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Graded 9 November 2026

Can Docsumo extract a repeated set from one page?

Docsumo extracted the invoice’s three line items with the right values attached to each item. It excluded the subtotal, VAT and total rows from the extracted set.

1 of 1 test case passed

Every test case in this scenario has a result.

Pass rate100%1 of 1 gradable
Coverage1 of 1test case with a result
1PassDid everything it was expected to do.
0FailNo test case failed.
0Not gradableEvery result here could be graded.
0UntestedEvery test case in this scenario has a result.
The pass rate is a summary. The evidence is the test case below: what we sent, what we checked, what the tool returned, and the proof.

The test case

Each test case is judged on its own: Pass, Fail, Not gradable, or Untested. The scenario result above is based on this test case.

Repeated set with correct associationPassEvidence
What we sent
Input 1Document (PDF)
Input PDF: the invoice’s three item rows and the totals beneath them
Open the PDF ↗
Input 2File (JSON)
Extraction schema: one line item table with five columns
JSON
{
  "Table": {
    "line_items": {
      "type": "table",
      "columns": [
        { "name": "description" },
        { "name": "item_code" },
        { "name": "quantity" },
        { "name": "unit_price" },
        { "name": "amount" }
      ]
    }
  }
}
Open the JSON file ↗
What the tool returned
JSON
{
  "description": {
    "position": [159, 5058, 1495, 5085],
    "value": "Dosing pump, 240V",
    "review_required": false,
    "confidence": 1
  },
  "item_code": {
    "position": [159, 5058, 1495, 5085],
    "value": "DP-2210",
    "review_required": false,
    "confidence": 1
  },
  "quantity": {
    "position": [159, 5058, 1495, 5085],
    "value": 2,
    "review_required": false,
    "confidence": 1
  },
  "unit_price": {
    "position": [159, 5058, 1495, 5085],
    "value": 340,
    "review_required": false,
    "confidence": 1
  },
  "amount": {
    "position": [159, 5058, 1495, 5085],
    "value": 680,
    "review_required": false,
    "confidence": 1
  }

Extraction JSON: three item rows with descriptions, codes, quantities, unit prices and amounts

Copied from Output file (JSON), lines 5–60

Open the JSON file ↗
JSON
{
  "description": {
    "position": [158, 5129, 1493, 5149],
    "value": "Chemical feed tubing, 10m coil",
    "review_required": false,
    "confidence": 1
  },
  "item_code": {
    "position": [158, 5129, 1493, 5149],
    "value": "CT-1040",
    "review_required": false,
    "confidence": 1
  },
  "quantity": {
    "position": [158, 5129, 1493, 5149],
    "value": 3,
    "review_required": false,
    "confidence": 1
  },
  "unit_price": {
    "position": [158, 5129, 1493, 5149],
    "value": 48,
    "review_required": false,
    "confidence": 1
  },
  "amount": {
    "position": [158, 5129, 1493, 5149],
    "value": 144,
    "review_required": false,
    "confidence": 1
  }

Copied from Output file (JSON), lines 62–117

JSON
{
  "description": {
    "position": [159, 5194, 1495, 5215],
    "value": "Inline flow sensor",
    "review_required": false,
    "confidence": 1
  },
  "item_code": {
    "position": [159, 5194, 1495, 5215],
    "value": "FS-3302",
    "review_required": false,
    "confidence": 1
  },
  "quantity": {
    "position": [159, 5194, 1495, 5215],
    "value": 1,
    "review_required": false,
    "confidence": 1
  },
  "unit_price": {
    "position": [159, 5194, 1495, 5215],
    "value": 215,
    "review_required": false,
    "confidence": 0.5
  },
  "amount": {
    "position": [159, 5194, 1495, 5215],
    "value": 215,
    "review_required": false,
    "confidence": 0.5
  }

Copied from Output file (JSON), lines 119–174

Expected vs. Found
✓Expected: Return all three genuine items once, keeping each description, item code, quantity, unit price and amount with the correct item.Found: Invoice and output each show three items: dosing pump, 2 at 340, amount 680; chemical feed tubing, 3 at 48, amount 144; inline flow sensor, 1 at 215, amount 215.
Supporting proof
Proof 1Screenshot
Results screenshot: the same three extracted rows in a single table
Open original ↗
Why this result

The requirement was to preserve which values belong to which item, not just count rows. The configured columns matched the invoice, and no item was dropped, duplicated or given another item’s values.

Also observed in this test case

Sensor price confidence. The inline flow sensor’s unit price and amount were correct at 215 each, yet received confidence 0.5. Every other field received 1.

Tested by Rugved Nichite · evidence dated 5 October 2026

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.

Software that produced the output
Docsumo
Build or version
Not exposed by the hosted product
Surface
Web app
Set up before the run
The task was to extract the invoice’s three item rows on page 3, keeping five fields together: description, item code, quantity, unit price and amount. Subtotal, VAT and total rows were not items.
Table schema
One table field, line_items, with columns description, item_code, quantity, unit_price and amount
Plan
Free Plan
Tested
5 October 2026 · Rugved Nichite

How this scenario is graded

How we decide Pass, Fail and Not gradable. The same rules apply to every tool tested on this scenario.

How results are decided

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.

The rules
  • 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 test case's result says which one 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 test case's result 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.

LevelNameScope
BenchmarkStructured Document Extraction →19 scenarios · 10 tools
CapabilityNested & Repeated Fields →
ScenarioA repeated set of records →
ToolDocsumo →

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.

from the publication record
10 November 2026First publishedStructured Document Extraction v1

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This matches what I see

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We have fixed this

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Vendor notice →
Filed against this evidenceNothing yet. Challenges, counter-evidence and fix notices appear here with their outcome, and stay on the page after they are resolved.
Cite this result
aidemos.com/benchmarks/structured-document-extraction/results/docsumo/a-repeated-set-of-records · 1 pass · 0 fail · coverage 1/1 · graded 2026-11-09

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.

Input 1 · Document (PDF) ↗application/pdf · 176 KB
Output file (JSON) ↗text/plain; charset=utf-8 · 4 KB
Input 2 · File (JSON) ↗application/json · 0 KB
Proof 1 · Screenshot ↗image/png · 91 KB
File fingerprints (SHA-256)

A fingerprint identifies the exact file used for this result.

Input 1 · Document (PDF)89fb14d7c0897bbfef47ffa3aa3930ee7eccf62c8a9430710d1906598c9bdfec
Output file (JSON)63969d2292ba9159f1f903a2de6794494933e901e432864aa97598c8215b0e7d
Input 2 · File (JSON)d2db0f340ed41c3b16073500d85ac73bd3a927c9df84c7e6a738ddd092ee7fa5
Proof 1 · Screenshot4b8bffcefc2644daa4151784ce322982a0b5af63cb50a35b89e5d112851302ba