Triple
T25430903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NGFU |
E637249
|
entity |
| Predicate | runwayUsedAs |
P160918
|
FINISHED |
| Object | community space when no flights |
—
|
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: community space when no flights | Statement: [NGFU, runwayUsedAs, community space when no flights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runwayUsedAs Context triple: [NGFU, runwayUsedAs, community space when no flights]
-
A.
runwayUsedAs
chosen
Indicates that a particular runway is being utilized for a specific purpose, role, or operational function.
-
B.
runway
Indicates a relationship where a runway serves as the takeoff and landing surface used by aircraft at an airport or airfield.
-
C.
hasRunwayUse
Indicates that a particular runway is authorized or designated for use by a specific aircraft, operation, or purpose.
-
D.
runwayUsage
Indicates that a particular runway is being used or assigned for aircraft operations such as takeoffs or landings.
-
E.
runwayAdjacentTo
Indicates that a runway is directly next to or alongside another feature or area, with no significant separation between them.
- 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_69e75db58a1c8190891b9ff7c2f8414e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f6135293908190809e255bf6334760 |
completed | May 2, 2026, 3:08 p.m. |
| PD | Predicate disambiguation | batch_69f611a72780819082f44e66ca2c6ac9 |
completed | May 2, 2026, 3 p.m. |
Created at: April 21, 2026, 1:58 p.m.