Triple
T2682947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gross–Pitaevskii equation |
E57416
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | mean-field theory |
C11707
|
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: mean-field theory Context triple: [Gross–Pitaevskii equation, instanceOf, mean-field theory]
-
A.
quantum many-body theory
Quantum many-body theory studies systems of a large number of interacting quantum particles, aiming to understand their collective behavior and emergent phenomena using quantum mechanics and statistical methods.
-
B.
model in superconductivity
A model in superconductivity is a theoretical framework that describes how electrons pair and move without resistance in certain materials below a critical temperature, capturing key phenomena such as the Meissner effect and energy gap formation.
-
C.
equation in statistical physics
An equation in statistical physics is a mathematical relation that connects microscopic properties of particles and their interactions to macroscopic thermodynamic quantities, enabling the prediction of a system’s collective behavior.
-
D.
problem in field theory
A problem in field theory is a conceptual or computational question involving the properties, structures, and interactions of fields—such as scalar, vector, or gauge fields—typically formulated within the framework of classical or quantum field theory.
-
E.
many-body quantum system
A many-body quantum system is a collection of a large number of interacting quantum particles whose collective behavior exhibits complex phenomena that cannot be understood by considering the particles individually.
- 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_69ab4a5028388190a36f3baf1588309e |
completed | March 6, 2026, 9:42 p.m. |
Created at: March 6, 2026, 9:54 p.m.