A data engineer receives a batch of scanned insurance forms saved as PDF files. The text layer is absent from all files. Which processing step is required before these documents can be passed to a large language model for information extraction?
- ARun a diffusion-based image enhancement model to upscale the scanned pages before ingestion.
- BApply optical character recognition to convert the rasterised page images into a plain-text representation. Correct
- CUse a CLIP-based embedding model to index the page images by semantic similarity before retrieval.
- DParse the PDF cross-reference table to locate embedded font descriptors and reconstruct the character stream.
Why A is wrong: Upscaling improves visual resolution but does not produce a machine-readable text layer; the LLM still receives no extractable text without an OCR step.
Why B is correct: Scanned PDFs contain only pixel data with no embedded text. OCR analyses the image and outputs a character sequence, producing the text layer an LLM can consume.
Why C is wrong: CLIP enables image-text similarity search but does not extract the document text itself; downstream LLM prompting still lacks the raw text content from the forms.
Why D is wrong: Font descriptor parsing applies to digitally-created PDFs that embed a text layer; scanned documents store pages as raster images and have no font or character stream to parse.