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license: mit
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# 🚗 BEst DrivEr’s License Performer (BEEP) Dataset
**BEEP** is a challenge benchmark designed to evaluate large language models (LLMs) through a simulation of the Italian driver’s license exam. This dataset focuses on understanding traffic laws and reasoning through driving situations, replicating the complexity of the Italian licensing process.
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## 📁 Dataset Structure
| Column | Data Type | Description |
| ---------------------- | ------------- | --------------------------------------------------------------------------- |
| `Categorisation Structure` | [String] | Hierarchical categorisation of major, minor, and subcategories for each question |
| `Question Text` | [String] | The actual content of the question |
| `True Answer` | [Boolean] | True or false answer |
| `Figure` | [String] | Reference to an accompanying figure, if present |
> **Note**: Questions are organised into a classification system that reflects the complexity of road rules and signage.
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## 📊 Summary Statistics
- **Total Questions**: 2920
- **Last Updated**: 01/07/2020
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## 🔍 Key Features
- **Source**: The dataset is derived from the publicly accessible official document "Listato A e B", provided by the Italian Ministry of Infrastructure and Transport. It includes all questions related to driver’s license categories A and B.
- **Hierarchical Structure**: Questions are classified into major categories, such as "Road Signage", and further subdivided into minor and subcategories for precise categorisation.
- **Question Format**: The dataset primarily consists of true/false questions aimed at evaluating knowledge of traffic laws, signage, and driving behavior.
- **Exclusions**: For the **CALAMITA** challenge, questions containing images are excluded, focusing solely on text-based questions.
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## 🛠️ Using the Dataset
### Loading Example
You can load this dataset in Python using `pandas`:
```python
import pandas as pd
# Load the dataset
df = pd.read_csv('beep_data.csv')
# Display the first few rows of the dataset
print(df.head())
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