Home/Education & Training/Professional Certification Exam Cross-Reference Question Answering Dataset
Professional Certification Exam Cross-Reference Question Answering Dataset
#Cross-Document Retrieval #Multi-Hop Question Answering #Retrieval-Augmented Generation #Evidence Attribution #Professional Exam Preparation #Regulatory Reference Lookup #Textbook Question Answering #Intelligent Learning Assistants
- 6500
- 0.4GB
- JSON
- CATL
MOBIUSI INC
Updated:2026-11-04
AI Analysis & Value Prop
Designed for professional certification exam questions that require information from multiple sources, this dataset provides questions, reference materials such as exam textbooks and regulations, synthesized answers, reasoning notes, and supporting evidence with source locations. By bringing together knowledge scattered across documents, it supports the development and evaluation of retrieval-augmented systems that answer with verifiable evidence. Typical uses include open-book question answering, multi-document retrieval, and evidence-grounded response generation.
Dataset Insights
Sample Examples
{}
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| answer | string | A synthesized answer based on information from the supplied reference materials. |
| evidence | array | The specific source passages and locations that substantiate the answer. |
| question | string | The original professional examination question to be answered using the supplied reference materials. |
| reference_materials | array | Source materials available for answering the question, including relevant content and source-location details. |
| synthesis_rationale | string | A concise explanation of how information from multiple references was combined to produce the answer. |
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 include?
- Each sample centers on a professional certification exam question and includes the question text, reference materials, a synthesized answer, an explanation of how sources were combined, and supporting passages with source locations.
- Which capabilities can this dataset support?
- It can support training and evaluation for cross-document retrieval, multi-hop question answering, retrieval-augmented generation, evidence-grounded answer generation, and source attribution, especially when answers require information from textbooks and regulations.
- How is evidence for each answer presented?
- Samples provide the relevant source content and location, along with a concise synthesis rationale describing how information from different references supports the answer. This makes responses easier to verify and assess for traceability.
- How can I obtain the dataset, and what are the licensing terms?
- Check the dataset product page or contact the provider for access options. Permitted uses, commercial rights, and redistribution restrictions are governed by the applicable license and product terms.
Can't find the data you need?
Post a request and let data providers reach out to you.
Get this Dataset
Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Professional Certification Exam Cross-Reference Question Answering Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/35d9645a1e127417f7ac2c9b9e5a2d77?dataset_scene_id=7},
urldate={2026-10-26},
keywords={professional exam QA dataset,cross-document question answering,multi-document QA,retrieval augmented generation dataset,open-book question answering,certification exam AI,evidence localization,knowledge retrieval training},
version={1.0}
}Using this in research? Please cite us.
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder