---
license: other
language:
- es
- guc
- inb
- kbh
- pbb
task_categories:
- translation
tags:
- machine-translation
- indigenous-languages
- colombia
- low-resource
- wayuunaiki
- inga
- kamentsa
- nasa-yuwe
pretty_name: 'CIL-Dataset: Colombian Indigenous Languages'
size_categories:
- 100K<n<1M
configs:
- config_name: inga
  data_files: inga.csv
- config_name: kamentsa
  data_files: kamentsa.csv
- config_name: nasa_yuwe
  data_files: nasa_yuwe.csv
- config_name: wayuunaiki
  data_files: wayuunaiki.csv
- config_name: wayuunaiki_monolingual
  data_files: wayuunaiki_monolingual.csv
- config_name: wayuunaiki_rephrasing_completo
  data_files:
  - split: train
    path: rephrasing/wayuu_completo_rephrasing_train.csv
  - split: validation
    path: rephrasing/wayuu_completo_rephrasing_dev.csv
  - split: test
    path: rephrasing/wayuu_completo_rephrasing_test.csv
- config_name: wayuunaiki_rephrasing_sin_dict
  data_files:
  - split: train
    path: rephrasing/wayuu_sin_dict_rephrasing_train.csv
  - split: validation
    path: rephrasing/wayuu_sin_dict_rephrasing_dev.csv
  - split: test
    path: rephrasing/wayuu_sin_dict_rephrasing_test.csv
---

# CIL-Dataset: Colombian Indigenous Languages

Parallel and monolingual corpora for machine translation between **Spanish** and
four Colombian Indigenous languages: **Wayuunaiki**, **Inga**, **Kamëntsá** and
**Nasa Yuwe**. Compiled for the thesis *Data-Centric Strategies for Low-Resource
Neural Machine Translation in Colombian Indigenous Languages* (Universidad de los
Andes, FLAG Lab).

## Languages

| Language | Column | ISO 639-3 |
|---|---|---|
| Spanish | `esp` | spa |
| Wayuunaiki | `way` | guc |
| Inga | `ing` | inb |
| Kamëntsá | `kam` | kbh |
| Nasa Yuwe | `nas` | pbb |

## Contents

### Parallel and monolingual corpora

Full corpora, one aligned segment per row.

| Config | File | Rows | Columns |
|---|---|---|---|
| `inga` | `inga.csv` | 4,552 | `esp`, `ing`, `origen` |
| `kamentsa` | `kamentsa.csv` | 281 | `esp`, `kam`, `origen` |
| `nasa_yuwe` | `nasa_yuwe.csv` | 4,031 | `esp`, `nas`, `origen` |
| `wayuunaiki` | `wayuunaiki.csv` | 83,579 | `esp`, `way`, `origen` |
| `wayuunaiki_monolingual` | `wayuunaiki_monolingual.csv` | 2,676 | `way`, `origen` |

The `origen` column is a provenance identifier formatted as
`<language>__<type>_<source>__<year>` (for example
`wayuu__dictionary_negrete_amaya__2021`). Sources include Bible translations,
dictionaries, grammars, constitutional texts, short stories and books.

### Rephrasing subset (Wayuunaiki)

Train/validation/test splits used to study rogue memorization. In the training
split, the Spanish side of biblical rows is replaced by an alternate human Spanish
Bible translation, which reduces repeated Spanish targets. The Wayuunaiki side is
never modified, and validation/test keep the original Spanish.

| Config | Split | Rows |
|---|---|---|
| `wayuunaiki_rephrasing_completo` | train / validation / test | 67,135 / 8,222 / 8,222 |
| `wayuunaiki_rephrasing_sin_dict` | train / validation / test | 7,469 / 763 / 764 |

Extra columns in the rephrasing files: `source_row_id`, `esp_original`,
`esp_target_rephrased`, `verse_id`, `repeat_group_size`, `assigned_version`,
`rephrase_applied`, `rephrase_strategy`.

## Usage

```python
from datasets import load_dataset

# a parallel corpus
inga = load_dataset("Flaglab/CIL-Dataset", "inga")

# the rephrasing splits
reph = load_dataset("Flaglab/CIL-Dataset", "wayuunaiki_rephrasing_completo")
print(reph["train"][0])
```

## Trained models

NLLB-200 fine-tunes built on this data are available in the collection
[Machine Translation for Colombian Indigenous Languages](https://huggingface.co/collections/Flaglab/machine-translation-for-indigenous-language-preservation-6a51849c7b97d28984f9df4d).

## Sources and licensing

The corpora were assembled from heterogeneous materials (Bible translations,
dictionaries, grammars, constitutional texts, community stories and books). These
sources carry their own copyrights and licenses. The dataset is released for
**non-commercial research use**; downstream users are responsible for respecting
the licensing of each underlying source. The rephrasing subset draws Spanish
renderings from public Spanish Bible versions in the BibleNLP/eBible corpus.