Triple
T25500037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katerina Lvovna Izmailova |
E639083
|
entity |
| Predicate | operaRoleType |
P148812
|
FINISHED |
| Object | soprano role |
—
|
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: soprano role | Statement: [Katerina Lvovna Izmailova, operaRoleType, soprano role]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operaRoleType Context triple: [Katerina Lvovna Izmailova, operaRoleType, soprano role]
-
A.
operaActRole
Indicates the role or character that a performer portrays in a specific act of an opera.
-
B.
operaStructureRole
Indicates the functional or narrative role that a structural element plays within an opera.
-
C.
operaOrOratorioCharacterType
chosen
Indicates that the subject is a character type or role as it appears specifically within an opera or an oratorio.
-
D.
operaAct
Indicates that an entity performs in or takes part in an act (segment) of an opera performance.
-
E.
theaterRole
Indicates that an entity holds or performs a specific role or character in a theatrical production in relation to another entity (such as a play or performance).
- 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_69e75dbbd2a88190b70e1e645de14b9a |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f739a638748190808e7a2930dce16e |
completed | May 3, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f732f2dc6c8190a4e86da98cc5eb05 |
completed | May 3, 2026, 11:35 a.m. |
Created at: April 21, 2026, 2:42 p.m.