Triple
T7816480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phu Quoc International Airport |
E181017
|
entity |
| Predicate | hasApronFor |
P40477
|
FINISHED |
| Object | commercial jets |
—
|
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: commercial jets | Statement: [Phu Quoc International Airport, hasApronFor, commercial jets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApronFor Context triple: [Phu Quoc International Airport, hasApronFor, commercial jets]
-
A.
hasApron
Indicates that one entity possesses or is wearing an apron in relation to another context or entity.
-
B.
hasApronType
Indicates that an entity is associated with or characterized by a specific type or category of apron.
-
C.
hasMilitaryApron
chosen
Indicates that a location or facility includes a designated apron area specifically used for military aircraft operations.
-
D.
hasGarment
Indicates that one entity possesses, wears, or is associated with a particular garment.
-
E.
wornOver
Indicates that one item of clothing or accessory is positioned on top of and covering another item when worn.
- 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_69ca828153f48190bdb27ac46f8e0745 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf96ea6d881908eff5f750e0f6700 |
completed | March 30, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69cae91687788190af9cb7aaa996d291 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:39 p.m.