Triple
T31851611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OpenVINO |
E813078
|
entity |
| Predicate | supportsAccelerationTechnique |
P207534
|
FINISHED |
| Object | graph-level optimizations |
—
|
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: graph-level optimizations | Statement: [OpenVINO, supportsAccelerationTechnique, graph-level optimizations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsAccelerationTechnique Context triple: [OpenVINO, supportsAccelerationTechnique, graph-level optimizations]
-
A.
supportsHardwareAcceleration
Indicates that one entity enables or provides hardware-based acceleration capabilities for another entity’s operations or processes.
-
B.
supports3DAcceleration
Indicates that one entity provides or enables hardware- or software-based 3D graphics acceleration for another entity.
-
C.
supports2DGraphicsAcceleration
Indicates that an entity provides hardware or software capabilities to accelerate the processing and rendering of two-dimensional graphics operations.
-
D.
usedAccelerator
Indicates that an entity has applied or made use of an accelerator (such as a device, mechanism, or process) to increase speed, performance, or progress in relation to another entity or activity.
-
E.
hardwareAcceleration
Indicates that an operation or process is executed using specialized hardware resources (such as GPU or dedicated accelerators) rather than relying solely on general-purpose CPU computation.
- 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_69f348eb327881909b4584b925742f6e |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e7aa0c8190bdc9ee4d54fc821b |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 30, 2026, 11:51 p.m.