---
dataset_info:
  features:
  - name: id
    dtype: int64
  - name: question
    dtype: string
  - name: choices
    sequence: string
  - name: answerID
    dtype: int64
  splits:
  - name: eval
    num_bytes: 396224
    num_examples: 1954
  - name: few_shot_prompts
    num_bytes: 4077
    num_examples: 20
  download_size: 222012
  dataset_size: 400301
configs:
- config_name: default
  data_files:
  - split: eval
    path: data/eval-*
  - split: few_shot_prompts
    path: data/few_shot_prompts-*
---
# social_i_qa Dataset

## Overview
This repository contains the processed version of the social_i_qa dataset. The dataset is formatted as a collection of multiple-choice questions.

## Dataset Structure
Each example in the dataset contains the following fields:
```json
{
  "id": 0,
  "question": "Tracy didn't go home that evening and resisted Riley's attacks. What does Tracy need to do before this?",
  "choices": [
    "make a new plan",
    "Go home and see Riley",
    "Find somewhere to go"
  ],
  "answerID": 2
}
```

## Fields Description
- `id`: Unique identifier for each example
- `question`: The question or prompt text
- `choices`: List of possible answers
- `answerID`: Index of the correct answer in the choices list (0-based)

## Loading the Dataset
You can load this dataset using the Hugging Face datasets library:
```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("DatologyAI/social_i_qa")

# Access the data
for example in dataset['train']:
    print(example)
```

## Example Usage
```python
# Load the dataset
dataset = load_dataset("DatologyAI/social_i_qa")

# Get a sample question
sample = dataset['train'][0]

# Print the question
print("Question:", sample['question'])
print("Choices:")
for i, choice in enumerate(sample['choices']):
    print(f"{{i}}. {{choice}}")
print("Correct Answer:", sample['choices'][sample['answerID']])
```

## Dataset Creation
This dataset was processed to ensure:
- All entries are sorted by ID
- All string values have been stripped of extra whitespace
- Consistent JSON formatting