Triple
T7897006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Built-in Render Pipeline |
E183363
|
entity |
| Predicate | hasRenderingModel |
P15683
|
FINISHED |
| Object | forward rendering |
—
|
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: forward rendering | Statement: [Built-in Render Pipeline, hasRenderingModel, forward rendering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRenderingModel Context triple: [Built-in Render Pipeline, hasRenderingModel, forward rendering]
-
A.
renderingModel
chosen
Indicates the specific rendering engine or model used to generate the visual or graphical output for an entity.
-
B.
canRender
Indicates that one entity has the capability or functionality to generate or display another entity in a visual or presentable form.
-
C.
hasComponentModel
Indicates that an entity includes or is associated with a specific component model as part of its structure or configuration.
-
D.
hasColorModel
Indicates that an entity uses or is associated with a particular color representation model (such as RGB, CMYK, or HSV) for defining its colors.
-
E.
hasModelStatus
Indicates that an entity is assigned a particular model-related state or condition, such as its current phase, validity, or operational status within a modeling context.
- 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_69ca828c474c8190a254d6499871eaff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a187a0081909a0c0822c6dab1da |
completed | March 31, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69cae92d94448190b4425bbfb64c658c |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:01 p.m.