Triple
T12180801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MAJ |
E290211
|
entity |
| Predicate | airportHasPassengerService |
P95217
|
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: [MAJ, airportHasPassengerService, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportHasPassengerService Context triple: [MAJ, airportHasPassengerService, yes]
-
A.
airportTypePresent
Indicates that a specific type or category of airport is present or exists in relation to the referenced entity.
-
B.
isPassengerAirport
chosen
Indicates that an airport primarily serves commercial passenger air traffic rather than cargo or other specialized operations.
-
C.
airportServesAs
Indicates that an airport functions in a particular role or capacity (such as primary, secondary, or hub) for a specified area, organization, or service.
-
D.
airportServed
Indicates that a particular airport provides service to, or is used for air travel to and from, a given location or area.
-
E.
airportUse
Indicates that an airport is used or utilized by a particular entity, such as an airline, organization, or service.
- 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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91a83012c81908d04bbab5fdcd8c2 |
completed | April 10, 2026, 3:42 p.m. |
| PD | Predicate disambiguation | batch_69d91510a258819090ef8fbdc2d8707b |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:50 p.m.