README.md

---
license: cc-by-sa-4.0
language:
  - so
size_categories:
  - 100K<n<1M
task_categories:
  - text-generation
  - fill-mask
pretty_name: SomaliWeb v1
configs:
  - config_name: default
    data_files:
      - split: train
        path: "train-*.parquet"
      - split: validation
        path: validation.parquet
tags:
  - somali
  - low-resource
  - pretraining
  - web-corpus
  - deduplicated
  - quality-filtered
  - arxiv:2605.18232
---

# SomaliWeb v1 — Quality-filtered Somali web corpus

[![arXiv](https://img.shields.io/badge/arXiv-2605.18232-b31b1b.svg)](https://arxiv.org/abs/2605.18232)
[![Code](https://img.shields.io/badge/Code-GitHub-181717.svg?logo=github)](https://github.com/khaledyusuf44/somali-corpus)

**📄 Paper:** [arXiv:2605.18232](https://arxiv.org/abs/2605.18232) — *SomaliWeb v1: A Quality-Filtered Somali Web Corpus with a Matched Tokenizer and a Public Language-Identification Benchmark*

**💻 Construction pipeline (MIT):** [github.com/khaledyusuf44/somali-corpus](https://github.com/khaledyusuf44/somali-corpus)

**SomaliWeb v1** is a cleaned, deduplicated, and quality-filtered Somali-language web corpus of **~303 million tokens** (819,322 documents), built by aggregating three public Somali-heavy web distributions (HPLT v2, CC100, Somali Wikipedia) and passing them through a reproducible six-stage pipeline.

This is, to our knowledge, the first dedicated and versioned Somali-only pretraining corpus released on Hugging Face with a complete dataset card, a matched tokenizer, and a public language-identification benchmark. The full audit-trail, equations, and findings are documented in the companion paper ([arXiv:2605.18232](https://arxiv.org/abs/2605.18232)).

## Dataset summary

- **Language**: Somali (Standard Somali, Latin script). No Maay Maay detected in the final distribution.
- **Token count**: ~303M approximate tokens (`words × 1.3`), **233M whitespace-separated words**.
- **Document count**: 819,322 (train: 778,355 · validation: 40,967, 95/5 split).
- **Script**: Latin.
- **Period of source content**: ~2019–2024, inherited from HPLT v2 and CC100.
- **License**: CC-BY-SA 4.0 (see Licensing below; sources have compatible terms).

## Why this dataset

Somali is a low-resource language with ~25 million speakers worldwide. Existing Somali text appears *inside* multilingual dumps (HPLT, CC100, mC4, OSCAR) but no standalone, named, versioned Somali pretraining corpus has been published with a documented construction pipeline. SomaliWeb v1 fills that gap and ships with:

- A reproducible pipeline anyone can re-run and audit.
- A comparison baseline tokenizer trained on HPLT-raw, released alongside.
- An evaluation against FLORES-200 Somali showing measurable fertility improvements over general-purpose tokenizers.

## Dataset structure

### Data fields

Each row in the train shards (`train-*.parquet`) and `validation.parquet` has the schema:

- `id` (string): source-prefixed unique identifier (e.g. `hplt2-so_12345`).
- `text` (string): the document body, cleaned and length-filtered.
- `source` (string): one of `hplt2-so`, `cc100-so`, `wikipedia-so`.
- `n_words` (int): whitespace-separated word count after cleaning.
- `quality_score` (float): Phase-5 quality score (0–1, higher = cleaner Somali).
- `lang_conf` (float): langdetect top-1 confidence for Somali.
- `dialect_tag` (string, optional): GlotLID v3 dialect tag (almost always `som_Latn`).

### Data splits

| Split | Documents | Approx tokens |
|---|---:|---:|
| `train` (95%) | 778,355 | ~288M |
| `validation` (5%) | 40,967 | ~15M |

### Source composition (of the combined train + validation)

| Source | Documents | Fraction |
|---|---:|---:|
| HPLT v2 `som_Latn` | 582,257 | 71.07% |
| CC100-so (statmt.org) | 233,394 | 28.49% |
| Somali Wikipedia (dump 2023-11-01) | 3,671 | 0.45% |

## Construction pipeline

Full details + intermediate metrics in the companion GitHub repository's `reports/` directory. The pipeline is six phases:

1. **Merge + byte-exact dedup.** Combine the three sources under a unified schema; drop documents whose SHA-256 of `lowercase(whitespace-collapsed(text))` is already seen (first-seen wins). Removed **189,692 duplicates (13.83%)**, of which **166,628 (17.3%) came from within HPLT v2's own "cleaned" distribution**, demonstrating that HPLT's dedup is not byte-exact.

2. **Clean + normalize.** Mojibake fix via `ftfy`, whitespace collapse, repeated-char-run collapse, minimum-length filter (≥ 50 words). **ftfy fixed mojibake in 615,314 documents (52.04% of input)** — notably **56.1% of HPLT v2's documents** contained fixable encoding artifacts.

3. **LID verification.** `langdetect` (seeded) on every surviving document; keep only top-1 = `so` with confidence ≥ 0.50. Drop rate 0.21% — HPLT/CC100 already LID-filtered solidly. GlotLID v3 second pass tagged dialect: `som_Latn` 99.96%, `ymm_Latn` (Maay Maay) 0.00%.

4. **MinHash near-duplicate detection.** Word-3-gram shingles hashed inline to 31-bit ints, 64 MinHash signatures, (16, 4) LSH banding (`s* ≈ 0.50`), τ = 0.80 Jaccard verification, union-find clustering, `keep-longest` rule. Removed **113,896 near-duplicates (10.57%)**. Largest cluster: 75 copies of one article — HPLT missed it.

5. **Quality filter.** Character 5-gram coverage against a clean Somali Wikipedia seed (2,221 articles ≥ 200 words, 828K unique 5-grams). Dropped bottom 15% by coverage score (threshold 0.9029). Filter catches template-like listings and encoding-degraded content; a known false-positive rate applies to news with heavy proper-noun density.

6. **Release structuring.** Shuffled (seed 0), 95/5 train/val split, metadata consolidated.

## Evaluation

### Tokenizer fertility on FLORES-200 Somali devtest (1,012 held-out sentences)

| Tokenizer | Training corpus | Vocab | Tokens | Fertility ↓ |
|---|---|---:|---:|---:|
| **SomaliWeb-v1** (this dataset) | 350M tokens (cleaned) | 16K | 35,867 | **1.538** |
| HPLT-raw | 505M tokens (raw HPLT v2) | 16K | 35,854 | 1.537 |
| GPT-4 `cl100k_base` | proprietary | 100K | 60,010 | 2.573 |

**Two results:**

- SomaliWeb v1 matches HPLT-raw's tokenizer fertility at 30% smaller training corpus — our dedup + quality filter preserves tokenizer quality.
- SomaliWeb v1's tokenizer is **40.2% more token-efficient than GPT-4's `cl100k_base`** on Somali text. The "tokenization tax" that penalizes low-resource languages is concretely measurable here.

The companion tokenizer is published alongside as `tokenizer_somaliweb.json` (HF tokenizers JSON format).

## Limitations and considerations

- **Source inheritance.** The upstream sources (HPLT v2, CC100, Somali Wikipedia) each have their own coverage biases. HPLT and CC100 are CC-derived and therefore dominated by whatever Somali content happened to be on the public web during ~2019–2024.
- **No Maay Maay.** GlotLID v3 tagged 0 documents as `ymm_Latn` in the final distribution. Either the upstream distributions filtered it out, or GlotLID undercounts Maay on web text — either way, this corpus should be described as **Standard Somali only**. Future versions should source Maay Maay content separately.
- **Quality filter false positives.** The char-5-gram filter can drop real news articles heavy in proper nouns because the seed is predominantly Wikipedia encyclopedic prose. v2 should use a mixture seed or a trained classifier.
- **Known encoding artifacts caught, not created.** 52% of docs had mojibake fixed by `ftfy`. We did not find evidence of residual mojibake, but this hasn't been exhaustively audited.
- **Dialect scope.** Standard Somali only.
- **PII.** We did not run a dedicated PII-removal pass. Upstream sources may retain names, phone numbers, or emails embedded in news content. Empirical scan of the released splits: **~7.9% of documents contain at least one email-shaped string** (mostly newsroom contact addresses such as `editor@…`, `support@…`, but also occasional personal `gmail.com` / `hotmail.com` addresses). Presidio does not cover Somali; a Somali-specific PII filter is planned for v2. **Users building consumer-facing applications must apply additional PII handling.**
- **Copyright.** Sources are public web documents. Somali news sites are the largest contributors via HPLT/CC100. Users should consider downstream licensing obligations for their specific use case.
- **Bias.** The corpus inherits any biases of the upstream crawls — the Somali internet skews toward diaspora, news, politics, and religion. Under-represented registers include conversational speech, technical writing, and long-form fiction.

## Usage

### Load with `datasets`

```python
from datasets import load_dataset

ds = load_dataset("khaledyusuf44/somaliweb-v1")
print(ds)
# DatasetDict({'train': Dataset(num_rows=778355), 'validation': Dataset(num_rows=40967)})

sample = ds["train"][0]
# {'id': 'hplt2-so_12345', 'text': '...', 'source': 'hplt2-so', ...}
```

### Load the companion tokenizer

```python
from tokenizers import Tokenizer
tok = Tokenizer.from_file("tokenizer_somaliweb.json")
print(tok.encode("Soomaaliya waa dal ku yaal geeska Afrika.").ids)
```

### Intended uses

- Somali LLM pretraining (the primary use case).
- Somali tokenizer training and evaluation.
- Low-resource NLP research.
- Somali downstream task fine-tuning (classification, NER, translation) — as a base for domain adaptation.

### Out-of-scope uses

- **Consumer-facing applications without additional PII filtering.**
- **Claims of representing all Somali dialects.** This corpus is Standard Somali only.
- **Evaluation tasks that require contamination control.** Source documents predate construction and may overlap with FLORES-200 or other public Somali evaluation sets. We recommend a contamination audit before using this corpus to train models you intend to evaluate on those benchmarks.

## Dataset Curators

Khalid Yusuf Dahir (`khaledyusuf44` on GitHub and Hugging Face).

## Licensing

Released under **CC-BY-SA 4.0**, inheriting the most restrictive license among the upstream sources:

- HPLT v2: CC0 (permissive).
- CC100: public domain / MIT-like (permissive).
- Somali Wikipedia: CC-BY-SA 3.0 (requires attribution + share-alike).

Users of SomaliWeb v1 must honor CC-BY-SA 4.0 (attribution + share-alike). Citations appreciated.

## Citation

If you use SomaliWeb v1, the matched tokenizer, the LID benchmark, or the construction pipeline, please cite the companion paper:

```bibtex
@article{dahir2026somaliweb,
  title         = {SomaliWeb v1: A Quality-Filtered Somali Web Corpus with a Matched Tokenizer and a Public Language-Identification Benchmark},
  author        = {Dahir, Khalid Yusuf},
  year          = {2026},
  eprint        = {2605.18232},
  archivePrefix = {arXiv},
  primaryClass  = {cs.CL},
  url           = {https://arxiv.org/abs/2605.18232}
}
```

## Acknowledgments

This dataset builds on:

- **HPLT v2** (University of Helsinki / Turku / Edinburgh consortium) — the primary CC-derived source.
- **CC100** (Wenzek et al., 2020) — the secondary CC-derived source distributed via statmt.org.
- **Somali Wikipedia** contributors — the clean anchor and quality-filter seed.
- **Common Crawl** — the underlying web archive all three upstream corpora were built from.
- **FLORES-200** (NLLB Team et al., 2022) — held-out evaluation set.
- **GlotLID** (Kargaran et al., 2023) — dialect tagging.

## Changelog

- **v1.0** (2026-04-23): Initial release.
- **v1.0.1** (2026-05-19): Added arXiv:2605.18232 paper citation and reference.