metadata

language:
  - it
  - en
license: apache-2.0
size_categories:
  - 100K<n<1M
task_categories:
  - question-answering
pretty_name: Pinocchio
dataset_info:
  - config_name: multimodal
    features:
      - name: question
        dtype: string
      - name: options
        list:
          - name: key
            dtype: string
          - name: value
            dtype: string
      - name: answer
        dtype: string
      - name: image
        dtype: image
      - name: macro
        dtype: string
      - name: category
        dtype: string
    splits:
      - name: generale
        num_bytes: 673172291.25
        num_examples: 34275
    download_size: 590129851
    dataset_size: 673172291.25
  - config_name: text
    features:
      - name: question
        dtype: string
      - name: options
        list:
          - name: key
            dtype: string
          - name: value
            dtype: string
      - name: answer
        dtype: string
      - name: macro
        dtype: string
      - name: category
        dtype: string
    splits:
      - name: cultura
        num_bytes: 4058099
        num_examples: 10000
      - name: diritto
        num_bytes: 4552269
        num_examples: 10000
      - name: lingua_straniera
        num_bytes: 1918919
        num_examples: 10000
      - name: logica
        num_bytes: 3466676
        num_examples: 10000
      - name: matematica_e_scienze
        num_bytes: 2632463
        num_examples: 10000
      - name: generale
        num_bytes: 20438794
        num_examples: 52574
    download_size: 19120837
    dataset_size: 37067220
configs:
  - config_name: multimodal
    data_files:
      - split: generale
        path: multimodal/generale-*
  - config_name: text
    data_files:
      - split: cultura
        path: text/cultura-*
      - split: diritto
        path: text/diritto-*
      - split: lingua_straniera
        path: text/lingua_straniera-*
      - split: logica
        path: text/logica-*
      - split: matematica_e_scienze
        path: text/matematica_e_scienze-*
      - split: generale
        path: text/generale-*
tags:
  - evaluation

Dataset Card

Pinocchio is a comprehensive and challenging Natural Language Understanding (NLU) dataset designed to rigorously evaluate language models' capabilities, with a particular focus on Italian language, culture, and various specialized domains.

📖Paper (maybe soon)

[2024.07.16] Pinocchio dataset released, featuring ~140,000 questions across modalities and ~40 disciplines.

Dataset Description

Curated by: Edoardo Federici
Language(s) (NLP): Italian
License: Apache 2.0

1. What's unique about Pinocchio?

Compared to other NLU datasets, Pinocchio offers several distinctive features:

Comprehensive Italian Focus: While many datasets prioritize English, Pinocchio is tailored specifically for Italian language and culture, filling a crucial gap in NLU evaluation.
Diverse Specialized Domains: Pinocchio includes dedicated splits for law, foreign languages, logic, and STEM, allowing for in-depth evaluation of models' performance across various fields.
Multimodal Evaluation: With a substantial multimodal split, Pinocchio enables assessment of models' ability to understand and reason about both text and images.
Difficulty Stratification: The dataset provides carefully curated subsets, allowing for nuanced evaluation of model capabilities.

2. Dataset Summary

Questions and Options: Each question within the dataset typically has multiple-choice options. The number of options may vary depending on the specific task and split.
Languages: The primary language is Italian, with some tasks in the 'Lingua Straniera' split featuring other languages to assess foreign language proficiency.
Modalities: While most of the dataset is text-based, the 'Multimodale' split incorporate both text and images.
Disciplines Covered: The dataset spans a wide range of topics including general knowledge, Italian culture, law, foreign languages, logic, mathematics, and sciences.

Split	Number of Questions	Focus Area
Generale	50,000	Comprehensive multi-topic evaluation
Cultura	10,000	Italian and international culture
Diritto	10,000	Italian law and legal concepts
Lingua Straniera	10,000	Foreign language proficiency
Logica	10,000	Logical reasoning and problem-solving
Matematica e Scienze	10,000	Mathematics and scientific knowledge
Multimodale	36,000	Text and image-based tasks
Total	136,000

3. Dataset Construction

We leveraged our access to a substantial volume of Italian-language data to create Pinocchio. The initial corpus consisted of questions and tasks from real-world exams, professional assessments, and domain-specific challenges. This approach ensured that our dataset would reflect the actual knowledge and skills required in various Italian professional and academic contexts.

4. Leaderboard

SOON

6. Ethical Considerations and Limitations

Cultural Specificity: Given its focus on Italian language and culture, Pinocchio may not be suitable for evaluating models primarily trained on other languages or cultural contexts, but it can be useful to measure how reasoning capabilities translate between languages in a multilingual model.
Potential Biases: Users should be aware of potential biases in question selection and framing, particularly in culturally sensitive areas.
Multimodal Limitations: The multimodal split may have limitations in terms of image diversity and complexity.

7. Dataset Maintenance

If you find any mistake or error, please start a new discussion or open a pull request.

8. Citation

If you use the Pinocchio dataset in your research, please cite it as:

@software{pinocchio2024nlu,
  author = {Federici, Edoardo},
  title = {Pinocchio: An Italian, Culture-Aware, Language Understanding Dataset},
  month = July,
  year = 2024,
  url = {https://huggingface.co/datasets/efederici/pinocchio},
}