Triple

T1127427
Position Surface form Disambiguated ID Type / Status
Subject Mike Gartner E24751 entity
Predicate givenName P17 FINISHED
Object Michael E21023 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 | Statement: [Mike Gartner, givenName, Michael]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael
Context triple: [Mike Gartner, givenName, Michael]
  • A. Michael chosen
    Michael is a common masculine given name of Hebrew origin meaning "Who is like God?"
  • B. Kevin
    Kevin is the given name of Kevin Garnett, a Hall of Fame American professional basketball player known for his intensity, versatility, and NBA championship with the Boston Celtics.
  • C. Michael Jackson
    Michael Jackson was an American singer, songwriter, and dancer known as the "King of Pop," celebrated for his groundbreaking music, iconic dance moves, and immense influence on popular culture.
  • D. King
    King is a common English surname borne by numerous notable figures, including civil rights leader Martin Luther King Jr.
  • E. King
    King is a township in the Regional Municipality of York in Ontario, Canada, known for its rural landscapes, rolling hills, and equestrian farms within the Greater Toronto Area.
  • 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_69a4940712c88190aa244f3fc6070a65 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bbdd39b88190bf46de38818fe2df completed March 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac6f11a31481909e11a01b12841b3d completed March 7, 2026, 6:31 p.m.
Created at: March 1, 2026, 7:44 p.m.