Triple

T2628585
Position Surface form Disambiguated ID Type / Status
Subject Kauhava Air Base E59178 entity
Predicate hasCivilUse P23908 FINISHED
Object general aviation 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: general aviation | Statement: [Kauhava Air Base, hasCivilUse, general aviation]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCivilUse
Context triple: [Kauhava Air Base, hasCivilUse, general aviation]
  • A. civilianUse chosen
    Indicates that something is intended for, suitable for, or actually used by civilians rather than military or combat purposes.
  • B. hasSecularUse
    Indicates that something is used in a non-religious, worldly, or secular context or purpose.
  • C. hasHumanUse
    Indicates that something is used, employed, or utilized by humans for a particular purpose or benefit.
  • D. hasOfficialUse
    Indicates that something is used in an authorized or formally recognized capacity, typically by an official body or for official purposes.
  • E. hasCivilDivision
    Indicates that one administrative or political entity is subdivided into, or is associated with, a specific civil division (such as a county, district, or municipality).
  • F. None of above.

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_69ab4ac558388190962492cd2e1b0ce6 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abdb0e7b888190bfa5d2e33f00ec0f completed March 7, 2026, 8 a.m.
PD Predicate disambiguation batch_69abd810d7f481908e81c305772c4c14 completed March 7, 2026, 7:47 a.m.
Created at: March 6, 2026, 9:50 p.m.