Triple
T37843903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosalinde |
E943549
|
entity |
| Predicate | originalTheatreGenreOfWork |
—
|
GENERATED |
| Object | Viennese operetta |
—
|
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: originalTheatreGenreOfWork Context triple: [Rosalinde, originalTheatreGenreOfWork, Viennese operetta]
-
A.
theatricalGenre
chosen
Indicates the specific theatrical genre or style to which a performance, play, or production belongs.
-
B.
genreOfOriginWork
Indicates that a work is classified under a particular genre based on the genre of its original source work.
-
C.
theatreType
Indicates the specific category or kind of theatre associated with an entity, such as its format, style, or operational model.
-
D.
musicalTheatreWorkType
Indicates the specific type or category of a musical theatre work that characterizes the nature of the production.
-
E.
tipoDiOpera
Indicates that one entity is classified as a specific type or category of work (e.g., artwork, project, or production) in relation to another entity.
- 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_69f76eeb0f7081908d6d3adbc469889c |
completed | May 3, 2026, 3:51 p.m. |
Created at: May 3, 2026, 4:19 p.m.