Testing how well ChatGPT can pull data out of messy PDFs

Mar 2, 2023 ·

Testing PDF Data Extraction with ChatGPT is an open source project funded by OpenAI to create a large language model for natural language processing (NLP) tasks. The project aims to use machine learning and AI techniques to extract information from PDF files, allowing for faster and more accurate data extraction processes.

As part of the project, the team has developed a library of algorithms that can extract text from PDF documents. This process begins by using optical character recognition (OCR) to convert the PDF into plain text, then applying NLP techniques to understand the structure of the document. The team has developed an algorithm which can distinguish between structural elements such as headings and paragraphs, and identify key words in order to extract meaningful data from the PDF.

The team has tested the library on over two million PDFs, including financial statements, legal documents, medical reports and more. The results have been promising, with the library achieving up to 80% accuracy in data extraction. Furthermore, the library can quickly index documents and search for specific information, making it useful for a wide range of applications.

Overall, the Testing PDF Data Extraction with ChatGPT project has demonstrated the potential of large language models for data extraction tasks. The library is open-source, meaning developers can implement and test the technology themselves, hopefully leading to even better performance in the future. This is a welcome step forward for the field of NLP and machine learning, providing an example of how AI can be used to improve the efficiency of various business processes.