Produces a usable JSON result even on the messy resume, with the important sections still readable and structured.
What was measured
Output quality
Is the parsed result clean, complete, and usable overall?
decisive for this rankingtransformation
The whole point is usable structured extraction; clean, complete, usable output is the core measure of success. (3 of 3 judges)
What was given, what came back
Test input: Messy real-world resume — John Kumar · pdf · group: resume-parsing
Input — what we sent
Research media screenshot 202026 05 05 20124544.png
Messy real-world resume — John Kumar
A poorly formatted, inconsistent real-world resume for John Kumar, used to test robustness against noisy structure, inconsistent dates, and mixed-content sections.
Why this input is hard
- · messy formatting robustness
- · section detection fallback
- · inconsistent date parsing
- · soft-skills extraction
- · noise and hallucination control
Also checked on this input — same tool, 5 other criteria
Accuracy◐ MixedPreserves the education marks text verbatim, including the unnormalised '72 percent marks' value instead of converting it to a cleaner percentage format.Accuracy◐ MixedReturns both certification names in lowercase exactly as written, with no capitalization normalisation applied.Field coverage✓ WorkedStill covers the main resume fields on the messy input: name, email, phone, experience, education, skills, and certifications.Messy resume handling✓ WorkedHandles the noisy, inconsistent layout without crashing and still extracts the main sections.Noise in output⚠ StruggledEmits a blank Languages item when the resume has no languages section, leaving an empty placeholder instead of omitting the field.
Provenance
- Observation
- 5ecc3f0c-d625-475d-8251-0b44a2f88196
- Evidence run
- cbbef4db-964c-49fa-a57f-a2977822bdfc
- Study
- Parse resumes into structured data using an API
- Research task
- 86b9jm30n
- Tested at
- not recorded
- Source
- first-party
- Evidence state
- verified
- Proof shown
- input + output shown
- Cost / latency
- not captured
- Repeat run
- not captured
- Tester
- not captured
The last three rows are honest blanks, not placeholders — our capture has no field for them yet.
Query this
get_evidence({
tool: "extracta-labs",
scenario: "resume-parsing"
})MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 5 other tools
measured on Output quality
Airparser◐ MixedProduces usable JSON from noisy text, but the skills section collapses into one long string and one education record keeps an unnormalized marks value.HrFlow◐ MixedThe messy-resume output is moderate overall: contact and basic structure survive, but the result is incomplete for soft skills, certifications, and task detail.LlamaParse✓ WorkedThe messy-resume output was the richest and cleanest among the tested tools, with all 3 education entries, all 14 skills, both certifications, hobbies, and a boolean references field.Parseur⚠ StruggledSkills were returned as one unstructured, space-separated string with no array structure or delimiters, making them hard to split programmatically.Skima AI⚠ StruggledThe messy-resume output degraded sharply: responsibilities became a run-on string, skills collapsed into one concatenated line, and references/certifications/hobbies were missing.
This evidence is published in
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com