BUSTER: a "BUSiness Transaction Entity Recognition" dataset

Understand

Albeit Natural Language Processing has seen major breakthroughs in the last few years, transferring such advances into real-world business cases can be challenging.

• One of the reasons resides in the displacement between popular benchmarks and actual data.
• Lack of supervision, unbalanced classes, noisy data and long documents often affect real problems in vertical domains such as finance, law and health.
• To support industry-oriented research, we present BUSTER, a BUSiness Transaction Entity Recognition dataset.