Triple

T20003447
Position Surface form Disambiguated ID Type / Status
Subject Apple Special Event June 2014 E494391 entity
Predicate presenter P83 FINISHED
Object Phil Schiller 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: Phil Schiller | Statement: [Apple Special Event June 2014, presenter, Phil Schiller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Phil Schiller
Context triple: [Apple Special Event June 2014, presenter, Phil Schiller]
  • A. Phil Schiller chosen
    Phil Schiller is a longtime Apple executive who has played a key role in the company’s product marketing and major keynote presentations.
  • B. Phil Klemmer
    Phil Klemmer is an American television writer and producer best known for his work on genre series such as DC's Legends of Tomorrow and Chuck.
  • C. Randy Komisar
    Randy Komisar is an American venture capitalist, entrepreneur, and author known for his work with Silicon Valley startups and his role as a partner at Kleiner Perkins.
  • D. Steve Levine
    Steve Levine is a British record producer best known for his work in the 1980s with artists such as Culture Club and The Beach Boys.
  • E. Jonathan I. Schwartz
    Jonathan I. Schwartz is an American technology executive best known for serving as the CEO of Sun Microsystems during the mid-2000s.
  • 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_69da626b2d748190886981ea90c8b2ea completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e661a3ad148190918f9dce755fe470 completed April 20, 2026, 5:25 p.m.
Created at: April 11, 2026, 3:33 p.m.