Apply self-consistency to improve data extraction accuracy. ## Source Document {{source_document}} ## Extraction Schema {{extraction_schema}} Perform multiple independent extractions: **Extraction 1: Sequential Scan** Read document start to finish, extract fields. ```json // Extraction result 1 ``` **Extraction 2: Schema-Driven** For each schema field, find matching content. ```json // Extraction result 2 ``` **Extraction 3: Key Phrase Focus** Identify key phrases, map to schema fields. ```json // Extraction result 3 ``` **Consistency Analysis** - Fields with consistent values - Fields with discrepancies - Confidence scores per field **Final Extraction** Consensus result with: - Most confident values - Uncertainty flags - Extraction confidence per field ```json // Final consensus extraction ```
Self-Consistency for Data Extraction
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Apply self-consistency to data extraction using sequential, schema-driven, and key phrase approaches for improved accuracy.
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Category
AnalysisUse Cases
Data extractionDocument processingAccuracy improvement
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claude-sonnet-4-20250514gpt-4o
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