Triple

T694813
Position Surface form Disambiguated ID Type / Status
Subject Mike Schmidt E13872 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 Schmidt, givenName, Michael]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael
Context triple: [Mike Schmidt, 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
    The King is the reigning male monarch who serves as the head of state of the United Kingdom within its constitutional monarchy system.
  • 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_69a493406c408190957eeec9048a8fb6 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a0c3f39c8190a3014df428817492 completed March 1, 2026, 8:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69a637514c9081909938d0801f071fea completed March 3, 2026, 1:20 a.m.
Created at: March 1, 2026, 7:36 p.m.