Triple

T2631812
Position Surface form Disambiguated ID Type / Status
Subject CAF E59649 entity
Predicate hasSubsidiary P254 FINISHED
Object CAF USA E59649 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: CAF USA | Statement: [CAF, hasSubsidiary, CAF USA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CAF USA
Context triple: [CAF, hasSubsidiary, CAF USA]
  • A. CAF chosen
    CAF is a Spanish multinational company that designs and manufactures railway vehicles and related transport equipment used by metro systems worldwide.
  • B. CAF
    CAF is the commonly used acronym for the Canadian Armed Forces, the unified military organization responsible for defending Canada and supporting international peace and security operations.
  • C. CAF
    CAF is an abbreviation that can refer to various organizations or groups, most notably the Cactus Air Force, a World War II Allied air unit based on Guadalcanal.
  • D. CAF
    CAF is the commonly used abbreviation for the Chief of Air Force, the professional head of an air force service.
  • E. CAF
    CAF is the Confederation of African Football, the governing body for association football in Africa and one of FIFA’s six continental confederations.
  • 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_69ab4ac8596c8190b34997e73d9e991c completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8c6e540819087c7f92432b27b0f completed March 7, 2026, 7:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69af90a7021081909f81c4ddb48fa00c completed March 10, 2026, 3:31 a.m.
Created at: March 6, 2026, 9:50 p.m.