Triple
T10330254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KML |
E242853
|
entity |
| Predicate | supports3DVisualization |
P92769
|
FINISHED |
| Object | extruded polygons |
—
|
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: extruded polygons | Statement: [KML, supports3DVisualization, extruded polygons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supports3DVisualization Context triple: [KML, supports3DVisualization, extruded polygons]
-
A.
supports3DPerspective
chosen
Indicates that one entity provides or enables three-dimensional perspective viewing or rendering capabilities for another.
-
B.
supports3DTransforms
Indicates that one entity provides or is compatible with three-dimensional transform capabilities for another entity or within a given context.
-
C.
supports3DAcceleration
Indicates that one entity provides or enables hardware- or software-based 3D graphics acceleration for another entity.
-
D.
stereoscopic3D
Indicates that the subject is presented or perceived using stereoscopic 3D techniques, creating a depth effect by delivering slightly different images to each eye.
-
E.
supports2DGraphicsAcceleration
Indicates that an entity provides hardware or software capabilities to accelerate the processing and rendering of two-dimensional graphics operations.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7fb77348190ac8ff887f6f03450 |
completed | April 7, 2026, 10:10 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f760e88190abea6dcc4f04f2c1 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:52 a.m.