Fig. 6: LLM-powered workflows for data annotation and literature-based knowledge extraction.
From: Large language model powered knowledge graph construction for mental health exploration
a Workflow for literature-based triplet annotation using large language models (LLMs). The process begins with downloading abstracts and applying biomedical named entity recognition (e.g., BERN2, QuickUMLS). Annotated entities are used to construct transformed sentences, which are then submitted to GPT-based prompts for relation extraction. Human annotators manually review and refine the generated triplets to ensure accuracy. b Pipeline for extracting baseline characteristics from PDFs using LLM-powered question answering.
