In our last post, we began by trying to create a model for veracity, and ended with the idea of creating a model for intention using the syntax of sentences. In this post, we are going to start looking into the particulars for a model of intention using syntax.
At Forge.AI, we capture events from unstructured data and represent them in a manner suitable for machine learning, decision making, and other algorithmic tasks for our customers (for a broad technical overview, see this blog post). In order to do this, we employ a suite of state of the art machine learning and natural language understanding technologies, many of which are supervised learning systems. For our business to scale aggressively, we need an economically viable way to acquire training data quickly for those supervised learners. We use natural language generation to do just that, supplementing human annotations with annotated synthetic language in an agile fashion.