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metadata
annotations_creators:
  - no-annotation
language_creators:
  - crowdsourced
language:
  - ace
  - ban
  - bcl
  - bjn
  - bug
  - cbk
  - ceb
  - gor
  - id
  - ilo
  - jv
  - km
  - lo
  - mad
  - min
  - mnw
  - ms
  - my
  - nia
  - pag
  - pam
  - shn
  - su
  - ta
  - th
  - tl
  - tet
  - vi
  - war
license:
  - cc-by-sa-4.0
multilinguality:
  - multilingual
source_datasets:
  - Wikipedia
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
        num_bytes: 18198909
        num_examples: 20987
      - name: bcl
        num_bytes: 20258642
        num_examples: 15743
      - name: bjn
        num_bytes: 6792259
        num_examples: 10519
      - name: bug
        num_bytes: 3298561
        num_examples: 15880
      - name: cbk_zam
        num_bytes: 2033238
        num_examples: 3285
      - name: ceb
        num_bytes: 4572804910
        num_examples: 6302896
      - name: gor
        num_bytes: 6239133
        num_examples: 15359
      - name: id
        num_bytes: 1118834498
        num_examples: 665622
      - name: ilo
        num_bytes: 16719139
        num_examples: 15371
      - 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
        num_bytes: 116824020
        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: pag
        num_bytes: 1370162
        num_examples: 2665
      - name: pam
        num_bytes: 8218370
        num_examples: 9006
      - name: shn
        num_bytes: 33754296
        num_examples: 13945
      - name: su
        num_bytes: 47516268
        num_examples: 61555
      - name: ta
        num_bytes: 809156746
        num_examples: 160651
      - name: tet
        num_bytes: 1454499
        num_examples: 1468
      - name: th
        num_bytes: 1012930269
        num_examples: 159719
      - name: tl
        num_bytes: 85356818
        num_examples: 45341
      - name: vi
        num_bytes: 1603057633
        num_examples: 1288680
      - name: war
        num_bytes: 454304567
        num_examples: 1266394
    download_size: 1829748651
    dataset_size: 10923905691
  - 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
        num_bytes: 18025267
        num_examples: 20611
      - name: bcl
        num_bytes: 19977232
        num_examples: 14079
      - name: bjn
        num_bytes: 6786207
        num_examples: 10503
      - name: bug
        num_bytes: 2182435
        num_examples: 9969
      - name: cbk_zam
        num_bytes: 1579651
        num_examples: 2242
      - name: ceb
        num_bytes: 4346511153
        num_examples: 5815254
      - name: gor
        num_bytes: 6217480
        num_examples: 15290
      - name: id
        num_bytes: 1117891512
        num_examples: 662443
      - name: ilo
        num_bytes: 16719001
        num_examples: 15369
      - name: jv
        num_bytes: 71997517
        num_examples: 73080
      - name: km
        num_bytes: 102698901
        num_examples: 11466
      - name: lo
        num_bytes: 14908444
        num_examples: 4897
      - name: mad
        num_bytes: 1612542
        num_examples: 1192
      - name: map_bms
        num_bytes: 5067489
        num_examples: 11839
      - name: min
        num_bytes: 116721269
        num_examples: 225972
      - name: mnw
        num_bytes: 47243333
        num_examples: 3271
      - name: ms
        num_bytes: 414783365
        num_examples: 348045
      - name: my
        num_bytes: 312990457
        num_examples: 108819
      - name: nia
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        num_examples: 1714
      - name: pag
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        num_examples: 1108
      - name: pam
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        num_examples: 8932
      - name: shn
        num_bytes: 33616591
        num_examples: 13662
      - name: su
        num_bytes: 47512744
        num_examples: 61529
      - name: ta
        num_bytes: 809061339
        num_examples: 160580
      - name: tet
        num_bytes: 1452151
        num_examples: 1464
      - name: th
        num_bytes: 1012868861
        num_examples: 159666
      - name: tl
        num_bytes: 85286023
        num_examples: 45121
      - name: vi
        num_bytes: 1602830022
        num_examples: 1287912
      - name: war
        num_bytes: 454266479
        num_examples: 1266204
    download_size: 1811459996
    dataset_size: 10686876247
  - config_name: seawiki_with_countries_all
    features:
      - name: url
        dtype: string
      - name: title
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: brn_ms
        num_bytes: 419662356
        num_examples: 368628
      - 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
        num_bytes: 2153274
        num_examples: 1714
      - name: idn_su
        num_bytes: 47516268
        num_examples: 61555
      - name: idn_tet
        num_bytes: 1454499
        num_examples: 1468
      - name: khm_km
        num_bytes: 103146669
        num_examples: 11994
      - name: lao_lo
        num_bytes: 15240262
        num_examples: 5014
      - name: mmr_my
        num_bytes: 313370839
        num_examples: 109310
      - name: mmr_shn
        num_bytes: 33754296
        num_examples: 13945
      - name: mmr_mnw
        num_bytes: 47321734
        num_examples: 3296
      - name: mys_ms
        num_bytes: 419662356
        num_examples: 368628
      - name: mys_ta
        num_bytes: 809156746
        num_examples: 160651
      - name: phl_war
        num_bytes: 454304567
        num_examples: 1266394
      - name: phl_tl
        num_bytes: 85356818
        num_examples: 45341
      - name: phl_ilo
        num_bytes: 16719139
        num_examples: 15371
      - name: phl_bcl
        num_bytes: 20258642
        num_examples: 15743
      - name: phl_pam
        num_bytes: 8218370
        num_examples: 9006
      - name: phl_cbk_zam
        num_bytes: 2033238
        num_examples: 3285
      - name: phl_pag
        num_bytes: 1370162
        num_examples: 2665
      - name: phl_ceb
        num_bytes: 4572804910
        num_examples: 6302896
      - name: sgp_ms
        num_bytes: 419662356
        num_examples: 368628
      - name: sgp_ta
        num_bytes: 809156746
        num_examples: 160651
      - name: tha_th
        num_bytes: 1012930269
        num_examples: 159719
      - name: tha_mnw
        num_bytes: 47321734
        num_examples: 3296
      - name: tha_shn
        num_bytes: 33754296
        num_examples: 13945
      - name: tls_tet
        num_bytes: 1454499
        num_examples: 1468
      - name: vnm_vi
        num_bytes: 1603057633
        num_examples: 1288680
    download_size: 1829748651
    dataset_size: 13074580034
  - config_name: seawiki_with_countries_dedup_all
    features:
      - name: url
        dtype: string
      - name: title
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: brn_ms
        num_bytes: 414783365
        num_examples: 348045
      - name: idn_ace
        num_bytes: 4944916
        num_examples: 12979
      - name: idn_ban
        num_bytes: 18025267
        num_examples: 20611
      - name: idn_bjn
        num_bytes: 6786207
        num_examples: 10503
      - name: idn_bug
        num_bytes: 2182435
        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
        num_bytes: 5067489
        num_examples: 11839
      - name: idn_min
        num_bytes: 116721269
        num_examples: 225972
      - name: idn_ms
        num_bytes: 414783365
        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: khm_km
        num_bytes: 102698901
        num_examples: 11466
      - name: lao_lo
        num_bytes: 14908444
        num_examples: 4897
      - 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: mys_ms
        num_bytes: 414783365
        num_examples: 348045
      - name: mys_ta
        num_bytes: 809061339
        num_examples: 160580
      - name: phl_war
        num_bytes: 454266479
        num_examples: 1266204
      - name: phl_tl
        num_bytes: 85286023
        num_examples: 45121
      - name: phl_ilo
        num_bytes: 16719001
        num_examples: 15369
      - name: phl_bcl
        num_bytes: 19977232
        num_examples: 14079
      - name: phl_pam
        num_bytes: 8205723
        num_examples: 8932
      - name: phl_cbk_zam
        num_bytes: 1579651
        num_examples: 2242
      - name: phl_pag
        num_bytes: 764869
        num_examples: 1108
      - name: phl_ceb
        num_bytes: 4346511153
        num_examples: 5815254
      - name: sgp_ms
        num_bytes: 414783365
        num_examples: 348045
      - name: sgp_ta
        num_bytes: 809061339
        num_examples: 160580
      - name: tha_th
        num_bytes: 1012868861
        num_examples: 159666
      - name: tha_mnw
        num_bytes: 47243333
        num_examples: 3271
      - name: tha_shn
        num_bytes: 33616591
        num_examples: 13662
      - name: tls_tet
        num_bytes: 1452151
        num_examples: 1464
      - name: vnm_vi
        num_bytes: 1602830022
        num_examples: 1287912
    download_size: 1811459996
    dataset_size: 12822599756

SEA Wikipedia Data Repository


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. Since Wikipedia iteslf has license cc-by-sa 4.0, we decided to follow this instead of Wikipedia HF data has of cc-by-sa 3.0 since it gives more rights to initial author/contributor.

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"
)

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). All tables are sorted by the leftmost column.

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
phl Philippines 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

ISO 639-3 Lang Code Dataset Lang Code Lang Name Country Codes Spoken Wiki Info Total Data Total Size (MiB rounded)
ace ace Acehnese idn Wiki Link 12979 4.72
ban ban Balinese idn Wiki Link 20611 17.19
bcl bcl Central Bicolano phl Wiki Link 14079 19.05
bjn bjn Banjarese idn Wiki Link 10503 6.47
bug bug Buginese idn Wiki Link 9969 2.08
bur my Burmese mmr Wiki Link 108819 298.49
cbk cbk_zam Zamboanga Chavacano/Chavacano phl Wiki Link 2242 1.51
ceb ceb Cebuano phl Wiki Link 5815254 4,145.16
gor gor Gorontalo idn Wiki Link 15290 5.93
ilo ilo Ilokano phl Wiki Link 15369 15.94
ind id Indonesian idn Wiki Link 662443 1,066.10
jav jv Javanese idn Wiki Link 73080 68.66
khm km Khmer khm Wiki Link 11466 97.94
lao lo Lao lao Wiki Link 4897 14.22
mad mad Madurese idn Wiki Link 1192 1.54
may ms Malay mys, sgp, brn, idn Wiki Link 348045 395.57
min min Minangkabau idn Wiki Link 225972 111.31
mnw mnw Mon mmr Wiki Link 3271 45.05
nia nia Nias idn Wiki Link 1714 2.05
pag pag Pangasinan phl Wiki Link 1108 0.73
pam pam Kapampangan phl Wiki Link 8932 7.83
shn shn Shan mmr Wiki Link 13662 32.06
sun su Sundanese idn Wiki Link 61529 45.31
tam ta Tamil mys, sgp Wiki Link 160580 771.58
tgl tl Tagalog phl Wiki Link 45121 81.34
tha th Thai tha Wiki Link 159666 965.95
tet tet Tetum tls, idn Wiki Link 1464 1.38
vie vi Vietnamese vnm Wiki Link 1287912 1,528.58
war war Waray phl Wiki Link 1266204 433.22
(dialect) map_bms Banyumasan
(Dialect of Javanese)
idn Wiki Link 11839 4.83

3. Table of Token Statistics for Covered Languages

The token statistics is generated using tiktoken using encoder for GPT-4.

Dataset Lang Code Total Token Avg Token per Article Min Token Max Token Token Deciles List
ace 1,370,829 105.61899992295247 3 9,659 [38.0, 52.0, 54.0, 69.0, 76.0, 84.0, 90.0, 123.0, 126.0]
ban 5,924,610 287.44893503469024 5 24,364 [97.0, 144.0, 165.0, 187.0, 209.0, 245.0, 276.0, 315.0, 421.0]
bcl 6,234,838 442.8466510405569 2 54,049 [55.0, 95.0, 143.0, 179.0, 226.0, 304.0, 419.0, 587.0, 917.2]
bjn 1,935,505 184.28115776444827 2 30,170 [36.0, 38.0, 39.0, 40.0, 42.0, 51.0, 82.0, 151.0, 367.0]
bug 553,693 55.54147858360919 1 13,951 [31.0, 42.0, 43.0, 46.0, 48.0, 50.0, 52.0, 55.0, 57.0]
cbk_zam 402,703 179.6177520071365 2 6,494 [35.0, 41.2, 56.0, 69.0, 90.0, 120.0, 138.0, 155.0, 294.9]
ceb 1,319,601,771 226.92074516435568 4 221,802 [93.0, 108.0, 123.0, 136.0, 163.0, 207.0, 278.0, 377.0, 426.0]
gor 1,575,766 103.05860039241334 2 5,525 [55.0, 58.0, 60.0, 62.0, 64.0, 66.0, 69.0, 75.0, 96.0]
id 325,411,713 491.22975561670967 1 198,597 [54.0, 93.0, 123.0, 145.0, 180.0, 226.0, 332.0, 543.0, 1068.0]
ilo 5,593,491 363.94632051532307 17 18,202 [59.0, 80.0, 91.0, 111.0, 152.0, 213.0, 303.0, 461.0, 856.0]
jv 23,528,314 321.95284619594963 2 342,156 [48.0, 60.0, 75.0, 88.0, 117.0, 175.0, 270.0, 420.0, 772.0]
km 54,559,721 4,758.391854177568 1 1,110,771 [160.0, 293.0, 452.0, 693.0, 1032.0, 1609.0, 2644.0, 4745.0, 9607.0]
lo 9,395,636 1,918.6514192362672 3 107,154 [134.0, 184.2, 285.0, 494.0, 658.0, 894.6, 1258.0, 1971.2, 4153.8]
mad 611,736 513.2013422818792 14 17,093 [80.1, 110.2, 135.0, 161.0, 194.0, 242.0, 302.7, 531.4, 1167.1]
map_bms 1,307,244 110.41844750401216 1 20,629 [20.0, 21.0, 22.0, 24.0, 30.0, 35.0, 36.0, 38.0, 111.0]
min 33,114,184 146.54109358681606 3 58,387 [81.0, 91.0, 96.0, 108.0, 119.0, 135.0, 156.0, 168.0, 170.0]
mnw 31,595,647 9,659.3234484867 6 1,450,765 [425.0, 601.0, 629.0, 682.0, 763.0, 2103.0, 4255.0, 7724.0, 14517.0]
ms 121,343,673 348.64363228892813 1 68,545 [32.0, 40.0, 49.0, 63.0, 105.0, 138.0, 216.0, 362.0, 788.0]
my 189,439,447 1,740.8673761015998 10 1,376,658 [164.0, 269.0, 350.0, 508.0, 559.0, 578.0, 605.0, 892.4, 3369.0]
nia 795,527 464.134772462077 8 18,650 [59.0, 61.0, 63.0, 65.0, 67.0, 86.0, 239.1, 623.4, 1249.7]
pag 222,366 200.6913357400722 5 10,143 [31.0, 51.0, 73.0, 110.0, 118.0, 120.0, 127.0, 181.0, 355.8]
pam 2,269,091 254.04064039408868 1 14,912 [38.0, 56.0, 78.0, 108.0, 121.0, 150.0, 193.0, 289.0, 525.8]
shn 23,125,637 1,692.6977748499487 2 204,094 [460.0, 480.0, 585.0, 679.0, 715.0, 740.0, 756.0, 780.0, 1580.9]
su 14,710,124 239.07627297697022 1 99,456 [41.0, 43.0, 45.0, 49.0, 70.0, 146.0, 216.0, 219.0, 419.0]
ta 376,043,508 2,341.782961763607 15 177,054 [543.0, 700.0, 824.0, 1001.0, 1153.0, 1465.0, 1992.0, 2911.0, 4652.0]
tet 487,016 332.6612021857924 4 24,287 [30.3, 47.0, 66.9, 101.0, 164.0, 177.0, 187.0, 248.6, 604.4]
th 330,964,733 2,072.8566695476807 1 289,150 [231.0, 390.0, 546.0, 727.0, 969.0, 1276.0, 1741.0, 2533.0, 4361.0]
tl 27,789,730 615.8934864032269 7 60,728 [73.0, 116.0, 161.0, 214.0, 281.0, 360.0, 465.0, 666.0, 1136.0]
vi 546,481,913 424.3161900813099 3 246,463 [46.0, 64.0, 71.0, 80.0, 86.0, 92.0, 120.0, 240.0, 824.0]
war 117,438,315 92.74833676090108 1 25,689 [60.0, 77.0, 81.0, 84.0, 87.0, 90.0, 94.0, 99.0, 110.0]

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 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 unavailable 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/UTF-8 chars validated). The source code can be found on this Github Repo SEA Wiki Github Source Code

How do I extract new Wikipedia Dataset of SEA languages?

Please refer to the corresponding Github Repo for more detailed info SEA Wiki Github Source Code

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"}