Triple
T12895447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prelude in D minor, BWV 851 |
E308479
|
entity |
| Predicate | usesTuningConcept |
P29977
|
FINISHED |
| Object | well-temperament |
—
|
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: well-temperament | Statement: [Prelude in D minor, BWV 851, usesTuningConcept, well-temperament]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTuningConcept Context triple: [Prelude in D minor, BWV 851, usesTuningConcept, well-temperament]
-
A.
tuningMethod
Indicates the method or approach used to adjust or optimize something’s parameters or performance.
-
B.
usesAutoTune
Indicates that the subject employs automatic pitch-correction technology (Auto-Tune) on their vocal or audio recordings.
-
C.
tuning
chosen
Indicates the adjustment or calibration of something’s parameters or settings to achieve desired performance or behavior.
-
D.
tunedBy
Indicates that one entity has been adjusted or calibrated in its settings, parameters, or configuration by another entity.
-
E.
usesModulation
Indicates that one entity applies or employs a particular modulation method or scheme in relation to another entity or process.
- 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9717d859481908957510babac2d69 |
completed | April 10, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69d96fa776648190b9b5c30722ea50b6 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:40 p.m.