Triple
T11018770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suite bergamasque |
E260431
|
entity |
| Predicate | hasTempoIndicationMovementPassepied |
P60128
|
FINISHED |
| Object | Allegretto ma non troppo |
—
|
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: Allegretto ma non troppo | Statement: [Suite bergamasque, hasTempoIndicationMovementPassepied, Allegretto ma non troppo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTempoIndicationMovementPassepied Context triple: [Suite bergamasque, hasTempoIndicationMovementPassepied, Allegretto ma non troppo]
-
A.
hasTempoChanges
Indicates that the tempo of the piece or segment changes over its duration, rather than remaining constant.
-
B.
hasTempoMarking
chosen
Indicates that a musical passage, piece, or event is associated with a specific tempo indication or marking.
-
C.
tempoIndicationOfThirdMovement
Indicates the tempo marking that specifies the speed or character of the third movement in a multi-movement work.
-
D.
hasTempoCategory
Indicates that something is associated with a particular tempo classification or speed category.
-
E.
fourthMovementTempoMarking
Indicates the specified tempo marking used in the fourth movement of a musical work.
- 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_69d6aa9687448190b28d353b1b6a610e |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797a9e8788190a0f45b52bad1bfb5 |
completed | April 9, 2026, 12:12 p.m. |
| PD | Predicate disambiguation | batch_69d72e995e008190bbffb314129ed0cd |
completed | April 9, 2026, 4:44 a.m. |
Created at: April 8, 2026, 9:25 p.m.