Triple

T7828328
Position Surface form Disambiguated ID Type / Status
Subject Korea Football Association E181300 entity
Predicate hasAbbreviation P43 FINISHED
Object KFA E695347 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: KFA | Statement: [Korea Football Association, hasAbbreviation, KFA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KFA
Context triple: [Korea Football Association, hasAbbreviation, KFA]
  • A. KFA chosen
    KFA is the commonly used abbreviation for the Korea Football Association, the governing body of football in South Korea.
  • B. KAF
    KAF is the Kenya Air Force, the aerial warfare branch of the Kenya Defence Forces responsible for defending Kenyan airspace and providing air support to military operations.
  • C. AFA
    AFA is the Argentine Football Association, the main governing body responsible for organizing and regulating football in Argentina, including its national teams and professional leagues.
  • D. FAFC
    FAFC is the common abbreviation for Forfar Athletic Football Club, a Scottish professional football team based in the town of Forfar.
  • E. GFA
    GFA is the ICAO airline designator used for Gulf Air, the national carrier of Bahrain.
  • 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_69ca8282ccec819083c48efb72d21cf9 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb04a97d748190b1924890b1328bf1 completed March 30, 2026, 11:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb5a854fac8190802599615a0f7bc4 completed March 31, 2026, 5:24 a.m.
Created at: March 30, 2026, 4:43 p.m.