Triple
T37198102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tosca |
E921647
|
entity |
| Predicate | operaNumberInPucciniCareer |
—
|
GENERATED |
| Object | 5 |
—
|
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: operaNumberInPucciniCareer Context triple: [Tosca, operaNumberInPucciniCareer, 5]
-
A.
operaNumberInVerdiOeuvre
Indicates the ordinal position of an opera within the complete body of operatic works composed by Verdi.
-
B.
operaNumberInComposerOutput
chosen
Indicates the ordinal position or catalog number assigned to an opera within the complete body of works by a specific composer.
-
C.
numberOfOperas
Indicates the total count of operas associated with a given entity (such as a person, organization, or catalog entry).
-
D.
operaNumberInMozartsOutput
Indicates the ordinal position or catalog number assigned to an opera within the complete body of Mozart’s operatic works.
-
E.
estimatedNumberOfOperas
Indicates the approximate count of operas associated with an entity, rather than an exact, verified number.
- 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_69f76ea313a08190a54404cd1e47da90 |
completed | May 3, 2026, 3:49 p.m. |
Created at: May 3, 2026, 4:15 p.m.