---
dataset_info:
  features:
  - name: question
    dtype: string
  - name: number
    dtype: int64
  - name: id
    dtype: string
  - name: alternatives
    sequence: string
  - name: associated_images
    sequence: binary
  - name: answer
    dtype: string
  - name: has_associated_images
    dtype: bool
  - name: alternatives_type
    dtype: string
  - name: subject
    sequence: string
  - name: IU
    dtype: bool
  - name: MR
    dtype: bool
  - name: CR
    dtype: bool
  splits:
  - name: train
    num_bytes: 783159
    num_examples: 140
  download_size: 505636
  dataset_size: 783159
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: cc-by-4.0
task_categories:
- question-answering
- multiple-choice
language:
- pt
tags:
- poscomp
- portuguese
- evaluation
- benchmark
- computer-science
size_categories:
- n<1K
---

# POSCOMP

Questions from the **POSCOMP** exams of **2022** and **2023**. POSCOMP (Exame Nacional para Ingresso na Pós-Graduação em Computação) is the Brazilian national exam for admission to graduate programs in Computing, administered by the Sociedade Brasileira de Computação (SBC). The dataset contains 140 multiple-choice questions in Portuguese covering mathematics, computer fundamentals, and computer technology.

This dataset was released as part of **PoETa v2**.

## Dataset Structure

A single `train` split with 140 rows. Each example has the following fields:

| Field | Type | Description |
|---|---|---|
| `question` | string | The question text. |
| `number` | int64 | Question number within its exam. |
| `id` | string | Unique identifier (e.g. `POSCOMP_2023_56`). |
| `alternatives` | list[string] | The multiple-choice options (A–E). |
| `associated_images` | list | Images associated with the question, if any. |
| `answer` | string | The correct alternative (letter). |
| `has_associated_images` | bool | Whether the question has associated images. |
| `alternatives_type` | string | Type of the alternatives. |
| `subject` | list[string] | Subject area(s): `mathematics`, `computer_fundamentals`, `computer_technology`. |
| `IU` | bool | Requires image understanding. |
| `MR` | bool | Requires mathematical reasoning. |
| `CR` | bool | Requires complex reasoning. |

## Usage

```python
from datasets import load_dataset

ds = load_dataset("maritaca-ai/poscomp", split="train")
print(ds[0])
```

## Citation

If you use this dataset, please cite:

```bibtex
@article{almeida2025poeta,
  title={PoETa v2: Toward More Robust Evaluation of Large Language Models in Portuguese},
  author={Almeida, Thales Rog{\'e}rio Sales and Pires, Ramon and Abonizio, Hugo and Nogueira, Rodrigo and Pedrini, Helio},
  journal={IEEE Access},
  volume={13},
  pages={214180--214200},
  year={2025},
  publisher={IEEE}
}
```