---
Modalities: Text
language:
- en
license: cc-by-4.0
task_categories:
- question-answering
task_ids:
- multiple-choice-qa
modalities:
- text
formats:
- parquet
size_categories:
- n<1K
tags:
  - english
  - non-stem
  - question-answering
  - mcqa
  - multiple-choice-questions
  - educational
  - education
  - humanities
  - social-science
  - history
  - geography
  - economics
  - polity
  - general-knowledge
  - reasoning
  - exam-preparation
  - competitive-exams
  - nlp
  - llm
  - instruction-tuning
  - sft
  - rlhf
  - self-supervised-learning
  - knowledge-retrieval
  - educational-ai
  - english-language
pretty_name: STEM QnA Sample Dataset
---
**Dataset Description:**

**This dataset is a large-scale collection of English Non-STEM Multiple-Choice Question Answering (MCQA) data, containing 2,581,532 question-answer pairs, designed to support the development and training of advanced NLP systems and AI models for language understanding, reasoning, knowledge retrieval, and educational learning in English.**

It is well-suited for **Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF) workflows**, helping improve model performance in question answering, reasoning, and domain-general tasks.

**Dataset Specification**

    -Total: 2,581,532
    -Modality: English text (MCQ-based question-answer pairs)
    -Type: Educational /(Non-STEM)
    -Data Source: Curated academic and general knowledge resources
    -Data Nature: Real-world and curated data
    -Content: Questions with options and correct answers

**Key Use Cases**

    -Question Answering (QA) (MCQ-based)
    -Automated tutoring and educational assistants
    -Knowledge retrieval systems
    -Model benchmarking and evaluation


**Value of This Dataset**

    -Supports learning of general knowledge domains
    -Improves reasoning and comprehension capabilities of AI models
    -Enables development of general-purpose QA systems
    -Enhances accuracy of LLMs in non-STEM domains
    -Provides broad coverage across diverse subjects

**Basic JSON Schema**
```json
{
  "section": "string",
  "answer_type": "string",
  "q_string": "string",
  "q_option": [
    "string"
  ],
  "q_answer": "string",
  "q_exp": "string",
  "lang_code": "string",
  "category": "string"
}
```
**Full Dataset Overview**

  6.5M+ Questions / 1.8B+ Tokens
  
  This scale provides extensive domain coverage, rich contextual learning, and significantly improves language understanding, reasoning, and model performance.

**Data Creation**

  Procured through formal agreements and generated in the ordinary course of business.

**Considerations**

  This dataset is provided for research and educational purposes only. It contains only sample data. For access to the full dataset and enterprise licensing options, please visit our website [InfoBay.AI](https://infobay.ai/) or contact us directly.

    -Ph: (91) 8303174762
    -Email: datareq@infobay.ai