Triple

T2683783
Position Surface form Disambiguated ID Type / Status
Subject Larry Holmes vs. Gerry Cooney E57433 entity
Predicate fighter2RacePortrayal P41493 FINISHED
Object White LITERAL 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: White | Statement: [Larry Holmes vs. Gerry Cooney, fighter2RacePortrayal, White]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fighter2RacePortrayal
Context triple: [Larry Holmes vs. Gerry Cooney, fighter2RacePortrayal, White]
  • A. fighter2
    Indicates that the subject is the second participant (opponent) in a fighting or combat relationship or event.
  • B. fighter1
    Indicates that the subject is the first participant or primary combatant in a fight or competitive physical confrontation.
  • C. mainFighterAircraft
    Indicates that an aircraft serves as the primary fighter aircraft for a given country, organization, or military force.
  • D. primaryGermanFighterAircraft
    Indicates that the subject is the main or principal fighter aircraft used by Germany in a given context or time period.
  • E. primaryFighterModel
    Indicates that one entity is the main or standard fighter aircraft model associated with another entity (such as a country, air force, or military unit).
  • F. None of above. chosen

Provenance (4 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_69ab4a5028388190a36f3baf1588309e completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9d7692c81909d8fd9ce3817161b completed March 7, 2026, 7:55 a.m.
PD Predicate disambiguation batch_69abd81c9b4c81908e5e0da6ac5f828b completed March 7, 2026, 7:47 a.m.
PDg Predicate description generation batch_69abd891bcd481909af5340a64ff69f9 completed March 7, 2026, 7:49 a.m.
Created at: March 6, 2026, 9:54 p.m.