The search-based parser extracted 350 complete seed-mediated recipes with the morphological outcomes, which were all manually corrected to give 331 recipes. A sample of 224 recipes from this along with 22 recipes sampled from the "hard" dataset were used as training data to fine-tune Llama-2 (13B, 8-bit quantized) 39 so that, from a given seed-mediated recipe text, the model can extract a structured recipe in JSON format. Annotations of these recipes were carefully curated to use only text as presented verbatim in the input text, thereby attempting to avoid hallucination artifacts. As LLMs are sequence-to-sequence models, output order could cause variations in the output, so annotations were made to reflect the order the precursors were presented in the input text. The keys of the output JSON were 'seed solution', 'growth solution', and 'mixed seed'.