Triple

T6097186
Position Surface form Disambiguated ID Type / Status
Subject Giorgio Parisi E135905 entity
Predicate notableWork P4 FINISHED
Object Parisi solution of spin glasses
The Parisi solution of spin glasses is a groundbreaking theoretical framework that exactly characterizes the complex energy landscape and phase structure of mean-field spin glass models through hierarchical replica symmetry breaking.
E569063 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: Parisi solution of spin glasses | Statement: [Giorgio Parisi, notableWork, Parisi solution of spin glasses]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Parisi solution of spin glasses
Context triple: [Giorgio Parisi, notableWork, Parisi solution of spin glasses]
  • A. Ising models
    Ising models are mathematical models in statistical mechanics that describe systems of interacting binary variables (spins) on a lattice, widely used to study phase transitions, magnetism, and as a foundation for various probabilistic and machine learning models.
  • B. Potts model
    The Potts model is a generalization of the Ising model in statistical mechanics that describes interacting spins with more than two possible states, used to study phase transitions and critical phenomena.
  • C. Langevin theory of paramagnetism
    The Langevin theory of paramagnetism is a classical statistical model that explains how the magnetization of paramagnetic materials depends on temperature and applied magnetic field by treating atomic magnetic moments as non-interacting dipoles subject to thermal agitation.
  • D. Kramers–Wannier duality in the Ising model
    Kramers–Wannier duality in the Ising model is a mathematical transformation that relates the high-temperature and low-temperature phases of the two-dimensional Ising model, revealing the location of its critical point and illustrating a deep symmetry between ordered and disordered states.
  • E. Yang–Lee theory
    Yang–Lee theory is a framework in statistical mechanics and phase transition theory that studies the distribution of zeros of the partition function in the complex plane to understand critical phenomena.
  • 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: Parisi solution of spin glasses
Triple: [Giorgio Parisi, notableWork, Parisi solution of spin glasses]
Generated description
The Parisi solution of spin glasses is a groundbreaking theoretical framework that exactly characterizes the complex energy landscape and phase structure of mean-field spin glass models through hierarchical replica symmetry breaking.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Parisi solution of spin glasses
Target entity description: The Parisi solution of spin glasses is a groundbreaking theoretical framework that exactly characterizes the complex energy landscape and phase structure of mean-field spin glass models through hierarchical replica symmetry breaking.
  • A. Ising models
    Ising models are mathematical models in statistical mechanics that describe systems of interacting binary variables (spins) on a lattice, widely used to study phase transitions, magnetism, and as a foundation for various probabilistic and machine learning models.
  • B. Potts model
    The Potts model is a generalization of the Ising model in statistical mechanics that describes interacting spins with more than two possible states, used to study phase transitions and critical phenomena.
  • C. Langevin theory of paramagnetism
    The Langevin theory of paramagnetism is a classical statistical model that explains how the magnetization of paramagnetic materials depends on temperature and applied magnetic field by treating atomic magnetic moments as non-interacting dipoles subject to thermal agitation.
  • D. Kramers–Wannier duality in the Ising model
    Kramers–Wannier duality in the Ising model is a mathematical transformation that relates the high-temperature and low-temperature phases of the two-dimensional Ising model, revealing the location of its critical point and illustrating a deep symmetry between ordered and disordered states.
  • E. Yang–Lee theory
    Yang–Lee theory is a framework in statistical mechanics and phase transition theory that studies the distribution of zeros of the partition function in the complex plane to understand critical phenomena.
  • 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_69c0087cd3c48190b459848c72d84eb1 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05a987ce081908cbe22940f31ee2f completed March 22, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1254365708190b8feb95dfb2b730d completed March 23, 2026, 11:34 a.m.
NEDg Description generation batch_69c125d888cc819092b765d47f1d9f9f completed March 23, 2026, 11:36 a.m.
NED2 Entity disambiguation (via description) batch_69c126f308988190ab6cb6c79ea12877 completed March 23, 2026, 11:41 a.m.
Created at: March 22, 2026, 4:12 p.m.