Triple
T10299126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 01R/19L |
E241577
|
entity |
| Predicate | airportTypeServed |
P54051
|
FINISHED |
| Object | civil airport |
—
|
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: civil airport | Statement: [Runway 01R/19L, airportTypeServed, civil airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportTypeServed Context triple: [Runway 01R/19L, airportTypeServed, civil airport]
-
A.
airportServed
Indicates that a particular airport provides service to, or is used for air travel to and from, a given location or area.
-
B.
servesAirportType
chosen
Indicates that a transportation service or facility provides service to, or is designated for, a specific type or category of airport.
-
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.
associatedAirportServes
Indicates that a given airport provides service to, or is used by, the associated entity (such as a city, region, or facility).
-
E.
servesAirport
Indicates that a transportation service or route provides access to and operates for a particular 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2ee10f88190b1615c49b8f24a26 |
completed | April 7, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f35e548190be3b4d92d65d2d20 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:44 a.m.