Triple

T16811231
Position Surface form Disambiguated ID Type / Status
Subject Caitlyn Jenner E408615 entity
Predicate givenName P17 FINISHED
Object Caitlyn E408615 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: Caitlyn | Statement: [Caitlyn Jenner, givenName, Caitlyn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caitlyn
Context triple: [Caitlyn Jenner, givenName, Caitlyn]
  • A. Caitlyn chosen
    Caitlyn is the given name of Caitlyn Jenner, the American television personality and former Olympic gold medal–winning decathlete.
  • B. Sona
    Sona is a notoriously brutal and lawless Panamanian prison featured in the television series "Prison Break."
  • C. Katarina
    Katarina is a feminine given name, commonly used in various European cultures, that is a variant of the name Catherine.
  • D. Maria Lilina
    Maria Lilina was a prominent Russian stage actress of the Moscow Art Theatre and the wife and close artistic collaborator of theatre director Konstantin Stanislavski.
  • E. Leona
    Leona is a feminine given name used in various cultures, often derived from the Latin word for "lion."
  • 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_69d88393905081908d00a86b99996ac8 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b2d0793c81909d938ac174a6e63a completed April 18, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00b290d8e4819082880444b42ffa43 completed May 10, 2026, 4:30 p.m.
Created at: April 10, 2026, 5:23 a.m.