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metadata
annotations_creators:
  - no-annotation
language_creators:
  - crowdsourced
language:
  - ace
  - ban
  - bjn
  - bug
  - gor
  - km
  - id
  - jv
  - lo
  - mad
  - mnw
  - min
  - ms
  - my
  - nia
  - shn
  - su
  - tet
  - th
  - vi
license:
  - cc-by-sa-3.0
  - gfdl
multilinguality:
  - multilingual
source_datasets:
  - Wikipedia-HF
task_categories:
  - text-generation
  - fill-mask
task_ids:
  - language-modeling
  - masked-language-modeling
pretty_name: Wikipedia Archive for SEA Languages
tags:
  - Wikipedia
  - Southeast Asia (SEA)
  - Dialect
  - Banyumasan Dialect of Javanese (Ngapak)
  - SEA-related Languages
  - SEA Local Languages
dataset_info:
  - config_name: seawiki_all
    features:
      - name: url
        dtype: string
      - name: title
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: ace
        num_bytes: 4952102
        num_examples: 13003
      - name: ban
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        num_examples: 20987
      - name: bjn
        num_bytes: 6792259
        num_examples: 10519
      - name: bug
        num_bytes: 3298561
        num_examples: 15880
      - name: gor
        num_bytes: 6239133
        num_examples: 15359
      - name: id
        num_bytes: 1118834498
        num_examples: 665622
      - name: jv
        num_bytes: 72101470
        num_examples: 73380
      - name: km
        num_bytes: 103146669
        num_examples: 11994
      - name: lo
        num_bytes: 15240262
        num_examples: 5014
      - name: mad
        num_bytes: 1612542
        num_examples: 1192
      - name: map_bms
        num_bytes: 5221506
        num_examples: 13580
      - name: min
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        num_examples: 227143
      - name: mnw
        num_bytes: 47321734
        num_examples: 3296
      - name: ms
        num_bytes: 419662356
        num_examples: 368628
      - name: my
        num_bytes: 313370839
        num_examples: 109310
      - name: nia
        num_bytes: 2153274
        num_examples: 1714
      - name: shn
        num_bytes: 33754296
        num_examples: 13945
      - name: su
        num_bytes: 47516268
        num_examples: 61555
      - name: tet
        num_bytes: 1454499
        num_examples: 1468
      - name: th
        num_bytes: 1012930269
        num_examples: 159719
      - name: vi
        num_bytes: 1603057632
        num_examples: 1288680
    download_size: 4959860254
    dataset_size: 4953683098
  - config_name: seawiki_dedup_all
    features:
      - name: url
        dtype: string
      - name: title
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: ace
        num_bytes: 4944916
        num_examples: 12979
      - name: ban
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        num_examples: 20611
      - name: bjn
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        num_examples: 10503
      - name: bug
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        num_examples: 9969
      - name: gor
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        num_examples: 15290
      - name: id
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        num_examples: 662443
      - name: jv
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        num_examples: 73080
      - name: km
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        num_examples: 11466
      - name: lo
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        num_examples: 4897
      - name: mad
        num_bytes: 1612542
        num_examples: 1192
      - name: map_bms
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        num_examples: 11839
      - name: min
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        num_examples: 225972
      - name: mnw
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        num_examples: 3271
      - name: ms
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        num_examples: 348045
      - name: my
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        num_examples: 108819
      - name: nia
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        num_examples: 1714
      - name: shn
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        num_examples: 13662
      - name: su
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        num_examples: 61529
      - name: tet
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        num_examples: 1464
      - name: th
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        num_examples: 159666
      - name: vi
        num_bytes: 1602828123
        num_examples: 1287910
    download_size: 4950689052
    dataset_size: 4944502878
  - config_name: seawiki_with_countries_all
    features:
      - name: url
        dtype: string
      - name: title
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: idn_ace
        num_bytes: 4952102
        num_examples: 13003
      - name: idn_ban
        num_bytes: 18198909
        num_examples: 20987
      - name: idn_bjn
        num_bytes: 6792259
        num_examples: 10519
      - name: idn_bug
        num_bytes: 3298561
        num_examples: 15880
      - name: idn_gor
        num_bytes: 6239133
        num_examples: 15359
      - name: idn_id
        num_bytes: 1118834498
        num_examples: 665622
      - name: idn_jv
        num_bytes: 72101470
        num_examples: 73380
      - name: idn_mad
        num_bytes: 1612542
        num_examples: 1192
      - name: idn_map_bms
        num_bytes: 5221506
        num_examples: 13580
      - name: idn_min
        num_bytes: 116824020
        num_examples: 227143
      - name: idn_ms
        num_bytes: 419662356
        num_examples: 368628
      - name: idn_nia
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        num_examples: 1714
      - name: idn_su
        num_bytes: 47516268
        num_examples: 61555
      - name: idn_tet
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        num_examples: 1468
      - name: sgp_ms
        num_bytes: 419662356
        num_examples: 368628
      - name: mys_ms
        num_bytes: 419662356
        num_examples: 368628
      - name: brn_ms
        num_bytes: 419662356
        num_examples: 368628
      - name: tha_th
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        num_examples: 159719
      - name: mmr_my
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        num_examples: 109310
      - name: mmr_shn
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        num_examples: 13945
      - name: mmr_mnw
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        num_examples: 3296
      - name: lao_lo
        num_bytes: 15240262
        num_examples: 5014
      - name: vnm_vi
        num_bytes: 1603057632
        num_examples: 1288680
      - name: khm_km
        num_bytes: 103146669
        num_examples: 11994
      - name: tls_tet
        num_bytes: 1454499
        num_examples: 1468
    download_size: 4959860254
    dataset_size: 6214124665
  - config_name: seawiki_with_countries_dedup_all
    features:
      - name: url
        dtype: string
      - name: title
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: idn_ace
        num_bytes: 4944916
        num_examples: 12979
      - name: idn_ban
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        num_examples: 20611
      - name: idn_bjn
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        num_examples: 10503
      - name: idn_bug
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        num_examples: 9969
      - name: idn_gor
        num_bytes: 6217480
        num_examples: 15290
      - name: idn_id
        num_bytes: 1117891512
        num_examples: 662443
      - name: idn_jv
        num_bytes: 71997517
        num_examples: 73080
      - name: idn_mad
        num_bytes: 1612542
        num_examples: 1192
      - name: idn_map_bms
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        num_examples: 11839
      - name: idn_min
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        num_examples: 225972
      - name: idn_ms
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        num_examples: 348045
      - name: idn_nia
        num_bytes: 2153274
        num_examples: 1714
      - name: idn_su
        num_bytes: 47512744
        num_examples: 61529
      - name: idn_tet
        num_bytes: 1452151
        num_examples: 1464
      - name: sgp_ms
        num_bytes: 414783365
        num_examples: 348045
      - name: mys_ms
        num_bytes: 414783365
        num_examples: 348045
      - name: brn_ms
        num_bytes: 414783365
        num_examples: 348045
      - name: tha_th
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        num_examples: 159666
      - name: mmr_my
        num_bytes: 312990457
        num_examples: 108819
      - name: mmr_shn
        num_bytes: 33616591
        num_examples: 13662
      - name: mmr_mnw
        num_bytes: 47243333
        num_examples: 3271
      - name: lao_lo
        num_bytes: 14908444
        num_examples: 4897
      - name: vnm_vi
        num_bytes: 1602828123
        num_examples: 1287910
      - name: khm_km
        num_bytes: 102698901
        num_examples: 11466
      - name: tls_tet
        num_bytes: 1452151
        num_examples: 1464
    download_size: 4950689052
    dataset_size: 6190305124

SEA Wikipedia Data Repository


license: cc-by-sa-3.0

Welcome to SEA Wikipedia Data Repository. The datasets are extracted from Wikipedia HF and processed using the scripts available in this repository for reproducibility purpose.

FAQS

What are the available languages provided in dataset and from which country?

You may check the following tables to understand the current coverage of this dataset (languages, countries, data size & volume).

1. Table of Countries and its Country Code

Country Code Country Name Wiki Info
brn Brunei Wiki Link
idn Indonesia Wiki Link
khm Cambodia Wiki Link
lao Laos Wiki Link
mmr Myanmar Wiki Link
mys Malaysia Wiki Link
sgp Singapore Wiki Link
tha Thailand Wiki Link
tls East Timor Wiki Link
vnm Vietnam Wiki Link

2. Table of Languages and Countries of its speakers

Lang Code Lang Name Country Codes Spoken Wiki Info Total Data Total Size (bytes)
ace Acehnese idn Wiki Link 12904 4867838
ban Balinese idn Wiki Link 19837 17366080
bjn Banjarese idn Wiki Link 10437 6655378
bug Buginese idn Wiki Link 9793 2072609
gor Gorontalo idn Wiki Link 14514 5989252
km Khmer khm Wiki Link 11994 103146669
id Indonesian idn Wiki Link 654287 1100932403
jv Javanese idn Wiki Link 72667 69774853
lo Lao lao Wiki Link 5014 15240262
mad Madurese idn Wiki Link 1192 1612542
map_bms Banyumasan
(Dialect of Javanese)
idn Wiki Link 11832 5060989
mnw Mon mmr Wiki Link 3296 47321734
min Minangkabau idn Wiki Link 225858 116376870
ms Malay mys, sgp, brn, idn Wiki Link 346186 410443550
my Burmese mmr Wiki Link 109310 313370839
nia Nias idn Wiki Link 1650 1938121
shn Shan mmr Wiki Link 13945 33754296
su Sundanese idn Wiki Link 61494 47410439
tet Tetum tls, idn Wiki Link 1465 1452716
th Thai tha Wiki Link 159719 1012930269
vi Vietnamese vnm Wiki Link 1288680 1603057632

Some other languages in SEA that are already exists its Wiki Index at Wikimedia might be missing from this list. Any lang update PR is greatly appreciated!

How do I extract new Wikipedia Dataset of SEA languages?

You may check to the script extract_raw_wiki_data.py to understand its implementations, or you can adjust the bash provided in extract_raw_wiki_data_sea.sh to extract it on your own. Please note that this dataset is extensible to any languages of your choice.

How do I extract new Wikipedia Dataset of SEA languages?

You may visit this Wikipedia Dump Index to check any latest available data and this link Wikipedia Language Coverage to map into any languages that you're wanting to extract.

How does the data being preprocessed? What makes it different from loading it directly from Wikipedia HF?

The data available in here are processed with following flows:

  1. Raw data is being deduplicated on title and text (text-content from a given article), to remove articles containing boilerplate text (template text that are used usually for no-available informations or asking for contributions of content in that article), which usually deemed noisy for NLP data.
  2. Furthermore, the title and text data are being checked for string-matching duplication (duplication of text that are being pre-processed, i.e symbols removed, HTML tags striped, or ASCII-chars validated). You may check this dedup_raw_wiki_data.py script to understand its implementation.

Getting Started

To read the datasets directly

Use one of the following code chunks to load it from HuggingFace Hub: You can refer to the 2nd args of config name using the following script

dataset = load_dataset(
  "sabilmakbar/sea_wiki",
  "seawiki_dedup_all" # a config name, can be "seawiki_dedup_all" or "seawiki_with_countries_all", or "seawiki_with_countries_dedup_all" , defaults to "seawiki_dedup_all"
)

Or you can provide both lang and date_stamp (or just lang only by assuming the date_stamp will take the newest one)

dataset = load_dataset(
  "sabilmakbar/sea_wiki",
  lang = "id", # see README for complete lang choices
  date_stamp="20230901"
)

Or you can provide a country params with similar fashion to lang args(providing both country and lang will prioritize the lang kwarg)

dataset = load_dataset(
  "sabilmakbar/sea_wiki",
  lang = "id", # see the splits for complete lang choices
  date_stamp="20230901"
)

To replicate the whole dataset generation process

  1. Set-up a new Python/Conda Environment (recommended Python version: 3.9.6 to 3.9.18 or 3.10.0 to 3.10.13) and install the requirements on requirements.txt use this codebase via pip install -r requirements.txt.
  2. Activate the chosen Python/Conda environment which the requirements are being installed.
  3. Force install multiprocess==0.70.15 by using pip install multiprocess==0.70.15 to avoid this issue (there's no other workaround for now, esp for Python 3.10.x)
  4. Run this sh script for extractions from Wikimedia Dump:<\b> sh extract_raw_wiki_data_sea.sh.
  5. Run this sh script of deduplication:<\b> sh dedup_raw_wiki_data_sea.sh.

Citation Info:

@ONLINE{wikidump,
    author = "Wikimedia Foundation",
    title  = "Wikimedia Downloads",
    url    = "https://dumps.wikimedia.org"}
@ONLINE{wikipedia-hf,
    title  = "Huggingface Wikipedia Dataset",
    url    = "https://huggingface.co/datasets/wikipedia"}