Triple
T6981697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stanly County Airport |
E161860
|
entity |
| Predicate | has control tower |
P7890
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [Stanly County Airport, has control tower, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: has control tower Context triple: [Stanly County Airport, has control tower, no]
-
A.
hasControlTower
chosen
Indicates that one entity possesses, hosts, or is equipped with a control tower that manages or oversees its operations.
-
B.
hasTower
Indicates that one entity possesses, contains, or is characterized by the presence of a tower.
-
C.
hasRunwayAccessTo
Indicates that one location or facility is directly connected to another via a usable runway, allowing aircraft to move between them without leaving runway infrastructure.
-
D.
hasRunwayAccessVia
Indicates that an entity has access to a runway by means of a specified connecting route, facility, or intermediary.
-
E.
hasHeliport
Indicates that an entity possesses or is equipped with a heliport facility for helicopter landing and takeoff.
- 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_69c68855dc0481909b4c7e9e9ed273db |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db6d3f3c8190b0121f7934440c34 |
completed | March 27, 2026, 7:33 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c262508190a7708b3d9cf23d7c |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:31 p.m.