Triple
T37208607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rel |
E922236
|
entity |
| Predicate | featuresVeteranComedian |
—
|
GENERATED |
| Object | Sinbad |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresVeteranComedian Context triple: [Rel, featuresVeteranComedian, Sinbad]
-
A.
starsComedianKnownFor
Indicates that a work features a comedian who is particularly recognized or famous for that role or performance.
-
B.
comedian
Indicates that the subject performs comedy or is recognized for engaging in comedic entertainment.
-
C.
hasLeadComedian
chosen
Indicates that one entity serves as the primary or main comedian associated with another entity, such as a show, event, or performance.
-
D.
comedicDynamicWith
Indicates a relationship in which two or more entities interact in a way that creates or supports comedic effect, timing, or contrast.
-
E.
featuresVaudeville
Indicates that something includes or presents vaudeville-style performance as a notable element or component.
- F. None of above.
Provenance (1 batch)
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_69f76ea4849481909b4a3073efb0114c |
completed | May 3, 2026, 3:49 p.m. |
Created at: May 3, 2026, 4:15 p.m.