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Reasoning prompt-response pairs dataset

Updated May 7, 2025

This set of more than 700 prompt-response pairs (PRPs) is designed to develop and evaluate core reasoning abilities in language models. Focused on fostering abstract thinking, logical deduction and conceptual clarity, the dataset presents a diverse range of problem formats and multi-step inference tasks.

Specifications

Modalities
Text
Language
English
Licensable
Yes
Volume
700+
Average token per PRP
382
Number of tokens
272,991
Task category
Prompt-response pairs
Domain
Reasoning
Source
Expert-generated
Complexity
3 levels ranging from moderate to very hard

Accelerate model development & training processes

  • Diverse reasoning challenges

    Each entry presents a carefully crafted reasoning scenario designed to engage and test a model’s ability to think critically and apply logic across domains.

  • Broad topic coverage

    Spanning topics such as arithmetic, equations, inductive reasoning, empathy and problem solving, the dataset helps models simulate both mathematical and human-like reasoning patterns.

  • Real-world alignment

    Scenarios are based on real-world tasks, like interpreting time-based sequences or resolving ambiguous math problems, enabling models to generalize from abstract logic to practical decision-making.

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Case Studies

Explore our success stories

  • Evaluating a conversational AI model with a highly complex multimodal STEM dataset

    Man using his mobile device with a chatbot illustration above the device.

    Discover how our off-the-shelf science, technology, engineering and mathematics (STEM) dataset contributed to enhancing scientific reasoning and visual processing capabilities in a chatbot model crafted by a leading-edge tech and AI company.


    • 4485 Physics prompt-response pairs


    • 9606 Math prompt-response pairs

    Download case study
  • Improving large language model logic and reasoning with a specialized fine-tuning dataset

    Person working at a laptop holding a mobile phone with an overlaid illustration of LLM features.

    Explore how TELUS Digital created an off-the-shelf dataset to advance the capabilities of large language models (LLMs).


    • 50 KSTEM-based prompt-response pairs created


    • 300 Highly-skilled contributors

    Download case study

Access the reasoning prompt-response pairs dataset

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