Triple

T12356657
Position Surface form Disambiguated ID Type / Status
Subject The Lover E294629 entity
Predicate hasCharacter P2308 FINISHED
Object John unclear NED1 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: John | Statement: [The Lover, hasCharacter, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [The Lover, hasCharacter, John]
  • A. John
    John is the nickname of John Riggins, a former American football running back best known for his Hall of Fame career with the Washington Redskins in the NFL.
  • B. John
    John is the given name of the American composer John Luther Adams, known for his works inspired by nature and environmental themes.
  • C. John
    John is the given name of John Boyd-Carpenter, a prominent British Conservative politician who served in several senior government positions in the mid-20th century.
  • D. John
    John is the given name of actor John Cho, a Korean American performer known for roles in the "Harold & Kumar" films and the "Star Trek" reboot series.
  • E. John
    John is the first name of the fictional character John Connor, the prophesied leader of the human resistance in the Terminator franchise.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69d6ab6ccbec8190b09e2d357aa80064 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f8e64dc81908c2242c68cd1b86e completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63461cacc81909958fbd745e5d065 completed May 2, 2026, 5:29 p.m.
Created at: April 8, 2026, 9:54 p.m.