Triple
T27382541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 16L/34R |
E691273
|
entity |
| Predicate | hasPositionRelativeToParallelRunways |
P164319
|
FINISHED |
| Object | left |
—
|
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: left | Statement: [Runway 16L/34R, hasPositionRelativeToParallelRunways, left]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPositionRelativeToParallelRunways Context triple: [Runway 16L/34R, hasPositionRelativeToParallelRunways, left]
-
A.
hasRunwayPosition
chosen
Indicates the spatial or designated placement of an aircraft or object relative to a specific runway.
-
B.
hasParallelRunwayIndicator
Indicates that one runway serves as a parallel counterpart or reference indicator for another runway within an airport or airfield.
-
C.
hasRelativePositionAtAirport
Indicates that one entity has a specific spatial or positional relationship to another entity within the context or layout of an airport.
-
D.
hasOppositeRunway
Indicates that one runway is paired with another runway that has the opposite or reciprocal orientation or designation.
-
E.
hasParallelRunwaySystemRole
Indicates that an entity holds a specific role or function within a parallel runway system.
- 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_69ef52022538819081f873d0c84a6dd6 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c475c58c8190a883554231e88c88 |
completed | May 3, 2026, 9:56 p.m. |
Created at: April 27, 2026, 12:23 p.m.