Triple
T27885327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Intel Core m3-7Y30 |
E705207
|
entity |
| Predicate | supportsOpenCL |
P172036
|
FINISHED |
| Object | 2.0 |
—
|
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: 2.0 | Statement: [Intel Core m3-7Y30, supportsOpenCL, 2.0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsOpenCL Context triple: [Intel Core m3-7Y30, supportsOpenCL, 2.0]
-
A.
openclSupport
chosen
Indicates that one entity provides, enables, or is compatible with OpenCL functionality for another entity.
-
B.
supportsGPUType
Indicates that one entity is compatible with, or capable of operating using, a specified type of GPU.
-
C.
supportsNEON
Indicates that one entity provides or enables NEON (ARM Advanced SIMD) instruction set support for another entity.
-
D.
supportsShadingLanguage
Indicates that one entity provides compatibility with, or can correctly interpret and execute, a specified shading language used for programmable graphics rendering.
-
E.
supportsNeuralNetworkAcceleration
Indicates that one entity provides hardware or software capabilities that enhance the speed or efficiency of neural network computations for another entity.
- F. None of above.
Provenance (3 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_69ef96b39c448190a9b3aa6672a5168f |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_6a002962f6e081909906d6436bae6407 |
completed | May 10, 2026, 6:44 a.m. |
| PD | Predicate disambiguation | batch_6a00284c9c7c8190a77f18a41eee55df |
completed | May 10, 2026, 6:40 a.m. |
Created at: April 27, 2026, 6:32 p.m.