Question Bank Clarification-Based Multi-Turn QA Evaluation Dataset

#question answering #semantic clarification #multi-turn context understanding #educational question answering #question clarification #multi-turn learning dialogue

5000
0.3GB
JSON
CATL
MOBIUSI INC

Updated:2026-11-02

AI Analysis & Value Prop

This dataset combines question page content from digital question banks, including prompts, options, answers, and explanations, with multi-turn follow-up questions and responses about question meaning, terminology, option differences, and answer rationale. Structured clarification focuses, resolved interpretations, and reference conclusions support evaluation of semantic understanding, context retention, and response consistency in web-based question bank settings. It can help assess and improve educational QA systems and teaching assistants.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
question_page	object	Original page information directly available on the question webpage, including the prompt, options, answer, and explanation.
clarification_focus	string	The main clarification category inferred from the question page and multi-turn dialogue.
reference_resolution	object	The final reference answer and its rationale compiled from the question page and clarification dialogue.
clarification_summary	string	A combined summary of the user's questions, the assistant's responses, and the final clarification.
clarification_dialogue	array	User follow-up questions and corresponding responses about question meaning, terminology, option differences, or answer rationale.
resolved_interpretation	object	A structured clarification of the question conditions, terminology, options, and solution rationale derived from the dialogue.
context_consistency_assessment	object	An assessment of whether the responses consistently follow the question page, user follow-ups, and meanings established earlier in the dialogue.

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 dataset contain?: It includes question page content such as prompts, options, answers, and explanations, along with multi-turn follow-up questions and responses about question meaning, terminology, option differences, and answer rationale. Structured fields also capture clarification focus, summaries, reference conclusions, and context consistency assessments.

Which capabilities can this dataset evaluate?: It can evaluate multi-turn question answering, semantic understanding of questions, terminology and option disambiguation, answer rationale verification, and whether responses consistently follow the question page and earlier dialogue context.

How can I obtain the dataset?: Please follow the download, request, or delivery options listed on the product page. Before acquisition, check the available data format, field documentation, and delivery scope.

What are the licensing and usage terms?: The license and permitted uses are determined by the product page or the provider's formal agreement. Confirm the usage rights for question page content and related materials before training, evaluation, or commercial deployment.

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Cite this Work

@dataset{Mobiusi2026,
  title={Question Bank Clarification-Based Multi-Turn QA Evaluation Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/b4bbe71d62a1cecb039a6afc59795441?cate=3},
  urldate={2026-10-15},
  keywords={question bank QA dataset,multi-turn QA evaluation,educational semantic understanding,question clarification dialogue,context consistency evaluation,web question answering,answer rationale verification,educational AI},
  version={1.0}
}

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