--- 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. > [!TIP] > **Human Readers / 普通读者:** For normal reading, open **[Files and versions -> content](https://huggingface.co/datasets/qurancn/MuslimLife/tree/main/content)** and start with **[content/README.md](https://huggingface.co/datasets/qurancn/MuslimLife/blob/main/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](https://huggingface.co/datasets/qurancn/MuslimLife/blob/main/content/2744-%E8%8E%B1%E9%BA%A6%E4%B8%B9%E4%B8%8D%E5%90%8C%E9%9D%A2%E8%B2%8C%E6%96%8B%E6%9C%88%E4%B8%AD%E7%9A%84%E4%BA%BA%E6%95%85%E4%BA%8B%E4%B8%8E%E4%BF%A1%E4%BB%B0%E7%8E%B0%E5%9C%BA.md)**. For web-style rendering, use **[GitHub Pages](https://salaamalykum.github.io/MuslimLife/)**. ## Dataset Viewer - Articles viewer: https://huggingface.co/datasets/qurancn/MuslimLife/viewer/articles/subset - Retrieval viewer: https://huggingface.co/datasets/qurancn/MuslimLife/viewer/retrieval/subset - Embedding preview: https://huggingface.co/datasets/qurancn/MuslimLife/viewer/embeddings/subset - Embeddable viewer URL: `https://huggingface.co/datasets/qurancn/MuslimLife/embed/viewer/articles/subset` Embed example: ```html ``` 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 ```bibtex @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} } ```