Triple

T3262213
Position Surface form Disambiguated ID Type / Status
Subject Cameron Douglas E68437 entity
Predicate father P120 FINISHED
Object Michael Douglas E10733 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: Michael Douglas | Statement: [Cameron Douglas, father, Michael Douglas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Douglas
Context triple: [Cameron Douglas, father, Michael Douglas]
  • A. Michael Douglas chosen
    Michael Douglas is an acclaimed American actor and producer known for films like "Wall Street" and "Fatal Attraction," who has also been recognized for his humanitarian and peace-promoting work.
  • B. Ned Beatty
    Ned Beatty was an acclaimed American character actor known for his powerful supporting roles in films such as "Deliverance," "Network," and "Superman."
  • C. William Hurt
    William Hurt was an acclaimed American actor known for his intense, introspective performances in films such as "Kiss of the Spider Woman," "Broadcast News," and "The Big Chill."
  • D. Richard Gere
    Richard Gere is an American actor known for his leading roles in films such as "American Gigolo," "An Officer and a Gentleman," and "Pretty Woman."
  • E. James Woods
    James Woods is an American actor known for his intense performances in film and television, including acclaimed roles in movies such as "Salvador," "Videodrome," and "Casino."
  • 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_69ad8590444081909e8107a8aeef3a23 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adafa908e881908cbb2ad137819ffb completed March 8, 2026, 5:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34bb1c468819083b50b5858f8afe0 completed March 12, 2026, 11:26 p.m.
Created at: March 8, 2026, 3:09 p.m.