Triple
T3999627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 07L/25R |
E87182
|
entity |
| Predicate | hasRightRunwayIn25Direction |
P53418
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Runway 07L/25R, hasRightRunwayIn25Direction, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRightRunwayIn25Direction Context triple: [Runway 07L/25R, hasRightRunwayIn25Direction, true]
-
A.
hasRunwayOrientation
Indicates that a runway is aligned or oriented in a specific directional heading.
-
B.
hasRunwayApproachType
Indicates the specific type or category of approach procedure associated with a runway.
-
C.
hasRunwayPresence
Indicates that an entity maintains a physical runway or landing strip suitable for aircraft operations.
-
D.
hasRunwayConfiguration
Indicates a specific arrangement or setup of runways associated with an airport, airfield, or similar facility.
-
E.
hasRunwayType
Indicates that an airport or airfield has a runway of a specified type or surface classification.
- 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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa8579288190940487ad07e38de0 |
completed | March 9, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69aef8f89f2881909b0965419d15d46c |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefa815f2c8190818c9ffd9d1bf478 |
completed | March 9, 2026, 4:51 p.m. |
Created at: March 9, 2026, 3:34 p.m.