Triple
T18635011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barra–Glasgow |
E455522
|
entity |
| Predicate | usesRunwayTypeAtBarra |
P15527
|
FINISHED |
| Object | beach runway |
—
|
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: beach runway | Statement: [Barra–Glasgow, usesRunwayTypeAtBarra, beach runway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesRunwayTypeAtBarra Context triple: [Barra–Glasgow, usesRunwayTypeAtBarra, beach runway]
-
A.
hasRunwayType
chosen
Indicates that an airport or airfield has a runway of a specified type or surface classification.
-
B.
isRunwayOf
Indicates that a physical runway is a component or facility belonging to, used by, or officially associated with a particular airport or airfield.
-
C.
usesRunwayOf
Indicates that one entity makes use of the runway that belongs to or is associated with another entity.
-
D.
hasRunwaySide
Indicates that a runway is located on or associated with a particular side or boundary of another feature (such as an airport or airfield area).
-
E.
hasRunwayLengthCategory
Indicates that an airport or airfield is associated with a specific categorical range of runway lengths (e.g., short, medium, long).
- 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_69d8d38cc7948190a55ea64e5638994e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54fc80b308190932303231524d372 |
completed | April 19, 2026, 9:57 p.m. |
| PD | Predicate disambiguation | batch_69e478d4a7948190a4bb9223bb5dddfc |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:46 a.m.