LocalDoc/azerbaijani-text-quality-labeled

Azerbaijani Text Quality — Labeled Dataset

249,949 Azerbaijani web documents annotated with a quality score 0-3. Used to train a document-level quality classifier for filtering a web corpus before language-model pretraining.

Source and labeling

• Texts: sampled from LocalDoc/community_oscar_azerbaijani, an OSCAR-derived Common Crawl corpus. The texts are NOT original to this dataset.
• Labels: generated by the LLM Mistral-Small-24B-Instruct-2501, not by humans.

Fields

• index — position of the document in the source stream
• score — quality label, integer 0-3
• text — the document text

Score scale

• 3 — clean, coherent Azerbaijani prose
• 2 — substantial good prose mixed with junk (menus, footers, ads)
• 1 — mostly junk, little recoverable prose
• 0 — pure junk: navigation, spam, machine translation, non-Azerbaijani text

Label distribution

score	count	share
0	25,567	10.2%
1	89,296	35.7%
2	91,393	36.6%
3	43,693	17.5%

Caveats

• Labels are LLM-generated and not verified against human annotation.
• About two thirds of the documents are low quality (score 0-1) — this is expected: junk documents are needed as negative examples for the classifier.
• Texts are raw web crawl and may contain personal data; no PII removal applied.