Triple

T19917612
Position Surface form Disambiguated ID Type / Status
Subject U.S. Triple Crown E478704 entity
Predicate notableWinner P2766 FINISHED
Object War Admiral 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: War Admiral | Statement: [U.S. Triple Crown, notableWinner, War Admiral]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: War Admiral
Context triple: [U.S. Triple Crown, notableWinner, War Admiral]
  • A. War Admiral chosen
    War Admiral was a legendary American Thoroughbred racehorse who won the U.S. Triple Crown in 1937 and became one of the most celebrated champions in racing history.
  • B. Admiral Grant
    Admiral Grant is a fictional high-ranking naval officer portrayed by actor John Amos.
  • C. Almirante
    Almirante is a coastal town in Panama known as a key port and transport hub in the Bocas del Toro region.
  • D. Nimitz
    Nimitz is a German-origin surname most famously associated with U.S. Fleet Admiral Chester W. Nimitz, a leading naval commander in the Pacific during World War II.
  • E. Morison
    Morison is a surname most notably associated with Samuel Eliot Morison, the Pulitzer Prize–winning American historian and naval officer.
  • 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_69d8e521855c8190b41871700afc8d6a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65995bd60819097cfad003dd29731 completed April 20, 2026, 4:51 p.m.
Created at: April 10, 2026, 1:53 p.m.