| --- |
| license: cc-by-sa-4.0 |
| language: |
| - ba |
| - ru |
| pretty_name: Bashkir-Russian Wikipedia Parallel Corpus |
| task_categories: |
| - translation |
| configs: |
| - config_name: cleaned |
| data_files: |
| - split: train |
| path: cleaned/data.parquet |
| - config_name: precleaned |
| data_files: |
| - split: train |
| path: precleaned/data.parquet |
| - config_name: scored |
| data_files: |
| - split: train |
| path: scored/data.parquet |
| - config_name: filtered |
| data_files: |
| - split: train |
| path: filtered/data.parquet |
| tags: |
| - bashkir |
| - russian |
| - wikipedia |
| - cyrillic |
| - low-resource |
| - parallel-corpus |
| - sentence-level |
| - bitext-mining |
| --- |
| |
| # Bashkir-Russian Wikipedia Parallel Corpus |
|
|
| Sentence-level Bashkir-Russian parallel data extracted from the Bashkir and |
| Russian Wikipedia dumps dated `2026-08-01`. |
|
|
| This repository provides four configurations. The default `cleaned` |
| configuration is recommended for machine translation training. The |
| `precleaned` configuration is an earlier, less filtered extraction provided |
| for alternative preprocessing and research. The `scored` configuration adds |
| LASER-based quality scores to the `cleaned` pairs. The `filtered` |
| configuration applies a conservative two-encoder filter on top of `scored`. |
|
|
| ## Configurations |
|
|
| ### cleaned |
|
|
| - 72,007 sentence pairs |
| - 34,566 linked article pairs |
| - URLs, MediaWiki markup, card fragments and malformed punctuation removed |
| - duplicate and identical pairs removed |
| - sentence indices retained |
|
|
| Fields: |
|
|
| - `ba_title`: Bashkir Wikipedia article title |
| - `ru_title`: Russian Wikipedia article title |
| - `section`: `lead` or `facts` |
| - `ba`: Bashkir sentence |
| - `ru`: Russian sentence |
| - `ba_sentence_index`: sentence index in the Bashkir article |
| - `ru_sentence_index`: sentence index in the Russian article |
|
|
| ### precleaned |
|
|
| - 91,949 sentence pairs |
| - earlier extraction with lighter filtering |
| - contains older Wiki markup, links and alignment noise |
|
|
| Fields: |
|
|
| - `ba_title`, `ru_title`, `section`, `ba`, `ru` |
|
|
| ### scored |
|
|
| - 72,007 sentence pairs — **identical rows to `cleaned`**, nothing added or removed |
| - quality scores computed with Meta LASER sentence embeddings: |
| - `laser_cos`: cosine similarity between LASER embeddings of the pair |
| - `laser_margin`: margin normalized by same-language kNN density |
| - `laser_margin_xling`: margin normalized by **cross-lingual** kNN density |
| (Artetxe & Schwenk, 2018) — the recommended LASER filter score |
| |
| Encoders: LASER3 `bak_Cyrl` (NLLB) for Bashkir, LASER2 for Russian, |
| 1024-dim L2-normalized embeddings, k=4 neighbours |
| (`laser_encoders`, facebookresearch/LASER). |
|
|
| ### filtered |
|
|
| - **69,706 sentence pairs** (−3.20% from `scored`) |
| - conservative two-encoder filter: a pair is removed only when **both** |
| scorers place it in their bottom 5%: |
| `laser_margin_xling < 0.876 AND labse_margin_xling < 0.723` |
| - second encoder: **LaBSE** (Google, 481M parameters, fp16) — independent |
| architecture and training data, so its errors are largely uncorrelated |
| with LASER's |
| - all score columns retained: `laser_cos`, `laser_margin`, |
| `laser_margin_xling`, `labse_cos`, `labse_margin_xling` |
| - removed pairs are dominated by template mismatch sentences (river-tributary |
| stubs with different facts) and cross-article topic matches |
|
|
| Score distributions over the full 72,007 pairs: |
|
|
| | score | p01 | p05 | p25 | p50 | p75 | p95 | p99 | |
| |---|---|---|---|---|---|---|---| |
| | `laser_cos` | 0.597 | 0.705 | 0.828 | 0.863 | 0.887 | 0.914 | 0.928 | |
| | `laser_margin_xling` | 0.760 | 0.876 | 0.988 | 1.033 | 1.063 | 1.102 | 1.129 | |
| | `labse_cos` | 0.206 | 0.408 | 0.698 | 0.789 | 0.859 | 0.932 | 0.963 | |
| | `labse_margin_xling` | 0.373 | 0.723 | 1.035 | 1.132 | 1.202 | 1.295 | 1.358 | |
|
|
| ## Source and Processing |
|
|
| The data was extracted from corresponding Bashkir and Russian Wikipedia |
| articles using the `bawiki-20260801` and `ruwiki-20260801` dumps. |
|
|
| The cleaned configuration uses article-local sentence indices, numeric |
| anchors for factual pairs, length-ratio checks, language checks, duplicate |
| removal and service-fragment filtering. The `scored` and `filtered` |
| configurations add multilingual sentence-embedding scoring on top of the |
| same alignment without modifying any text. |
|
|
| ## License |
|
|
| The source text is derived from Wikipedia and is distributed under the |
| [Creative Commons Attribution-ShareAlike 4.0 International license](https://creativecommons.org/licenses/by-sa/4.0/). |
|
|
| Please preserve Wikipedia attribution when redistributing or publishing |
| derivative datasets. |
|
|
| ## Loading |
|
|
| ```python |
| from datasets import load_dataset |
| |
| cleaned = load_dataset("failed09/bashkir-wikipedia-parallel", "cleaned") |
| scored = load_dataset("failed09/bashkir-wikipedia-parallel", "scored") |
| filtered = load_dataset("failed09/bashkir-wikipedia-parallel", "filtered") |
| |
| # strict MT-training subset with your own threshold |
| df = scored["train"].to_pandas() |
| strict = df[(df.laser_margin_xling >= 0.90) & (df.labse_margin_xling >= 1.0)] |
| ``` |
|
|
| ## Citation |
|
|
| ```bibtex |
| @dataset{failed09_bashkir_russian_wikipedia_parallel_2026, |
| title = {Bashkir-Russian Wikipedia Parallel Corpus}, |
| author = {failed09}, |
| year = {2026}, |
| publisher = {Hugging Face}, |
| url = {https://huggingface.co/datasets/failed09/bashkir-wikipedia-parallel} |
| } |
| ``` |
|
|
