Navigating the Challenges of Data Extraction with AI Tools
Hello everyone,
I hope this post finds you well. I’m currently facing a bit of a predicament with a data extraction task that I thought would be straightforward, and I’m looking for your insights and potential solutions.
Here’s the situation: I have a collection of 27 images that contain a dataset comprising 835 line items. My initial thought was to leverage the power of GPT to transform these images into a CSV or Excel table, a task I believed would be seamless for an advanced AI.
To kick things off, I attempted to process just two images with GPT. Unfortunately, it struggled to extract the information accurately from them. Not one to be easily deterred, I then utilized an online Optical Character Recognition (OCR) tool to convert the images into text, thinking that this would simplify the process. I later provided the extracted text to GPT, hoping it would convert that into a structured table format.
To my surprise, that approach also fell short. This led me to wonder: Why is this task proving to be so challenging for GPT? Given its capabilities, I assumed that restructuring data would be one of its strong suits.
If anyone has dealt with a similar challenge or possesses any strategies that could help tackle this task, I would greatly appreciate your input. Additionally, any guidance on a viable solution would be incredibly valuable. Thank you in advance for your help!
Leave a Reply