Two different surrogate models were trained on the two cleaned datasets, namely a BigBirdPegasus model and a LongformerEncoderDecoder (LED) model . Both models have been used in the past for sequence-to-sequence language modelling tasks (such as machine translation or text summarization) and shown excellent performance. Both are transformer models based on the BART architecture with Table : Evaluation metrics of the surrogate models trained on the two different datasets when compared to the cleaned dataset created by the Llama models as the ground truth. The results for the raw and cleaned datasets created by ChemicalTagger and the raw dataset created by Llama-3.1-8B-Instruct are also given for comparison.