llm-extraction-formfill

To convert OCR text to structured JSON with provenance, you can use schema-guided extraction to emit a filled_form.json containing value, confidence, source_spans, and rationale for each field.

The best way to fill forms from transcripts without hallucinations is applying deterministic validators and schema-constrained decoding to return unknown_reason when derivation is not possible.

Yes, schema-constrained decoding works with local LLMs for document extraction by applying extraction prompts and validation workflows to safely fill structured fields from OCR transcripts.

To track uncertainty and source spans during JSON extraction, the workflow emits fields for confidence, source_spans, and rationale alongside the extracted value in the structured output.

Your OCR to JSON extraction returns unknown_reason when the schema-guided extraction process determines that derivation of a specific field is not possible from the available document text.

Yes, you can use reusable prompts and schemas to extract structured fields from documents, enabling deterministic validation and safe form-filling across multiple OCR transcripts.