Triple
T23227281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luisa Miller |
E581047
|
entity |
| Predicate | vocalTypeOfRodolfo |
P151435
|
FINISHED |
| Object | tenor |
—
|
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: tenor | Statement: [Luisa Miller, vocalTypeOfRodolfo, tenor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vocalTypeOfRodolfo Context triple: [Luisa Miller, vocalTypeOfRodolfo, tenor]
-
A.
voiceType
Indicates the specific vocal style, quality, or role associated with an entity’s voice in a given context.
-
B.
voiceTypeForGermont
Indicates the specific vocal classification assigned to the character Germont.
-
C.
vocalTypeOfSharpless
Indicates that one entity is the vocal type or vocal classification associated with the entity Sharpless.
-
D.
vocalGender
Indicates the perceived or assigned gender associated with an entity’s voice in a vocal performance or recording.
-
E.
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).
- 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_69e246043c48819089bae72c9a9c306c |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f1922f5b4081908145d66ea7534493 |
completed | April 29, 2026, 5:07 a.m. |
| PD | Predicate disambiguation | batch_69effcdadec0819092ec1749ee453b4e |
completed | April 28, 2026, 12:18 a.m. |
| PDg | Predicate description generation | batch_69f01d8770d081908897c28b04e5faea |
completed | April 28, 2026, 2:37 a.m. |
Created at: April 17, 2026, 4:09 p.m.