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Expert Dossiers
Meetings

Attendee Extraction

Derive likely participants from transcript text, calendar context, mentions, and source metadata.

Purpose

Build the candidate person set used by speaker verification, follow-up drafting, and relationship context.

When to use it

  • The transcript mentions people not present on the invite.
  • The calendar roster is incomplete or unavailable.
  • You need to distinguish attendees, mentioned people, and owners.

Inputs

  • Transcript segments
  • Calendar roster
  • Known people list

Outputs

  • Candidate attendees
  • Mentioned non-attendees
  • Unresolved person references

Steps

  1. Collect names and email handles from calendar, transcript, and source metadata.
  2. Classify each person as expected, spoken, mentioned, or unresolved.
  3. Merge duplicates only when evidence is strong.
  4. Return unresolved nicknames and pronouns for review.

Quality checks

  • Attendee status is not treated as speaking proof.
  • External people and internal people are not merged by first name alone.

Failure modes

  • A common first name maps to the wrong person.
  • Transcript labels use roles instead of names.

Privacy notes

  • Person rosters can reveal sensitive customer or employee context.
  • Keep unresolved names out of public artifacts.

Example prompt

Extract candidate attendees and mentioned non-attendees. Separate expected attendance from evidence that someone spoke.

Example structured output

{"expected":["Dana","Lee"],"spokenCandidates":["Dana","Morgan"],"mentionedOnly":["Erich"],"unresolved":["Ray?"]}