Triple
T8935850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McComb-Pike County Airport |
E212772
|
entity |
| Predicate | has use |
P8225
|
FINISHED |
| Object | civil |
—
|
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: civil | Statement: [McComb-Pike County Airport, has use, civil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: has use Context triple: [McComb-Pike County Airport, has use, civil]
-
A.
hasHumanUse
chosen
Indicates that something is used, employed, or utilized by humans for a particular purpose or benefit.
-
B.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
C.
endedUseWith
Indicates that an entity has stopped or terminated its use or association with another entity.
-
D.
usedAt
Indicates that something is employed, applied, or utilized at a particular place, time, or context.
-
E.
usedOver
Indicates that one entity has been utilized, applied, or consumed in relation to another entity, typically as a resource, medium, or tool in a particular context or period.
- 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_69ca8395c438819087d7cb844ab5990c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc66928cec8190915636d663f843af |
completed | April 1, 2026, 12:28 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed3286c8190a21de2ee11f2639f |
completed | March 31, 2026, 11:54 p.m. |
Created at: March 30, 2026, 6:58 p.m.