Data ingestion infrastructure built for a TRR 266 working paper, extracting machine-readable corporate annual report sections for NLP analysis.
Academic researchers studying climate disclosure compliance needed financial statements and audit reports from six years of STOXX Europe 600 annual reports (2018–2023) converted into structured NLP datasets. Manual coding across thousands of unstructured PDF pages was impossible.
Developed an automated data pipeline using PyMuPDF and LLM-backed section identification. Built an explicit page-level provenance tracking layer so that any extracted sentence in the final NLP dataset could be traced back directly to its exact page in the source PDF.
Extracted 6.3M+ structured paragraphs across STOXX Europe 600 corporate filings, serving as the empirical foundation for SSRN 4763140.
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