Triple

T2134286
Position Surface form Disambiguated ID Type / Status
Subject Jeff Skoll E46613 entity
Predicate notableWork P4 FINISHED
Object Participant Media E177062 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Participant Media | Statement: [Jeff Skoll, notableWork, Participant Media]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Participant Media
Context triple: [Jeff Skoll, notableWork, Participant Media]
  • A. Participant Media chosen
    Participant Media is an American film and television production company known for creating socially conscious, issue-driven content that aims to inspire activism and change.
  • B. Participant Productions
    Participant Productions is a film production company known for creating socially conscious, issue-driven movies and documentaries.
  • C. 1+1 Media Group
    1+1 Media Group is a major Ukrainian media holding company that operates television channels, digital platforms, and other media assets.
  • D. Intermedia Films
    Intermedia Films is an independent film production company known for financing and producing a range of international feature films.
  • E. Katalyst Media
    Katalyst Media is a production company co-founded by actor and entrepreneur Ashton Kutcher, known for creating television, film, and digital media content.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a88a174ab48190a5db20c132e5dccf completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbba24004819091ffb9440e8615fa completed March 7, 2026, 5:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae58d3275481909c8d74ca7c037ddd completed March 9, 2026, 5:21 a.m.
Created at: March 4, 2026, 7:44 p.m.