Triple
T10984865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pratt & Whitney Canada PT6A |
E259602
|
entity |
| Predicate | typicalTBO |
P96459
|
FINISHED |
| Object | up to 6,000 hours depending on model and operation |
—
|
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: up to 6,000 hours depending on model and operation | Statement: [Pratt & Whitney Canada PT6A, typicalTBO, up to 6,000 hours depending on model and operation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTBO Context triple: [Pratt & Whitney Canada PT6A, typicalTBO, up to 6,000 hours depending on model and operation]
-
A.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
B.
typicalBase
Indicates that one entity serves as the standard or most representative base or foundation for another entity in typical or common cases.
-
C.
typicalGoing
Indicates that an entity is engaged in or undergoing a normal, expected instance of going or movement from one place to another.
-
D.
typicalPerformance
Indicates the usual or characteristic level at which an entity performs under normal conditions.
-
E.
typicalEngine
Indicates that an entity is the standard or commonly used engine for another entity (such as a vehicle, device, or system).
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d772ed1eb88190b7333b746f76a088 |
completed | April 9, 2026, 9:35 a.m. |
| PD | Predicate disambiguation | batch_69d72e9055908190b438f039574aaaaf |
completed | April 9, 2026, 4:44 a.m. |
| PDg | Predicate description generation | batch_69d732242fdc8190be77d1f730a42935 |
completed | April 9, 2026, 4:59 a.m. |
Created at: April 8, 2026, 9:24 p.m.