Triple
T32088590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 08/26 |
E819517
|
entity |
| Predicate | accommodatesAircraftType |
P46124
|
FINISHED |
| Object | large commercial aircraft |
—
|
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: large commercial aircraft | Statement: [Runway 08/26, accommodatesAircraftType, large commercial aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accommodatesAircraftType Context triple: [Runway 08/26, accommodatesAircraftType, large commercial aircraft]
-
A.
supportsAircraft
Indicates that one entity is capable of accommodating, carrying, or enabling the operation of an aircraft.
-
B.
runwaySupportsAircraftType
chosen
Indicates that a particular runway is suitable and certified for use by a specified type of aircraft.
-
C.
aircraftCapacity
Indicates the maximum number of passengers or amount of load that an aircraft is designed or allowed to carry.
-
D.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
E.
intendedAircraft
Indicates that an aircraft is the one planned or designated to be used for a particular flight, mission, or operation.
- 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_69f349004b2481908ce2e50af0d579a8 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b63982b88190a312d869093da48f |
completed | May 3, 2026, 2:43 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a7bdb481908d16a32f49e38c2c |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:25 a.m.