Triple
T8993043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elmo |
E214835
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | natural language processing 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: natural language processing model Context triple: [Elmo, instanceOf, natural language processing model]
-
A.
natural language processing technique
A natural language processing technique is a computational method or algorithm designed to enable computers to understand, interpret, generate, or manipulate human language in a meaningful way.
-
B.
natural language understanding platform
A natural language understanding platform is a system that interprets, analyzes, and derives meaning from human language input to enable intelligent, context-aware interactions and automation.
-
C.
natural language
Natural language is a human-developed system of spoken, written, or signed communication characterized by grammar, vocabulary, and usage conventions that evolve within a linguistic community.
-
D.
text-to-speech model
A text-to-speech model is a system that converts written text into natural-sounding spoken audio using linguistic analysis and speech synthesis techniques.
-
E.
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.
- 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_69ca83a05c608190bdfdbdb25e994b39 |
completed | March 30, 2026, 2:07 p.m. |
Created at: March 30, 2026, 7:04 p.m.