Dataset Viewer
Duplicate
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
dataset: string
version: string
generated_at: timestamp[s]
selection: struct<rule: string, unit: string, threshold_bytes: int64>
  child 0, rule: string
  child 1, unit: string
  child 2, threshold_bytes: int64
sources_note: string
languages: struct<af: struct<kept: int64, coverage: double, sources: struct<wikipedia-monthly: struct<text_byte (... 23266 chars omitted)
  child 0, af: struct<kept: int64, coverage: double, sources: struct<wikipedia-monthly: struct<text_bytes: int64, t (... 115 chars omitted)
      child 0, kept: int64
      child 1, coverage: double
      child 2, sources: struct<wikipedia-monthly: struct<text_bytes: int64, tokens: int64>, FineWeb2-HQ-plus: struct<text_by (... 27 chars omitted)
          child 0, wikipedia-monthly: struct<text_bytes: int64, tokens: int64>
              child 0, text_bytes: int64
              child 1, tokens: int64
          child 1, FineWeb2-HQ-plus: struct<text_bytes: int64, tokens: int64>
              child 0, text_bytes: int64
              child 1, tokens: int64
      child 3, text_bytes: int64
      child 4, tokens_total: int64
  child 1, am: struct<kept: int64, coverage: double, sources: struct<wikipedia-monthly: struct<text_bytes: int64, t (... 115 chars omitted)
      child 0, kept: int64
      child 1, coverage: double
      child 2, sources: struct<wikipedia-monthly: struct<text_bytes: int64, tokens: int64>, FineWeb2-HQ-plus: struct<text_by (... 27 chars omitted)
          child 0, wikipedia-monthly: struct<text_bytes
...
ly: struct<text_bytes: int64, tokens: int64>
              child 0, text_bytes: int64
              child 1, tokens: int64
          child 1, FineWeb2-HQ-plus: struct<text_bytes: int64, tokens: int64>
              child 0, text_bytes: int64
              child 1, tokens: int64
      child 3, text_bytes: int64
      child 4, tokens_total: int64
  child 109, zh: struct<kept: int64, coverage: double, sources: struct<wikipedia-monthly: struct<text_bytes: int64, t (... 175 chars omitted)
      child 0, kept: int64
      child 1, coverage: double
      child 2, sources: struct<wikipedia-monthly: struct<text_bytes: int64, tokens: int64>, Ultra-FineWeb-L3: struct<text_by (... 87 chars omitted)
          child 0, wikipedia-monthly: struct<text_bytes: int64, tokens: int64>
              child 0, text_bytes: int64
              child 1, tokens: int64
          child 1, Ultra-FineWeb-L3: struct<text_bytes: int64, tokens: int64>
              child 0, text_bytes: int64
              child 1, tokens: int64
          child 2, FineWeb2-HQ-plus: struct<text_bytes: int64, tokens: int64>
              child 0, text_bytes: int64
              child 1, tokens: int64
      child 3, text_bytes: int64
      child 4, tokens_total: int64
algorithm: string
generatedAt: timestamp[s]
files: list<item: struct<file: string, bytes: int64, sha256: string>>
  child 0, item: struct<file: string, bytes: int64, sha256: string>
      child 0, file: string
      child 1, bytes: int64
      child 2, sha256: string
to
{'generatedAt': Value('timestamp[s]'), 'algorithm': Value('string'), 'files': List({'file': Value('string'), 'bytes': Value('int64'), 'sha256': Value('string')})}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 544, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3052, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 558, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 361, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              dataset: string
              version: string
              generated_at: timestamp[s]
              selection: struct<rule: string, unit: string, threshold_bytes: int64>
                child 0, rule: string
                child 1, unit: string
                child 2, threshold_bytes: int64
              sources_note: string
              languages: struct<af: struct<kept: int64, coverage: double, sources: struct<wikipedia-monthly: struct<text_byte (... 23266 chars omitted)
                child 0, af: struct<kept: int64, coverage: double, sources: struct<wikipedia-monthly: struct<text_bytes: int64, t (... 115 chars omitted)
                    child 0, kept: int64
                    child 1, coverage: double
                    child 2, sources: struct<wikipedia-monthly: struct<text_bytes: int64, tokens: int64>, FineWeb2-HQ-plus: struct<text_by (... 27 chars omitted)
                        child 0, wikipedia-monthly: struct<text_bytes: int64, tokens: int64>
                            child 0, text_bytes: int64
                            child 1, tokens: int64
                        child 1, FineWeb2-HQ-plus: struct<text_bytes: int64, tokens: int64>
                            child 0, text_bytes: int64
                            child 1, tokens: int64
                    child 3, text_bytes: int64
                    child 4, tokens_total: int64
                child 1, am: struct<kept: int64, coverage: double, sources: struct<wikipedia-monthly: struct<text_bytes: int64, t (... 115 chars omitted)
                    child 0, kept: int64
                    child 1, coverage: double
                    child 2, sources: struct<wikipedia-monthly: struct<text_bytes: int64, tokens: int64>, FineWeb2-HQ-plus: struct<text_by (... 27 chars omitted)
                        child 0, wikipedia-monthly: struct<text_bytes
              ...
              ly: struct<text_bytes: int64, tokens: int64>
                            child 0, text_bytes: int64
                            child 1, tokens: int64
                        child 1, FineWeb2-HQ-plus: struct<text_bytes: int64, tokens: int64>
                            child 0, text_bytes: int64
                            child 1, tokens: int64
                    child 3, text_bytes: int64
                    child 4, tokens_total: int64
                child 109, zh: struct<kept: int64, coverage: double, sources: struct<wikipedia-monthly: struct<text_bytes: int64, t (... 175 chars omitted)
                    child 0, kept: int64
                    child 1, coverage: double
                    child 2, sources: struct<wikipedia-monthly: struct<text_bytes: int64, tokens: int64>, Ultra-FineWeb-L3: struct<text_by (... 87 chars omitted)
                        child 0, wikipedia-monthly: struct<text_bytes: int64, tokens: int64>
                            child 0, text_bytes: int64
                            child 1, tokens: int64
                        child 1, Ultra-FineWeb-L3: struct<text_bytes: int64, tokens: int64>
                            child 0, text_bytes: int64
                            child 1, tokens: int64
                        child 2, FineWeb2-HQ-plus: struct<text_bytes: int64, tokens: int64>
                            child 0, text_bytes: int64
                            child 1, tokens: int64
                    child 3, text_bytes: int64
                    child 4, tokens_total: int64
              algorithm: string
              generatedAt: timestamp[s]
              files: list<item: struct<file: string, bytes: int64, sha256: string>>
                child 0, item: struct<file: string, bytes: int64, sha256: string>
                    child 0, file: string
                    child 1, bytes: int64
                    child 2, sha256: string
              to
              {'generatedAt': Value('timestamp[s]'), 'algorithm': Value('string'), 'files': List({'file': Value('string'), 'bytes': Value('int64'), 'sha256': Value('string')})}
              because column names don't match

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

Word Frequency Lists (110 languages)

English | 中文说明

Small word-frequency lists for 110 languages, self-built for use as offline frequency dictionaries: one gzip-compressed MessagePack file per language, about 13 MB in total. These lists are also the direct vocabulary source of vocabradar/WordTranslation, which translates them word by word.

The lists come from a single pyicu BreakIterator segmentation pipeline over FineWeb2 HQ+, UltraFineWeb L3, and Wikipedia (each source capped at 1 GiB of text per language). Word selection uses a size-aware frequency gate: fu_w > 1e-6 AND fu_w / word_bytes > 2e-7, packed into 700 centibel bands.

Selection rule: a language is included when its total source text volume exceeds 100 MB (104,857,600 bytes, summed over sources; text_bytes in meta.json). Each source is capped at 1 GiB during corpus build.

Current revision: v7 (2026-10-26). See Version history.

Files

├── README.md
├── meta.json                      # dataset metadata (see fields below)
└── data/
    └── small_<code>.msgpack.gz    # one file per language,
                                   # e.g. small_en.msgpack.gz, small_th.msgpack.gz

meta.json records per language: kept (words in the list), coverage (real corpus coverage of the list), sources (per-source text_bytes / tokens), and derived text_bytes (total source volume) and tokens_total.

All languages use 700 centibel bands with the same cBpack encoding (header + list of bands). See Data format.

Cleaning rules

Single upstream pipeline (pyicu BreakIterator + all-script Unicode rule set), identical for every language:

  • Normalization: NFC for Latin/Greek/Cyrillic scripts, NFKC otherwise; abjad vowel-mark removal (ar, he, fa, ur, ps, sd, ug, ...); casefold with dotless-i for tr/az/kk; cedilla→comma fix for ro.
  • Rejection rules: no_letter, numeric, has_digit, domain_tld, diacritic_single, foreign (per-language script whitelist).
  • Frequency gate: fu_w > 1e-6 AND fu_w / word_bytes > 2e-7, where word_bytes is the word's UTF-8 length (+1 for languages written with spaces).

For implementation details see the source pipeline: WordFrequency/scripts/build_wordfreq.py (in the VocabRadar data repo).

Vocabulary lists

Alphabetical by language code.

code language native name first word cb float words cumulative coverage
af Afrikaans Afrikaans die 116 6.92e-02 27,289 87.9%
am Amharic አማርኛ እና 176 1.74e-02 30,174 75.6%
ar Arabic العربية في 153 2.95e-02 34,950 78.1%
arz Egyptian Arabic مصرى فى 144 3.63e-02 12,783 79.8%
as Assamese অসমীয়া আৰু 162 2.40e-02 18,601 77.9%
ast Asturian asturianu de 119 6.46e-02 36,867 84.2%
az Azerbaijani azərbaycan və 153 2.95e-02 38,016 80.2%
azb South Azerbaijani تۆرکجه و 168 2.09e-02 10,407 52.7%
ba Bashkir башҡортса һәм 171 1.95e-02 22,247 73.8%
be Belarusian беларуская і 156 2.75e-02 26,836 71.4%
bew Betawi Basa Betawi yang 169 2.04e-02 32,004 91.7%
bg Bulgarian български на 127 5.37e-02 23,184 77.4%
bn Bengali বাংলা এবং 187 1.35e-02 18,147 77.6%
bo Tibetan བོད་ཡིག པ 147 3.39e-02 4,812 97.4%
bs Bosnian bosanski i 144 3.63e-02 43,867 82.5%
ca Catalan català de 122 6.03e-02 30,554 87.0%
ce Chechen нохчийн а 149 3.24e-02 4,772 74.1%
ceb Cebuano Cebuano sa 124 5.75e-02 12,376 87.5%
ckb Central Kurdish کوردی لە 128 5.25e-02 23,055 77.6%
cs Czech čeština a 153 2.95e-02 43,516 78.7%
cy Welsh Cymraeg yn 133 4.68e-02 27,914 84.9%
da Danish dansk i 150 3.16e-02 31,312 83.9%
de German Deutsch der 149 3.24e-02 32,074 80.8%
dv Dhivehi ދިވެހި އެވެ 183 1.48e-02 22,674 81.7%
el Greek Ελληνικά και 151 3.09e-02 20,531 77.2%
en English English the 121 6.17e-02 25,475 90.9%
eo Esperanto Esperanto la 113 7.41e-02 38,703 80.3%
es Spanish español de 114 7.24e-02 29,488 89.4%
et Estonian eesti ja 151 3.09e-02 43,564 76.0%
eu Basque euskara eta 142 3.80e-02 37,926 81.0%
fa Persian فارسی و 140 3.98e-02 18,812 86.3%
fi Finnish suomi ja 148 3.31e-02 43,242 69.4%
fil Tagalog Tagalog sa 120 6.31e-02 25,283 91.6%
fr French français de 123 5.89e-02 30,283 88.9%
fy West Frisian Frysk de 130 5.01e-02 32,813 83.5%
ga Irish Gaeilge an 137 4.27e-02 27,106 88.2%
gl Galician galego de 127 5.37e-02 31,191 86.7%
gmh Middle High German Mittelhochdeutsch und 197 1.07e-02 35,007 86.3%
gu Gujarati ગુજરાતી છે 133 4.68e-02 19,297 80.5%
ha Hausa Harshen Hausa da 119 6.46e-02 23,058 89.0%
he Hebrew עברית של 162 2.40e-02 40,467 80.5%
hi Hindi हिन्दी के 138 4.17e-02 14,413 86.0%
hr Croatian hrvatski i 147 3.39e-02 45,220 81.4%
hu Hungarian magyar a 110 7.94e-02 39,941 74.3%
hy Armenian հայերեն է 140 3.98e-02 22,345 71.0%
id Indonesian Bahasa Indonesia yang 155 2.82e-02 29,234 86.3%
ig Igbo Asụsụ Igbo na 104 9.12e-02 23,765 87.1%
is Icelandic íslenska og 142 3.80e-02 33,521 84.2%
it Italian italiano di 139 4.07e-02 33,439 86.9%
ja Japanese 日本語 の 129 5.13e-02 27,259 88.8%
ka Georgian ქართული და 148 3.31e-02 19,548 65.9%
kk Kazakh қазақша және 185 1.41e-02 25,922 74.3%
km Khmer ខ្មែរ បាន 173 1.86e-02 12,302 89.9%
kn Kannada ಕನ್ನಡ ಮತ್ತು 172 1.91e-02 21,850 65.1%
ko Korean 한국어 년 187 1.35e-02 42,580 59.6%
ku Kurdish kurdî li 163 2.34e-02 30,109 82.8%
ky Kyrgyz кыргызча жана 175 1.78e-02 26,184 77.3%
la Latin Latina et 152 3.02e-02 41,416 81.4%
lb Luxembourgish Lëtzebuergesch an 162 2.40e-02 33,684 82.2%
lo Lao ພາສາລາວ ຂອງ 158 2.63e-02 8,165 90.6%
lt Lithuanian lietuvių ir 152 3.02e-02 44,180 79.3%
lv Latvian latviešu un 151 3.09e-02 41,008 82.8%
mg Malagasy Malagasy ny 111 7.76e-02 23,818 80.0%
mk Macedonian македонски на 125 5.62e-02 22,246 80.1%
ml Malayalam മലയാളം ഒരു 191 1.23e-02 19,303 52.5%
mn Mongolian монгол нь 162 2.40e-02 23,142 83.1%
mr Marathi मराठी आणि 178 1.66e-02 20,174 75.3%
ms Malay Bahasa Melayu yang 154 2.88e-02 26,033 89.9%
mt Maltese Malti l 142 3.80e-02 27,749 90.3%
my Myanmar မြန်မာ ကို 163 2.34e-02 8,704 92.2%
nb Norwegian Bokmål norsk bokmål og 149 3.24e-02 28,715 87.4%
ne Nepali नेपाली र 164 2.29e-02 19,634 80.1%
new Newari नेपाल भाषा thumb 294 1.15e-03 2,894 2.0%
nl Dutch Nederlands de 122 6.03e-02 29,041 84.6%
nn Norwegian Nynorsk norsk nynorsk i 140 3.98e-02 31,299 82.1%
no Norwegian norsk i 143 3.72e-02 36,870 76.3%
nrm Norman Normaund de 144 3.63e-02 37,834 65.2%
oc Occitan occitan de 115 7.08e-02 36,968 84.0%
or Odia ଓଡ଼ିଆ ଓ 192 1.20e-02 18,890 81.3%
pa Punjabi ਪੰਜਾਬੀ ਹੈ 156 2.75e-02 15,494 87.4%
pl Polish polski w 141 3.89e-02 44,785 78.6%
pnb Western Punjabi پنجابی دے 145 3.55e-02 19,856 83.2%
ps Pashto پښتو د 105 8.91e-02 19,349 89.3%
pt Portuguese português de 127 5.37e-02 30,823 88.7%
ro Romanian română de 133 4.68e-02 36,662 85.3%
ru Russian русский в 142 3.80e-02 28,737 73.3%
sd Sindhi سنڌي جي 134 4.57e-02 19,326 88.4%
sh Serbo-Croatian srpskohrvatski u 146 3.47e-02 43,563 79.3%
si Sinhala සිංහල සහ 214 7.24e-03 20,592 78.5%
sk Slovak slovenčina a 152 3.02e-02 44,353 79.9%
sl Slovenian slovenščina je 149 3.24e-02 43,561 82.4%
so Somali Soomaaliga oo 154 2.88e-02 33,472 88.8%
sq Albanian shqip të 119 6.46e-02 34,083 88.1%
sr Serbian српски је 155 2.82e-02 22,537 59.8%
sv Swedish svenska och 151 3.09e-02 32,738 81.7%
sw Swahili Kiswahili ya 122 6.03e-02 24,555 88.9%
ta Tamil தமிழ் ஒரு 207 8.51e-03 19,145 61.7%
te Telugu తెలుగు నుండి 205 8.91e-03 19,393 67.3%
tg Tajik тоҷикӣ дар 147 3.39e-02 21,633 77.1%
th Thai ไทย ที่ 162 2.40e-02 10,648 88.1%
tr Turkish Türkçe ve 156 2.75e-02 43,447 74.3%
tt Tatar татарча һәм 193 1.17e-02 12,504 68.5%
ug Uyghur ئۇيغۇرچە ۋە 183 1.48e-02 25,287 76.0%
uk Ukrainian українська в 172 1.91e-02 27,817 73.8%
ur Urdu اردو کے 142 3.80e-02 16,966 89.3%
uz Uzbek oʻzbekcha va 173 1.86e-02 32,259 54.6%
vi Vietnamese Tiếng Việt là 186 1.38e-02 12,420 91.9%
war Waray Winaray nga 123 5.89e-02 23,655 84.0%
yi Yiddish ייִדיש די 142 3.80e-02 21,665 85.9%
zh Chinese 中文 的 137 4.27e-02 35,707 90.8%
Total 110 languages — — — — 2,997,108 —

(first word = highest-frequency headword, sanity check. cb = centibel band of top word, float = token share. words = number of headwords in the list. cumulative coverage = Σ n_b × 10^(-b/100).)

Data format

Each file is a gzipped MessagePack array of [header, band_0..band_699]. Each band holds words whose frequency was rounded to that centibel (cB), so band b ≈ 10^(-b/100) of running tokens.

import gzip, msgpack

with gzip.open('data/small_en.msgpack.gz', 'rb') as f:
    obj = msgpack.unpackb(f.read(), raw=False)

header, *bands = obj
# header == {'format': 'cB', 'version': 1, 'lang': 'en',
#            'sources': ['ultrafineweb_l3', 'wikipedia']}

words = [(w, 10 ** (-b / 100)) for b, band in enumerate(bands) for w in band]
# words[0] ≈ ('the', ...) — rank 1 word of English

Version history

  • v7 (2026-10-26): full rebuild from the self-built pyicu pipeline (single source, no more wordfreq merge). Uniform 700 bands, word gate fu_w > 1e-6 and fu_w / word_bytes > 2e-7. Selection: total source text_bytes > 100 MB → 110 languages (Simple English simple excluded: a wiki edition code, not a language code). Tagalog/Filipino is published under the ISO 639-3 code fil (not the legacy tl), one code for Tagalog/Filipino. Script whitelists fixed for ce, ba, tt, azb, ug, pnb, sd, arz, skr (their non-Latin words were being rejected as foreign, leaving only Latin debris). Cross-source frequency merge uses a global volume denominator (a source the word is absent from counts as zero frequency); an earlier per-word renormalization inflated words unique to small sources (e.g. bew list coverage estimated at 110%).
  • v6 (merged 2026-10-26): merged wordfreq v4 (42 langs) into WordFrequency v5. Overlapping 42 languages use wf_v4 files+meta. 28 v5-only languages preserved. th file explicitly kept from v5 (user's own, higher-coverage pyicu result). 3 wf-v4-only languages restored (fil, is, sh).
  • v5 (2026-10-26): WordFrequency self-built pyicu BreakIterator corpus (wiki + ultra + fw2). 76 languages (10^-7 threshold, 700 bands).
  • v4 (2026-10-12): wordfreq v4 on HF — added digit_mix, possessive, mark_only, diacritic_single, stroke_single, jamo_single. 43 languages, cumulative counts across in-place revisions. Released as https://huggingface.co/datasets/vocabradar/wordfreq.
  • v3 (2026-10-10): wordfreq v3 — numeric rule (digit-led codes, CJK numerals, numeric phrases). meta.json reorganized as languages[lang] = {total, removed, kept}.
  • v1-v2: wordfreq 1-2 — initial small lists from wordfreq 3.0.2 + Unicode-script whitelist (foreign, pure_num, no_letter).

License

MIT.

About VocabRadar

This dataset is a VocabRadar project — the vocabulary radar. The VocabRadar browser extension marks up the words you do not know yet while you watch videos or browse the web: definitions in place, translation, bilingual subtitles and annotated subtitles. What you have read can also be on vocabradar.com, which turns it into related exercises and games so the words actually stick.


词频表(110 语)

English | 中文说明

(卡片为单文件双语,中文部分完整对应上方英文说明。)

110 种语言的小型词频表,自建管线产出,可直接当离线词频字典使用:每种语言一个 gzip 压缩的 MessagePack 文件,合计约 13 MB。本词表同时是 vocabradar/WordTranslation 的直接词源(逐词翻译成各语种)。

数据来自统一的 pyicu BreakIterator 分词管线,语料为 FineWeb2 HQ+、 UltraFineWeb L3、 Wikipedia(每语种每来源截断至 1 GiB 文本)。收词采用体积感知的频率双门槛: fu_w > 1e-6 且 fu_w / word_bytes > 2e-7,打包成 700 个 centibel 频段。

收录规则: 合计源头语料体积 大于 100 MB(104,857,600 字节,1024 进制;各来源 text_bytes 相加,即 meta.json 中的 text_bytes)的语种入选。构建期每来源封顶 1 GiB。

当前修订版:v7(2026-10-26)。 见版本历史。

文件结构

├── README.md
├── meta.json                      # 数据集元信息(字段见下)
└── data/
    └── small_<code>.msgpack.gz    # 每语种一个文件,
                                   # 如 small_en.msgpack.gz、small_th.msgpack.gz

meta.json 按语种记录:kept(词表词数)、coverage(词表在语料上的真实覆盖率)、 sources(各来源的 text_bytes / tokens),以及派生字段 text_bytes(合计源头 体积)与 tokens_total。

频段数:全部语种统一 700 段,共享 cBpack 编码(header + band 列表)。详见数据格式。

清洗规则

统一的上游管线(pyicu BreakIterator + 全脚本 Unicode 规则集),各语种一致:

  • 规范化:拉丁/希腊/西里尔文种 NFC,其余 NFKC;abjad 文种去元音点(ar、he、fa、 ur、ps、sd、ug 等);casefold(tr/az/kk 用 dotless-i 特殊处理); ro 的 cedilla→comma 修复。
  • 剔除规则:no_letter、numeric、has_digit、domain_tld、diacritic_single、 foreign(按语种的 script 白名单)。
  • 频率门槛:fu_w > 1e-6 且 fu_w / word_bytes > 2e-7;word_bytes 为词的 UTF-8 字节数(有空格分词的语言 +1 计入空格代价)。

实现细节见源管线:WordFrequency/scripts/build_wordfreq.py(VocabRadar 数据仓库内)。

词表一览

按语言代码字母序排列。

code language native name first word cb float words cumulative coverage
af 南非荷兰语 Afrikaans die 116 6.92e-02 27,289 87.9%
am 阿姆哈拉语 አማርኛ እና 176 1.74e-02 30,174 75.6%
ar 阿拉伯语 العربية في 153 2.95e-02 34,950 78.1%
arz 埃及阿拉伯语 مصرى فى 144 3.63e-02 12,783 79.8%
as 阿萨姆语 অসমীয়া আৰু 162 2.40e-02 18,601 77.9%
ast 阿斯图里亚斯语 asturianu de 119 6.46e-02 36,867 84.2%
az 阿塞拜疆语 azərbaycan və 153 2.95e-02 38,016 80.2%
azb 南阿塞拜疆语 تۆرکجه و 168 2.09e-02 10,407 52.7%
ba 巴什基尔语 башҡортса һәм 171 1.95e-02 22,247 73.8%
be 白俄罗斯语 беларуская і 156 2.75e-02 26,836 71.4%
bew 贝塔维语 Basa Betawi yang 169 2.04e-02 32,004 91.7%
bg 保加利亚语 български на 127 5.37e-02 23,184 77.4%
bn 孟加拉语 বাংলা এবং 187 1.35e-02 18,147 77.6%
bo 藏语 བོད་ཡིག པ 147 3.39e-02 4,812 97.4%
bs 波斯尼亚语 bosanski i 144 3.63e-02 43,867 82.5%
ca 加泰罗尼亚语 català de 122 6.03e-02 30,554 87.0%
ce 车臣语 нохчийн а 149 3.24e-02 4,772 74.1%
ceb 宿务语 Cebuano sa 124 5.75e-02 12,376 87.5%
ckb 中库尔德语 کوردی لە 128 5.25e-02 23,055 77.6%
cs 捷克语 čeština a 153 2.95e-02 43,516 78.7%
cy 威尔士语 Cymraeg yn 133 4.68e-02 27,914 84.9%
da 丹麦语 dansk i 150 3.16e-02 31,312 83.9%
de 德语 Deutsch der 149 3.24e-02 32,074 80.8%
dv 迪维希语 ދިވެހި އެވެ 183 1.48e-02 22,674 81.7%
el 希腊语 Ελληνικά και 151 3.09e-02 20,531 77.2%
en 英语 English the 121 6.17e-02 25,475 90.9%
eo 世界语 Esperanto la 113 7.41e-02 38,703 80.3%
es 西班牙语 español de 114 7.24e-02 29,488 89.4%
et 爱沙尼亚语 eesti ja 151 3.09e-02 43,564 76.0%
eu 巴斯克语 euskara eta 142 3.80e-02 37,926 81.0%
fa 波斯语 فارسی و 140 3.98e-02 18,812 86.3%
fi 芬兰语 suomi ja 148 3.31e-02 43,242 69.4%
fil 他加禄语 Tagalog sa 120 6.31e-02 25,283 91.6%
fr 法语 français de 123 5.89e-02 30,283 88.9%
fy 西弗里西亚语 Frysk de 130 5.01e-02 32,813 83.5%
ga 爱尔兰语 Gaeilge an 137 4.27e-02 27,106 88.2%
gl 加利西亚语 galego de 127 5.37e-02 31,191 86.7%
gmh 中古高地德语 Mittelhochdeutsch und 197 1.07e-02 35,007 86.3%
gu 古吉拉特语 ગુજરાતી છે 133 4.68e-02 19,297 80.5%
ha 豪萨语 Harshen Hausa da 119 6.46e-02 23,058 89.0%
he 希伯来语 עברית של 162 2.40e-02 40,467 80.5%
hi 印地语 हिन्दी के 138 4.17e-02 14,413 86.0%
hr 克罗地亚语 hrvatski i 147 3.39e-02 45,220 81.4%
hu 匈牙利语 magyar a 110 7.94e-02 39,941 74.3%
hy 亚美尼亚语 հայերեն է 140 3.98e-02 22,345 71.0%
id 印度尼西亚语 Bahasa Indonesia yang 155 2.82e-02 29,234 86.3%
ig 伊博语 Asụsụ Igbo na 104 9.12e-02 23,765 87.1%
is 冰岛语 íslenska og 142 3.80e-02 33,521 84.2%
it 意大利语 italiano di 139 4.07e-02 33,439 86.9%
ja 日语 日本語 の 129 5.13e-02 27,259 88.8%
ka 格鲁吉亚语 ქართული და 148 3.31e-02 19,548 65.9%
kk 哈萨克语 қазақша және 185 1.41e-02 25,922 74.3%
km 高棉语 ខ្មែរ បាន 173 1.86e-02 12,302 89.9%
kn 卡纳达语 ಕನ್ನಡ ಮತ್ತು 172 1.91e-02 21,850 65.1%
ko 韩语 한국어 년 187 1.35e-02 42,580 59.6%
ku 库尔德语 kurdî li 163 2.34e-02 30,109 82.8%
ky 吉尔吉斯语 кыргызча жана 175 1.78e-02 26,184 77.3%
la 拉丁语 Latina et 152 3.02e-02 41,416 81.4%
lb 卢森堡语 Lëtzebuergesch an 162 2.40e-02 33,684 82.2%
lo 老挝语 ພາສາລາວ ຂອງ 158 2.63e-02 8,165 90.6%
lt 立陶宛语 lietuvių ir 152 3.02e-02 44,180 79.3%
lv 拉脱维亚语 latviešu un 151 3.09e-02 41,008 82.8%
mg 马达加斯加语 Malagasy ny 111 7.76e-02 23,818 80.0%
mk 马其顿语 македонски на 125 5.62e-02 22,246 80.1%
ml 马拉雅拉姆语 മലയാളം ഒരു 191 1.23e-02 19,303 52.5%
mn 蒙古语 монгол нь 162 2.40e-02 23,142 83.1%
mr 马拉地语 मराठी आणि 178 1.66e-02 20,174 75.3%
ms 马来语 Bahasa Melayu yang 154 2.88e-02 26,033 89.9%
mt 马耳他语 Malti l 142 3.80e-02 27,749 90.3%
my 缅甸语 မြန်မာ ကို 163 2.34e-02 8,704 92.2%
nb 书面挪威语 norsk bokmål og 149 3.24e-02 28,715 87.4%
ne 尼泊尔语 नेपाली र 164 2.29e-02 19,634 80.1%
new 尼瓦尔语 नेपाल भाषा thumb 294 1.15e-03 2,894 2.0%
nl 荷兰语 Nederlands de 122 6.03e-02 29,041 84.6%
nn 新挪威语 norsk nynorsk i 140 3.98e-02 31,299 82.1%
no 挪威语 norsk i 143 3.72e-02 36,870 76.3%
nrm 诺曼语 Normaund de 144 3.63e-02 37,834 65.2%
oc 奥克语 occitan de 115 7.08e-02 36,968 84.0%
or 奥里亚语 ଓଡ଼ିଆ ଓ 192 1.20e-02 18,890 81.3%
pa 旁遮普语 ਪੰਜਾਬੀ ਹੈ 156 2.75e-02 15,494 87.4%
pl 波兰语 polski w 141 3.89e-02 44,785 78.6%
pnb 西旁遮普语 پنجابی دے 145 3.55e-02 19,856 83.2%
ps 普什图语 پښتو د 105 8.91e-02 19,349 89.3%
pt 葡萄牙语 português de 127 5.37e-02 30,823 88.7%
ro 罗马尼亚语 română de 133 4.68e-02 36,662 85.3%
ru 俄语 русский в 142 3.80e-02 28,737 73.3%
sd 信德语 سنڌي جي 134 4.57e-02 19,326 88.4%
sh 塞尔维亚-克罗地亚语 srpskohrvatski u 146 3.47e-02 43,563 79.3%
si 僧伽罗语 සිංහල සහ 214 7.24e-03 20,592 78.5%
sk 斯洛伐克语 slovenčina a 152 3.02e-02 44,353 79.9%
sl 斯洛文尼亚语 slovenščina je 149 3.24e-02 43,561 82.4%
so 索马里语 Soomaaliga oo 154 2.88e-02 33,472 88.8%
sq 阿尔巴尼亚语 shqip të 119 6.46e-02 34,083 88.1%
sr 塞尔维亚语 српски је 155 2.82e-02 22,537 59.8%
sv 瑞典语 svenska och 151 3.09e-02 32,738 81.7%
sw 斯瓦希里语 Kiswahili ya 122 6.03e-02 24,555 88.9%
ta 泰米尔语 தமிழ் ஒரு 207 8.51e-03 19,145 61.7%
te 泰卢固语 తెలుగు నుండి 205 8.91e-03 19,393 67.3%
tg 塔吉克语 тоҷикӣ дар 147 3.39e-02 21,633 77.1%
th 泰语 ไทย ที่ 162 2.40e-02 10,648 88.1%
tr 土耳其语 Türkçe ve 156 2.75e-02 43,447 74.3%
tt 塔塔尔语 татарча һәм 193 1.17e-02 12,504 68.5%
ug 维吾尔语 ئۇيغۇرچە ۋە 183 1.48e-02 25,287 76.0%
uk 乌克兰语 українська в 172 1.91e-02 27,817 73.8%
ur 乌尔都语 اردو کے 142 3.80e-02 16,966 89.3%
uz 乌兹别克语 oʻzbekcha va 173 1.86e-02 32,259 54.6%
vi 越南语 Tiếng Việt là 186 1.38e-02 12,420 91.9%
war 瓦瑞语 Winaray nga 123 5.89e-02 23,655 84.0%
yi 意第绪语 ייִדיש די 142 3.80e-02 21,665 85.9%
zh 中文 中文 的 137 4.27e-02 35,707 90.8%
合计 110 种语言 — — — — 2,997,108 —

(榜首词 = 最高频词条,快速确认语种正确。cb = 榜首词 centibel 频段,float = 榜首词 token 占比。词数 = 词表收录词条数。累计覆盖率 = Σ n_b × 10^(-b/100)。)

数据格式

每个文件是 gzip 压缩的 MessagePack 数组,结构为 [header, band_0..band_699]。每个 band 装有词频四舍五入到该 centibel 的词(约 10^(-b/100) token 概率)。

import gzip, msgpack

with gzip.open('data/small_en.msgpack.gz', 'rb') as f:
    obj = msgpack.unpackb(f.read(), raw=False)

header, *bands = obj
# header == {'format': 'cB', 'version': 1, 'lang': 'en',
#            'sources': ['ultrafineweb_l3', 'wikipedia']}

words = [(w, 10 ** (-b / 100)) for b, band in enumerate(bands) for w in band]
# words[0] ≈ ('the', ...) — 英语榜首词

版本历史

  • v7(2026-10-26):自建 pyicu 管线整体重建(单一来源,不再合并 wordfreq)。统一 700 频段,收词门槛 fu_w > 1e-6 且 fu_w / word_bytes > 2e-7。收录规则:合计源头 text_bytes > 100 MB,共 110 语 (剔除 simple 简明英语:维基站点代码,非语言码)。 语言代码采用 ISO 639-3 的 fil(他加禄语/菲律宾语合并为一个代码),不用旧代码 tl。修复 ce、ba、tt、azb、 ug、pnb、sd、arz、skr 的书写系统白名单(此前其非拉丁词被 foreign 全拒, 只剩拉丁残渣)。 跨来源词频合并改用全局体积分母(缺席来源按 0 频计);此前的逐词归一化使小来源 独有词频率虚高(如 bew 词表覆盖率估算达 110%)。
  • v6(合并于 2026-10-26):将 wordfreq v4(42 语)合并入 WordFrequency v5。重叠语种使用 wf_v4 文件 + 元数据,28 个 v5 独有语种保留,th 强制保留 v5 文件,3 个 wf_v4 独有语种恢复(fil、is、sh)。
  • v5(2026-10-26):WordFrequency 自建 pyicu BreakIterator 语料(wiki + ultra + fw2),76 语(阈值 10^-7、700 频段)。
  • v4(2026-10-12):wordfreq v4 (HF) —— 新增 digit_mix、possessive、mark_only、diacritic_single、stroke_single、jamo_single,43 语,累计计数。发布于 https://huggingface.co/datasets/vocabradar/wordfreq。
  • v3(2026-10-10):wordfreq v3 —— 新增 numeric 规则(数字起头代码、中文数字与数字短语)。meta.json 重组为 languages[lang] = {total, removed, kept}。
  • v1-v2:wordfreq 1-2 —— wordfreq 3.0.2 初始 small 列表 + Unicode 文字白名单清洗(foreign、pure_num、no_letter)。

许可证

MIT。

关于 VocabRadar

这项工作是 VocabRadar(词汇雷达)的工作:VocabRadar 浏览器扩展 让你在看视频、刷网页时把还不认识的生词就地标注出来 —— 释义、翻译、双语字幕、注释字幕; 看过的内容还能在 vocabradar.com,自动生成相关习题与游戏,把词真正记住。

Downloads last month
21