Triple
T12411064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kayseri Erkilet Airport |
E296513
|
entity |
| Predicate | civilMilitary |
P71540
|
FINISHED |
| Object | joint-use |
—
|
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: joint-use | Statement: [Kayseri Erkilet Airport, civilMilitary, joint-use]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: civilMilitary Context triple: [Kayseri Erkilet Airport, civilMilitary, joint-use]
-
A.
civilOrMilitary
Indicates that something is classified as either civil (non-military) or military in nature or function.
-
B.
countryMilitary
Indicates that a country possesses, controls, or is associated with a particular military force or armed organization.
-
C.
isCivilMilitary
chosen
Indicates that an entity or relationship involves both civilian and military components or functions.
-
D.
militaryDomain
Indicates that the relationship or action occurs within, pertains to, or is specifically associated with the military sphere or context.
-
E.
militaryIssue
Indicates that one entity formally provides or distributes military-related items, orders, or directives to another entity.
- 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_69d6ad9f464c81909db36d7e96e34b9e |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e1888b48190bd750f839a26e99e |
completed | April 10, 2026, 7:23 p.m. |
| PD | Predicate disambiguation | batch_69d94d354b488190adc83fb4f2770dd5 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:55 p.m.