Triple
T2265854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Springfield–Beckley Municipal Airport |
E50142
|
entity |
| Predicate | hasMilitaryOperations |
P14275
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Springfield–Beckley Municipal Airport, hasMilitaryOperations, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMilitaryOperations Context triple: [Springfield–Beckley Municipal Airport, hasMilitaryOperations, true]
-
A.
militaryActivity
Indicates that an entity is engaged in, associated with, or affected by actions, operations, or preparations conducted by armed forces.
-
B.
hasMilitaryPresence
chosen
Indicates that a military force is present in, stationed at, or operating within a particular location or entity.
-
C.
hasMilitaryBase
Indicates that one entity possesses, hosts, or contains a military base associated with or located on another entity.
-
D.
militaryForceUsed
Indicates that one entity employs or applies military power or armed force against, within, or in relation to another entity or situation.
-
E.
militaryConflict
Indicates a relationship where two or more parties are engaged in organized, armed hostilities or warfare against each other.
- 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_69a88b01e0048190ba96431b5f990ba9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc2ea65288190bc8644a07a11dfa9 |
completed | March 7, 2026, 6:17 a.m. |
| PD | Predicate disambiguation | batch_69abbdb592588190ac1ef5e8c54575b1 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.