Triple
T6088503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akai MPC3000 |
E135696
|
entity |
| Predicate | supportsQuantization |
P68599
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Akai MPC3000, supportsQuantization, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsQuantization Context triple: [Akai MPC3000, supportsQuantization, true]
-
A.
isQuantizationOf
Indicates that one entity is a quantized or discretized version of another, typically transforming a continuous model, signal, or system into a discrete counterpart.
-
B.
isQuantizedBy
Indicates that a continuous or variable quantity is represented or constrained using discrete units, levels, or steps defined by another entity.
-
C.
usedToQuantize
Indicates that one entity serves as the quantization method, scheme, or tool applied to another entity.
-
D.
supportsNeuralNetworkAcceleration
Indicates that one entity provides hardware or software capabilities that enhance the speed or efficiency of neural network computations for another entity.
-
E.
supportsOptimizationAlgorithm
Indicates that one entity is capable of running, integrating, or being compatible with a specified optimization algorithm.
- 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.