Triple
T38032747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strathaven Airfield |
E948957
|
entity |
| Predicate | hasNavigationLighting |
P13444
|
FINISHED |
| Object | limited or none |
—
|
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: limited or none | Statement: [Strathaven Airfield, hasNavigationLighting, limited or none]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNavigationLighting Context triple: [Strathaven Airfield, hasNavigationLighting, limited or none]
-
A.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
B.
hasLightingEffect
Indicates that one entity applies, produces, or is associated with a particular lighting effect on another entity or environment.
-
C.
hasLamp
Indicates that one entity possesses or is equipped with a lamp.
-
D.
hasRunwayLighting
chosen
Indicates that a runway is equipped with lighting systems to aid visibility and operations, typically during low-light or night conditions.
-
E.
hasNumberOfMainLights
Indicates the relationship that specifies how many primary or main lights are associated with an entity.
- 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_69f76efd1bc48190a729097fe5177b61 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69ffb97b8ff8819088b105d99a0820c9 |
completed | May 9, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69ffb88ef7388190a710120ed76edc0e |
completed | May 9, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:20 p.m.