---
license: mit
task_categories:
- question-answering
language:
- it
pretty_name: BEEP
size_categories:
- 1K<n<10K
---
# 🚗 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.

---

## 📁 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.

---

## 📊 Summary Statistics

- **Total Questions**: 2920
- **Last Updated**: 01/07/2020

---

## 🔍 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.

---

## 🛠️ 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())
```

## Citation

If you find our work interesting, please cite us:

**BibTeX:**

```
@inproceedings{mercorio2024beep,
  title={BEEP-BEst DrivEr’s License Performer: A CALAMITA Challenge},
  author={Mercorio, Fabio and Potert{\`\i}, Daniele and Serino, Antonio and Seveso, Andrea and others},
  booktitle={CEUR WORKSHOP PROCEEDINGS},
  volume={3878},
  year={2024}
}
```

**APA:**

Mercorio, F., Potertì, D., Serino, A., & Seveso, A. (2024). BEEP-BEst DrivEr’s License Performer: A CALAMITA Challenge. In CEUR WORKSHOP PROCEEDINGS (Vol. 3878).


## Contact

Andrea Seveso - andrea.seveso@unimib.it