Triple
T29065630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Make Me Smile |
E735665
|
entity |
| Predicate | movementNumberInSuite |
P12040
|
FINISHED |
| Object | first movement |
—
|
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: first movement | Statement: [Make Me Smile, movementNumberInSuite, first movement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: movementNumberInSuite Context triple: [Make Me Smile, movementNumberInSuite, first movement]
-
A.
movementNumber
chosen
Indicates the specific sequential position of a movement within a larger multi-movement work or performance.
-
B.
numberOfMovements
Indicates the total count of distinct movements or motion events associated with the given entity or context.
-
C.
movementCount
Indicates the number of times a movement or relocation action has occurred between the related entities.
-
D.
movementCountDescription
Indicates the textual description or explanation associated with a specific count or number of movements.
-
E.
movementNumberInOp130
Indicates the specific movement number of a work within Opus 130.
- 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_69f077e85498819088b65186550da8cd |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f68b7b03488190b1db5fde4c7dd6e5 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 28, 2026, 10:18 a.m.