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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: tokens
    sequence: string
  - name: labels
    sequence: string
  splits:
  - name: FOLD_1
    num_bytes: 9801188
    num_examples: 753
  - name: FOLD_2
    num_bytes: 9719997
    num_examples: 759
  - name: FOLD_3
    num_bytes: 9810761
    num_examples: 758
  - name: FOLD_4
    num_bytes: 9973098
    num_examples: 755
  - name: FOLD_5
    num_bytes: 9831525
    num_examples: 754
  - name: SILVER
    num_bytes: 80615802
    num_examples: 6196
  download_size: 20217911
  dataset_size: 129752371
---



# 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.