Triple
T29393798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NWI |
E745439
|
entity |
| Predicate | hasPassengerTerminalAtAirport |
P98033
|
FINISHED |
| Object | single terminal |
—
|
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: single terminal | Statement: [NWI, hasPassengerTerminalAtAirport, single terminal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerTerminalAtAirport Context triple: [NWI, hasPassengerTerminalAtAirport, single terminal]
-
A.
hasPassengerTerminal
Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
-
B.
hasPassengerTerminalFunction
Indicates that something serves the role or performs the function of a passenger terminal, supporting the handling and movement of passengers.
-
C.
hasPassengerTerminalSector
Indicates that a passenger terminal is divided into or associated with a specific sector or subsection within it.
-
D.
hasPassengerTerminalFacilities
Indicates that an entity provides facilities or infrastructure specifically intended for handling and serving passengers.
-
E.
hasNumberOfPassengerTerminalsAtAirport
chosen
Indicates the relationship that specifies how many passenger terminals are present at a given airport.
- 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_69f0a79dfabc81908755382ee47791e2 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69fd6a1c1c4881908090053bc359b181 |
completed | May 8, 2026, 4:44 a.m. |
| PD | Predicate disambiguation | batch_69fd696f24d8819091033afacbdaadc5 |
completed | May 8, 2026, 4:41 a.m. |
Created at: April 28, 2026, 2:44 p.m.