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Graded 30 October 2026

Does LlamaParse keep corrected data moving downstream?

LlamaParse did not carry the corrected receipt_number RHS-99999 downstream on the Extract screen. On the Free plan, the agentic four-field setup stayed read-only, and the downloaded JSON and opened export still showed receipt_number RHS-70234 with subtotal, tax, and total_due.

1 of 1 test case failed

Every test case in this scenario has a result.

Pass rate0%0 of 1 gradable
Coverage1 of 1test case with a result
0PassNo test case passed.
1FailMissed at least one thing it was expected to do; the reason and proof are with each test case below.
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.

Correction survives the delivery pathFailEvidence
What we sent
InputDocument (PDF)
Source receipt with the original receipt number and totals
Open the PDF ↗
What the tool returned
JSON
{
  "data": {
    "receipt_number": "RHS-70234",
    "subtotal": "$85.00",
    "tax": "$5.10",
    "total_due": "$90.10"
  },
  "extract_metadata": {

Downloaded JSON export with citations for the four extracted fields

Copied from Output file (JSON), lines 1–8

Open the JSON file ↗
Expected vs. Found
✗Expected: The delivery path carries the corrected receipt number.Found: The exported JSON and results panel still show receipt_number RHS-70234, and the panel offers no edit control; RHS-99999 does not appear.
Supporting proof
Proof 1Screenshot
Results screen with the fields and download control
Open original ↗
Proof 2Screenshot
Opened JSON export with receipt number highlighted
Open original ↗
Why this result

The delivery path had to carry the corrected receipt number, but the results panel and downloaded JSON still showed the original number and offered no edit control. That leaves the required correction absent, so the case fails.

Also observed in this test case

Export completeness. The downloaded JSON carries all four extracted values and per-field citations.

Read-only flags. Three money fields sit below 90%, while receipt number is above it; the panel still offers no edit control.

Tested by Rugved Nichite · evidence dated 13 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 v09046f5c); Extract, Agentic tier
Plan or tier
Free plan (20,000 credits)
Surface
Web app
Set up before the run
The corrected record had to already exist, then the same record had to be read back through the product's own delivery path.
Extraction schema
receipt_number, subtotal, tax, total_due
Tested
13 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

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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
29 October 2026First publishedStructured Document Extraction v1
30 October 2026Taken down
The page left the site; nothing was deleted.
2 November 2026Republished

Act on this result

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This matches what I see

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Agree →
This does not match

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Point out an issue

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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/llamaparse/corrected-data-goes-downstream · 0 pass · 1 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 · Document (PDF) ↗application/pdf · 54 KB
Proof 1 · Screenshot ↗image/png · 150 KB
Output file (JSON) ↗text/plain; charset=utf-8 · 3 KB
Proof 2 · Screenshot ↗image/png · 69 KB
File fingerprints (SHA-256)

A fingerprint identifies the exact file used for this result.

Input · Document (PDF)a96bbe1c5b22336e7b54169baf72b85e45eabf1312cd293a1821017b52fa85f7
Proof 1 · Screenshot7d0bf2bd3cb8f89a56b8d7b6cd836a9345363f9bf2f0df9d5cc737f934975761
Output file (JSON)3a7cfe20b9688699abbcea0d2145b4408c480c311ce89d021170eae7512658e5
Proof 2 · Screenshot1d26fb2fc8fcc3697299753a3c31429f440c159ffb70b30f0983932a0bd5f8d9