Triple
T35988400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 154th Maintenance Group |
E1040773
|
entity |
| Predicate | equipmentTypeMaintained |
P15250
|
FINISHED |
| Object | military aircraft |
—
|
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: military aircraft | Statement: [154th Maintenance Group, equipmentTypeMaintained, military aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equipmentTypeMaintained Context triple: [154th Maintenance Group, equipmentTypeMaintained, military aircraft]
-
A.
hasMaintenanceType
Indicates the specific category or kind of maintenance associated with an asset, component, or maintenance event.
-
B.
maintenanceType
Indicates the specific category or kind of maintenance activity associated with an entity or relationship.
-
C.
typeOfEquipmentManaged
chosen
Indicates the specific kind or category of equipment that an entity is responsible for managing.
-
D.
typeOfEquipmentUsed
Indicates that a particular piece or category of equipment is utilized in performing a specific action, process, or activity.
-
E.
equipmentTypeTrainedOn
Indicates the type of equipment on which an entity has received training or is qualified to operate.
- 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_69f76e28293c8190ae3f4e2208b87117 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7acaec1508190a38f2ac9cc5383e7 |
completed | May 3, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f7ab75387c819091afc3c2128eb903 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.