Triple
T37843903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosalinde |
E943549
|
entity |
| Predicate | originalTheatreGenreOfWork |
P41553
|
FINISHED |
| Object | Viennese operetta |
—
|
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: Viennese operetta | Statement: [Rosalinde, originalTheatreGenreOfWork, Viennese operetta]
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 (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_69f76eeb0f7081908d6d3adbc469889c |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a192a008190a9917688a9e804f4 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:19 p.m.