Construction of Functional Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model

arXiv:2404.03080v1 Announce Type: new
Abstract: The convergence of materials science and artificial intelligence has unlocked new opportunities for gathering, analyzing, and generating novel materials sourced from extensive scientific literature. Despite the potential benefits, persistent challenges such as manual annotation, precise extraction, and traceability issues remain. Large language models have emerged as promising solutions to address these obstacles. This paper introduces Functional Materials Knowledge Graph (FMKG), a multidisciplinary materials science knowledge graph. Through the utilization of advanced natural language processing techniques, …

abstract annotation artificial artificial intelligence arxiv benefits challenges construction convergence cs.ai cs.cl extraction functional graph intelligence knowledge knowledge graph language language model large language large language model literature materials materials science novel opportunities science scientific traceability type unlocked via