metadata
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
license:
- cc-by-sa-4.0
- gfdl
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
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num_examples: 13003
- name: ban
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num_examples: 20987
- name: bcl
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- name: bjn
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num_examples: 10519
- name: bug
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num_examples: 15880
- name: cbk_zam
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num_examples: 3285
- name: ceb
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num_examples: 6302896
- name: gor
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- name: id
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num_examples: 665622
- name: ilo
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- name: jv
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num_examples: 73380
- name: km
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num_examples: 11994
- name: lo
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num_examples: 5014
- name: mad
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num_examples: 1192
- name: map_bms
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- name: min
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num_examples: 227143
- name: mnw
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num_examples: 3296
- name: ms
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- name: my
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- name: nia
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- name: pag
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- name: pam
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- name: shn
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- name: su
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- name: ta
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num_examples: 160651
- name: tet
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num_examples: 1468
- name: th
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- name: tl
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- name: vi
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num_examples: 1288680
- name: war
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num_examples: 1266394
download_size: 10940051715
dataset_size: 10923905689
- config_name: seawiki_dedup_all
features:
- name: url
dtype: string
- name: title
dtype: string
- name: text
dtype: string
splits:
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- name: ban
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- name: bcl
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- name: bjn
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- name: bug
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- name: cbk_zam
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- name: ceb
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- name: gor
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- name: id
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- name: ilo
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- name: jv
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- name: km
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- name: lo
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- name: mad
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- name: map_bms
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- name: min
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- name: mnw
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- name: ms
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- name: my
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- name: nia
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- name: pag
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- name: pam
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- name: shn
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- name: su
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- name: ta
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- name: tet
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- name: th
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- name: tl
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- name: vi
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- name: war
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download_size: 10701952694
dataset_size: 10686874347
- config_name: seawiki_with_countries_all
features:
- name: url
dtype: string
- name: title
dtype: string
- name: text
dtype: string
splits:
- name: brn_ms
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num_examples: 368628
- name: idn_ace
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num_examples: 13003
- name: idn_ban
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num_examples: 20987
- name: idn_bjn
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num_examples: 10519
- name: idn_bug
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num_examples: 15880
- name: idn_gor
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num_examples: 15359
- name: idn_id
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num_examples: 665622
- name: idn_jv
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num_examples: 73380
- name: idn_mad
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num_examples: 1192
- name: idn_map_bms
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num_examples: 13580
- name: idn_min
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num_examples: 227143
- name: idn_ms
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num_examples: 368628
- name: idn_nia
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num_examples: 1714
- name: idn_su
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num_examples: 61555
- name: idn_tet
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num_examples: 1468
- name: khm_km
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num_examples: 11994
- name: lao_lo
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num_examples: 5014
- name: mmr_my
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num_examples: 109310
- name: mmr_shn
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- name: mmr_mnw
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num_examples: 3296
- name: mys_ms
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num_examples: 368628
- name: mys_ta
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- name: phl_war
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- name: phl_tl
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- name: phl_ilo
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- name: phl_bcl
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- name: phl_pam
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- name: phl_cbk_zam
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- name: phl_pag
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- name: phl_ceb
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- name: sgp_ms
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- name: sgp_ta
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- name: tha_th
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- name: tha_mnw
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- name: tha_shn
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- name: tls_tet
num_bytes: 1454499
num_examples: 1468
- name: vnm_vi
num_bytes: 1603057632
num_examples: 1288680
download_size: 10940051715
dataset_size: 13074580032
- 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
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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
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num_examples: 15290
- name: idn_id
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num_examples: 662443
- name: idn_jv
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num_examples: 73080
- name: idn_mad
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- name: idn_map_bms
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num_examples: 11839
- name: idn_min
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num_examples: 225972
- name: idn_ms
num_bytes: 414783365
num_examples: 348045
- name: idn_nia
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- name: idn_su
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num_examples: 61529
- name: idn_tet
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- name: khm_km
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- name: lao_lo
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- name: mmr_my
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- name: mmr_shn
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- name: mmr_mnw
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- name: mys_ms
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num_examples: 348045
- name: mys_ta
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- name: phl_war
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- name: phl_tl
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- name: phl_ilo
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num_examples: 15369
- name: phl_bcl
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- name: phl_pam
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- name: phl_cbk_zam
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- name: phl_ceb
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- name: sgp_ms
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- name: sgp_ta
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num_examples: 160580
- name: tha_th
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- 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: 1602828123
num_examples: 1287910
download_size: 10701952694
dataset_size: 12822597856
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).
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
| Lang Code | Lang Name | Country Codes Spoken | Wiki Info | Total Data | Total Size (MiB rounded) |
|---|---|---|---|---|---|
| ace | Acehnese | idn | Wiki Link | 12904 | 4.64 |
| ban | Balinese | idn | Wiki Link | 19837 | 16.56 |
| bjn | Banjarese | idn | Wiki Link | 10437 | 6.35 |
| bcl | Central Bicolano | phl | Wiki Link | 15743 | 19.32 |
| bug | Buginese | idn | Wiki Link | 9793 | 1.98 |
| ceb | Cebuano | phl | Wiki Link | Not Supported Yet | Not Supported Yet |
| cbk (ISO 639-3) cbk_zam (WikiMedia) |
Zamboanga Chavacano/Chavacano | phl | Wiki Link | 3285 | 1.94 |
| gor | Gorontalo | idn | Wiki Link | 14514 | 5.71 |
| ilo | Ilokano | phl | Wiki Link | 15371 | 15.94 |
| km | Khmer | khm | Wiki Link | 11994 | 98.37 |
| id | Indonesian | idn | Wiki Link | 654287 | 1049.93 |
| jv | Javanese | idn | Wiki Link | 72667 | 66.54 |
| lo | Lao | lao | Wiki Link | 5014 | 14.53 |
| mad | Madurese | idn | Wiki Link | 1192 | 1.54 |
| map_bms | Banyumasan (Dialect of Javanese) |
idn | Wiki Link | 11832 | 4.83 |
| mnw | Mon | mmr | Wiki Link | 3296 | 45.13 |
| min | Minangkabau | idn | Wiki Link | 225858 | 110.99 |
| ms | Malay | mys, sgp, brn, idn | Wiki Link | 346186 | 391.43 |
| my | Burmese | mmr | Wiki Link | 109310 | 298.85 |
| nia | Nias | idn | Wiki Link | 1650 | 1.85 |
| pag | Pangasinan | phl | Wiki Link | 2665 | 1.31 |
| pam | Kapampangan | phl | Wiki Link | 9006 | 7.84 |
| shn | Shan | mmr | Wiki Link | 13945 | 32.19 |
| su | Sundanese | idn | Wiki Link | 61494 | 45.21 |
| ta | Tamil | mys, sgp | Wiki Link | 160651 | 0.15 |
| tet | Tetum | tls, idn | Wiki Link | 1465 | 1.39 |
| th | Thai | tha | Wiki Link | 159719 | 966.00 |
| tl | Tagalog | phl | Wiki Link | 45341 | 81.42 |
| vi | Vietnamese | vnm | Wiki Link | 1288680 | 1528.79 |
| war | Waray | phl | Wiki Link | 1266394 | 433.26 |
3. Table of Token Statistics for Covered Languages
The token statistics is generated using tiktoken using encoder for GPT-4.
| 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] |
| 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 | 546,481,258 | 424.3163404275143 | 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:
- Raw data is being deduplicated on
titleandtext(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. - Furthermore, the
titleandtextdata 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). You may check thisdedup_raw_wiki_data.pyscript to understand its implementation.
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.
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. Please note that this dataset is extensible to any languages of your choice.
To replicate the whole dataset generation process
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.txtuse this codebase viapip install -r requirements.txt.Activate the chosen Python/Conda environment which the requirements are being installed.
Force install
multiprocess==0.70.15by usingpip install multiprocess==0.70.15to avoid this issue (there's no other workaround for now)Run this
shscript for extractions from Wikiedia HF usingsh extract_raw_wiki_data_sea.sh
This script will runextract_raw_wiki_data.pyto construct the Wiki Dataset.Run this
shscript for deduplications from extracted data in Step 4 usingsh dedup_raw_wiki_data_sea.sh
This script will rundedup_raw_wiki_data.pyto do Wiki Dataset Clenasing. Please note that the cleansing process can be language/dialect specific.
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"}