Triple

T17474024
Position Surface form Disambiguated ID Type / Status
Subject 11th Wing E425490 entity
Predicate hasAbbreviation P43 FINISHED
Object Ala 11 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: Ala 11 | Statement: [11th Wing, hasAbbreviation, Ala 11]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ala 11
Context triple: [11th Wing, hasAbbreviation, Ala 11]
  • A. Ala 11 chosen
    Ala 11 is a fighter wing of the Spanish Air Force known for operating modern combat aircraft and contributing to Spain’s air defense and tactical operations.
  • B. Ala 12
    Ala 12 is a fighter wing of the Spanish Air Force known for operating modern combat aircraft and participating in national and international air defense missions.
  • C. Ala 14
    Ala 14 is a fighter wing of the Spanish Air Force known for operating advanced combat aircraft in air defense and tactical missions.
  • D. Ala 31
    Ala 31 is a transport wing of the Spanish Air Force, primarily responsible for strategic and tactical airlift missions.
  • E. Ala 15
    Ala 15 is a fighter wing of the Spanish Air Force known for operating modern combat aircraft and conducting air defense and tactical missions.
  • 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_69d889dbc2e88190b18ea6115e819258 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e451baa7b0819092035fec42305397 completed April 19, 2026, 3:53 a.m.
Created at: April 10, 2026, 5:47 a.m.