diff --git a/.gitattributes b/.gitattributes index bed0738c7eeb449bca98b5d2f33c89a1ee56349a..3cbfb425747983f5310785b00b8edb29c0c6e7f3 100644 --- a/.gitattributes +++ b/.gitattributes @@ -58,3 +58,25 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text # Video files - compressed *.mp4 filter=lfs diff=lfs merge=lfs -text *.webm filter=lfs diff=lfs merge=lfs -text +documents/4kVtTRoL.pdf filter=lfs diff=lfs merge=lfs -text +documents/97uZroyv.pdf filter=lfs diff=lfs merge=lfs -text +documents/BnftpXVQ.pdf filter=lfs diff=lfs merge=lfs -text +documents/DtfW60lS.pdf filter=lfs diff=lfs merge=lfs -text +documents/Eet2wW3x.pdf filter=lfs diff=lfs merge=lfs -text +documents/GW7i2xbM.pdf filter=lfs diff=lfs merge=lfs -text +documents/IPm0MkgQ.pdf filter=lfs diff=lfs merge=lfs -text +documents/J6buHXQ4.pdf filter=lfs diff=lfs merge=lfs -text +documents/KpewWz3R.pdf filter=lfs diff=lfs merge=lfs -text +documents/NNaGgwE5.pdf filter=lfs diff=lfs merge=lfs -text +documents/NlWTPen5.pdf filter=lfs diff=lfs merge=lfs -text +documents/PSU5pciM.pdf filter=lfs diff=lfs merge=lfs -text +documents/SkD8Lz8o.pdf filter=lfs diff=lfs merge=lfs -text +documents/UnG6cLfP.pdf filter=lfs diff=lfs merge=lfs -text +documents/WnxX1Buq.pdf filter=lfs diff=lfs merge=lfs -text +documents/XhJyv5mb.pdf filter=lfs diff=lfs merge=lfs -text +documents/bjBNmyNw.pdf filter=lfs diff=lfs merge=lfs -text +documents/phovuuuk.pdf filter=lfs diff=lfs merge=lfs -text +documents/qQUPWQNA.pdf filter=lfs diff=lfs merge=lfs -text +documents/qoSTXgNE.pdf filter=lfs diff=lfs merge=lfs -text +documents/tLFa76nQ.pdf filter=lfs diff=lfs merge=lfs -text +documents/yTRFKVPx.pdf filter=lfs diff=lfs merge=lfs -text diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..4d51bf5c2fa8e216d51f4bd6f83d684b868a04d9 --- /dev/null +++ b/.gitignore @@ -0,0 +1,10 @@ +__pycache__/ +*.pyc +*.egg-info/ +.pytest_cache/ +.ruff_cache/ +.env +venv/ +.venv/ +.DS_Store +.idea \ No newline at end of file diff --git a/CITATION.cff b/CITATION.cff new file mode 100644 index 0000000000000000000000000000000000000000..bdcc0a75738122e7c879b509c4d158a37a65e5e4 --- /dev/null +++ b/CITATION.cff @@ -0,0 +1,19 @@ +cff-version: 1.2.0 +title: "DocuBench" +message: "If you use DocuBench, please cite this repository." +type: dataset +authors: + - family-names: "Merhav" + given-names: "Uri" + - family-names: "Dean" + given-names: "Nitai" +repository-code: "https://github.com/DocuPipe/docubench" +abstract: "A public benchmark for schema-guided structured extraction from real-world documents." +keywords: + - document extraction + - structured extraction + - benchmark + - JSON Schema +license: MIT +version: "0.1.0" +date-released: "2026-06-26" diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md new file mode 100644 index 0000000000000000000000000000000000000000..489a3bd337824837797b5d1cd40f94cd3e552ceb --- /dev/null +++ b/CONTRIBUTING.md @@ -0,0 +1,49 @@ +# Contributing + +DocuBench is intended to be reproducible benchmark infrastructure. Contributions should preserve that property. + +## Development Setup + +```bash +python3 -m venv .venv +source .venv/bin/activate +python3 -m pip install -e ".[dev]" +``` + +## Checks + +Run these before opening a pull request: + +```bash +docubench validate +docubench score +pytest +``` + +## Result Submissions + +Add new system outputs under `results//`. Each `.json` file should include a top-level `data` object. See [`docs/submissions.md`](docs/submissions.md). + +If your system uses a prompt or run configuration, commit it under [`prompts/`](prompts) alongside the existing baselines so the result set is reproducible and auditable. + +## Leaderboard Data + +The Hugging Face Space in [`space/`](space) renders `space/leaderboard.json`. After changing results or labels, refresh it so the leaderboard stays in sync: + +```bash +docubench report +python3 space/build_data.py +``` + +`tests/test_space.py` fails if the committed `space/leaderboard.json` is stale. + +## Dataset Changes + +Changes to documents, schemas, labels, or scoring behavior can change benchmark meaning. Include: + +- the reason for the change +- affected document IDs +- before/after scoring impact if applicable +- source and license details for any new document + +Scoring changes should be treated as benchmark-version changes. diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..238ad7a5f10cfa59e9b04484c826a793529fb2bb --- /dev/null +++ b/LICENSE @@ -0,0 +1,38 @@ +MIT License + +Copyright (c) 2026 DocuPipe + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + +--- + +NOTE ON NON-CODE CONTENT + +The MIT license above applies to the CODE in this repository (scorer.py and the +scripts/ directory). + +- The ground-truth labels (labels/), the JSON schemas (schemas/), and the + extraction results (results/) are released under Creative Commons Attribution + 4.0 International (CC BY 4.0). + +- The benchmark DOCUMENTS in documents/ each retain their own license. Every + document's original public source and license are listed in SOURCES.md. They + are included for research and evaluation; some are public-domain or openly + licensed, some are vendor sample documents that carry third-party copyright. + If you are a rights-holder and want a document removed, open an issue. diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..23582f1f719577eda68d1ba97cc037f5e867114b --- /dev/null +++ b/README.md @@ -0,0 +1,92 @@ +--- +pretty_name: DocuBench +license: cc-by-4.0 +task_categories: + - document-question-answering +language: + - en + - he + - ja + - zh + - ar + - fr + - de + - pt + - nl + - it + - es +tags: + - benchmark + - document-ai + - information-extraction + - structured-extraction + - key-information-extraction + - ocr + - document-understanding +size_categories: + - n<1K +--- + +# DocuBench + +A public benchmark for schema-guided structured extraction from 50 hard, real-world documents. + +Each example contains a source document, a JSON Schema, and a hand-verified JSON label. The task is to extract the labeled structured data from the document according to the schema. Scoring is macro-average field accuracy with order-independent array matching, computed by an open standalone scorer. + +Canonical repo, scorer, and raw baseline outputs: https://github.com/DocuPipe/DocuBench + +## Leaderboard + +Committed baselines, scored by the public scorer against the hand-verified labels: + +| Rank | System | Accuracy | +|---:|---|---:| +| 1 | DocuPipe (high effort) | 97.56% | +| 2 | DocuPipe (standard effort) | 96.31% | +| 3 | Gemini | 95.80% | +| 4 | GPT | 93.54% | +| 5 | Extend | 91.11% | +| 6 | Claude | 90.33% | + +DocuPipe built this benchmark. Every system, including DocuPipe, is scored by the same open scorer against the same labels, with identical schemas, and every raw model output is committed under `results/` in the GitHub repo so the table is reproducible. + +## Composition + +- 50 documents, 50 schemas, 50 hand-verified labels +- 10 file types: PDF, JPEG, PNG, TIFF, XLSX, CSV, XML, TXT, DOCX, HTML +- 11 languages/scripts: English, Hebrew, Japanese, Chinese, Arabic, French, German, Portuguese, Dutch, Italian, Spanish +- Failure modes covered: line-item arrays, multi-page tables, reconciling totals, right-to-left and CJK scripts, rotated scans, handwriting, nested objects, needle-in-haystack lookups + +Documents cover invoices, bank and brokerage statements, utility bills, annual reports, payslips, purchase orders, waybills, lab reports, discharge summaries, engineering drawings, insurance declarations, tax forms, spreadsheets, XML, CSV, text, and HTML. + +## Motivation + +Many document extraction evaluations focus on single-page, flat, or QA-style tasks. DocuBench focuses on end-to-end structured extraction into realistic JSON shapes, including arrays, nested objects, multipage context, non-Latin scripts, and non-PDF inputs. + +## Collection and labeling + +Documents were selected from public sources, vendor sample documents, government publications, open datasets, and benchmark-authored synthetic files. Each document has a source and license record in `SOURCES.md` and `sources.json` in the GitHub repo. Labels were authored for the benchmark and manually checked field by field against the source document. + +## Intended uses + +- Evaluating document extraction systems +- Testing schema-guided extraction robustness +- Comparing parser or extraction workflows on public artifacts +- Regression testing extraction systems across file types and languages + +## Out-of-scope uses + +- Training models on the test labels +- Claiming broad document AI superiority from the headline aggregate alone +- Evaluating privacy handling, security, or compliance controls +- Treating these 50 documents as representative of all enterprise documents + +## Licensing + +- Code is MIT licensed. +- Labels, schemas, benchmark-authored metadata, and benchmark-authored results are CC BY 4.0 unless stated otherwise. +- Source documents retain their original licenses or publication basis. + +## Citation + +If you use DocuBench, cite the GitHub repository: https://github.com/DocuPipe/DocuBench diff --git a/SOURCES.md b/SOURCES.md new file mode 100644 index 0000000000000000000000000000000000000000..c0e5ff6b1e50f350956fab12d3caf8f0ff9874cf --- /dev/null +++ b/SOURCES.md @@ -0,0 +1,58 @@ +# Document sources and licensing + +All 50 benchmark documents are included in this repository under `documents/.`. The table below records each document's original public source and license so provenance is fully traceable. + +Most documents are public-domain government/SEC filings, openly-licensed files (CC BY-SA, Apache, MIT), vendor sample documents published for distribution, or files we authored for this benchmark (released CC BY 4.0). A few are vendor sample forms that carry their own third-party copyright; they are included here for research and evaluation, and the rights-holder is named in the license column. If you are a rights-holder and want a document removed, open an issue. + +| # | doc_id | Document | Pages | Lang | Type | Original source | License / basis | +|---|---|---|---|---|---|---|---| +| 1 | `yTRFKVPx` | Smartsheet Construction Invoice | 4 | en | pdf | [link](https://www.smartsheet.com/sites/default/files/2021-11/IC-Free-Printable-Construction-Invoice-11215_PDF.pdf) | vendor free template (publicly posted) | +| 2 | `IPm0MkgQ` | Carson Bank Sample Statement | 6 | en | pdf | [link](https://www.carsonbank.com/wp-content/uploads/2021/01/Sample-Statement.pdf) | vendor sample (dummy data) | +| 3 | `ZXlksSpk` | Getbuildingworks BOQ Summary | 1 | en | pdf | [link](https://getbuildingworks.com/wp-content/uploads/2018/01/Bill-of-Quantities-Work-Section.pdf) | publicly posted sample | +| 4 | `QxoQ6zgn` | UICCP Packing List Carton Dimensions | 1 | en | pdf | [link](https://uiccp.com/wp-content/uploads/2014/06/Copy-of-OCM.pdf) | vendor spec sheet (publicly posted) | +| 5 | `PSU5pciM` | CPS Energy Electric Bill | 2 | en | pdf | [link](https://www.cpsenergy.com/content/dam/corporate/en/Documents/RAC/CustomerBills/Bill%20Sample%20-%20RA%20Rate%20-%20Non-Summer%20%20Redacted.pdf) | utility-published redacted sample | +| 6 | `NlWTPen5` | PPL Electric Two Bill Example | 3 | en | pdf | [link](https://www.pplelectric.com/-/media/PPLElectric/At-Your-Service/Docs/General-Supplier-Reference-Information/Two-Bill-Example.pdf) | utility reference sample | +| 7 | `phovuuuk` | University of Pittsburgh Filled Sample W-2 | 3 | en | pdf | [link](https://www.payroll.pitt.edu/sites/default/files/assets/Sample-W2.pdf) | university educational sample (no real PII) | +| 8 | `LYeb3G3s` | Labsmart CBC Lab Report | 2 | en | pdf | [link](https://www.labsmartlis.com/pdf/pathology/cbc-report-format.pdf) | LIS-vendor sample template (de-identified) | +| 9 | `BnftpXVQ` | SEC EDGAR FedEx Credit Agreement (excerpt) | 2 | en | pdf | [link](https://www.sec.gov/Archives/edgar/data/1048911/000156459019025065/d817656dex10207.htm) | SEC EDGAR (US gov, public domain) | +| 10 | `SkD8Lz8o` | SEC EDGAR Precision Lease 4th Amendment (excerpt) | 3 | en | pdf | [link](https://www.sec.gov/Archives/edgar/data/1357874/000095017024036817/dtil-ex10_12.htm) | SEC EDGAR (US gov, public domain) | +| 11 | `1ZVqiyJZ` | DC DISB Homeowners Declarations | 1 | en | pdf | [link](https://disb.dc.gov/sites/default/files/dc/sites/disb/publication/attachments/Declaration%20Page%20Sample%20Homeowners%2012.pdf) | DC gov sample (fictional names) | +| 12 | `Oe7iRM1G` | Sage French Bulletin de Paie (payslip) | 1 | fr | pdf | [link](https://www.amplitude-informatique.fr/app/download/5813294897/Bulletin+clarifie+(Exemple).PDF) | vendor demo payslip (fictional) | +| 13 | `XhJyv5mb` | German DEG Jahresabschluss Bilanz+GuV (excerpt) | 2 | de | pdf | [link](https://www.deginvest.de/DEG-Dokumente/Download-Center/DEG_JAB_2022_DE.pdf) | published corporate annual report | +| 14 | `5YJaBbNg` | Portuguese Balanco e Demonstracao de Resultados (excerpt) | 2 | pt | pdf | [link](https://www.balbino-faustino.pt/uploads/base/ficheiros/Relatorio_e_Contas_2023.pdf) | published corporate annual report | +| 15 | `62PhJTyf` | Dutch Jaarrekening Balans+Winst-en-verliesrekening (excerpt) | 3 | nl | pdf | [link](https://cournot.nl/wp-content/uploads/2018/03/voorbeeld-jaarrekening.pdf) | publicly posted sample (fictional company) | +| 16 | `WxP8Tqgf` | Italian Busta Paga (payslip) | 1 | it | pdf | [link](https://www.unife.it) | university-hosted example payslip | +| 17 | `DtfW60lS` | Spanish Iberdrola Factura Electricidad | 4 | es | pdf | [link](https://www.iberdrola.es) | real electricity invoice posted publicly | +| 18 | `nESapyAA` | Taub Hebrew Tax Invoice | 1 | he | pdf | [link](https://www.taubcenter.org.il/wp-content/uploads/2020/05/104880.pdf) | vendor-generated sample invoice (posted publicly) | +| 19 | `SBR9L7Y8` | Hebrew Payslip | 1 | he | jpeg | [link](https://commons.wikimedia.org/wiki/File:%D7%AA%D7%9C%D7%95%D7%A9_%D7%A9%D7%9B%D7%A8.jpg) | Wikimedia Commons, CC BY-SA 4.0 | +| 20 | `J6buHXQ4` | Majdal Shams Municipal Financials | 13 | he | pdf | [link](https://majdal.muni.gov.il/media/xnahdrcu/kasbi2023.pdf) | municipal government publication | +| 21 | `qoSTXgNE` | Zionist Strategy NGO Financials | 4 | he | pdf | [link](https://www.guidestar.org.il/organization/580429207/finances) | GuideStar Israel (gov NGO registry), public filing | +| 22 | `qQUPWQNA` | Ramat Gan Arnona Rates 2025 | 5 | he | pdf | [link](https://cms-media.ramat-gan.muni.il/media/a33jhfld/) | municipal government publication | +| 23 | `jlKc8eVi` | Hitachi Japanese Invoice | 1 | ja | pdf | [link](https://www.hitachi.co.jp/Prod/comp/soft1/pde/info/concept/pdf/sample1_b.pdf) | vendor product sample template | +| 24 | `45xidifn` | Hitachi Japanese Statement | 1 | ja | pdf | [link](https://www.hitachi.co.jp/Prod/comp/soft1/pde/info/concept/pdf/sample3_b.pdf) | vendor product sample template | +| 25 | `M66HZlWT` | Chang Gung Chinese Medical Receipt | 1 | zh | jpeg | [link](https://commons.wikimedia.org/wiki/File:Chang_Gung_Memorial_Hospital_medical_expenditure_receipt_20160224_face.jpg) | Wikimedia Commons, CC BY-SA 4.0 | +| 26 | `Eet2wW3x` | FRESA Arabic Tax Invoice | 1 | ar | pdf | [link](https://fresatechnologies.com/wp-content/uploads/report-formats/invoice-report-format-8-standard-invoice-arabic.pdf) | vendor sample report format (publicly posted) | +| 27 | `vBIz5dut` | Five Guys Receipt Photo | 1 | en | jpeg | [link](https://expressexpense.com/blog/free-receipt-images-ocr-machine-learning-dataset/) | ExpressExpense SRD dataset, MIT License | +| 28 | `5ukZftw0` | Financial Sample Spreadsheet (trimmed 30 rows) | 1 | en | xlsx | [link](https://learn.microsoft.com/en-us/power-bi/create-reports/sample-financial-download) | Microsoft sample-data terms (copy/use permitted) | +| 29 | `PYhFptk3` | EDI 850 Purchase Order | 1 | en | txt | [link](https://iwayinfocenter.informationbuilders.com/TLs/TL_soa_ebiz_edix12/source/sample_docs48.htm) | vendor docs sample X12 (synthetic) | +| 30 | `C7fe2lau` | Peppol UBL E-Invoice | 1 | en | xml | [link](https://github.com/OpenPEPPOL/peppol-bis-invoice-3/blob/master/rules/examples/base-example.xml) | OpenPEPPOL repo, Apache-2.0 | +| 31 | `iTruRDrG` | Vince Sea Waybill | 2 | en | pdf | [link](http://vincesupplierportal.vince.com/_uploads/ship/shipDocs/Seaway%20Bill%20Example.pdf) | vendor supplier-portal example | +| 32 | `UnG6cLfP` | Samson Oil & Gas Check Stub | 2 | en | pdf | [link](https://www.samsonco.com/images/Owner-RelationsPage-DetailedExplanationofCheckStub.pdf) | vendor sample (publicly posted) | +| 33 | `ENoM9faK` | NASA Mechanical Drawing (sliced from 128p) | 1 | en | pdf | [link](https://s3vi.ndc.nasa.gov/ssri-kb/static/resources/NASA%20GSFC-X-673-64-1F.pdf) | NASA (US gov work, public domain, 17 USC 105) | +| 34 | `97uZroyv` | Hyperfine Schedule Sheet (sliced from 16p) | 1 | en | pdf | [link](https://hyperfinearchitecture.com/wp-content/uploads/2018/06/HFC_01_Plan-Set.pdf) | (c) Hyperfine Architecture (publicly downloadable) | +| 35 | `NNaGgwE5` | NRCS Pedon Handwritten Form | 2 | en | pdf | [link](https://www.uvm.edu/femc/attachments/project/161/Field_Book_for_Describing_and_Sampling_Soils.pdf) | USDA-NRCS (US gov, public domain); UVM mirror | +| 36 | `OayFbGlG` | Optum Discharge Summary | 2 | en | pdf | [link](https://www.optumhealthsandiego.com/content/dam/san-diego/documents/ffsproviders/review-inpatient/Inpatient%20Note%20Example.pdf) | (c) Optum, sample note | +| 37 | `wVafMvAC` | German 1976 Wage Statement | 1 | de | jpeg | [link](https://commons.wikimedia.org/wiki/File:Entgeltabrechnung_in_einer_Versicherungsgesellschaft_1976.JPG) | CC BY 4.0 + GFDL 1.2+ (uploader Wolf1949, self-created); privately self-uploaded 1976 payslip, no printed personal name | +| 38 | `GW7i2xbM` | FL Homeowners Declarations | 1 | en | pdf | [link](https://myfloridacfo.com/docs-sf/consumer-services-libraries/consumerservices-documents/understanding-coverage/sample-declarations-page.pdf) | Florida state gov consumer-guide sample | +| 39 | `KpewWz3R` | FHA 1004 Appraisal (sliced from 21p) | 7 | en | pdf | [link](http://www.piekos.com/xSites/Appraisers/piekos/Content/UploadedFiles/FHA_1004_DEMO.pdf) | (c) Piekos / a la mode form (publicly hosted) | +| 40 | `tLFa76nQ` | Fidelity Brokerage Statement (sliced from 28p) | 18 | en | pdf | [link](https://www.fidelity.com/bin-public/060_www_fidelity_com/documents/sample-new-fidelity-acnt-stmt.pdf) | (c) Fidelity, published sample | +| 41 | `4kVtTRoL` | Moneck Merchant Statement | 5 | en | pdf | [link](https://moneck.com/uploads/samples/Merchant-Statement-Example-Format.pdf) | (c) Moneck, hosted sample | +| 42 | `FiFgt4a6` | Ethiopian Air Waybill | 1 | en | pdf | [link](https://www.againstmalaria.com/images/00/00/775.pdf) | public shipment AWB posting | +| 43 | `bjBNmyNw` | Gordmans PO Line Items | 1 | en | pdf | [link](https://mimage.opentext.com/alt_content/binary/businessnetwork/gordmans/gordmans-guide-12-20-19a.pdf) | publicly hosted vendor routing manual | +| 44 | `WnxX1Buq` | PG&E Solar NEM Statement | 4 | en | pdf | [link](https://www.pge.com/assets/pge/docs/account/billing-and-assistance/nem-monthly-transition-bill-base-services-charge.pdf) | utility published sample (fictitious data) | +| 45 | `zKibU88u` | Orders Export XML | 1 | en | xml | (generated by benchmark authors) | authored for this benchmark, CC BY 4.0 | +| 46 | `pw8elPW9` | Hebrew Financial Statement (DOCX) | 1 | he | docx | (generated by benchmark authors) | authored for this benchmark, CC BY 4.0 | +| 47 | `7ZhgzAzp` | Ethiopian Air Waybill (rotated 90, TIFF) | 1 | en | tiff | [link](https://www.againstmalaria.com/images/00/00/775.pdf) | derived (90deg rotation) from doc #42 | +| 48 | `B0nA2c30` | Five Guys Receipt (rotated 180, PNG) | 1 | en | png | [link](https://expressexpense.com/blog/free-receipt-images-ocr-machine-learning-dataset/) | derived (180deg rotation) from doc #27 (MIT) | +| 49 | `eKzY7gEA` | Clinical Discharge Summary (HTML) | 1 | en | html | (generated by benchmark authors) | authored for this benchmark, CC BY 4.0 | +| 50 | `ZN6HbuKp` | Bank Transaction Register (CSV) | 1 | en | csv | (generated by benchmark authors) | authored for this benchmark, CC BY 4.0 | diff --git a/docs/dataset-card.md b/docs/dataset-card.md new file mode 100644 index 0000000000000000000000000000000000000000..51994603a52636202d11827d6a3400c208e7bff3 --- /dev/null +++ b/docs/dataset-card.md @@ -0,0 +1,49 @@ +# Dataset Card + +## Dataset Summary + +DocuBench is a 50-document benchmark for schema-guided structured extraction. Each example contains a source document, a JSON Schema, and a hand-verified JSON label. The task is to extract the labeled structured data from the document according to the schema. + +## Composition + +- 50 documents +- 50 schemas +- 50 labels +- 10 file types: PDF, JPEG, PNG, TIFF, XLSX, CSV, XML, TXT, DOCX, HTML +- 11 languages/scripts: English, Hebrew, Japanese, Chinese, Arabic, French, German, Portuguese, Dutch, Italian, Spanish + +Documents cover invoices, bank and brokerage statements, utility bills, annual reports, payslips, purchase orders, waybills, lab reports, discharge summaries, engineering drawings, insurance declarations, tax forms, spreadsheets, XML, CSV, text, and HTML. + +## Motivation + +Many document extraction evaluations focus on single-page, flat, or QA-style tasks. DocuBench focuses on end-to-end structured extraction into realistic JSON shapes, including arrays, nested objects, multipage context, non-Latin scripts, and non-PDF inputs. + +## Collection And Labeling + +Documents were selected from public sources, vendor sample documents, government publications, open datasets, and benchmark-authored synthetic files. Each document has a source and license record in [`SOURCES.md`](../SOURCES.md) and [`sources.json`](../sources.json). + +Labels were authored for the benchmark and manually checked field by field against the source document. + +## Intended Uses + +- Evaluating document extraction systems +- Testing schema-guided extraction robustness +- Comparing parser or extraction workflows on public artifacts +- Regression testing extraction systems across file types and languages + +## Out-Of-Scope Uses + +- Training models on the test labels +- Claiming broad document AI superiority from the headline aggregate alone +- Evaluating privacy handling, security, or compliance controls +- Treating these 50 documents as representative of all enterprise documents + +## Licensing + +- Code is MIT licensed. +- Labels, schemas, benchmark-authored metadata, and benchmark-authored results are CC BY 4.0 unless stated otherwise. +- Source documents retain their original licenses or publication basis. + +## Maintenance + +Scoring changes, label corrections, document removals, or additions should be recorded in a changelog and reflected in the benchmark version. diff --git a/docs/explorer-preview.png b/docs/explorer-preview.png new file mode 100644 index 0000000000000000000000000000000000000000..ab27bf174f37ef5cd4ced39db6e70d8f56a05590 --- /dev/null +++ b/docs/explorer-preview.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a6f9bf5e904c17337696f9426864d323493d9b34729c1a8e189f5e2de1f7ea3c +size 357306 diff --git a/docs/limitations.md b/docs/limitations.md new file mode 100644 index 0000000000000000000000000000000000000000..10cf0e24b114c60eca7f53e6843735d943224016 --- /dev/null +++ b/docs/limitations.md @@ -0,0 +1,27 @@ +# Limitations + +DocuBench is intentionally hard, but it is not exhaustive. + +## Dataset Size + +The benchmark has 50 documents. That is enough for careful inspection and regression testing, but not enough to support broad statistical claims about every document domain. + +## Public-Document Bias + +All documents are public, publicly posted samples, openly licensed files, government publications, or benchmark-authored artifacts. This improves reproducibility, but it means the corpus may differ from private enterprise document distributions. + +## Label And Schema Scope + +Each schema asks for selected fields rather than every possible fact in a document. A system may extract useful information that is not measured by a given schema. + +## Scoring Scope + +The current scorer uses normalized exact matching and greedy array alignment. It does not yet support field-specific semantic matching, numeric tolerances beyond float normalization, or globally optimal array assignment. + +## Aggregate Interpretation + +The headline score is a macro average over documents. Users should inspect per-document and per-capability results before making system decisions. + +## Cost And Latency + +Some result files include cost and timing metadata, but the benchmark does not yet enforce a uniform cost/latency reporting contract across all systems. diff --git a/docs/scoring.md b/docs/scoring.md new file mode 100644 index 0000000000000000000000000000000000000000..8d11822217e3a38cbeb78e85c23f63d844866098 --- /dev/null +++ b/docs/scoring.md @@ -0,0 +1,64 @@ +# Scoring + +DocuBench scores schema-guided extraction output against hand-verified JSON labels. The scorer is intentionally small and inspectable; the canonical implementation is [`scorer.py`](../scorer.py). + +## Inputs + +Each scoring call takes: + +- `result`: the system output JSON object, usually from the top-level `data` key in `results//.json` +- `schema`: the JSON Schema in `schemas/.json` +- `label`: the hand-verified target JSON in `labels/.json` + +The schema determines which fields are scored. + +## Normalization + +Before comparison: + +- numeric values are cast to floats and rounded to six decimal places +- strings are lowercased +- whitespace is removed from strings +- punctuation and non-word separators are removed from strings +- empty strings, empty arrays, and empty objects are stripped +- `null` is preserved because it can represent an intentional labeled value + +This normalization is meant to avoid penalizing harmless formatting differences. It is not semantic matching. + +## Non-Array Fields + +Non-array leaves are scored as binary exact matches after normalization. + +- matching leaf: `1` +- mismatching leaf: `0` +- both sides empty: skipped +- one side empty: mismatch + +The non-array score is `correct / total` over scored leaf fields. + +## Array Fields + +Arrays are scored order-independently. + +1. Each labeled item is compared with each predicted item. +2. Item similarity is computed as binary leaf-field accuracy over the union of leaves present in either item. +3. The scorer greedily assigns the highest-scoring label/result item pairs without reusing either side. +4. Unmatched label or result items count against the score through the denominator. + +Array scores are weighted by the average non-empty leaf count in labeled array items. This keeps the final score approximately leaf-weighted rather than array-count-weighted. + +## Aggregate Metric + +For one document, the final score is a weighted average across array and non-array components. + +For a system, the headline benchmark score is the macro average of per-document final scores. Each document contributes equally to the headline aggregate. + +## Known Tradeoffs + +- Array matching is greedy, not globally optimal. +- String matching is normalized exact matching, not semantic equivalence. +- Extra fields outside the schema are ignored for non-array objects. +- Extra fields inside array items can affect item-level similarity because array item comparison uses the union of leaves. +- Field-specific tolerances are not yet expressed in schema metadata. + +These tradeoffs are documented so scores are interpretable and reproducible. Changes to scoring behavior should be treated as benchmark-version changes. diff --git a/docs/submissions.md b/docs/submissions.md new file mode 100644 index 0000000000000000000000000000000000000000..a52109e0218fddec07d852eb29c00201d85ff57a --- /dev/null +++ b/docs/submissions.md @@ -0,0 +1,97 @@ +# Submission Format + +DocuBench result sets live under: + +```text +results//.json +``` + +`` should be lowercase, filesystem-safe, and stable across reports. + +## Required Per-Document File + +Each document result should be a JSON object with a top-level `data` key: + +```json +{ + "data": { + "invoice_number": "INV-001", + "line_items": [] + } +} +``` + +The `data` object is scored against `labels/.json` using `schemas/.json`. + +## Recommended Metadata + +Include run metadata when available: + +```json +{ + "data": {}, + "cost": 0.0, + "time_sec": 0.0, + "meta": { + "system": "example-system", + "model": "model-or-api-version", + "run_date": "2026-06-26", + "configuration": "short human-readable config" + } +} +``` + +If a system fails to complete, refuses, or returns output that cannot be parsed into the +requested schema, still write a result file with an empty `data` object: + +```json +{ + "status": "failed", + "error": { + "type": "schema_mismatch", + "message": "model output did not conform to the schema" + }, + "data": {}, + "meta": { + "model": "model-or-api-version" + } +} +``` + +This makes the failure visible and causes all non-empty labeled fields for that document +to be counted as errors. + +## Validation And Scoring + +Run: + +```bash +docubench validate +docubench score --engine +``` + +To regenerate reports for all result sets: + +```bash +docubench report +``` + +## Prompts And Run Configuration + +Commit the prompt and run configuration that produced a submission under +[`prompts/`](../prompts), following the existing baselines. The committed LLM baselines +load their instruction from [`prompts/extraction_prompt.txt`](../prompts/extraction_prompt.txt) +at runtime, and each result file stamps its model id, provider, and `schema_mode` in +`meta` — together these make a result set reproducible and auditable. + +## Review Expectations + +Public submissions should state: + +- system name and version +- model or provider version, if applicable +- extraction settings that affect output +- date of run +- whether the run was produced by released code, proprietary code, or manual workflow +- any documents skipped or failed +- cost and latency if measured diff --git a/docubench-explorer.html b/docubench-explorer.html new file mode 100644 index 0000000000000000000000000000000000000000..5adc22fe18efd61dd63a3ba79406bf09bbc114d3 --- /dev/null +++ b/docubench-explorer.html @@ -0,0 +1,786 @@ + + + + + +DocuBench — Structured Extraction Benchmark + + + + + + + +
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+ + + DOCUPIPE + + Source & data on GitHub ↗ +
+
AI document-extraction benchmark
+

DocuBench

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DocuBench pairs 50 real-world documents with a JSON Schema and a hand-verified label, then scores each system on macro-average field accuracy. The set is deliberately hard: arrays and nested tables, right-to-left and CJK scripts, rotated scans, handwriting, and non-PDF formats.

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Macro-average field accuracy

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97.56%
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DocuPipe high
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The full DocuBench write-up

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Methodology, the scoring contract, worked examples, and a per-document analysis of where each system wins and loses.

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+ + + + diff --git a/docubench/__init__.py b/docubench/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..a746365f6d31001ed4c2664c05eeafc9b122e0da --- /dev/null +++ b/docubench/__init__.py @@ -0,0 +1,3 @@ +"""Utilities for the DocuBench structured document extraction benchmark.""" + +__version__ = "0.1.0" diff --git a/docubench/cli.py b/docubench/cli.py new file mode 100644 index 0000000000000000000000000000000000000000..d1473e6923a543be0a17e5388a36f77996f265aa --- /dev/null +++ b/docubench/cli.py @@ -0,0 +1,311 @@ +"""Command-line utilities for validating and scoring DocuBench.""" + +from __future__ import annotations + +import argparse +import csv +import json +import sys +from pathlib import Path +from typing import Any + +from scorer import score_standardization + + +DEFAULT_ENGINE_DISPLAY_NAMES = { + "claude": "Claude", + "docupipe_high": "DocuPipe high", + "docupipe_standard": "DocuPipe standard", + "extend": "Extend", + "gemini": "Gemini", + "gpt": "GPT", +} + + +def load_json(path: Path) -> Any: + with open(path, encoding="utf-8") as f: + return json.load(f) + + +def write_json(path: Path, data: Any) -> None: + path.parent.mkdir(parents=True, exist_ok=True) + with open(path, "w", encoding="utf-8") as f: + json.dump(data, f, ensure_ascii=False, indent=2) + f.write("\n") + + +def benchmark_ids(root: Path) -> list[str]: + return sorted(p.stem for p in (root / "labels").glob("*.json")) + + +def discover_engines(root: Path) -> list[str]: + results_dir = root / "results" + if not results_dir.exists(): + return [] + return sorted(p.name for p in results_dir.iterdir() if p.is_dir()) + + +def document_id_map(root: Path) -> dict[str, Path]: + docs: dict[str, Path] = {} + for path in (root / "documents").iterdir(): + if path.is_file(): + docs[path.stem] = path + return docs + + +def validate_benchmark(root: Path) -> tuple[list[str], list[str], dict[str, Any]]: + errors: list[str] = [] + warnings: list[str] = [] + + required_dirs = ["documents", "labels", "schemas", "results"] + for dirname in required_dirs: + if not (root / dirname).is_dir(): + errors.append(f"missing required directory: {dirname}/") + + sources_path = root / "sources.json" + if not sources_path.is_file(): + errors.append("missing sources.json") + sources = [] + else: + try: + sources = load_json(sources_path) + except json.JSONDecodeError as exc: + errors.append(f"sources.json is invalid JSON: {exc}") + sources = [] + + if errors: + return errors, warnings, {} + + doc_paths = document_id_map(root) + doc_ids = set(doc_paths) + label_ids = {p.stem for p in (root / "labels").glob("*.json")} + schema_ids = {p.stem for p in (root / "schemas").glob("*.json")} + source_ids = {row.get("doc_id") for row in sources if isinstance(row, dict)} + + expected_ids = label_ids | schema_ids | source_ids + for collection_name, ids in [ + ("documents", doc_ids), + ("labels", label_ids), + ("schemas", schema_ids), + ("sources", source_ids), + ]: + missing = sorted(expected_ids - ids) + extra = sorted(ids - expected_ids) + if missing: + errors.append(f"{collection_name} missing ids: {', '.join(missing)}") + if extra: + errors.append(f"{collection_name} has unexpected ids: {', '.join(extra)}") + + for directory in ["labels", "schemas"]: + for path in sorted((root / directory).glob("*.json")): + try: + load_json(path) + except json.JSONDecodeError as exc: + errors.append(f"{path.relative_to(root)} is invalid JSON: {exc}") + + engines = discover_engines(root) + for engine in engines: + engine_dir = root / "results" / engine + result_ids = {p.stem for p in engine_dir.glob("*.json")} + missing = sorted(label_ids - result_ids) + extra = sorted(result_ids - label_ids) + if missing: + warnings.append(f"results/{engine} missing ids: {', '.join(missing)}") + if extra: + warnings.append(f"results/{engine} has extra ids: {', '.join(extra)}") + for path in sorted(engine_dir.glob("*.json")): + try: + payload = load_json(path) + except json.JSONDecodeError as exc: + errors.append(f"{path.relative_to(root)} is invalid JSON: {exc}") + continue + if not isinstance(payload, dict): + errors.append(f"{path.relative_to(root)} must contain a JSON object") + elif "data" not in payload: + warnings.append(f"{path.relative_to(root)} has no top-level data key") + + summary = { + "documents": len(doc_ids), + "labels": len(label_ids), + "schemas": len(schema_ids), + "sources": len(source_ids), + "engines": engines, + } + return errors, warnings, summary + + +def score_engines(root: Path, engines: list[str] | None = None) -> dict[str, Any]: + doc_ids = benchmark_ids(root) + selected_engines = engines or discover_engines(root) + per_engine: dict[str, dict[str, float | None]] = {engine: {} for engine in selected_engines} + + for doc_id in doc_ids: + schema = load_json(root / "schemas" / f"{doc_id}.json") + label = load_json(root / "labels" / f"{doc_id}.json") + for engine in selected_engines: + result_path = root / "results" / engine / f"{doc_id}.json" + if not result_path.exists(): + per_engine[engine][doc_id] = None + continue + result_payload = load_json(result_path) + result = result_payload.get("data", {}) if isinstance(result_payload, dict) else {} + score = score_standardization(result=result, schema=schema, label=label) + per_engine[engine][doc_id] = score["final"] + + per_doc = [] + for doc_id in doc_ids: + row: dict[str, Any] = {"doc_id": doc_id} + for engine in selected_engines: + row[engine] = per_engine[engine][doc_id] + per_doc.append(row) + + aggregates = {} + for engine, scores_by_doc in per_engine.items(): + scores = [score for score in scores_by_doc.values() if score is not None] + aggregates[engine] = sum(scores) / len(scores) if scores else None + + return { + "benchmark": { + "name": "DocuBench", + "version": "0.1.0", + "doc_count": len(doc_ids), + "metric": "macro_average_field_accuracy", + }, + "engine_display_names": { + engine: DEFAULT_ENGINE_DISPLAY_NAMES.get(engine, engine) + for engine in selected_engines + }, + "aggregates": aggregates, + "breakdowns": build_breakdowns(root, per_doc, selected_engines), + "per_doc": per_doc, + } + + +def build_breakdowns(root: Path, per_doc: list[dict[str, Any]], engines: list[str]) -> dict[str, Any]: + sources_path = root / "sources.json" + if not sources_path.exists(): + return {} + sources = load_json(sources_path) + metadata = {row["doc_id"]: row for row in sources if isinstance(row, dict) and "doc_id" in row} + by_doc = {row["doc_id"]: row for row in per_doc} + breakdowns: dict[str, Any] = {} + + for dimension in ["ftype", "lang"]: + groups: dict[str, list[str]] = {} + for doc_id, row in metadata.items(): + value = str(row.get(dimension) or "unknown") + groups.setdefault(value, []).append(doc_id) + dimension_rows = [] + for value in sorted(groups): + doc_ids = sorted(doc_id for doc_id in groups[value] if doc_id in by_doc) + out: dict[str, Any] = {"value": value, "doc_count": len(doc_ids)} + for engine in engines: + scores = [by_doc[doc_id][engine] for doc_id in doc_ids if by_doc[doc_id][engine] is not None] + out[engine] = sum(scores) / len(scores) if scores else None + dimension_rows.append(out) + breakdowns[dimension] = dimension_rows + return breakdowns + + +def print_score_table(scores: dict[str, Any]) -> None: + engines = list(scores["aggregates"].keys()) + header = f"{'doc_id':<12}" + "".join(f"{engine:>20}" for engine in engines) + print(header) + print("-" * len(header)) + for row in scores["per_doc"]: + line = f"{row['doc_id']:<12}" + for engine in engines: + score = row[engine] + line += f"{(f'{score:.4f}' if score is not None else 'n/a'):>20}" + print(line) + print("-" * len(header)) + aggregate_line = f"{'AGGREGATE':<12}" + for engine in engines: + score = scores["aggregates"][engine] + aggregate_line += f"{(f'{score:.4f}' if score is not None else 'n/a'):>20}" + print(aggregate_line) + + +def write_summary_csv(path: Path, scores: dict[str, Any]) -> None: + engines = list(scores["aggregates"].keys()) + path.parent.mkdir(parents=True, exist_ok=True) + with open(path, "w", encoding="utf-8", newline="") as f: + writer = csv.DictWriter(f, fieldnames=["doc_id", *engines], lineterminator="\n") + writer.writeheader() + for row in scores["per_doc"]: + writer.writerow({key: row.get(key) for key in ["doc_id", *engines]}) + writer.writerow({"doc_id": "AGGREGATE", **scores["aggregates"]}) + + +def cmd_validate(args: argparse.Namespace) -> int: + errors, warnings, summary = validate_benchmark(args.root) + for warning in warnings: + print(f"warning: {warning}", file=sys.stderr) + if errors: + for error in errors: + print(f"error: {error}", file=sys.stderr) + return 1 + print( + "validated " + f"{summary['documents']} documents, " + f"{summary['labels']} labels, " + f"{summary['schemas']} schemas, " + f"{summary['sources']} source records, " + f"{len(summary['engines'])} result sets" + ) + return 0 + + +def cmd_score(args: argparse.Namespace) -> int: + scores = score_engines(args.root, args.engine) + if args.json: + print(json.dumps(scores, ensure_ascii=False, indent=2)) + else: + print_score_table(scores) + return 0 + + +def cmd_report(args: argparse.Namespace) -> int: + scores = score_engines(args.root, args.engine) + write_json(args.summary_json, scores) + write_summary_csv(args.summary_csv, scores) + print(f"wrote {args.summary_json}") + print(f"wrote {args.summary_csv}") + return 0 + + +def build_parser() -> argparse.ArgumentParser: + parser = argparse.ArgumentParser(prog="docubench") + parser.add_argument("--root", type=Path, default=Path.cwd(), help="repository root") + subparsers = parser.add_subparsers(dest="command", required=True) + + validate = subparsers.add_parser("validate", help="validate benchmark files") + validate.set_defaults(func=cmd_validate) + + score = subparsers.add_parser("score", help="score committed result sets") + score.add_argument("--engine", action="append", help="result directory to score; repeatable") + score.add_argument("--json", action="store_true", help="emit JSON instead of a table") + score.set_defaults(func=cmd_score) + + report = subparsers.add_parser("report", help="write summary JSON and CSV reports") + report.add_argument("--engine", action="append", help="result directory to score; repeatable") + report.add_argument("--summary-json", type=Path, default=Path("results/summary.json")) + report.add_argument("--summary-csv", type=Path, default=Path("results/summary.csv")) + report.set_defaults(func=cmd_report) + + return parser + + +def main(argv: list[str] | None = None) -> int: + parser = build_parser() + args = parser.parse_args(argv) + args.root = args.root.resolve() + if hasattr(args, "summary_json") and not args.summary_json.is_absolute(): + args.summary_json = args.root / args.summary_json + if hasattr(args, "summary_csv") and not args.summary_csv.is_absolute(): + args.summary_csv = args.root / args.summary_csv + return args.func(args) + + +if __name__ == "__main__": + 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Discharge Summary

+ + + +
Patient Name:Robert J. SampleMRN:00471829
Date of Birth:1958-03-14Sex:Male
Admission Date:2025-09-02Discharge Date:2025-09-08
Attending Physician:Dr. Elena Marsh, MDDisposition:Home with home health
+

Discharge Diagnoses

  1. Community-acquired pneumonia, right lower lobe
  2. Acute hypoxic respiratory failure
  3. Type 2 diabetes mellitus
  4. Essential hypertension
  5. Chronic kidney disease, stage 3
+

Allergies

  • Penicillin (rash)
  • Sulfonamides (hives)
+

Procedures Performed

  • Chest radiograph, two views
  • Complete blood count
  • Comprehensive metabolic panel
  • Blood cultures x2
+

Discharge Medications

  1. Levofloxacin 750 mg PO daily x5 days
  2. Metformin 1000 mg PO twice daily
  3. Lisinopril 20 mg PO daily
  4. Atorvastatin 40 mg PO at bedtime
  5. Albuterol inhaler 2 puffs every 4 hours as needed
+

Follow-up

Primary care in 1 week; nephrology in 2 weeks.

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steel", + "quantity": 30.0, + "rate": 165.0, + "total": 4950.0 + }, + { + "description": "Erection of concrete formworks for footings", + "quantity": 34.0, + "rate": 230.0, + "total": 7820.0 + } + ], + "labor": [ + { + "description": "Marking of foundation layout at site", + "hours": 30.0, + "rate": 60.0, + "amount": 1800.0 + }, + { + "description": "Earth excavation up to the required depth by machine", + "hours": 23.0, + "rate": 60.0, + "amount": 1380.0 + }, + { + "description": "Earth excavation and levelling of soil by hand- operated tools", + "hours": 19.0, + "rate": 60.0, + "amount": 1140.0 + }, + { + "description": "Placing of PCC", + "hours": 35.0, + "rate": 60.0, + "amount": 2100.0 + }, + { + "description": "Placement of reinforcement steel", + "hours": 76.0, + "rate": 60.0, + "amount": 4560.0 + }, + { + "description": "Erection of concrete formworks for footings", + "hours": 53.0, + "rate": 60.0, + "amount": 3180.0 + } + ], + "miscellaneousCharges": [ + { + "description": "Transportation of materials", + "amount": 430.0 + }, + { + "description": "Consultations with architect", + "amount": 760.0 + } + ], + "totals": { + "totalMaterials": 15790.0, + "totalLabor": 14160.0, + "totalMiscellaneous": 1190.0, + "subtotal": 31140.0, + "taxRate": 3.8, + "totalTax": 1183.32, + "total": 32323.32 + } +} \ No newline at end of file diff --git a/labels/zKibU88u.json b/labels/zKibU88u.json new file mode 100644 index 0000000000000000000000000000000000000000..14d5679a4bd0ba0aa8cc58886adfa54d11bb1731 --- /dev/null +++ b/labels/zKibU88u.json @@ -0,0 +1,58 @@ +{ + "currency": "USD", + "recordCount": 200, + "sourceSystem": "commerce-cloud-v4", + "schemaVersion": "orders.v4", + "focusOrderDate": "2025-10-27", + "focusOrderChannel": "store", + "focusOrderStatus": "shipped", + "focusOrderBuyerName": "Devon Marsh", + "focusOrderBuyerTier": "silver", + "focusOrderBuyerRegion": "WEST", + "focusOrderShippingCarrier": "DHL", + "focusOrderPaymentMethod": "paypal", + "focusOrderLineItems": [ + { + "sku": "SKU-SF-610", + "title": "Halden 3-Seat Sofa", + "category": "Seating", + "quantity": 4, + "unitPriceCents": 129900, + "discountCents": 1500 + }, + { + "sku": "SKU-SH-810", + "title": "Atlas Bookshelf", + "category": "Storage", + "quantity": 1, + "unitPriceCents": 33900, + "discountCents": 0 + }, + { + "sku": "SKU-SF-690", + "title": "Otis Loveseat", + "category": "Seating", + "quantity": 1, + "unitPriceCents": 89900, + "discountCents": 1000 + }, + { + "sku": "SKU-AP-205", + "title": "Nimbus Floor Lamp", + "category": "Lighting", + "quantity": 2, + "unitPriceCents": 15900, + "discountCents": 1500 + }, + { + "sku": "SKU-CH-340", + "title": "Marlow Lounge Chair", + "category": "Seating", + "quantity": 1, + "unitPriceCents": 38900, + "discountCents": 0 + } + ], + "earlyOrderCarrier": "USPS", + "lateOrderPaymentMethod": "mastercard" +} \ No newline at end of file diff --git a/prompts/README.md b/prompts/README.md new file mode 100644 index 0000000000000000000000000000000000000000..4811611b470bc1e746aca0e51b6b90fa00e52b8f --- /dev/null +++ b/prompts/README.md @@ -0,0 +1,45 @@ +# Prompts + +This directory commits the exact instructions and run configuration used to produce +every committed baseline result set. Nothing here is decorative: the model-based runners +in [`scripts/`](../scripts) load [`extraction_prompt.txt`](extraction_prompt.txt) at +runtime, so the file in this directory is provably the prompt that was sent. + +A benchmark number is only meaningful if you can see the prompt, the model, and the +schema handling that produced it. Models drift and providers deprecate versions, so each +committed result file also stamps the model id, provider, and `schema_mode` in its +`meta` block — pair that with the files here to reproduce or audit any score. + +## Canonical extraction prompt + +All three LLM runners (OpenAI, Anthropic, Google) send the same user instruction, +templated on `extraction_prompt.txt`. It is deliberately minimal — the JSON Schema +carries the field-level intent, and structured-output / response-schema modes enforce +shape — so the prompt does not leak task-specific hints that would inflate scores. + +```text +Extract the document into the supplied JSON schema. Use only information present in the +document. Return null for fields that are not printed or cannot be determined. Preserve +table rows as arrays and preserve the document language for values. Document id: {doc_id}. +``` + +`{doc_id}` is filled with the benchmark document id at runtime. + +## Per-system configuration + +| System | Result dir | Runner | Prompt / config | +|---|---|---|---| +| OpenAI GPT | `results/gpt` | [`scripts/run_gpt.py`](../scripts/run_gpt.py) | [`gpt.md`](gpt.md) | +| Anthropic Claude | `results/claude` | [`scripts/run_claude.py`](../scripts/run_claude.py) | [`claude.md`](claude.md) | +| Google Gemini | `results/gemini` | [`scripts/run_gemini.py`](../scripts/run_gemini.py) | [`gemini.md`](gemini.md) | +| Extend | `results/extend` | [`scripts/run_extend.py`](../scripts/run_extend.py) | [`extend.md`](extend.md) | +| DocuPipe | `results/docupipe_*` | (vendor product) | [`docupipe.md`](docupipe.md) | + +## How the schema is used + +The raw `schemas/.json` is JSON Schema draft-07. Each runner transforms it into +the strict subset its provider accepts (every object property required, objects/primitives +made nullable, unsupported keywords stripped) before constraining the model output. The +transform is part of the runner and is described in each per-system file. Extend and +DocuPipe consume the schema through their own extraction configuration rather than a +free-text prompt. diff --git a/prompts/claude.md b/prompts/claude.md new file mode 100644 index 0000000000000000000000000000000000000000..8d010d1c3857f5dc500122201c630e6d800eddaa --- /dev/null +++ b/prompts/claude.md @@ -0,0 +1,42 @@ +# Claude (Anthropic) + +- **Runner:** [`scripts/run_claude.py`](../scripts/run_claude.py) +- **Result set:** `results/claude/.json` +- **Default model:** `claude-sonnet-4-6` (override with `ANTHROPIC_MODEL`) +- **API:** Anthropic Messages API (`/v1/messages`), `anthropic-version: 2023-06-01` +- **Schema mode:** `anthropic_output_config_nullable_v1` + +## Prompt + +The user instruction is the canonical [`extraction_prompt.txt`](extraction_prompt.txt) +with one trailing sentence added, because Claude returns conversational text by default: + +```text +Extract the document into the supplied JSON schema. Use only information present in the +document. Return null for fields that are not printed or cannot be determined. Preserve +table rows as arrays and preserve the document language for values. Document id: {doc_id}. +Return only the JSON object, with no prose or markdown. +``` + +PDFs are sent as a base64 `document` block, images as `image` blocks, multipage TIFF as a +sequence of PNG `image` blocks, and DOCX/XLSX/text formats as extracted plain text. + +## Output constraint + +The normalized strict schema (shared with the GPT runner via `normalize_output_schema`) +is passed as `output_config.format` of type `json_schema`. If the provider rejects the +compiled grammar (for example a schema construct it cannot compile), the runner retries +once with the schema embedded in the prompt instead and records +`schema_fallback: "prompt_json_schema"` in `meta`. Code-fenced or prose-wrapped JSON is +unwrapped before parsing. + +## Run knobs (environment) + +- `ANTHROPIC_API_KEY` (required) +- `ANTHROPIC_MODEL`, `ANTHROPIC_API_BASE`, `ANTHROPIC_MAX_TOKENS` +- `ANTHROPIC_INPUT_USD_PER_1M`, `ANTHROPIC_OUTPUT_USD_PER_1M` (optional cost estimate) + +## Failure handling + +Truncation (`stop_reason` of `max_tokens`), empty output, invalid JSON, and +schema-validation failures are written as `status: "failed"` with `data: {}`. diff --git a/prompts/docupipe.md b/prompts/docupipe.md new file mode 100644 index 0000000000000000000000000000000000000000..b55692709e1fdd0226f430e9be09d0369d0d8f67 --- /dev/null +++ b/prompts/docupipe.md @@ -0,0 +1,26 @@ +# DocuPipe + +- **Result sets:** `results/docupipe_high/.json`, `results/docupipe_standard/.json` +- **Runner:** none in this repository (vendor product) + +## No natural-language prompt + +DocuPipe is a hosted document-extraction product ([docupipe.ai](https://www.docupipe.ai)), +not a chat model, so there is no free-text prompt to commit. Each document was processed +through the product using the same benchmark schema (`schemas/.json`) as every +other system, with default extraction settings at two effort levels: + +- **`docupipe_high`** — high-effort extraction +- **`docupipe_standard`** — standard-effort extraction + +The two result sets exist so the cost/latency/accuracy trade-off of a single product is +visible on the same documents. + +## Reproducibility note + +DocuPipe's internal extraction pipeline is proprietary and is not run by code in this +repository. The committed result files are the product's raw outputs, scored by the same +public scorer against the same labels as all other systems. They are presented as +baseline submissions, not as a privileged reference — anyone can score a competing system +against these documents with `docubench score`. Each result file records its run +metadata (cost, time, effort level) in the result envelope. diff --git a/prompts/extend.md b/prompts/extend.md new file mode 100644 index 0000000000000000000000000000000000000000..2ca8f084309a92b4d7b9050302ea62bc04575c34 --- /dev/null +++ b/prompts/extend.md @@ -0,0 +1,40 @@ +# Extend + +- **Runner:** [`scripts/run_extend.py`](../scripts/run_extend.py) +- **Result set:** `results/extend/.json` +- **API:** Extend (`https://api.extend.ai`), `x-extend-api-version: 2026-02-09` + +## No natural-language prompt + +Extend is a configured extraction product, not a chat model, so there is no free-text +prompt to commit. The task is expressed entirely through an **extractor** created from the +benchmark schema. The committed configuration is: + +- `baseProcessor: extraction_performance` +- `baseVersion: 4.1.1` +- `parseConfig.engine: parse_performance` + +## Schema handling + +`schemas/.json` is transformed into Extend's accepted schema subset +(`transform_schema` / `transform_node`): + +- strip `$schema`, `examples`, `default`, `title`, and any `x_*` keys +- primitives become nullable unions (`["string", "null"]`); enums gain a `null` member +- `format: "date"` becomes `extend:type: "date"` +- every object sets `additionalProperties: false`; arrays and nested objects recurse +- the reserved top-level property name `id` is renamed on the Extend side and mapped back + in the output + +## Run procedure + +Each run uploads the source file with a **fresh `file_id`** (the first `/extract` on a +file id caches the parse output, so reusing it would silently serve a stale parse) and +creates a uniquely named extractor so the current schema is always used. The runner then +calls `/extract`, polls `/extract_runs/` until `PROCESSED`, and maps the output back +to the original field names. Cost is derived from reported credits at +`$0.0125`/credit. + +## Run knobs (environment) + +- `EXTEND_API_KEY` (required, for your own Extend workspace) diff --git a/prompts/extraction_prompt.txt b/prompts/extraction_prompt.txt new file mode 100644 index 0000000000000000000000000000000000000000..3a99f80dfbfe2c73909d69784e77ee6809bb1592 --- /dev/null +++ b/prompts/extraction_prompt.txt @@ -0,0 +1 @@ +Extract the document into the supplied JSON schema. Use only information present in the document. Return null for fields that are not printed or cannot be determined. Preserve table rows as arrays and preserve the document language for values. Document id: {doc_id}. diff --git a/prompts/gemini.md b/prompts/gemini.md new file mode 100644 index 0000000000000000000000000000000000000000..1cf2d7cbaa660bc30ee41568e8fc1ddace6404a6 --- /dev/null +++ b/prompts/gemini.md @@ -0,0 +1,39 @@ +# Gemini (Google) + +- **Runner:** [`scripts/run_gemini.py`](../scripts/run_gemini.py) +- **Result set:** `results/gemini/.json` +- **Default model:** `gemini-3.5-flash` (override with `GEMINI_MODEL`) +- **API:** Generative Language API (`/v1beta/models/:generateContent`) +- **Schema mode:** `gemini_response_schema_nullable_v1` + +## Prompt + +Identical to the canonical [`extraction_prompt.txt`](extraction_prompt.txt): + +```text +Extract the document into the supplied JSON schema. Use only information present in the +document. Return null for fields that are not printed or cannot be determined. Preserve +table rows as arrays and preserve the document language for values. Document id: {doc_id}. +``` + +PDFs and images are sent as `inline_data`, multipage TIFF as a sequence of inline PNG +pages, and DOCX/XLSX/text formats as extracted plain text. + +## Output constraint + +`generationConfig.responseMimeType` is set to `application/json` and +`generationConfig.responseSchema` carries the schema rendered into Gemini's typed schema +form (`OBJECT`/`ARRAY`/`STRING`/`NUMBER`/`INTEGER`/`BOOLEAN`, `nullable` flags, +`propertyOrdering`). The same normalized strict schema used by the GPT runner is the +input to this conversion. + +## Run knobs (environment) + +- `GOOGLE_API_KEY` or `GEMINI_API_KEY` (required) +- `GEMINI_MODEL`, `GEMINI_API_BASE`, `GEMINI_MAX_OUTPUT_TOKENS` +- `GEMINI_INPUT_USD_PER_1M`, `GEMINI_OUTPUT_USD_PER_1M` (optional cost estimate) + +## Failure handling + +Missing candidates, non-`STOP` finish reasons, empty output, invalid JSON, and +schema-validation failures are written as `status: "failed"` with `data: {}`. diff --git a/prompts/gpt.md b/prompts/gpt.md new file mode 100644 index 0000000000000000000000000000000000000000..71601d2cea406768e0f59a44a07ae1c98f065cc8 --- /dev/null +++ b/prompts/gpt.md @@ -0,0 +1,45 @@ +# GPT (OpenAI) + +- **Runner:** [`scripts/run_gpt.py`](../scripts/run_gpt.py) +- **Result set:** `results/gpt/.json` +- **Default model:** `gpt-5.5` (override with `OPENAI_MODEL`) +- **API:** OpenAI Responses API (`/v1/responses`) with Structured Outputs +- **Schema mode:** `openai_strict_nullable_v1` + +## Prompt + +The user instruction is loaded from [`extraction_prompt.txt`](extraction_prompt.txt): + +```text +Extract the document into the supplied JSON schema. Use only information present in the +document. Return null for fields that are not printed or cannot be determined. Preserve +table rows as arrays and preserve the document language for values. Document id: {doc_id}. +``` + +The document is attached as an `input_file` (PDF / native files via the Files API), an +`input_image` (JPEG/PNG/WebP/GIF), or a sequence of PNG pages converted from multipage +TIFF. + +## Output constraint + +The schema is sent as `text.format` of type `json_schema` with `strict: true`. The raw +benchmark schema is first normalized (`normalize_output_schema`) into OpenAI's strict +subset: + +- drop `$schema`, `examples`, `default`, `title`, `format`, and any `x_*` keys +- every object lists all properties in `required` and sets `additionalProperties: false` +- objects and primitives are made nullable so a labeled `null` can be returned +- enum literals are sanitized and gain a `null` member when nullable + +## Run knobs (environment) + +- `OPENAI_API_KEY` (required) +- `OPENAI_MODEL`, `OPENAI_API_BASE` +- `OPENAI_MAX_OUTPUT_TOKENS`, `OPENAI_REASONING_EFFORT` +- `OPENAI_INPUT_USD_PER_1M`, `OPENAI_OUTPUT_USD_PER_1M` (optional cost estimate) + +## Failure handling + +API errors, refusals, empty output, invalid JSON, or schema-validation failures are +written as `status: "failed"` with `data: {}`, so the scorer counts every labeled field +as an error instead of silently dropping the document. diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000000000000000000000000000000000000..4db288f808b4baa704fe0b8783c5a3db3e518c0f --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,51 @@ +[build-system] +requires = ["setuptools>=68"] +build-backend = "setuptools.build_meta" + +[project] +name = "docubench" +version = "0.1.0" +description = "A public benchmark for schema-guided structured extraction from real-world documents." +readme = "README.md" +requires-python = ">=3.10" +license = { text = "MIT" } +dependencies = [ + "pillow>=10", + "requests>=2.31" +] +authors = [ + { name = "DocuBench maintainers" } +] +keywords = [ + "benchmark", + "document extraction", + "structured extraction", + "json schema", + "ocr", + "document ai" +] +classifiers = [ + "Development Status :: 3 - Alpha", + "Intended Audience :: Developers", + "Intended Audience :: Science/Research", + "License :: OSI Approved :: MIT License", + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3 :: Only", + "Topic :: Scientific/Engineering :: Artificial Intelligence" +] + +[project.optional-dependencies] +dev = [ + "pytest>=8" +] + +[project.scripts] +docubench = "docubench.cli:main" + +[tool.setuptools] +packages = ["docubench"] +py-modules = ["scorer"] + +[tool.pytest.ini_options] +testpaths = ["tests"] +pythonpath = ["."] diff --git a/results/claude/1ZVqiyJZ.json b/results/claude/1ZVqiyJZ.json new file mode 100644 index 0000000000000000000000000000000000000000..c60ad07894b527edfd3568d118480bdfcf18bd06 --- /dev/null +++ b/results/claude/1ZVqiyJZ.json @@ -0,0 +1,70 @@ +{ + "status": "ok", + "cost": null, + "time_sec": 15.55333399772644, + "data": { + "namedInsured": "John Doe and Susy Doe", + "policyNumber": "254H089SJ425", + "policyForm": "HO-3", + "inceptionDate": "2020-03-30", + "expirationDate": "2021-03-30", + "deductible": 1000, + "policyPremium": 1200, + "yearBuilt": 2010, + "construction": "Masonry Veneer", + "propertyAddress": "1427 Sample Drive Washington, DC 40000", + "agentName": "Frank Stallings", + 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