The certification field merged three content types — certifications, skills, and references — into one extracted value instead of separating them.
What was measured
Noise in output
Does it add incorrect or hallucinated fields?
decisive for this rankingtransformation
Incorrect or hallucinated fields mean the resume parser is not producing reliable structured data, which is central to the job. (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
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
Output — unretouched
Also checked on this input — same tool, 3 other criteria
Accuracy✗ FailedThe second employer name was merged with the role title, returning 'Junior Developer XYZ InfoTech' instead of just 'XYZ InfoTech'.Field coverage✗ FailedOnly the B.E. education entry was extracted; the visible 12th and 10th entries were omitted from the parsed output.Messy resume handling✓ WorkedOn the poorly formatted resume, the parser still recovered the main structure instead of failing outright, including contact data, experience, education, skills, and hobbies.
Provenance
- Observation
- 53baa4b9-f590-4704-af4d-1715255eb658
- 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: "hireability",
scenario: "resume-parsing"
})MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 5 other tools
measured on Noise in output
Affinda✗ FailedThe skills output includes hallucinated taxonomy noise, such as Business Education, that does not appear in the resume.CVParserPro✗ FailedThe parser hallucinated unsupported month values in the work date range, expanding 2019–2021 into January 2019 to December 2021.Extracta.ai⚠ StruggledEmits a blank Languages item when the resume has no languages section, leaving an empty placeholder instead of omitting the field.HrFlow◐ MixedThe messy parse can bleed location text into a task item, prepending 'Pune' to one extracted responsibility.Skima AI✗ FailedThe messy-resume skills block was collapsed into a single concatenated string with no separators, making the field hard to reuse downstream.
This evidence is published in
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com