Triple
T12675284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford Airport |
E302792
|
entity |
| Predicate | supportsMilitaryOperations |
P55335
|
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: [Ford Airport, supportsMilitaryOperations, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsMilitaryOperations Context triple: [Ford Airport, supportsMilitaryOperations, true]
-
A.
militarySupportActivity
Indicates an action where one entity provides military-related assistance, resources, or operational support to another.
-
B.
supportedDuringWar
Indicates that one entity provided assistance, resources, or backing to another entity specifically during a time of war.
-
C.
belligerentSupport
Indicates support given to a party engaged in conflict or hostilities, often implying backing one side in a belligerent or warlike context.
-
D.
militarySupportTheme
Indicates that one entity provides, requests, or is associated with military assistance, backing, or involvement in relation to another entity or situation.
-
E.
hasMilitaryOperators
chosen
Indicates that a military force or organization operates, controls, or makes active use of the referenced asset, system, or equipment.
- 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961b0d9c88190a05d6cbcb7a1642d |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960bb64ec8190bd0400cf0cc8b0a7 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:20 p.m.