pith:JMKYAYSQ
Unlocking Crowdsourcing for Ontology Matching Validation
A crowdsourcing system with three quality mechanisms enables scalable validation of the many ontology mappings produced by large language models.
arxiv:2605.12226 v2 · 2026-05-12 · cs.IR
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\pithnumber{JMKYAYSQQL32PQMN3TGBTUDNAH}
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Claims
We demonstrate that our crowdsourcing system can be integrated with state-of-the-art OM systems to enable human-in-the-loop validation. Two real-world use cases illustrate the effectiveness of our crowdsourcing system.
The three proposed mechanisms (differential trustworthiness, coherence pre-filling, and time-dependent beliefs) are sufficient to ensure high-quality crowdsourced validations for ontology matching without introducing new errors or biases.
A crowdsourcing system using differential trustworthiness, coherence pre-filling, and time-dependent beliefs supports human-in-the-loop validation for LLM-based ontology matching, as shown in two real-world cases.
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| First computed | 2026-05-20T02:05:45.929903Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
4b1580625082f7a7c18ddccc19d06d01e6e243150f7c3a8aaf8bace5e9f0282b
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/JMKYAYSQQL32PQMN3TGBTUDNAH \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 4b1580625082f7a7c18ddccc19d06d01e6e243150f7c3a8aaf8bace5e9f0282b
Canonical record JSON
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