Triple
T18691724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canadair CT-133 Silver Star |
E457015
|
entity |
| Predicate | serviceDurationInCanada |
P132305
|
FINISHED |
| Object | over 50 years |
—
|
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: over 50 years | Statement: [Canadair CT-133 Silver Star, serviceDurationInCanada, over 50 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceDurationInCanada Context triple: [Canadair CT-133 Silver Star, serviceDurationInCanada, over 50 years]
-
A.
operatorStyleCanada
Indicates a relationship where an operator follows or is associated with a style, standard, or mode of operation specific to Canada.
-
B.
durationInUK
Indicates the length of time that an entity has spent or is expected to spend in the United Kingdom.
-
C.
banDurationApproximate
Indicates that the duration of a ban is known only approximately rather than as an exact, precise time period.
-
D.
approximateTravelTimeCoastToCoast
Indicates the estimated duration required to travel from one coast to the opposite coast.
-
E.
hasServiceTime
Indicates that an entity is associated with a specific duration or schedule during which a service is provided.
- 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_69d8d391eb488190ac2e9abf5bf255e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e562e3a6d08190b2409bcbf0c42444 |
completed | April 19, 2026, 11:18 p.m. |
| PD | Predicate disambiguation | batch_69e478de85088190ba5f005f1d39f587 |
completed | April 19, 2026, 6:40 a.m. |
| PDg | Predicate description generation | batch_69e484133ee48190a80f1889d79f34c9 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 11:49 a.m.