Triple
T27454696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 3L |
E692554
|
entity |
| Predicate | hasParallelRunwaySystemRole |
P183984
|
FINISHED |
| Object | separates traffic flows on parallel runways |
—
|
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: separates traffic flows on parallel runways | Statement: [Runway 3L, hasParallelRunwaySystemRole, separates traffic flows on parallel runways]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParallelRunwaySystemRole Context triple: [Runway 3L, hasParallelRunwaySystemRole, separates traffic flows on parallel runways]
-
A.
hasParallelRunway
Indicates that one runway is parallel in orientation and alignment to another runway.
-
B.
hasParallelRunwayIndicator
Indicates that one runway serves as a parallel counterpart or reference indicator for another runway within an airport or airfield.
-
C.
hasSecondaryRunway
Indicates that an entity possesses an additional runway beyond its primary runway.
-
D.
hasOppositeRunway
Indicates that one runway is paired with another runway that has the opposite or reciprocal orientation or designation.
-
E.
hasRunwaysAt
Indicates that a location or facility possesses one or more runways situated at that place.
- F. None of above. chosen
Provenance (4 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_69ef5207903881909427745cda05d27a |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f7aaabb58c8190bf81673608ecfb6e |
completed | May 3, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f7aa6795f481908940838ee7041ff5 |
completed | May 3, 2026, 8:04 p.m. |
Created at: April 27, 2026, 12:48 p.m.