docs: v1.1.0 structured extraction — README + website#3
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README: - Updated pipeline diagram to show JSON output - Added --schema CLI option to options table - New "Structured Extraction" section with JSON, KV, table, normalization, and schema-guided extraction docs + examples - Updated MCP server and project structure sections Website (site/index.html): - Version bump to v1.1.0 - Two new feature cards: structured extraction + value normalization - New "Structured Extraction" section with JSON output examples - Pipeline step 6 (Structure) added - FAQ and footer updated Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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README: - Updated pipeline diagram to show JSON output - Added --schema CLI option to options table - New "Structured Extraction" section with JSON, KV, table, normalization, and schema-guided extraction docs + examples - Updated MCP server and project structure sections Website (site/index.html): - Version bump to v1.1.0 - Two new feature cards: structured extraction + value normalization - New "Structured Extraction" section with JSON output examples - Pipeline step 6 (Structure) added - FAQ and footer updated Co-authored-by: Nameet Potnis <nameetpotnis@Nameets-MacBook-Pro.local> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
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…dataloader-bench) - Add Docling table overlay for docs the classifier missed (TEDS 0.704 → 0.884) - Add TOC table filter to prevent false table injection - Add split bold heading detection for multi-span bold patterns - Add horizontal-line table detection (h_lines >= 4) - Add garbage table filter in fast.py for PyMuPDF 1.27 regression - Update README with #3 ranking (0.867 overall) Benchmark: 0.8671 overall, 0.910 NID, 0.884 TEDS, 0.739 MHS Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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