Triple
T21347315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 05R/23L |
E526371
|
entity |
| Predicate | hasParallelRunwayDesignation |
P54806
|
FINISHED |
| Object | right |
—
|
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: right | Statement: [Runway 05R/23L, hasParallelRunwayDesignation, right]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParallelRunwayDesignation Context triple: [Runway 05R/23L, hasParallelRunwayDesignation, right]
-
A.
hasParallelRunwayIndicator
Indicates that one runway serves as a parallel counterpart or reference indicator for another runway within an airport or airfield.
-
B.
hasParallelRunway
Indicates that one runway is parallel in orientation and alignment to another runway.
-
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.
hasRunwayDesignationSide
chosen
Indicates that a runway designation is associated with a specific side or direction of the runway (e.g., left, right, or center).
- 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_69e0b51cd5cc81909ac1187971e8a8ad |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69ee5ba8f1c8819089c5d753876b44d5 |
completed | April 26, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_69e6161feea4819091d13bb003363279 |
completed | April 20, 2026, 12:03 p.m. |
Created at: April 16, 2026, 4:56 p.m.