SAT Math Concepts and Formula Evidence Retrieval Dataset

#information retrieval #question answering #evidence retrieval #SAT math concept retrieval #mathematical formula lookup #theorem-based problem solving

5000
0.5GB
JSON
CATL
MOBIUSI INC

Updated:2026-10-19

AI Analysis & Value Prop

Designed for SAT math questions, this dataset pairs original question text and structured conditions with relevant concept definitions, formulas or theorems, applicability conditions, solution links, and source materials. Its JSON records include consolidated retrieval text and an evidence quality score ranging from 0 to 1, supporting workflows that retrieve reliable mathematical grounds for each question. Typical uses include RAG knowledge retrieval, evidence-backed explanations, and retrieval system development and evaluation.

Dataset Insights

Sample Examples

{}

Technical Specifications

Field	Type	Description
file_name	string	File name
question_text	string	The complete original SAT math question, including its prompt, requested task, and mathematical expressions.
retrieval_text	string	Evidence text combining question conditions, concepts, formulas or theorems, applicability conditions, and solution links for RAG retrieval and generation.
evidence_quality	number	A composite score from 0 to 1 assessing mathematical evidence accuracy, source traceability, and relevance to solving the question.
source_knowledge	string	Original materials used to extract or verify mathematical concepts, definitions, formulas, theorems, and their sources. May include textbooks, official resources, or curated knowledge excerpts.
solution_relation	object	Annotations describing how the question conditions and mathematical evidence correspond to the solution process.
knowledge_evidence	object	Concept definitions, formulas or theorems, applicability conditions, and reliable source evidence relevant to solving the question.
structured_conditions	object	Structured information extracted from the question text, such as question type, given conditions, objective, and answer choices.

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?: Records are organized around SAT math questions and include question text, structured conditions, source knowledge materials, mathematical evidence, solution links, retrieval text, and an evidence quality score.

What does the evidence quality score indicate?: The score ranges from 0 to 1 and reflects evidence accuracy, source traceability, and relevance to solving the question. It can help with filtering and evaluation, but important instructional or assessment use should still involve checking the original sources and evidence.

What are the intended use cases?: The dataset supports SAT math RAG retrieval and generation, knowledge grounding, evidence-backed solution explanations, and retrieval workflow development and evaluation. Its structured conditions and retrieval text can also support matching questions to concepts, formulas, or theorems.

How can I access the data, and what are the licensing terms?: The data is organized in JSON; refer to the product page or provider's license for specific download methods, availability, and usage terms. Any textbooks, official materials, or other referenced sources remain subject to their applicable copyright and usage requirements.

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Cite this Work

@dataset{Mobiusi2026,
  title={SAT Math Concepts and Formula Evidence Retrieval Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/978e10b8a93cc6c184790b670a704d3a?dataset_scene_id=7},
  urldate={2026-10-14},
  keywords={SAT math dataset, SAT math questions, math formula retrieval, mathematical evidence, RAG training data, evidence retrieval, structured math problems, knowledge grounding},
  version={1.0}
}

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