Payroll and Overtime Constraint Verification Dataset

#Constraint Verification #Payroll Calculation Validation #Calculation Difference Analysis #RLVR Reward Evaluation #Payroll Processing #Overtime Pay Auditing #HR Rule Verification #Payroll Automation
Records
5880
Size
0.4GB
Format
JSON
Provider
MOBIUSI INCMOBIUSI INC
Updated
v1.02026-11-04
AI Analysis & Value Prop

Each JSON record captures a payroll period, regular and overtime hours, pay components, and the applicable human-resources rule version, alongside a candidate calculation, an independently computed result, and individual constraint checks. The records support training and evaluating models that verify payroll and overtime calculations against stated rules, with deterministic checks providing auditable reward signals. They are suited to human capital management, payroll automation, and research on reinforcement learning with verifiable rewards.

Overview

Dataset Insights

Preview

Sample Examples

sample.json
{}

Schema

Technical Specifications

file_namestringFile name
is_validbooleanWhether all required payroll and overtime constraints pass within the configured comparison tolerance.
pay_periodobjectThe date range and payroll frequency associated with the record.
work_hoursobjectRecorded regular, overtime, and total hours for the payroll period.
reward_scorenumberThe deterministic reward assigned to the verification result, typically one for a valid calculation and zero otherwise.
overtime_ruleobjectThe applicable human-resources rule version and parameters for overtime pay.
pay_componentsobjectSource rates and other amounts used in the candidate payroll calculation.
constraint_checksobjectIndividual deterministic checks comparing the recorded data and candidate results with the applicable payroll constraints.
expected_calculationobjectPayroll amounts independently computed from the source inputs and overtime rule.
candidate_calculationobjectThe proposed monetary results to be checked against the recorded hours, pay components, and applicable rule.
calculation_differencesobjectSigned differences between candidate and independently computed amounts, expressed in the record currency.

Trust

Compliance Statement

Authorization Type

Proprietary - Commercial AI Training License (No Redistribution)

Commercial Use

Requires exclusive subscription or authorization contract (monthly or per-invocation charging)

Privacy and Anonymization

No PII, no real company names, simulated scenarios follow industry standards

Compliance System

Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

FAQ

Frequently Asked Questions

What does the dataset contain?
Each record covers a payroll period, regular and overtime hours, pay components, the applicable overtime rule, candidate and expected calculations, constraint checks, calculation differences, overall validity, and a reward score.
How can a candidate payroll calculation be verified?
Compare the candidate calculation with the record's inputs, applicable rule, and independently computed result. Review the individual constraint checks, monetary differences, and overall validity. Use the rule parameters and comparison tolerance specified in each record.
Which training and evaluation tasks does it support?
It supports payroll and overtime calculation verification, rule-compliance evaluation, constraint checking, and reinforcement learning with verifiable rewards (RLVR). Confirm that the rules used in the records match the intended business context.
How can I obtain the data, and what are the license terms?
Check the dataset product page or the supplier's designated channel for access details. Before use, review the applicable license, permitted uses, and redistribution restrictions. Specific access methods and license terms are not provided here.

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Cite this Work

@dataset{Mobiusi2026,
  title={Payroll and Overtime Constraint Verification Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/e67bae2b68a615895ee3587e11080f22?dataset_scene_id=3},
  urldate={2026-10-26},
  keywords={payroll calculation dataset,overtime pay verification,payroll constraint checks,wage calculation validation,HR rules data,RLVR training data,verifiable reward reinforcement learning,payroll automation},
  version={1.0}
}

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