Triple
T32605758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Daughter of the Regiment |
E833508
|
entity |
| Predicate | tenorRole |
P24740
|
FINISHED |
| Object | Tonio |
—
|
NE NERFINISHED |
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: Tonio | Statement: [The Daughter of the Regiment, tenorRole, Tonio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tenorRole Context triple: [The Daughter of the Regiment, tenorRole, Tonio]
-
A.
tenor
Indicates a relationship where an entity serves as the primary participant, subject, or focus in a communicative or experiential process (e.g., the one who feels, thinks, says, or experiences something).
-
B.
musicalRole
chosen
Indicates the specific function or part an entity performs within a musical context, such as in a performance, composition, or ensemble.
-
C.
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).
-
D.
hasMezzoSopranoRole
Indicates that an entity is assigned or associated with a role intended for a mezzo-soprano voice.
-
E.
operaActRole
Indicates the role or character that a performer portrays in a specific act of an opera.
- 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_69f3492bfa648190b6ae472074634e29 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6c6c6357c819093691b67103657ad |
completed | May 3, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2c138481908afa3ee3e91f8900 |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 1:05 a.m.