Triple
T2173554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fermi liquid theory |
E48476
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | many-body theory |
C1716
|
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: many-body theory Context triple: [Fermi liquid theory, instanceOf, many-body theory]
-
A.
quantum many-body theory
chosen
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.
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.
-
C.
quantum phase of matter
A quantum phase of matter is a distinct state of a many-body quantum system characterized by unique patterns of quantum correlations and symmetries that remain stable under small changes in external conditions.
-
D.
quantum statistics
Quantum statistics is the branch of physics and mathematics that studies the statistical behavior of systems of indistinguishable quantum particles, governed by Bose-Einstein or Fermi-Dirac distributions rather than classical Maxwell-Boltzmann statistics.
-
E.
molecular quantum mechanics method
A molecular quantum mechanics method is a theoretical and computational approach that applies quantum mechanical principles to describe and predict the electronic structure, properties, and behavior of molecules.
- 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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
Created at: March 4, 2026, 7:45 p.m.