Triple
T19012727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lensky – tenor |
E465267
|
entity |
| Predicate | typicalSingerProfile |
P41733
|
FINISHED |
| Object | light to full lyric 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: light to full lyric tenor | Statement: [Lensky – tenor, typicalSingerProfile, light to full lyric tenor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSingerProfile Context triple: [Lensky – tenor, typicalSingerProfile, light to full lyric tenor]
-
A.
typicalProfile
chosen
Indicates that an entity represents the standard or most representative profile or pattern for another entity.
-
B.
typicalPlayerProfile
Indicates the usual or characteristic attributes, behaviors, or demographics associated with a representative player in a given context.
-
C.
typicalPerformerRoleType
Indicates the usual or characteristic role type that a performer commonly plays or is associated with in their performances.
-
D.
typicalSpeaker
Indicates that the subject is a prototypical or characteristic speaker or source of utterances in the context of the object.
-
E.
featuresMusician
Indicates that something (such as a work, event, or recording) prominently includes or showcases a particular musician.
- 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_69d8dd025c188190a1d81f5b4ec7e2c6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6a9bac8819093f9af57000667b0 |
completed | April 20, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69e4a2fd80c081908237317a3a883e1c |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:02 p.m.