Triple
T1844135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | F-22 Raptor |
E41244
|
entity |
| Predicate | numberOperational |
P34085
|
FINISHED |
| Object | around 180 |
—
|
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: around 180 | Statement: [F-22 Raptor, numberOperational, around 180]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOperational Context triple: [F-22 Raptor, numberOperational, around 180]
-
A.
operatingStatus
Indicates whether an entity is currently functioning, active, or in service versus inactive, closed, or out of service.
-
B.
operationalRange
Indicates the span of conditions (such as distance, time, or environment) within which a system, device, or process can function effectively and safely.
-
C.
operationOf
Indicates that one entity is the function, activity, or process carried out by another entity (such as a system, device, or organization).
-
D.
daysOfOperation
Indicates the specific days on which an entity (such as a service, facility, or operation) is active or functioning.
-
E.
numberBuilt
Indicates the total count of items or structures that have been constructed or produced.
- F. None of above. chosen
Provenance (4 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_69a88648cd44819093303206d96d76ad |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb32d35508190bf1c487dffbecaf0 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafdb0d2c8190a67f584e67979fa3 |
completed | March 7, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69abb32a8d548190a231c7c2ce276a5e |
completed | March 7, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:33 p.m.