Harnessing the Power of LLMs for Automated Data Extraction

In the realm of natural language processing, Large Language Models (LLMs) have transformed tasks such as automated data extraction by offering advanced contextual understanding and precise entity identification. This blog post explores using LLMs for data extraction in loan applications, leveraging the Seldon Enterprise Platform. A specific workflow is demonstrated where an OpenAI LLM model extracts relevant features from user-submitted text, which are then fed into a classification model to decide loan application outcomes. The process involves deploying an OpenAI LLM model using MLServer technology and creating a Seldon-Core-V2 pipeline to connect the data extraction step to a Random Forest classifier. This implementation exemplifies how LLMs, supported by Seldon Core, enable the creation of sophisticated natural language pipelines, highlighting their adaptability and the seamless integration of data extraction with downstream tasks in various domains.