Triple
T8499029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | kora |
E201168
|
entity |
| Predicate | hasTuningSystem |
P65278
|
FINISHED |
| Object | heptatonic scale |
—
|
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: heptatonic scale | Statement: [kora, hasTuningSystem, heptatonic scale]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTuningSystem Context triple: [kora, hasTuningSystem, heptatonic scale]
-
A.
usesMusicalSystem
chosen
Indicates that one entity employs or operates according to a particular musical system, framework, or set of musical rules.
-
B.
isTunedTo
Indicates that one entity has been adjusted or configured to operate at, receive, or correspond to the frequency, channel, or setting of another entity.
-
C.
tuningMethod
Indicates the method or approach used to adjust or optimize something’s parameters or performance.
-
D.
tuning
Indicates the adjustment or calibration of something’s parameters or settings to achieve desired performance or behavior.
-
E.
tuningMachines
Indicates a relationship where an instrument or device is equipped with or associated with specific tuning machines used to adjust string tension.
- 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_69ca831ee390819095fae73400bbfafc |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe5984d7481908c41c57bef9cf254 |
completed | March 31, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69cbd10a4b0881909e254117780dc823 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:14 p.m.