README.md

---
dataset_info:
  features:
  - name: corpus
    dtype: string
  - name: book
    dtype: string
  - name: date
    dtype: int32
  - name: filename
    dtype: string
  - name: transcription
    dtype: string
  - name: aadi
    dtype: string
  - name: paddleocr
    dtype: string
  - name: tesseract
    dtype: string
  - name: transkribus
    dtype: string
  - name: img
    dtype: image
  - name: complex_layout
    dtype: bool
  - name: language
    dtype: string
  splits:
  - name: train
    num_examples: 3782
configs:
- config_name: default
  data_files:
  - split: train
    path: data/PORTO-part-*
license: cc-by-4.0
task_categories:
- image-to-text
- fill-mask
- text-generation
language:
- pt
tags:
- OCR
- Post-OCR
- Historical
size_categories:
- 1K<n<10k
pretty_name: Corpus / Book / Date / Filename / Transcription / AADI /
  PaddleOCR / Tesseract / Transkribus / Image / Complex Layout / Language
---

# **P**ost-**O**CR **R**esources for **T**ext **O**ptimisation

Resource for evaluation and develop OCRs and Post-OCR focused on historical Portuguese.


How to load the dataset:
```
from datasets import load_dataset

dataset = load_dataset("LIACC/PORTO")
```

# Citation
When using or citing this corpus, kindly cite the following publication:
```
@inproceedings{10.1145/3746252.3761633,
author = {Freitas Os\'{o}rio, Tom\'{a}s and Lopes Cardoso, Henrique},
title = {Portuguese post-OCR Resources for Text Optimisation},
year = {2025},
isbn = {9798400720406},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3746252.3761633},
doi = {10.1145/3746252.3761633},
booktitle = {Proceedings of the 34th ACM International Conference on Information and Knowledge Management},
pages = {6361–6366},
numpages = {6},
keywords = {historical portuguese corpora, ocr evaluation, post-ocr correction resources},
location = {Seoul, Republic of Korea},
series = {CIKM '25}
}
```