Triple
T29858599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GeForce 256 |
E758255
|
entity |
| Predicate | supportsHardwareTransformAndLighting |
P92764
|
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: [GeForce 256, supportsHardwareTransformAndLighting, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsHardwareTransformAndLighting Context triple: [GeForce 256, supportsHardwareTransformAndLighting, true]
-
A.
supports3DTransforms
chosen
Indicates that one entity provides or is compatible with three-dimensional transform capabilities for another entity or within a given context.
-
B.
supportsShadingLanguage
Indicates that one entity provides compatibility with, or can correctly interpret and execute, a specified shading language used for programmable graphics rendering.
-
C.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
D.
supportsHardwareAcceleration
Indicates that one entity enables or provides hardware-based acceleration capabilities for another entity’s operations or processes.
-
E.
usesLightingFor
Indicates that one entity employs or relies on a particular lighting setup, technology, or condition to achieve a purpose or perform an action.
- 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_69f2245b4dec8190b85f664d918a00a5 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e0f3d88190a4ee7b0673f1ef90 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 5:47 p.m.