Triple
T7227390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adisutjipto International Airport |
E154813
|
entity |
| Predicate | isMilitaryCivilian |
P71540
|
FINISHED |
| Object | joint-use airport |
—
|
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 airport | Statement: [Adisutjipto International Airport, isMilitaryCivilian, joint-use airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMilitaryCivilian Context triple: [Adisutjipto International Airport, isMilitaryCivilian, joint-use airport]
-
A.
isCivilMilitary
chosen
Indicates that an entity or relationship involves both civilian and military components or functions.
-
B.
isCivilian
Indicates that an entity is a non-military, non-combatant individual in the context of a given situation or system.
-
C.
isCivilianOffice
Indicates that an office or position is non-military and belongs to the civilian sphere of authority or administration.
-
D.
isMilitaryOfficer
Indicates that the subject holds an official position as an officer within a military organization.
-
E.
hasMilitaryStatus
Indicates that an entity possesses a specific military affiliation, role, or status (such as active duty, reserve, or veteran).
- 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_69c68811dd1c8190ac460bb39e64e1f0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6e9df72cc81908d1c04e6e310fbb4 |
completed | March 27, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69c6e761b7fc8190857794d78af1b468 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:54 p.m.