dataset_info:
features:
- name: src_text
dtype: large_string
- name: tgt_text
dtype: large_string
- name: src_lang
dtype: large_string
- name: tgt_lang
dtype: large_string
- name: source
dtype: large_string
splits:
- name: train
num_bytes: 954517359
num_examples: 2967678
download_size: 449761134
dataset_size: 954517359
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
Chagatai / Central-Asian Parallel Corpus
A unified parallel-translation dataset assembled from the sources catalogued in
Datasets_chagatai_final(1) (1).xlsx. Every underlying corpus is normalised to a
single flat schema so it can be loaded and mixed in one line.
Schema
| column | type | description |
|---|---|---|
src_text |
string | segment in the source language |
tgt_text |
string | its translation in the target language |
src_lang |
string | source language code (normalised, see below) |
tgt_lang |
string | target language code (normalised) |
source |
string | which underlying dataset the pair came from |
Language codes are normalised to short ISO-639 forms: ar Arabic, ru Russian,
en English, fa Persian, kk Kazakh, tk Turkmen, tr Turkish, ug Uyghur,
uz Uzbek (Northern/Latin), uzs Uzbek (Southern/Arabic script), azb South
Azerbaijani, chg Chagatai.
Load
from datasets import load_dataset
ds = load_dataset("parquet", data_files="data/chagatai_parallel.parquet")["train"]
# or the Arrow copy written by the build script:
from datasets import load_from_disk
ds = load_from_disk("hf_dataset")
Contents (current build)
Built from every HuggingFace source in the catalog (public + gated, which required a token with granted access) plus the local Chagatai corpora (Eric Schluessel textbook, dictionary, exercises — downloaded from Google Drive). Totals are after cleaning (trim, drop empty/duplicate pairs, strip BOM/zero-width).
24 language pairs · 2,967,678 pairs total.
| language pair | rows | source dataset(s) |
|---|---|---|
| en → ar | 959,928 | sentence-transformers/parallel-sentences-opus-100 |
| kk → tr | 711,658 | liboaccn/nmt-parallel-corpus + issai/kazparc |
| azb → en | 549,604 | Kartal-Ol/en-azb-548k + facebook/flores |
| ar → kk | 346,680 | liboaccn/nmt-parallel-corpus |
| kk → en | 290,875 | issai/kazparc |
| uz → uzs | 37,163 | tahrirchi/lutfiy |
| ar → en | 17,814 | haoranxu/X-ALMA-Parallel-Data + kingkaung/islamqainfo |
| en → fa | 8,579 | aiana94/polynews-parallel |
| kk → ug | 4,499 | liboaccn/nmt-parallel-corpus |
| ug → en | 3,087 | kingkaung/islamqainfo + facebook/flores |
| tr → en | 2,945 | kingkaung/islamqainfo |
| ar → ru | 2,385 | aiana94/polynews-parallel |
| en → uzs | 2,530 | tahrirchi/lutfiy |
| kk → tk | 1,116 | liboaccn/nmt-parallel-corpus |
| Chagatai (chg + chg_latn) | 28,815 | Eric Schluessel textbook / dictionary / exercises |
| chg → kk | 5,076 | textbook + dictionary |
| chg → en | 2,912 | textbook + exercises |
| chg → ru | 2,682 | textbook |
| chg → tr | 2,587 | textbook |
| chg → uz | 2,433 | textbook |
| chg_latn → {en,kk,ru,tr,uz} | 2,904 / 2,542 / 2,681 / 2,574 / 2,424 | textbook + exercises |
| total | 2,967,678 |
chg = Chagatai in Arabic script, chg_latn = Chagatai in Latin transliteration.
See stats.json for the exact per-source / per-pair breakdown of the last build.
The Chagatai loaders read three local files that must sit next to the script (download them from the Google Drive links in the catalog):
Textbook on Chagatai (Eric Schluessel).xlsxЛИНГВИСТЕРГЕ.xlsx(dictionary → Kazakh definitions)Eric_Exercise .xlsx
If they are absent the build simply skips them and logs why.
Not yet included
Dataset_OCR(Chagatai OCR, on institute SharePoint) andoutput_images_clean(images) — not sentence-parallel text, so out of scope for this schema.uy_ts_articles(Uyghur) and the monolingualcis-lmu/GlotSparse,Uyghur-Corpus/Uyghur-Corpus— monolingual, no target side.
Rebuild / extend
pip install datasets pyarrow huggingface_hub pandas
# public sources only:
python build_dataset.py
# include the gated Kazakh sources (after requesting access on each dataset page):
export HF_TOKEN=hf_xxx
python build_dataset.py
The source registry (SOURCES in build_dataset.py) is config-driven — add a
local Chagatai CSV by appending one entry with a small loader function.