Triple
T10214220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Core Animation |
E242401
|
entity |
| Predicate | supports2DTransforms |
P203
|
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: [Core Animation, supports2DTransforms, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supports2DTransforms Context triple: [Core Animation, supports2DTransforms, true]
-
A.
supports2DGraphicsAcceleration
Indicates that an entity provides hardware or software capabilities to accelerate the processing and rendering of two-dimensional graphics operations.
-
B.
supportsHardwareAcceleration
Indicates that one entity enables or provides hardware-based acceleration capabilities for another entity’s operations or processes.
-
C.
supportsOffscreenRendering
Indicates that the subject is capable of performing rendering operations to an offscreen buffer or surface rather than directly to the visible display.
-
D.
supportsFeature
chosen
Indicates that one entity provides, enables, or is compatible with a particular feature or capability of another.
-
E.
supportsGraphicsSwitching
Indicates that an entity can dynamically switch between different graphics hardware or rendering modes, typically to balance performance and power usage.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa273bdc8190bc4cf67a7923cebc |
completed | April 6, 2026, 12:42 p.m. |
| PD | Predicate disambiguation | batch_69d39559e5ac8190b88eca75956b7e6a |
completed | April 6, 2026, 11:13 a.m. |
Created at: April 6, 2026, 11:04 a.m.