To avoid capturing misleading relations, we devised a set of rules to be fulfilled in every single sentence: (i) The same number of materials, products, and FE values should be reported, (ii) the same number of materials and FEs should be reported for a single CO 2 RR product, or (iii) the same number of FEs and CO 2 RR products should be reported with a single material composition. In addition, the sentence should explicitly contain the term "faradaic efficiency" or "FE" and a value reported with "%" as a unit. Finally, to ensure the quality of the data we employed the GPT API extracted, the target product, one of the ten elements obtained in our first analysis, and the sentence from which the relation was extracted. We set all parameters to zero except the maximum token length, which we set to 1, thereby, drastically reducing the probability of the model "hallucinating".