Triple
T28332182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Il barbiere di Siviglia |
E717564
|
entity |
| Predicate | mainMaleRoleVoiceType |
P2000
|
FINISHED |
| Object | baritone (Figaro) |
—
|
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: baritone (Figaro) | Statement: [Il barbiere di Siviglia, mainMaleRoleVoiceType, baritone (Figaro)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainMaleRoleVoiceType Context triple: [Il barbiere di Siviglia, mainMaleRoleVoiceType, baritone (Figaro)]
-
A.
voiceType
chosen
Indicates the specific vocal style, quality, or role associated with an entity’s voice in a given context.
-
B.
voiceActorMale
Indicates that the subject is a male voice actor who provides the voice for the associated character or role.
-
C.
vocalGender
Indicates the perceived or assigned gender associated with an entity’s voice in a vocal performance or recording.
-
D.
originalMaleLeadRole
Indicates that an entity was the first male actor to play a particular leading role in a work or production.
-
E.
roleInTheVoices
Indicates that an entity has a specific role or participation in the production or performance of "The Voices."
- 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_69eff6e9a57c8190a69c2c74b5d72119 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f64e37f7fc819083809149b6661e3c |
completed | May 2, 2026, 7:19 p.m. |
| PD | Predicate disambiguation | batch_69f64caede108190a35cc7cbfead866f |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 28, 2026, 12:33 a.m.