Triple
T10345750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RADARSAT-1 |
E243739
|
entity |
| Predicate | actualOperationalLife |
P13716
|
FINISHED |
| Object | over 17 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 17 years | Statement: [RADARSAT-1, actualOperationalLife, over 17 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: actualOperationalLife Context triple: [RADARSAT-1, actualOperationalLife, over 17 years]
-
A.
durationOfUse
chosen
Indicates the length of time for which something is used or remains in use.
-
B.
hasMeanLifetime
Indicates the characteristic average time duration for which an entity, state, or condition persists before it decays, ends, or changes.
-
C.
lastOperationalExample
Indicates that something is the most recent instance of an example that was actually used or functioning in practice.
-
D.
serviceLifeTarget
Indicates the intended or planned duration of time that a service, asset, or component is expected to remain in use or perform its function.
-
E.
periodOfMajorUse
Indicates the time span during which something was primarily or most intensively used.
- 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e923e3d08190971073ce41ff860f |
completed | April 7, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69d4dfa657f481909cc5cc8fec00ad19 |
completed | April 7, 2026, 10:42 a.m. |
Created at: April 6, 2026, 11:56 a.m.