Professional Exam Exception and Negation Rules QA Benchmark

#question answering #exception rule identification #evidence-based rule reasoning #professional certification exam preparation #exam rule interpretation #exception and negation analysis

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CATL
MOBIUSI INC

Updated:2026-11-05

AI Analysis & Value Prop

This benchmark focuses on exception conditions, applicability limits, and negated statements in professional exam rules. Each record provides a question, reference answer, source context, supporting evidence, and evidence location. It highlights details that can be overlooked when general rules dominate retrieval, making it useful for evaluating whether retrieval-augmented generation systems can find the relevant provisions and answer accurately based on the source.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
question	string	The professional exam question to be answered.
gold_answer	string	The correct answer grounded in the source context.
rule_feature	string	The primary rule detail tested by the question.
evidence_quote	string	The exact source wording that supports the answer, including any relevant exception, limitation, or negation.
source_context	string	The source rule or passage needed to answer the question.
evidence_location	string	A locator for the supporting evidence, such as a document title, article, section, page, or paragraph.

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

Frequently Asked Questions

What does the benchmark contain?: Each record centers on a question about a professional exam rule and includes the relevant source context, a reference answer, the supporting source wording and its location, and the primary rule feature being tested.

Which capabilities does it evaluate?: It focuses on whether a system can retrieve exception conditions, applicability limits, and negated statements; distinguish special cases from general rules; and answer accurately using the source evidence.

What are suitable use cases?: Use it to develop and evaluate retrieval-augmented generation systems, open-book question-answering models, and educational QA tools for professional exam preparation. It is also suitable for testing rule-detail retrieval and answer grounding.

What are the dataset size and licensing terms?: The available information does not specify the number of records, exact data format, or license terms. Refer to the product page and accompanying license agreement, and verify the permitted scope before use.

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Cite this Work

@dataset{Mobiusi2026,
  title={Professional Exam Exception and Negation Rules QA Benchmark},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/26d1d4b8de08ae5801b6d66c80aa8364},
  urldate={2026-10-22},
  keywords={professional exam QA benchmark,exam rule exceptions,negation rule questions,professional exam dataset,RAG evaluation data,open-book QA benchmark,evidence localization,rule detail retrieval},
  version={1.0}
}

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