Datasets:

tmquan
/

vbpl-vn

@@ -70,46 +70,6 @@ configs:
 | Trung vị đoạn văn · Median paragraphs / doc | 39 |
 | Trung vị câu · Median sentences / doc | 51 |
-## Tổng quan trực quan · Visual overview
-Sáu hình tóm tắt cấu trúc của corpus. Tất cả hình được tạo bằng `plotly` + `kaleido` (Chromium headless) và lưu thành PNG tĩnh để hiển thị trong dataset card. — Six pictures summarising the corpus structure. All figures are rendered with `plotly` + `kaleido` (headless Chromium) and saved as static PNG for the dataset card.
-### Phân bố theo lĩnh vực pháp luật
-![Phân bố theo lĩnh vực pháp luật](./overview-legalarea-treemap.png)
-Top 25 legal areas sized by document count. The pale `Chưa phân loại` ('uncategorised') rectangle covers ~72% on its own -- vbpl.vn editors haven't tagged most legacy docs.
-### Phạm vi → loại văn bản
-![Phạm vi → loại văn bản](./overview-scope-doctype-sunburst.png)
-Two-level radial split: `scope` (inner) → `doc_type` (outer, top 12 per scope). Reveals where the corpus weight sits -- `dia_phuong` (~66%) is mostly `QĐ` (decisions) and `NQ` (resolutions), while `trung_uong` mixes `QĐ` / `NĐ` (decrees) / `TT` (circulars).
-### Top 20 loại văn bản
-![Top 20 loại văn bản](./overview-doctype-bars.png)
-Document types ranked by count, with the canonical short code, full Vietnamese name, and an English gloss.
-### Số văn bản theo năm và phạm vi
-![Số văn bản theo năm và phạm vi](./overview-year-stack.png)
-Stacked area of documents issued per year, split by `scope`. The legacy CMS migration concentrates early years; modern post-2010 output is dominated by `dia_phuong`.
-### Loại văn bản qua các năm
-![Loại văn bản qua các năm](./overview-doctype-year-heatmap.png)
-Top-12 `doc_type` × year heatmap (log₁₀ scale). Shows the shift from `CT` directives in the early 90s to `QĐ` decisions as the workhorse instrument from 2000 onwards.
-### Top 15 cơ quan ban hành
-![Top 15 cơ quan ban hành](./overview-agency-bars.png)
-Top issuing agencies. Quốc hội + Chính phủ + the larger ministries dominate `trung_uong`; provincial People's Councils / Committees split the `dia_phuong` half.
 ## Phạm vi · Scope split
 Bộ dữ liệu chia làm hai nhánh: ``trung_uong`` (văn bản pháp luật do
@@ -325,14 +285,14 @@ The parquet has three families of columns:
 | Field | Type | Description |
 |---|---|---|
-| `markdown` | string | NFC-normalised, modern-orthography Vietnamese markdown (page-segmented with `## Page N` headings when parsed from a PDF). |
 | `num_pages` | int32 | Page count from the parser (PDF/DOCX only). |
 | `num_sections` / `num_paragraphs` / `num_sentences` | int32 | Counts from the structure layer. |
-| `char_len` | int32 | Character length of `markdown`. |
-| `text_hash` | string | SHA-256 first-32 hex of `markdown` (re-run-stable id). |
 | `parser_model` | string | Backend that produced the markdown (`local/pypdf`, `local/markdownify`, `nvidia/nemoretriever-parse`, …). |
 | `parser_runtime` | string | The configured `parser.runtime` (`local` / `nim` / `hybrid`). |
-| `body_source` | string | Which source produced the body: `file` (downloaded PDF/.doc/.docx), `body_html` (API-captured), `shell_html` (Next.js shell fallback). |
 | `parsed_at` | string | ISO 8601 parser timestamp. |
 ### Hierarchy + entities

 | Trung vị đoạn văn · Median paragraphs / doc | 39 |
 | Trung vị câu · Median sentences / doc | 51 |
 ## Phạm vi · Scope split
 Bộ dữ liệu chia làm hai nhánh: ``trung_uong`` (văn bản pháp luật do
 | Field | Type | Description |
 |---|---|---|
+| `markdown` | string | NFC-normalised, modern-orthography Vietnamese markdown (page-segmented with `## Page N` headings when parsed from a PDF). Gateway / Word / Next.js scaffolding is stripped: the `Document Content\\n\\nbody { font-family: ... }\\np { margin: ... }` API preamble (~50 % of bodies), Word `<!-- /* Font Definitions */ @font-face { ... } p.MsoNormal { ... } -->` stylesheet dumps, standalone CSS rule blocks gated by property / selector / structural CSS tells, Ant Design `:where(.css-...){ ... }@keyframes ...{ ... }` chains (`shell_html` docs), orphan selector fragments, and malformed inline `<span lang="..." style="...">` tags. ~90 % of rows lose 1-200 KB of boilerplate; total corpus markdown shrunk by ~1.77 GB / 42 %. `body_source="shell_html"` rows (the Next.js shell fallback) get replaced by a synthesized metadata-only body because no real document text was ever delivered for those URLs. |
 | `num_pages` | int32 | Page count from the parser (PDF/DOCX only). |
 | `num_sections` / `num_paragraphs` / `num_sentences` | int32 | Counts from the structure layer. |
+| `char_len` | int32 | Character length of `markdown` **after** the junk-strip pass (recomputed at export time so consumers can dedupe on the actual shipped body). |
+| `text_hash` | string | SHA-256 first-32 hex of `markdown` **after** the junk-strip pass (re-run-stable id; differs from the upstream `extract.jsonl` hash for any row that had scaffolding removed). |
 | `parser_model` | string | Backend that produced the markdown (`local/pypdf`, `local/markdownify`, `nvidia/nemoretriever-parse`, …). |
 | `parser_runtime` | string | The configured `parser.runtime` (`local` / `nim` / `hybrid`). |
+| `body_source` | string | Which source produced the body: `file` (downloaded PDF/.doc/.docx), `body_html` (API-captured), `shell_html` (Next.js shell fallback -- always carries a synthesized metadata body in the exported `markdown`). |
 | `parsed_at` | string | ISO 8601 parser timestamp. |
 ### Hierarchy + entities