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Datasets:
qurancn
/
MuslimLife

Tasks:
Text Retrieval
Question Answering
Text Generation
Modalities:
Tabular
Text
Formats:
parquet
Sub-tasks:
document-retrieval
semantic-similarity-scoring
open-domain-qa
Languages:
Chinese
Size:
< 1K
Tags:
muslim-life
chinese-muslim
islamic-culture
halal-life
muslim-travel
ramadan
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
xet
 Community
MuslimLife / README.md
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Release MuslimLife dataset v1.0.0
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metadata 
license: other
language:
  - zh
size_categories:
  - n<1K
task_categories:
  - text-retrieval
  - question-answering
  - text-generation
  - feature-extraction
task_ids:
  - document-retrieval
  - semantic-similarity-scoring
  - open-domain-qa
  - language-modeling
pretty_name: Muslim Life Knowledge Base & RAG Dataset
tags:
  - muslim-life
  - chinese-muslim
  - islamic-culture
  - halal-life
  - muslim-travel
  - ramadan
  - chinese
  - zh-Hans
  - public-web-archive
  - rag
  - document-retrieval
  - semantic-search
  - knowledge-base
  - parquet
  - dataset-viewer
  - salaamalykum
configs:
  - config_name: articles
    data_files:
      - split: train
        path: data/articles/train-*.parquet
      - split: validation
        path: data/articles/validation-*.parquet
      - split: test
        path: data/articles/test-*.parquet
      - split: subset
        path: data/articles/subset-*.parquet
  - config_name: retrieval
    data_files:
      - split: train
        path: data/retrieval/train-*.parquet
      - split: validation
        path: data/retrieval/validation-*.parquet
      - split: test
        path: data/retrieval/test-*.parquet
      - split: subset
        path: data/retrieval/subset-*.parquet
  - config_name: embeddings
    data_files:
      - split: subset
        path: data/embeddings/subset-*.parquet

Muslim Life Knowledge Base & RAG Dataset

Contains 90 public Simplified Chinese articles from the Salaam Alykum 穆斯林生活 / Muslim Life topic, packaged as a production-ready Hugging Face dataset with Parquet splits, Markdown article files, retrieval rows, metadata indexes, and a lightweight embedding preview layer.

Human Readers / 普通读者： For normal reading, open Files and versions -> content and start with content/README.md. Example article: 2744 莱麦丹不同面貌：斋月中的人、故事与信仰现场. For web-style rendering, use GitHub Pages.

Dataset Viewer

Embed example:

<iframe src="https://huggingface.co/datasets/qurancn/MuslimLife/embed/viewer/articles/subset" width="100%" height="560"></iframe>

The primary machine-readable files are Parquet shards under data/. The first columns are lightweight identifiers, titles, dates, previews, counts, and URLs; full content_text, content_markdown, and retrieval text are intentionally later in the schema to keep the Viewer preview stable and readable.

Splits and configs

Config Split Rows Purpose
articles train 72 Article-level view for training/evaluation experiments with human review.
articles validation 9 Article-level validation slice.
articles test 9 Article-level held-out slice.
articles subset 10 Lightweight preview subset for the Dataset Viewer and demos.
retrieval train 72 RAG/search rows with one retrieval chunk per article.
retrieval validation 9 Retrieval validation slice.
retrieval test 9 Retrieval held-out slice.
retrieval subset 10 Lightweight retrieval preview subset.
embeddings subset 90 Public embedding preview layer using deterministic local character n-gram hashing.

Files

  • data/articles/*.parquet — article-level rows with title, provenance, readable previews, full text, Markdown, hashes, and source URLs.
  • data/retrieval/*.parquet — retrieval/RAG rows optimized for search, citation indexing, and QA experiments.
  • data/embeddings/subset-*.parquet — lightweight embedding preview columns: x, y, embedding_32, and source metadata.
  • content/*.md — human-readable Markdown article files.
  • metadata/article_index.csv and metadata/article_index.jsonl — lightweight index for citation, SQL filtering, and external crawlers.
  • metadata/field_schema.json — exact field names and Parquet types.
  • metadata/release-v1.0.0.json — release manifest.
  • visualizations/embedding_preview.html — static local scatter/table preview generated from the embedding subset.

Field design for SQL/Data Studio

The dataset is shaped as a queryable product, not only a file dump. Common filter fields include article_id, title, language, date_published, year, primary_topic, topic_tags_text, author, char_count, has_media, media_count, source_url, hf_markdown_url, github_pages_url, and content_sha256. Use the Hugging Face Dataset Viewer, Data Studio, or SQL Console to filter by year, topic tag, author, media presence, or source URL.

Format truth

This is an article corpus and RAG/retrieval corpus. It is not a native ShareGPT, Alpaca, chat, or instruction-response dataset. It may be converted into instruction-tuning examples later only if a separate conversion pipeline and new dataset card document that transformation truthfully.

Source and provenance

Source topic: https://salaamalykum.com/cn/topic/%E7%A9%86%E6%96%AF%E6%9E%97%E7%94%9F%E6%B4%BB

Each row includes source traceability through source_url, canonical_url, date_published, date_modified, author, topic_tags, and content_sha256. The GitHub public archive is https://github.com/salaamalykum/MuslimLife and the readable Pages site is https://salaamalykum.github.io/MuslimLife/.

Cleaning and generation rules

  • Records were extracted only from public Salaam Alykum topic/article pages.
  • The live public topic/AJAX listing for this source batch resolves to 90 included article cards. Non-topic navigation/footer links are not counted as topic articles.
  • Article HTML was normalized into Markdown and plain text.
  • Media URLs are kept as public links; media binaries are not republished in this dataset.
  • Raw SQL backups, user tables, passwords, tokens, cookies, sessions, IP logs, private tickets, and server secrets are excluded.
  • Content hashes are SHA-256 values for integrity and deduplication.
  • Parquet shards were written with small row groups and page indexes for stable preview/search behavior.

License and rights

license: other. Article bodies remain source-specific because many posts are translated or reposted public internet material. Do not assume commercial training rights for all article bodies. Generated metadata, schemas, indexes, and packaging files may be reused where the maintainer has rights to license them.

Recommended uses

  • Public-interest search and citation indexing.
  • RAG retrieval experiments with human review.
  • Media monitoring and public-web archival research.
  • Chinese-language Muslim life, halal travel, Ramadan, Islamic culture, and Chinese Muslim community exploration.

Limitations and failure boundaries

  • Small corpus: 90 articles and 90 retrieval chunks.
  • Primary language: Simplified Chinese (zh-Hans).
  • Some source posts are reposted or translated public internet material; always cite original source URLs where possible.
  • This dataset is not a legal claim, not a private database, and not a comprehensive representation of all Muslim-life-related material.
  • Empty or very short source articles are preserved when they existed publicly, with hashes and metadata intact.
  • The embedding preview uses deterministic local character n-gram hashing. It is useful for lightweight visualization and repeatable demos, but it is not a substitute for a production semantic embedding model.

Versioning

Current release: v1.0.0 for source batch v2026.07.30-muslim-life-topic-90. Cite a version tag or commit revision for reproducible downstream work.

Citation 

@dataset{qurancn_muslim_life_2026,
  author    = {Salaamalykum},
  title     = {Muslim Life Knowledge Base & RAG Dataset},
  year      = {2026},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/datasets/qurancn/MuslimLife},
  version   = {v1.0.0}
}