Large-scale dataset of automatically classified rhetorical sections in scientific papers

Researchers present a dataset of section-level annotations for millions of scientific papers from the Semantic Scholar Open Research Corpus (S2ORC). Using a rule-based classification algorithm, they identified and labeled major sections across 15.6 million papers after quality filtering.

• The dataset covers primarily STEM disciplines with strong representation in medicine and biology.
• Validation shows classifier agreement with human annotators is on par with human inter-annotator agreement.
• The resource enables large-scale computational studies of scientific discourse and writing patterns.