_size": 61434}, {"config_name": "tl", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 148682, "num_examples": 1000}, {"name": "test", "num_bytes": 152964, "num_examples": 1000}, {"name": "train", "num_bytes": 1518784, "num_examples": 10000}], "download_size": 234008884, "dataset_size": 1820430}, {"config_name": "tr", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2280517, "num_examples": 10000}, {"name": "test", "num_bytes": 2276920, "num_examples": 10000}, {"name": "train", "num_bytes": 4501912, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 9059349}, {"config_name": "tt", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 282535, "num_examples": 1000}, {"name": "test", "num_bytes": 282691, "num_examples": 1000}, {"name": "train", "num_bytes": 283392, "num_examples": 1000}], "download_size": 234008884, "dataset_size": 848618}, {"config_name": "ug", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 35219, "num_examples": 100}, {"name": "test", "num_bytes": 31129, "num_examples": 100}, {"name": "train", "num_bytes": 26620, "num_examples": 100}], "download_size": 234008884, "dataset_size": 92968}, {"config_name": "uk", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 2934897, "num_examples": 10000}, {"name": "test", "num_bytes": 2928200, "num_examples": 10000}, {"name": "train", "num_bytes": 5928026, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 11791123}, {"config_name": "ur", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 203747, "num_examples": 1000}, {"name": "test", "num_bytes": 203138, "num_examples": 1000}, {"name": "train", "num_bytes": 4108707, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 4515592}, {"config_name": "uz", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 184625, "num_examples": 1000}, {"name": "test", "num_bytes": 184713, "num_examples": 1000}, {"name": "train", "num_bytes": 186105, "num_examples": 1000}], "download_size": 234008884, "dataset_size": 555443}, {"config_name": "vec", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 19335, "num_examples": 100}, {"name": "test", "num_bytes": 20254, "num_examples": 100}, {"name": "train", "num_bytes": 20437, "num_examples": 100}], "download_size": 234008884, "dataset_size": 60026}, {"config_name": "vep", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 22306, "num_examples": 100}, {"name": "test", "num_bytes": 21371, "num_examples": 100}, {"name": "train", "num_bytes": 21387, "num_examples": 100}], "download_size": 234008884, "dataset_size": 65064}, {"config_name": "vi", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 1944856, "num_examples": 10000}, {"name": "test", "num_bytes": 1960024, "num_examples": 10000}, {"name": "train", "num_bytes": 3915944, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 7820824}, {"config_name": "vls", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 27895, "num_examples": 100}, {"name": "test", "num_bytes": 26778, "num_examples": 100}, {"name": "train", "num_bytes": 26183, "num_examples": 100}], "download_size": 234008884, "dataset_size": 80856}, {"config_name": "vo", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 14385, "num_examples": 100}, {"name": "test", "num_bytes": 14001, "num_examples": 100}, {"name": "train", "num_bytes": 14442, "num_examples": 100}], "download_size": 234008884, "dataset_size": 42828}, {"config_name": "wa", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 22493, "num_examples": 100}, {"name": "test", "num_bytes": 21581, "num_examples": 100}, {"name": "train", "num_bytes": 23072, "num_examples": 100}], "download_size": 234008884, "dataset_size": 67146}, {"config_name": "war", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 16834, "num_examples": 100}, {"name": "test", "num_bytes": 19912, "num_examples": 100}, {"name": "train", "num_bytes": 18829, "num_examples": 100}], "download_size": 234008884, "dataset_size": 55575}, {"config_name": "wuu", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 15123, "num_examples": 100}, {"name": "test", "num_bytes": 15067, "num_examples": 100}, {"name": "train", "num_bytes": 17016, "num_examples": 100}], "download_size": 234008884, "dataset_size": 47206}, {"config_name": "xmf", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 39979, "num_examples": 100}, {"name": "test", "num_bytes": 36081, "num_examples": 100}, {"name": "train", "num_bytes": 31796, "num_examples": 100}], "download_size": 234008884, "dataset_size": 107856}, {"config_name": "yi", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 25269, "num_examples": 100}, {"name": "test", "num_bytes": 25005, "num_examples": 100}, {"name": "train", "num_bytes": 27303, "num_examples": 100}], "download_size": 234008884, "dataset_size": 77577}, {"config_name": "yo", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 17738, "num_examples": 100}, {"name": "test", "num_bytes": 17996, "num_examples": 100}, {"name": "train", "num_bytes": 18984, "num_examples": 100}], "download_size": 234008884, "dataset_size": 54718}, {"config_name": "zea", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 24916, "num_examples": 100}, {"name": "test", "num_bytes": 22997, "num_examples": 100}, {"name": "train", "num_bytes": 21252, "num_examples": 100}], "download_size": 234008884, "dataset_size": 69165}, {"config_name": "zh", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 4839728, "num_examples": 10000}, {"name": "test", "num_bytes": 4709458, "num_examples": 10000}, {"name": "train", "num_bytes": 9524981, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 19074167}, {"config_name": "zh-classical", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 59980, "num_examples": 100}, {"name": "test", "num_bytes": 65885, "num_examples": 100}, {"name": "train", "num_bytes": 56238, "num_examples": 100}], "download_size": 234008884, "dataset_size": 182103}, {"config_name": "zh-min-nan", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 24533, "num_examples": 100}, {"name": "test", "num_bytes": 24326, "num_examples": 100}, {"name": "train", "num_bytes": 19358, "num_examples": 100}], "download_size": 234008884, "dataset_size": 68217}, {"config_name": "zh-yue", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PER", "2": "I-PER", "3": "B-ORG", "4": "I-ORG", "5": "B-LOC", "6": "I-LOC"}}}}, {"name": "langs", "sequence": "string"}, {"name": "spans", "sequence": "string"}], "splits": [{"name": "validation", "num_bytes": 4934158, "num_examples": 10000}, {"name": "test", "num_bytes": 4964029, "num_examples": 10000}, {"name": "train", "num_bytes": 9950629, "num_examples": 20000}], "download_size": 234008884, "dataset_size": 19848816}]}
TAGS
#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-machine-generated #language_creators-crowdsourced #multilinguality-multilingual #size_categories-n<1K #source_datasets-original #language-Achinese #language-Afrikaans #language-Tosk Albanian #language-Amharic #language-Aragonese #language-Old English (ca. 450-1100) #language-Arabic #language-Official Aramaic (700-300 BCE) #language-Egyptian Arabic #language-Assamese #language-Asturian #language-Aymara #language-Azerbaijani #language-Bashkir #language-Bavarian #language-Belarusian #language-Bulgarian #language-bh #language-Bengali #language-Tibetan #language-Breton #language-Bosnian #language-Catalan #language-Chavacano #language-Min Dong Chinese #language-Chechen #language-Cebuano #language-Central Kurdish #language-Corsican #language-Crimean Tatar #language-Czech #language-Kashubian #language-Chuvash #language-Welsh #language-Danish #language-German #language-Dimli (individual language) #language-Dhivehi #language-Modern Greek (1453-) #language-Emiliano-Romagnolo #language-English #language-Esperanto #language-Spanish #language-Estonian #language-Basque #language-Extremaduran #language-Persian #language-Finnish #language-Faroese #language-French #language-Northern Frisian #language-Friulian #language-Western Frisian #language-Irish #language-Gan Chinese #language-Scottish Gaelic #language-Galician #language-Guarani #language-Gujarati #language-Hakka Chinese #language-Hebrew #language-Hindi #language-Croatian #language-Upper Sorbian #language-Hungarian #language-Armenian #language-Interlingua (International Auxiliary Language Association) #language-Indonesian #language-Igbo #language-Iloko #language-Ido #language-Icelandic #language-Italian #language-Japanese #language-Lojban #language-Javanese #language-Georgian #language-Kazakh #language-Khmer #language-Kannada #language-Korean #language-Kölsch #language-Kurdish #language-Kirghiz #language-Latin #language-Luxembourgish #language-Limburgan #language-Ligurian #language-Lombard #language-Lingala #language-Lithuanian #language-Latvian #language-Literary Chinese #language-Malagasy #language-Eastern Mari #language-Maori #language-Minangkabau #language-Macedonian #language-Malayalam #language-Mongolian #language-Marathi #language-Malay (macrolanguage) #language-Maltese #language-Mirandese #language-Burmese #language-Mazanderani #language-Min Nan Chinese #language-Neapolitan #language-Low German #language-Nepali (macrolanguage) #language-Dutch #language-Norwegian Nynorsk #language-Norwegian #language-Novial #language-Occitan (post 1500) #language-Oriya (macrolanguage) #language-Ossetian #language-Panjabi #language-Pennsylvania German #language-Polish #language-Piemontese #language-Western Panjabi #language-Pushto #language-Portuguese #language-Quechua #language-Romansh #language-Romanian #language-Russian #language-Kinyarwanda #language-Sanskrit #language-Yakut #language-Sicilian #language-Scots #language-Sindhi #language-Samogitian #language-Serbo-Croatian #language-Sinhala #language-Slovak #language-Slovenian #language-Somali #language-Albanian #language-Serbian #language-Sundanese #language-Swedish #language-Swahili (macrolanguage) #language-Silesian #language-Tamil #language-Telugu #language-Tajik #language-Thai #language-Turkmen #language-Tagalog #language-Turkish #language-Tatar #language-Uighur #language-Ukrainian #language-Urdu #language-Uzbek #language-Venetian #language-Veps #language-Vietnamese #language-Vlaams #language-Volapük #language-Võro #language-Walloon #language-Waray (Philippines) #language-Wu Chinese #language-Mingrelian #language-Yiddish #language-Yoruba #language-Yue Chinese #language-Zeeuws #language-Chinese #license-unknown #arxiv-1902.00193 #region-us 

Dataset Card for WikiANN
========================


Table of Contents
-----------------


* Dataset Description
	+ Dataset Summary
	+ Supported Tasks and Leaderboards
	+ Languages
* Dataset Structure
	+ Data Instances
	+ Data Fields
	+ Data Splits
* Dataset Creation
	+ Curation Rationale
	+ Source Data
	+ Annotations
	+ Personal and Sensitive Information
* Considerations for Using the Data
	+ Social Impact of Dataset
	+ Discussion of Biases
	+ Other Known Limitations
* Additional Information
	+ Dataset Curators
	+ Licensing Information
	+ Citation Information
	+ Contributions


Dataset Description
-------------------


* Homepage: Massively Multilingual Transfer for NER
* Repository: Massively Multilingual Transfer for NER
* Paper: The original datasets come from the *Cross-lingual name tagging and linking for 282 languages* paper by Xiaoman Pan et al. (2018). This version corresponds to the balanced train, dev, and test splits of the original data from the *Massively Multilingual Transfer for NER* paper by Afshin Rahimi et al. (2019).
* Leaderboard:
* Point of Contact: Afshin Rahimi or Lewis Tunstall or Albert Villanova del Moral


### Dataset Summary


WikiANN (sometimes called PAN-X) is a multilingual named entity recognition dataset consisting of Wikipedia articles annotated with LOC (location), PER (person), and ORG (organisation) tags in the IOB2 format. This version corresponds to the balanced train, dev, and test splits of Rahimi et al. (2019), which supports 176 of the 282 languages from the original WikiANN corpus.


### Supported Tasks and Leaderboards


* 'named-entity-recognition': The dataset can be used to train a model for named entity recognition in many languages, or evaluate the zero-shot cross-lingual capabilities of multilingual models.


### Languages


The dataset contains 176 languages, one in each of the configuration subsets. The corresponding BCP 47 language tags
are:



Dataset Structure
-----------------


### Data Instances


This is an example in the "train" split of the "af" (Afrikaans language) configuration subset:


### Data Fields


* 'tokens': a 'list' of 'string' features.
* 'langs': a 'list' of 'string' features that correspond to the language of each token.
* 'ner\_tags': a 'list' of classification labels, with possible values including 'O' (0), 'B-PER' (1), 'I-PER' (2), 'B-ORG' (3), 'I-ORG' (4), 'B-LOC' (5), 'I-LOC' (6).
* 'spans': a 'list' of 'string' features, that is the list of named entities in the input text formatted as '': ''


### Data Splits


For each configuration subset, the data is split into "train", "validation" and "test" sets, each containing the
following number of examples:



Dataset Creation
----------------


### Curation Rationale


### Source Data


#### Initial Data Collection and Normalization


#### Who are the source language producers?


### Annotations


#### Annotation process


#### Who are the annotators?


### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------


### Social Impact of Dataset


### Discussion of Biases


### Other Known Limitations


Additional Information
----------------------


### Dataset Curators


### Licensing Information


The original 282 datasets are associated with this article


while the 176 languages supported in this version are associated with the following article


### Contributions


Thanks to @lewtun and @rabeehk for adding this dataset.



### Dataset Summary


WikiANN (sometimes called PAN-X) is a multilingual named entity recognition dataset consisting of Wikipedia articles annotated with LOC (location), PER (person), and ORG (organisation) tags in the IOB2 format. This version corresponds to the balanced train, dev, and test splits of Rahimi et al. (2019), which supports 176 of the 282 languages from the original WikiANN corpus. ### Supported Tasks and Leaderboards


* 'named-entity-recognition': The dataset can be used to train a model for named entity recognition in many languages, or evaluate the zero-shot cross-lingual capabilities of multilingual models. ### Languages


The dataset contains 176 languages, one in each of the configuration subsets. The corresponding BCP 47 language tags
are:



Dataset Structure
----------------- ### Data Instances


This is an example in the "train" split of the "af" (Afrikaans language) configuration subset: ### Data Fields


* 'tokens': a 'list' of 'string' features.
* 'langs': a 'list' of 'string' features that correspond to the language of each token.
* 'ner\_tags': a 'list' of classification labels, with possible values including 'O' (0), 'B-PER' (1), 'I-PER' (2), 'B-ORG' (3), 'I-ORG' (4), 'B-LOC' (5), 'I-LOC' (6).
* 'spans': a 'list' of 'string' features, that is the list of named entities in the input text formatted as '': '' ### Data Splits


For each configuration subset, the data is split into "train", "validation" and "test" sets, each containing the
following number of examples:



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information


The original 282 datasets are associated with this article


while the 176 languages supported in this version are associated with the following article ### Contributions


Thanks to @lewtun and @rabeehk for adding this dataset.
TAGS
#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-machine-generated #language_creators-crowdsourced #multilinguality-multilingual #size_categories-n<1K #source_datasets-original #language-Achinese #language-Afrikaans #language-Tosk Albanian #language-Amharic #language-Aragonese #language-Old English (ca. 450-1100) #language-Arabic #language-Official Aramaic (700-300 BCE) #language-Egyptian Arabic #language-Assamese #language-Asturian #language-Aymara #language-Azerbaijani #language-Bashkir #language-Bavarian #language-Belarusian #language-Bulgarian #language-bh #language-Bengali #language-Tibetan #language-Breton #language-Bosnian #language-Catalan #language-Chavacano #language-Min Dong Chinese #language-Chechen #language-Cebuano #language-Central Kurdish #language-Corsican #language-Crimean Tatar #language-Czech #language-Kashubian #language-Chuvash #language-Welsh #language-Danish #language-German #language-Dimli (individual language) #language-Dhivehi #language-Modern Greek (1453-) #language-Emiliano-Romagnolo #language-English #language-Esperanto #language-Spanish #language-Estonian #language-Basque #language-Extremaduran #language-Persian #language-Finnish #language-Faroese #language-French #language-Northern Frisian #language-Friulian #language-Western Frisian #language-Irish #language-Gan Chinese #language-Scottish Gaelic #language-Galician #language-Guarani #language-Gujarati #language-Hakka Chinese #language-Hebrew #language-Hindi #language-Croatian #language-Upper Sorbian #language-Hungarian #language-Armenian #language-Interlingua (International Auxiliary Language Association) #language-Indonesian #language-Igbo #language-Iloko #language-Ido #language-Icelandic #language-Italian #language-Japanese #language-Lojban #language-Javanese #language-Georgian #language-Kazakh #language-Khmer #language-Kannada #language-Korean #language-Kölsch #language-Kurdish #language-Kirghiz #language-Latin #language-Luxembourgish #language-Limburgan #language-Ligurian #language-Lombard #language-Lingala #language-Lithuanian #language-Latvian #language-Literary Chinese #language-Malagasy #language-Eastern Mari #language-Maori #language-Minangkabau #language-Macedonian #language-Malayalam #language-Mongolian #language-Marathi #language-Malay (macrolanguage) #language-Maltese #language-Mirandese #language-Burmese #language-Mazanderani #language-Min Nan Chinese #language-Neapolitan #language-Low German #language-Nepali (macrolanguage) #language-Dutch #language-Norwegian Nynorsk #language-Norwegian #language-Novial #language-Occitan (post 1500) #language-Oriya (macrolanguage) #language-Ossetian #language-Panjabi #language-Pennsylvania German #language-Polish #language-Piemontese #language-Western Panjabi #language-Pushto #language-Portuguese #language-Quechua #language-Romansh #language-Romanian #language-Russian #language-Kinyarwanda #language-Sanskrit #language-Yakut #language-Sicilian #language-Scots #language-Sindhi #language-Samogitian #language-Serbo-Croatian #language-Sinhala #language-Slovak #language-Slovenian #language-Somali #language-Albanian #language-Serbian #language-Sundanese #language-Swedish #language-Swahili (macrolanguage) #language-Silesian #language-Tamil #language-Telugu #language-Tajik #language-Thai #language-Turkmen #language-Tagalog #language-Turkish #language-Tatar #language-Uighur #language-Ukrainian #language-Urdu #language-Uzbek #language-Venetian #language-Veps #language-Vietnamese #language-Vlaams #language-Volapük #language-Võro #language-Walloon #language-Waray (Philippines) #language-Wu Chinese #language-Mingrelian #language-Yiddish #language-Yoruba #language-Yue Chinese #language-Zeeuws #language-Chinese #license-unknown #arxiv-1902.00193 #region-us 
 ### Dataset Summary


WikiANN (sometimes called PAN-X) is a multilingual named entity recognition dataset consisting of Wikipedia articles annotated with LOC (location), PER (person), and ORG (organisation) tags in the IOB2 format. This version corresponds to the balanced train, dev, and test splits of Rahimi et al. (2019), which supports 176 of the 282 languages from the original WikiANN corpus. ### Supported Tasks and Leaderboards


* 'named-entity-recognition': The dataset can be used to train a model for named entity recognition in many languages, or evaluate the zero-shot cross-lingual capabilities of multilingual models. ### Languages


The dataset contains 176 languages, one in each of the configuration subsets. The corresponding BCP 47 language tags
are:



Dataset Structure
----------------- ### Data Instances


This is an example in the "train" split of the "af" (Afrikaans language) configuration subset: ### Data Fields


* 'tokens': a 'list' of 'string' features.
* 'langs': a 'list' of 'string' features that correspond to the language of each token.
* 'ner\_tags': a 'list' of classification labels, with possible values including 'O' (0), 'B-PER' (1), 'I-PER' (2), 'B-ORG' (3), 'I-ORG' (4), 'B-LOC' (5), 'I-LOC' (6).
* 'spans': a 'list' of 'string' features, that is the list of named entities in the input text formatted as '': '' ### Data Splits


For each configuration subset, the data is split into "train", "validation" and "test" sets, each containing the
following number of examples:



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information


The original 282 datasets are associated with this article


while the 176 languages supported in this version are associated with the following article ### Contributions


Thanks to @lewtun and @rabeehk for adding this dataset.
passage:  passage: TAGS
#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-machine-generated #language_creators-crowdsourced #multilinguality-multilingual #size_categories-n<1K #source_datasets-original #language-Achinese #language-Afrikaans #language-Tosk Albanian #language-Amharic #language-Aragonese #language-Old English (ca. 450-1100) #language-Arabic #language-Official Aramaic (700-300 BCE) #language-Egyptian Arabic #language-Assamese #language-Asturian #language-Aymara #language-Azerbaijani #language-Bashkir #language-Bavarian #language-Belarusian #language-Bulgarian #language-bh #language-Bengali #language-Tibetan #language-Breton #language-Bosnian #language-Catalan #language-Chavacano #language-Min Dong Chinese #language-Chechen #language-Cebuano #language-Central Kurdish #language-Corsican #language-Crimean Tatar #language-Czech #language-Kashubian #language-Chuvash #language-Welsh #language-Danish #language-German #language-Dimli (individual language) #language-Dhivehi #language-Modern Greek (1453-) #language-Emiliano-Romagnolo #language-English #language-Esperanto #language-Spanish #language-Estonian #language-Basque #language-Extremaduran #language-Persian #language-Finnish #language-Faroese #language-French #language-Northern Frisian #language-Friulian #language-Western Frisian #language-Irish #language-Gan Chinese #language-Scottish Gaelic #language-Galician #language-Guarani #language-Gujarati #language-Hakka Chinese #language-Hebrew #language-Hindi #language-Croatian #language-Upper Sorbian #language-Hungarian #language-Armenian #language-Interlingua (International Auxiliary Language Association) #language-Indonesian #language-Igbo #language-Iloko #language-Ido #language-Icelandic #language-Italian #language-Japanese #language-Lojban #language-Javanese #language-Georgian #language-Kazakh #language-Khmer #language-Kannada #language-Korean #language-Kölsch #language-Kurdish #language-Kirghiz #language-Latin #language-Luxembourgish #language-Limburgan #language-Ligurian #language-Lombard #language-Lingala #language-Lithuanian #language-Latvian #language-Literary Chinese #language-Malagasy #language-Eastern Mari #language-Maori #language-Minangkabau #language-Macedonian #language-Malayalam #language-Mongolian #language-Marathi #language-Malay (macrolanguage) #language-Maltese #language-Mirandese #language-Burmese #language-Mazanderani #language-Min Nan Chinese #language-Neapolitan #language-Low German #language-Nepali (macrolanguage) #language-Dutch #language-Norwegian Nynorsk #language-Norwegian #language-Novial #language-Occitan (post 1500) #language-Oriya (macrolanguage) #language-Ossetian #language-Panjabi #language-Pennsylvania German #language-Polish #language-Piemontese #language-Western Panjabi #language-Pushto #language-Portuguese #language-Quechua #language-Romansh #language-Romanian #language-Russian #language-Kinyarwanda #language-Sanskrit #language-Yakut #language-Sicilian #language-Scots #language-Sindhi #language-Samogitian #language-Serbo-Croatian #language-Sinhala #language-Slovak #language-Slovenian #language-Somali #language-Albanian #language-Serbian #language-Sundanese #language-Swedish #language-Swahili (macrolanguage) #language-Silesian #language-Tamil #language-Telugu #language-Tajik #language-Thai #language-Turkmen #language-Tagalog #language-Turkish #language-Tatar #language-Uighur #language-Ukrainian #language-Urdu #language-Uzbek #language-Venetian #language-Veps #language-Vietnamese #language-Vlaams #language-Volapük #language-Võro #language-Walloon #language-Waray (Philippines) #language-Wu Chinese #language-Mingrelian #language-Yiddish #language-Yoruba #language-Yue Chinese #language-Zeeuws #language-Chinese #license-unknown #arxiv-1902.00193 #region-us 
### Dataset Summary


WikiANN (sometimes called PAN-X) is a multilingual named entity recognition dataset consisting of Wikipedia articles annotated with LOC (location), PER (person), and ORG (organisation) tags in the IOB2 format. This version corresponds to the balanced train, dev, and test splits of Rahimi et al. (2019), which supports 176 of the 282 languages from the original WikiANN corpus.### Supported Tasks and Leaderboards


* 'named-entity-recognition': The dataset can be used to train a model for named entity recognition in many languages, or evaluate the zero-shot cross-lingual capabilities of multilingual models.### Languages


The dataset contains 176 languages, one in each of the configuration subsets. The corresponding BCP 47 language tags
are:



Dataset Structure
-----------------### Data Instances


This is an example in the "train" split of the "af" (Afrikaans language) configuration subset:### Data Fields


* 'tokens': a 'list' of 'string' features.
* 'langs': a 'list' of 'string' features that correspond to the language of each token.
* 'ner\_tags': a 'list' of classification labels, with possible values including 'O' (0), 'B-PER' (1), 'I-PER' (2), 'B-ORG' (3), 'I-ORG' (4), 'B-LOC' (5), 'I-LOC' (6).
* 'spans': a 'list' of 'string' features, that is the list of named entities in the input text formatted as '': ''### Data Splits


For each configuration subset, the data is split into "train", "validation" and "test" sets, each containing the
following number of examples:



Dataset Creation
----------------### Curation Rationale### Source Data#### Initial Data Collection and Normalization#### Who are the source language producers?### Annotations#### Annotation process#### Who are the annotators?### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------