Triple
T1425551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nantucket Memorial Airport |
E30322
|
entity |
| Predicate | hasAirlineService |
P12356
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Nantucket Memorial Airport, hasAirlineService, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAirlineService Context triple: [Nantucket Memorial Airport, hasAirlineService, yes]
-
A.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
-
B.
servesAirlineType
Indicates that a service provider (such as an airport, terminal, or facility) accommodates or operates flights for a specified type or category of airline.
-
C.
servesAirline
chosen
Indicates that a transportation facility or location provides service for, or is regularly used by, a specified airline.
-
D.
hasPassengerOnlyService
Indicates that the service provided involves only the transportation of passengers, with no freight or cargo component.
-
E.
airlineType
Indicates the classification or category of an airline based on its operational or service characteristics.
- 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_69a498fb823c8190a67ce4c4837e641a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c52e4ed881908d85e0cb9fe851ac |
completed | March 1, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69a4c4752abc8190a33b634c4d6fad28 |
completed | March 1, 2026, 10:57 p.m. |
Created at: March 1, 2026, 8 p.m.