Revert "Mark dataset as coming soon and remove data files"

This reverts commit 21a387e84c52b61c9f88775a2b4e57a88c64bd2a.

README.md

@@ -1,6 +1,5 @@
 ---
 license: cc-by-4.0
-pretty_name: MSQA
 task_categories:
   - question-answering
 language:
@@ -15,22 +14,106 @@ language:
   - ms
   - id
   - es
+pretty_name: MSQA
 size_categories:
   - 1K<n<10K
+configs:
+  - config_name: default
+    data_files:
+      - split: test
+        path: msqa.jsonl
 ---
 
-# MSQA — Coming Soon 🚧
+# MSQA Dataset Card
+
+**MSQA** (Multilingual and Multicultural SimpleQA) is a benchmark of
+**1,064 natively sourced questions** measuring whether large language models
+possess genuine, locally grounded cultural knowledge — as opposed to fluency
+that merely *looks* culturally competent.
+
+Every question was authored or curated from native, in-language sources (not
+translated from English), and each has a single verifiable answer.
+
+## Files
+
+| File | Description |
+|------|-------------|
+| `msqa.jsonl` | The benchmark, one JSON object per line (UTF-8). |
+| `msqa.csv`   | The same data as CSV (UTF-8 with BOM). |
+
+A single split is provided: **`test`** (1,064 items).
+
+## Fields
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `id` | string | Unique item id (prefixed by language, e.g. `PT-01`). |
+| `session_id` | string | Source authoring/session id. |
+| `language` | string | BCP-47-style code, e.g. `pt-PT`, `zh-ZH`, `en-EN`. |
+| `culture_circle` | string | Cultural sphere the item targets (e.g. `Portuguese`, `Latin American`). |
+| `category` | string | One of the five cultural dimensions (see below). |
+| `question` | string | The question, in its native language. |
+| `answer` | string | The single gold answer. |
+| `question_zh` | string | Chinese translation of the question (reference aid; may be empty). |
+| `answer_zh` | string | Chinese translation of the answer (reference aid; may be empty). |
+| `source_url` | string | Primary source URL (may be empty). |
+| `source_url_desc` | string | Short description of the source (may be empty). |
+
+## Composition
+
+**Languages (11):**
 
-**MSQA (Multilingual and Multicultural SimpleQA)** is a benchmark of 1,064
-natively sourced questions spanning 11 language groups and 5 cultural dimensions.
+| Language | Count |   | Language | Count |
+|----------|------:|---|----------|------:|
+| English (`en-EN`)    | 151 | | Japanese (`ja-JP`)    | 83 |
+| Chinese (`zh-ZH`)    | 150 | | Malay (`ms-MY`)       | 82 |
+| Thai (`th-TH`)       | 95  | | Indonesian (`id-ID`)  | 81 |
+| Russian (`ru-RU`)    | 92  | | Spanish (`es-ES`)     | 80 |
+| Korean (`ko-KR`)     | 86  | | Portuguese (`pt-PT`)  | 80 |
+| French (`fr-FR`)     | 84  | | | |
 
-**The dataset is not yet publicly available — it will be released here soon.**
+**Cultural dimensions (5):**
 
-- 📄 Paper: <https://arxiv.org/abs/2607.00724>
-- 💻 Code: <https://github.com/huayuankou333/MSQA>
+| Dimension | Count |
+|-----------|------:|
+| History and Collective Memory | 261 |
+| Language Expression and Communication Arts | 220 |
+| Cultural Products and Symbols | 208 |
+| Beliefs, Values, and Knowledge Systems | 189 |
+| Social Norms and Customs | 186 |
+
+> **Note on difficulty tiers.** The paper discusses three difficulty tiers
+> (Easy/Medium/Hard). This release does not ship a per-item difficulty column; if
+> you need tier labels, refer to the paper's appendix taxonomy.
+
+## Loading
+
+```python
+# From the Hugging Face Hub
+from datasets import load_dataset
+ds = load_dataset("m-a-p/MSQA", split="test")
+
+# From a local file (this repo)
+from msqa.data import load_dataset
+items = load_dataset(path="data/msqa.jsonl", language="pt-PT")
+```
+
+## Provenance
+
+Items were sourced from native-language references (encyclopedias, official
+sources, cultural documentation). `source_url` records the primary source where
+available. The clean release format is produced from the internal workbook by
+[`tools/build_dataset.py`](../tools/build_dataset.py).
+
+## License
+
+Released under **CC BY 4.0**. Individual items reference third-party sources via
+`source_url`; please also respect the terms of those original sources.
 
 ## Citation
 
+Paper: <https://arxiv.org/abs/2607.00724>
+
 ```bibtex
 @misc{chen2026msqanativelysourcedmultilingual,
       title={MSQA: A Natively Sourced Multilingual and Multicultural SimpleQA Benchmark},