Triple
T6088474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akai MPC3000 |
E135696
|
entity |
| Predicate | sequencerResolution |
P68595
|
FINISHED |
| Object | 96 ppqn |
—
|
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: 96 ppqn | Statement: [Akai MPC3000, sequencerResolution, 96 ppqn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sequencerResolution Context triple: [Akai MPC3000, sequencerResolution, 96 ppqn]
-
A.
sequencerType
Indicates the specific kind or category of sequencer associated with or used in relation to an entity.
-
B.
sensorResolution
Indicates the level of detail or precision with which a sensor can measure or distinguish changes in the observed quantity or environment.
-
C.
programSequenceNumber
Indicates the position or order of a program within a sequence or series of programs.
-
D.
spectralResolution
Indicates the fineness with which a system can distinguish or separate different wavelengths or frequencies within a spectrum.
-
E.
timeScaleType
Indicates the type or category of temporal scaling applied to an event, process, or measurement (e.g., real-time, accelerated, aggregated).
- 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_69c0087bcc788190b20f093d3a6c60ec |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c057a6f7588190b265d6005fbaf6b3 |
completed | March 22, 2026, 8:57 p.m. |
| PD | Predicate disambiguation | batch_69c049f3b1ec8190bea67a7bec6442a5 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8d4a148190bd8f95caae978e1b |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:12 p.m.