Datasets:
File size: 8,014 Bytes
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---
language:
- pt
size_categories:
- 10M<n<100M
task_categories:
- text-generation
pretty_name: CrawlPT (deduplicated)
dataset_info:
- config_name: OSCAR-2301
features:
- name: id
dtype: int64
- name: text
dtype: string
- name: meta
struct:
- name: categories
sequence: string
- name: dedup
struct:
- name: exact_norm
struct:
- name: cluster_main_idx
dtype: int64
- name: cluster_size
dtype: int64
- name: exact_hash_idx
dtype: int64
- name: is_duplicate
dtype: bool
- name: minhash
struct:
- name: cluster_main_idx
dtype: int64
- name: cluster_size
dtype: int64
- name: is_duplicate
dtype: bool
- name: minhash_idx
dtype: int64
- name: harmful_pp
dtype: float64
- name: identification
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- name: label
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- name: quality_warnings
sequence: string
- name: sentence_identifications
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- name: prob
dtype: float64
- name: tlsh
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- name: warc_headers
struct:
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- name: content-type
dtype: string
- name: warc-block-digest
dtype: string
- name: warc-date
dtype: string
- name: warc-identified-content-language
dtype: string
- name: warc-record-id
dtype: string
- name: warc-refers-to
dtype: string
- name: warc-target-uri
dtype: string
- name: warc-type
dtype: string
splits:
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num_examples: 10888966
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- config_name: brwac
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- name: text
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struct:
- name: exact_norm
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dtype: int64
- name: cluster_size
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dtype: int64
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- name: cluster_size
dtype: int64
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dtype: int64
- name: text
dtype: string
- name: meta
struct:
- name: dedup
struct:
- name: exact_norm
struct:
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dtype: int64
- name: cluster_size
dtype: int64
- name: exact_hash_idx
dtype: int64
- name: is_duplicate
dtype: bool
- name: minhash
struct:
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dtype: int64
- name: cluster_size
dtype: int64
- name: is_duplicate
dtype: bool
- name: minhash_idx
dtype: int64
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- name: train
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num_examples: 38059979
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configs:
- config_name: OSCAR-2301
data_files:
- split: train
path: OSCAR-2301/train-*
- config_name: all
data_files:
- split: train
path: all/train-*
- config_name: brwac
data_files:
- split: train
path: brwac/train-*
- config_name: cc100
data_files:
- split: train
path: cc100/train-*
---
# CrawlPT (deduplicated)
CrawlPT is a generic Portuguese corpus extracted from various web pages.
This version is deduplicated using MinHash algorithm and Locality Sensitive Hashing, following the approach of Lee et al. (2022).
The raw version is also available [here](https://huggingface.co/datasets/eduagarcia/CrawlPT).
## Dataset Details
Dataset is composed by three corpora:
[brWaC](https://aclanthology.org/L18-1686/), [C100-PT](https://arxiv.org/abs/1911.02116), [OSCAR-2301](http://arxiv.org/abs/2201.06642).
- **brWaC**: a web corpus for Brazilian Portuguese from 120,000 different websites.
- **C100-PT**: Portuguese subset from CC-100. C100 was created for training the multilingual Transformer XLM-R, containing two terabytes of cleaned data from 2018 snapshots of the [Common Crawl project](\url{https://commoncrawl.org/about/) in 100 languages. We use the , which contains 49.1 GiB of text.
- **OSCAR-2301-PT**: curation from OSCAR-2301 in the Portuguese language.
### Dataset Description
- **Language(s) (NLP):** Brazilian Portuguese (pt-BR)
- **Repository:** https://github.com/eduagarcia/roberta-legal-portuguese
- **Paper:** https://aclanthology.org/2024.propor-1.38/
## Data Collection and Processing
Raw corpora sizes in terms of billions of tokens and file size in GiB:
| Corpus | Domain | Tokens (B) | Size (GiB) |
|-----------------|:-------:|:----------:|:----------:|
| brWaC | General | 2.7 | 16.3 |
| CC100 (PT) | General | 8.4 | 49.1 |
| OSCAR-2301 (PT) | General | 18.1 | 97.8 |
CrawlPT is deduplicated using [MinHash algorithm](https://dl.acm.org/doi/abs/10.5555/647819.736184) and [Locality Sensitive Hashing](https://dspace.mit.edu/bitstream/handle/1721.1/134231/v008a014.pdf?sequence=2&isAllowed=y), following the approach of [Lee et al. (2022)](http://arxiv.org/abs/2107.06499).
We used 5-grams and a signature of size 256, considering two documents to be identical if their Jaccard Similarity exceeded 0.7.
Deduplicate rate found by the Minhash-LSH algorithm for the CrawlPT corpus:
| Corpus | Documents | Docs. after deduplicatio} | Duplicates (%) |
|------------------------|:----------:|:-------------------------:|:--------------:|
| brWaC | 3,530,796 | 3,513,588 | 0.49 |
| OSCAR-2301 (PT Subset) | 18,031,400 | 10,888,966 | 39.61 |
| CC100 (PT Subset) | 38,999,388 | 38,059,979 | 2.41 |
| Total (CrawlPT) | 60,561,584 | 52,462,533 | 13.37 |
## Citation
```bibtex
@inproceedings{garcia-etal-2024-robertalexpt,
title = "{R}o{BERT}a{L}ex{PT}: A Legal {R}o{BERT}a Model pretrained with deduplication for {P}ortuguese",
author = "Garcia, Eduardo A. S. and
Silva, Nadia F. F. and
Siqueira, Felipe and
Albuquerque, Hidelberg O. and
Gomes, Juliana R. S. and
Souza, Ellen and
Lima, Eliomar A.",
editor = "Gamallo, Pablo and
Claro, Daniela and
Teixeira, Ant{\'o}nio and
Real, Livy and
Garcia, Marcos and
Oliveira, Hugo Gon{\c{c}}alo and
Amaro, Raquel",
booktitle = "Proceedings of the 16th International Conference on Computational Processing of Portuguese",
month = mar,
year = "2024",
address = "Santiago de Compostela, Galicia/Spain",
publisher = "Association for Computational Lingustics",
url = "https://aclanthology.org/2024.propor-1.38",
pages = "374--383",
}
```
## Acknowledgment
This work has been supported by the AI Center of Excellence (Centro de Excelência em Inteligência Artificial – CEIA) of the Institute of Informatics at the Federal University of Goiás (INF-UFG). |