  The development of annotated datasets over the 21st century has helped us
truly realize the power of deep learning. Most of the datasets created for the
named-entity-recognition (NER) task are not domain specific. Finance domain
presents specific challenges to the NER task and a domain specific dataset
would help push the boundaries of finance research. In our work, we develop the
first high-quality NER dataset for the finance domain. To set the benchmark for
the dataset, we develop and test a weak-supervision-based framework for the NER
task. We extend the current weak-supervision framework to make it employable
for span-level classification. Our weak-ner framework and the dataset are
publicly available on GitHub and Hugging Face.
