Triple

T22356518
Position Surface form Disambiguated ID Type / Status
Subject Air Force Academy E552664 entity
Predicate abbreviation P43 FINISHED
Object AFA 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: AFA | Statement: [Air Force Academy, abbreviation, AFA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AFA
Context triple: [Air Force Academy, abbreviation, AFA]
  • A. AFA
    AFA is the IATA airport code for San Rafael's main airport in Mendoza Province, Argentina.
  • B. AFA
    AFA is an abbreviation commonly used for the ARY Film Awards, a Pakistani awards ceremony honoring achievements in the film industry.
  • C. AFA chosen
    AFA is the commonly used abbreviation for Academia da Força Aérea, the Brazilian Air Force Academy responsible for training future Air Force officers.
  • D. 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.
  • E. AFAA
    AFAA is the organization responsible for organizing and presenting the Asian Film Awards, which honor excellence in Asian cinema.
  • 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_69e11e4a0ad08190a385b4d343cf6524 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f157d08b148190a9a4e445e8579219 completed April 29, 2026, 12:58 a.m.
Created at: April 16, 2026, 8:44 p.m.