Triple
T29372209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | YM-2151 |
E744882
|
entity |
| Predicate | hasDetuneFunction |
P193121
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [YM-2151, hasDetuneFunction, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDetuneFunction Context triple: [YM-2151, hasDetuneFunction, yes]
-
A.
hasToneFunction
Indicates that one entity serves a specific tonal or harmonic function in relation to another entity within a musical context.
-
B.
hasTuningDivision
Indicates that one entity specifies or uses a particular system or scheme for dividing a range (such as a musical interval or scale) into tuning units.
-
C.
haveTone
Indicates that an entity possesses or exhibits a particular tone, such as a specific attitude, mood, or quality of expression.
-
D.
hasPitchWheel
Indicates that an entity possesses a pitch wheel control used to bend or modify musical pitch.
-
E.
hasToneFrequencyResolution
Indicates that one entity specifies the smallest distinguishable difference in tone frequency that can be measured or represented 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_69f0a79ba954819094597628112c6091 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69fd389cb28c819099a77e28d25f258a |
completed | May 8, 2026, 1:13 a.m. |
| PD | Predicate disambiguation | batch_69fd3826d8048190ada79a5868d1d7f3 |
completed | May 8, 2026, 1:11 a.m. |
| PDg | Predicate description generation | batch_69fd389b653c81908a97ab2eff98c6ea |
completed | May 8, 2026, 1:12 a.m. |
Created at: April 28, 2026, 2:28 p.m.