Datasets:
pretty_name: Open Reason
license: apache-2.0
task_categories:
- text-generation
- question-answering
language:
- en
tags:
- reasoning
- coding
- mathematics
- science
- education
- provenance
- evaluation
size_categories:
- 1K<n<10K
configs:
- config_name: coding
data_files:
- split: train
path: data/release/coding.parquet
- config_name: reasoning
data_files:
- split: train
path: data/release/reasoning.parquet
- config_name: science
data_files:
- split: train
path: data/release/science.parquet
- config_name: mathematics
data_files:
- split: train
path: data/release/mathematics.parquet
- config_name: human
data_files:
- split: train
path: data/release/human.parquet
- config_name: education
data_files:
- split: train
path: data/release/education.parquet
- config_name: core
data_files:
- split: train
path: data/release/core.parquet
- config_name: verified
data_files:
- split: train
path: data/release/verified.parquet
- config_name: all
data_files:
- split: train
path: data/release/all.parquet
Dataset Card for Open Reason
An open, verified dataset for coding, science, mathematics, and human reasoning.
- Dataset: https://huggingface.co/datasets/theworker02/open-reason
- Small model: https://huggingface.co/theworker02/open-reason-small (~1.3M CPU causal LM; not 1B)
- Medium model: https://huggingface.co/theworker02/open-reason-medium (~13.9M CPU causal LM; not 1B)
- GitHub: https://github.com/theworker02/open-reason
- Site: https://theworker02.github.io/open-reason/
Open Reason is a provenance-aware corpus plus a reproducible pipeline. It is intended for training and evaluating systems on coding, mathematics, science, structured decision-making, and human problem solving.
Open Reason does not use Reddit as a data source. Quora is not a primary source of truth. Case study: docs/why-not-reddit.md.
Supported tasks
- Code generation, debugging, SQL, systems simulations, packaging, and defensive validation
- Structured reasoning (planning, constraints, causal and temporal problems)
- Mathematical problem solving with symbolic or integer checks
- Scientific calculation, modeling, and experimental-design counts
- Teaching, explanation, and synthesis (human-authored)
- Curriculum-aligned education tasks with concept ids and education levels
Languages
Prompts and solutions are English. Verified coding languages in v1.4.0: Python, SQL, JavaScript (when the sandbox can run them). Other languages appear as original concept tasks and are not marked verified.
Source information
| Kind | How to recognize | v1.4.0 |
|---|---|---|
| Human-authored | provenance.source_type = human_authored |
Teaching, synthesis, qualitative items |
| Synthetic | provenance.source_type = synthetic plus generator |
Math, science, most reasoning/coding, curriculum |
| Source-derived | open_source / community with provenance URL/commit |
GitHub-permissive original tasks; Stack Overflow seeds (verbatim=false) |
| Verified | quality.verified = true and verification.passed = true |
Coding sandbox, sympy, numeric, constraint checks |
| Unverified | quality.verified = false |
Reviewed teaching and misconception items (tier A) |
Never treat synthetic rows as human-authored. Never treat unverified rows as executed.
Licensing
Original dataset content and pipeline: Apache 2.0. Per-row provenance.license_spdx is authoritative for upstream GitHub/SO snippets.
Provenance
See docs/provenance.md. Unknown origin requires unknown_reason.
Preprocessing
Unicode NFKC, newline normalization, trimmed lists, task_type slugging. Meaning is not paraphrased.
Deduplication
Exact SHA-256 of canonical fields, normalized prompt/answer hashes, 64-bit simhash. Stats in the release manifest.
Contamination controls
configs/denylist.yaml fingerprints known eval sets. Hits are reported, not silently deleted. --strict fails the build on hits. Hold out benchmarks/ from training.
Quality controls
Schema, SPDX allowlist, Reddit rejection, Quora-as-source rejection, PII heuristics, sandbox/sympy/numeric checks, community-votes-are-not-verification. Tiers S/A/B/C: docs/quality.md. Reddit case study: docs/why-not-reddit.md. evidence_confidence is not a claim of truth.
Intended uses
Research on reasoning and code models; filtering by domain, language, tier, and license; evaluation using the separate benchmarks/ suite.
Limitations
Small v1.4.0 corpus (~3.2K rows); still English-centric; verified coding languages limited to sandbox runtimes; teaching items are not executable oracles unless a numeric/sympy/sandbox check exists; third-party educational sites are registered but not scraped; denylists cannot be complete.
Bias considerations
Synthetic generators encode the authors' choice of topics (software engineering, STEM calculations, operational triage). They under-represent many human domains and languages.
Ethical considerations
No Reddit/social dumps. Case study: docs/why-not-reddit.md. Defensive security only. Minimize PII. Do not present this as a universal "human reasoning" sample.
Maintenance
Issues and PRs: https://github.com/theworker02/open-reason
Hugging Face dataset: https://huggingface.co/datasets/theworker02/open-reason
Small CPU model (1.3M): https://huggingface.co/theworker02/open-reason-small13.9M): https://huggingface.co/theworker02/open-reason-medium
Medium CPU model (
Releases are immutable; GitHub tags map to Hub revisions. Fixes ship in a new version. Shards are not stored in the GitHub git tree.
Citation
See CITATION.cff and the README BibTeX entry.
v1.4.0 snapshot
Pipeline version 1.4.0.
| Configuration | Examples | Verified | Human-authored |
|---|---|---|---|
| coding | 400 | 386 | 0 |
| reasoning | 580 | 580 | 0 |
| science | 527 | 527 | 0 |
| mathematics | 1050 | 1050 | 0 |
| human | 289 | 261 | 28 |
| education | 345 | 111 | 0 |
| core | 3175 | 2899 | 28 |
| verified | 2899 | 2899 | 0 |
| all | 3175 | 2899 | 28 |
Rebuild with open-reason build --config all --seed 42 --out data/release.
Full tables: data/release/statistics.md.