Triple

T16332190
Position Surface form Disambiguated ID Type / Status
Subject Auberjonois E396581 entity
Predicate notableBearer P458 FINISHED
Object René Auberjonois E91827 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: René Auberjonois | Statement: [Auberjonois, notableBearer, René Auberjonois]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: René Auberjonois
Context triple: [Auberjonois, notableBearer, René Auberjonois]
  • A. Rene Auberjonois chosen
    Rene Auberjonois was an American actor best known for his character roles in film and television, including his portrayal of Odo on "Star Trek: Deep Space Nine."
  • B. Tim Russ
    Tim Russ is an American actor, director, and musician best known for playing the Vulcan security officer Tuvok on Star Trek: Voyager.
  • C. Jeff Bennett
    Jeff Bennett is an American voice actor known for his extensive work in animation, including numerous roles in popular Cartoon Network and Disney series.
  • D. Seymour Cassel
    Seymour Cassel was an American character actor known for his longtime collaboration with director John Cassavetes and his roles in numerous independent and mainstream films.
  • E. Peter D. Graves
    Peter D. Graves is a film producer best known for his work on major Hollywood action and science fiction movies, including Terminator Salvation.
  • 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_69d87f255b788190a400eba031dd85d8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2c4e0b1388190824b286e8452fb32 completed April 17, 2026, 11:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a002dabc89481908005f5b2060abded completed May 10, 2026, 7:03 a.m.
Created at: April 10, 2026, 5:07 a.m.