The first step to building your knowledge graph is to extract text from PDF documents. Noisy extraction creates duplicate entities and messy relationships — but the right balance of speed and quality depends on your dataset and how much you’re willing to resolve downstream.
In this module, you’ll extract text from PDFs using multiple approaches and understand the tradeoffs between speed, quality, and cost.
You’ll learn:
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What one can do with a structured graph from unstructured text
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Approaches to extracting text from PDF documents to plain text
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How to handle garbled and image-only PDFs with OCR
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How combined extraction packages and vision models compare to modular tools
This module builds the foundation — everything downstream depends on extraction quality.