Instead of labeling your data manually, use Predictly’s customizable legal clause identification dataset to train a model which can identify legal clauses in a contract quickly.
All contract sentences have been annotated by professional lawyers which makes it a highly accurate and balanced dataset in the branch of contract analysis and with the right machine learning model you can achieve 90% and beyond accuracy.
The dataset is available with a fully customizable option which allows you to fuse any clause label according to your requirement and annotate it. It provides rapid integration to consume the dataset easily and efficiently.
We often see hundreds of contracts or tenders coming up for review. In law firms we usually come across many tenders and their described contents and the first thing we do is to identify from which clause it comes from. We use the prescribed playbook to look for the suitable clause for the described content or sentence. And this actually comes at a cost of time, we spend a lot of time just looking through one contract or tender. Then just imagine the time it will take to analyze or review hundreds of contracts or tenders. That’s where we need to automate this and how do we automate this, by building an automated contract review system. In that automated contract review system we will have several machine learning models like clause identification, risk assessment (level of risk associated with) and whether it’s compliance with the prescribed playbook or not. We will not cover all of them in this story, we will only go through the clause identification.