Triple
T10126503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Der fliegende Holländer |
E226227
|
entity |
| Predicate | inOperaRepertoire |
P92129
|
FINISHED |
| Object | standard repertoire |
—
|
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: standard repertoire | Statement: [Der fliegende Holländer, inOperaRepertoire, standard repertoire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inOperaRepertoire Context triple: [Der fliegende Holländer, inOperaRepertoire, standard repertoire]
-
A.
operaAct
Indicates that an entity performs in or takes part in an act (segment) of an opera performance.
-
B.
associatedOpera
Indicates that there is a relationship linking an entity to an opera with which it is connected or related (e.g., as subject, inspiration, or context).
-
C.
operaActRole
Indicates the role or character that a performer portrays in a specific act of an opera.
-
D.
theaterWork
Indicates a relationship where an entity is a theatrical work (such as a play or stage production) associated with another entity, typically as its subject, creator, or context.
-
E.
musicalTheatreWork
Indicates that one entity is a musical theatre work (such as a musical or operetta) associated with or characterized by the other entity.
- F. None of above. chosen
Provenance (4 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_69ca843057b48190a86730167f5d6b98 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cdd2eef7388190b95ffd02814f2d1f |
completed | April 2, 2026, 2:22 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba1d360819087698d04a53cc87e |
completed | April 1, 2026, 4:45 p.m. |
| PDg | Predicate description generation | batch_69cd4fed19d481909d2c7ff1114664b6 |
completed | April 1, 2026, 5:03 p.m. |
Created at: March 30, 2026, 9:05 p.m.