Triple
T5074703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsuiki Air Base |
E114364
|
entity |
| Predicate | airspaceRole |
P61259
|
FINISHED |
| Object | airspace surveillance |
—
|
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: airspace surveillance | Statement: [Tsuiki Air Base, airspaceRole, airspace surveillance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airspaceRole Context triple: [Tsuiki Air Base, airspaceRole, airspace surveillance]
-
A.
appliesToAirspaceOf
Indicates that a rule, restriction, or condition is specifically relevant to, or in effect within, a particular airspace.
-
B.
airportRole
Indicates that an entity serves a specific functional role or capacity within the context of an airport.
-
C.
hasAirspace
Indicates that one entity possesses, controls, or is associated with a defined region of airspace relative to another entity or area.
-
D.
testAircraftRole
Indicates that an aircraft is assigned or evaluated for a specific operational role or function.
-
E.
flightRegime
Indicates the operational conditions or phase of flight under which an aircraft or aerospace vehicle is functioning (e.g., speed, altitude, and atmospheric regime).
- F. None of above. chosen
Provenance (4 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_69bd443cf28c8190ad371d603563dbdd |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74d0be1c819081b26235fe602a30 |
completed | March 20, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69bd7157fe608190b4515d56fdd0a616 |
completed | March 20, 2026, 4:10 p.m. |
| PDg | Predicate description generation | batch_69bd73d90b608190bd6c2407e84e2b64 |
completed | March 20, 2026, 4:20 p.m. |
Created at: March 20, 2026, 1:39 p.m.