Triple
T5206309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Orleans jazz |
E117517
|
entity |
| Predicate | typicalEnsembleConfiguration |
P25465
|
FINISHED |
| Object | front line and rhythm section |
—
|
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: front line and rhythm section | Statement: [New Orleans jazz, typicalEnsembleConfiguration, front line and rhythm section]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalEnsembleConfiguration Context triple: [New Orleans jazz, typicalEnsembleConfiguration, front line and rhythm section]
-
A.
typicalEnsembleType
chosen
Indicates the usual or characteristic type of ensemble associated with or used to perform a given work, piece, or musical context.
-
B.
typicalSetup
Indicates that an entity is arranged, configured, or organized in its standard or commonly used setup relative to another entity or context.
-
C.
typeOfEnsemble
Indicates the specific kind or category of ensemble that an entity belongs to or represents.
-
D.
typicalDeployment
Indicates that one entity represents the standard or most commonly used deployment configuration or pattern for the other entity.
-
E.
typicalBase
Indicates that one entity serves as the standard or most representative base or foundation for another entity in typical or common cases.
- 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_69bd4463dd3c81909966123f20b79d57 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7a490338819080481df79d3aae01 |
completed | March 20, 2026, 4:48 p.m. |
| PD | Predicate disambiguation | batch_69bd77bb4e8c819094b5ac7cf61512f9 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:47 p.m.