Datasets:
metadata
dataset_info:
- config_name: LeNER-Br
features:
- name: idx
dtype: int32
- name: tokens
sequence: string
- name: ner_tags
sequence:
class_label:
names:
'0': O
'1': B-ORGANIZACAO
'2': I-ORGANIZACAO
'3': B-PESSOA
'4': I-PESSOA
'5': B-TEMPO
'6': I-TEMPO
'7': B-LOCAL
'8': I-LOCAL
'9': B-LEGISLACAO
'10': I-LEGISLACAO
'11': B-JURISPRUDENCIA
'12': I-JURISPRUDENCIA
splits:
- name: train
num_bytes: 3953896
num_examples: 7825
- name: validation
num_bytes: 715819
num_examples: 1177
- name: test
num_bytes: 819242
num_examples: 1390
download_size: 1049906
dataset_size: 5488957
- config_name: UlyssesNER-Br-PL-coarse
features:
- name: idx
dtype: int32
- name: tokens
sequence: string
- name: ner_tags
sequence:
class_label:
names:
'0': O
'1': B-DATA
'2': I-DATA
'3': B-EVENTO
'4': I-EVENTO
'5': B-FUNDAMENTO
'6': I-FUNDAMENTO
'7': B-LOCAL
'8': I-LOCAL
'9': B-ORGANIZACAO
'10': I-ORGANIZACAO
'11': B-PESSOA
'12': I-PESSOA
'13': B-PRODUTODELEI
'14': I-PRODUTODELEI
splits:
- name: train
num_bytes: 1511905
num_examples: 2271
- name: validation
num_bytes: 305472
num_examples: 489
- name: test
num_bytes: 363207
num_examples: 524
download_size: 431964
dataset_size: 2180584
- config_name: UlyssesNER-Br-PL-fine
features:
- name: idx
dtype: int32
- name: tokens
sequence: string
- name: ner_tags
sequence:
class_label:
names:
'0': O
'1': B-DATA
'2': I-DATA
'3': B-EVENTO
'4': I-EVENTO
'5': B-FUNDapelido
'6': I-FUNDapelido
'7': B-FUNDlei
'8': I-FUNDlei
'9': B-FUNDprojetodelei
'10': I-FUNDprojetodelei
'11': B-LOCALconcreto
'12': I-LOCALconcreto
'13': B-LOCALvirtual
'14': I-LOCALvirtual
'15': B-ORGgovernamental
'16': I-ORGgovernamental
'17': B-ORGnaogovernamental
'18': I-ORGnaogovernamental
'19': B-ORGpartido
'20': I-ORGpartido
'21': B-PESSOAcargo
'22': I-PESSOAcargo
'23': B-PESSOAgrupocargo
'24': I-PESSOAgrupocargo
'25': B-PESSOAindividual
'26': I-PESSOAindividual
'27': B-PRODUTOoutros
'28': I-PRODUTOoutros
'29': B-PRODUTOprograma
'30': I-PRODUTOprograma
'31': B-PRODUTOsistema
'32': I-PRODUTOsistema
splits:
- name: train
num_bytes: 1511905
num_examples: 2271
- name: validation
num_bytes: 305472
num_examples: 489
- name: test
num_bytes: 363207
num_examples: 524
download_size: 437232
dataset_size: 2180584
- config_name: fgv-coarse
features:
- name: idx
dtype: int32
- name: tokens
sequence: string
- name: ner_tags
sequence:
class_label:
names:
'0': O
'1': B-Academic_Citation
'2': I-Academic_Citation
'3': B-Legislative_Reference
'4': I-Legislative_Reference
'5': B-Person
'6': I-Person
'7': B-Precedent
'8': I-Precedent
splits:
- name: train
num_bytes: 19490545
num_examples: 415
- name: validation
num_bytes: 3934464
num_examples: 60
- name: test
num_bytes: 6080343
num_examples: 119
download_size: 3917469
dataset_size: 29505352
- config_name: rrip
features:
- name: idx
dtype: int32
- name: sentence
dtype: string
- name: label
dtype:
class_label:
names:
'0': '1'
'1': '2'
'2': '3'
'3': '4'
'4': '5'
'5': '6'
'6': '7'
'7': '8'
splits:
- name: train
num_bytes: 1174840
num_examples: 8257
- name: validation
num_bytes: 184668
num_examples: 1053
- name: test
num_bytes: 235217
num_examples: 1474
download_size: 929466
dataset_size: 1594725
configs:
- config_name: LeNER-Br
data_files:
- split: train
path: LeNER-Br/train-*
- split: validation
path: LeNER-Br/validation-*
- split: test
path: LeNER-Br/test-*
- config_name: UlyssesNER-Br-PL-coarse
data_files:
- split: train
path: UlyssesNER-Br-PL-coarse/train-*
- split: validation
path: UlyssesNER-Br-PL-coarse/validation-*
- split: test
path: UlyssesNER-Br-PL-coarse/test-*
- config_name: UlyssesNER-Br-PL-fine
data_files:
- split: train
path: UlyssesNER-Br-PL-fine/train-*
- split: validation
path: UlyssesNER-Br-PL-fine/validation-*
- split: test
path: UlyssesNER-Br-PL-fine/test-*
- config_name: fgv-coarse
data_files:
- split: train
path: fgv-coarse/train-*
- split: validation
path: fgv-coarse/validation-*
- split: test
path: fgv-coarse/test-*
- config_name: rrip
data_files:
- split: train
path: rrip/train-*
- split: validation
path: rrip/validation-*
- split: test
path: rrip/test-*
task_categories:
- token-classification
- text-classification
language:
- pt
tags:
- legal
pretty_name: PortuLex benchmark
size_categories:
- 10K<n<100K
extra_gated_heading: Access PortuLex on Hugging Face
extra_gated_prompt: >-
The PortuLex benchmark includes datasets with specific access requirements:
1. RRI dataset requires the acceptance of these terms:
https://bit.ly/rhetoricalrole.
2. For the FGV-STF corpus, you must request it directly from the original
authors:
https://www.sciencedirect.com/science/article/abs/pii/S0306457321002727.
extra_gated_fields:
Full Name: text
Official Email Address: text
Affiliation: text
Country: text
I accepted the RRIP Terms of Commitment: checkbox
I have obtained permission to access the FGV-STF benchmark directly from the original authors: checkbox
PortuLex_benchmark
"PortuLex" benchmark is a four-task benchmark designed to evaluate the quality and performance of language models in the Portuguese legal domain.
| Dataset | Task | Train | Dev | Test |
|---|---|---|---|---|
| RRI | CLS | 8.26k | 1.05k | 1.47k |
| LeNER-Br | NER | 7.83k | 1.18k | 1,39k |
| UlyssesNER-Br | NER | 3.28k | 489 | 524 |
| FGV-STF | NER | 415 | 60 | 119 |
Dataset Details
PortuLex is composed by: LeNER-Br, Rhetorical Role Identification (RRI), FGV-STF, UlyssesNER-Br.
- LeNER-Br: the first Named Entity Recognition (NER) corpus for the legal domain in Brazilian Portuguese from higher and state-level courts.
- RRI: rhetorical annotations from judicial sentences from the Court of Justice of Mato Grosso do Sul (Brazil).
- FGV-STF: decisions from the Supreme Federal Court for entity extraction.
- UlyssesNER-Br: NER corpus of bills and legislative queries from the Chamber of Deputies of Brazil.
Dataset Description
- Language(s) (NLP): Brazilian Portuguese (pt-BR)
- License: Creative Commons Attribution 4.0 International Public License
- Repository: https://github.com/eduagarcia/roberta-legal-portuguese
- Paper: [More Information Needed]
Dataset Evaluation
Macro F1-Score (%) for multiple models evaluated on PortuLex benchmark test splits:
| Model | LeNER | UlyNER-PL | FGV-STF | RRIP | Average (%) |
|---|---|---|---|---|---|
| Coarse/Fine | Coarse | ||||
| BERTimbau-based | 88.34 | 86.39/83.83 | 79.34 | 82.34 | 83.78 |
| BERTimbau-large | 88.64 | 87.77/84.74 | 79.71 | 83.79 | 84.60 |
| Albertina-PT-BR-base | 89.26 | 86.35/84.63 | 79.30 | 81.16 | 83.80 |
| Albertina-PT-BR-xlarge | 90.09 | 88.36/86.62 | 79.94 | 82.79 | 85.08 |
| BERTikal-base | 83.68 | 79.21/75.70 | 77.73 | 81.11 | 79.99 |
| JurisBERT-base | 81.74 | 81.67/77.97 | 76.04 | 80.85 | 79.61 |
| BERTimbauLAW-base | 84.90 | 87.11/84.42 | 79.78 | 82.35 | 83.20 |
| Legal-XLM-R-base | 87.48 | 83.49/83.16 | 79.79 | 82.35 | 83.24 |
| Legal-XLM-R-large | 88.39 | 84.65/84.55 | 79.36 | 81.66 | 83.50 |
| Legal-RoBERTa-PT-large | 87.96 | 88.32/84.83 | 79.57 | 81.98 | 84.02 |
| Ours | |||||
| RoBERTaTimbau-base (Reproduction of BERTimbau) | 89.68 | 87.53/85.74 | 78.82 | 82.03 | 84.29 |
| RoBERTaLegalPT-base (Trained on LegalPT) | 90.59 | 85.45/84.40 | 79.92 | 82.84 | 84.57 |
| RoBERTaCrawlPT-base (Trained on CrawlPT) | 89.24 | 88.22/86.58 | 79.88 | 82.80 | 84.83 |
| RoBERTaLexPT-base (Trained on CrawlPT + LegalPT) | 90.73 | 88.56/86.03 | 80.40 | 83.22 | 85.41 |
Citation
@InProceedings{garcia2024_roberlexpt,
author="Garcia, Eduardo A. S.
and Silva, N{\'a}dia F. F.
and Siqueira, Felipe
and Gomes, Juliana R. S.
and Albuqueruqe, Hidelberg O.
and Souza, Ellen
and Lima, Eliomar
and De Carvalho, André",
title="RoBERTaLexPT: A Legal RoBERTa Model pretrained with deduplication for Portuguese",
booktitle="Computational Processing of the Portuguese Language",
year="2024",
publisher="Association for Computational Linguistics"
}
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).