| --- |
| license: other |
| license_name: us-government-edict-public-domain |
| task_categories: |
| - image-to-text |
| language: |
| - en |
| tags: |
| - ocr |
| - document-parsing |
| - legal |
| - unlimited-ocr |
| --- |
| |
| # OCR Demo Documents — state court opinions |
|
|
| Public state appellate opinions parsed with |
| [baidu/Unlimited-OCR](https://huggingface.co/baidu/Unlimited-OCR), served on |
| vLLM. Each document is published as the original PDF, the raw model output, |
| the converted HTML, and the PDF's own text layer. |
|
|
| ## Layout |
|
|
| | Path | Contents | |
| |---|---| |
| | `pdf/` | Source PDFs, exactly as downloaded from the court | |
| | `pages/` | Page images fed to the model (PNG, 300 dpi) | |
| | `raw/` | Unmodified model output, including `<\|det\|>` layout markers | |
| | `html/` | Converted HTML — the deliverable | |
| | `text/` | The PDF's embedded text layer, used as ground truth | |
| | `layout/` | One JSON record per block: text plus its position on the page | |
| | `cases/` | Structured case JSON: caption facts, panel, disposition, grounded citations | |
| | `manifest.jsonl` | One row per document: provenance, parameters, scores | |
|
|
| ## Documents |
|
|
| | id | Case | Court | Pages | Text-layer match | |
| |---|---|---|---|---| |
| | `2968s18` | Evans v. Jean-Charles, No. 2968 | Maryland Court of Special Appeals | 4 | 91.95% | |
| | `0260s20` | Johnson v. Secretary of Public Safety, No. 260 | Maryland Court of Special Appeals | 3 | 89.10% | |
| | `CAAP-11-0000713conada` | CAAP-11-0000713 (concurring opinion) | Hawaii Intermediate Court of Appeals | 3 | 99.65% | |
|
|
| ## Method |
|
|
| Pages are rendered at 300 dpi with PyMuPDF, then all pages of a document |
| are sent in a **single** `Multi page parsing.` request — the long-horizon |
| capability the model is named for. Multi-image input puts the model in base |
| mode; `window_size` is 1024 (rather than the single-image 128) and |
| `skip_special_tokens` is false so the layout markers survive. |
|
|
| The `<|det|>` markers are parsed rather than stripped: block categories drive |
| the HTML structure (titles become headings, tables stay tables) and bounding |
| boxes are preserved as `data-bbox` attributes. |
|
|
| ## Text with coordinates |
|
|
| The model grounds every block it emits, so each piece of text can be traced |
| back to where it sits on the page. `layout/<doc_id>.jsonl` carries one record |
| per block with the text, its category, its page number, and its bounding box |
| in four coordinate spaces: |
|
|
| | Field | Space | Matches | |
| |---|---|---| |
| | `bbox_norm` | 0-1000, origin top-left | the model's own output | |
| | `bbox_pt` | PDF points, origin top-left | PyMuPDF, pdfplumber | |
| | `bbox_pt_pdf` | PDF points, origin bottom-left | the PDF specification | |
| | `bbox_px` | pixels at 300 dpi | the rendered page images | |
|
|
| The normalized origin was verified against the PDF text layer rather than |
| assumed: a heading the model reports at 0.306/0.085 of the page is measured |
| by PyMuPDF at 0.312/0.086. |
|
|
| Two limits worth knowing. Granularity is block level — paragraphs, headings, |
| footnotes — not per word or per character. And coverage is not exhaustive: |
| occasional blocks have boxes that stop short of all the text they |
| transcribed, so the text is more complete than the geometry. |
|
|
| ## Structured case data |
|
|
| `cases/<doc_id>.json` is a layout-aware reading of each opinion. Caption |
| facts are taken from the page *geometry* — on a Maryland caption page the |
| left column carries the originating court, the right column carries docket, |
| term, the parties around the standalone "V." block, the panel between the |
| appellee and "JJ.", and the filed date. The extraction covers: |
|
|
| * court, docket number, term, publication status, parties, panel (with |
| senior-judge annotations), opinion type/author, filed date, originating |
| court and case number; |
| * the disposition, found as an indented mostly-uppercase block with an |
| outcome keyword, classified into outcomes and cost allocation; |
| * every case citation, parsed into name / volume / reporter / first page / |
| pinpoint / year, with parallel citations grouped, signals (See, Cf.) and |
| trailing parentheticals captured; |
| * rule and statute citations (Md. Rules, HRS §§, Code articles). |
|
|
| Every extracted property carries a `grounding` object — page, block index, |
| and bounding box (plus character offsets for citations) — so each fact can |
| be traced to the exact place on the page it was read from. |
|
|
| This extraction is **heuristic**: it was built and verified against state |
| appellate opinions of this shape. On the three documents here it recovers |
| 12/12 case citations with names and years; fields it cannot find are null |
| rather than guessed. OCR misreads pass through verbatim by design (e.g. a |
| reporter rendered as `Hawaii'`), so the JSON reflects what the model read, |
| not a cleaned-up ideal. |
|
|
| ## On the accuracy numbers |
|
|
| These opinions are **born-digital** PDFs with real embedded text, which is |
| why a text-layer match score is available at all — it is a genuine |
| character-level comparison, not an estimate. It also means they are an easy |
| OCR target: they validate the pipeline end to end, but they do not |
| demonstrate performance on scanned or degraded documents. |
|
|
| ## Licensing |
|
|
| US state court opinions are government edicts and are not subject to |
| copyright. The pipeline that produced the derived files lives in the |
| accompanying demo repository. |
|
|
