Triple
T26766958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilmington Air Park |
E674963
|
entity |
| Predicate | hasBasedAirline |
P165825
|
FINISHED |
| Object | Amazon Air |
—
|
NE NERFINISHED |
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: Amazon Air | Statement: [Wilmington Air Park, hasBasedAirline, Amazon Air]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBasedAirline Context triple: [Wilmington Air Park, hasBasedAirline, Amazon Air]
-
A.
usedByAirlineBase
chosen
Indicates that a particular airline base is utilized or operated by a specific airline.
-
B.
ownsAirline
Indicates that one entity has legal ownership or controlling interest in an airline company.
-
C.
hasAirlines
Indicates that one entity (such as an airport, city, or country) is served by or associated with one or more airline operators.
-
D.
hasBasedAircraft
Indicates that an aircraft is regularly stationed or primarily based at a particular location or facility.
-
E.
servesAirline
Indicates that a transportation facility or location provides service for, or is regularly used by, a specified airline.
- 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_69eecda85298819097ee1c38a3d772e7 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 27, 2026, 4 a.m.