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.