SOURCE-LINKED INTELLIGENCE
Extracting ontology-compliant knowledge from scientific text describing irradiated materials using large language models
The quest for new materials increasingly relies on predictive models and comprehensive simulations that span scales from atomic to macroscopic levels. However, essential data necessary for these models and simulations are often embedded in scientific literature as unstructured text, limiting reusability and posing challenges for researchers seeking to leverage existing knowledge effectively. While extracting structured data from unstructured text using large language models is gaining popularity, traditional methods typically generate key-value pairs data with straightforward schemas. In contr
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-15T15:05:57.000Z
First collected: 2026-09-20T08:40:59.508Z. This is not the publication date.