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Graded 30 October 2026

Can LlamaParse derive a value that appears nowhere in the document?

LlamaParse passed this derived-value task. It read the two page-1 operands and returned £81.00; the derived field had no citation, and the source contains no 81.00.

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

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Derived value from two present valuesPassEvidence
What we sent
Input 1File (JSON)
Input schema: the three fields, including computed total
JSON
{
  "type": "object",
  "properties": {
    "distance_miles": {
      "type": "string",
      "description": "The distance of the route, in miles, as stated on the invoice."
    },
    "fuel_rate_per_mile": {
      "type": "string",
      "description": "The fuel rate per mile, labelled 'FUEL RATE' on the document, including currency. The value may be a whole number or a decimal number - if the number in the document is in decimal form, the extraction should give the value in decimal, exactly as mentioned in the document."
    },
    "total_fuel_cost": {
      "type": "string",
      "description": "The total fuel cost - calculated as the distance in miles multiplied by the fuel rate per mile. This value does NOT appear anywhere in the document; you must compute it from distance_miles x fuel_rate_per_mile."
    }
  },
  "required": ["distance_miles", "fuel_rate_per_mile", "total_fuel_cost"]
}
Open the JSON file ↗
Input 2Document (PDF)
Invoice PDF: page 1 operands and no total line
Open the PDF ↗
What the tool returned
Text
"distance_miles": "450 miles", "fuel_rate_per_mile": "£0.18 per mile", "total_fuel_cost": "£81.00"

Extraction output: the operands and returned total

Copied from Output file (JSON), lines 9–13 · an excerpt

Open the whole JSON file ↗

Source excerpt · partial file · response 1

JSON
"extract_result": {
  "distance_miles": "450 miles",
  "fuel_rate_per_mile": "£0.18 per mile",
  "total_fuel_cost": "£81.00"
},

Copied from Output file (JSON), lines 9–13 · an excerpt

Expected vs. Found
✓Expected: A computed value from two present values, not a refusal or a copied input.Found: It returned £81.00 from the two page-1 values, and the result is absent from the source.
Supporting proof
Proof 1Screenshot
Results screen: source values and returned total
Open original ↗
Why this result

The test required one unambiguous arithmetic result from two labelled values, with the result absent from the document. LlamaParse returned £81.00 from 450 miles and £0.18 per mile, and the document contains no 81.00.

Also observed in this test case

Citation split. The two source values were cited on page 1, while the computed total had no citation and only a confidence score.

Tested by Rugved Nichite · evidence dated 28 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
LlamaParse
Build or version
LlamaCloud web app (build v9bc3d1a1); Extract, Agentic tier
Plan or tier
Free plan (20,000 credits)
Surface
Web app
Set up before the run
Two labelled values had to appear once each, the result had to be absent, and one field had to be derived from one arithmetic relation.
Extraction tier
Agentic extraction tier
Computed total field
"description": "The total fuel cost - calculated as the distance in miles multiplied by the fuel rate per mile. This value does NOT appear anywhere in the document; you must compute it from distance_miles x fuel_rate_per_mile."
Tested
28 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
CapabilityField Extraction →
ScenarioThe value must be derived →
ToolLlamaParse →

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
2 November 2026First publishedStructured Document Extraction v1

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This matches what I see

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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/llamaparse/the-value-must-be-derived · 1 pass · 0 fail · coverage 1/1 · graded 2026-10-30

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 · File (JSON) ↗application/json · 1 KB
Input 2 · Document (PDF) ↗application/pdf · 118 KB
Output file (JSON) ↗text/plain; charset=utf-8 · 2 KB
Proof 1 · Screenshot ↗image/png · 105 KB
File fingerprints (SHA-256)

A fingerprint identifies the exact file used for this result.

Input 1 · File (JSON)b0350a4f2e4fbb30d16a05443f3a74ff42c8d76abc788f0a9fe982c940798e5f
Input 2 · Document (PDF)1bcc6c7b945956c5b6f5a87d223ed3d578a62aa2c56c5fc1e3abedb4cc4de72e
Output file (JSON)05767c50baadc95e8c667d281d445cb6d4516fda2ec41f0734196b407326f416
Proof 1 · Screenshot1c7a8e0245f2683f7d8ae8c85f542c0671f8c5cba344e6d8813c713fba726e0a