Triple
T1549537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 09/27 |
E33055
|
entity |
| Predicate | hasNoiseAbatementProcedures |
P31134
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Runway 09/27, hasNoiseAbatementProcedures, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoiseAbatementProcedures Context triple: [Runway 09/27, hasNoiseAbatementProcedures, yes]
-
A.
hasRunwayOperations
Indicates that an entity conducts or is involved in operational activities on an airport runway, such as takeoffs, landings, or related ground movements.
-
B.
hasInstrumentApproach
Indicates that an approach procedure to a location or runway is conducted using specified navigation instruments or instrument-based methods.
-
C.
hasRunwayUse
Indicates that a particular runway is authorized or designated for use by a specific aircraft, operation, or purpose.
-
D.
hasSpecialProcedure
Indicates that a particular entity is associated with or governed by a designated special procedure or process.
-
E.
hasAirspace
Indicates that one entity possesses, controls, or is associated with a defined region of airspace relative to another entity or area.
- 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_69a885ee6db8819099502bc5ce8af881 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa574094048190a2d7fc3ac904d51e |
completed | March 6, 2026, 4:25 a.m. |
| PD | Predicate disambiguation | batch_69a907b426dc8190975c024a50955368 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69aa573ee8e0819084abf59f1ddbd1da |
completed | March 6, 2026, 4:25 a.m. |
Created at: March 4, 2026, 7:26 p.m.