  Techniques for automatically extracting important content elements from
business documents such as contracts, statements, and filings have the
potential to make business operations more efficient. This problem can be
formulated as a sequence labeling task, and we demonstrate the adaption of BERT
to two types of business documents: regulatory filings and property lease
agreements. There are aspects of this problem that make it easier than
"standard" information extraction tasks and other aspects that make it more
difficult, but on balance we find that modest amounts of annotated data (less
than 100 documents) are sufficient to achieve reasonable accuracy. We integrate
our models into an end-to-end cloud platform that provides both an easy-to-use
annotation interface as well as an inference interface that allows users to
upload documents and inspect model outputs.
