How to Extract JSON-LD from Web Pages and Verify Its Claims
Inventory embedded JSON-LD with a tested Python example, select the right entity, and check extracted fields against readable page evidence.
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Inventory embedded JSON-LD with a tested Python example, select the right entity, and check extracted fields against readable page evidence.
Design narrow agent web tools with validated inputs, bounded content, URL identity, explicit errors, and usage fields. Includes a tested public-page adapter.
Check extracted documents for missing facts, sidebar noise, broken structure, and unknown provenance before admitting them to model context.
Build a reviewable screenshot evidence bundle with source URLs, separate capture times, companion text, file hashes, and explicit human review decisions.
Keep pricing observations comparable with billing and currency context, original text, screenshots, and review states. Includes a tested collector and evidence record.
Match paper identity, distinguish preprints from published versions, and preserve the passage behind each citation. Includes a BERT example and tested page collector.
Build a reviewable news monitoring workflow with source states, separate timestamps, correction handling, and optional screenshot evidence. Includes a tested collection probe.
Match an image candidate to its source page, caption, and credit. Build a claim-scoped evidence record that keeps missing context and provenance questions visible.
Decide when cached web content is fresh enough for an answer, preserve original observations, and handle unknown age or failed refreshes without hiding them.