We used four Python libraries, BeautifulSoup 34 , re 35 , regex and chemdataextractor (CDE) for splitting the files in our corpus into sentences and identifying sections from which they were extracted in the articles. The latter step is particularly important as some of the information we intend to gather may predominantly reside in specific sections, and relying on data from other sections could potentially yield inaccurate outcomes. For instance, when examining the frequency of elements employed in catalysts, we exclusively considered abstracts as they are more direct, concise summaries of the article's scope and avoid connections with the literature (see subsection 2.3). Including the introduction section could add false counts to a particular element since it might be cited solely for contextualization. Similarly, adding the discussion section could also lead to false positives once authors often compared their results with the existing literature.