Datasets:
metadata
dataset_info:
- config_name: None-None
features:
- name: identifier
dtype: string
- name: collection
dtype: string
- name: open_type
dtype: string
- name: license
dtype: string
- name: date
dtype: float64
- name: title
dtype: string
- name: creator
dtype: string
- name: language
dtype: string
- name: language_type
dtype: string
- name: word_count
dtype: int64
- name: token_count
dtype: int64
- name: text
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 17203.146235850876
num_examples: 2
download_size: 14479
dataset_size: 17203.146235850876
- config_name: Open Culture-BNL Newspapers (1841-1879)
features:
- name: identifier
dtype: string
- name: collection
dtype: string
- name: open_type
dtype: string
- name: license
dtype: string
- name: date
dtype: float64
- name: title
dtype: string
- name: creator
dtype: string
- name: language
dtype: string
- name: language_type
dtype: string
- name: word_count
dtype: int64
- name: token_count
dtype: int64
- name: text
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 361266.0709528684
num_examples: 42
download_size: 34939
dataset_size: 361266.0709528684
- config_name: Open Culture-Danish-PD
features:
- name: identifier
dtype: string
- name: collection
dtype: string
- name: open_type
dtype: string
- name: license
dtype: string
- name: date
dtype: float64
- name: title
dtype: string
- name: creator
dtype: string
- name: language
dtype: string
- name: language_type
dtype: string
- name: word_count
dtype: int64
- name: token_count
dtype: int64
- name: text
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 309656.63224531576
num_examples: 36
download_size: 1094483
dataset_size: 309656.63224531576
- config_name: Open Culture-Dutch-PD
features:
- name: identifier
dtype: string
- name: collection
dtype: string
- name: open_type
dtype: string
- name: license
dtype: string
- name: date
dtype: float64
- name: title
dtype: string
- name: creator
dtype: string
- name: language
dtype: string
- name: language_type
dtype: string
- name: word_count
dtype: int64
- name: token_count
dtype: int64
- name: text
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
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num_examples: 198090
download_size: 5093949247
dataset_size: 1703885618.9298499
- config_name: Open Culture-English-PD
features:
- name: identifier
dtype: string
- name: collection
dtype: string
- name: open_type
dtype: string
- name: license
dtype: string
- name: date
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- name: title
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dtype: string
- name: word_count
dtype: int64
- name: token_count
dtype: int64
- name: text
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- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 22553324.7152005
num_examples: 2622
download_size: 69909009
dataset_size: 22553324.7152005
- config_name: Open Culture-Europeana
features:
- name: identifier
dtype: string
- name: collection
dtype: string
- name: open_type
dtype: string
- name: license
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- name: date
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- name: title
dtype: string
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- name: language
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dtype: string
- name: word_count
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- name: token_count
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splits:
- name: train
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num_examples: 126
download_size: 3462663
dataset_size: 1083798.2128586052
- config_name: Open Culture-French-PD-Books
features:
- name: identifier
dtype: string
- name: collection
dtype: string
- name: open_type
dtype: string
- name: license
dtype: string
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- name: title
dtype: string
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dtype: int64
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- name: text
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- name: __index_level_0__
dtype: int64
splits:
- name: train
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num_examples: 195
download_size: 5419836
dataset_size: 1677306.7579954604
- config_name: Open Culture-French-PD-Newspapers
features:
- name: identifier
dtype: string
- name: collection
dtype: string
- name: open_type
dtype: string
- name: license
dtype: string
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dtype: string
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- name: __index_level_0__
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splits:
- name: train
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num_examples: 117
download_size: 2415475
dataset_size: 1006384.0547972762
- config_name: Open Culture-French-PD-diverse
features:
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dtype: string
- name: collection
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- name: open_type
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splits:
- name: train
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- config_name: Open Culture-German-PD
features:
- name: identifier
dtype: string
- name: collection
dtype: string
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splits:
- name: train
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num_examples: 1744
download_size: 49741959
dataset_size: 15001143.517661963
- config_name: Open Culture-German-PD-Newspapers
features:
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dtype: string
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dtype: string
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dtype: string
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dtype: string
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splits:
- name: train
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num_examples: 27
download_size: 699054
dataset_size: 232242.4741839868
- config_name: Open Culture-Greek-PD
features:
- name: identifier
dtype: string
- name: collection
dtype: string
- name: open_type
dtype: string
- name: license
dtype: string
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splits:
- name: train
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num_examples: 1
download_size: 45314
dataset_size: 8601.573117925438
- config_name: Open Culture-Gutenberg
features:
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dtype: string
- name: collection
dtype: string
- name: open_type
dtype: string
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splits:
- name: train
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num_examples: 4844
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dataset_size: 41666020.18323082
- config_name: Open Culture-Italian-PD
features:
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dtype: string
- name: collection
dtype: string
- name: open_type
dtype: string
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splits:
- name: train
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num_examples: 253
download_size: 7358849
dataset_size: 2176197.9988351357
- config_name: Open Culture-Latin-PD
features:
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dtype: string
- name: collection
dtype: string
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dtype: string
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dtype: string
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splits:
- name: train
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num_examples: 637
download_size: 18272894
dataset_size: 5479202.076118504
- config_name: Open Culture-LoC-PD-Books
features:
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dtype: string
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splits:
- name: train
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num_examples: 480
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dataset_size: 4128755.09660421
- config_name: Open Culture-Multilingual-PD
features:
- name: identifier
dtype: string
- name: collection
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- name: open_type
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splits:
- name: train
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num_examples: 3164
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dataset_size: 27215377.345116083
- config_name: Open Culture-NewZealand-PD-Newspapers
features:
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splits:
- name: train
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num_examples: 70
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- config_name: Open Culture-Polish-PD
features:
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splits:
- name: train
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- config_name: Open Culture-Portuguese-PD
features:
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splits:
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- config_name: Open Culture-Spanish-PD-Books
features:
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splits:
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- config_name: Open Culture-Spanish-PD-Newspapers
features:
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splits:
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- config_name: Open Culture-US-PD-Books
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splits:
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dataset_size: 31946242.559975076
- config_name: Open Culture-US-PD-Newspapers
features:
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splits:
- name: train
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dataset_size: 12713125.068293797
- config_name: Open Culture-Wikisource
features:
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splits:
- name: train
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- config_name: Open Government-Caselaw Access Project
features:
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splits:
- name: train
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- config_name: Open Government-Court Listener
features:
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splits:
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- config_name: Open Government-Eurlex
features:
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splits:
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- config_name: Open Government-Eurovoc
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splits:
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- config_name: Open Government-French Open Data
features:
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splits:
- name: train
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- config_name: Open Government-GATT_library
features:
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splits:
- name: train
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- config_name: Open Government-Marianne-Europe
features:
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splits:
- name: train
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- config_name: Open Government-OECD
features:
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splits:
- name: train
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configs:
- config_name: None-None
data_files:
- split: train
path: None-None/train-*
- config_name: Open Culture-BNL Newspapers (1841-1879)
data_files:
- split: train
path: Open Culture-BNL Newspapers (1841-1879)/train-*
- config_name: Open Culture-Danish-PD
data_files:
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path: Open Culture-Danish-PD/train-*
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data_files:
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path: Open Culture-Dutch-PD/train-*
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path: Open Culture-English-PD/train-*
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path: Open Culture-Europeana/train-*
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data_files:
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path: Open Culture-French-PD-Books/train-*
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data_files:
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path: Open Culture-French-PD-Newspapers/train-*
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data_files:
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path: Open Culture-French-PD-diverse/train-*
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path: Open Culture-German-PD/train-*
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data_files:
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path: Open Culture-German-PD-Newspapers/train-*
- config_name: Open Culture-Greek-PD
data_files:
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path: Open Culture-Greek-PD/train-*
- config_name: Open Culture-Gutenberg
data_files:
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path: Open Culture-Gutenberg/train-*
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data_files:
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path: Open Culture-Italian-PD/train-*
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path: Open Culture-Latin-PD/train-*
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data_files:
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path: Open Culture-LoC-PD-Books/train-*
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path: Open Culture-Multilingual-PD/train-*
- config_name: Open Culture-NewZealand-PD-Newspapers
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path: Open Culture-NewZealand-PD-Newspapers/train-*
- config_name: Open Culture-Polish-PD
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path: Open Culture-Polish-PD/train-*
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path: Open Culture-Spanish-PD-Books/train-*
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path: Open Culture-Spanish-PD-Newspapers/train-*
- config_name: Open Culture-US-PD-Books
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path: Open Culture-US-PD-Books/train-*
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- split: train
path: Open Culture-US-PD-Newspapers/train-*
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path: Open Culture-Wikisource/train-*
- config_name: Open Government-Caselaw Access Project
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path: Open Government-Court Listener/train-*
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path: Open Government-French Open Data/train-*
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path: Open Government-GATT_library/train-*
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path: Open Government-Marianne-Europe/train-*
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path: Open Government-OECD/train-*
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path: Open Government-TEDEUTenders/train-*
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path: Open Government-UN-Digital-Library/train-*
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path: Open Government-USPTO/train-*
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path: Open Government-WTO/train-*
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path: Open Science-French-Science-Pile/train-*
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data_files:
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path: Open Science-German-Science-Pile/train-*
- config_name: Open Science-Open-Science-Pile
data_files:
- split: train
path: Open Science-Open-Science-Pile/train-*
- config_name: Open Science-OpenAlex
data_files:
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path: Open Science-OpenAlex/train-*
- config_name: Open Science-Spanish-Science-Pile
data_files:
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path: Open Science-Spanish-Science-Pile/train-*
- config_name: Open Web-StackExchange
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path: Open Web-StackExchange/train-*
- config_name: Open Web-Wikipedia
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path: Open Web-Wikipedia/train-*
- config_name: Open Web-Youtube-Commons
data_files:
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path: Open Web-Youtube-Commons/train-*
- config_name: all
default: true
data_files:
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path: all/train-*
task_categories:
- text-generation
language:
- nl
pretty_name: Common Corpus v2 NL
size_categories:
- 1M<n<10M
Common Corpus v2 NL
This is a version of Common Corpus v2 filtered to keep only the rows where language is "Dutch".
Common Corpus is a very large open and permissible licensed text dataset created by Pleias. Please be sure to acknowledge the creators of the original dataset when using this filtered version.
Filtering
Common Corpus is a collection of disparate datasets.
Note that filtering the entire collection for rows where the language is "Dutch" is not the same as filtering for entire datasets that are supposed to be Dutch-language.
Since language classification is an automated process,
there may be false positives and false negatives.
Examples are:
- false positives: code from
StackExchange, French fromFrench-PD-diverseare included in Common Corpus NL when they shouldn't be. - false negatives: rows from
Dutch-PDthat were misclassified, for example as English, are not included in Common Corpus NL when they should be.
If you want to use entire datasets, you either have to look up what the source was for including it into Common Corpus, or filter Common Corpus yourself.
Usage
from datasets import load_dataset
# load the full dataset
dataset = load_dataset('Rijgersberg/common_corpus_nl', 'all', split='train')
# load only a specific subset
wikipedia = load_dataset('Rijgersberg/common_corpus_nl', 'Open Web-Wikipedia', split='train')
Contents
The dataset has the following content.
Tokens are measured by the robbert-2023-dutch-base Dutch tokenizer on the text column only.
word_count is taken directly from the word_count column of the dataset.
| collection | open_type | row_count | word_count | token_count |
|---|---|---|---|---|
| Dutch-PD | Open Culture | 198,090 | 1,341,547,229 | 2,453,085,804 |
| French-PD-diverse | Open Culture | 5,357 | 38,359,009 | 75,965,219 |
| Gutenberg | Open Culture | 4,844 | 44,405,784 | 74,446,253 |
| US-PD-Books | Open Culture | 3,714 | 23,298,108 | 53,772,090 |
| Multilingual-PD | Open Culture | 3,164 | 22,935,496 | 45,033,262 |
| English-PD | Open Culture | 2,622 | 18,344,861 | 38,407,512 |
| German-PD | Open Culture | 1,744 | 12,434,468 | 26,319,336 |
| US-PD-Newspapers | Open Culture | 1,478 | 5,297,259 | 11,335,348 |
| Latin-PD | Open Culture | 637 | 4,406,870 | 9,623,548 |
| LoC-PD-Books | Open Culture | 480 | 3,384,886 | 6,359,398 |
| Italian-PD | Open Culture | 253 | 1,767,994 | 4,185,808 |
| French-PD-Books | Open Culture | 195 | 1,462,312 | 3,326,121 |
| Europeana | Open Culture | 126 | 751,961 | 2,018,302 |
| Spanish-PD-Books | Open Culture | 114 | 819,389 | 1,831,298 |
| French-PD-Newspapers | Open Culture | 117 | 589,899 | 1,352,344 |
| Danish-PD | Open Culture | 36 | 260,479 | 578,291 |
| Spanish-PD-Newspapers | Open Culture | 34 | 221,839 | 533,701 |
| German-PD-Newspapers | Open Culture | 27 | 155,979 | 398,229 |
| NewZealand-PD-Newspapers | Open Culture | 70 | 135,552 | 348,682 |
| Polish-PD | Open Culture | 6 | 37,573 | 135,721 |
| Portuguese-PD | Open Culture | 5 | 35,666 | 84,105 |
| Greek-PD | Open Culture | 1 | 11,084 | 23,343 |
| BNL Newspapers (1841-1879) | Open Culture | 42 | 6,409 | 17,658 |
| Wikisource | Open Culture | 1 | 36 | 58 |
| Eurlex | Open Government | 269,340 | 948,031,137 | 2,104,235,522 |
| Eurovoc | Open Government | 46,006 | 480,170,115 | 971,763,805 |
| French Open Data | Open Government | 228,097 | 211,210,103 | 546,913,250 |
| Marianne-Europe | Open Government | 10,101 | 44,308,181 | 113,369,293 |
| TEDEUTenders | Open Government | 5,105 | 3,423,351 | 8,123,266 |
| USPTO | Open Government | 40 | 410,010 | 1,505,353 |
| UN-Digital-Library | Open Government | 19 | 95,691 | 436,028 |
| WTO | Open Government | 11 | 55,733 | 125,785 |
| Court Listener | Open Government | 243 | 22,176 | 82,334 |
| OECD | Open Government | 5 | 30,895 | 56,160 |
| Caselaw Access Project | Open Government | 450 | 13,344 | 33,405 |
| GATT_library | Open Government | 1 | 282 | 1,112 |
| OpenAlex | Open Science | 11,867 | 76,200,223 | 142,457,454 |
| French-Science-Pile | Open Science | 1,485 | 6,197,572 | 18,685,715 |
| Open-Science-Pile | Open Science | 1,199 | 4,711,962 | 8,011,769 |
| German-Science-Pile | Open Science | 985 | 4,234,708 | 7,488,555 |
| Spanish-Science-Pile | Open Science | 163 | 1,071,826 | 2,263,934 |
| Wikipedia | Open Web | 2,135,977 | 367,689,443 | 634,440,794 |
| StackExchange | Open Web | 270,147 | 117,494,333 | 464,336,069 |
| Youtube-Commons | Open Web | 1,982 | 5,886,772 | 8,329,426 |
| None | None | 2 | 729 | 1,685 |
| total | 3,206,382 | 3,791,928,728 | 7,841,842,145 |
Code
In principle it is very easy to create Common Corpus NL by filtering Common Corpus using Hugging Face datasets' dataset.filter() functionality.
However, Common Corpus is larger than my available disk space.
A possible solution is to process Common Corpus streaming and relying on the fact that the Dutch subset will be much, much smaller than the full dataset. The code for that solution is below. However, I was having trouble streaming the entire dataset without any connection errors along the way.
from datasets import load_dataset, Dataset
common_corpus = load_dataset('PleIAs/common_corpus', split='train', streaming=True)
def nl():
for row in common_corpus:
if row['language'] == 'Dutch':
yield row
common_corpus_nl = Dataset.from_generator(nl)
common_corpus_nl.push_to_hub('Rijgersberg/common_corpus_nl')
Therefore I took the approach for every one of ten subfolders of Common Corpus:
- downloading the subfolder in a fault-tolerant way
- doing the filtering to Dutch rows only
- uploading that by itself to the Hugging Face hub
- deleting all the downloaded files and datasets cache files (around 1.5 TB for every subfolder)
Then finally I concatenated the ten Dutch datasets into a single one, which is the one you are looking at.
import shutil
from datasets import concatenate_datasets, load_dataset
from huggingface_hub import snapshot_download
from huggingface_hub.errors import LocalEntryNotFoundError
from requests import ReadTimeout
local_dir = '/path/to/downloadfolder/commoncorpus'
for i in range(1, 10+1):
success = False
while not success:
try:
# download one common corpus folder at a time to a local directory
snapshot_download( # will skip files that have already been downloaded
repo_id='PleIAs/common_corpus',
repo_type='dataset',
allow_patterns=f'common_corpus_{i}/*',
local_dir=local_dir
)
success = True
except (LocalEntryNotFoundError, ReadTimeout) as e:
print(e)
subdataset = load_dataset(local_dir, split='train')
subdataset = subdataset.filter(lambda lang: lang == 'Dutch', input_columns=['language'])
subdataset.push_to_hub(f'Rijgersberg/common_corpus_nl_{i}')
# remove local copies of the data to free up disk space
shutil.rmtree(local_dir)
shutil.rmtree('/path/to/cache/huggingface/datasets/commoncorpus')
# concatenate all (much smaller) Dutch datasets into a single dataset
common_corpus_nl = concatenate_datasets([load_dataset(f'Rijgersberg/common_corpus_nl_{i}', split='train')
for i in range(1, 10+1)])
common_corpus_nl.push_to_hub('Rijgersberg/common_corpus_nl')