Update README.md

README.md

@@ -35,4 +35,172 @@ dataset_info:
     num_examples: 756774
   download_size: 34467223
   dataset_size: 116790842
+language:
+- kab
 ---
+
+# tatoeba-kabyle-mono-cleaned
+
+[![Kabyle](https://img.shields.io/badge/lang-kab-blue)](https://en.wikipedia.org/wiki/Kabyle_language)
+[![License](https://img.shields.io/badge/license-CC0--1.0-green)](https://creativecommons.org/publicdomain/zero/1.0/)
+[![Dataset](https://img.shields.io/badge/dataset-HuggingFace-yellow)](https://huggingface.co/datasets/boffire/tatoeba-kabyle-mono-cleaned)
+
+Cleaned and quality-assessed monolingual Kabyle corpus extracted from Tatoeba.
+
+---
+
+## Summary
+
+This dataset contains sentences from Tatoeba tagged as Kabyle (`lang == "kab"`), processed through a multi-layer linguistic filtering pipeline combining **orthographic normalization**, **language identification** (GlotLID v3 + DistilBERT Kabyle/Tachelhit classifier), **code-switching detection** (MaskLID), and **lexical validation** (Kabyle Hunspell dictionary). Only the subset qualified as **pure** is published here.
+
+**Language**: Kabyle (kab) -- standardized Latin script (INALCO 1996 / KIM).  
+**Source**: [Tatoeba sentences.csv](https://downloads.tatoeba.org/exports/sentences.csv)  
+**License**: CC0 1.0 Universal (Tatoeba)  
+**Format**: HuggingFace `datasets` (Arrow)  
+**Author**: [boffire](https://huggingface.co/boffire)
+
+---
+
+## Cleaning Pipeline
+
+### 1. Orthographic Normalization
+- Correction of **character false friends** (Greek, Cyrillic, Turkish, etc.): `ε → ɛ`, `γ → ɣ`, `Γ → Ɣ`, `Σ → Ɛ`, etc.
+- Removal of forbidden characters and normalization of French diacritics.
+- Unicode NFC normalization and whitespace cleanup.
+
+### 2. Berber Validation (DistilBERT)
+- Model: [`boffire/distilbert-kabyle-tachelhit-classifier-v2`](https://huggingface.co/boffire/distilbert-kabyle-tachelhit-classifier-v2)
+- Adaptive thresholds based on sentence length.
+- Classification: `kab` (Kabyle) vs `tach` (Tachelhit).
+- Scope: first 10,000 sentences analyzed; remainder flagged as `SKIPPED`.
+
+### 3. Language Identification (GlotLID v3)
+- Model: `cis-lmu/glotlid`
+- Confidence threshold: **>= 0.95** for the published subset.
+
+### 4. Code-Switching Detection (MaskLID)
+- Token-level analysis combining GlotLID, Kabyle Hunspell (Belkacem77), and an auxiliary vocabulary.
+- Detection of isolated borrowings and IOB2 annotation.
+- CS threshold: > 15% non-Kabyle tokens.
+
+### 5. "Pure" Filter
+The published subset retains only sentences that simultaneously satisfy:
+- `is_cs == False` (no code-switching)
+- `len(contaminants) == 0` (no false friends or forbidden characters)
+- `is_mismatch == False` (no GlotLID=kab / DistilBERT=tach divergence)
+- `berber_status` in `{"HIGH_CONF", "SKIPPED"}`
+- `glot_conf >= 0.95`
+
+---
+
+## Statistics
+
+| Metric | Value |
+|---|---|
+| Source sentences (Tatoeba `lang=kab`) | 789,712 |
+| Retained sentences (**pure** subset) | **756,774** |
+| Conservation rate | **95.8%** |
+| Hunspell coverage (token-level) | **85.1%** (3,173,402 / 3,730,724 tokens) |
+| Code-switching detection rate | **0.24%** (1,915 phrases) |
+| Orthographic contamination rate | **3.66%** (28,887 phrases) |
+| Contaminant types | `faux_ami`: 31,805 / `non_canonique`: 10,092 / `forbidden`: 617 |
+| GlotLID confidence >= 0.95 | **99.7%** (787,561 phrases) |
+| DistilBERT HIGH_CONF (analyzed) | 9,679 / 10,000 |
+| DistilBERT mismatch kab->tach | 67 (0.67% of analyzed) |
+
+---
+
+## Column Structure
+
+| Column | Type | Description |
+|---|---|---|
+| `id` | `string` | Original Tatoeba identifier |
+| `text` | `string` | **Normalized** Kabyle text (use for training) |
+| `raw_text` | `string` | Original raw text (before normalization) |
+| `glot_lang` | `string` | Language predicted by GlotLID v3 |
+| `glot_conf` | `float` | GlotLID confidence score |
+| `berber_label` | `string` | DistilBERT label (`kab` / `tach`) |
+| `berber_score` | `float` | DistilBERT confidence score |
+| `berber_status` | `string` | `HIGH_CONF` / `LOW_CONF` / `REJECT` / `NON_BERBER` / `SKIPPED` |
+| `dominant_lang` | `string` | Dominant language detected by MaskLID |
+| `dominant_ratio` | `float` | Ratio of tokens in the dominant language |
+| `lang_distribution` | `string` | JSON distribution of detected languages (token-level) |
+
+---
+
+## Quick Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("boffire/tatoeba-kabyle-mono-cleaned", split="train")
+
+# Example
+print(ds[0]["text"])
+# -> "Tecfiḍ fell-i ?"
+
+# Iteration
+for example in ds:
+    print(example["text"])
+```
+
+---
+
+## Recommended Use Cases
+
+- **Continued pre-training** of language models (LLM, mT5, etc.)
+- **Fine-tuning** of Kabyle Sentence Transformers
+- **Tokenizer training** for Kabyle-specialized SentencePiece / BPE
+- **Perplexity benchmark** for evaluating the quality of new corpora
+- **Semantic search** (FAISS indexing) and RAG
+
+---
+
+## Known Limitations
+
+1. **Isolated sentence corpus**: Tatoeba provides short utterances without discursive context. For LLM pre-training, this corpus should be complemented with longer documents (Wikipedia, forums, etc.).
+2. **Technical borrowings**: Integrated technical terms in Kabyle (e.g., *aselkim*, *asiggez*) are retained as they belong to the contemporary lexicon. They do not constitute code-switching.
+3. **DistilBERT limited scope**: Only the first 10,000 sentences were validated by DistilBERT; the remainder of the corpus is filtered by GlotLID + MaskLID only.
+4. **Standardized orthography**: Normalization applies the INALCO 1996 / KIM inventory. Non-standard orthographic variants are corrected or discarded.
+
+---
+
+## Related Resources
+
+| Resource | Link |
+|---|---|
+| Full pipeline (script) | *to be published* |
+| Raw Tatoeba dataset | [tatoeba.org](https://tatoeba.org) |
+| Berber classifier | [`distilbert-kabyle-tachelhit-classifier-v2`](https://huggingface.co/boffire/distilbert-kabyle-tachelhit-classifier-v2) |
+| Kabyle T5 tokenizer | [`kabyle-tokenizer-T5`](https://huggingface.co/boffire/kabyle-tokenizer-T5) |
+| Sentence Transformer | [`kabyle-sentence-transformer-mpnet`](https://huggingface.co/boffire/kabyle-sentence-transformer-mpnet) |
+| Hunspell dictionary | [Imseɣti n tira n teqbaylit](https://github.com/Belkacem77/imseti_n_tira_n_teqbaylit) (Belkacem77, MIT) |
+| Kabyle language specifications | [kabyle-specs.github.io](https://kabyle-specs.github.io) |
+
+---
+
+## Citation
+
+If you use this dataset, please cite:
+
+```bibtex
+@dataset{tatoeba_kabyle_mono_cleaned_2026,
+  author = {Mokraoui, Athmane},
+  title = {Tatoeba Kabyle Mono Cleaned},
+  year = {2026},
+  publisher = {HuggingFace},
+  url = {https://huggingface.co/datasets/boffire/tatoeba-kabyle-mono-cleaned}
+}
+```
+
+---
+
+## Changelog
+
+| Version | Date | Change |
+|---|---|---|
+| `1.0.0` | 2026-08-01 | Initial release (756,774 pure sentences) |
+
+---
+
+*Dataset maintained by [boffire](https://huggingface.co/boffire). For questions or contributions, please open an issue on the repository.*