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 The `sec-parser` project simplifies extracting meaningful information from SEC EDGAR HTML documents by organizing them into semantic elements and a tree structure. Semantic elements might include section titles, paragraphs, and tables, each classified for easier data manipulation. This forms a semantic tree that corresponds to the visual and informational structure of the document. If you're familiar with the <a href="https://www.google.com/search?tbm=isch&q=image+semantic+segmentation" target="_blank">Image Semantic Segmentation</a> concept, it's the same but applied to HTML documents.
 
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 This tool is especially beneficial for Artificial Intelligence (AI), Machine Learning (ML), and Large Language Models (LLM) applications by streamlining data pre-processing and feature extraction.
 
 - Explore the [**Demo**](https://parser.app.alphanome.dev/)