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Dataset Card for Polyglot-NER
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
Languages
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
: astring
feature.lang
: astring
feature.words
: alist
ofstring
features.ner
: alist
ofstring
features.
bg
id
: astring
feature.lang
: astring
feature.words
: alist
ofstring
features.ner
: alist
ofstring
features.
ca
id
: astring
feature.lang
: astring
feature.words
: alist
ofstring
features.ner
: alist
ofstring
features.
combined
id
: astring
feature.lang
: astring
feature.words
: alist
ofstring
features.ner
: alist
ofstring
features.
cs
id
: astring
feature.lang
: astring
feature.words
: alist
ofstring
features.ner
: alist
ofstring
features.
Data Splits
name | train |
---|---|
ar | 339109 |
bg | 559694 |
ca | 372665 |
combined | 21070925 |
cs | 564462 |
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
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.
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