Triple
T8820759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SceneKit |
E209895
|
entity |
| Predicate | supportsRenderingBackend |
P84807
|
FINISHED |
| Object | Metal |
—
|
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: Metal | Statement: [SceneKit, supportsRenderingBackend, Metal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsRenderingBackend Context triple: [SceneKit, supportsRenderingBackend, Metal]
-
A.
supportsCompositingBackend
Indicates that one entity provides compatibility with or can operate using a specified compositing backend.
-
B.
renderingTechnology
Indicates the graphics or visualization method used to generate the visual representation of an object, scene, or interface.
-
C.
supportsHardwareAcceleration
Indicates that one entity enables or provides hardware-based acceleration capabilities for another entity’s operations or processes.
-
D.
supportsHardwareRayTracing
Indicates that one entity provides or enables hardware-level ray tracing capabilities for another entity or within a given context.
-
E.
canRender
Indicates that one entity has the capability or functionality to generate or display another entity in a visual or presentable form.
- 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_69ca8364e13081909c85fe80f44fe86f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc601126248190b6f10c22f1aeac9a |
completed | April 1, 2026, midnight |
| PD | Predicate disambiguation | batch_69cc5c21e64c81908490e3b0875dc0d6 |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5cff3608819081d2d7e5c16d44b7 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:46 p.m.