Triple

T18482014
Position Surface form Disambiguated ID Type / Status
Subject Aubrey O’Day E451583 entity
Predicate givenName P17 FINISHED
Object Aubrey NE NERFINISHED

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: Aubrey | Statement: [Aubrey O’Day, givenName, Aubrey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aubrey
Context triple: [Aubrey O’Day, givenName, Aubrey]
  • A. Aubrey chosen
    Aubrey is the first name of Canadian rapper, singer, and actor Drake (Aubrey Drake Graham).
  • B. Aubrey
    Aubrey is a small suburban town in the greater Dallas–Fort Worth metropolitan area in Texas.
  • C. Aubrey Lee
    Aubrey Lee is a television producer best known for serving as an executive producer on the mystery-comedy series "The Afterparty."
  • D. Aubrey Morris
    Aubrey Morris was a British character actor known for his distinctive eccentric roles in films such as "A Clockwork Orange" and numerous television appearances.
  • E. Aubrey Woods
    Aubrey Woods was a British actor best known for his role as Bill the Candy Man in the 1971 film "Willy Wonka & the Chocolate Factory."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38465a0819099b9b42d2a662ac1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e531d49a1881908cc2ad6132953c96 completed April 19, 2026, 7:49 p.m.
Created at: April 10, 2026, 11:35 a.m.