Abstract

Locating new sources of critical minerals begins with understanding where these minerals have been found in the past. However, historical data about mineral occurrences is often locked in disparate, unstructured, and inconsistent formats, ranging from government databases to mining reports and journal articles. To address this challenge, we have developed a set of scalable technologies that extract, normalize, and semantically integrate information from these sources into a unified knowledge graph. Our approach combines ontology-driven modeling, large-language models for information extraction and classification, and tools for linking and validating data across sources. The result is a semantically enriched, queryable knowledge graph that supports reproducible analysis, expert validation, and geoscientific applications such as deposit classification and prospectivity modeling. Through this work, we have …

Date

October 29, 2025

Authors

Craig A Knoblock, Binh Vu, Basel Shbita, Yao-Yi Chiang, Pothula Punith Krishna, Xiao Lin, Goran Muric, Jiyoon Pyo, Adriana Trejo-Sheu, Meng Ye

Book

International Semantic Web Conference

Pages

451-471

Publisher

Springer Nature Switzerland