Triple
T14342741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Joint Conference on Neural Networks |
E355642
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | neural networks conference |
C33826
|
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: neural networks conference Context triple: [International Joint Conference on Neural Networks, instanceOf, neural networks conference]
-
A.
natural language processing conference
A natural language processing conference is a formal gathering where researchers, practitioners, and industry professionals present, discuss, and advance methods and applications for computational understanding and generation of human language.
-
B.
award of the International Neural Network Society
An award of the International Neural Network Society is a formal recognition conferred by the society to honor outstanding contributions and achievements in the field of neural networks and related areas.
-
C.
neural network design method
A neural network design method is a systematic approach for selecting, structuring, and configuring neural network architectures and training procedures to solve specific computational or learning tasks.
-
D.
neuromorphic computing initiative
A neuromorphic computing initiative is a coordinated effort to research, develop, and deploy hardware and software systems that emulate the structure and function of biological neural networks to achieve more efficient, brain-like computation.
-
E.
theoretical computer science conference
A theoretical computer science conference is a formal academic gathering where researchers present, discuss, and critique new results and ideas in areas such as algorithms, complexity theory, cryptography, and formal methods.
- 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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
Created at: April 10, 2026, 1:14 a.m.