Datasets:

LocalDoc
/

azerbaijani-text-quality-labeled

license: cc-by-4.0
language:
  - az
task_categories:
  - text-classification
tags:
  - azerbaijani
  - text-quality
  - data-filtering
size_categories:
  - 100K<n<1M

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.