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BUSTER

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Token Classification
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BUSTER / README.md
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metadata
license: apache-2.0
task_categories:
  - token-classification
language:
  - en
tags:
  - finance
pretty_name: buster
size_categories:
  - 10K<n<100K

dataset_info: config_name: BUSTER 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.