This work compares task-specific fine-tuning of smaller LLMs (Figure branch A) with ICL of foundation LLMs (Figure branch B) on a NER task in the materials fatigue domain. The datasets, algorithms, and tools are described thoroughly in the Methods section and summarized in the following paragraphs. The Ma-terioMiner dataset acts as the test dataset on which the NER approaches are compared. An additional dataset was created by annotating text extracted from 47 peer-reviewed publications in the materials fatigue domain. This dataset was further split into a training and a validation set. All datasets are based on the materials mechanics ontology 31 , which amongst others describes the named entity types as classes. While the same annotation guidelines were followed to create the datasets, they exhibit distinct data distributions, specifically different distribution of annotated classes and a small domain shift. Complementary to the stronger emphasis on materials fatigue in the train and validation set, the scientific articles that contribute to the test set have additionally a focus on microstructure-property relationships.