Triple
T23876926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Méphistophélès |
E592891
|
entity |
| Predicate | voiceTypeInOpera |
P2000
|
FINISHED |
| Object | bass |
—
|
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: bass | Statement: [Méphistophélès, voiceTypeInOpera, bass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: voiceTypeInOpera Context triple: [Méphistophélès, voiceTypeInOpera, bass]
-
A.
operaOrOratorioCharacterType
Indicates that the subject is a character type or role as it appears specifically within an opera or an oratorio.
-
B.
operaActRole
Indicates the role or character that a performer portrays in a specific act of an opera.
-
C.
voiceType
chosen
Indicates the specific vocal style, quality, or role associated with an entity’s voice in a given context.
-
D.
voiceTypeOfOscar
Indicates the type or category of voice associated with an Oscar-related role, performance, or recognition.
-
E.
associatedOpera
Indicates that there is a relationship linking an entity to an opera with which it is connected or related (e.g., as subject, inspiration, or context).
- 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_69e25d23a5c88190ae3999c70ca15e08 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1cc02277c8190b0c15d6525f3b38d |
completed | April 29, 2026, 9:14 a.m. |
| PD | Predicate disambiguation | batch_69f1614a65a88190bde1efb368a151e4 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:15 p.m.