Triple
T4975789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mott transition |
E111761
|
entity |
| Predicate | theoreticalFramework |
P2450
|
FINISHED |
| Object |
Gutzwiller approximation
The Gutzwiller approximation is a variational method in condensed matter physics used to study strongly correlated electron systems, particularly metal–insulator (Mott) transitions in lattice models like the Hubbard model.
|
E484700
|
NE FINISHED |
How this triple was built (4 steps)
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.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Gutzwiller approximation | Statement: [Mott transition, theoreticalFramework, Gutzwiller approximation]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gutzwiller approximation Context triple: [Mott transition, theoreticalFramework, Gutzwiller approximation]
-
A.
Kirkwood approximation in statistical mechanics
The Kirkwood approximation in statistical mechanics is a method for approximating many-particle correlation functions by expressing higher-order correlations in terms of lower-order ones, simplifying the description of interacting particle systems.
-
B.
Brillouin–Wigner perturbation theory
Brillouin–Wigner perturbation theory is a formulation of quantum mechanical perturbation theory that uses an energy-dependent effective Hamiltonian to obtain improved approximations to eigenvalues and eigenstates.
-
C.
Jordan–Wigner transformation
The Jordan–Wigner transformation is a mathematical mapping in quantum many-body physics that converts spin operators into fermionic creation and annihilation operators, enabling the study of spin systems using fermionic methods.
-
D.
Hubbard model
The Hubbard model is a fundamental theoretical model in condensed matter physics that describes interacting electrons on a lattice and is widely used to study phenomena such as magnetism, metal–insulator transitions, and high-temperature superconductivity.
-
E.
Born expansion of Green’s function
The Born expansion of Green’s function is a perturbative series representation used in scattering theory to express the Green’s function as a sum of successive interaction terms.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Gutzwiller approximation Triple: [Mott transition, theoreticalFramework, Gutzwiller approximation]
Generated description
The Gutzwiller approximation is a variational method in condensed matter physics used to study strongly correlated electron systems, particularly metal–insulator (Mott) transitions in lattice models like the Hubbard model.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gutzwiller approximation Target entity description: The Gutzwiller approximation is a variational method in condensed matter physics used to study strongly correlated electron systems, particularly metal–insulator (Mott) transitions in lattice models like the Hubbard model.
-
A.
Kirkwood approximation in statistical mechanics
The Kirkwood approximation in statistical mechanics is a method for approximating many-particle correlation functions by expressing higher-order correlations in terms of lower-order ones, simplifying the description of interacting particle systems.
-
B.
Brillouin–Wigner perturbation theory
Brillouin–Wigner perturbation theory is a formulation of quantum mechanical perturbation theory that uses an energy-dependent effective Hamiltonian to obtain improved approximations to eigenvalues and eigenstates.
-
C.
Jordan–Wigner transformation
The Jordan–Wigner transformation is a mathematical mapping in quantum many-body physics that converts spin operators into fermionic creation and annihilation operators, enabling the study of spin systems using fermionic methods.
-
D.
Hubbard model
The Hubbard model is a fundamental theoretical model in condensed matter physics that describes interacting electrons on a lattice and is widely used to study phenomena such as magnetism, metal–insulator transitions, and high-temperature superconductivity.
-
E.
Born expansion of Green’s function
The Born expansion of Green’s function is a perturbative series representation used in scattering theory to express the Green’s function as a sum of successive interaction terms.
- F. None of above. chosen
Provenance (5 batches)
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_69bd441a0eb481908050fa4273b19eae |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7230086c81909c045614721bd89f |
completed | March 20, 2026, 4:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be8a01e548819087e3a6ae2cd581b9 |
completed | March 21, 2026, 12:07 p.m. |
| NEDg | Description generation | batch_69be8c193f2c8190a220ffc2571bcb64 |
completed | March 21, 2026, 12:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69be8c6723f08190b0e722dbb1171173 |
completed | March 21, 2026, 12:17 p.m. |
Created at: March 20, 2026, 1:33 p.m.