SNORKEL EXPERT DATA-AS-A-SERVICE
STEM Reasoning
The STEM Reasoning data captures the kind of problem solving experts perform across science, technology, engineering, and mathematics—multi-step reasoning, factual precision, and arriving at a single, verifiable conclusion.
Developed by Snorkel’s AI Data Research Lab in collaboration with leading experts across STEM domains, this dataset is designed to help you build, test, and tune AI systems to reason accurately and reliably across STEM domains.
Expert-led validation
Human review — Domain experts verify correctness, clarity, originality, and reasoning depth.
LLMaJ validation — Automated checks detect ambiguity, insufficient context, contamination, and underspecified problem statements.
Deterministic testing — Final answers must be exact, checkable, and validated with deterministic match rules.
Guardrails — Problems are screened for contamination, trivial variants, multimodal content, or reliance on external data.
STEM domains including:
Mathematics (algebra, calculus, probability, statistics, geometry, etc.)
Physics (mechanics, E&M, thermodynamics, quantum, relativity)
Chemistry (organic, physical, analytical, inorganic, biochemistry)
Biology (genetics, physiology, microbiology, ecology, immunology)
Computer science (algorithms, theory, ML, systems, databases)
Engineering (mechanical, electrical, civil, chemical, materials)
Professions (legal, medical, business, technical)
Why the Snorkel Data Series
Lab-to-lab partnership
Expert-network design
Deterministic ground truth & verifiers
Let’s talk
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