Datasets:

qurancn
/

islamic-articles-corpus

license: cc0-1.0
language:
  - zh
size_categories:
  - n<1K
task_categories:
  - text-generation
  - feature-extraction
tags:
  - islam
  - travel
  - mosques
  - halal
  - raw-corpus
  - rag
pretty_name: Salaamalykum Islamic Articles
configs:
  - config_name: corpus
    data_files:
      - split: train
        path: data/corpus.parquet
  - config_name: rag_chunks
    data_files:
      - split: train
        path: data/rag_chunks.parquet

Salaamalykum Islamic Articles Corpus (Parquet)

This is a highly structured, machine-readable dataset comprising 34 original articles curated from salaamalykum.com. It has been natively formatted in Parquet to support efficient SQL querying in the Hugging Face Dataset Viewer and Data Studio.

Strict Metadata Adherence

Dataset Hygiene: Contains ONLY informational articles. No fake ShareGPT or Alpaca tags are used.
Data Provenance: All articles are authored by Hasan09, tracking Muslim travel guides, mosque histories, and cross-sectarian observations.

Views (Splits)

This repository exposes two subsets via Parquet formatting to prevent TooBigContentError and enable scalable RAG architectures:

1. `corpus` (Full Articles)

Designed for LLM pre-training and long-context analysis.

id: Unique article identifier.
title: Article title.
url: Canonical URL.
word_count: Length of the text for easy filtering in SQL.
tags: Comma-separated categories.
preview: Lightweight summary for UI viewers.
content: The complete Markdown text.

2. `rag_chunks` (Retrieval-Augmented Generation)

Designed for Embedding models, Semantic Search, and Atlas visualizations.

chunk_id: Unique chunk identifier.
text: Specific paragraph.
chunk_index: Position of the paragraph in the original text.

Usage (SQL Console)

You can directly query this dataset via the Hugging Face SQL Console:

SELECT title, url FROM "corpus" WHERE word_count > 1000