|
--- |
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dataset_info: |
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- config_name: LeNER-Br |
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features: |
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- name: idx |
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dtype: int32 |
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- name: tokens |
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sequence: string |
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- name: ner_tags |
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sequence: |
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class_label: |
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names: |
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'0': O |
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'1': B-ORGANIZACAO |
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'2': I-ORGANIZACAO |
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'3': B-PESSOA |
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'4': I-PESSOA |
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'5': B-TEMPO |
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'6': I-TEMPO |
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'7': B-LOCAL |
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'8': I-LOCAL |
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'9': B-LEGISLACAO |
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'10': I-LEGISLACAO |
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'11': B-JURISPRUDENCIA |
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'12': I-JURISPRUDENCIA |
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splits: |
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- name: train |
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num_bytes: 3953896 |
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num_examples: 7825 |
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- name: validation |
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num_bytes: 715819 |
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num_examples: 1177 |
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- name: test |
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num_bytes: 819242 |
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num_examples: 1390 |
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download_size: 1049906 |
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dataset_size: 5488957 |
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- config_name: UlyssesNER-Br-PL-coarse |
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features: |
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- name: idx |
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dtype: int32 |
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- name: tokens |
|
sequence: string |
|
- name: ner_tags |
|
sequence: |
|
class_label: |
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names: |
|
'0': O |
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'1': B-DATA |
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'2': I-DATA |
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'3': B-EVENTO |
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'4': I-EVENTO |
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'5': B-FUNDAMENTO |
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'6': I-FUNDAMENTO |
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'7': B-LOCAL |
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'8': I-LOCAL |
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'9': B-ORGANIZACAO |
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'10': I-ORGANIZACAO |
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'11': B-PESSOA |
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'12': I-PESSOA |
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'13': B-PRODUTODELEI |
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'14': I-PRODUTODELEI |
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splits: |
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- name: train |
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num_bytes: 1511905 |
|
num_examples: 2271 |
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- name: validation |
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num_bytes: 305472 |
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num_examples: 489 |
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- name: test |
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num_bytes: 363207 |
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num_examples: 524 |
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download_size: 431964 |
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dataset_size: 2180584 |
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- config_name: UlyssesNER-Br-PL-fine |
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features: |
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- name: idx |
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dtype: int32 |
|
- name: tokens |
|
sequence: string |
|
- name: ner_tags |
|
sequence: |
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class_label: |
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names: |
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'0': O |
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'1': B-DATA |
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'2': I-DATA |
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'3': B-EVENTO |
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'4': I-EVENTO |
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'5': B-FUNDapelido |
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'6': I-FUNDapelido |
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'7': B-FUNDlei |
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'8': I-FUNDlei |
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'9': B-FUNDprojetodelei |
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'10': I-FUNDprojetodelei |
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'11': B-LOCALconcreto |
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'12': I-LOCALconcreto |
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'13': B-LOCALvirtual |
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'14': I-LOCALvirtual |
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'15': B-ORGgovernamental |
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'16': I-ORGgovernamental |
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'17': B-ORGnaogovernamental |
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'18': I-ORGnaogovernamental |
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'19': B-ORGpartido |
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'20': I-ORGpartido |
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'21': B-PESSOAcargo |
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'22': I-PESSOAcargo |
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'23': B-PESSOAgrupocargo |
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'24': I-PESSOAgrupocargo |
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'25': B-PESSOAindividual |
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'26': I-PESSOAindividual |
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'27': B-PRODUTOoutros |
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'28': I-PRODUTOoutros |
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'29': B-PRODUTOprograma |
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'30': I-PRODUTOprograma |
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'31': B-PRODUTOsistema |
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'32': I-PRODUTOsistema |
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splits: |
|
- name: train |
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num_bytes: 1511905 |
|
num_examples: 2271 |
|
- name: validation |
|
num_bytes: 305472 |
|
num_examples: 489 |
|
- name: test |
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num_bytes: 363207 |
|
num_examples: 524 |
|
download_size: 437232 |
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dataset_size: 2180584 |
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- config_name: fgv-coarse |
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features: |
|
- name: idx |
|
dtype: int32 |
|
- name: tokens |
|
sequence: string |
|
- name: ner_tags |
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sequence: |
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class_label: |
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names: |
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'0': O |
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'1': B-Academic_Citation |
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'2': I-Academic_Citation |
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'3': B-Legislative_Reference |
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'4': I-Legislative_Reference |
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'5': B-Person |
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'6': I-Person |
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'7': B-Precedent |
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'8': I-Precedent |
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splits: |
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- name: train |
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num_bytes: 19490545 |
|
num_examples: 415 |
|
- name: validation |
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num_bytes: 3934464 |
|
num_examples: 60 |
|
- name: test |
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num_bytes: 6080343 |
|
num_examples: 119 |
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download_size: 3917469 |
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dataset_size: 29505352 |
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- config_name: rrip |
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features: |
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- name: idx |
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dtype: int32 |
|
- name: sentence |
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dtype: string |
|
- name: label |
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dtype: |
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class_label: |
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names: |
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'0': '1' |
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'1': '2' |
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'2': '3' |
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'3': '4' |
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'4': '5' |
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'5': '6' |
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'6': '7' |
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'7': '8' |
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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: |
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- config_name: LeNER-Br |
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data_files: |
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- split: train |
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path: LeNER-Br/train-* |
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- split: validation |
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path: LeNER-Br/validation-* |
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- split: test |
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path: LeNER-Br/test-* |
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- config_name: UlyssesNER-Br-PL-coarse |
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data_files: |
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- split: train |
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path: UlyssesNER-Br-PL-coarse/train-* |
|
- split: validation |
|
path: UlyssesNER-Br-PL-coarse/validation-* |
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- split: test |
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path: UlyssesNER-Br-PL-coarse/test-* |
|
- config_name: UlyssesNER-Br-PL-fine |
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data_files: |
|
- split: train |
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path: UlyssesNER-Br-PL-fine/train-* |
|
- split: validation |
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path: UlyssesNER-Br-PL-fine/validation-* |
|
- split: test |
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path: UlyssesNER-Br-PL-fine/test-* |
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- config_name: fgv-coarse |
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data_files: |
|
- split: train |
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path: fgv-coarse/train-* |
|
- split: validation |
|
path: fgv-coarse/validation-* |
|
- split: test |
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path: fgv-coarse/test-* |
|
- config_name: rrip |
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data_files: |
|
- split: train |
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path: rrip/train-* |
|
- split: validation |
|
path: rrip/validation-* |
|
- split: test |
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path: rrip/test-* |
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task_categories: |
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- token-classification |
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- text-classification |
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language: |
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- pt |
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tags: |
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- legal |
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pretty_name: PortuLex benchmark |
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size_categories: |
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- 10K<n<100K |
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extra_gated_heading: Access PortuLex on Hugging Face |
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extra_gated_prompt: >- |
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The PortuLex benchmark includes datasets with specific access requirements: |
|
|
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1. RRI dataset requires the acceptance of these terms: https://bit.ly/rhetoricalrole. |
|
|
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2. For the FGV-STF corpus, you must request it directly from the original authors: https://www.sciencedirect.com/science/article/abs/pii/S0306457321002727. |
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extra_gated_fields: |
|
Full Name: text |
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Official Email Address: text |
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Affiliation: text |
|
Country: text |
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I accepted the RRIP Terms of Commitment: checkbox |
|
I have obtained permission to access the FGV-STF benchmark directly from the original authors: checkbox |
|
--- |
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|
|
|
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# PortuLex_benchmark |
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|
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"PortuLex" benchmark is a four-task benchmark designed to evaluate the quality and performance of language models in the Portuguese legal domain. |
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| Dataset | Task | Train | Dev | Test | |
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|---------------|------|-------|-------|-------| |
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| RRI | CLS | 8.26k | 1.05k | 1.47k | |
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| LeNER-Br | NER | 7.83k | 1.18k | 1,39k | |
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| UlyssesNER-Br | NER | 3.28k | 489 | 524 | |
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| FGV-STF | NER | 415 | 60 | 119 | |
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|
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## Dataset Details |
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|
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PortuLex is composed by: [LeNER-Br](http://link.springer.com/10.1007/978-3-319-99722-3_32), [Rhetorical Role Identification (RRI)](https://dl.acm.org/doi/abs/10.1007/978-3-030-91699-2_38), [FGV-STF](https://www.sciencedirect.com/science/article/pii/S0306457321002727), [UlyssesNER-Br](https://dl.acm.org/doi/abs/10.1007/978-3-030-98305-5_1). |
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|
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- **LeNER-Br**: the first Named Entity Recognition (NER) corpus for the legal domain in Brazilian Portuguese from higher and state-level courts. |
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- **RRI**: rhetorical annotations from judicial sentences from the Court of Justice of Mato Grosso do Sul (Brazil). |
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- **FGV-STF**: decisions from the Supreme Federal Court for entity extraction. |
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- **UlyssesNER-Br**: NER corpus of bills and legislative queries from the Chamber of Deputies of Brazil. |
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|
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### Dataset Description |
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|
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- **Language(s) (NLP):** Brazilian Portuguese (pt-BR) |
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- **License:** [Creative Commons Attribution 4.0 International Public License](https://creativecommons.org/licenses/by/4.0/deed.en) |
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- **Repository:** https://github.com/eduagarcia/roberta-legal-portuguese |
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- **Paper:** [More Information Needed] |
|
|
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## Dataset Evaluation |
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|
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Macro F1-Score (\%) for multiple models evaluated on PortuLex benchmark test splits: |
|
|
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| **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 | |
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| BERTimbau-large | 88.64 | 87.77/84.74 | 79.71 | **83.79** | 84.60 | |
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| Albertina-PT-BR-base | 89.26 | 86.35/84.63 | 79.30 | 81.16 | 83.80 | |
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| Albertina-PT-BR-xlarge | 90.09 | 88.36/**86.62** | 79.94 | 82.79 | 85.08 | |
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| BERTikal-base | 83.68 | 79.21/75.70 | 77.73 | 81.11 | 79.99 | |
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| JurisBERT-base | 81.74 | 81.67/77.97 | 76.04 | 80.85 | 79.61 | |
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| BERTimbauLAW-base | 84.90 | 87.11/84.42 | 79.78 | 82.35 | 83.20 | |
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| Legal-XLM-R-base | 87.48 | 83.49/83.16 | 79.79 | 82.35 | 83.24 | |
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| Legal-XLM-R-large | 88.39 | 84.65/84.55 | 79.36 | 81.66 | 83.50 | |
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| 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 | |
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| RoBERTaLegalPT-base (Trained on LegalPT) | 90.59 | 85.45/84.40 | 79.92 | 82.84 | 84.57 | |
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| [RoBERTaCrawlPT-base](https://huggingface.co/eduagarcia/RoBERTaCrawlPT-base) (Trained on CrawlPT) | 89.24 | 88.22/86.58 | 79.88 | 82.80 | 84.83 | |
|
| [RoBERTaLexPT-base](https://huggingface.co/eduagarcia/RoBERTaLexPT-base) (Trained on CrawlPT + LegalPT) | **90.73** | **88.56**/86.03 | **80.40** | 83.22 | **85.41** | |
|
|
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## Citation |
|
|
|
```bibtex |
|
@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", |
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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). |
