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---
language:
- en
license: apache-2.0
size_categories:
- 10K<n<100K
task_categories:
- token-classification
pretty_name: buster
tags:
- finance
configs:
- config_name: default
data_files:
- split: FOLD_1
path: data/FOLD_1-*
- split: FOLD_2
path: data/FOLD_2-*
- split: FOLD_3
path: data/FOLD_3-*
- split: FOLD_4
path: data/FOLD_4-*
- split: FOLD_5
path: data/FOLD_5-*
- split: SILVER
path: data/SILVER-*
dataset_info:
features:
- name: document_id
dtype: string
- name: text
dtype: string
- name: tokens
sequence: string
- name: labels
sequence: string
splits:
- name: FOLD_1
num_bytes: 13597946
num_examples: 753
- name: FOLD_2
num_bytes: 13477878
num_examples: 759
- name: FOLD_3
num_bytes: 13602552
num_examples: 758
- name: FOLD_4
num_bytes: 13834760
num_examples: 755
- name: FOLD_5
num_bytes: 13632431
num_examples: 754
- name: SILVER
num_bytes: 108914416
num_examples: 6196
download_size: 0
dataset_size: 177059983
---
# 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. |