metadata
license: mit
🚗 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:
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())