Building an LLM Document Extraction Benchmark Framework
· 5 min read
Large Language Models (LLMs) are increasingly being used for structured information extraction from documents such as resumes, invoices, and reports. However, different LLMs behave differently in terms of extraction accuracy, execution time, consistency, and output quality. Choosing the right model for document extraction tasks therefore becomes an important challenge.
To address this, we built an LLM Document Extraction Benchmark System that compares multiple LLMs on structured document extraction tasks. The framework evaluates models using common prompts and documents, then measures their performance using metrics such as execution time, accuracy, precision, recall, and F1 score.