Can Nanonets extract data from a document mixing digital and scanned pages?
Nanonets handled the mixed digital-and-scanned document in this test. It returned the five requested values, including the two that appear only in the scanned page image, and kept the digital-page values unchanged. The JSON output itself does not show per-value page provenance.
1 of 1 test case passed
Every test case in this scenario has a result.
The test case
Each test case is judged on its own: Pass, Fail, Not gradable, or Untested. The scenario result above counts this row.
Values on both digital and scanned pagesPassEvidence
“Extract the following fields from this document and return the result as JSON…”
{ "invoice_reference": "HIS-4402", "order_reference": "FWT-PO-2291", "vehicle_registration": "LR19 KVM", "received_by": "J. Whitlock", "total_due": "£1,246.80" }
Copied from Proof 1 · Output file (JSON), lines 1–7
Open the JSON file ↗Its contents are printed above, under What the tool returned.
Open the JSON file ↗| ✓ | Expected: All requested values returned, including scanned-page values, with digital-page values left exact.Found: All five requested values are returned; the scanned-page values match verbatim and the digital-page values stay unchanged. |
The output was checked against the document page by page. The two values found only in the rendered scanned page came back verbatim, the digital-page values stayed exact, and no extra values appeared.
Source links shown. Each value shows a chain-link icon, and the download menu includes JSON with sources.
Configuration and setup
How this tool was set up for the run and what the test needed in place. Each row is a fact from the run's records; a fact the records do not hold is left out, not guessed.
How this scenario is graded
How we decide Pass, Fail and Not gradable. The same rules apply to every tool tested on this scenario.
Each test case gets one result per tool: Pass, Fail or Not gradable. A test case we haven't run yet shows Untested. There are no partial results.
- Pass: the tool did everything the test expected, and nothing it said contradicts the correct answer.
- Fail: at least one expected behaviour clearly didn't happen; the row says which and quotes the tool.
- Not gradable: our evidence couldn't settle the outcome (for example a record we needed is missing). It is never counted as a fail, and the row says what's missing.
Where this sits in the benchmark
This page is one cell of a larger study: one tool, one scenario. Only this benchmark's frame appears here.
| Level | Name | Scope |
|---|---|---|
| Benchmark | Structured Document Extraction → | 19 scenarios · 10 tools |
| Capability | OCR → | |
| Scenario | A document mixing digital and scanned pages → | |
| Tool | Nanonets → |
Global scenario definition → · Global capability definition → · Nanonets product page →
History of this result
What has happened to this result since it was first published. Runs and grades are never overwritten: a retest or a re-grade publishes a new result and keeps the earlier one readable.
Act on this result
Nothing filed here edits the run or the grade. A challenge opens a review, and a review can produce a new run or a re-grade — which becomes the current result and leaves this one in the history.
You run the same kind of test against your own setup and get the same behaviour.
Agree →Yours behaves differently. Tell us what you got, with a screenshot if you have one.
Disagree →Something here is wrong — a reference value, a transcription, a grade.
Report an issue →Tell us what changed and we schedule a rerun of the failing test case. The old result stays as history.
Vendor notice →The same record is available as structured data through the AI Demos MCP server, with the counts, the coverage and every per-test-case reason carried as fields.
Verify the proof files
These files support this result. Open a file to inspect the original evidence.
File fingerprints (SHA-256)
A fingerprint identifies the exact file used for this result.