Triple

T19504321
Position Surface form Disambiguated ID Type / Status
Subject Apple September 2022 event E487979 entity
Predicate presenter P83 FINISHED
Object Kaiann Drance 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: Kaiann Drance | Statement: [Apple September 2022 event, presenter, Kaiann Drance]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaiann Drance
Context triple: [Apple September 2022 event, presenter, Kaiann Drance]
  • A. Kaiann Drance chosen
    Kaiann Drance is a senior Apple executive who frequently appears in product launch events to present and explain new iPhone features.
  • B. Keeve Trennis
    Keeve Trennis is a young Jedi Knight from Star Wars’ High Republic era, known for her strong connection to the Force, self-doubt, and growth amid the Republic’s golden age.
  • C. Kai Dugan
    Kai Dugan is the son of American actress Jennifer Connelly, known primarily for his connection to his famous mother.
  • D. Kai Knapp
    Kai Knapp is the daughter of American actress Alexis Knapp and actor Ryan Phillippe, known primarily for her connection to her celebrity parents.
  • E. Kai Widdrington
    Kai Widdrington is a British professional dancer and choreographer best known for his appearances on television dance competitions such as Strictly Come Dancing.
  • 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_69d8e8d9d1c88190b01cd78b8be49384 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e635105db8819084915dc2d047188d completed April 20, 2026, 2:15 p.m.
Created at: April 10, 2026, 1:40 p.m.