Corpus-NZ/Math-Expanded

Massive Step-by-Step Mathematics Instruction Dataset

Dataset Description

This is a 60GB, highly knowledge-dense dataset designed to teach Large Language Models (LLMs) rigorous mathematical reasoning.

Unlike standard math datasets that only provide the final answer, this dataset emphasizes Chain-of-Thought (CoT) reasoning. Every single row contains a detailed, step-by-step breakdown of how to arrive at the solution, making it ideal for supervised fine-tuning (SFT) to improve an LLM's logical reasoning capabilities.

Dataset Structure

The dataset is stored as a single CSV file (math_dataset.csv) and contains two columns:

• —prompt: The mathematical question or instruction.
• —completion: The step-by-step reasoning and final answer.

Mathematical Domains Covered

The dataset contains hundreds of millions of examples spanning 10 core mathematical disciplines:

1. 1.Arithmetic: Long division with rigorous verification (quotient and remainder proofs).
2. 2.Algebra: Quadratic equations utilizing the discriminant (handling both real and complex roots).
3. 3.Calculus: Indefinite integration using the power rule, and derivatives using the chain rule.
4. 4.Linear Algebra: 2x2 matrix multiplication with explicit dot-product calculations.
5. 5.Geometry: Pythagorean theorem calculations for right-angled triangles.
6. 6.Fractions: Addition of fractions requiring Least Common Multiple (LCM) calculation and simplification via Greatest Common Divisor (GCD).
7. 7.Statistics: Calculation of mean, population variance, and standard deviation.
8. 8.Trigonometry: Exact trigonometric values derived from the unit circle and special triangles.
9. 9.Logarithms: Evluation of logarithms by converting between logarithmic and exponential forms.

License

Open Data Attribution Training Disclosure License (ODATL‑1.0)