Datasets:

Multilinguality:
multilingual
Size Categories:
unknown
Language Creators:
found
Annotations Creators:
machine-generated
Source Datasets:
original
ArXiv:
Tags:
License:
polyglot_ner / README.md
albertvillanova's picture
Convert dataset sizes from base 2 to base 10 in the dataset card (#2)
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metadata
annotations_creators:
  - machine-generated
language_creators:
  - found
language:
  - ar
  - bg
  - ca
  - cs
  - da
  - de
  - el
  - en
  - es
  - et
  - fa
  - fi
  - fr
  - he
  - hi
  - hr
  - hu
  - id
  - it
  - ja
  - ko
  - lt
  - lv
  - ms
  - nl
  - 'no'
  - pl
  - pt
  - ro
  - ru
  - sk
  - sl
  - sr
  - sv
  - th
  - tl
  - tr
  - uk
  - vi
  - zh
license:
  - unknown
multilinguality:
  - multilingual
pretty_name: Polyglot-NER
size_categories:
  - unknown
source_datasets:
  - original
task_categories:
  - token-classification
task_ids:
  - named-entity-recognition
paperswithcode_id: polyglot-ner
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        dtype: string
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        dtype: string
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      - name: ner
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Dataset Card for Polyglot-NER

Table of Contents

Dataset Description

Dataset Summary

Polyglot-NER A training dataset automatically generated from Wikipedia and Freebase the task of named entity recognition. The dataset contains the basic Wikipedia based training data for 40 languages we have (with coreference resolution) for the task of named entity recognition. The details of the procedure of generating them is outlined in Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data corresponding to a different language. For example, "es" includes only spanish examples.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

ar

  • Size of downloaded dataset files: 1.11 GB
  • Size of the generated dataset: 183.55 MB
  • Total amount of disk used: 1.29 GB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "id": "2",
    "lang": "ar",
    "ner": ["O", "O", "O", "O", "O", "O", "O", "O", "LOC", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "PER", "PER", "PER", "PER", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O"],
    "words": "[\"وفي\", \"مرحلة\", \"موالية\", \"أنشأت\", \"قبيلة\", \"مكناسة\", \"الزناتية\", \"مكناسة\", \"تازة\", \",\", \"وأقام\", \"بها\", \"المرابطون\", \"قلعة\", \"..."
}

bg

  • Size of downloaded dataset files: 1.11 GB
  • Size of the generated dataset: 190.51 MB
  • Total amount of disk used: 1.30 GB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "id": "1",
    "lang": "bg",
    "ner": ["O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O"],
    "words": "[\"Дефиниция\", \"Наименованията\", \"\\\"\", \"книжовен\", \"\\\"/\\\"\", \"литературен\", \"\\\"\", \"език\", \"на\", \"български\", \"за\", \"тази\", \"кодифи..."
}

ca

  • Size of downloaded dataset files: 1.11 GB
  • Size of the generated dataset: 143.75 MB
  • Total amount of disk used: 1.25 GB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "id": "2",
    "lang": "ca",
    "ner": "[\"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O\", \"O...",
    "words": "[\"Com\", \"a\", \"compositor\", \"deixà\", \"un\", \"immens\", \"llegat\", \"que\", \"inclou\", \"8\", \"simfonies\", \"(\", \"1822\", \"),\", \"diverses\", ..."
}

combined

  • Size of downloaded dataset files: 1.11 GB
  • Size of the generated dataset: 6.29 GB
  • Total amount of disk used: 7.39 GB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "id": "18",
    "lang": "es",
    "ner": ["O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O"],
    "words": "[\"Los\", \"cambios\", \"en\", \"la\", \"energía\", \"libre\", \"de\", \"Gibbs\", \"\\\\\", \"Delta\", \"G\", \"nos\", \"dan\", \"una\", \"cuantificación\", \"de..."
}

cs

  • Size of downloaded dataset files: 1.11 GB
  • Size of the generated dataset: 156.79 MB
  • Total amount of disk used: 1.26 GB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "id": "3",
    "lang": "cs",
    "ner": ["O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O"],
    "words": "[\"Historie\", \"Symfonická\", \"forma\", \"se\", \"rozvinula\", \"se\", \"především\", \"v\", \"období\", \"klasicismu\", \"a\", \"romantismu\", \",\", \"..."
}

Data Fields

The data fields are the same among all splits.

ar

  • id: a string feature.
  • lang: a string feature.
  • words: a list of string features.
  • ner: a list of string features.

bg

  • id: a string feature.
  • lang: a string feature.
  • words: a list of string features.
  • ner: a list of string features.

ca

  • id: a string feature.
  • lang: a string feature.
  • words: a list of string features.
  • ner: a list of string features.

combined

  • id: a string feature.
  • lang: a string feature.
  • words: a list of string features.
  • ner: a list of string features.

cs

  • id: a string feature.
  • lang: a string feature.
  • words: a list of string features.
  • ner: a list of string features.

Data Splits

name train
ar 339109
bg 559694
ca 372665
combined 21070925
cs 564462

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

@article{polyglotner,
         author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},
         title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},
         journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},
         month     = {April},
         year      = {2015},
         publisher = {SIAM},
}

Contributions

Thanks to @joeddav for adding this dataset.