Triple
T28332400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tancredi |
E717569
|
entity |
| Predicate | vocalTypeOfTancredi |
P170397
|
FINISHED |
| Object | mezzo-soprano (trouser 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: mezzo-soprano (trouser role) | Statement: [Tancredi, vocalTypeOfTancredi, mezzo-soprano (trouser role)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vocalTypeOfTancredi Context triple: [Tancredi, vocalTypeOfTancredi, mezzo-soprano (trouser role)]
-
A.
vocalTypeOfRodolfo
Indicates the specific vocal classification or voice type associated with the character Rodolfo.
-
B.
voiceTypeOfRiccardo
Indicates the specific vocal classification or voice type that characterizes Riccardo.
-
C.
voiceTypeOfRenato
Indicates the specific vocal classification or type that characterizes Renato’s voice.
-
D.
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).
-
E.
vocalCounterpartType
Indicates the type or category of a vocal counterpart relationship that one entity has to another (e.g., spoken, sung, dubbed, narrated).
- 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_69eff6e9a57c8190a69c2c74b5d72119 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f69063edbc81909e7735954aabee0b |
completed | May 3, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_69f68b78f29481908cc8f390496dee97 |
completed | May 2, 2026, 11:40 p.m. |
| PDg | Predicate description generation | batch_69f68f6584a88190a8c4d95c0c84bee9 |
completed | May 2, 2026, 11:57 p.m. |
Created at: April 28, 2026, 12:33 a.m.