|
--- |
|
license: apache-2.0 |
|
task_categories: |
|
- token-classification |
|
language: |
|
- en |
|
tags: |
|
- finance |
|
pretty_name: buster |
|
size_categories: |
|
- 10K<n<100K |
|
configs: |
|
- config_name: default |
|
data_files: |
|
- split: FOLD_1 |
|
path: "FOLD_1.json" |
|
- split: FOLD_2 |
|
path: "FOLD_2.json" |
|
- split: FOLD_3 |
|
path: "FOLD_3.json" |
|
- split: FOLD_4 |
|
path: "FOLD_4.json" |
|
- split: FOLD_5 |
|
path: "FOLD_5.json" |
|
- split: SILVER |
|
path: "SILVER.json" |
|
dataset_info: |
|
features: |
|
- name: document_id |
|
dtype: string |
|
- name: tokens |
|
sequence: string |
|
- name: labels |
|
sequence: |
|
class_label: |
|
names: |
|
'0': O |
|
'1': B-Parties.BUYING_COMPANY |
|
'2': I-Parties.BUYING_COMPANY |
|
'3': B-Parties.SELLING_COMPANY |
|
'4': I-Parties.SELLING_COMPANY |
|
'5': B-Parties.ACQUIRED_COMPANY |
|
'6': I-Parties.ACQUIRED_COMPANY |
|
'7': B-Advisors.LEGAL_CONSULTING_COMPANY |
|
'8': I-Advisors.LEGAL_CONSULTING_COMPANY |
|
'9': B-Advisors.GENERIC_CONSULTING_COMPANY |
|
'10': I-Advisors.GENERIC_CONSULTING_COMPANY |
|
'11': B-Generic_Info.ANNUAL_REVENUES |
|
'12': I-Generic_Info.ANNUAL_REVENUES |
|
splits: |
|
- name: FOLD_1 |
|
num_bytes: 11508541 |
|
num_examples: 753 |
|
- name: FOLD_2 |
|
num_bytes: 11409488 |
|
num_examples: 759 |
|
- name: FOLD_3 |
|
num_bytes: 11524994 |
|
num_examples: 758 |
|
- name: FOLD_4 |
|
num_bytes: 11714536 |
|
num_examples: 755 |
|
- name: FOLD_5 |
|
num_bytes: 11543314 |
|
num_examples: 754 |
|
- name: SILVER |
|
num_bytes: 94702584 |
|
num_examples: 6196 |
|
download_size: 20824877 |
|
dataset_size: 152403457 |
|
--- |
|
|
|
|
|
|
|
# Dataset Card for BUSTER |
|
BUSiness Transaction Entity Recognition dataset. |
|
|
|
BUSTER is an Entity Recognition (ER) benchmark for entities related to business transactions. It consists of a gold corpus of |
|
3779 manually annotated documents on financial transactions that were randomly divided into 5 folds, |
|
plus an additional silver corpus of 6196 automatically annotated documents that were created by the model-optimized RoBERTa system. |