Triple
T33436988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SensorML |
E856259
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | sensor description language |
C60562
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: sensor description language Context triple: [SensorML, instanceOf, sensor description language]
-
A.
material description language
A material description language is a formal specification system used to define the physical, chemical, and structural properties of materials in a precise, machine-readable way for simulation, design, and analysis.
-
B.
3D scene description framework
A 3D scene description framework is a structured system for representing, organizing, and exchanging information about objects, materials, lighting, and spatial relationships within a three-dimensional environment.
-
C.
optical system descriptor
An optical system descriptor is a structured representation that defines the components, configurations, and performance characteristics of an optical system for analysis, design, or simulation.
-
D.
descriptor
A descriptor is an object attribute that defines customized behavior for attribute access, assignment, and deletion through special methods, enabling controlled and reusable management of an attribute’s value.
-
E.
user interface description language
A user interface description language is a formal, often platform-independent notation used to specify the structure, behavior, and presentation of a user interface so it can be rendered or generated by different systems.
- F. None of above. chosen
Provenance (1 batch)
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_69f349709e7881908c342b4d34f555f4 |
completed | April 30, 2026, 12:22 p.m. |
Created at: May 1, 2026, 1:36 a.m.