Triple
T18204233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RoBERTa |
E435864
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | masked language model |
C25414
|
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: masked language model Context triple: [RoBERTa, instanceOf, masked language model]
-
A.
multimodal large language model family
A multimodal large language model family is a group of related neural models that can jointly process and generate multiple data modalities—such as text, images, audio, or video—using shared architectures, training objectives, and parameterizations.
-
B.
natural language processing model
chosen
A natural language processing model is a computational system designed to understand, interpret, generate, and manipulate human language in a meaningful way.
-
C.
large-scale model
A large-scale model is a computational model, often in machine learning or simulation, that operates with vast numbers of parameters or variables to capture complex patterns or behaviors across extensive datasets or systems.
-
D.
plate margin network
A plate margin network is the interconnected system of tectonic plate boundaries and their associated geological structures and processes that collectively govern the distribution and interaction of Earth’s lithospheric plates.
-
E.
metalanguage
A metalanguage is a language or formal system used to describe, analyze, or define another language (the object language), including its syntax, semantics, and rules.
- F. None of above.
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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
Created at: April 10, 2026, 10:32 a.m.