Add dataset card

README.md

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+---
+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.