Triple
T19256276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian classical music |
E481523
|
entity |
| Predicate | usesTuningReference |
P135075
|
FINISHED |
| Object | drone on tonic |
—
|
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: drone on tonic | Statement: [Indian classical music, usesTuningReference, drone on tonic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTuningReference Context triple: [Indian classical music, usesTuningReference, drone on tonic]
-
A.
tuningType
Indicates the specific method or configuration by which something is adjusted or calibrated to achieve a desired performance or behavior.
-
B.
usesAutoTune
Indicates that the subject employs automatic pitch-correction technology (Auto-Tune) on their vocal or audio recordings.
-
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.
tunedBy
Indicates that one entity has been adjusted or calibrated in its settings, parameters, or configuration by another entity.
- F. None of above. chosen
Provenance (4 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_69d8e8cd9d1081908a181d02b88b59b8 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fb3572c08190a55f1c71cdb18b42 |
completed | April 20, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69e4dd002d00819088b625056edfb74e |
completed | April 19, 2026, 1:47 p.m. |
| PDg | Predicate description generation | batch_69e4ddcf50108190a09d0f1291c17374 |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 1:28 p.m.